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2020 Urban Water Management Plan
SECTION 8 – Water Shortage Contingency Planning
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In addition to the demand reduction actions noted in Table 8-11, the City may consider augmenting supply with increased groundwater pumping to help meet demands, as detailed in Table 8-12. The City primarily relies on imported water from wholesalers, and typically only pumps groundwater to exercise the wells and conduct sampling. However, as indicated in the supply reliability assessment summarized in Section 8.1, the City has the capability to increase the amount of groundwater pumped to offset anticipated deficiencies from other sources during any shortage condition.
Table 8-12: Supply Augmentation and Other Actions
Shortage Level Supply Augmentation Methods and Other Actions by Water Supplier
Reduction in shortage gap?
(%)
All Augment supply with groundwater use if needed 10% – >50%
8.5 Consumption Reduction Methods
There are several methods actively implemented by the City to encourage consumption reduction, which are described below.
8.5.1 Public Outreach/Rebates
The City participates in public information campaigns and available water conservation rebates managed by each wholesaler encouraging water conservation . During dry periods, the City notifies the public of water conservation programs available through the City’s website, bill stuffers, and direct mailing.
8.5.2 Water Rate Structure for Conservation
A major part of Sunnyvale’s strategy for water conservation developed in 1989 is a block rate pricing structure involving a lifeline rate set at 15% above the existing rates, a conservation block rate set at a multiple of two times usage in applicable existing rate blocks, and a high impact/high use category at a multiple of three and a half times the existing rate blocks. The lifeline category exists for all categories of users whereas the conservation and high use rates are applied to recognize the greatest opportunities and needs for reduction and to be sensitive to the importance of manufacturing production and commercial needs. The same approach would be used should the City move to other shortage levels or stages. However, the multipliers would escalate.
The City restructured its residential water rate tiers in 2018, collapsing a four -tier inclining block structure into a two-tier indoor-versus-outdoor framework effective July 1, 2018; subsequent rate actions have modified prices but not tier definitions.
Separate metering systems have been set up for fire and landscape uses with potable water utilized for landscaping purposes at a different rate than domestic water.
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8.5.3 Enforcement Approach
The thrust of enforcement of Sunnyvale’s conservation program is to solicit cooperation from water users who are unaware of the restrictions or have failed to comply with the provisions of the ordinance. Every effort is made to inform these users of the need for conserving water . If discussions with the user are unsuccessful in obtaining compliance, enforcement mechanisms are available.
The Environmental Services Department (ESD) and the Department of Public Safety (DPS) cooperate on the responsibility for enforcement of the City’s conservation plan. Computerized systems track complaints throughout the enforcement process. The process i nvolves first establishing contact with the individual who may be in violation; giving the individual information about code requirements; and verbally requesting that the user comply with these requirements.
If a complaint has been registered with Neighborhood Preservation, the complainant is contacted and notified of the results of the preliminary investigation. The complainant is kept informed at each step of the process. Upon receipt of a second violation complaint, the violator will receive a written notice to comply and a warning that the next violation may result in a citation and/or the installation of a flow restricting device at the water meter. This flow restricting device would reduce the flow of water to a trickle, thereby allowing the occup ant only enough water for health and sanitation purposes. If there are further complaints and a citation is to be issued, DPS is called to issue the citation.
A “hot line” telephone number is established for drought information and to register complaints .
Trained staff are available to provide information and to respond to complaints.
8.6 Water Use Monitoring Procedure
Water Code §10632(a)(9) requires the description of the monitoring and reporting procedures that will ensure data is collected, tracked, and analyzed for purposes of monitoring customer compliance with, and effectiveness of, WSCP measures implemented durin g a drought/water shortage. During normal conditions, the City can monitor long -term water use through regular meter readings, allowing them to flag exceptionally high usage for verification of water loss or abuse. Additional and more frequent monitoring may be undertaken to improve the precision of water use data to meet specific water use reduction targets, depending on water shortage conditions.
Table 8-13 lists the mechanisms available for the City to monitor water use and determine actual reductions in water use, as well as the type and quality of data expected.
Table 8-13: Water Use Monitoring Mechanisms
Mechanisms for Determining
Actual Reductions Type and Quality of Data Expected
Customer meter readings Hourly/daily/monthly water consumption data for a specific user depending on frequency of readings
Production meter readings Hourly/daily/monthly water production data depending on frequency of readings; includes customer water use plus system losses DRAFT
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During a drought/water shortage, these data would be analyzed with increased frequency as the water shortage condition worsens, and any concerns would be brought to City Council to support the need for implementation of additional water conservation measures as needed.
8.6.1 Determining Water Shortage Reductions
As customers begin to comply with water reduction measures the overall water use will decrease.
The City continuously monitors water usage each month from billed consumption through water meters and will be able to determine the amount of water reductions compared to previous years.
The City’s billing system provides the capability for the City to evaluate water consumption from customer types. In stages 3 and higher, the City would expect to see large reductions from the dedicated landscape meters and residential customers due to mandatory restrictions on outdoor irrigation.
8.7 Analysis of Revenue Impacts of Reduced Sales during Shortages In the event of a water shortage scenario, water fund revenues may decrease from the implementation of conservation measures and corresponding reduction in water sales .
Conversely, expenses will increase because of the implementation and enforcement of water conservation measures. Expenditures will also rise on a per-unit basis, as wholesalers increase their per-unit price to compensate for the loss of revenue from wholesale sales.
The City has several options to address financial issues during a water shortage . First, the City retains two significant reserves, one for operating contingencies (Contingency Reserve) such as water shortages that is set at 25% of operations and purchased water costs, and a second for the purpose of stabilizing rates over time (Rate Stabilization Reserve). Each will help the City balance the Water Supply and Distribution fund during supply shortages. Finally, the City has four sources of supply and the ability to move most of its supply from any one point to any other point (the exception being recycled water). In the event of a water shortage, especially in the short term, the City has multiple supply options that should contribute to a more stable revenue base than if the City were under very limited wholesale supplies.
8.8 Emergency Response Plan
Water Code §10632(a)(3)(A) specifies that WSCP shortage levels shall also apply to other catastrophic interruptions of water supplies including, but not limited to, a regional power outage, an earthquake, or other potential emergency event.
8.8.1 Sunnyvale Emergency Response Plan
America’s Water Infrastructure Act of 2018 §2013(b) also requires community water systems serving populations greater than 3,300 to develop or update an ERP that describes strategies, resources, communication protocols, and procedures that the utility can use to prepare for and respond to an incident, natural or man-made, that threatens life, property, or the environment. In accordance, the City’s ERP was last updated in 2025.
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The ERP coordinates the overall City response to disasters of various types in its service area .
In addition, the ERP requires the City to have a local disaster plan that coordinates emergency responses with other agencies in the area . The ERP provides a detailed set of actions to be undertaken during specific catastrophic events, and Table 8-14 provides a summary of actions for three of the most common possible catastrophic events: regional power outages, earthquakes, and malevolent acts.
In addition to the specific actions listed in Table 8-14, the City performs regular maintenance activities – such as annual inspections – for earthquake safety and budgets for emergency items – such as auxiliary generators – to prepare for potential catastrophic events and protect the local surface water and groundwater resources.
Table 8-14: Summary of Actions for Catastrophic Events
Event Summary of Actions
Regional power
outage
• Isolate areas that will take the longest to repair and/or present a public health threat. Arrange to provide emergency water.
• Establish water distribution points and ration water if necessary. • If water service is restricted, attempt to provide potable water tankers or bottled water to the area.
• Make arrangements to conduct bacteriological tests, to determine possible contamination. • Utilize backup power supply to operate pumps in conjunction with elevated storage. • Manually reset wells that experience a power surge due to the restoration of power.
Earthquake
• Assess the condition of the water supply system.
• Complete the damage assessment checklist for reservoirs, water treatment plants, wells and boosters, system transmission and distribution.
• Coordinate with California Emergency Management Agency (Cal EMA) utilities group or fire district to identify immediate firefighting needs.
• Isolate areas that will take the longest to repair and/or present a public health threat. Arrange to provide emergency water.
• Prepare report of findings, report assessed damages, advise as to materials of immediate need, and identify priorities including hospitals, schools, and other emergency operation centers.
• Take actions to preserve storage.
• Determine any health hazard of the water supply and issue any “Boil Water Order” or “Unsafe Water Alert” notification to the customers, if necessary. • Cancel the order or alert information after completing comprehensive water quality testing. • Make arrangements to conduct bacteriological tests, to identify possible contamination.
Malevolent acts
• Assess threat or actual intentional contamination of the water system. • Notify local law enforcement to investigate the validity of the threat. • Get notification from public health officials if potential water contamination. • Determine any health hazard of the water supply and issue any “Boil Water Order” or “Unsafe Water Alert” notification to the customers, if necessary. • Assess any structural damage from an intentional act. • Isolate areas that will take the longest to repair and or present a public health threat. Arrange to provide emergency water.
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8.8.2 SFPUC Emergency Preparedness Plan
Following the 1989 Loma Prieta earthquake, the SFPUC created a departmental Emergency Operations Plan (EOP). The SFPUC EOP was originally released in 1992 and has since been updated as necessary. The SFPUC EOP addresses a broad range of potential emergency situations that may affect the SFPUC and supplements the City’s Emergency Response Plan, which was prepared by the Department of Emergency Management and most recently updated in 2017. The purpose of the SFPUC EOP is to describe the SFPUC’s emergency m anagement organization, roles and responsibilities, and emergency policies and procedures.
In addition, the SFPUC’s enterprises each have their own emergency plans (in alignment with the SFPUC EOP), which detail that entity’s specific emergency management organization, roles and responsibilities, emergency policies and procedures, and response t o hazardous events (e.g., hazardous materials, power interruption, etc.). In 2025, the SFPUC developed a Water Emergency Operations Plan (Water EOP) to comply with the America’s Water Infrastructure Act passed in 2018. The Water EOP integrates directly into, and functions as an annex to, the SFPUC EOP. The Water EOP addresses SFPUC water transmission and distribution systems and identifies the agency’s enterprises, divisions, and bureaus with direct roles and responsibilities for those systems. The SFPUC EOP functions as a front end for the SFPUC’s enterprise EOPs, covering emergency response at the department level, while each enterprise EOP covers enterprise-specific information on the enterprise’s emergency organization and response procedures specific to enterprise responsibilities, assets, technical scope, and operations.
The SFPUC exercises its EOPs on a regular basis by conducting emergency exercises and through real-world response. Through these exercises and activations, the SFPUC learns how well the plans and procedures will or will not work in response to an emergency. EOP improvements are based on the results of these exercises and real -world event response and evaluation. The SFPUC also has an emergency response training plan that is based on Federal, State, and local standards and exercise and incident improvemen t plans. SFPUC employees have emergency training assignments based on their emergency response roles, as identified in the EOPs.
The types of events affecting the SFPUC that require emergency plans include but are not limited to:
• Major earthquake
• Loss of power
• Loss of water supply
• Major fire
• Hazardous material release that threatens water supply or environment • Major pipeline breaks
• Dam incident
• Significant outage of SFPUC services
• Man-made or intentional acts of terrorism resulting in damage to the system or interruption in service
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In addition to the documents described above, the SFPUC also maintains various plans and procedures that deal with the possibility of alternate supply schemes and options. These plans and procedures include:
• Emergency Disinfection and Recovery Plan
• Emergency Response Action Plan
• Emergency Drinking Water Equipment and Alternatives Report • Disinfection of SFPUC Water Trailers Procedure
• San Francisco Water Division Hydrant Manifold Standard Operating Procedure SFPUC Emergency Drinking Water Planning
The SFPUC has implemented several projects to increase its capability to provide emergency drinking water during a catastrophic emergency. These projects include:
• Completion of many WSIP projects and other capital upgrades to improve security, detection, and communication (see Section 10.4);
• Development of public information and educational materials for residents and businesses; • Construction of a disinfection and fill station at the existing San Francisco Zoo well, and obtaining a permit to utilize this well as a standby emergency drinking water source; • Construction of six wells as part of the San Francisco Groundwater Supply Project, two of which also serve as emergency drinking water supplies, including a distribution system to fill emergency water tankers;
• Purchase and engineering of emergency-related equipment, including water tanker trucks and water distribution manifolds, to help with distribution post-disaster; and • Coordination of planning with other City departments, neighboring jurisdictions, and other public and private partners to maximize resources and supplies for emergency response.
The SFPUC also maintains a Water Quality Notifications and Communications Plan. Initially prepared in 1996 and most recently updated in 2022, this plan provides contact information and guidelines on notifications that SFPUC staff will issue in the event of water quality impacts that warrant communications internally and externally with the State, the wholesale customers, and/or public. The plan treats water quality issues as potential or actual supply problems, which fall under the emergency response structure of the SFPUC EOP.
Power Outage Preparedness and Response by SFPUC
The SFPUC’s water transmission system is primarily gravity fed from Hetch Hetchy Reservoir to the City. Within the in-City distribution system, key pump stations have generators on site, and all others have connections in place that would allow the use of portable generators.
Although power outages would not greatly impact water conveyance throughout the RWS because it is gravity fed, the SFPUC has prepared for potential regional power outages as follows:
• The Tesla Treatment Facility, the Sunol Valley Water Treatment Plant (SVWTP), the Sunol Valley Chloramination Facility (SVCF), and the San Antonio Pump Station (SAPS) have back- DRAFT
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up power on site in the form of generators. Additionally, SVWTP, SVCF, and SAPS would not be impacted by a failure of the regional power grid because these facilities are powered by hydropower generated by Hetch Hetchy Water and Power via the Calaveras Substation. • Both the Harry Tracy Water Treatment Plant and the Baden Pump Station (part of the Peninsula System) have back-up generators in place.
• Administrative facilities that may act as emergency operation centers also have back -up power.
• The SFPUC has a water supply connection with the Santa Clara Valley Water District (Valley Water or VW), known as the SFPUC-VW Intertie, which also has back-up generators in place. • Additionally, various WSIP projects expanded the SFPUC’s ability to remain in operation during power outages and other emergency situations.
8.8.3 Valley Water Catastrophic Interruption Planning
This section describes planning that Valley Water has undertaken to prepare for catastrophic interruption of water supplies during a disaster.
Infrastructure Reliability Plan
Valley Water completed its first Infrastructure Reliability Plan (IRP) in 2005 and updated it in 2016.
The IRP analyzes several outage scenarios for Valley Water’s system, including an earthquake, extreme storm, Delta outage, and power outage. Valley Water and retailers agreed on a reliability target during an emergency that Valley Water should be able to restore treated water deliveries to meet the equivalent of a winter month’s demand (i.e., February) within 30 days after a major disaster even t. Modeling and analyses estimated service restoration time of Valley Water’s existing system for minimum winter demands in each of the outage scenarios.
The worst-case outage scenario was a magnitude 7.9 earthquake on the San Andreas fault, which would result in an estimated 30-day outage time before Valley Water can provide minimum treated water demands to retailers. In the Delta outage scenario, modeling demonstrated Valley Water can continue limited service (at an assumed 20% demand reduction) for a 24 -month period with no imported water supplies if it occurred in a normal hydrologic year and started with normal groundwater supplies. In a regional power outage, Valley Water can operate facilities on backup fuel storage for an estimated 3 to 10 days, or longer given regular external fuel deliveries.
The 2016 IRP recommends efficient and targeted opportunities to improve system reliability and performance by either shortening Valley Water system outage time following an event or strengthening retailer capability to withstand Valley Water system outages . Important concepts that were incorporated into the identification of project opportunities and the analysis methodology are:
1. Incorporate recent operational knowledge: Planned and unplanned maintenance outages of Valley Water pipelines and treatment plants have allowed retailers to learn how to operate their systems without Valley Water treated water supplies . Retailers have operated with Valley Water treated water supply interruptions for up to eight weeks in some cases.
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2. Account for backup supply redundancy : Most retailer service areas have adequate groundwater pumping capacity to serve as a backup to treated water deliveries and may not require large investments in additional reliability.
3. Consider raw water and treated water system interdependencies : Strengthening Valley Water’s treated water pipeline system alone may not dramatically improve reliability in scenarios where raw water pipelines fail. The opposite also applies, as strengthening Valley Water’s raw water pipeline system alone may not dramatically improve reliability in cases where treated water pipelines fail . Strengthening key portions of both the raw and treated water pipeline systems is needed to provide improved reliability . These improvements are being planned and recommended through the development of a distribution system master plan.
4. Leverage existing investments: Where possible and beneficial, leveraging existing assets is preferred, as Valley Water, retailers, and SFPUC have made significant investments in increasing system reliability and operational flexibility since the 2005 IRP.
5. Favor frequently used assets : Assets that can be used more frequently to enhance daily operations or periodic maintenance operations, are preferred over assets that would be designated as standby for infrequent use only during major emergencies.
6. Address specific vulnerable areas : There are specific retailer service areas that are more vulnerable to outages of Valley Water treated water or managed recharge . Focusing on localized solutions to improve reliability in these specific areas may be more effective, with lower costs, than major infrastructure improvements.
Ultimately, Valley Water and retailers determined that targeting specific vulnerable areas for improvement will effectively address identified reliability needs. A total of 20 projects are identified in the 2016 IRP to improve reliability in these specific areas . Some projects were identified for retailer implementation, some for Valley Water implementation, and others for joint implementation. Valley Water has been working to complete the identified projects since 2016.
Emergency Operations Center
Valley Water finalized the updated Emergency Operations Plan (EOP) in 2025. Valley Water’s EOP establishes the framework for coordinated response and recovery during emergencies and disasters. The plan defines roles, responsibilities, and operational procedures to ensure effective activation and management of the Emergency Operations Center (EOC).
The EOC serves as the central location for coordination, communication, and decision -making during incidents that impact Valley Water’s facilities, infrastructure, or service delivery. Through the EOC, Valley Water coordinates with Santa Clara County, local jurisdictions, state and federal agencies, and other partners to support life safety, protect critical infrastructure, maintain essential water and flood protection services, and provide timely, accurate information to the public during emergencies.
Emergency operations are conducted in alignment with the Standardized Emergency Management System (SEMS), the National Incident Management System (NIMS), and applicable local, state, and federal requirements. These coordinated efforts help ensure Valley W ater can effectively respond to emergencies while supporting the public, critical infrastructure and impacted communities through communication, situational awareness, and service continuity. During any emergency, Valley Water continues the primary missions of providing clean, safe water and flood protection to the people of Santa Clara County. Valley Water maintains a full -time professional DRAFT
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emergency management staff trained and equipped to respond quickly to support Valley Water’s EOC and field responders. To ensure rapid response and continuous readiness, Valley Water’s Office of Emergency Services (OES) maintains 24 hours a day, seven day s a week on -call staffing. OES staff are available at all times to monitor incidents, coordinate notifications, support EOC activation, and facilitate timely communication and operational coordination. These efforts help maintain situational awareness, reduce misinformation, and support impacted communities throughout the incident lifecycle.
Milpitas Intertie
During an emergency, in addition to retailers relying on groundwater and their own supplies, Valley Water has a 40-MGD intertie with the SFPUC located in the City of Milpitas, which allows the SFPUC and the East Pipeline systems to exchange water during emergencies and planned maintenance.
Treatment Plant and Pipeline Shutdown Notification
Valley Water has emergency plans to cover the shutdown of pipelines and plant processes due to earthquakes, fire, or other disturbances to water quality or delivery. Efficient communication with Valley Water’s retailers is imperative in the case of an eme rgency, so Valley Water utilizes the Rapid Notification Plan to ensure prompt notification of emergencies that impact treated water deliveries to retailers. The Rapid Notification Plan is implemented in the event of any water quality or plant failure, a reduction in service, or a startup/shutdown condition.
Delta-Conveyed Supply Interruption
Valley Water relies on imported water from the Delta for about 40% of its annual supply. The interruption of Delta -conveyed supply will pose significant risks to Valley Water’s water supply reliability. In the event of an outage in the Delta, a strategy was developed by DWR, the Army Corps of Engineers (Corps), Bureau of Reclamation, California Office of Emergency Services (Cal OES), and the State Water Contractors to provide water supply protections that would enable resumption of at least partial deliveries from the Delta in less than six months in the event of an outage.
Valley Water analyzed the impacts of a six-month Delta outage to determine the effect on service.
The analysis assumed that all local infrastructure remains intact, as an earthquake or flood in the Delta is unlikely to badly damage local infrastructure . The analysis also assumed normal hydrologic conditions and starting storage conditions, rather than stacking disaster upon disaster (i.e., earthquake plus drought, etc.), access to SFPUC supplies, and implementation of water use reductions of 20 percent. The impacts of such an outage are largely operational as retailers would be required to use groundw ater instead of their usual treated water supplies and Valley Water would actively manage the groundwater recharge program to meet countywide needs. Even with increased pumping, groundwater storage is estimated to remain in the normal (Stage 1) range .
Thus, the impacts of a six -month Delta outage are manageable assuming a normal starting position. Valley Water would potentially need to call for more aggressive water use reductions if a Delta outage were to occur during or immediately following a drought.
The Delta Flood Emergency Management Plan (DWR, 2018) provides strategies for responses to Delta levee failures, including earthquake -induced numerous levee failures during dry conditions with multiple flooded islands and extensive saltwater intrusion, resulting in curtailment of export operations. Under these severe conditions, an emergency freshwater pathway would DRAFT
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be established from the central Delta along Middle River and Victoria Canal to the export pumps in the south Delta. The plan includes the pre-positioning of emergency construction materials at stockpile and warehouse sites in the Delta, and development of tactical modeling tools (DWR Emergency Response Tool) to predict levee repair logistics, timelines of levee repair, and suitable water quality to restore exports. Using pre-positioned materials, multiple earthquake-generated levee breaches and levee slum ping along the freshwater pathway can be repaired in less than six months. Significant improvements to the central and south Delta levee systems along the emergency freshwater pathway began in 2010 and are continuing . Continued efforts under analysis strive to mitigate not only flood and earthquake risk but also address future sea-level rise risk.
8.9 Seismic Risk Assessment and Mitigation Plan
8.9.1 Sunnyvale Seismic Risk Assessment and Mitigation Plans In 2023, Santa Clara County, in coordination with the City and other local jurisdictions, completed an update to the Santa Clara County Multijurisdictional Hazard Mitigation Plan (MJHMP). This plan provides a comprehensive strategy for reducing risks from natural and human -caused hazards. The 2023 update significantly enhances the previous plan by incorporating updated hazard data, addressing and emphasizing the impacts of climate change, and refining mitigation strategies specific to each participating jurisdiction. Volume I of the MJHMP can be found at the following link: Santa Clara County MJHMP.
The City has an annex within Volume II of the MJHMP (included as Appendix I of the UWMP) which, together with Volume I, explicitly addresses the City's unique risks, and mitigation priorities, related to hazards such as earthquakes, flooding, and extreme heat, while also considering the City's growth and development trends. Mitigation strategies outlined in the City’s annex include seismic retrofitting critical facilities, flood control measures, and public education initiatives to increase community resilience. The annex was developed in coordination with various stakeholders, including neighboring jurisdictions, non -profits, and local businesses, ensuring a comprehensive and inclusive approach to hazard mitigation.
The City also completed a Seismic Engineering Study in 2025 that presents a detailed seismic risk assessment of the City’s water system facilities and identifies recommended seismic mitigation projects to address vulnerabilities identified during the evaluation.
8.9.2 SFPUC Seismic Risk Assessment and Mitigation Plan As part of the SFPUC’s Facilities Reliability Program and WSIP, the SFPUC performed an extensive multi-year evaluation of seismic risks to its water system that resulted in major capital improvements to increase seismic reliability. The goals of WSIP include enhancing the ability of the SFPUC water system to meet identified levels of service goals for water quality, seismic reliability, delivery reliability, and water supply. One of the reasons the SFPUC developed WSIP was to reduce the likelihood of shortages, thereby reducing the likelihood of needing to implement the WSCP. Several WSIP projects located in San Francisco improved the seismic reliability of the in-City distribution system, such as additional wells that can be used as emergency drinking water sources. Many WSIP projects related to the RWS outside of San Francisco, the majority of which are now complete, addressed both seismic reliability and overall system reliability. The DRAFT
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SFPUC completed the San Francisco portion of WSIP as of October 2020 and forecasts that the overall WSIP will be complete in June 2032.
The Level of Service (LOS) Goals and Objectives for seismic reliability informed development of WSIP capital projects and guided program implementation. The LOS established post - earthquake delivery and recovery objectives under the following seismic scenarios:
• Magnitude 7.9 event on the San Andreas fault
• Magnitude 7.3 event on the Hayward fault
• Magnitude 6.9 event on the Calaveras fault
An assessment of seismic risk and resilience is contained in the body of analysis performed to support the WSIP. The risks associated with the seismic scenarios considered are reflected in the delivery objectives established in the LOS, specifically:
• Delivery of winter month demand 24 hours after a major earthquake, and • Delivery of average day demand 30 days after a major earthquake In addition to the improvements that have or will come from the WSIP, the SFPUC has already constructed system interties for use during catastrophic emergencies, short -term facility maintenance and upgrade activities, and times of water shortages. These are listed below:
• An intertie that may transfer up to 30 mgd between the SFPUC and East Bay Municipal Utilities District (EBMUD) systems, allowing EBMUD to serve the City of Hayward (an SFPUC wholesale customer) and/or supply the SFPUC directly (and vice versa); • An intertie that may transfer up to 40 mgd between the SFPUC and Valley Water systems; and,
• An intertie between the SFPUC the South Bay Aqueduct that the SFPUC used in 1991-1992 and may upgrade to enable the SFPUC to receive State Water Project water in the event of a future emergency.
The WSIP also includes projects related to standby power facilities at various locations. These projects provide for standby electrical power at six critical facilities to keep them in operation during power outages and other emergency situations. Permanent engine generators are located at four locations (San Pedro Valve Lot, Millbrae Facility, Alameda West, and Harry Tracy Water Treatment Plant), while hookups for portable engine generators are at two locations (San Antonio Reservoir and Calaveras Reservoir).
The City and County of San Francisco also have a Hazards and Climate Resilience Plan (https://www.onesanfrancisco.org/hazards-and-climate-resilience-plan) which was last updated in July 2025. This plan is a roadmap to minimizing the impacts of natural hazards and climate change on buildings, infrastructure, and communities. The plan also serves as San Francisco’s Local Hazard Mitigation Plan which it updates every five years to include the latest understanding of natural hazards and climate change impacts, local risks, and community priorities. Examples of hazards analyzed in the plan include dam or reservoir failure, flooding, drought, and wildfire.
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8.9.3 Valley Water Local Hazard Mitigation Plan
Valley Water’s Local Hazard Mitigation Plan (LHMP) identifies capabilities, resources, information, and strategies for building resilience and reducing physical and social vulnerabilities to disasters. It also coordinates mitigation actions, providing essential guidance for Valley Water to reduce its vulnerability to disasters . Valley Water developed the LHMP to be consistent with current legislation, conditions, and best available science . This ensures that hazards are accurately profiled; policies are consistent with current Valley Water standards and relevant Federal, State, or regional regulations; and Valley Water has an updated LHMP consistent with Federal Emergency Management Agency (FEMA) ERP requirements. The LHMP also includes strategies to reduce vulnerability to disaster through education and outreach programs, foster the development of partnerships, and implement risk reduction activities.
Since 2017, Valley Water’s LHMP is attached an annex to the Santa Clara County’s MJHMP, maintained by the Santa Clara County Office of Emergency Management. The Valley Water LHMP was most recently updated in 2023 and approved by FEMA in February 2024 and is valid for the period of February 8, 2024, through February 7, 2029.
8.10 Legal Authority
The City regulates water use under Sunnyvale’s Municipal Code Chapter 12. With the approval of City Council, the City has the authority to establish a WSCP to prepare a set of actions to respond to water supply restrictions caused by drought conditions, supply disruptions, and/or any other unforeseen emergencies. Typically, City Council reviews and approves all WSCP policies and programs as part of the UWMP planning process before they can be implemented and placed into practice. However, because the WSC P is a standalone document, it can be modified and updated as a separate process as described further in this section.
When a water shortage is suspected, the City will work with its wholesalers and other regional partners to discuss the possible proclamation of a local emergency per the California Government Code, California Emergency Services Act (Article 2, §8558). The City’s Environmental Services Director will identify and recommend a water shortage level to be acknowledged, and upon approval, City Council shall declare a water shortage emergency, in accordance with Water Code Division 1, §350.
8.11 Plan Adoption, Submittal, and Availability
As part of the 2025 UWMP planning cycle, the City’s 2025 WSCP was adopted together with the 2025 UWMP. However, because the Water Code requires that the WSCP be adopted as a standalone plan, the WSCP can be amended or updated as necessary outside of the five -year UWMP planning cycle. This section describes the steps taken by the City to meet the requirements of the Water Code pertaining to public availability, adoption, submittal, and availability of the 2025 WSCP as well as the steps needed to amend the WSCP. The resolution approving the 2025 WSCP for the City is included in Appendix L of the UWMP.
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8.11.1 60-Day Notification
Notifications indicating preparation of the City’s 2025 WSCP were provided to the cities and counties listed in Table 8-15 at least 60 days in advance of the public hearing as required by the Water Code; a copy of the notice is included in Appendix A of the UWMP.
8.11.2 Notice to Cities and Counties
The public hearing notice for the 202 5 UWMP and WSCP was sent to the cities and counties listed in Table 8-15 and prior to the public hearing. Three notices were posted in the Sunnyvale Sun to inform the public of the upcoming public hearing. The notices include the time and place of the hearing, as well as locations where the plans were made available for public inspection .
The first notice was published on May 15, 2026, the second on May 22, 2026, and the third on May 29, 2026. A copy of the notice is included in Appendix A of the UWMP.
Table 8-15: Notification to Cities and Counties
City Name 60 Day Notice Notice of Public Hearing
City of Hayward
City of Milpitas
City of Mountain View
City of Palo Alto
City of Santa Clara
City of Brisbane
City of Burlingame
City of Daly City
City of Menlo Park
City of Millbrae
City of Redwood City
City of San Bruno
City of East Palo Alto
City of San Jose
City of Foster City
County Name 60 Day Notice Notice of Public Hearing
Alameda County
Santa Clara County
The draft plans were made available for the community and posted on the City’s website (www.sunnyvale.ca.gov) on May 15, 2026. Copies of all public notices of the hearing are included in Appendix A.
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Attachment 1
City of Sunnyvale
2020 Urban Water Management Plan
SECTION 8 – Water Shortage Contingency Planning
www.hydroscience.com
8.11.3 Public Hearing and Adoption
The public hearing for consideration and adoption of the 202 5 UWMP and WSCP by the City Council took place on June 16, 2026 during a normal City Council session. The session began with the public hearing to allow community input prior to the formal adoption of both plans by City Council. All public input received was considered before final adoption of both documents. The adopted resolution is included in Appendix L of the UWMP.
8.11.4 Plan Submittal
Upon adoption of the 202 5 UWMP and WSCP by City Council, implementation took place as identified in this document . Submission of the adopted plans to DWR was done electronically within 30 days from the date of adoption, and no later than July 1, 2026.
8.11.5 Public Availability
The adopted UWMP and WSCP were posted on the City’s website (www.sunnyvale.ca.gov) within 30 days of submission to DWR and were submitted to the California State Library.
8.11.6 Amending an Adopted WSCP
This WSCP has been developed to act as a set of guidelines for steps to take during a drought/water shortage. Given the variable nature of water and the climate and the intersection of many different factors, no two drought situations will be identical, and therefore, there must be room for improvement/alteration in the way that the City responds to each individua l water shortage condition as it is encountered . This WSCP is an adaptive framework that is based on the City’s response to the 2012 -2016 and 2021-2023 droughts, but it is open to refinement and amendment as the effectiveness of current practices is evaluated, new and different conditions are experienced, and new options for drought mitigation measures (demand management, supply augmentation, etc.) become available.
Based on the results of monitoring and reporting processes described in Section 8.6, the City can amend the procedures outlined in this WSCP pending the approval of City Council. The City’s 2025 WSCP will only be modified following notification, public hearing, adoption, and submittal as prescribed in the Water Code.
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Attachment 1
City of Sunnyvale
2025 Urban Water Management Plan
SECTION 9 – Demand Management Measures
www.hydroscience.com
– DEMAND MANAGEMENT MEASURES
The City of Sunnyvale has a commitment to water conservation and implementation of the Demand Management Measures (DMMs) identified by the State . DMMs can be water conservation programs, outreach , or monetary incentives offered to customers as well as institutional tools to help water purveyors reduce water use.
Many of the DMMs offered by the City to customers are programs run by, or coordinated through, the wholesaler Valley Water or BAWSCA. The programs are either funded through the wholesale water rates paid by the City or are directly reimbursed by the City. Additional program descriptions including implementation over the past five years and the nature and extent of each program component within a DMM are explained in this section.
Table 9-1 below lists current and planned program components implemented by the City for each measure and indicates who administers the program.
Table 9-1: Demand Management Measures (DMMs)
Demand Management Measure City Program Valley Water
Program
BAWSCA
Program
Water Waste Prevention Ordinance
Adopted water waste prohibition ordinance X
Metering
Fully metered service connections X
Retrofit or replacement of aging meters X
Submeter rebate program X
Conservation Pricing
Conservation rate structures X
Public Education and Outreach
Public information programs X X
School education programs X X
Programs to assess and manage distribution system real loss System water audits, leak detection, AMI meters, and repair X Water loss management program X
Water Conservation Program Coordination and Staffing Support Dedicated water conservation coordinator X
Other Demand Management Measures
Residential surveys and water use reports X
Residential plumbing retrofit X
Large landscape conservation programs and incentives X Graywater landscape irrigation rebates and incentives X Rain barrel rebate program X X
Conservation programs for residential, and Commercial,
Industrial, Institutional (CII) customers X
Regional Water Conservation Program X
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City of Sunnyvale
2025 Urban Water Management Plan
SECTION 9 – Demand Management Measures
www.hydroscience.com
The City, as a municipally owned water utility, has the legal authority to implement DMMs by ordinance or resolution of the City Council . This authority has been exercised through past implementation of DMMs, fees, and penalties . This section describes the DMMs that are implemented within the City’s service area to continue to encourage water conservation in support of the City’s supply reliability.
9.1 Demand Management Measures for Wholesale Agencies
Both Valley Water and SFPUC implement DMMs to promote conservation and reduce demand on water supply through metering, public education and outreach, and water conservation program coordination.
9.2 Demand Management Measures for Retail Agencies
Below is a description of the various DMMs that are implemented within the City either by the City, Valley Water, or BAWSCA.
9.2.1 Water Waste Prevention Ordinances
Implementation: Drought and water conservation requirements are implemented by the City and will continue to be implemented by the City in the future.
Description: On May 12, 2015, the City Council adopted a resolution and established a 30% water use reduction target from 2013 levels (increased from 15%) through June 2016 out of concern for drought conditions, groundwater depletion and land subsidence. The City’s resolution instituted a two-day watering schedule, prohibits outdoor irrigation within 48 hours of rainfall, and requires hotels to give patrons the option of having linens laundered daily.
In June 2016, the City Council adopted a n ordinance to declare a continued drought condition through June 2017. The ordinance set a 15% water use reduction target from 2013 levels and limited the use of potable water for landscape and turf irrigation to three days a week. The ordinance also prohibits the use of potable water to irrigate ornamental turf on public street medians. Prohibitions implemented by the City include:
• Water waste due to broken or defective plumbing, sprinkler, watering, or irrigation systems; • The application of potable water to outdoor landscapes in a manner that causes runoff; • Landscape irrigation between the hours of 9 AM and 6 PM; • Landscape irrigation for more than 15 minutes per day per station when using a landscape irrigation system or a watering device that is not continuously attended; • Using a hose without a positive shutoff valve to wash cars, buses, boats, or trailers; • The application of potable water to driveways and sidewalks; • The use of potable water in a fountain or other decorative water features unless the water is part of a recirculating system;
• The application of potable water to outdoor landscapes within 48 hours or rainfall; DRAFT
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City of Sunnyvale
2025 Urban Water Management Plan
SECTION 9 – Demand Management Measures
www.hydroscience.com
• Serving water in restaurants except upon request;
• The use of potable water to irrigate ornamental turf on public street medians; and • The installation of single pass cooling process in new construction.
Violation of these provisions may escalate to installation of a flow restricting device upon the water service lines and cumulative fines . The Water Conservation Plan and Municipal Code are included as Appendix G and Appendix J, respectively.
9.2.2 Metering
Implementation: The City implements metering requirements within the service area and will continue to do so. Additionally, the City implements a program to retrofit and replace meters as they age. Through Valley Water, the City offers multi-family housing the opportunity to receive a rebate for installation of submeters.
Description: The City requires that all service connections within the service area are metered .
All new service connections are metered and are billed by volume of water used . There are no known connections operating without a meter. Connections to the City are governed by Chapter
12.24 of the Sunnyvale Municipal Code, which is provided as Appendix J.
Sunnyvale encourages all new commercial, industrial, and multi -family developments to have dedicated water meters and separate accounts and meters for landscape irrigation . As older developments are replaced with newer ones, any customers without a dedicated landscape irrigation meter will be encouraged to acquire one.
Valley Water’s Submeter Rebate Program: Beginning as a pilot in 2001 and extended in 2008, this program provides a $150 rebate for every submeter installed at multi-family housing complexes, such as mobile home parks and condominium complexes. Individual well owners, homes on a shared well, and ADUs also qualify. Cost sharing agreements increase the rebate rate in some areas.
Water use records from participating mobile home parks showed an average water savings of 23% per mobile home in a pilot study. This program has issued 7,588 rebates to date. The increase in development and use of ADUs on residential properties in recent years provides an opportunity to generate more participation in this program. Valley Water plans to continue to offer this program in the future to reach the region’s long-term water conservation goals.
9.2.3 Conservation Pricing
Implementation: Conservation pricing is implemented by the City and will continue to be implemented by the City in the future.
Description: In March 1989, in response to drought conditions, the City adopted a water conservation plan that required implementation of DMMs such as an inverted rate structure, deterrents to water waste, landscaping restrictions and the institution of a recycled water program.
Prior to the 1976 -1978 drought, the City had a traditional declining -rate block structure, which meant that the more water that was used by a customer, the lower the cost per unit . In 1977, a DRAFT
Attachment 1
City of Sunnyvale
2025 Urban Water Management Plan
SECTION 9 – Demand Management Measures
www.hydroscience.com
flat-rate block structure was established with costs fixed regardless of the quantity used . In the year following the drought, an inverted rate structure was adopted and was regularly modified to ensure water conservation and to adequately reflect the high cost of developing new water resources projects. The City restructured its residential water rate tiers in 2018, collapsing a four-tier inclining block structure into a two-tier indoor-versus-outdoor framework effective July 1, 2018; subsequent rate actions have modified prices but not tier definitions.
Sunnyvale’s Fiscal Year 2024/2025 Utility Fee Schedule is attached as Appendix K.
9.2.4 Public Education and Outreach
City of Sunnyvale Public Information Campaigns
Implementation: The City participates in developing and implementing public information programs. The City also implements outreach programs in the service area . The City will continue to implement public information programs in the future.
Description: The City has carried out various public information campaigns in the past and continues to do so. Multi-media advertising has covered topics such as water conservation, urban runoff pollution prevention, water quality, groundwater recharge, water supply, water recycling, watershed and flood protection, and stream stewardship. Efforts included paid advertising, public service announcements, bill inserts/brochures, targeted mailings, website development, social media, community outreach, school programs, and special events. One highlight was for a high efficiency washing machine, encouraging participation in rebate programs, and learning more about the City’s conservation efforts . Campaigns have been carried out in various languages including English, Spanish, Vietnamese, and Chinese.
The City also participates by including inserts and information flyers in customer utility bills, and by distributing articles and information in newsletters and reports sent to City residents. All utility bills include a water usage chart comparing current year to previous year usage to help customers who have unknowingly increased their water consumption to check on the cause of the increase.
Sunnyvale also participates in public activities such as the Farmer’s Market and Earth Day Celebration. Partnerships with the Public Safety and Community Services departments in activities sponsored by those departments (Pancake Breakfast, Summer Camp) provide more opportunities to reach youth and the public with a message extolling the virtue of water conservation.
The City maintains a water conservation page on the City’s website that provides information on water conservation program incentives and rebates, water conservation tips and tools, drought restrictions, and links to wholesaler water conservation programs or other informative websites.
City of Sunnyvale School Education Programs
Implementation and Description: The City also has a water pollution and conservation outreach program spearheaded by Sunnyvale’s Environmental Services Department (ESD) staff. This program offers tours of the WPCP, classroom presentations , City Hall field trips, and a creek water education program. Plant tours teach youth about the function of wastewater treatment, water pollution prevention, and water conservation . Oftentimes, the tour is a supplement to a DRAFT
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City of Sunnyvale
2025 Urban Water Management Plan
SECTION 9 – Demand Management Measures
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water study module in the classroom, and approximately 50% are repeat tours scheduled year after year by teachers.
The Creek Education program provides watershed, urban runoff, water pollution prevention, storm water, creek education, water conservation and wastewater information to Sunnyvale students at schools in the Cupertino & Sunnyvale school districts. Students take a yearly field trip to Stevens Creek at McClellan Ranch Park after studying water and structures of life courses in class.
Classroom presentations involve a watershed pollution demonstration designed to correlate with the State of California curriculum standards for earth sciences . Subjects covered include water cycle, groundwater, aquifers, water pollution and water conservation.
City Hall Field Trips allow students to meet City staff and learn how departments such as ESD and Public Safety keep the City running. The field trips include presentations on the responsibilities of ESD and water conservation tips that students can apply in their daily lives.
All City School Education Programs were halted in 2020 due to the COVID -19 outbreak and in the interest of public health and safety. All City School Education Programs have been reinstated in 2022. However, due to construction and safety concerns of the COVID -19 pandemic, plant tours are limited to staff and specific groups such as Leadership Sunnyvale since 2023.
Valley Water Public Information Campaigns
Implementation and Description: Valley Water conducts outreach activities which include multi- media marketing campaigns directed at the diverse county population, website development and maintenance, social media, publications, public meetings, community events, interagency partnerships, water conservation w orkshops and seminars, and a speaker’s bureau. Outreach efforts focus on supporting customers , water retailers, and other key stakeholders to make conservation a way of life in Santa Clara County (in alignment with Board Resolution 23 -52), as well as advancing community knowledge, awareness, and understanding of the conservation and water supply services provided by Valley Water.
Recognizing that landscape irrigation accounts for more than half of residential water use, Valley Water's water conservation campaigns encourage Santa Clara County residents to replace water- intensive lawns with drought-tolerant landscapes and to schedule free outdoor water surveys to identify opportunities to improve outdoor water efficiency. The annual multilingual effort focuses on accessibility, clear calls to action, and culturally relevant stories of landscape transformations. • Multilingual Digital Outreach: Ads and landing pages are shared in English, Spanish, Vietnamese, and written Chinese, ensuring that Santa Clara County's diverse community can connect with the call to conserve water in culturally relevant ways. • Landscape Rebate Program Stories: Valley Water's multilingual resident -driven videos highlight real homeowners who have transformed their yards. The stories help build trust and emotional connection while showcasing the benefits and beauty of drought -tolerant landscapes.
Through targeted messaging and inclusive storytelling, Valley Water reaches underserved and non-English-speaking communities, building trust and inspiring lasting behavioral change. By combining digital innovation, inclusive storytelling, and community-centered engagement, Valley Water demonstrates how strategic communications can drive meaningful behavior change.
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City of Sunnyvale
2025 Urban Water Management Plan
SECTION 9 – Demand Management Measures
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Valley Water’s public outreach efforts also include social media and updates to its water conservation program website ( www.watersavings.org). The website is updated throughout the year to include the latest program information, new reports/studies, and updates on workshops.
Landscape Summit: Since 2016, Valley Water has annually held the Landscape Summit, an event developed through Valley Water’s Landscape Committee as a forum for landscape professionals to learn about water issues in the county and California as a whole, and how water relates to t he landscaping industry. It is also an opportunity for Valley Water to get valuable feedback from landscape professionals, and for attendees to collaborate and exchange ideas.
The 10th Annual Landscape Summit was held in-person and virtually on February 27, 2025.
Nursery Program: To increase the public’s awareness of water -efficient gardening techniques, Valley Water developed the Nursery Program in 1995. This program distributes, at least quarterly, a series of educational materials to nurseries, irrigation supply stores, and big box store retailers throughout the county. In March 2025, Valley Water developed nursery outreach pedestal signs to be placed in participating nurseries. These pedestals streamline program marketing to customers of relevant stores by displaying QR codes th at redirect to conservation program resources and program applications. The Nursery Program literature is currently being distributed to and displayed at more than 30 participating nurseries and vendors.
Demonstration Gardens : Demonstration gardens can inspire community members to incorporate sustainable, ecological, or water -wise plants and techniques into their landscaping.
Valley Water has maintained a list of water -wise and California -native plant demonstration gardens to help guide community members in converting their own gardens to be more water - efficient. In June 2025, Valley Water finalized a contract with BFS Landscape Architects to provide design services for a planned demonstration garden at Valley Water’s Headquarters building. The approximately 26,000 square feet garden will showcase water conservation and sustainable practices, serve as a public gathering and educational space, and emphasize Valley Water's Landscape Rebate Program requirements . The garden will highlight a watershed approach by incorporating features such as native and climate -appropriate plants, high -efficiency irrigation systems, educational signage, and integrated rainwater capture. Funded through the Safe, Clean Water and Natural Flood Protection Program, the design of the demonstration garden is expected to be completed in 2026, and construction will be completed by the close of FY 2028.
Workshops: Valley Water promotes water conservation through workshops and trainings throughout the community. Examples of these include Graywater Laundry to Landscape workshops and presentations to schools, local universities, industry association gatherings, nursery staff, community gardens, native plant society members, corporate events, local Master Gardeners, water conservation peers at various conferences, and many more. On average, Valley Water conservation staff attend over forty-five presentations and present at over a dozen events (excluding webinars discussed below) each year. In April 2022, Valley Water began offering “Office Hours” to provide drop-in opportunities for customers to ask about program benefits and the application process. This has been a particularly effective service reaching customers in small groups during regularly scheduled events throughout each month. In addition, Valley Water launched a Webinar series to amplify awareness of its water conservation rebates and services.
The webinars were live translated into Spanish, Vietnamese, and Mandarin and are uploaded to www.youtube.com/valleywater.
Growing Native Garden Tour: To showcase exemplary native plant gardens, Valley Water has been a sponsor of the Growing Native Garden Tour every spring since 2003. Each year, thousands of participants visit upwards of 60 gardens. These native plant gardens demonstrate DRAFT
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City of Sunnyvale
2025 Urban Water Management Plan
SECTION 9 – Demand Management Measures
www.hydroscience.com
the beauty and efficiency of well-maintained native gardens to residents of Santa Clara and San Mateo counties. In addition to showcasing native plants, at least one garden offers native plants for sale each year. As an expanded community -based outreach opportunity, Valley Water has produced eight Landscape Rebate Success Story testimonial videos featuring gardens on the tour to help promote Valley Water’s Landscape Rebate Program.
Community Events: Each year, Valley Water staff participate in a variety of public events to engage with the Santa Clara County community on water -related issues, such as water conservation, water recycling and purification, flood preparedness, and communit y-specific projects. The agency’s community outreach effort provides opportunities for collaboration with Valley Water’s civic, business, and nonprofit partners through hosting informational booths at more than 170 conferences, symposia, science fairs, and other community events from 2021 through 2025.
Valley Water School Education Programs
Implementation and Description: Valley Water’s Education Outreach (EO) program was established in 1995 to develop and implement water education programs. Education Outreach provides free grade-level appropriate classroom presentations, assemblies, and field trips at Valley Water outdoor classrooms to schools and youth serving organizations within Santa Clara County. The objective is to educate youth about water with a focus on water conservation, water supply, watershed stewardship, pollution reduction, and flood preparedness. EO also provides free education materials to educators, including workbooks and videos.
From 2021 to 2025, Valley Water’s EO program reached an average of 9,000 youth per year, engaging a total of 54,546 youth. EO has supported over 2,526 educators through classroom presentations, field trips, and resources. Youth from over 1,873 classrooms have participated in hands-on, Next Generation Science Standards related programs and field trips. Examples include lessons using storytelling for pre-K and early elementary students and using hands-on science activities for middle school and high school students.
9.2.5 Programs to Assess and Manage Distribution System Real Loss Implementation: The City continuously implements water audits and leak detection and repair for the water distribution system . In addition to City staff continuously monitoring the water distribution system through SCADA technology and field inspections, the City maintains an active leak detection program. The City also has an upcoming project to modernize water meters with Advanced Metering Infrastructure (AMI) meters that would further reduce water losses. The City expects this to be an ongoing program.
Description: To fulfill this measure, all accounts within the City service area are metered . The City also offers help to its residential customers in determining if a leak exists at the property .
Water Meter Readers report leaky meters or water meters running when a residence does not appear to be occupied so that a technician can be dispatched to investigate and make repairs as needed.
Additionally, a leak detection company conducts annual inspections of distribution pipeline. The length of pipe inspected annually is determined by the City . The leak detection contractor generates a condition assessment report for the inspected pipeline, and reported leaks are DRAFT
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2025 Urban Water Management Plan
SECTION 9 – Demand Management Measures
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promptly remediated by City staff or a hired contractor . These programs have helped the City track and reduce system losses.
The City has an upcoming AMI meter project that will replace existing meters with newer, more accurate technology. The transition to AMI meters is expected to further reduce water losses from leaks or unregistered consumption. The AMI meter project will include an online customer portal that allows customers to monitor their water use and receive alerts for unusual consumption, which may result in behavioral changes that support water conservation.
BAWSCA’s Water Loss Management Program (WLMP): Established in 2018, this program supports participating BAWSCA member agencies in reducing water losses to an economically optimized level and complying with water loss requirements implemented by the SWRCB per SB 555. The program includes two components:
• Loss Evaluation & Knowledge (LEAK) workgroup : A Core Conservation Program to provide water loss control education and peer -to-peer learning opportunities for BAWSCA member agencies.
• WLMP Subscription Program: Offers individualized support to BAWSCA agencies on water audit completion, validation, and other tasks associated with water loss management.
9.2.6 Water Conservation Program Coordination and Staffing Support Implementation and Description: Since 1999, the City’s regular staffing has included an Environmental Programs Specialist position (formerly Environmental Outreach Coordinator) whose scope has included education, outreach, and implementation of programs for water conservation. The current Environmental Programs Specialist’s information is provided below. It is expected that there will continue to be a staff member whose scope includes water conservation programs.
Environmental Programs Specialist:
Name: Claire Wong
Title: Environmental Programs Specialist, Environmental Services Department Address: City of Sunnyvale
456 W. Olive Ave
Sunnyvale, CA 94086
Phone: (408) 730-7734
Email: [email protected]
9.2.7 Other Demand Management Measures
Residential Programs
Implementation and Description: The Water Wise Survey Program, formerly known as the Water Wise House Call Program, was first implemented in July of 1998 as a pilot program. Since then, there have been multiple residential programs administered by Valley Water to meet the DRAFT
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SECTION 9 – Demand Management Measures
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region’s long-term water conservation goals. The City shares the cost to support these programs.
The implementation of each program is described below:
• Water Use Reports: Water use reports have been proven effective at encouraging residents to save water and when combined with Advanced Metering Infrastructure, can inform residents about water leaks quickly. In FY 2014, Valley Water started a program to share costs with the local water retailers on home water use reports. The program has expanded to provide services beyond single-family residential homes. Since the start of this cost sharing program, nearly 4.4 million reports have been distributed. In FY 2 025, over 106,000 sites received water use reports (the number of sites varies over the year and by water retailer).
These metrics exclude other service areas that offer water use reports independent of Valley Water funding. Valley Water plans to continue to share in the cost of various programs that benefit customers’ awareness of how they use water.
• Water Wise Survey Program: Valley Water is the administrator for the City and County residential Water Wise Survey Program, formerly known as the Water Wise House Call Program. Water Wise Outdoor Survey Program offers a free, comprehensive consultation from a trained irrigation professional to single-family and small multi-family sites with a working irrigation system. The consultation includes evaluating the irrigation system, flagging issues onsite, irrigation scheduling assistance, identifying rebate pr ograms for which participants may also qualify, and creating a custom report detailing the survey findings. Since it launched in 2017, Valley Water performed 1,296 residential Water Wise Outdoor Surveys.
Valley Water’s residential survey program includes educating the customer on how to read a water meter; checking flow rates; installing low-flow devices; checking for leaks; checking the irrigation system for efficiency; measuring landscaped area; developing an efficient irrigation schedule for different seasons; and providing the customer with evaluation results, water savings recommendations, and other educational materials. Valley Water increased efficiency and participation by using landscape measurements from this program as an initial qualifying step for the Landscape Rebate Program.
• Fixture Distribution: Valley Water also distributes high -quality, low-flow showerheads and faucet aerators to community members through water retailers and public events. To improve distribution efficiency and expand program accessibility, Valley Water launched the Online Shopping Program (eCart Program) in 2021. This program offers a centralized online platform through which customers can order a range of water-efficient devices. Since its inception, the eCart Program has processed a total of 18,386 orders. Distribution to single-family residential customers includes 14,924 faucet aerators, 11,166 showerheads, and 3,066 DIY kits, in addition to other conservation devices and educational materials.
Between July 2022 and August 2023, Valley Water participated in the Water Coordination Program, an initiative that leveraged Pacific Gas & Electric’s (PG&E) Energy Savings Assistance (ESA) Program , to deliver water conservation services to income -qualified customers. Two pilot efforts —the Leak Assessment and Repair Pilot and the Toilet Assessment and Retrofit Pilot —provided equitable, cost -effective conservation services to low-income households . Through a coordinated approach, Valley Water and its partners successfully delivered 214 in-home leak assessments, 103 toilet retrofits to Ultra HETs, and replaced leaking fixtures including 66 bathroom faucets, 20 kitchen faucets, and 45 outdoor hose bibs among other measures alongside PG&E’s energy efficiency services. These totals are not included in Table 9 -1. Collectively, the measures installed through this program are estimated to achieve water savings of 12,123,560 gallons over the expected useful life of the installed devices.
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Residential Plumbing Retrofit
Implementation: This program was first implemented in 1992 . It is an active program administered by Valley Water . The City also implements the program and shares the cost to support this program. The City plans to continue offering free showerheads and aerators both directly and through Valley Water’s Water-Wise House Call Program.
Description: The City and Valley Water distribute high-quality, low-flow showerheads and faucet aerators to single -family and multi -family residents as the implementation of the residential plumbing retrofits program . The City makes low -flow showerheads and aerators available to residents free of charge and to date has directly distributed thousands of units to interested parties.
Large Landscape Conservation Programs and Incentives
Implementation and Description: Large landscape conservation programs are administered by Valley Water. All programs described below are currently active and are expected to continue to be implemented in the future.
• Large Landscape Program: The Large Landscape Program provides landscape surveys and site -specific landscape water budgets for qualifying sites since 2014 (https://www.valleywater.org/saving-water/rebates-surveys/commercial-landscape-surveys).
Qualifying sites are automatically enrolled into the program through partnership agreements with participating retailers, including the cities of Gilroy, Milpitas, Morgan Hill, Mountain View, Palo Alto, Santa Clara, Sunnyvale, San José ( San José Municipal Water), and San Jose Water. Site stakeholders for enrolled sites can access an online platform through https://www.waterfluence.com/ to access their site -specific landscape budgets, request a landscape survey, and utilize additional tools and resources to improve irrigation efficiency.
During FY 2021-2025, Valley Water lowered the eligibility threshold resulting in the enrollment of 1,821 additional sites, for a total of 4,821 sites at the end of FY 2025. The program now covers 99% of dedicated irrigation meter (DIM) landscapes throughout incorporated areas of the county. Since program launch, Valley Water has distributed over 300,000 water -use reports and monthly budgets, conducted 309 surveys through FY 2025, and encourages sites to participate in the Landscape Rebate Program to improve water -use efficiency and aid Valley Water’s long-term savings goals.
This program is a key compliance tool for retailers in meeting the State’s Making Conservation a California Way of Life regulatory framework. To further improve support for retailers’ compliance with needing landscape area measurements for all DIM sites, small DIM sites that were previously not enrolled in the program due to their landscape size will be addressed during FY 2026.
As of the end of 2025, the sites enrolled in Valley Water program were saving 31% on irrigation usage compared to 2013 usage. Valley Water will continue to offer and expand this program in the future to reach the region’s long-term water conservation goals, particularly with regards to opportunities for this program to assist compliance with elements of AB 1668/SB 606. • Landscape Rebate Program: Valley Water began to focus on water efficient landscapes by launching a version of the program in early 2005. In an effort to expedite program participation, Valley Water’s Board supported doubling the maximum rebate from $1,000 to $2,000 for residents and from $10,000 to $20,000 for commercial sites in 2009. The rebate cap for commercial, institutional (CII), and multi-family (5 or more units) sites was then increased to DRAFT
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$50,000 in January 2020. In July 2021, the turf conversion rebate was increased to $2 per square foot and the residential site cap was increased to $3,000. In response to an emergency regulation that prohibits the watering of non-functional turf areas at commercial, industrial, and institutional sites, issued by the State Water Resources Control Board in June 2022 , Valley Water introduced a Lawn to Mulch rebate in July 2022 for commercial properties. Valley Water then increased the lifetime cap for CII sites to $100,000. Cost sharing agreements increase the rate per square foot and rebate cap in some areas.
Currently, any qualified property in Santa Clara County with qualifying high -water using landscape can receive rebates for converting to qualifying low water using landscape with a minimum of 50% qualifying plant coverage; 2 to 3 inches of mulch; and a con version from overhead irrigation to drip, micro spray, bubbler, or no irrigation.
In January of 2019, Valley Water added Rainwater Capture Rebates to the Landscape Rebate Program. Customers now have the opportunity to receive rebates for the installation of rain barrels, cisterns, and rain gardens. Since the start of the Rainwater Capture Rebates, rainwater has been diverted from nearly 80,500 square feet of roof area into qualifying rain gardens, 779 rain barrels have been installed, and cisterns with a total combined capacity of over 56,500 gallons have received a rebate.
Lawn Busters Program: Lawn Busters Program is designed to provide a low cost, expedient option for low -income, elderly, disabled or veteran homeowners and institutions within disadvantaged communities throughout Santa Clara County who wish to convert their lawns to low -water using landscape. In targeting these hard -to-reach sectors, the Lawn Busters Program is intended to help Valley Water meet its short-term drought response goals as well as its long-term water conservation goals. Since the start of the Lawn Busters Program, nearly 280,000 square feet of lawn were converted to low -water using landscape. The program concluded in June 2024 and Valley Water is in the process of developing an enhanced direct installation program to serve low-income customers within Santa Clara County. • Irrigation Equipment Rebates : Over 26,000 pieces of irrigation equipment were rebated between FY 2021 and FY 2025, including high efficiency sprinkler nozzles and bodies, rain sensors, and flow sensors.
Additionally, over 2,400 Weather-Based Irrigation Controllers (WBICs) have been installed during FY 2021 and FY 2025. Sometimes referred to as “smart controllers”, WBICs utilize the principles of evapotranspiration or “ET” to automatically calculate a site -specific irrigation schedule based on several factors, including plants and soil type. The controller then adjusts the irrigation schedule as local weather changes to regulate unnecessary irrigation, saving up to 20% of irrigation water use when used prop erly. Valley Water plans to continue to offer rebates for WBICs in the future in order to reach the region’s long -term water conservation goals.
• Landscape Maintenance Consultation Program: The Landscape Maintenance Consultation Program, started in May 2018, was developed as a way to help Landscape Rebate Program participants learn how to properly maintain their newly converted low water use gardens. To date, 1,441 residential rebate customers have participated in the program.
During the free, one-hour consultation, the customer has an opportunity to walk through their garden with a landscape professional, reviewing site specific recommendations for plant maintenance and pruning, soil health, pest management, and irrigation scheduling and maintenance. The Landscape Maintenance Consultation Program will continue to be offered to new rebate program participants whose gardens are at least one year established.
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Attachment 1
City of Sunnyvale
2025 Urban Water Management Plan
SECTION 9 – Demand Management Measures
www.hydroscience.com
The City also issued Ordinance No. 19.37 regulating conservation in landscaping. This ordinance applies to all new and rehabilitated landscaping for public agency projects and private development projects that require a permit, as well as developer-installed landscaping in single- family and multi-family projects. A copy of this ordinance is included in Appendix J.
Graywater Landscape Irrigation Rebates and Incentives
Implementation: This program has been active since 2014 and is offered to residential customers interested in using graywater from laundry machines to irrigat e landscape at their homes.
Description: In the last 5 years, Valley Water issued 36 graywater rebates and funded the direct installation of 71 graywater systems. To date, 160 total graywater systems have been installed.
Valley Water’s Graywater Laundry to Landscape (L2L) Rebate Program offers $200 rebate, and cities of Milpitas, Morgan Hill, Palo Alto Utilities, and Santa Clara, and San José Municipal Water cost-share with this program to increase the rebate to $400 total. In addition to providing a rebate for properly connecting a clothes washer to a laundry -to-landscape system, the graywater program also provides information, resources, and workshops on graywater. Graywater use in irrigated landscapes decreases potable w ater use by approximately 17 gallons per person per day or 14,565 gallons per household (on average), depending on the site and system design.
Rain Barrel Rebate Program
Implementation: This program began in October 2014 in partnership with BAWSCA to offer rebates to user s of rain barrel s as part of encouraging using alternative water sources for landscaping water needs.
Description: Sunnyvale offers $50 rebates per rain barrel that is 50 gallons or larger for up to two barrels per household or four for commercial properties. Owners are responsible for installing the barrels according to program guidelines, including screening to prevent mosquito breeding.
Conservation Programs for Commercial, Industrial, and Institutional (CII) Accounts Implementation and Description: Since 1992, Valley Water has implemented various programs targeting CII customers for water efficiency outreach and education . Both the City and Valley Water expect to continue the programs in the future, with the potential for minor changes based on technological advancements . The initiatives and programs implemented to increase water efficiency in the CII sectors are described below.
• Commercial Toilet and Urinal Programs: Valley Water has been replacing inefficient toilets in CII sites since 1994. The CII toilet rebate programs have frequently been offered in tandem with various iterations of high -efficiency urinal (HEU) programs, HET and HEU direct install programs, and retrofit programs for urinal valve installation. Since 2015, over 7,300 HETs were installed or rebated. Additionally, since 2005, Valley Water has had a program to replace urinal flush valves of old, inefficient 1.0 gpf or more urinals with a flush valve that uses only a
0.5 gallon per flush. Since the program was started, approximately 2,580 urinals had been retrofitted or rebated, with 464 installed in the last five years.
In May 2021, Valley Water launched the Fixture Replacement Program (FixRP), a direct-install initiative focused on replacing inefficient indoor plumbing fixtures with high -efficiency, WaterSense-certified models in multi-family residential and commercial properties. Since FY DRAFT
Attachment 1
City of Sunnyvale
2025 Urban Water Management Plan
SECTION 9 – Demand Management Measures
www.hydroscience.com
2021, the program supported 63 sites—48 multi-family properties and 15 schools—and completed the installation of 811-bathroom aerators, 410 kitchen aerators, 1,543 showerheads, 6,420 Ultra HET, and 61 HEUs. The program concluded in April 2025 and has since been replaced by the Direct Retrofit Indoor Plumbing (DRIP) Program, which expands eligibility to include single-family homes.
Commercial Indoor Water Survey Pilot Program: Valley Water initiated the Commercial Indoor Water Use Survey Pilot Program (CIW Survey Pilot) in FY 2024 to support the State’s conservation requirements under Making Conservation a California Way of Life (AB 1668/SB 606) and to engage with hard-to-reach commercial, industrial, and institutional (CII) customers. Developed in partnership with a subset of water retailers, the pilot sought to improve understanding of CII indoor water use, update water savings assumptions, and strengthen coordination among agencies and customers. While initial outreach yielded limited participation, revised efforts resulted in modest engagement and valuable insights, highlighting challenges related to customer contact data, data-sharing constraints, technology gaps, and outreach timing.
In FY 2025, Valley Water strengthened and expanded the pilot, refining outreach strategies and partnering with new retail partners. Outreach to more than 700 CII customers resulted in 15 completed surveys county-wide, representing a more than 500% increase in engagement compared to FY 2024. Targeted follow-up proved essential to improving participation, and the pilot demonstrated strong potential as an engagement and data-gathering tool. Water Efficient Technology Rebate Program: The Water Efficient Technology Rebate (WET Rebate or WET Program) provides rebates for process, technology, and equipment retrofits that save water at CII and multi-family properties. Qualifying retrofit projects that meet program requirements are eligible for a rebate of either $4 per hundred cubic feet (CCF) of water saved annually or up to 100% of equipment costs excluding taxes and labor, whichever is less, up to $100,000. To qualify, projects must save at least 100 cubic feet of water annually.
Examples of eligible projects include ozone laundry systems, cooling towers efficiency upgrades, onsite water reuse, water softeners, and any other equipment that results in measurable water savings, including customized equipment. Cost sharing agreements increase the rate and maximum rebate in some areas. In 2023, eligibility for WET was expanded to include multi-family properties, such as condominium, apartment, and townhome complexes.
To date, Valley Water has funded 114 projects, saving approximately 691,727 CCF/year (1,588 AFY). Since 2020, the WET Rebate has helped save over 11,064 CCF per year from 4 completed projects. The WET Rebate continues to be one of Valley Water’s most cost- effective programs in meeting the region’s long-term water conservation goals.
Regional Water Conservation Program
BAWSCA manages a Regional Water Conservation Program comprised of several programs and initiatives that support and augment member agencies’ and customers’ efforts to use water more efficiently. These efforts extend limited water supplies that are available to meet both current and future water needs; increase drought reliability of the existing water system; and save money for both the member agencies and their customers.
The implementation of the Regional Water Conservation Program builds upon the BAWSCA Demand Study, completed in December of 2025. These efforts include both Core Programs (implemented regionally throughout the BAWSCA service area) and Subscription Programs DRAFT
Attachment 1
City of Sunnyvale
2025 Urban Water Management Plan
SECTION 9 – Demand Management Measures
www.hydroscience.com
(funded by individual member agencies that elect to participate and implement them within their respective service areas).
BAWSCA’s Core Conservation Programs include organizing classes focused on sustainable and water-efficient landscape design, assistance related to automated metering infrastructure, and other associated programs that work to pr omote smart water use and practices . BAWSCA’s Subscription Programs include numerous rebate programs, educational programs that can be offered to area schools, technical assistance to member agencies in evaluating water loss, and programs that use data analytics to provide customized water-saving recommendations to customers. In total, BAWSCA offers 2 4 programs to its member agencies and that number continues to grow over time.
Each fiscal year, BAWSCA prepares an Annual Water Conservation Report that documents several conservation program metrics exemplifying the benefits of the Regional Water Conservation Program to all 26 BAWSCA member agencies. Additionally, the report highlights how all 26 member agencies participate in one or more of the Subscription Programs offered by BAWSCA, such as rebates, water loss management and large landscape audits . The Demand Study indicates that through a combination of active and passive conservation, 16.14 MGD will be conserved by BAWSCA’s member agencies by 2050.
The Core Programs provided as a part of the Regional Water Conservation Program include conservation measures that benefit from regional implementation and provide overall regional benefit and are funded through the annual BAWSCA budget. The Subscription Programs are conservation measures that individual agencies must elect to participate in and whose benefits are primarily realized within individual water agency service areas. As such, the Subscription Programs are funded by individual member agencies, based on their participation level. The City is actively participating in the rain barrel rebates and water loss management Subscription Programs.
9.3 Reporting Implementation
9.3.1 Planned DMM Implementation
The City plans to continue to offer the current DMM suite of programs over the next five years to achieve and maintain water use targets . Every year the City evaluates programs for cost - effectiveness and may discontinue certain rebate or incentive programs to be replaced with new programs to target certain water savings. The City may promote programs based on popularity or demand, for example the rain barrel rebate program will likely be promoted until funds are exhausted.
9.3.2 Evaluation of Effectiveness
Evaluating the effectiveness of a single DMM is difficult and generally not cost -effective for the City, so each program is not necessarily monitored separately for effectiveness and water savings. Evaluating the effectiveness of all DMMs collectively provides a better representation and can be translated into overall water conservation savings. The City will use countywide water savings tracked by Valley Water to evaluate the effectiveness of overall implementation efforts by both the City and Valley Water.
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City of Sunnyvale
2025 Urban Water Management Plan
SECTION 10 – Plan Adoption, Submittal, and Implementation
www.hydroscience.com
– PLAN ADOPTION, SUBMITTAL, AND IMPLEMENTATION
This 2025 UWMP and WSCP were prepared in 2025-2026 in accordance with the Guidebook .
Both plans were adopted on June 16, 2026 by City Council. This section describes the steps taken by the City to meet the requirements of the Water Code pertaining to public availability, adoption, submittal, and implementation of the 2025 UWMP and WSCP.
10.1 Inclusion of All 2025 Data
The 2025 UWMP and WSCP include all data for water use and planning for the calendar year of 2025.
10.2 60-Day Notification
The Water Code states that cities and counties must be notified that the Supplier will be reviewing the UWMP and considering amendments to the Plan. This notice must be sent at least 60 days prior to the public hearing. The City provided notices to the agencies listed below in Table 10-1.
A copy of the notification is included in Appendix A.
10.3 Notice of Public Hearing
The public hearing notice for the 202 5 UWMP and WSCP was sent to the cities and counties listed in Table 10-1 and prior to the public hearing. Three notices were posted in the Sunnyvale Sun to inform the public of the upcoming public hearing. The notices include the time and place of the hearing, as well as locations where the plans were made available for public inspection.
The first notice was published on May 15, 2026, the second on May 22, 2026, and the third on May 29, 2026. A copy of the notice is included in Appendix A.
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City of Sunnyvale
2025 Urban Water Management Plan
SECTION 10 – Plan Adoption, Submittal, and Implementation
www.hydroscience.com
Table 10-1: Notification to Cities and Counties
City Name 60 Day Notice Notice of Public Hearing
City of Hayward
City of Milpitas
City of Mountain View
City of Palo Alto
City of Santa Clara
City of Brisbane
City of Burlingame
City of Daly City
City of Menlo Park
City of Millbrae
City of Redwood City
City of San Bruno
City of East Palo Alto
City of San Jose
City of Foster City
County Name 60 Day Notice Notice of Public Hearing
Alameda County
Santa Clara County
The draft plans were made available for the community and posted on the City’s website (www.sunnyvale.ca.gov) on May 15, 2026. Copies of all public notices of the hearing are included in Appendix A.
10.4 Public Hearing and Adoption
The public hearing for consideration and adoption of the 202 5 UWMP and WSCP by the City Council took place on June 16, 2026 during a normal City Council session. The session began with the public hearing to allow community input prior to the formal adoption of both plans by City Council. All public input received was considered before final adoption of both documents. The adopted resolution is included in Appendix L.
10.5 Plan Submittal
Upon adoption of the 2025 UWMP and WSCP by City Council, implementation took place as identified in this document . Submission of the adopted plans to DWR was done electronically within 30 days from the date of adoption, and no later than July 1, 2026.
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City of Sunnyvale
2025 Urban Water Management Plan
SECTION 10 – Plan Adoption, Submittal, and Implementation
www.hydroscience.com
10.6 Public Availability
The adopted UWMP and WSCP were posted on the City’s website ( www.sunnyvale.ca.gov) within 30 days of submission to DWR and were submitted to the California State Library.
10.7 Amending an Adopted UWMP and WSCP
The City’s 2025 UWMP and WSCP will only be modified following notification, public hearing, adoption, and submittal as prescribed in the Water Code.
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2025 Urban Water Management Plan
SECTION 10 – Plan Adoption, Submittal, and Implementation
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HydroScience is a civil engineering firm that plans, designs, and manages the construction of water, wastewater, and recycled water projects. With offices in San Jose, Berkeley, and Sacramento, we understand and address the complex water and wastewater needs of Northern California.
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APPENDIX A
City of Sunnyvale
2025 Urban Water Management Plan
Postings and Notifications for UWMP and WSCP Preparation DRAFT
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CITY OF SUNNYVALE
NOTICE OF PUBLIC HEARING
The City of Sunnyvale is in the process of updating its 2025 Urban Wa8 ter Management Plan (UWMP) and Water Shortage Contingency Plan (WSCP). The City Council will conduct a public hearing and consider adoption of the 2025 UWMP and WSCP at its regularly scheduled meet8 ing on:
Tuesday, June 16, 2026, at 7 P.M. or shortly thereafter.
The meeting will be held online and in8person at the Council Chamber, City Hall, 456 W. Olive Ave., Sunnyvale, CA 94086.
In8person public comments may be provided by completing a speaker card (optional) and submitting it to the City Clerk.
Public comments may also be provided remotely by attending the tele8 conference meeting online or by telephone. To request to speak, use the Raise Hand feature (*9 by telephone):
Online meeting link: https://sunnyvale8ca8gov.zoom.us/j/96111580540 Meeting call8in telephone number: 833854880276
Meeting ID: 961 1158 0540
Written comments may be submitted by email to [email protected] a.gov no later than four hours before the meeting. Comments may also be mailed or delivered to: City Clerk, 456 W. Olive Ave., Sunnyvale, CA 94086.
An electronic copy of the draft 2025 UWMP and WSCP is available for public review on the City’s website at www.sunnyvale.ca.gov. City staff will be available at the public hearing to answer questions regarding the plan.
The final 2025 UWMP and WSCP will be posted on the City’s website and submitted to the California State Library. To request a copy of the final plan upon completion, or to provide comments on the draft, please contact:
Winola Cheong, P.E.
Deputy Director of ESD – Water and Sewer
P. O. Box 3707
Sunnyvale, CA 94088-3707
(408) 730-7763
[email protected]
Please note that parties requesting paper copies of the plan may incur associated printing costs.
SVSU 6961263 May 15, 22, 29, 2026
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APPENDIX B
City of Sunnyvale
2025 Urban Water Management Plan
City of Sunnyvale Detailed Demographic Data
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APPENDIX C
City of Sunnyvale
2025 Urban Water Management Plan
BAWSCA’s Regional Water Demand and Conservation
Projections
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Regional Water Demand
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Projections Study
Final Report
December 8, 2025
San
Francisco
Bay
Hayward
San Jose
San Mateo
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Table of Contents
Executive Summary ................................................................................................................................ ES-1
1. Introduction ........................................................................................................................................ 1-1
2. Historical Data Collection and Review .............................................................................................. 2-1
2.1 Data Sources and Collection Process....................................................................................... 2-1
2.1.1 Data Collected from Member Agencies, BAWCSA, and Santa Clara Valley Water District ........................................................................................................................ 2-1
2.1.2 Collection of External Data Sets................................................................................. 2-1
2.2 Data Processing and Standardization ....................................................................................... 2-2
2.2.1 Geographical Processing of Demographic Data ......................................................... 2-3
2.2.2 Characterization and Standardization of Water Demand Sectors ............................... 2-4
2.2.3 Derived Demographic Variables ................................................................................ 2-4
2.3 Summary of Historical Demographic and Water Use Trends ................................................. 2-5
2.3.1 Historical Demographic Data ..................................................................................... 2-5
2.3.2 Historical Water Use Data .......................................................................................... 2-7
3. Water Demand Forecasting Approach and Model Development ...................................................... 3-1
3.1 Econometric Model Design ..................................................................................................... 3-1
3.2 Summary of Econometric Model Fitting Process .................................................................... 3-3
3.3 Historical Model Performance ................................................................................................. 3-5
4. Water Conservation Analysis and Projection ..................................................................................... 4-1
4.1 Passive Water Savings Assessment ......................................................................................... 4-1
4.1.1 Baseline Fixture Stock and Efficiency Trends ........................................................... 4-1
4.1.2 Passive Water Savings Summary ............................................................................... 4-5
4.2 Active Water Conservation Program Development ................................................................ 4-6
4.2.1 Compilation of Existing Program Information ........................................................... 4-6
4.2.2 Identification of Technically Applicable Measures .................................................... 4-6
4.2.3 Addressing Uncertainty and Adaptive Management .................................................. 4-7
4.2.4 Program Water Savings .............................................................................................. 4-7
4.2.5 Cost-Effectiveness and Key Drivers ........................................................................... 4-8
4.2.6 Distribution of Program Savings by Sector ................................................................ 4-9
4.2.7 Implications for Program Prioritization .................................................................... 4-10
4.3 Water Conservation Summary ............................................................................................... 4-16
5. Baseline 2050 Water Demand Projection Scenario ........................................................................... 5-1
5.1 Selection of Base Period and Econometric Model Calibration ............................................... 5-1 DRAFT
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5.2 Scenario Definition and Assumptions ..................................................................................... 5-2
5.3 Demographic Assumptions ...................................................................................................... 5-3
5.4 Weather and Climate Assumptions.......................................................................................... 5-5
5.5 Assumptions for Economic Variables ..................................................................................... 5-7
5.6 Conservation and Pricing Assumptions ................................................................................... 5-7
5.6.1 Future Water Prices .................................................................................................... 5-8
5.7 NRW and Other Water Use Assumptions ............................................................................... 5-8
5.8 Baseline Forecast Results ........................................................................................................ 5-8
5.8.1 Sectoral Forecasts without Additional Conservation .................................................. 5-9
5.8.2 Regional Forecasts Including Conservation ............................................................. 5-10
5.9 Total Forecasts by Member Agency ...................................................................................... 5-11
6. Urban Water Use Objective (UWUO) ............................................................................................... 6-1
6.1 Regulatory Context .................................................................................................................. 6-1
6.2 Methodology and Assumptions for Estimating UWUO .......................................................... 6-3
6.2.1 Net Reference Evapotranspiration (Net ETo) Projections .......................................... 6-4
6.2.2 Existing CII DIMs LAM Projections ......................................................................... 6-5
6.2.3 Other Assumptions and Considerations for UWUO Projections ................................ 6-6
6.3 Comparison of Projected Water Demands with the Estimated UWUO .................................. 6-8
7. Analysis of Alternative Forecast Scenarios ....................................................................................... 7-1
7.1 Scenario Development Process ................................................................................................ 7-1
7.2 Alternate Scenario Assumptions .............................................................................................. 7-3
7.2.1 Demographic and Development ................................................................................. 7-3
7.2.2 Socioeconomic Conditions ......................................................................................... 7-5
7.2.3 Conservation and Pricing ............................................................................................ 7-6
7.2.4 Climate Change .......................................................................................................... 7-7
7.2.5 New High Water Users – Data Centers ...................................................................... 7-8
7.2.6 Consolidated Scenario Assumptions ........................................................................ 7-11
7.3 Alternate Scenario Results ..................................................................................................... 7-13
8. Summary and Recommendations ....................................................................................................... 8-1
8.1 Recommendations for Future Analyses and Studies ............................................................... 8-2
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List of Tables
Table ES-1: Summary of Historical Data Collected for Model Development ....................................... ES-3 Table 2-1: Summary of Historical Data Collected for Model Development ............................................. 2-2 Table 2-2: Summary of Standardized Water Use Sectors Used for Demand Model Development .......... 2-4 Table 2-3: Summary of Derived Demographic Explanatory Variables ..................................................... 2-5 Table 3-1: Summary of Collected Explanatory Variables ......................................................................... 3-3 Table 3-2: Summary of Econometric Model Fitting Process ..................................................................... 3-4 Table 4-1: SF Fixture Stock Distribution by Technology Tier (2025 and 2050) ....................................... 4-4 Table 4-2: MF Fixture Stock Distribution by Technology Tier (2025 and 2050) ..................................... 4-4 Table 4-3: CII Toilet & Urinal Efficiency Distribution by Technology Tier (2025 and 2050) ................. 4-5 Table 4-4: Additional Annual Passive Savings Estimates by Sector, MGD .............................................. 4-5 Table 4-5: Portfolio of Single-Family Program Active Water Savings and Unit Costs (2050) ............... 4-12 Table 4-6: Portfolio of Multifamily Program Active Water Savings and Unit Costs (2050) .................. 4-13 Table 4-7: Portfolio of CII Program Active Water Savings and Unit Costs (2050) ................................ 4-14 Table 4-8: Portfolio of Irrigation Program Active Water Savings and Unit Costs (2050) ...................... 4-14 Table 4-9: Portfolio of Education Program Water Savings and Unit Costs (2050) ................................. 4-15 Table 5-1: Summary of Calibration Factors .............................................................................................. 5-1 Table 5-2: Summary of Baseline Scenario Assumptions ........................................................................... 5-2 Table 5-3: Average Annual Maximum Temperature Increases in 2050 (Relative to 2025) Derived from CalAdapt CMIP5 RCP 4.5 and RCP 8.5 ......................................................................................... 5-6 Table 5-4: Baseline Forecast Including Passive and Active Conservation .............................................. 5-11 Table 5-5: Total Baseline Forecast Without Additional Conservation by Member Agency ................... 5-12 Table 5-6: Total Baseline Forecast with Passive Conservation by Member Agency .............................. 5-13 Table 5-7: Total Baseline Forecast with Passive and Active Conservation by Member Agency ............ 5-14 Table 6-1: Residential Indoor Water Use Standards and Compliance Timeline ....................................... 6-3 Table 6-2: Residential Outdoor Landscape Efficiency Factors and Compliance Timeline ....................... 6-3 Table 6-3: CII with DIMs Landscape Efficiency Factors and Compliance Timeline ............................... 6-3 Table 6-4: UWUO Budget Components, Inputs, Regulatory Equations, and Estimation Methodologies 6-7 Table 7-1: Alternate Scenario Demographic and Development Data Sources and Assumptions .............. 7-3 Table 7-2: Summary of Regional GDP and Unemployment Scenario Assumptions ................................ 7-5 Table 7-3: Projected Data Center Water Use (MGD) for “High” Scenario Reflecting 0.2 L/kWh WUE ... 7- 11 Table 7-4: Consolidated Summary of Scenario Assumptions ................................................................. 7-12 Table 7-5: Tabular Comparison of Water Demand Scenarios (MGD) .................................................... 7-13
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List of Figures
Figure ES-1: Overview of Water Demand Projection Framework ............................................................... 2 Figure 2-1: Example of TAZ Tract Overlapping an Adjacent Member Agency Service Areas ................ 2-3 Figure 2-2: Historical Regional Population ............................................................................................... 2-6 Figure 2-3: Historical Regional SF and MF Housing Units ...................................................................... 2-6 Figure 2-4: Historical Regional Job Totals ................................................................................................ 2-7 Figure 2-5: Historical Water Consumption (Excludes NRW) ................................................................... 2-8 Figure 3-1: Overall Water Demand Modeling Approach .......................................................................... 3-1 Figure 3-2: General Iterative Process for Developing Econometric Models ............................................. 3-4 Figure 3-3: Regional Average SF Observed and Predicted Rate of Use ................................................... 3-6 Figure 3-4: Scatterplot Illustrating Monthly Observed SF Water Use vs. Historical Model Predictions .. 3-6 Figure 3-5: Regional Average MF Observed and Predicted Rate of Use .................................................. 3-7 Figure 3-6: Scatterplot Illustrating Monthly Observed MF Water Use vs. Historical Model Predictions . 3-7 Figure 3-7: Regional Average CII Observed and Predicted Rate of Use................................................... 3-8 Figure 3-8: Scatterplot Illustrating Monthly Observed CII Water Use vs. Historical Model Predictions . 3-8 Figure 3-9: Regional Average Irrigation Observed and Predicted Rate of Use ......................................... 3-9 Figure 3-10: Scatterplot Illustrating Monthly Observed Irrigation Water Use vs. Historical Model Predictions ....................................................................................................................................... 3-9 Figure 3-11: Scatterplot Illustrating Monthly Observed Recycled Water Use vs. Historical Model Predictions ..................................................................................................................................... 3-10 Figure 5-1: Historical and Projected Regional Population ........................................................................ 5-4 Figure 5-2: Historical and Projected Regional Housing Units ................................................................... 5-4 Figure 5-3: Historical and Projected Regional Jobs ................................................................................... 5-5 Figure 5-4: Example Modeled Annual Precipitation in Santa Clara County Under Future Climate Change Conditions........................................................................................................................................ 5-6 Figure 5-5: Baseline Sectoral Forecast Without Additional Conservation ................................................ 5-9 Figure 5-6: Baseline Forecast Including Passive and Active Conservation ............................................. 5-11 Figure 6-1: Regulatory Formulation of UWUO......................................................................................... 6-2 Figure 6-2: Example UWUO Projection Envelope based on High and Low Net ETo values ................... 6-5 Figure 7-1: Comparison of Regional Population Scenarios ....................................................................... 7-4 Figure 7-2: Comparison of Regional Housing Units Scenarios ................................................................. 7-4 Figure 7-3: Comparison of Regional Job Scenarios .................................................................................. 7-5 Figure 7-4: 2050 Passive Savings by Sector .............................................................................................. 7-6 Figure 7-5: Annual Change in Water Rates in Real Terms ....................................................................... 7-7 Figure 7-6: CEC Annual Energy Use Projections for Data Centers, Organized by Power Utility ............ 7-9 Figure 7-7: Estimated Total Annual Data Center Energy Use in BAWSCA Service Area Inferred from CEC Projections ............................................................................................................................ 7-10 Figure 7-8: Projected Data Center Water Use Organized by Assumed WUE ......................................... 7-11 Figure 7-9: Graphical Comparison of Water Demand Scenarios ............................................................ 7-13
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List of Appendices
Appendix A: Procedure for Reprojecting Demographic Data Appendix B: Monthly and Bimonthly Smoothing Procedure
Appendix C: Estimated Model Coefficient Ranges
Appendix D: Summary of Econometric Model Fits
Appendix E: Supplementary Conservation Tables
List of Acronyms
Abbreviation Definition
AB Assembly Bill
ACS American Community Survey (US Census)
AFY Acre-Feet per Year
AMI Advanced Metering Infrastructure
AWE Alliance for Water Efficiency
AWE Tracking Tool Alliance for Water Efficiency Tracking Tool BAWSCA Bay Area Water Supply and Conservation Agency
CALGreen California Green Building Standards Code (Title 24, Part 11) CEC California Energy Commission
CII Commercial, Industrial, and Institutional
CMIP5/CMIP6 Coupled Model Intercomparison Project Phase 5/6 COVID Coronavirus Disease (context: pandemic indicator) DIM Dedicated Irrigation Meter
DOF California Department of Finance
DWR Department of Water Resources (California)
EPACT Energy Policy Act (US federal law)
FRED Federal Reserve Economic Data
GCM Global Climate Model
GDP Gross Domestic Product
GIS Geographic Information System
HET High-Efficiency Toilet
HOA Homeowners’ Association
INR Indoor Residential (context: water use)
KAF Thousand Acre-Feet
LAM Landscape Area Measurement
LEF Landscape Efficiency Factor
LEHD Longitudinal Employer-Household Dynamics
LODES Origin-Destination Employment Statistics
MF Multifamily (housing units or residential sector)
MG Million Gallons
MGD Million Gallons per Day
NAICS North American Industry Classification System
Net ETo Net Reference Evapotranspiration
NRW Non-Revenue Water
OUTR Outdoor Residential (context: water use)
PG&E Pacific Gas and Electric Company
PPH Persons per Household
PRISM Parameter-elevation Regressions on Independent Slopes Model QWEL Qualified Water Efficient Landscaper
RCP Representative Concentration Pathway (climate scenario) RLA Residential Landscape Area
RSAT Residential Self-Audit Tool
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Abbreviation Definition
SB Senate Bill
SB X7-7 Senate Bill X7-7 (California Water Conservation Act) SF Single Family (housing units or residential sector)
SLA Special Landscape Area
SMUD Sacramento Municipal Utility District
SSP Shared Socioeconomic Pathway (climate scenario)
SVP Silicon Valley Power
TAZ Traffic Analysis Zone
Title 20 California Appliance Efficiency Regulations
UHET Ultra-High-Efficiency Toilet
ULFT Ultra-Low-Flush Toilet
UWMP Urban Water Management Plan
UWUO Urban Water Use Objective
WF Water Factor (for appliances)
WUE Water Usage Effectiveness
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Executive Summary
The Bay Area Water Supply and Conservation Agency (BAWSCA) and its 26 member agencies face a dynamic and challenging water future, shaped by population growth, climate change, regulatory requirements, and evolving patterns of water use. This report presents a comprehensive regional water demand and conservation analysis, providing a robust foundation for long-term planning and strategic decision-making through 2050.
The primary objective of the Regional Water Demand and Conservation Projections Study (2025 Demand Study or Project) was to deliver updated, agency-specific water demand forecasts and conservation assessments to support the 2025 Urban Water Management Plan (UWMP) cycle and align with BAWSCA’s Long-Term Water Supply Reliability Strategy (Strategy 2050) initiative. The effort integrated socioeconomic and demographic data collection, econometric modeling, and conservation program evaluation to forecast water demand across major water use sectors and customer classifications.
The demand projections presented in this report were developed for the specific purpose of this Project, utilizing a single, standardized set of planning assumptions. These assumptions were collaboratively agreed upon by the member agencies solely for the uniform analysis conducted herein.
It is important to note that as individual member agencies develop their own unique, official planning documents for their own purposes, including regulatory compliance (e.g., UWMPs), their internal decision-making processes may necessitate the use of different assumptions, methodologies, or policy considerations, which may differ from the illustrative estimates unique to this specific project.
Furthermore, agencies often do not consider any demand projections finalized until they have been formally reviewed and adopted by their respective Council or Board. For the most current and officially adopted demand projections, please consult the corresponding member agency's planning documents.
Demand Projection Approach
The Project employed a hybrid water demand modeling framework (illustrated in Figure ES-1) that integrates econometric regression techniques with end-use conservation accounting. This approach allows for a clear separation between the structural factors influencing water demand – such as demographic changes, climate variability, and economic trends – and the impacts resulting from policy decisions and conservation programs.
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Figure ES-1: Overview of Water Demand Projection Framework The econometric models describe the influence of key explanatory variables on historical water demand; these explanatory variables include weather conditions, the price of water, regional macroeconomic conditions, socioeconomic factors, long-term trends in passive conservation savings, and historical drought restrictions. The models forecast future water demand based on projected scenarios that define the values of the same explanatory variables. The baseline water demand scenario as well as additional scenarios that help bound future uncertainty are further described below.
Separate to econometric modeling, the Project explicitly quantified both passive conservation impacts, driven by codes and regulations, and future active conservation impacts, resulting from programmatic initiatives and behavioral changes. Passive and active conservation savings were estimated using an end use accounting framework via the Alliance for Water Efficiency Tracking Tool (AWE Tracking Tool).
The Project concluded with scenario analyses to address uncertainties inherent in long-term planning. The scenarios examined demographic shifts different from those presented in the baseline, unforeseen economic fluctuations, climate variability, and the prevalence of demand sectors with highly uncertain growth and water use rates (e.g., data centers). These scenario analyses provide valuable insights into the range of possible future outcomes and support informed decision-making for regional water supply planning. Five scenarios in addition to the baseline were considered, establishing both “high” and “low” bookends of projected water demand based on differences in underlying model assumptions.
Baseline Scenario Water Demand Projections
The baseline scenario was developed through close collaboration with BAWSCA member agencies and is grounded in the following key assumptions:
• Demographics: Future population, housing units, and jobs were based on Plan Bay Area 2050 growth rates, with adjustments from member agency planning departments to reflect local realities.
• Climate: Future temperatures were adjusted using annual average projections from CalAdapt CMIP5 RCP 8.5 modeling, while precipitation was held at historical averages.
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• Economy: The mix of industries, regional rates of change in GDP, and unemployment rates were assumed to remain constant at recent historical levels. • Conservation: Passive conservation (fixture and appliance turnover, new construction standards) was assumed to continue steadily into the future, while active conservation programs were assumed to be implemented based on plans discussed and reviewed by member agencies.
• Water Pricing: Water rates are assumed to keep pace with inflation, resulting in no real change in price over the planning horizon, except for agencies that provided approved future rate increases.
• Non-Revenue Water and Other Uses: Held constant at recent observed levels.
Under these conditions, regional water demand is projected to increase gradually over the planning period, moderated by ongoing conservation efforts and efficiency improvements. The forecasted total demand (all sectors, including passive and active conservation) is presented in Table ES-1 below.
Table ES-1: Summary of Baseline Regional Water Demand Forecast Assumption 2025 2030 2035 2040 2045 2050
Regional Demand
without Additional
Conservation (mgd)
190 203 212 220 228 237
Passive and Active
Conservation (mgd) 1 6 10 12 14 16
Total Regional Demand 189 197 202 208 213 220
The projections reflect a modest but steady increase in demand, primarily driven by demographic growth, with conservation programs offsetting what would otherwise be higher increases.
Alignment with Expected Urban Water Use Objectives
The Project also evaluated each member agency’s baseline projected water use, including passive and active conservation, against the State’s Urban Water Use Objective (UWUO) regulatory standards through 2050. The results illustrate that the majority of BAWSCA member agencies are expected to remain in compliance with their UWUOs throughout the planning period. With both passive and active conservation in place, only 4 out of 23 agencies are projected to exceed their UWUO at any point between 2025 and 2050. This demonstrates that, under baseline assumptions, the region is generally well- positioned to meet regulatory efficiency requirements, though a small number of agencies may need to consider additional measures or targeted strategies in future years.
Addressing Uncertainty
The Project attempted to address future uncertainty in water demands through a scenario analysis informed through coordination with member agency representatives, external stakeholders, and the San Francisco Public Utilities Commission (SFPUC). The scenario analysis aimed to demonstrate how variations in demographic, economic, climate, pricing, and conservation assumptions influence regional DRAFT
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water demand trajectories through 2050. Five scenarios were developed that reflected a range of plausible regional narratives. Key findings from the analysis included the following:
• Demographics are the dominant factor shaping long-term demand. • Pricing and conservation assumptions, particularly rate increases over inflation and additional conservation programming can exert off-setting (downward) pressures on demand. • High-water-use customers (e.g., data centers) can introduce localized risk under high-growth futures.
By 2050, volumetric demand differences between High and Low scenarios exceed 30% (264 mgd on the high end and 155 mgd on the low end), underscoring the potential impact of uncertainties in planning assumptions.
Future Analyses and Next Steps
The report identifies several recommendations to improve monitoring, tracking, and understanding water demands as key drivers evolve in the future, including:
• Monitor Emerging High-Use Sectors: Establish ongoing tracking of data centers and other large water users and explore incorporating energy consumption as a driver in future econometric models.
• Consider Future Droughts in Scenario Planning: Expand scenario analysis to include severe drought conditions and test rebounds from future droughts, integrating lessons from recent events.
• Consider Optimization of Conservation Measures: Conservation modeling suggests that member agencies could further optimize their active conservation programming by prioritizing investment in lower cost-per-gallon-saved programs.
• Continuous Model Improvements: Maintain clear documentation, continue annual data collection from member agencies, and regularly refine model structure and assumptions to reflect new trends in development and other drivers.
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1. Introduction
Background and Context
The Bay Area Water Supply and Conservation Agency (BAWSCA) plays a critical role in ensuring reliable, high-quality water supply for 26 member agencies serving over 1.8 million residents, businesses, and communities throughout the San Francisco Bay Area. BAWSCA’s represents the collective interests of its member agencies in regional water planning, supply reliability, and conservation, while supporting local agencies’ efforts to meet both current and future water needs. As the region faces increasing pressures from population growth, climate change, regulatory requirements, and evolving water use patterns, proactive and data-driven planning has become increasingly essential.
Project Scope
This report presents the results of the Regional Water Demand and Conservation Projections Project (Project) conducted for BAWSCA and its member agencies. The Project encompasses the development of updated, agency-specific water demand forecasts through 2050, using a robust modeling framework that integrates socioeconomic and demographic data collection, econometric analysis, and conservation program evaluation. The analysis covers the major customer sectors that make up municipal water demands—single family, multifamily, commercial/industrial/institutional, irrigation, and recycled water—and explicitly quantifies both passive (code-driven) and active (programmatic) conservation impacts.
The demand projections presented herein are based on a single, standardized set of assumptions developed exclusively for the analytical scope of this Project. These figures are not the official planning forecasts for any individual member agency, which may differ from the illustrative estimates unique to this specific project.
Agencies maintain the authority to develop and adopt their own distinct projections (e.g., in their UWMPs) based on independent internal processes and assumptions. Final, official demand projections must be obtained directly from the corresponding member agency's adopted planning documents.
Project Objectives and Alignment with Regional Planning Efforts The primary objectives of the Project were to:
• Provide scenario-ready forecasts of regional and agency-level water demand through 2050; • Quantify the impacts of ongoing and planned conservation measures; • Support member agencies in meeting the requirements of the 2025 Urban Water Management Plan (UWMP) cycle, including compliance with new regulatory standards such as the Urban Water Use Objective (UWUO); and
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• Align demand forecasting and conservation planning with BAWSCA’s Long-Term Reliable Water Supply Strategy (Strategy 2050) initiative, which is conducting parallel scenario analyses to assess long-term water supply reliability and inform regional investment decisions.
By integrating demand-side analysis with the broader Strategy 2050 effort, the Project ensures that BAWSCA and its member agencies are equipped to evaluate a range of plausible futures, identify potential risks and opportunities, and make informed, adaptive decisions to secure the region’s water future.
Structure of the Report
The report is organized in the following main sections:
• Historical Data Collection and Review: Overview of data sources, coordination with member agencies, and data processing methods.
• Water Demand Forecasting Approach and Model Development: Description of the modeling framework, particularly the econometric methods. • Water Conservation Analysis and Projection: Overview of the Project’s conservation modeling, analysis, and projections.
• Baseline 2050 Water Demand Projection Scenario: Presentation of baseline assumptions, forecast results, and sectoral/regional breakdowns.
• Urban Water Use Objective (UWUO): Description of the methodology for projecting member agencies’ UWUO out to 2050 and summary of expected compliance under the baseline scenario.
• Analysis of Alternative Forecast Scenarios: Exploration of alternative futures, including demographic, economic, climate, and policy uncertainties. • Summary and Recommendations: Summary of findings, recommendations for future analyses, and strategic linkages to ongoing initiatives. • Appendices: Supporting data, technical details, and additional documentation.
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2. Historical Data Collection and Review
This section documents the historical data collection process for the Project, including coordination with the member agencies, and overview of the data collected, and a review of key data processing exercises.
This section also documents historical demographic and water consumption trends for the region. Future demographic projections, which are key drivers of future water demand, are further documented in Section 5, which describes baseline assumptions of future conditions, and Section 7, which presents alternative scenario assumptions.
2.1 Data Sources and Collection Process
Development of econometric and end-use accounting models is a highly data intensive process that requires a robust historical dataset consisting of water consumption, demographic data, and explanatory variables used to explain variability in water use. This section summarizes the data sources collected in support of the Project’s modeling effort.
2.1.1 Data Collected from Member Agencies, BAWCSA, and Santa Clara Valley Water District
Historical records of billed consumption and accounts are perhaps the most important data for developing water demand models. In support of this effort, member agency-specific billing and consumption records from 1980 to 2020 were made available from prior demand studies. This historical data was supplemented with an additional request from member agencies to collect updated data for the years 2020-2023.
Additional data, including historical water rates, water shortage history, and conservation program information were also provided by member agencies and supplemented with additional context and data from BAWSCA and Santa Clara Valley Water District (Valley Water).
Following this initial data collection, the project team reviewed member agency data and identified inconsistencies (e.g., billing records agencies reported monthly that appeared to be bimonthly) and coordinated with agency staff through emails and phone calls regarding the data.
2.1.2 Collection of External Data Sets
Additional data gathered for the Project encompassed a comprehensive array of demographic, socioeconomic, and climatic information relevant to the region. Table 2-1 presents a summary of the primary external data sources, which are not directly produced by BAWSCA or its member agencies.
These data mainly served as explanatory variables, either directly or through derivation, in the Project’s econometric models.
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Table 2-1: Summary of Historical Data Collected for Model Development Explanatory Variable Years
Collected
Data Sources
Population
2000-2023
California Department of Finance (DOF) annual jurisdictional dataset1 and US Census American Community Survey (ACS)2 Single Family (SF) housing
units3 DOF and member agency account data Multifamily (MF) housing units4
Employment by North
American Industry
Classification System
(NAICS) Sector
2002-2022
U.S. Census Bureau Longitudinal Employer-Household
Dynamics (LEHD) Origin-Destination Employment Statistics (LODES) dataset5. The LODES dataset provides annual,
geographically detailed estimates of where people work and live, including job counts by industry sector at the census block or tract level, enabling analysis of employment patterns and economic activity within specific service areas.
Observed weather (monthly
precipitation, monthly
maximum temperature)
2000-2023 Gridded historical climate data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM)6
Regional real Gross
Domestic Product (GDP) 2002-2021 Federal Reserve Economic Data (FRED) database7 Regional unemployment rate
Median income 2000-2023 US Census ACS
Land use and zoned area
measurements 2023 California Geoportal General Plan Landuse Dataset8
2.2 Data Processing and Standardization
Prior to utilizing demographic and water use data for modeling and analysis, the data were subjected to multiple processing and standardization procedures. This section outlines the reasons for these steps and describes the general methods applied.
1 California Department of Finance (DOF). Population and Housing Estimates for California Cities, Counties, and the State: E-8 Historical Estimates (1990–2000; 2000–2010; 2010–2020) and E-1 Annual Estimates (2021–2023). Sacramento, CA: DOF, 2001, 2012, 2023, and May 2024.
2 U.S. Census Bureau. “American Community Survey 5-Year Estimates 2009–2022.” ACS 5-Year Summary File, December 2024 edition.
3 SF housing units are generally equivalent in number to single-family accounts. 4 Differences between member agency single-family account data and DOF single-family housing units were reallocated to multi- family housing units to preserve the total housing units. 5 U.S. Census Bureau, Longitudinal-Employer Household Dynamics (LEHD) Program. (2024). LEHD Origin-Destination Employment Statistics (LODES), 2002–2022 [Dataset]. Retrieved from https://lehd.ces.census.gov/data/#lodes 6 PRISM Climate Group, Oregon State University. (2025). PRISM climate data: maximum temperature (Tmax) and precipitation, 2000–2023 [Dataset]. https://prism.oregonstate.edu
7 U.S. Bureau of Economic Analysis & U.S. Bureau of Labor Statistics. (2022). Real gross domestic product (GDPC1) and civilian unemployment rate (UNRATE), 2000–2021 [Data sets]. FRED, Federal Reserve Bank of St. Louis. Retrieved from https://fred.stlouisfed.org
8 California Office of Planning and Research (OPR). (2025). California General Plan Land Use [GIS dataset]. State of California Geoportal. Retrieved from https://gis.data.ca.gov/datasets/Gov-OPR::california-general-plan-land-use DRAFT
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2.2.1 Geographical Processing of Demographic Data
Key demographic information necessary for water demand forecasting—such as population, employment figures, and housing units—must align with the boundaries of each member agency's service area.
Historical and projected records for these data (via DOF and Plan Bay Area 2050) are available at jurisdictional, census tract, and/or Traffic Analysis Zone (TAZ) geographical boundaries, which often do not directly align with member agency service area boundaries. This concept is illustrated in Figure 2-1 below. All demographic data utilized in the Project was reprojected to member agency service area boundaries using a GIS-based allocation procedure, further documented in Appendix A.
Figure 2-1: Example of TAZ Tract Overlapping an Adjacent Member Agency Service Areas
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2.2.2 Characterization and Standardization of Water Demand Sectors Member agencies provided billing and account data organized by their internal billing classifications.
There were 93 unique billing classifications across all member agencies. Residential billing classifications (SF and MF) were generally consistent across member agencies. The City of East Palo Alto, City of San Bruno, and the Town of Hillsborough were the only agencies with a single residential billing classification. Non-residential billing classifications were less consistent across member agencies. While most agencies defined a commercial billing classification, the distinction and definition of industrial, institutional, and irrigation (i.e., landscape) classes were inconsistent across the member agencies.
In order to develop consistent water demand models across the region and to align with water conservation program categories defined in the AWE Tracking Tool (see Section 4), it was necessary to standardize member agency classifications to a consolidated set of water demand sectors. Table 2-2 summarizes the consolidated water use sectors used for model development and projection.
Table 2-2: Summary of Standardized Water Use Sectors Used for Demand Model Development Model Sector Description
SF Water use associated with SF residential homes.
MF Water use associated with MF residential properties.
Commercial, Industrial, and Institutional (CII) Water use associated with all CII activity.
Dedicated irrigation (potable)
Water use associated with separately metered outdoor
irrigation. Typically non-residential, but occasionally inclusive of common multifamily landscaped area
and/or Homeowners’ Associations (HOAs).
Recycled and raw water
Water use associated with current recycled and raw
water use. Typically non-residential irrigation, but
occasionally inclusive of some CII process water
consumption, and common multifamily landscaped
area and/or Homeowners’ Associations (HOAs).
Other
Other water use, often categorized as “other” by retail agencies, but also inclusive of classifications not well represented by the standardized water use sectors
above (e.g., construction, fire line, miscellaneous).
Other water use does not include nonrevenue water
(NRW).
In addition to standardizing water use sectors, member agency consumption data needed to be “smoothed” in order to standardize for consumption billed on monthly and bimonthly cycles. This exercise is necessary prior to statistical analysis and econometric model fitting to ensure that actual monthly consumption is accurately represented. Appendix B provides more detailed mathematical documentation of the smoothing approach applied.
2.2.3 Derived Demographic Variables
Several additional demographic explanatory variables were derived from the datasets identified in Table 2-2. These data are summarized in Table 2-3 below.
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Table 2-3: Summary of Derived Demographic Explanatory Variables Derived Explanatory Variable Description
Persons per household (PPH)
Calculated as the total population by housing type (SF or MF) divided by the total number of households. Unique PPH values were calculated for each member agency annually between 2000-2023.
Housing density
Derived from housing units (SF and MF) estimated for each member agency divided by zoned SF or MF residential area obtained from the California Geoportal General Plan Landuse Dataset.
Mix of industries / economic activity
Reflects the proportional number of jobs in each NACIS sector documented within the LODES dataset relative to overall employment. Calculated for each NACIS sector and member agency service area.
Housing units and jobs per account
• SF accounts reflect a 1-1 ratio with housing units.
• MF housing units per account were calculated by dividing the number of housing units by recorded number of accounts.
• CII jobs per account were calculated by dividing the number of jobs within a service area by the total number of CII accounts.
2.3 Summary of Historical Demographic and Water Use Trends This section provides a summary of the historical demographic and water use trends within the overall BAWSCA region.
2.3.1 Historical Demographic Data
Figures 2-2 through 2-4 illustrate regional historical trends in population, housing unit development, and job growth from 2000-2023. These data reflect historical jurisdictional DOF data, reprojected to member agency service area boundaries using the approach defined in Section 2.2.1, and aggregated to the overall BAWSCA service area. Historical population, housing units, and job data were validated by comparing to prior BAWSCA water demand study estimates, member agencies 2020 UWMPs, and through discussions with member agency representatives.
Between 2000 and 2023, the BAWSCA service area experienced steady population growth, moderate housing expansion, and employment increases, reflecting broader regional economic and urbanization trends. Population rose from approximately 1.57 million in 2000 to about 1.80 million in 2023, an increase of roughly 14%, with most growth occurring after 2010 following a period of relative stability in the early 2000s. Housing units also expanded, with single-family units increasing from about 317,000 in 2000 to roughly 360,000 by 2023, though growth was uneven, with notable acceleration during the mid- 2010s. The trend illustrates a gradual shift toward higher-density development, as multifamily housing grew at a faster rate than single-family units in recent years. Employment trends tend to mirror population growth, with job counts rising steadily across the period, driven by technology and service sectors, although the data indicate some volatility during economic downturns such as the 2008 recession and the COVID-19 pandemic.
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Figure 2-2: Historical Regional Population
Figure 2-3: Historical Regional SF and MF Housing Units
1,567,233
1,638,670
1,792,529
1,801,844
1,400,000
1,450,000
1,500,000
1,550,000
1,600,000
1,650,000
1,700,000
1,750,000
1,800,000
1,850,000
2000 2005 2010 2015 2020
Population
317,225
348,084 358,955 360,181
221,396
266,554
307,293
330,048
0 50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
2000 2005 2010 2015 2020
Housing Units
Historical SF Units Historical MF Units
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Figure 2-4: Historical Regional Job Totals
2.3.2 Historical Water Use Data
Historical water consumption9 in the region for the primary water use sectors identified in Table 2-2 are presented in Figure 2-5 on the following page. Figure 2-5 illustrates that total water use across the BAWSCA service area has fluctuated significantly from 2000 through 2023, shaped by economic cycles, conservation programs, and climatic conditions. Demand peaked in the mid-2000s before declining during the 2008–2010 recession and again during the 2014–2016 drought, when mandatory restrictions and heightened conservation awareness drove sharp reductions in use. Following these events, water demand rebounded modestly but remained below early-2000s levels, signaling a structural shift toward lower per-capita consumption due to ongoing efficiency improvements and potential behavioral changes.
The COVID-19 pandemic in 2020 introduced a temporary shift in water use patterns: residential demand increased as more people stayed home, while CII use declined due to widespread closures. Effects of the COVID-19 pandemic overlapped with the most recent drought and resulted in a net decrease in overall demand, reinforcing the sensitivity of water use to socio-economic disruptions and temporary water use restrictions.
9 Consumption excludes NRW.
940,207 897,092
1,146,543
1,123,173
0 200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
2000 2005 2010 2015 2020
Jobs
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Figure 2-5: Historical Water Consumption (Excludes NRW)
229 224
214
176
195
173
0 50
100
150
200
250
300
2000 2005 2010 2015 2020 2023
Water Consumption (mgd)
Single Family Multifamily CII Irrigation Recyled Other
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3. Water Demand Forecasting Approach and Model Development BAWSCA’s updated water demand forecasting framework produces agency‑specific, monthly projections of water demand by explicitly linking drivers (households, accounts, jobs) and explanatory variables (weather, price, demographics, economy) to observed water use. The generalized approach (Figure 3-1) is a “hybrid” methodology that combines econometric regression for representing historical variability in water demand with an end‑use conservation toolset to reflect passive code‑driven efficiency and evaluate future active conservation programming. The approach was designed to be “scenario ready” as model inputs and assumptions are straightforward to change to reflect alternate future conditions. This section provides a brief overview of the econometric model approach. The end use accounting conservation module is further discussed in Section 4.
Figure 3-1: Overall Water Demand Modeling Approach
3.1 Econometric Model Design
Member agency demand for any sector is calculated as the product of “driver units” and a corresponding rate of use. Driver units reflect the scale of growth over time while the rate of use reflects the intensity of water use. The rate of use framework is an important concept in water demand forecasting because it decouples growth in customers from behavioral/technology effects on per‑unit use. Equation 3-1 below provides a mathematical representation of this concept:
𝑄𝑎,𝑠,𝑚 = 𝑁𝑎,𝑠,𝑚 ∗ 𝑞𝑎,𝑠,𝑚 (3-1)
Where Q is total consumption for agency a, water use sector s, and month m; N are the driver units (e.g., accounts); and q is the rate of use per account. For this analysis, an econometric approach is used to estimate the rate of use per account, q, using a set of linear regression equations that explain historical rates of water use as a function of several weather, socioeconomic, and other explanatory variables.
Linear regression produces the coefficients applied to each explanatory variable to closely reproduce the historical rate of use per driver unit. Equation 3-2 shows an example linear regression for single family water use, where the price of water and temperatures are example, and only a subset of possible, explanatory variables.
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𝐻𝑖𝑠𝑡𝑜𝑟𝑖𝑐𝑎𝑙 𝑆𝑖𝑛𝑔𝑙𝑒 𝐹𝑎𝑚𝑖𝑙𝑦 𝑈𝑠𝑒
𝑆𝑖𝑛𝑔𝑙𝑒 𝐹𝑎𝑚𝑖𝑙𝑦 𝐴𝑐𝑐𝑜𝑢𝑛𝑡 = 𝐶𝐼𝑛𝑡𝑒𝑟𝑐𝑒𝑝𝑡 + 𝐶𝑅 × 𝐻𝑖𝑠𝑡𝑜𝑟𝑖𝑐𝑎𝑙 𝑃𝑟𝑖𝑐𝑒 𝑜𝑓 𝑊𝑎𝑡𝑒𝑟 + 𝐶𝑇 × 𝐻𝑖𝑠𝑡𝑜𝑟𝑖𝑐𝑎𝑙 𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒𝑠 + …
(3-2)
A key feature of the econometric approach applied to the Project was to implement a “panel” regression methodology to model the rate of water use. Panel regression is a statistical method for analyzing data that combines both cross-sectional data (e.g., geographical data specific to member agencies, such as weather or housing density) and time-series data (e.g., observations of water consumption over multiple time periods). Panel regression is generally preferred to fitting independent models for each agency in isolation, as the approach improves statistical power, supports agencies with shorter or noisier billing records, and allows inclusion of important explanatory variables that vary more across geography than time (e.g., persons‑per‑household, housing density).
A key feature of the econometric approach is a “panel” regression methodology that models the rate of water use (q). Panel regression is a statistical method for analyzing data that combines both cross- sectional data (e.g., geographical data specific to member agencies, such as weather or housing density) and time-series data (e.g., observations of water consumption over multiple time periods). Panel regression is generally preferred to fitting independent models for each agency in isolation, as the approach improves statistical power, supports agencies with shorter or noisier billing records, and allows inclusion of important explanatory variables that vary more across geography than time (e.g., persons‑per‑household, housing density). A prerequisite of applying a panel regression approach was to have consistent definitions of water use types across member agencies, which were established in Table 2-2. Note that other water uses (defined in Table 2-2) were not modeled econometrically and were projected using a recent average of historical consumption.
Econometric models of historical per account water use were developed using a set of explanatory variables that meet the following set of criteria and are further defined in Table 3-1:
• Logical causal relationship with historical changes in water consumption (note the relevance and relationships articulated in Table 3-1, Column 2):
• Available historical record consistent with the time series of observed water consumption and accounts; and
• Availability of future projections consistent with the Project forecast horizon (i.e., 2025-2050) or a reasonable basis for deriving or assuming future projected values.
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| Water Demand Forecasting Approach and Model Development 3-3 Table 3-1: Summary of Collected Explanatory Variables
Explanatory Variable Relevance to Water Consumption
Monthly / Seasonal Pattern Reflects average fluctuations of water consumption consistent with the seasons (e.g., water use tends to be larger in the summer than in the winter).
Temperature10 Higher temperatures are associated with higher demands.
Precipitation11 Higher precipitation is associated with lower demands.
Price of Water Economic theory suggests that demand for water decreases as price increases.
Regional GDP
Water demand is positively correlated with regional economic output. An index reflecting departures in Regional GDP from long-term trend was considered in this study.
Average Unemployment Rate
Higher rates of unemployment are associated with lower rates of consumption independent of GDP, which includes the integration of labor, capital, and technology.
Housing Density Housing density is negatively correlated with demand. Residences with smaller lot sizes tend to use less water for outdoor uses.
Persons per Household Residences with more people tend to use larger amounts of water.
Mix of Industries / Economic
Activity
CII sector water use is linked to the distribution of industries and economic activity in a region.
Jobs or Housing Units per
Account12
Reflects the intensity of housing development and employment per account for each member agency. Generally positively correlated with water demand.
Historical Passive Efficiency
Reflects long-term historical implementation of plumbing code and fixture replacement. Negatively correlated with water demand. Historical estimates were derived from AWE Tracking Tool (see Section 4).
Drought Restrictions Short term drought restrictions tend to decrease the amount of water consumed by customers.
COVID
Billing records indicate different water use patterns during the COVID pandemic (Assumed active from March 2020 – May 2023), conceptually related to stay-at- home orders and the increased prevalence of remote work.
3.2 Summary of Econometric Model Fitting Process
Development of econometric models was an iterative process, reflected in the following Figure 3-2 and summarized in more detail in Table 3-2. Models were fit using monthly records of the rate of water consumption, generally over the 2000-2023 time period, though this range varied based on individual member agency data availability. Data utilized for the dedicated irrigation and recycled/raw water models tended to be shorter in length, as the prevalence of these customer classes tended to be newer relative to more established classes such as single family residential.13
10 The econometric model was developed using historical weather data specific to each member agency’s service area boundaries.
Future weather conditions used for projections are further discussed in Sections 5 and 7. 11 Ibid.
12 SF accounts reflect a 1-1 ratio with housing unit. MF housing units per account were calculated by dividing the number of housing units by recorded number of accounts. CII jobs per account were calculated by dividing the number of jobs within a service area by the total number of CII accounts.
13 To ensure data quality and consistency in model calibration, all irrigation and recycled water use data were restricted to post- 2005. Additional agency-specific restrictions were applied where historical patterns or anomalies warranted tighter controls.
Specifically, irrigation data for North Coast CWD were limited to post-2020, and Purissima Hills WD irrigation data were DRAFT
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Figure 3-2: General Iterative Process for Developing Econometric Models Table 3-2: Summary of Econometric Model Fitting Process Model Fitting Procedure Description
Collect and pre-process
model input data
Conduct necessary pre-processing calculations prior to model fitting, e.g.:
• Collaborative development of historical demographic data (e.g., housing units, jobs, and population) with member agencies.
• Calculate rate of use (e.g., gallons per account per day). • Calculate natural logarithms of sectoral rate of use and appropriate predictors. • Calculate departures from normal conditions for appropriate predictors (i.e., economic trend and weather).
• Calculate any index, “dummy,” or interacted parameters (e.g., seasonal cycle, geography, drought severity).
• Smoothing monthly and bimonthly data to adjust for irregular billing cycles.
Fit regression models for
each sector
Use statistical estimation software (e.g., R, EViews) to fit linear regression equations to per unit use with the selected explanatory variables.
Examine coefficient
estimates and measure of fit
Review measures of fit (e.g., R2) and coefficient estimates for reasonable magnitude, direction/sign, and significance.
Refine model to improve
measures of fit and
coefficient estimates
If the model fit is poor or if coefficient estimates are illogical or insignificant, several actions can be taken, including but not limited to:
• Identifying and removing outlier data points that have significant leverage on coefficient estimates.
• Remove predictors with insignificant or illogical coefficient estimates from the regression equation.
• Testing alternate specifications of explanatory variables.
Check models for cross-
sector consistency
Model fits and predictors are compared across sectors to judge estimates relative to prior expectations; e.g., testing if the relative effects of price and socioeconomic variables vary by sector in a logical way based on past experience.
Consistent with the panel regression process, several model coefficients are unique to each member agency, while others are shared across all agencies. Model coefficient ranges for each of the econometric models are documented in Appendix C.
restricted to post-2011. For recycled water, City of Redwood City and City of Palo Alto data were limited to post-2020, City of Mountain View to post-2013, and San Jose Muni to post-2015.
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3.3 Historical Model Performance
Overall, the econometric models showed strong performance over the historical dataset and are of sufficient strength to be useful in forecasting future water demand. Figures 3-3 through 3-11 on the following pages illustrate timeseries plots overlaying regional average per-account water use compared to the econometric model fits as well as scatter plots illustrating all monthly observations and model predictions for all member agencies. Visual inspection indicates that on a regional scale the econometric models well represent both seasonal trends as well as the long-term historical trend in declining per- account use. Note that SF and MF models tend to show the strongest statistical performance. The CII model is less accurate on a monthly basis relative to the SF and MF models, but faithfully reflects long- term trends in per-account water consumption. Regionally, the irrigation and recycled water models show strong correlation with seasonal water use patterns, which is expected for sectors that are dominated by outdoor water use. Note that a regional timeseries plot for the recycled water model is not shown, as the differences in the available billed data between member agencies makes a regional average difficult to interpret.14
Appendix D provides additional statistics demonstrating the strength of the statistical model fits, including ranges of values across the member agencies models.
14 Ibid.
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Figure 3-3: Regional Average SF Observed and Predicted Rate of Use
Figure 3-4: Scatterplot Illustrating Monthly Observed SF Water Use vs. Historical Model Predictions
0 100
200
300
400
500
600
2000
2005
2010
2015
2020
2023
Gallons/Account/Day
Observed Predicted
R² = 0.9756
0 200
400
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1,000
1,200
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0 200 400 600 800 1,000 1,200 1,400 1,600 1,800
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Observed Gallons/Account/Day
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Figure 3-5: Regional Average MF Observed and Predicted Rate of Use
Figure 3-6: Scatterplot Illustrating Monthly Observed MF Water Use vs. Historical Model Predictions
0 500
1,000
1,500
2,000
2,500
3,000
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2005
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Gallons/Account/Day
Observed Predicted
R² = 0.9762
0 1000
2000
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4000
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6000
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8000
0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000
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Figure 3-7: Regional Average CII Observed and Predicted Rate of Use
Figure 3-8: Scatterplot Illustrating Monthly Observed CII Water Use vs. Historical Model Predictions
0 500
1,000
1,500
2,000
2,500
3,000
2002
2005
2010
2015
2020
2022
Gallons/Account/Day
Observed Predicted
R² = 0.9399
0 1,000
2,000
3,000
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7,000
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0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 Predicted Gallons/Account/Day
Observed Gallons/Account/Day
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Figure 3-9: Regional Average Irrigation Observed and Predicted Rate of Use
Figure 3-10: Scatterplot Illustrating Monthly Observed Irrigation Water Use vs. Historical Model Predictions
0 1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
2006
2010
2015
2020
2023
Gallons/Accounts/Day
Observed Predicited
R² = 0.901
0 2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
20,000
0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 20,000 Predicted Gallons/Account/Day
Observed Gallons/Account/Day
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Figure 3-11: Scatterplot Illustrating Monthly Observed Recycled Water Use vs. Historical Model Predictions
R² = 0.9031
0 500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 Predicted Gallons/Account/Day
Observed Gallons/Account/Day
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4. Water Conservation Analysis and Projection
BAWSCA’s conservation analysis is anchored by the AWE Tracking Tool, a Microsoft Excel–based platform designed to help utilities assess technological efficiency, estimate water savings, and evaluate the cost-effectiveness of conservation measures. The tool supports long-term planning by modeling both passive and active efficiency improvements across the SF, MF, CII, and Irrigation sectors.
The analysis uses detailed inputs, including housing units, population, water demand, and historical program installations, to model current fixture stocks and project future efficiency gains. Savings are categorized as passive (code-driven, naturally occurring replacement) or active (utility-sponsored interventions). Together, these components define remaining conservation potential and inform the development of regional program portfolios.
4.1 Passive Water Savings Assessment
Passive water savings represent the efficiency gains expected to occur naturally as fixtures and appliances reach the end of their useful lives and are replaced with models that comply with the Energy Policy Act (EPACT), CALGreen, and Title 20 standards:15
• EPACT: A U.S. federal law establishing national water efficiency standards for plumbing fixtures and appliances (e.g., toilets, faucets, showerheads). • CALGreen: California’s mandatory green building code (Title 24, Part 11) requiring sustainable practices, including indoor and outdoor water efficiency measures. • Title 20: California Appliance Efficiency Regulations setting minimum energy and water performance standards for appliances sold in the state.
The AWE stock model simulates these changes using expected useful lives, housing and population growth, and code-based installation requirements. This establishes both a long-term indoor efficiency trajectory and the baseline against which active program savings are evaluated.
Passive turnover defines remaining retrofit potential for active programs. Several high-efficiency technologies, most notably 0.8 gallons per flush (gpf) Ultra-High-Efficiency Toilets (UHETs), cannot be achieved through passive replacement alone, as codes plateau at higher flush volumes. Similarly, outdoor uses experience no passive turnover, making them a central focus of active conservation.
4.1.1 Baseline Fixture Stock and Efficiency Trends
Understanding the distribution of residential fixture stock, such as toilets, showerheads, faucets, clothes washers, and dishwashers, is critical for accurately estimating both passive and active water savings potential. This section analyzes the current and projected efficiency levels of these fixtures, categorized
15 https://www.energy.ca.gov/rules-and-regulations/appliance-efficiency-regulations-title-20; https://www.dgs.ca.gov/bsc/calgreen; https://www.congress.gov/bill/102nd-congress/house-bill/776 DRAFT
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by regulatory standards (EPACT, Title 20) and market-driven ultra-high-efficiency technologies, to inform conservation planning and program targeting.
Baseline fixture stock distributions for SF, MF, and CII customers were developed using the AWE stock models. These distributions incorporate:
• Historical adoption of efficient technologies;
• Participation in BAWSCA, Valley Water, and Cal Water programs; • Housing age, population and natural replacement rates; • Federal and California efficiency standards; and
• Market adoption of WaterSense and ENERGY STAR technologies.
Tables 4-1 through 4-3 present the distribution of fixture and appliance stock by technology tier for 2025 and 2050. Detailed five-year incremental projections in Appendix E (Tables E-3 and E-4) show a continued decline in pre-EPACT fixtures, increasing penetration of ultra-efficient technologies, and remaining opportunities in multifamily shared laundry facilities and specific CII equipment categories not fully captured by passive modeling.
Single-Family Fixture Stock
In the SF sector, passive savings occur primarily through replacement of toilets, clothes washers, dishwashers, and showerheads as homes age, remodel, or change ownership. The model assumes a steady rate of stock turnover based on each fixture’s expected useful life and the efficiency level required by current California standards.
Key Findings:
• Pre-EPACT toilets are projected to decline sharply by 2050, nearly disappearing from the stock.
• Ultra-high-efficiency toilets (UHET/WaterSense) are expected to become predominant, especially in new construction.
• The market for showerheads and aerators is expected to reach near-universal efficiency where most products in the market meet or exceed the highest efficiency standards. • Clothes washers still present significant turnover potential, with many older models expected to remain in use.
• ENERGY STAR dishwashers are projected to dominate the market by 2050.
Multifamily Fixture Stock
The MF sector presents a more complex profile due to wide variation in building configurations, age, occupancy patterns, and management practices. Water use and conservation potential are influenced by factors such as whether units are individually sub-metered, whether landscape irrigation is tenant- or DRAFT
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owner-managed, and the presence of shared laundry facilities. These factors create greater variability in passive efficiency trends compared to SF housing.
Key Findings:
• MF toilets are transitioning toward high-efficiency (HET) and UHET models by 2050. • High-flow showerheads are expected to nearly disappear. • Shared laundry facilities remain a significant opportunity for efficiency improvements, even in 2050.
• ENERGY STAR and ENERGY STAR Most Efficient clothes washers are gaining substantial market share.
• Overall, MF stock remains less efficient than SF stock across most end uses.
Additional characteristics of multifamily buildings further influence this trajectory. Multifamily properties often retain a higher proportion of inefficient fixtures and adopt efficient appliances more slowly, due to factors such as cost-sharing, building age, and limited incentives for property owners.
Shared-laundry facilities commonly rely on older, high-water-use machines, underscoring significant remaining market potential for both passive and active savings.
CII Fixture Stock
CII fixture stock varies widely across business types. The baseline assessment focuses on commercial toilets and urinals, which are the only CII indoor end uses for which the AWE Tracking Tool provides stock-turnover-based passive savings modeling. Passive efficiency gains in this sector tend to occur more gradually due to longer equipment life spans, slower renovation cycles and diversity of facility types and uses.
Other CII equipment types, such as pre-rinse spray valves, commercial dishwashers, steamers, combination ovens, and laundry systems are not modeled through AWE’s stock module. These technologies are incorporated only through active conservation measures where applicable and are not included in passive turnover estimates. Turnover occurs through renovations, tenant improvements, equipment failure, and business transitions.
Key Findings include:
• CII turnover is slower than residential turnover, but deep efficiency shifts occur by 2050. • High-efficiency urinals (0.5 gpf) become the dominant urinal technology. • Ultra-high-efficiency and waterless urinals grow steadily. • Pre-EPACT toilets largely disappear but remain a retrofit opportunity in the near term. • Shares of ULFT toilets shrink but remain substantial due to long commercial fixture lifespans.
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Understanding the existing fixture stock and its efficiency levels provides the foundation for estimating passive savings. As older, less efficient fixtures are naturally replaced over time with code-compliant models, these stock changes drive ongoing reductions in water use without additional program intervention. The following section quantifies these passive savings.
Table 4-1: SF Fixture Stock Distribution by Technology Tier (2025 and 2050) Fixture Type Technology Tier Efficiency Level Share (2025) Share (2050) Toilets Pre-EPACT 3.5–5.0 gpf 10% 2%
ULFT (EPACT Standard) 1.6 gpf 40% 18%
HET 1.28 gpf 45% 55%
UHET/WaterSense ≤1.1 gpf 5% 25%
Showerheads Legacy >2.5 gpm 5% 1%
EPACT 2.5 gpm 10% 4%
Title 20 2.0 gpm 50% 40%
Market Trend 1.8 gpm 35% 55%
Faucet Aerators Legacy >2.2 gpm <5% 0%
EPACT 2.2 gpm 20% 8%
Title 20 / WaterSense 1.5–1.2 gpm 75% 92%
Clothes Washers Legacy Top-Loader High WF 30% 8%
Standard Efficiency Medium WF 30% 17%
ENERGY STAR Low WF 30% 45%
ENERGY STAR Most Efficient Very Low WF 10% 30%
Dishwashers Legacy Non-rated 20% 5%
Standard Efficiency Mid-efficiency 40% 25%
ENERGY STAR High efficiency 40% 70%
Table 4-2: MF Fixture Stock Distribution by Technology Tier (2025 and 2050) Fixture Type Technology Tier Efficiency Level Share (2025) Share (2050) Toilets Pre-EPACT 3.5–5.0 gpf 20% 5%
ULFT (EPACT Standard) 1.6 gpf 45% 25%
HET 1.28 gpf 30% 45%
UHET/WaterSense ≤1.1 gpf 5% 25%
Showerheads Legacy >2.5 gpm 10% 2%
EPACT 2.5 gpm 15% 6%
Title 20 2.0 gpm 45% 38%
Market Trend 1.8 gpm 30% 54%
Shared Laundry
Washers
Legacy High WF 55% 15%
Standard Medium WF 25% 20%
ENERGY STAR Low WF 15% 40%
ENERGY STAR Most Efficient Very Low WF 5% 25%
In-Unit Washers Legacy High WF 35% 10%
Standard Medium WF 30% 20%
ENERGY STAR Low WF 30% 45%
ENERGY STAR Most Efficient Very Low WF 5% 25%
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Table 4-3: CII Toilet & Urinal Efficiency Distribution by Technology Tier (2025 and 2050) Fixture Type Technology Tier Efficiency Level Share (2025) Share (2050) Toilets Pre-EPACT 3.5 gpf 20% 5%
ULFT (EPACT Standard) 1.6 gpf 47% 25%
HET 1.28 gpf 28% 45%
UHET/WaterSense ≤1.1 gpf 5% 25%
Urinals Legacy >1.5 gpf 15% 2%
Standard Efficiency 1.0–1.5 gpf 40% 25%
High-Efficiency (HEU) 0.5 gpf 35% 50%
Ultra-High-Efficiency ≤0.125 gpf 10% 23%
4.1.2 Passive Water Savings Summary
The passive savings estimates presented in Table 4-4 illustrate projected water use reductions resulting from natural fixture turnover and compliance with plumbing codes over the planning horizon. Passive savings were evaluated in five-year increments using the AWE stock model. Results show regional passive indoor savings increasing from 3.97 mgd in 2030 to 12.15 mgd in 2050.
Key observations include:
• Steady Growth in Savings: Passive savings increase gradually each year as older fixtures are replaced, creating a compounding effect over time.
• Residential Sector Dominance: Single-family and multifamily accounts contribute the largest share of passive savings, driven primarily by toilet and clothes washer replacements. • CII Contribution: While smaller in absolute terms, CII savings are significant for fixtures like urinals and commercial washers, reinforcing the importance of turnover in nonresidential settings. • Baseline Impact: These savings occur without active program investment, forming a critical foundation for demand management and reducing the burden on active conservation programs.
Table 4-4: Additional Annual Passive Savings Estimates by Sector, MGD Utility 2025 2030 2035 2040 2045 2050 Total
(2025-2050)
Single-Family 0 2 3 4 5 5 89
Multi-Family 0 1 3 3 4 5 73
CII 0 1 1 1 2 2 28
Regional Total 0 4 7 9 11 12 190
The average rate of use for each end use technology was rebased to 2025 to ensure that only new or additional passive efficiency gains are captured in the projections. The econometric model is fit to historical water use data, which already reflects the effects of passive efficiency improvements that occurred prior to 2025, such as fixture and appliance turnover and code-driven efficiency gains. Rebasing to 2025 prevents double-counting of efficiency improvements that are already embedded in historical consumption rates. As a result, only incremental passive savings, those resulting from future fixture turnover and new code requirements not yet reflected in the historical data, are included in the DRAFT
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projections. This approach provides a more accurate estimate of additional water savings over the planning horizon and ensures that demand forecasts are not artificially reduced by efficiency gains that have already occurred.
4.2 Active Water Conservation Program Development
BAWSCA’s active conservation program portfolio was developed through a structured process ensuring that selected measures are technically applicable, cost-effective, and aligned with regional needs. The process included compiling historical program data, reviewing end uses and measure applicability, incorporating member agency input, and evaluating each program using consistent assumptions. The active conservation component reflects the implementation of utility-sponsored programs designed to accelerate or expand efficiency improvements beyond natural replacement trends. These measures address both indoor and outdoor end uses across the SF, MF, and CII sectors.
4.2.1 Compilation of Existing Program Information
BAWSCA manages a Regional Water Conservation Program consisting of multiple initiatives available to all member agencies. Ten agencies also participate in other regional programs—City of Milpitas, City of Mountain View, City of Palo Alto, City of San Jose Municipal Water, City of Santa Clara, Stanford University, and City of Sunnyvale participate in Valley Water programs, while California Water Service (Cal Water) administers programs within its districts, including Bear Gulch, Mid-Peninsula, and South San Francisco. Additionally, some agencies operate their own programs as advertised on their websites.
Historical program data were compiled from BAWSCA archives, Valley Water, Cal Water, and member agency documentation, including participation histories, budgets, and measure descriptions. Conservation measures and cost information published on agency websites were also incorporated into the regional database. These data were consolidated and used to pre-populate assumptions in the utility survey.
To validate and refine this information, an Excel-based survey was developed to present the regional program database and collect feedback on program status, costs, savings, and annual participation.
Distributed in January 2025, the workbook included program lists, assumptions, and participation history.
Member agencies reviewed and completed the survey in February 2025, confirming measure applicability, refining cost and savings assumptions, and providing planned participation from 2025– 2050. This process ensured regional consistency while allowing flexibility to reflect local conditions.
With program data validated and future participation plans established, the next step was to identify the full set of technically applicable measures across all sectors. This analysis ensures that conservation planning considers both existing programs and emerging opportunities for efficiency improvements.
4.2.2 Identification of Technically Applicable Measures A comprehensive review of indoor and outdoor end uses identified the full set of efficiency measures applicable to each sector. Reviewed technologies included plumbing fixtures, appliances, irrigation hardware, CII process equipment, leak detection tools, landscape transformation programs, and education and outreach initiatives. Potentially applicable measures considered for program development target indoor and outdoor use within single-family, multifamily, and CII sectors.
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As discussed in Section 4.1, the passive analysis established the baseline indoor efficiency trajectory.
Subsequent integration of both passive and active components ensured that:
• Passive savings are not double counted;
• Active programs focus on meaningful remaining potential; • High-efficiency technologies not achieved through passive turnover are prioritized through active programs; and
• Outdoor measures receive emphasis due to the absence of passive turnover.
This integration revealed that there are significant remaining opportunities on a regional-level, particularly UHET retrofits and substantial additional outdoor savings potential. To support effective implementation, maintaining up-to-date estimates of fixture and appliance stock by sector and efficiency level is essential. Participation assumptions for active programs should be revisited annually, incorporating observed uptake and feedback from member agencies. Targeted outreach and incentives, especially for multifamily properties and shared-laundry facilities, should be adjusted based on participation trends to accelerate adoption. Tailored communication strategies for property owners and managers can help overcome barriers to upgrading inefficient fixtures in multifamily buildings.
4.2.3 Addressing Uncertainty and Adaptive Management
Uncertainty in participation rates, technology adoption, and cost projections underscores the need for adaptive management. Programs should be periodically reassessed in light of new data, regulatory changes, or emerging technologies to ensure continued effectiveness.
Robust data collection and transparent resolution of gaps are critical for validating savings estimates and refining program assumptions over time. Member agencies should continue providing detailed program implementation data, costs, and savings, while documenting any assumptions or interpolations used in the analysis. This approach supports adaptive planning and ensures confidence in reported outcomes.
4.2.4 Program Water Savings
The AWE Tracking Tool was used to estimate per-unit savings, measure life, retrofit potential, program costs, and cumulative savings through 2050 for all active programs. This uniform framework enables transparent comparison across sectors and supports portfolio development.
Table 4-5 through Table 4-9 present program-level results, including:
• Lifetime units installed;
• Total and annual savings;
• Cumulative savings through 2050;
• Regional program costs;
• Cost-effectiveness ($/1,000 gallons saved); and
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• Share of sector savings (%).
Appendix E (Tables E-5 and E-6) present annual active savings and regional program costs by program.
For each measure, the total gallons saved reflect cumulative savings over the useful life of the technology, which varies by end use, implementation assumptions, and participation rates.16 The tables illustrate how active programs complement passive savings by accelerating efficiency gains beyond natural fixture turnover.
Key observations include:
• Active programs deliver incremental savings to passive conservation, with irrigation measures providing the largest overall impact on outdoor water use. • Residential and multifamily retrofits contribute significant indoor savings, particularly through high-efficiency toilets and clothes washers.
• Commercial and institutional programs, such as audits and direct-install kits, offer targeted opportunities for cost-effective savings in high-use facilities. • Savings projections, reflect cumulative impacts through 2050, emphasizing the importance of sustained participation and adaptive management to achieve long-term goals.
The following section builds on these results by examining cost-effectiveness, enabling agencies to prioritize programs that deliver the greatest water savings per dollar invested.
4.2.5 Cost-Effectiveness and Key Drivers
Cost-effectiveness was evaluated using the AWE Tracking Tool, incorporating both utility and participant costs. For each measure, the total gallons saved reflect cumulative savings over the useful life of the technology, which varies by end use, implementation assumptions, and participation rates. This structure provides agencies with a consistent analytical foundation while allowing flexibility to select programs that best fit local priorities, customer demographics, and resource objectives.
Table 4-5 through Table 4-9 present the program water savings and unit costs used to estimate program cost-effectiveness, measured in cost per 1,000 gallons, for the single family, multi-family, non-residential (CII), and irrigation sectors, respectively.17
For context, programs with a unit cost below $3–$5 per 1,000 gallons saved are generally considered highly cost-effective based on regional and industry benchmarks. Measures exceeding $10 per 1,000 gallons may still warrant inclusion if they deliver significant total savings or support compliance objectives.
16 Assumptions for unit savings rates, and useful life of the technology are default values associated with programs included in the AWE Tracking Tool.
17 Cost-effectiveness values shown in this Tables 4-5 through Table 4-9 reflect regional costs and savings aggregated across all participating utilities over the full planning horizon. These results do not represent the cost-effectiveness of individual programs.
Detailed program-level cost-effectiveness is provided separately in Appendix E. Higher cost-effectiveness values may reflect uncertainty in savings projections, participation rates, or program costs at the planning level.
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| Water Conservation Analysis and Projection 4-9
Cost-effectiveness varies significantly by sector and technology, reflecting differences in retrofit potential, measure life, and implementation costs:
• Single-Family: Indoor conservation kits (~$2 per 1,000 gallons) and smart irrigation controllers (~$3 per 1,000 gallons) rank among the most cost-effective measures. Inline drip conversions and AMI leak alerts also fall below the $5 benchmark, while turf replacement often exceeds $10 but delivers large total savings.
• Multifamily: Irrigation controllers (~$3–$4 per 1,000 gallons) and UHET retrofits (~$4–$5) offer strong returns. Efficient clothes washer rebates average $8–$9 per 1,000 gallons, above the benchmark but still valuable for high-density properties. • CII: Spray valves and aerators typically cost less than $3 per 1,000 gallons, making them among the most cost-effective measures. Restroom fixture upgrades and commercial laundry technologies generally fall in the $4–$6 range.
• Irrigation: Large landscape controllers and inline drip conversions often achieve costs near $3–$4 per 1,000 gallons, while water budgets and audits remain under $5. Turf conversion programs exceed $10 but provide significant regional impact. • Education & Outreach: While not quantified in cost-effectiveness terms, these efforts are essential for driving participation and supporting compliance with the UWUO.
These findings underscore the importance of prioritizing programs that maximize water savings per dollar invested while maintaining a balanced portfolio that addresses all sectors. Utilities should incorporate cost-effectiveness metrics into future planning cycles to ensure resources are directed toward measures with the greatest impact. Programs with high total savings but moderate unit costs, such as large-scale irrigation retrofits, may still warrant inclusion for their regional impact and compliance objectives.
4.2.6 Distribution of Program Savings by Sector
Understanding how savings are distributed across programs provides the foundation for strategic decision-making. The Share of Sector Savings (%) metric presented in Table 4-5 through Table 4-9 highlights some implications for prioritizing investments.
Key observations include:
• Irrigation: Controllers, audits, inline drip conversions, and turf replacement dominate outdoor savings.
• Residential Indoor: UHET retrofits, conservation kits, and AMI leak alerts provide significant indoor savings.
• CII: Spray valves, aerators, restroom upgrades, and ozone laundry systems deliver strong savings in high-use facilities.
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BAWSCA December 8, 2025
Regional Water Demand and Conservation Projections Study Final Report
| Water Conservation Analysis and Projection 4-10
Strategic implications include:
• Focus resources on programs that represent the highest percentage of sector savings relative to program costs.
• Use distribution analysis to identify “high-leverage” measures that accelerate conservation savings.
Building on these patterns, the next section translates this analysis into actionable priorities, linking program selection to cost-effectiveness, sector-specific strategies, and long-term compliance objectives
4.2.7 Implications for Program Prioritization
The combined passive and active assessment supports several key planning decisions and provides a roadmap for cost-effective, strategically targeted conservation investments across the BAWSCA region.
Current Priorities
• Emphasize irrigation and AMI measures for long-term impact. • Maintain strong indoor offerings, especially UHETs and fixture retrofits. • Incorporate education programs to enable participation in high-impact measures.
While these priorities provide a solid foundation, the analysis also reveals opportunities to improve program selection. As agencies seek to maximize water savings and ensure long-term compliance with regulatory objectives, it becomes increasingly important to move beyond a “one-size-fits-all” approach.
Enhanced prioritization, grounded in cost-effectiveness, a tiered implementation framework, and sector- specific strategies, enables agencies to focus resources where they will have the greatest impact.
Opportunities for Enhanced Prioritization
1. Link to Cost-Effectiveness: Programs with the lowest cost per 1,000 gallons saved and highest cumulative savings should form the core portfolio.
2. Adopt a Tiered Framework for Program Implementation:
• Tier 1: High savings + high cost-effectiveness (e.g., irrigation controllers, UHET retrofits, AMI leak alerts).
• Tier 2: Moderate savings or higher cost but strategic importance (e.g., turf replacement for drought resilience).
• Tier 3: Supportive programs (education/outreach) that enable participation and compliance.
3. Sector-Specific Strategies
• Multifamily: Target incentives for shared laundry facilities and tailored outreach for property managers.
• CII: Focus on audits and high-use fixture upgrades in commercial kitchens and laundries.
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| Water Conservation Analysis and Projection 4-11
4. Integrate Regulatory Compliance: Align prioritization with need to meet UWUO targets and long-term reliability objectives.
5. Dynamic Monitoring: Review participation and savings annually; adjust priorities based on performance and emerging technologies.
Agencies exceeding or nearing the UWUO should prioritize regulatory compliance in their planning.
Those close to the UWUO threshold should strongly consider implementing the outlined recommendations to ensure compliance and avoid potential penalties. This caveat ensures that resources are directed where regulatory risk is highest, while still encouraging proactive planning for others.
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| Water Conservation Analysis and Projection 4-12
Table 4-5: Portfolio of Single-Family Program Active Water Savings and Unit Costs (2050) Program
ID Program Name Units
Program Cost Parameters
Life of
Savings
(Years)
Cumulative
Program
Costs ($K)
Cumulative
Program
Savings (MG)
Share of
Sector
Savings
Cost
Effectiveness
($/1000 gal)(a)
1 Toilets - Conventional (>=3.5 gpf) to HET (1.28 gpf) Toilet 25 $212.05 392 2.7% $0.54 4 Toilets - ULFT (>=1.6 gpf) to HET (1.28 gpf) Toilet 25 $0.00 0 0.0% - 7 Toilets - HET (1.28 gpf) to HET+ (<=1.0 gpf) Toilet 25 $0.00 0 0.0% - 11 SFR Washer Rebate (WF <=4) Washer 15 $614.30 204 1.4% $3.01 13 Water Conservation Kits - Indoor Kit 10 $1,800.64 2,640 18.3% $0.68 14 Water Conservation Kits - Outdoor Kit 10 $404.05 427 3.0% $0.95 15 Water Conservation Kits - LivingWise Kit 10 $1,069.48 692 4.8% $1.54 19 SFR Turf Replacement Square-foot 10 $23,882.21 2,123 14.7% $11.25 22 Rain Garden Addition Square-foot 10 $640.36 75 0.5% $8.56 23 SFR In-Line Drip Irrigation Conversion Square-foot 10 $187.65 2,563 17.8% $0.07 26 SFR Smart Irrigation Controller Rebate Device 10 $1,530.24 1,189 8.3% $1.29 29 SFR Irrigation Nozzle Replacement Device 10 $203.90 167 1.2% $1.22 32 Rainwater Capture - Rain Barrel <200 Barrel 5 $20,747.17 414 2.9% $50.16 35 SFR Graywater Laundry to Landscape Rebate Household 10 $106.54 30 0.2% $3.50 38 SFR Water Use Audit Household 5 $1,870.12 578 4.0% $3.24 41 SFR Wireless Flow Monitor Monitor 5 $42,668.36 1,947 13.5% $21.91 42 SFR AMI Leak Alert Household 1 $3,702.66 809 5.6% $4.58 62 Showerhead Replacement (<= 1.8 gpm) Showerhead 10 $99.00 79 0.5% $1.26 64 Bathroom Direct Install Toilet 25 $0.00 0 0.0% -
66 Irrigation System Flow Sensor Rebate Controller 10 $5.00 1 0.0% $7.05 68 SFR Medium Cistern (501-999 gal) Rebate Barrel 5 $150.00 40 0.3% $3.75 69 SFR Large Cistern (1000+ gal) Rebate Barrel 5 $132.00 43 0.3% $3.10 SINGLE-FAMILY TOTAL $100,027 14,413 100% $6.94
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| Water Conservation Analysis and Projection 4-13
Table 4-6: Portfolio of Multifamily Program Active Water Savings and Unit Costs (2050) Program
ID Program Name Units
Program Cost Parameters
Life of
Savings
(Years)
Cumulative
Program
Costs ($K)
Cumulative
Program
Savings (MG)
Share of
Sector
Savings
Cost
Effectiveness
($/1000 gal)
2 Toilets - Conventional (>=3.5 gpf) to HET (1.28 gpf) Toilet 25 $27.64 40 0.7% $0.69 5 Toilets - ULFT (>=1.6 gpf) to HET (1.28 gpf) Toilet 25 $131.67 229 3.9% $0.58 8 Toilets - HET (1.28 gpf) to HET+ (<=1.0 gpf) Toilet 25 $10.50 11 0.2% $1.00 12 MFR In-Unit Washer Rebate (WF <=4) Washer 15 $0.00 0 0.0% - 20 MFR Turf Replacement Square-foot 10 $4,949.58 545 9.3% $9.08 24 MFR In-Line Drip Irrigation Conversion Square-foot 10 $553.87 366 6.3% $1.51 27 MFR Large Landscape Smart Irrigation Controller
Rebate
Device 10 $724.31 2,212 37.8% $0.33
30 MFR Irrigation Nozzle Replacement Device 10 $758.86 287 4.9% $2.65 33 Rainwater Capture - Cistern >=200 Barrel 5 $420.14 70 1.2% $6.01 36 Submetering - Other Meter 20 $119.20 29 0.5% $4.07
37 SFR Unmetered to Metered Meter 20 $25.19 38 0.6% $0.67 39 MFR Water Use Audit Property 5 $157.72 15 0.3% $10.57 43 MFR (4 or fewer units) AMI Leak Alert Property 1 $92.72 1,924 32.9% $0.05 63 Showerhead Replacement (<= 1.8 gpm) Showerhead 10 $62.48 48 0.8% $1.31 65 Bathroom Direct Install Toilet 25 $52.85 38 0.6% $1.39 67 Irrigation System Flow Sensor Rebate Controller 10 $4.94 2 0.0% $2.33 MULTIFAMILY TOTAL $8,092 5,853 100% $1.38
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BAWSCA December 8, 2025
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| Water Conservation Analysis and Projection 4-14
Table 4-7: Portfolio of CII Program Active Water Savings and Unit Costs (2050) Program
ID Program Name Units
Program Cost Parameters
Life of
Savings
(Years)
Cumulative
Program
Costs ($K)
Cumulative
Program
Savings (MG)
Share of
Sector
Savings
Cost
Effectiveness
($/1000 gal)
3 Toilets - Conventional (>=3.5 gpf) to HET (1.28 gpf) Toilet 25 $27.29 49 3.8% $0.56 6 Toilets - ULFT (>=1.6 gpf) to HET (1.28 gpf) Toilet 25 $368.69 310 24.1% $1.19 9 Toilets - HET (1.28 gpf) to HET+ (<=1.0 gpf) Toilet 25 $10.50 13 1.0% $0.80 10 CII Urinal (1/8 gpf) Replacement Urinal 25 $68.69 40 3.1% $1.70 16 Water Conservation Kits - Spray Valves Kit 10 $83.04 568 44.1% $0.15 17 Water Conservation Kits - Aerators/Showerheads Kit 10 $309.47 167 13.0% $1.85 34 Rainwater Capture - Cistern >=200 Barrel 5 $220.21 35 2.8% $6.20 57 Certification - Green Business Certification 0 $259.60 0 0.0% - 61 Building Efficiency Program CII Establishment 0 $0.00 0 0.0% - 70 CII Ozone Laundry Washer Rebate Washer 15 $54.60 73 5.7% $0.75 71 CII Commercial Kitchen Dishwasher Rebate Dishwasher 20 $0.00 0 0.0% - 72 CII Commercial Kitchen Spray Rinse Valve Rebate Spray Valve 10 $10.40 10 0.8% $1.07 73 CII Commercial Kitchen Food Steamer Rebate Food Steamer 10 $39.65 21 1.6% $1.93 74 CII Restaurant Dipper Well Rebate Dipper Well 10 $0.00 0 0.0% - 76 Acoustic Hydrant Cap Hydrant Cap 0 $0.00 0 0.0% -
CII TOTAL $1,452 1,286 100.0% $1.13
Table 4-8: Portfolio of Irrigation Program Active Water Savings and Unit Costs (2050) Program
ID Program Name Units
Program Cost Parameters
Life of
Savings
(Years)
Cumulative
Program
Costs ($K)
Cumulative
Program
Savings (MG)
Share of
Sector
Savings
Cost
Effectiveness
($/1000 gal)
18 CII Technologies CCF 10 $570.20 845 5.5% $0.67
21 CII Large Landscape Turf Replacement Square-foot 10 $13,536.34 1,128 7.3% $12.00 25 CII In-Line Drip Irrigation Conversion Square-foot 10 $1,570.07 1,100 7.1% $1.43 28 CII Large Landscape Irrigation Controller Station 10 $956.84 1,793 11.6% $0.53 31 CII Large Landscape Irrigation Nozzle Replacement Station 10 $208.72 143 0.9% $1.46 40 CII Large Landscape Water Audit Property 5 $2,760.57 2,947 19.0% $0.94 75 CII Large Landscape Water Budget Site 1 $1,079.39 7,548 48.7% $0.08 IRRIGATION TOTAL $20,682 15,504 100.0% $1.33
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BAWSCA December 8, 2025
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| Water Conservation Analysis and Projection 4-15
Table 4-9: Portfolio of Education Program Water Savings and Unit Costs (2050) Program
ID Program Name Units
Program Cost Parameters
Life of
Savings
(Years)
Cumulative
Program
Costs ($K)
Cumulative
Program
Savings (MG)
Share of
Sector
Savings
Cost
Effectiveness
($/1000 gal)
44 Water Use Monitoring - Water Calculator Household 0 $0.00 0 0.0% - 45 Water Use Monitoring - Footprint Calculator Household 0 $0.00 0 0.0% - 46 Water Use Monitoring - RSAT Kit/Home Survey Kit Household 0 $61,779.00 0 0.0% - 47 In-School Education - Poster Contest Household 0 $693,500.00 0 0.0% - 48 In-School Education - EarthCapades Performance 0 $66,108,606.00 0 0.0% - 49 In-School Education - Water-Wise Kit 10 $9,685,010.00 0 0.0% - 50 In-School Education - Classroom Visit Household 0 $1,377,000.00 0 0.0% - 51 In-School Education - Teacher Training Household 0 $25,500.00 0 0.0% - 52 Public Outreach Household 0 $9,437,771.00 0 0.0% -
53 Water Efficient Landscaping - Conservation Garden Household 0 $0.00 0 0.0% - 54 Water Efficient Landscaping - Education Classes Household 0 $474,566.00 0 0.0% - 55 Water Efficient Landscaping - Garden Tours Household 0 $36,480.00 0 0.0% - 56 Water Efficient Landscaping - Water-Wise Tool Household 0 $0.00 0 0.0% - 58 Certification - QWEL Certification 0 $0.00 0 0.0% - 59 Affordability/Equity - Grants Grant 0 $0.00 0 0.0% - 60 Affordability/Equity - Assistance Program Grant 0 $2,812,840.00 0 0.0% - EDUCATION TOTAL $90,713,052 $0 0.0% -
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| Water Conservation Analysis and Projection 4-16
4.3 Water Conservation Summary
Section 4 has provided a comprehensive evaluation of conservation program options for BAWSCA and its member agencies. The analysis quantifies both the ongoing impact of code-driven fixture turnover and the additional savings achievable through targeted utility programs. The use of the AWE Tracking Tool, combined with agency feedback and cost-effectiveness analysis, ensures that program selection is grounded in real-world data and tailored to local needs.
This approach also highlights the importance of adaptive management as regulatory requirements and water use patterns evolve. The findings underscore the need for ongoing monitoring, transparent documentation, and regular updates to program assumptions to maximize water savings and cost efficiency across the region.
With these insights as a foundation, the following recommendations are offered to help member agencies translate analysis into effective action, ensuring that conservation efforts remain responsive and aligned with both regional goals and state regulations.
Key findings include:
• Passive conservation will continue to deliver steady, compounding savings, especially in the residential sector.
• High-impact indoor measures, including spray valves, aerators, showerheads, and UHET toilets, remain essential contributors.
• Active programs generate the majority of long-term savings, particularly through irrigation measures, but they require sustained investment and adaptive management to remain effective. • Cost-effectiveness varies widely across programs, with some measures delivering much greater savings per dollar.
• Education and outreach support awareness, enhance participation, and strengthen long-term efficiency behavior.
A balanced regional conservation strategy, combining high-impact irrigation with AMI measures, targeted indoor upgrades and strong education and engagement, ensures sustained long-term water savings and supports compliance with evolving state and local efficiency requirements.
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| Baseline 2050 Water Demand Projection Scenario 5-1
5. Baseline 2050 Water Demand Projection Scenario
The baseline scenario serves as the foundation for BAWSCA’s regional water demand projections, providing a consistent set of assumptions for demographic growth, climate, economic conditions, and efficiency trends across all member agencies. BAWSCA worked closely with member agency representatives to adjust published regional assumptions for the baseline scenario, that are agency- approved forecasts for housing units, population, and jobs to 2050. This section provides a summary of the baseline scenario assumptions and reviews the resulting water demand and conservation forecast regionally and by member agency.
5.1 Selection of Base Period and Econometric Model Calibration Calibration refers to adjustments for residual biases in the output of fitted econometric models to establish an historical point in time to anchor projections of the future to a recent, representative historical period for each agency and sector. The calibration approach implemented a simple scalar calibration at the per‑account (rate‑of‑use) level for each agency and sector. The use of simple scalar (i.e., a constant multiplicative factor) preserves the econometric relationships (e.g., weather and price elasticities) while removing differences/errors in the statistical model predictions for the selected calibration period. The 2022–2023 time frame was selected as the base period for SF and MF sectors and 2021–2022 for CII.
These windows align the model to the most recent billed records provided by each member agency for which model predictions were available and not subject to drought restrictions.
For each member agency and model sector a calibration factor was calculated as the ratio needed to make the model’s average predicted per‑unit use equal the observed per‑unit use over the selected calibration period. Calculated factors were then applied multiplicatively to all forward-looking monthly rate‑of‑use predictions. The initial calibrated forecast point, 2025, was checked against FY23-24 volumetric data reflected in BAWSCA’s most recent Annual Survey and member agency profiles. Across member agencies, the initial calibrated 2025 forecast point closely aligned with FY23-24 volumetric data. A handful of member agencies18 were able to provide preliminary FY24-25 volumetric data to further refine the calibration factors. Table 5-1 provides a summary of the final calibration factors developed for the econometric models. Since each member agency and sector has a unique calibration factor, Table 5-1 illustrates the range for each model sector.
Table 5-1: Summary of Calibration Factors
Model Sector Calibration Factor Range
SF 0.900 to 1.300
MF 0.920 to 2.000
CII 0.800 to 1.250
Dedicated Irrigation (potable) 0.400 to 1.400
Recycled & Raw Water 0.681 to 1.270
18 ACWD, City of Palo Alto, City of Redwood City, City of Hayward, City of Sunnyvale, and the City of Milpitas.
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BAWSCA December 8, 2025
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| Baseline 2050 Water Demand Projection Scenario 5-2
5.2 Scenario Definition and Assumptions
Over the course of two Water Management Representative (WMR) meetings19 and individual comments from member agency representatives over a four-month period, BAWSCA reviewed and solicited feedback on the baseline forecast assumptions. Table 5-2 below provides a summary of key assumptions for the baseline future water demand scenario. Additional discussion of demographic, weather and climate, economic, conservation and pricing, and losses are included in the following subsections.
Table 5-2: Summary of Baseline Scenario Assumptions
Explanatory Variable Future Assumption and Data Sources Demographic Variables
Housing Units • Based on growth rates from Plan Bay Area 2050, reviewed and adjusted by member agencies’ planning departments and cities (see Figure 5-1, Figure 5-2, Figure 5-3).
Population
Total Jobs
Persons Per Household (PPH) • Derived from projected housing units and population identified above.
Housing Density
• Derived from projected housing units and residential land use processed from the California General Plan Land Use dataset published by the California State Geoportal.
Jobs per Account • Assumed to be consistent with 2023 averages. MF Housing Units per Account SF, MF, CII Accounts • Grows proportionally to housing units and jobs projections using jobs and MF housing units per account factors.
Irrigation and Recycled Water
Accounts
• Held constant into future unless specific account growth specified from member agency representatives.20
Weather and Climate Variables
Monthly Maximum Temperature • Climate change adjusted temperature from 2025-2050 from CalAdapt CMIP-5 downscaled projections.
Monthly Total Precipitation • Consistent with historical normal values.
Economic Variables
Mix of Industries / Economic Activity • Consistent with 2022 sectoral jobs reports from LODES dataset. • Assumed to hold constant into the future.
Regional GDP and Unemployment
Rate
• Consistent with long-term trend in historical data.
• Assumed to hold constant into the future.
Conservation and Pricing
Passive Savings • Consistent with AWE Tracking Tool projections given projected demographic data (housing units, population, jobs).
Active Savings • Consistent with projected savings from annual measures described in Section 3.
Price of Water • Member agencies with known rate increases provided expected changes in prices.
• Otherwise, prices held constant in real terms (i.e., assumed to keep pace with inflation).
Losses and Other Assumptions
Non-Revenue Water • Non-revenue water volumes consistent with 2023 AWWA water loss audits.
• Assumed constant into the future.
Other Water Uses • Held constant at average of billed consumption for years 2000-2023.
19 May 29, 2025 and July 8, 2025.
20 ACWD, City of Brisbane, City of Hayward, and the City of Redwood City provided specific account growth for irrigation and recycled water accounts.
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BAWSCA December 8, 2025
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| Baseline 2050 Water Demand Projection Scenario 5-3
5.3 Demographic Assumptions
Future demographic projections for housing units, population, and jobs are foundational inputs for both the econometric water demand model and a conservation planning tool (i.e., AWE Tracking Tool). These projections drive estimates of future water use, passive savings, and the capacity for conservation programs across BAWSCA member agencies.
Future demographic projections for population, SF housing units, MF housing units, and jobs were extrapolated from the historical values used to develop the econometric models as defined in Section
2.3.1. Future projections of these explanatory variables were primarily based on the Plan Bay Area 2050 TAZ dataset,21 which provides modeled demographic data for 2015, 2035, and 2050. TAZ geographies, which are similar in size and shape to census tracts, were aggregated and reprojected to align with member agency service areas using the procedure described in Section 2.2.1. Rather than using absolute values from Plan Bay Area (which may not align with historical estimates), the rate of change (slope) between projection years was applied to the most recent historical estimates for each agency. Application of the rate of change based on Plan Bay Area, as opposed to the actual Plan Bay Area values, avoids unrealistic jumps and ensures continuity between historical and projected data. The rate of change was applied to the most recent historical values in two steps, that reflect the two disparate growth rates in the Plan Bay Area forecasts:
• An initial “Slope A” reflecting 2015–2035 Plan Bay Area projections was calculated for population, SF/MF housing units, and jobs and imposed on 2023 historical data to generate annual projections.
• A second “Slope B” reflecting 2035–2050 Plan Bay Area projections was calculated for population, SF/MF housing units, and jobs and imposed on the 2035 projection.
As an additional validation step, the resulting demographic projections were compared to member agency Regional Housing Needs Assessment (RHNA) targets and were reviewed by member agency representatives. Adjustments to make the Plan Bay Area projections consistent with RHNA requirements were made as needed to reflect local planning realities as communicated by member agency representatives.
Demographic projections illustrated in Figures 5-1 through 5-3 on the following pages indicate steady growth across all key drivers—population, housing units, and employment—through 2050, consistent with regional planning assumptions from Plan Bay Area 2050 and local agency inputs. Regional population is expected to grow 37% over the planning horizon. Housing unit growth closely tracks population trends, with a notable shift toward higher-density multifamily development, reflecting urbanization and land-use constraints. This shift has implications for per-capita water use, as multifamily units typically exhibit lower indoor consumption but may increase outdoor irrigation demand in shared
21 Association of Bay Area Governments (ABAG) and Metropolitan Transportation Commission (MTC). Plan Bay Area 2050:
Traffic Analysis Zone (TAZ) Dataset. San Francisco, CA, 2021. Plan Bay Area, https://planbayarea.org/. Accessed 2024.
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BAWSCA December 8, 2025
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| Baseline 2050 Water Demand Projection Scenario 5-4 landscapes. Regional employment projections show a similar growth rate to population, which is likely to influence growth in CII water use.
Figure 5-1: Historical and Projected Regional Population
Figure 5-2: Historical and Projected Regional Housing Units
1,567,233 1,638,670 1,792,529
1,801,844
1,896,180
2,048,994
2,303,905
2,595,684
0 500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000Population
Historical Population Projected Population
317,225 348,084 358,955 360,181
367,753 374,503 377,303
221,396
266,554
307,293
330,048
402,405
509,181
618,684
0 100,000
200,000
300,000
400,000
500,000
600,000
700,000Housing Units
Historical SF Units Projected SF Units Historical MF Units Projected MF Units DRAFT
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BAWSCA December 8, 2025
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| Baseline 2050 Water Demand Projection Scenario 5-5
Figure 5-3: Historical and Projected Regional Jobs 22
As discussed in Table 5-2, all additional future demographic variables, including future accounts, PPH, and housing density were derived from the projected population, housing units, and job projections illustrated in Figures 5-1 through 5-3.
5.4 Weather and Climate Assumptions
Based on discussions with member agency representatives, inclusion of climate change adjusted future weather conditions was considered appropriate to include as a part of the baseline scenario assumptions.
Downscaled CMIP5 data23 were obtained from CalAdapt’s Local Climate Change Snapshot tool.24 Climate projection data, including annual precipitation and maximum temperature, was collected for the three counties that overlay BAWSCA’s member agencies, including Alameda, San Mateo, and Santa Clara counties. Data were collected for two Representative Concentration Pathways (RCP), RCP 4.5 and RCP 8.525 for the multi-ensemble means26 of the CalAdapt CMIP5 projections.
22 Note that historical jobs data from the LODES dataset start in 2002. 23 Note that at the time climate change data were obtained for this study, only CMIP5 data were available in a post-processed form from CalAdapt. CMIP6 data have since been released. 24 https://cmip5.cal-adapt.org/tools/local-climate-change-snapshot 25 RCP 4.5 represents a moderate climate change scenario where greenhouse gas emissions peak around 2040 and then decline, assuming significant mitigation efforts. In contrast, RCP 8.5 assumes continued high emissions throughout the century, leading to more severe warming and climate impacts due to minimal mitigation. 26 The multi-ensemble mean refers to the average output derived from multiple climate model simulations, often across different models and scenarios. This approach helps reduce individual model biases and internal variability, providing a more robust and representative projection of future climate conditions—such as temperature, precipitation, or water demand—by capturing the consensus across a range of plausible futures.
940,207 897,092
1,123,173
1,239,834
1,373,105
1,504,507
0 200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000Jobs
Historical Jobs Projected Jobs
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BAWSCA December 8, 2025
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| Baseline 2050 Water Demand Projection Scenario 5-6 Modeled temperatures from the CalAdapt CMIP5 RCP 4.5 and RCP 8.5 datasets were processed annually for 2025 – 2050 and included as potential inputs to the demand model. Table 5-3 summarizes the estimated increases in temperature between 2025 and 2050. Based on conversations with BAWSCA staff and member agency representatives, future changes from historical normal temperatures associated with RCP 8.5 were selected to include in the baseline scenario. Using RCP 8.5 captures the upper‑end warming signal from CalAdapt’s multi‑model ensemble, supporting a conservative (i.e., non‑understating) baseline for regional planning.
Table 5-3: Average Annual Maximum Temperature Increases in 2050 (Relative to 2025) Derived from CalAdapt CMIP5 RCP 4.5 and RCP 8.5
County RCP 4.5 RCP 8.5
Alameda 1.20 °F 2.03 °F
Santa Clara 1.25 °F 2.05 °F
San Mateo 1.06 °F 1.77 °F
Climate change impacts for annual precipitation were also considered for inclusion in the baseline scenario assumptions. Based on the analysis, precipitation impacts were excluded from initial climate change considerations as modeled changes in precipitation in each county did not appear to have a significant change in mean between 2025 and 2050 for either RCP 4.5 or RCP 8.5. An example plot27 illustrating this concept for Santa Clara County is presented below in Figure 5-4.
Figure 5-4: Example Modeled Annual Precipitation in Santa Clara County Under Future Climate Change Conditions
27 Similar trends were observed for Alameda and San Mateo Counties.
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BAWSCA December 8, 2025
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| Baseline 2050 Water Demand Projection Scenario 5-7
5.5 Assumptions for Economic Variables
Three economic explanatory variables were considered as inputs to the CII econometric model including, the future mix of industries in each member agency service area, regional GDP, and county-wide unemployment rate. Future shifts in jobs between industries are highly uncertain (Plan Bay Area did not indicate a significant shift between 2035 and 2050) and therefore the relative percentages were assumed to be constant based on 2022 observations from the LODES dataset.28 Future evolution of GDP and unemployment are similarly difficult to predict and were elected to remain constant at historical trends in the baseline scenario.
5.6 Conservation and Pricing Assumptions
Future conservation, both passive efficiency gains and active program implementation, moderates projected water demand growth. These savings are applied as annual deductions to sectoral consumption forecasts generated by the econometric models. Detailed methodologies and assumptions related to conservation are provided in Section 4; this section summarizes only the key elements relevant to demand projections.
Passive Savings reflect ongoing fixture and appliance turnover and code-compliant installations in new construction, consistent with California standards (Title 20 and CALGreen). These improvements occur independently of utility programs and are incorporated prospectively using the AWE Tracking Tool to ensure demand forecasts account for gradual efficiency gains.
Although new development contributes to total water demand growth, it also adds only high-efficiency fixtures to the system, thereby reducing average use per housing unit over time. These effects are considered passive because they occur independently of active utility programs and are not captured in the historical water-use data used to estimate average per-unit consumption in the econometric demand models. The AWE Tracking Tool therefore provides a mechanism to incorporate these incremental efficiency gains prospectively, ensuring that future demand projections reflect the ongoing impact of both fixture turnover and efficient new construction. Member agency estimates developed using the AWE Tracking Tool indicate that passive conservation will continue at a steady rate through 2050 driven by both ongoing MF housing growth and plumbing fixture turnover in existing SF homes.
Active Savings represent incremental reductions achieved through utility-sponsored programs beyond natural turnover. Program assumptions draw from the analysis in Section 4.3 and include measures targeting indoor and outdoor use across single-family, multifamily, and CII sectors.
28 The City of Hayward provided alternate future distribution of jobs by industry based on a Lightcast dataset. These projections were incorporated into the baseline scenario for the City of Hayward but were not applied to other agencies given the geographical specificity of the dataset.
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| Baseline 2050 Water Demand Projection Scenario 5-8
5.6.1 Future Water Prices
In addition to conservation effects, the econometric models explicitly account for changes in the real price of water, allowing the impacts and of pricing and conservation to be evaluated independently. To keep the baseline focused on “business‑as‑usual conditions” and to avoid making assumptions associated with future policy choices, the baseline scenario generally assumes no real change in customer prices over time with the exception of a handful of agencies29 that provided approved rate increases for inclusion. More specifically, nominal rates are assumed to change with general inflation so that the real (inflation‑adjusted) marginal volumetric price is held constant throughout the forecast horizon. This treatment isolates the effects of demographics, weather/climate, efficiency, and the economy from unapproved or uncertain future pricing actions. This establishes a neutral, defensible baseline for comparing alternative conservation portfolios, without presuming future Board / Council actions on rates.
A review of SFPUC’s 10-year financial plan30 indicates that wholesale rates are expected to rise in nominal terms at an annual average of 2.2% over the next 10-years, which is slightly below the assumed rate of general inflation of 3% annually. This also suggests that holding prices constant in real terms is a reasonable baseline from which other pricing scenarios can be evaluated.
5.7 NRW and Other Water Use Assumptions
NRW and “Other” water use were handled outside the econometric rate‑of‑use equations to avoid introducing noise into the modeled sectors and to preserve a transparent link to member‑reported data and AWWA water‑loss practices.
For each agency, “Other” water use was projected using the latest five-year average, with no applied trend. Meanwhile, NRW was anchored to member agency‑reported 2023 AWWA water loss reporting (and/or historical production‑vs‑consumption series), ensuring consistency with the State reporting framework. For each member agency, NRW was assumed to be constant in percentage terms with the aforementioned historical data. These percentages were multiplied by total projected water use for the total of each modeled sector plus other water uses. The baseline scenario holds NRW at a constant share of total consumption in the future, consistent with each agency’s 2023 AWWA water loss reporting (or historically observed production‑consumption relationship). As total demand grows or declines, the volumetric NRW moves proportionally, but the percentage remains constant.
5.8 Baseline Forecast Results
This section summarizes the baseline water demand projections for BAWSCA member agencies between 2025-2050. The forecast reflects the combined influence of assumptions articulated in Sections 2, 3, and 4, including demographic growth, passive efficiency improvements, planned active conservation implementation, and expected climate change, while holding general economic conditions and real water rates constant. It serves as the reference point for evaluating conservation strategies and UWUO
29 Several agencies, including the City of Redwood City, City of Palo Alto, and Estero MID provided approved increases in water rates, which were incorporated into the baseline assumptions. 30 https://www.sfpuc.gov/sites/default/files/about-us/policies-reports/FY-2026-10-Year-Plan-Report.pdf DRAFT
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| Baseline 2050 Water Demand Projection Scenario 5-9 regulatory compliance as developed by the State Water Resources Control Board (see Section 6).
Forecasted demand is summarized sectorally without additional conservation, regionally with passive and active conservation, and by member agency.
5.8.1 Sectoral Forecasts without Additional Conservation Across the region, SF demand remains the largest share of total consumption, but its growth is modest due to near build-out conditions. MF demand shows a stronger upward trajectory, driven by regional housing policies and higher-density development patterns anticipated in Plan Bay Area 2050 projections.
The CII sector reflects moderate growth aligned with employment forecasts. Dedicated Irrigation demand remains sensitive to climate assumptions and are generally expected to be stable into the future. Low growth in this sector is consistent with the baseline assumption that Dedicated Irrigation accounts are not expected to significantly increase in the region. Recycled and raw water projections reflect expected use of existing recycled and raw water accounts.31 As discussed in Section 3, Other water use and non- revenue water are assumed to remain constant at existing (i.e., 2023) volumes and rates, respectively. The baseline forecast organized by modeled sector is presented in Figure 5-5.
Figure 5-5: Baseline Sectoral Forecast Without Additional Conservation
31 Several agencies indicated that several existing CII accounts and some MF accounts may switch supply sources to recycled water in the future. These changes in classification are not reflected in the baseline forecast, and should be evaluated as changes in source of supply.
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203 212 220 228
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Forecasted Water Demand (mgd)
SF Forecast MF Forecast CII Forecast Irrigation Forecast Recycled Forecast Other Forecast Non-Revenue Forecast
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5.8.2 Regional Forecasts Including Conservation
Between 2025 and 2050, passive conservation is expected to deliver a steady, compounding reduction in indoor water use as legacy fixtures and appliances are naturally replaced with code‑compliant, higher‑efficiency models. This effect is strongest in the SF and MF sectors driven by turnover of toilets, showerheads, faucets, clothes washers, and dishwashers) and remains meaningful for select CII end uses such as urinals). Passive savings trajectories are based on adopted California fixture standards and assumed replacement rates developed through the AWE Tracking Tool.
Building on the underlying passive glidepath, active conservation programs deliver incremental, implementation‑dependent water savings. Measure options encompass both indoor and outdoor applications across SF, MF, CII, and irrigation sectors including direct‑install and rebate programs, landscape conversions, smart controllers. Unit savings and measure costs taken from member submittals or Valley Water inputs supplemented by AWE Tracking Tool defaults where local data were unavailable.
Because the econometric baseline holds real prices constant and embeds only passive efficiency gains, the water savings attributed to active program portfolios are modeled as additive adjustments to the forecast.
This approach supports transparent comparisons among alternative program mixes and budget levels.
In aggregate, the 2025–2050 period is characterized by monotonic increases in passive savings that steadily lower indoor use per unit, with discretionary active savings layered on where and when agencies choose to implement programs. Outdoor savings potential is especially sensitive to active measures such as turf conversion, irrigation system retrofits and smart control adoption), while indoor savings reflect a mix of passive fixture turnover and active program acceleration). Figure 5-6 and Table 5-4 summarize the baseline forecast incorporating estimates of future passive and active conservation effects across all sectors. Between 2025 and 2050, passive conservation is projected to reduce total regional demand by roughly 12 MGD, a 5 percent reduction relative to the baseline forecast. When active conservation measures are included, total demand declines by approximately 16 MGD, or about 7 percent below the baseline by 2050. These reductions equate to roughly 13,500 acre-feet per year (AFY) from passive efficiency improvements alone, and up to 19,000 AFY when active programs are implemented.
While passive savings accrue steadily across all sectors as fixtures turn over and new developments are built to California’s stringent efficiency codes, active savings depend on continued program investment and customer participation. Together, these effects moderate long-term demand growth and improve the region’s supply reliability, effectively offsetting the equivalent of a small new water supply source by 2050.
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Figure 5-6: Baseline Forecast Including Passive and Active Conservation
Table 5-4: Baseline Forecast Including Passive and Active Conservation (MGD) Forecast Assumption 2025 2030 2035 2040 2045 2050
Forecast without Additional Conservation 190 203 212 220 228 237 Total Forecast w/ Passive Conservation 190 199 205 211 217 224 Total Forecast w/ Passive + Active Conservation 189 197 202 208 213 220
5.9 Total Forecasts by Member Agency
The total baseline forecast scenario for each member agency with and without conservation is summarized in Tables 5-5 through 5-7 on the following pages. As previously stated, the demand projections presented in this report were developed exclusively for the analytical scope of this Project.
Final, official demand projections must be obtained directly from the corresponding member agency's adopted planning documents. Separate to this report each member agency has been provided a water demand projection workbook containing detailed model inputs, econometric model equations, and sectoral summaries of water conservation projections.
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| Baseline 2050 Water Demand Projection Scenario 5-12 Table 5-5: Total Baseline Forecast Without Additional Conservation by Member Agency (MGD) Member Agency 2025 2030 2035 2040 2045 2050
Alameda County Water District 34.35 35.38 36.49 37.52 38.50 40.86 California Water Service Company -- Bear Gulch 9.01 9.14 9.28 9.33 9.36 9.40 California Water Service Company -- Mid-Peninsula 11.59 11.80 12.02 12.13 12.19 12.27 California Water Service Company -- South San Francisco 5.54 5.89 6.24 6.41 6.54 6.69 City of Brisbane/Guadalupe Municipal Improvement District 0.68 0.95 0.97 1.00 1.01 1.01 City of Burlingame Municipal 3.89 4.01 4.13 4.36 4.56 4.75 City of Daly City 6.34 6.39 6.45 6.65 6.81 6.98
City of East Palo Alto 1.64 1.68 1.73 1.76 1.78 1.80
City of Hayward 13.67 15.73 17.01 18.46 20.06 21.93
City of Menlo Park 2.70 2.80 2.90 2.99 3.07 3.16
City of Millbrae 1.89 2.03 2.17 2.29 2.41 2.52
City of Milpitas 8.76 9.19 9.68 10.11 10.39 10.69
City of Mountain View 9.12 9.96 10.80 11.37 11.89 12.46 City of Palo Alto 10.30 10.23 10.45 10.55 10.62 10.72
City of Redwood City 8.31 8.23 8.42 8.75 9.05 9.36
City of San Bruno 2.90 2.94 2.99 3.08 3.15 3.22
City of San Jose Municipal Water System - North San José - Alviso 4.72 8.41 9.02 10.00 10.91 11.81 City of Santa Clara 19.76 21.28 22.82 23.74 24.58 25.48 City of Sunnyvale 17.52 18.59 19.66 20.28 20.83 21.41
Coastside County Water District 1.57 1.60 1.61 1.63 1.64 1.66 Estero Municipal Improvement District 3.94 4.01 4.12 4.18 4.21 4.25 Mid-Peninsula Water District 2.66 2.89 3.09 3.34 3.57 3.63 North Coast County Water District 2.25 2.37 2.49 2.61 2.62 2.65 Purissima Hills Water District 1.37 1.37 1.38 1.39 1.39 1.40 Stanford University 2.65 2.86 3.08 3.16 3.24 3.32
Town of Hillsborough 2.12 2.12 2.14 2.16 2.17 2.19
Westborough Water District 0.85 0.88 0.91 0.93 0.95 0.98 Regional Total 190 203 212 220 228 237
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| Baseline 2050 Water Demand Projection Scenario 5-13
Table 5-6: Total Baseline Forecast with Passive Conservation by Member Agency (MGD) Member Agency 2025 2030 2035 2040 2045 2050
Alameda County Water District 34.35 34.70 35.36 36.07 36.80 38.79 California Water Service Company -- Bear Gulch 9.01 9.02 9.08 9.07 9.05 9.05 California Water Service Company -- Mid-Peninsula 11.59 11.51 11.51 11.45 11.38 11.35 California Water Service Company -- South San Francisco 5.54 5.74 5.97 6.05 6.12 6.22 City of Brisbane/Guadalupe Municipal Improvement District 0.68 0.94 0.95 0.97 0.97 0.97 City of Burlingame Municipal 3.89 3.94 4.00 4.17 4.31 4.46 City of Daly City 6.34 6.20 6.13 6.21 6.28 6.38
City of East Palo Alto 1.64 1.62 1.62 1.62 1.61 1.62
City of Hayward 13.67 15.36 16.38 17.65 19.11 20.85
City of Menlo Park 2.70 2.75 2.82 2.89 2.95 3.02
City of Millbrae 1.89 1.97 2.05 2.15 2.24 2.35
City of Milpitas 8.76 9.04 9.40 9.74 9.96 10.21
City of Mountain View 9.12 9.71 10.34 10.82 11.28 11.79 City of Palo Alto 10.30 10.05 10.12 10.15 10.17 10.23
City of Redwood City 8.31 8.05 8.12 8.34 8.55 8.79
City of San Bruno 2.90 2.82 2.79 2.81 2.83 2.86
City of San Jose Municipal Water System - North San José - Alviso 4.72 8.33 8.87 9.76 10.58 11.40 City of Santa Clara 19.76 20.99 22.30 23.07 23.78 24.57 City of Sunnyvale 17.52 18.27 19.11 19.54 19.93 20.39
Coastside County Water District 1.57 1.57 1.55 1.55 1.54 1.55 Estero Municipal Improvement District 3.94 3.93 3.99 4.01 4.02 4.03 Mid-Peninsula Water District 2.66 2.83 2.98 3.19 3.40 3.44 North Coast County Water District 2.25 2.31 2.39 2.46 2.46 2.47 Purissima Hills Water District 1.37 1.36 1.36 1.36 1.36 1.37 Stanford University 2.65 2.84 3.04 3.10 3.16 3.23
Town of Hillsborough 2.12 2.10 2.10 2.11 2.12 2.14
Westborough Water District 0.85 0.85 0.86 0.87 0.87 0.89 Regional Total 190 199 205 211 217 224
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| Baseline 2050 Water Demand Projection Scenario 5-14 Table 5-7: Total Baseline Forecast with Passive and Active Conservation by Member Agency (MGD) Member Agency 2025 2030 2035 2040 2045 2050
Alameda County Water District 34.27 34.28 34.74 35.38 36.02 37.93 California Water Service Company -- Bear Gulch 9.00 8.99 9.03 9.02 9.00 9.00 California Water Service Company -- Mid-Peninsula 11.58 11.47 11.45 11.38 11.30 11.27 California Water Service Company -- South San Francisco 5.53 5.72 5.94 6.02 6.08 6.17 City of Brisbane/Guadalupe Municipal Improvement District 0.63 0.78 0.78 0.81 0.81 0.81 City of Burlingame Municipal 3.89 3.92 3.99 4.15 4.30 4.44 City of Daly City 6.33 6.18 6.08 6.15 6.21 6.29
City of East Palo Alto 1.64 1.62 1.62 1.62 1.61 1.62
City of Hayward 13.38 14.97 15.92 17.17 18.61 20.33
City of Menlo Park 2.69 2.73 2.79 2.86 2.91 2.98
City of Millbrae 1.88 1.91 1.99 2.09 2.18 2.29
City of Milpitas 8.73 8.92 9.22 9.51 9.69 9.89
City of Mountain View 9.11 9.67 10.28 10.75 11.20 11.71 City of Palo Alto 10.16 9.69 9.61 9.58 9.58 9.63
City of Redwood City 8.29 7.93 7.92 8.13 8.36 8.60
City of San Bruno 2.90 2.82 2.79 2.81 2.83 2.86
City of San Jose Municipal Water System - North San José - Alviso 4.71 8.29 8.79 9.68 10.51 11.33 City of Santa Clara 19.74 20.84 22.02 22.72 23.36 24.09 City of Sunnyvale 17.52 18.26 19.11 19.54 19.93 20.39
Coastside County Water District 1.57 1.56 1.55 1.55 1.54 1.54 Estero Municipal Improvement District 3.93 3.90 3.92 3.93 3.91 3.90 Mid-Peninsula Water District 2.66 2.82 2.97 3.18 3.39 3.43 North Coast County Water District 2.24 2.27 2.33 2.40 2.40 2.40 Purissima Hills Water District 1.37 1.36 1.35 1.36 1.36 1.37 Stanford University 2.65 2.84 3.04 3.10 3.16 3.23
Town of Hillsborough 2.11 2.09 2.08 2.09 2.11 2.12
Westborough Water District 0.85 0.84 0.84 0.84 0.85 0.86 Regional Total 189 197 202 208 213 220
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| Urban Water Use Objective (UWUO) 6-1
6. Urban Water Use Objective (UWUO)
This section evaluates BAWSCA member agencies’ projected compliance with the State’s UWUO through 2050. It summarizes the methodology, key assumptions, and high-level results, highlighting where agencies are expected to meet or exceed regulatory efficiency targets under baseline and conservation scenarios.
6.1 Regulatory Context
Passed in 2018, Senate Bill 606 (Hertzberg) and Assembly Bill 1668 (Friedman) established a long-term water use efficiency framework32 that required the State Water Resources Control Board (SWRCB) to adopt new regulations for indoor and outdoor water use for urban retail water suppliers33 (URWSs) across the state. A centerpiece of this legislation was the development of UWUOs that would regulate residential indoor and outdoor use, CII irrigation, and real water losses together as an aggregate water use efficiency standard. The SWRCB adopted this regulation mandating UWUO reporting and compliance on July 3rd, 2024.
The regulatory formulation of the UWUO34 consists of an Indoor Residential Water Use Budget, an Outdoor Residential Water Use Budget, a CII Landscape with dedicated irrigation meters (DIMs) Water Use Budget, a Real Water Loss Budget, and any variance or provision volumes, as well as any allowable “Bonus Incentive Adjustments,” as shown in Figure 6-1. Notably, no BAWSCA member agency qualifies for any “Bonus Incentive Adjustments” related to potable recycled water, so no calculations of the Bonus Incentive were required for this study. Although the UWUO is composed of four separate water use budgets, compliance with the UWUO only requires that total UWUO is not exceeded by the sum of the UWUO-regulated sectors of water use in aggregate. In other words, individual UWUO water use budgets can be exceeded as long as the overall UWUO is not.
32 Also known as the Making Conservation a California Way of Life framework 33 As defined in the California Water Code section 10608.12, an urban retail water supplier (URWS) is “a water supplier, either publicly or privately owned, that directly provides potable municipal water to more than 3,000 end users or that supplies more than 3,000 acre-feet of potable water annually at retail for municipal purposes.” 34 Final WCL Primer 2018
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| Urban Water Use Objective (UWUO) 6-2
Figure 6-1: Regulatory Formulation of UWUO
As described in the final text of the Making Conservation a California Way of Life regulation, compliance with the UWUO regulation requires that “no later than January 1, 2025, and by January 1 every year thereafter, each urban retail water supplier shall calculate its urban water use objective and, beginning January 1, 2027, annually demonstrate compliance with its objective.” Consequently, all UWRSs must calculate and report their UWUO to the state every year into the future and also demonstrate compliance with their new efficiency standards as soon as January 1, 2027.
Within the UWUO calculation methodology developed by the state, budgets for indoor residential water use, outdoor residential water use, and CII with DIMs water use are all required to become more stringent over time.35 For indoor residential water use, this is the result of mandatory reductions in gallons per capita per day (gpcd) requirements over time, and for outdoor residential water use, and CII with DIMs water use, it is the result of reductions in landscape efficiency factors (LEFs)36 over time, as shown in Tables 6-1 through 6-3. As result, UWUO compliance may become increasingly challenging for some agencies in the future.
35Water Code section 10609.4
36Final Text of Regulation Making Conservation a Way of Life DRAFT
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| Urban Water Use Objective (UWUO) 6-3
Table 6-1: Residential Indoor Water Use Standards and Compliance Timeline Compliance Date Residential Indoor Water Use Standard (gpcd) Through December 31, 2024 55
January 1, 2025 47
January 1, 2030 42
Table 6-2: Residential Outdoor Landscape Efficiency Factors and Compliance Timeline Compliance Date
Landscape Efficiency Factors (LEFs) for Residential Outdoor Budget Existing Residential
Outdoor Use
Special Landscape Area
(SLA) New Construction
Through June 30, 2035 0.8 1 0.55
July 1, 2035 0.63 1 0.55
July 1, 2040 0.55 1 0.55
Table 6-3: CII with DIMs Landscape Efficiency Factors and Compliance Timeline Compliance Date
Landscape Efficiency Factors (LEFs) for CII DIMs Budget Existing CII DIMs
Special Landscape Area
(SLA) New Construction
Through June 30, 2028
Actual deliveries
associated with landscape
irrigation reported to the
State Board pursuant to
Health and Safety Code
section 116530 1 0.45
July 1, 2028 0.8 1 0.45
July 1, 2035 0.63 1 0.45
July 1, 2040 0.45 1 0.45
6.2 Methodology and Assumptions for Estimating UWUO
UWUO projections were developed for all BAWSCA member agencies that qualified as URWSs.37 To create projections for each agency across the 2025 – 2050 time period, baseline inputs were taken from agencies’ January 1, 2025 UWUO regulatory reporting submissions to the state. These regulatory submissions contained the following agency-specific information necessary for UWUO estimation:
37 The City of Brisbane, Purissima Hills WD, and Stanford University are not URWSs and do not have UWUO estimates as part of this study.
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• Landscape area measurements (LAMs) developed by the Department of Water Resources (DWR);
• CII dedicated irrigation meters’ (DIMs) actual water use from FY 2023-24; • Real water loss standards;
• Variance and provision calculation volumes, if any; and • Senate Bill X7-7 (SB X7-7) water use efficiency targets.
In addition to this baseline data, development of long-term UWUO projections required the following external inputs:
• Annual population projections;38
• Net reference evapotranspiration (Net ETo) projections; and • Existing CII DIMs landscape area measurement (LAM) projections.
6.2.1 Net Reference Evapotranspiration (Net ETo) Projections Net ETo is defined as the difference between reference evapotranspiration and effective precipitation, in inches per year. As can be inferred from the definition, high Net ETo values occur during hot and dry years while low Net ETo values occur during cool and wet years. This Net ETo parameter acts as a scalar and significantly affects the annual calculation for the Outdoor Residential Water Use Budget as well as the CII DIMs Water Use Budget within the overall UWUO, as shown in the UWUO regulatory equations below:
𝑅𝑜𝑢𝑡𝑑𝑜𝑜𝑟 𝐵𝑢𝑑𝑔𝑒𝑡 = 𝑆𝑜𝑢𝑡𝑑𝑜𝑜𝑟 × 𝑅𝐿𝐴 × 𝑵𝒆𝒕 𝑬𝑻𝒐 × 0.62
𝐶𝐼𝐼𝐷𝐼𝑀 𝐵𝑢𝑑𝑔𝑒𝑡 = 𝑆𝐷𝐼𝑀 × 𝐷𝐼𝑀 𝐿𝐴 × 𝑵𝒆𝒕 𝑬𝑻𝒐 × 0.62
Due to overall UWUO sensitivity to this parameter, and because future climatological data is not yet known and the required inputs for reference evapotranspiration and effective precipitation derivations are difficult to estimate, BAWSCA opted to use a DWR-developed historical dataset for Net ETo (the 2017- 2021 Provisional Dataset) that was released as part of the Making Conservation a California Way of Life proposed regulation. Key benefits of using this DWR dataset were concurrence with the reference evapotranspiration and effective precipitation derivations used in the UWUO Reporting Form, as well as a 5-year dataset that included both a wet and a critically dry hydrologic year. Furthermore, to address the future climatological uncertainty out to 2050, BAWSCA approved an “envelope” approach that calculated an “upper bound” and “lower bound” UWUO projection into the future for each agency, one based on the highest Net ETo value from the 2017-2021 Provisional Dataset, and the other based on the lowest Net ETo value. Figure 6-2 shows an example UWUO projection “envelope” for an anonymized agency.
38 Annual population projections by agency were developed as part of the Baseline Forecast. Please refer to Section 5 for more information on this projection methodology.
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| Urban Water Use Objective (UWUO) 6-5
Figure 6-2: Example UWUO Projection Envelope based on High and Low Net ETo values
6.2.2 Existing CII DIMs LAM Projections
While the January 1, 2025 UWUO regulatory submissions included agencies’ CII DIMs actual water use from FY 2023-24, long-term UWUO projections required an estimate of existing CII DIMs LAMs to appropriately adjust the CII DIMs Water Use Budget over time. Since DWR had not completed the CII DIMs LAMs dataset prior to this study’s development, BAWSCA approved the following methodology for back-calculating CII DIMs LAMs using January 1, 2025 UWUO regulatory submission data as well as the Making Conservation a California Way of Life regulatory equation shown below:
𝐶𝐼𝐼𝐷𝐼𝑀 𝐵𝑢𝑑𝑔𝑒𝑡 = 𝑆𝐷𝐼𝑀 × 𝐷𝐼𝑀 𝐿𝐴 × 𝑁𝑒𝑡 𝐸𝑇𝑜 × 0.62
Within this equation, values for 𝐶𝐼𝐼𝐷𝐼𝑀 𝐵𝑢𝑑𝑔𝑒𝑡 (which DWR equated to the CII DIMs actual water use from fiscal year 2023-24 for this submission) and 𝑁𝑒𝑡 𝐸𝑇𝑜 were taken from the January 1, 2025 UWUO regulatory submissions by agency. Assuming that 𝑆𝐷𝐼𝑀 (i.e. the landscape efficiency factor [LEF] standard) equaled 1.0, since compliance with CII DIMs LEFs only begins July 1, 2028 and no efficiency reductions are required before that date, the equation above can be rewritten to solve for 𝐷𝐼𝑀 𝐿𝐴:
𝐷𝐼𝑀 𝐿𝐴 = 𝐶𝐼𝐼𝐷𝐼𝑀 𝐵𝑢𝑑𝑔𝑒𝑡
𝑆𝐷𝐼𝑀 × 𝑁𝑒𝑡 𝐸𝑇𝑜 × 0.62
0.0 100.0
200.0
300.0
400.0
500.0
600.0
700.0
800.0
900.0MG
UWUO: High Net ETo UWUO: Low Net ETo
UWUO Regulated Sector Forecast UWUO Regulated Sector Forecast w/ Passive UWUO Regulated Sector Forecast w/ Passive + Active
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| Urban Water Use Objective (UWUO) 6-6
Note that this equation also assumes that DIM LA is the sum of both CII DIM LA and CII DIM special landscape area (SLA), since any distinctions between LA and SLA are not captured within actual water use volumes.
Estimation of the existing CII DIMs LAMs by agency was important for the overall UWUO projections because it allowed the CII DIMs Water Use Budget to reduce over time due to changing Landscape Efficiency Factors (LEFs). This approach also allowed for the correct handling of different Net ETo values within the CII DIMs Wate Use Budget projections. Once derived, the back-calculated CII DIMs LAMs values were assumed to be constant across the 2025 – 2050 timeframe unless agency-specific changes were requested.
6.2.3 Other Assumptions and Considerations for UWUO Projections Various other assumptions and considerations were also required as part of the UWUO estimation methodology, including:
• No changes to residential or CII DIMs LAMs over time39 unless specifically requested by an agency.
• No inclusion of the 20% Irrigable Not Irrigated (INI) “buffer” component of the UWUO calculation,40 as it is a temporary measure that will be discontinued once suppliers update/approve the landscape area values in the original dataset provided by DWR. • As required under the final Making Conservation a California Way of Life regulation, and as developed in the UWUO Reporting Form, the UWUO projection methodology incorporates a SB X7-7 cap on the UWUO so that the governing water use efficiency objective will always be the minimum of either the calculated UWUO or the SB X7-7 individual target-based total use less any excluded demands.41
Agencies were also able to provide more granular data for incorporation into the UWUO projections if desired, including 1) changes to currently reported landscape areas, 2) future landscape areas for new development (residential outdoor, CII DIMs), and 3) any additional variance and provision volumes.
Numerous BAWSCA agencies provided additional information on landscape areas, both existing and planned, but no agency provided any additional variance or provision volumes.
A summary of the UWUO budget components, required budget inputs, regulatory equations, and estimation methodologies used to develop the overall UWUO projections is provided in Table 6-4.
39 As part of this task, Hazen conducted a sensitivity analysis and determined that updating residential LAM areas over time was unlikely to significantly impact UWUO projections. The sensitivity analysis developed a "typical square footage" per SFR unit and MFR unit, respectively, and then scaled the LAMs over time based on SFR and MFR housing growth projections.
Numerically, the most likely scenario (i.e. "typical" based on empirical GIS analysis) in terms of residential LAM adjustments over time increased the UWUO projections of the evaluated agencies by less than 5% compared to the "no LAM adjusted" baseline.
40 The 20% INI buffer only applies if Actual Water Use exceeds the UWUO. 41 Excluded demands are defined as values provided by the supplier to the Board pursuant to Health and Safety Code section 116530, for the following delivery categories: other; commercial and institutional; and industrial.
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Table 6-4: UWUO Budget Components, Inputs, Regulatory Equations, and Estimation Methodologies
UWUO Budget
Component
Regulatory or DWR-
provided Inputs
Agency
Inputs Regulatory Equation42 Estimation Methodology for UWUO Budget Component
Indoor Residential
Water Use
Budget
• Indoor Water Use
Standards
• DWR LAMs
• DWR Provisional
Dataset for NET
ETo
Agency
population
projections
𝐼𝑛𝑑𝑜𝑜𝑟 𝑅𝑒𝑠𝑖𝑑𝑒𝑛𝑡𝑖𝑎𝑙
𝐵𝑢𝑑𝑔𝑒𝑡
= 𝑆𝑖𝑛𝑑𝑜𝑜𝑟 × 𝑃
× 𝑑𝑎𝑦𝑠 𝑖𝑛 𝑦𝑒𝑎𝑟
Multiplied the appropriate
Indoor Residential Water Use
standard (Water Code section
10609.4) in gallons per capita
per day by the residential
service area population
projection and by 365 days,
accounting for fiscal year
reporting.
Outdoor
Residential Water
Use Budget
• LEFs
• DWR LAMs
• DWR Provisional
Dataset for NET
ETo
𝑂𝑢𝑡𝑑𝑜𝑜𝑟
𝑅𝑒𝑠𝑖𝑑𝑒𝑛𝑡𝑖𝑎𝑙
𝐵𝑢𝑑𝑔𝑒𝑡
= 𝑆𝑜𝑢𝑡𝑑𝑜𝑜𝑟 × 𝑅𝐿𝐴𝑀
× 𝑁𝑒𝑡 𝐸𝑇𝑜 × 0.62
Multiplied the appropriate LEF
standard by DWR's residential
LAM in square feet, the Net
ETo value as developed from
DWR's Provisional Dataset,
and the conversion factor of
0.62. CII with DIMs (or
Equivalent
Technology)
Water Use
Budget
• LEFs
• DWR LAMs
• DWR Provisional
Dataset for NET
ETo
Back-
calculated CII
DIMs LAMs
𝐶𝐼𝐼 𝐷𝐼𝑀𝑠
𝐵𝑢𝑑𝑔𝑒𝑡
= 𝑆𝐷𝐼𝑀 × 𝐷𝐼𝑀 𝐿𝐴𝑀
× 𝑁𝑒𝑡 𝐸𝑇𝑜 × 0.62
Multiplied the appropriate LEF
standard by the back-calculated
CII DIMs LAM in square feet,
the Net ETo value as
developed from DWR's
Provisional Dataset, and the
conversion factor of 0.62.
Water Loss
Budget
• Agency-specific
real water loss
standard (gallons
per connection per
day)
Agency
number of
account
projections
𝑊𝑎𝑡𝑒𝑟 𝐿𝑜𝑠𝑠
𝐵𝑢𝑑𝑔𝑒𝑡
= 𝑆𝑤𝑎𝑡𝑒𝑟 𝑙𝑜𝑠𝑠 × 𝐶
× 𝑑𝑎𝑦𝑠 𝑖𝑛 𝑦𝑒𝑎𝑟
Multiplied the agency-specific
real water loss standard in
gallons per connection per day
by the total annual agency
number of accounts projection
and by 365 days.
Variances or
Provisions
Variable Any agency-
specific inputs
Variable None requested, although
residential agricultural variance
calculations were incorporated
in the underlying DWR data
populated in the January 1,
2025 UWUO Report
submissions and were
therefore carried forward for
relevant agencies in the UWUO
projections.
SB X7-7 Target-
based Total Use
• Agency-specific
SB X7-7 target
𝑆𝐵 𝑋7𝑥7 𝑇𝑎𝑟𝑔𝑒𝑡
𝑏𝑎𝑠𝑒𝑑 𝑇𝑜𝑡𝑎𝑙 𝑈𝑠𝑒
= 𝐴𝑔𝑒𝑛𝑐𝑦 𝑆𝐵 𝑋7𝑥7
𝑡𝑎𝑟𝑔𝑒𝑡 × 𝑃
× 𝑑𝑎𝑦𝑠 𝑖𝑛 𝑦𝑒𝑎𝑟
Multiplied the agency-specific
SB X7-7 target in gallons per
capita per day by the residential
service area population
projection and by 365 days.
42 Where, P = population, S = applicable standard, RLAM = residential landscape area measurement, Net ETo = net reference evapotranspiration, and C = total number of service connections.
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6.3 Comparison of Projected Water Demands with the Estimated UWUO A primary goal of this study was to assess if BAWSCA agencies are anticipated to exceed their UWUOs over the course of 2025 – 2050, given the baseline forecast, and if so, by how much and when. This information can help agencies understand how much time they might have to adopt additional conservation measures to meet their future water use efficiency regulatory requirements. To develop this analysis, agency UWUO projections were compared to the water demand projections of the UWUO- regulated sectors. Within the Demand Study, these UWUO-regulated sectors included the SF Forecast, the MF Forecast, the Irrigation Forecast, the Recycled Forecast (the portion used for residential and/or CII large landscapes), and the real water loss component of the Non-Revenue Forecast.
The results from this comparison demonstrate that the majority of BAWSCA agencies are anticipated to meet their UWUOs across the full time period 2025 – 2050. However, 7 of 23 agencies43 are anticipated to exceed their UWUOs over the 25-year period with only passive conservation, and 5 of 23 agencies are anticipated to exceed their UWUOs over the 25-year period with both passive and active conservation. If only the High Net ETo UWUO projections (which result in higher objectives) are evaluated, 4 of 23 agencies are anticipated to exceed their UWUOs over the 25-year period with conservation included. The earliest anticipated UWUO exceedance occurs in 2031 with only passive conservation (if evaluating the Low Net ETo projection) and in 2035 with only passive or with both passive and active conservation (if evaluating the High Net ETo projection). Other anticipated exceedances begin between 2035 – 2040.
Due to the step-wise reductions in the indoor residential gpcd standards as well as step-wise reductions in the landscape efficiency factors (LEFs) within the UWUO calculation, some agencies only show a brief window of UWUO exceedance and then again show demand dropping below the UWUO into the future.
This is the result of steady and more gradual conservation (passive only or both passive and active) catching up with the UWUOs over time. With conservation included in the forecast (passive only or both passive and active), only 5 of 23 agencies are anticipated to exceed their UWUOs in 2050 (if evaluating the Low Net ETo projection), and only 4 of 23 are anticipated to exceed their UWUOs in 2050 (if evaluating the High Net ETo projection).
43 The City of San Jose was not included in this metric because its UWUO encompasses geographies that are outside of BAWSCA’s service area.
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7. Analysis of Alternative Forecast Scenarios
Water demand forecasting is sensitive to uncertainties in assumptions around future conditions.
Population growth and demographic shifts introduce variability, as migration patterns and urbanization trends are difficult to predict. Economic development and industrial activity add further complexity, as fluctuations in economic output and changes in water-intensive industries are driven (or derived) by the demand for various goods and services. Technological adoption—such as water-saving devices and reuse systems—depends on uncertain behavioral and policy factors. Finally, data quality and model structure themselves pose risks, as simplifying assumptions may propagate errors over time. Given these layers of uncertainty, scenario analysis offers a practical framework to explore a range of plausible futures, enabling water suppliers to test assumptions and assess the resilience of strategies under varying conditions.
BAWSCA worked with member agency representatives, external stakeholders, and SFPUC to develop five additional water demand scenarios to bracket the baseline forecast summarized in Section 5. This section provides a summary of the scenario development process, a description of the key scenario assumptions, and an overview of the alternative scenario projections on a regional basis.
7.1 Scenario Development Process
Alternative water demand scenarios were developed in concert with member agency representatives, stakeholders, and SFPUC staff with the intent to leverage additional expertise around key uncertainties that may impact future water demands. Aside from member agency representatives, organizations providing input to the scenario development process included:
• Association of Bay Area Governments (ABAG)
• Acterra (formerly Sustainable Silicon Valley)
• City/County Association of Governments of San Mateo County (C/CAG) • County of San Mateo
• Tuolumne River Conservancy (formerly Friends of the Tuolumne River) • Sierra Club
• Sustainable San Mateo
During a two-month period, BAWCSA engaged with member agency representatives, SFPUC, and stakeholders through direct discussions, online surveys, and two workshops. The process included determining key explanatory variables affecting water demand, evaluating baseline assumptions and data sources, and assessing uncertainty regarding future conditions—such as identifying alternative projection datasets. Throughout this engagement, assumptions for potential future scenarios for the Bay Area were collaboratively developed and systematically categorized into four general groups that align with water DRAFT
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demand model inputs: (1) Demographics and development; (2) Socioeconomic conditions; (3) Conservation and pricing; and (4) Climate and other trends/concerns.
Using this organizational approach, plausible regional scenarios were developed to set reasonable bounds on future water demand predictions. During the workshops, conceptual scenarios were designed to align with both high and low regional water needs, relative to the baseline scenario. The main results from these workshop activities are summarized below according to “High” and “Low” demand scenarios.
Higher Demand Scenarios
Demographic and Development: There was interest in considering alternative data sources for population, housing units, and job projections, with the application of raw Plan Bay Area 2050 projections as the preferred upper bound.44 Workshop participants noted that while some commercial, industrial, and institutional (CII) land uses could be converted to residential, a less dense future housing scenario was unlikely and there was a preference to keep density constant at 2025 levels to reflect the high scenario.
Socioeconomic Conditions: Workshop participants were interested in scenarios incorporating greater economic growth, anticipating a potential increase in demands associated with the technology industry in the region.
Conservation and Pricing: Workshop participants generally agreed that a decrease in active conservation savings could potentially occur in the future, dependent on societal norms and availability of water. Workshop participants discussed water rates and pricing and concluded that a decrease in real price was not likely given regional trends and infrastructure needs. Workshop participants also discussed the potential for rate structures to change from tiered volumetric rates to uniform volumetric rates. It is unclear what effect this transition may have on price levels and how this may influence price elasticity regionally. Given these observations, it was recommended to keep future pricing constant in real terms for the high scenario.
Climate and Other Trends: Workshop participants wanted to consider hotter and dryer global climate models (GCMs). Workshop participants also expressed strong interest in scenarios with an increase in high water use industries, particularly data centers and biotech applying water for cooling.
Lower Demand Scenarios
Demographic and Development: There was interest in considering alternative data sources for population, housing units, and job projections, with the application of the California Department of Finance (CA DOF) projections as the preferred lower bound.
Socioeconomic Conditions: Workshop participants were interested in scenarios incorporating lower economic growth, with discussion including the potential negative impacts of federal tariff and immigration policies, and how this may influence the job market/economic output in the region.
44 Baseline water demand model demographic assumptions are based on Plan Bay Area 2050 projections but included revisions from member agencies’ planning departments that in aggregate moderated future demographic growth on a regional level and to align with RHNA numbers as appropriate.
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Conservation and Pricing: Workshop participants noted that rate increases may be likely due to future infrastructure investments and showed interest in further water conservation. To prevent overlapping savings from both price hikes and new conservation programs, per capita use was reviewed before adding volumetric conservation in the low scenario. Participants also want to assess how non-functional turf (NFT) bans affect outdoor water consumption.
Climate and Other Trends: Workshop participants wanted to consider GCMs projecting less warming and wetter conditions, or climate models that consider a shift in weather patterns throughout the year.
7.2 Alternate Scenario Assumptions
This section documents the key assumptions and data sources forming the scenario inputs.
7.2.1 Demographic and Development
Three scenarios articulating alternate future demographic and development conditions were developed in response to feedback from member agency representatives, SFPUC, and stakeholders. Key assumptions and data sources are summarized in Table 7-1 on the following page.45 Table 7-1: Alternate Scenario Demographic and Development Data Sources and Assumptions Scenario Name Data Sources Assumptions
Adjusted ABAG
• Plan Bay Area 2050
• Member agency
approved future
demographics
Reflects the maximum of member agency-approved projections and Plan Bay Area 2050.
Historical Trend
• Member agency
approved historical
demographics
Reflects the continuation (extrapolation) of the long-term trends (2000-2023) in population, housing units, and jobs. This scenario aligns with assumptions articulated in SFPUC’s “Scenario B” in their concurrent demand projection update.
DOF
• DOF Population
projections46
• DOF Housing Unit
Projections47
• Reflects DOF projections for population and housing units. • DOF projects total population, and historical single
family/multifamily persons-per-household ratios were used to develop the population split.
• Housing units are projected by DOF through 2030; beyond 2030, housing unit growth was projected to 2050 by applying the average annual growth rate from 2020–2030.
• Because CA DOF reports only total housing units, the future single family and multifamily split was estimated by applying the historical multifamily share to total units, with single family units calculated as the remainder.
• Note that DOF does not project jobs, so jobs were assumed to increase at the same rate as population.
45 For all Scenarios, Stanford University demographic assumptions were kept consistent with the baseline. 46 California Department of Finance, Demographic Research Unit. (2025). State and County Population Projections, 2020–2070 𝑀𝑖𝑐𝑟𝑜𝑠𝑜𝑓𝑡𝐸𝑥𝑐𝑒𝑙𝑓𝑖𝑙𝑒. Sacramento, CA: California Department of Finance. Retrieved September 2025. 47California Department of Finance, Demographic Research Unit. (2025). Household Projections for California Counties: 2020– 2030 (P-4) 𝑀𝑖𝑐𝑟𝑜𝑠𝑜𝑓𝑡𝐸𝑥𝑐𝑒𝑙𝑓𝑖𝑙𝑒. Sacramento, CA: California Department of Finance. Retrieved September 2025.
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Plots illustrating the regional projection scenarios relative to the baseline are summarized in Figures 7-1 through 7-3 below.
Figure 7-1: Comparison of Regional Population Scenarios
Figure 7-2: Comparison of Regional Housing Units Scenarios
2,595,684
2,231,538
1,965,097
2,749,642
0 500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
2025 2030 2035 2040 2045 2050
Regional Population
Baseline Historical Trend DOF Adjusted ABAG
998,955
806,828
869,704
1,087,789
0 200,000
400,000
600,000
800,000
1,000,000
1,200,000
2025 2030 2035 2040 2045 2050
Total Regional Housing Units (SF + MF)
Baseline Historical Trend DOF Adjusted ABAG
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Figure 7-3: Comparison of Regional Job Scenarios
7.2.2 Socioeconomic Conditions
Alternate future socioeconomic conditions were represented by considering different assumptions in future regional real GDP growth and the unemployment rate. Recall that the baseline scenario considers regional real GDP growth and unemployment rate to remain constant at long-term trends. Future scenarios deviating from the long-term trend were selected from the distribution of available historical data. Per discussions in Section 3, higher GDP is associated with higher water demand and higher unemployment rate is associated with lower water demand. Table 7-2 summarizes the regional GDP and unemployment assumptions by scenario.
Table 7-2: Summary of Regional GDP and Unemployment Scenario Assumptions Scenario Name Percentile of Historical GDP
Percentile of Historical
Unemployment
High 90th 10th
Moderated-High 75th 25th
Moderated-Low 25th 75th
Low 10th 90th
1,504,507
1,487,754
1,164,495
1,778,185
0 200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
1,800,000
2,000,000
2025 2030 2035 2040 2045 2050
Total Regional Jobs
Baseline Historical Trend DOF* Adjusted ABAG
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7.2.3 Conservation and Pricing
Conservation and pricing scenarios examine how variations in water rates and efficiency measures influence future demand.
Conservation Assumptions
Passive and active conservation assumptions reflect how demographic trends and policy measures shape long-term efficiency gains. Volumetric passive savings are tied to development, as higher efficiency fixtures are expected to be installed as new development proceeds. This results in higher volumetric savings projected under scenarios using the Adjusted ABAG demographics and lower savings under DOF projections. Figure 7-4 illustrates modeled 2050 passive savings by sector comparing the different demographic scenarios. For example, single-family sectors show modest differences, while multifamily and CII sectors exhibit up to 54% variation in passive savings between high-growth and low-growth demographic cases. Active conservation programs—such as rebates and outreach—were held constant across lower demand scenarios, consistent with member agency plans, meaning no additional active measures are introduced in alternative futures. In response to feedback from workshop participants, additional outdoor conservation reflecting regulatory actions like AB 1572 nonfunctional turf restrictions were considered in the lowest demand scenario. This scenario incorporated additional reductions for combined CII and irrigation seasonal use by an estimated 15% region-wide starting in 2028. Collectively, these assumptions ensure that conservation effects are realistically represented without overstating behavioral change beyond what agencies have committed to implement.
Figure 7-4: 2050 Passive Savings by Sector
2,172
1,904
765
2,122
1,096
536
2,046
1,317
611
0 500
1,000
1,500
2,000
2,500
SF Sector MF Sector CII Sector
Passive Savings, MG
Plan Bay Area 2050 CA DOF Historical Trend
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Water Pricing
Water pricing assumptions vary across scenarios to reflect different regional pricing conditions. The Baseline, High, and Moderated-High scenarios assume rates remain constant in real terms, meaning nominal increases only offset inflation without altering consumption behavior further. In contrast, the Moderated-Low scenario applies a sustained real price increase of approximately 2.5% annually over the planning horizon, while the Low scenario introduces a steeper adjustment—5% per year for the first decade, followed by 2.5% annually thereafter—to simulate more aggressive long-term real rate increases.
The Historical Trend scenario aligns with SFPUC’s 10-year financial plan, incorporating planned wholesale rate changes adjusted for inflation. Note that rate increases from the 2025 SFPUC 10-year financial plan reflect nominal rates. The SFPUC wholesale rate changes have been reduced by an assumed 3% annual rate of inflation to calculate the implied change in real rates each year. These differentiated water rate paths (plotted together in Figure 7-5) allow the analysis to capture how pricing signals influence demand elasticity.
Figure 7-5: Annual Change in Water Rates in Real Terms
7.2.4 Climate Change
Climate change assumptions were incorporated to capture the potential variability in temperature and precipitation patterns that influence outdoor water use and seasonal demand. Each scenario applies a distinct climate projection drawn from widely recognized global climate models (GCMs) and representative concentration pathways (RCPs). At the time scenario analysis was conducted, CMIP6 -5.0%
-2.5%
0.0%
2.5%
5.0%
7.5%
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
2048
2049
2050
Rate Increases in Real Terms
Baseline/High/Moderated-High* Moderated-Low Low Historical Trend DRAFT
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modeling was released and available for consideration. CMIP6 data was utilized for alternative scenarios although CMIP5 was maintained for the baseline (see Section 5.4).
An analysis was performed for each county in the BAWSCA service area to assess the individual CMIP6 models to select individual models that resulted in both higher and lower temperature and precipitation changes relative to the baseline.
High-demand scenarios adopt the hottest and driest conditions from CMIP6 SSP5-8.5 (KACE-1-0-G), while low-demand scenarios assume cooler and wetter futures using CMIP6 SSP2-4.5 (CNRM-ESM2-1).
Moderated scenarios apply intermediate assumptions, such as CMIP5 RCP4.5 for temperature combined with historical precipitation norms. These climate inputs were selected to bracket plausible extremes and mid-range conditions, ensuring that the scenario analysis reflects both the risks of intensified drought and the potential for milder future climates.
7.2.5 New High Water Users – Data Centers
In the scenario analysis workshops and surveys, participants identified a handful of industries that have the potential to significantly expand and increase water use regionally. Data centers received a high degree of interest / concern and were selected to further evaluate.
Data centers represent a unique challenge in water demand forecasting because their consumption patterns are not well captured by traditional employment or account-based model drivers. Instead, water use in these facilities is closely tied to energy consumption and cooling technology choices. With rapid and uncertain growth in cloud computing and AI workloads, the potential for large-scale data center development introduces significant uncertainty into long-term demand projections.
The data center analysis relied on 2024 energy demand projections from the California Energy Commission (CEC), which forecasted peak power demand and annual energy use for data center growth through 2040.48 Figure 7-6 depicts data center power projections provided by CEC for major power utilities in CA.49 The analysis selected projections from power utilities within BAWSCA's service area, including Silicon Valley Power (SVP), City of San José, City of Palo Alto, and PG&E. 90% of PG&E's projected data center power demand was included, as the majority of data center growth in the state is expected to occur within the Bay Area.
48 California Energy Commission. Data Center Forecast. Final Report. March 2025. Available at:
https://www.energy.ca.gov/sites/default/files/2025-03/Data_Center_Forecast_Final_ada.pdf. 49 Ibid.
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Figure 7-6: CEC Annual Energy Use Projections for Data Centers, Organized by Power Utility Figure 7-7 illustrates the total annual data center energy demand in BAWSCA's service area consistent with these assumptions. Note that localized ("behind the meter") power production was not included in these projections.
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Figure 7-7: Estimated Total Annual Data Center Energy Use in BAWSCA Service Area Inferred from CEC Projections
To translate projected electricity use into water demand, Water Usage Effectiveness (WUE) factors were obtained from Lawrence Berkeley National Laboratory (LBNL) that reflect a range of existing cooling technologies currently used by data centers to cool IT equipment, and, specifically, water used for humidification and water evaporated cooling of the data center and its support systems.50 Three WUE values were considered from the LBNL study including:
• 0.2 L/kWh for liquid cooling technology using dry coolers with adiabatic assist (air-cooled chillers);51
• 1.9 L/kWh for liquid cooling technology using waterside economizers (water-cooled chillers); and
• 1.05 L/kWh reflecting the average of the air-cooled and water-cooled chillers identified above.
Figure 7-8 illustrates projected water use for data centers obtained by multiplying the regional annual energy use (in GWh) by the WUE factors identified above. It is unlikely that liquid cooling technology using waterside economizers (1.9 L/kWh) will be adopted at scale in the Bay Area given broader water supply constraints in the region. In general, data centers being developed in water stressed regions tend to select more water efficient cooling technologies, such as air-cooled chillers. Based on these observations, the 0.2 L/kWh WUE was selected to inform projected data center water use for the scenario analysis.
50 Shehabi, Arman, et al. 2024 United States Data Center Energy Usage Report. Lawrence Berkeley National Laboratory, Dec. 2024. https://eta-publications.lbl.gov/sites/default/files/2024-12/lbnl-2024-united-states-data-center-energy-usage-report_1.pdf. 51 0.2 L/kWh reflects annual demands. Note that peak monthly uses for this technology can be significantly higher. 0 5,000
10,000
15,000
20,000
25,000
30,000
2024 2026 2028 2030 2032 2034 2036 2038 2040
Projected Annual Energy Use (GWh)
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Additional demands for data centers were only considered for the “High” scenario and are tabulated in Table 7-3.
Figure 7-8: Projected Data Center Water Use Organized by Assumed WUE Table 7-3: Projected Data Center Water Use (MGD) for “High” Scenario Reflecting 0.2 L/kWh WUE Scenario 2025 2030 2035 2040 2045 2050
“High” 0.6 1.6 3.6 4.1 5.9 7.3
7.2.6 Consolidated Scenario Assumptions
A consolidated summary of scenario assumptions consistent with Sections 7.2.1 through 7.2.5 is presented in Table 7-4 on the following page.
7.3 38.3
69.3 0
10 20
30 40
50 60
70 80
2025 2030 2035 2040 2045 2050
Projected Data Centrer Water Use (MGD)
0.2 L/kWh 1.05 L/kWh 1.9 L/kWh
DRAFT
Attachment 1
BAWSCA December 8, 2025
Regional Water Demand and Conservation Projections Study Final Report
| Analysis of Alternative Forecast Scenarios 7-12
Table 7-4: Consolidated Summary of Scenario Assumptions Scenario Temperature and Precipitation High Water Users Conservation Assumptions Water Rates Demographics Socioeconomics Baseline • CMIP5 RCP8.5 multi-model
mean temperature
• Historical mean precipitation
• No additional high water users • Passive savings consistent with demographic growth
• Active savings consistent with
member agency planned annual
measures
• Keeps pace with inflation
(constant in real terms)
• Planned 5–10-year rate
increases for select agencies
• Member agency approved
adjustments to Plan Bay Area
2050
• Housing density increases with
housing units (as approved by
member agencies)
• Historical trend GDP and
unemployment rate
Low CMIP6 SSP2 4.5 CNRM-ESM2-1
• Lowest temperature GCM
• Highest precipitation scenario
GCM
• No additional high water users • Passive savings consistent with demographic growth
• Active savings consistent with
member agency planned annual
measures
• Considers lower outdoor use
(i.e., approximated NFT ban)
• Initial 10-year real price increase
at 5% annually
• Annual 2.5% real price increase
over remainder of 25-year
period
• Reflects DOF projections
• Housing density consistent with
baseline calculations
• Lower than trend GDP (10th
percentile)
• Higher than trend unemployment
rate (90th percentile)
Moderated-Low • CMIP5 RCP 4.5 multi-model
mean temperature (lower
temperature impact from
baseline)
• Historical mean precipitation
• No additional high water users • Passive savings consistent with demographic growth
• Active savings consistent with
member agency planned annual
measures
• Annual 2.5% real price increase
over entire 25-year period
• Reflects DOF projections
• Housing density consistent with
baseline calculations
• Lower than trend GDP (25th
percentile)
• Higher than trend unemployment
rate (75th percentile)
High CMIP6 SSP5 8.5 KACE-1-0-G
• Highest temperature GCM
• Lowest precipitation scenario
GCM
• Data center projections
consistent with Section 7.2.5
• Passive savings consistent with
demographic growth
• No implementation of active
programs
• Keeps pace with inflation
(constant in real terms)
• Planned 5–10-year rate
increases for select agencies
• Maximum of agency approved
demographics and “raw” Plan
Bay Area 2050 projections
• Housing density remains
constant at 2025 levels
• Higher than trend GDP (90th
percentile)
• Lower than trend unemployment
rate (10th percentile)
Moderated-High
• Hottest GCM from CMIP6
(SSP5 8.5 KACE-1-0-G)
• Historical mean precipitation
• No additional high water users
• Passive savings consistent with
demographic growth
• No implementation of active
programs
• Keeps pace with inflation
(constant in real terms)
• Planned 5–10-year rate
increases for select agencies
• Maximum of agency approved
demographics and “raw” Plan
Bay Area 2050 projections
• Housing density remains
constant at 2025 levels
• Higher than trend GDP (75th
percentile)
• Lower than trend unemployment
rate (25th percentile)
Historical Trend • CMIP5 RCP8.5 multi-model
mean temperature
• Historical mean precipitation
• No additional high water users • Passive savings consistent with demographic growth
• Active savings consistent with
member agency planned annual
measures
• Aligns with real rate increases
presented in SFPUC 10-year
plan (wholesale)
• Historical growth consistent with
trend extrapolation from agency-
approved historical
demographics
• Housing density increases with
housing units (as approved by
member agencies)
• Historical trend GDP and
unemployment rate
DRAFT
Attachment 1