Drivers and Influencers of Water Demand Criteria for Selecting ‘Best’ Water Demand Forecasting Approach l Goals & Objectives u What information is needed by planners and decision-makers? u What type of models are needed to provide this information? l Data Availability u What is available? u What is the quality? u What models will the data support? l Budget u What are financial constraints? Goals Goals Data Data Budget Budget Water Demand Forecast Approaches Cost & Complexity Cost & Complexity Low Low High High Trend Trend Extrapolation Extrapolation Per Per Capita Capita Unit Unit Use Use Econometric Econometric Trend Extrapolation 0 50 100 150 200 250 1 98 0 1 98 5 19 9 0 19 9 5 2000 2005 2 01 0 2 01 5 20 2 0 Historical Linear Trend Pros: l Only historical demand data required l Very low cost Cons: l Assumes past trend carries into the future l No ability to “explain” water demands l Cannot account for changes in demographics, weather, or other factors Approach: Per Capita Approach: l Divide historical total demand by population to get per capita use l Multiply per capita use by projected population to get future demand Pros: l Simple to understand l Allows for main driver, population, to be accounted for Cons: l Demands do not always follow population growth l Does not account for factors such as price, income, types of housing, employment trends, or other influencers of demand 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 1980 1983 1986 1989 1992 1995 1998 2001 2004 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 4,000,000 4,500,000 Water Demand Population Unit Use Pros: l Allows for all major sectors & drivers of water demand to be accounted for Cons: l Water use factors, such as weather, income, price and others are not incorporated Approach: l Get sector demands (e.g., single- family, multifamily, non- residential) l Divide each sector demands by appropriate drivers (e.g., housing or employment) to get unit use Example: Example: Single Single - - family demand = 150 MGD family demand = 150 MGD Single Single - - family homes = 500,000 family homes = 500,000 Unit use = 150,000,000 gal/day Unit use = 150,000,000 gal/day ÷ ÷ 500,000 homes = 500,000 homes = 300 gallons/home/day 300 gallons/home/day Econometric Approach: l Statistically correlates sector water demands with factors that influence those demands l For each water use factor, an elasticity is estimated l Elasticities change the unit use rates over time Pros: l Site specific statistical estimation of demand and its influencers l Significant ability to “explain” water use over time l Allows for probabilistic results Cons: l Data intensive l More costly to produce than other methods Elasticity Defined: A statistical rate of change that describes how a water use factor influences demand. A price elasticity of -0.10 means that a ten percent increase in real price will result in a one percent decrease in water demand Example Elasticities The following are elasticities estimated for water use factors from almost 200 statistical water demand equations in the United States Water Use Factor Water Use Factor Winter Season Winter Season Summer Season Summer Season Marginal Price Marginal Price - - 0.050 0.050 to to - - 0.250 0.250 - - 0.150 to 0.150 to - - 0.350 0.350 Income Income +0.200 +0.200 to +0.500 to +0.500 +0.300 to +0.600 +0.300 to +0.600 Household Size Household Size +0.400 +0.400 to +0.600 to +0.600 +0.200 to +0.500 +0.200 to +0.500 Housing Density Housing Density - - 0.200 0.200 to to - - 0.500 0.500 - - 0.400 to 0.400 to - - 0.800 0.800 Precipitation Precipitation - - 0.010 0.010 to to - - 0.150 0.150 - - 0.050 to 0.050 to - - 0.200 0.200 Temperature Temperature +0.300 +0.300 to +0.600 to +0.600 +0.800 to +1.500 +0.800 to +1.500 ( ( Paredes Paredes , 1996). , 1996). Probabilistic Results from Econometric Forecasts 2010 2060 2030 Water Demand (mgd) B a s e l i n e F o r e c a s t B a s e l i n e F o r e c a s t R a n g e d u e t o h i s t o r i c a l w e a th e r R a n g e d u e t o h i s t o r i c a l w e a th e r R a n g e d u e t o d e m o g r a p h i c R a n g e d u e t o d e m o g r a p h i c g r o w t h u n c e r t a i n t y g r o w t h u n c e r t a i n t y R a n g e d u e t o c l i m a t e c h a n g e R a n g e d u e t o c l i m a t e c h a n g e 75% 75% 50% 50% 95% 95% Ranges of Uncertainty: @Risk Model vs. All High/All Low Assumptions 0 25 50 75 100 125 150 175 200 225 250 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 Annual Average MGD 90th-95th 85th-90th 80th-85th 75th-80th 70th-75th 65th-70th 60th-65th 55th-60th 50th-55th 45th-50th 40th-45th 35th-40th 30th-35th 25th-30th 20th-25th 15th-20th 10th-15th 5th-10th Zero-5th Percentile Actual Demand Firm Yield Oal Forecas t 5th Percentile Forecas t All Low (≈0% probability) All High (≈0% probability) 95th Percentile Forecas t Draft Official Forecas t Growth in Population & Water Consumption 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 0 30 60 90 120 150 180 210 1975 1980 1985 1990 1995 2000 2005 Population Annual MGD Population Total Consumption Billed Consumption Non-Rev Per capita Implications Actual and Forecast Water Consumption Per Capita: Seattle & Non-CWA With and Without Programmatic Conservation after 2005 0 20 40 60 80 100 120 140 160 180 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 GPD per Person GPD per Person WITHOUT Conservation GPD per Person WITH Conservation Actual GPD per Person Impact of All Forms of Conservation on Past and Forecast Water Demand 0 25 50 75 100 125 150 175 200 225 250 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 Annual MGD Unattributed Savings Transitory Savings Conservation Programs Plumbing Code Rate Impacts System Operation Improvements 1990 Forecast with No Conservation Actual Demand 2007 Forecast with Conservation 38 40 42 44 46 48 50 52 54 2004 2005 2006 2007 2008 2009 2010 2011 2012 2004TSP Composite Projecti on 2004 Financial Forecast Actual Demand Cascade average daily demand (mgd) Three-stage supply evaluation Screening: Eliminates projects that are not feasible and do not warrant further investigation, using pass/fail criteria Multi-Criteria Analysis : More refined analysis that evaluates projects using multiple ranking criteria Detailed Evaluation Detailed infrastructure and financial evaluation of the highest ranked projects # Name Description 10 Everett - Sultan River Supply Expansion Increase withdrawals from the Sultan River Basin (need further information on conveyance concept) 13 Lake Sammamish Develop supply from Lake Sammamish with Treatment Facility 14 Off-Stream Storage Impound water from tributaries in the high flow season and used to satisfy irrigation needs 18 OASIS – Phases 1 & 2 Members utilize Lakehaven's ASR program water (directly, or via water swap between green river supply and ASR groundwater) 22 Water from Puget Sound Construct a desalination plant either alone or in partnership with others. Construct conveyance. 25 South Treatment Plant Expand reclaimed water uses in Tukwila from South Plant. 30 Rainwater Collection Collect and store rainwater fo up to 7 Golf Courses 33 Regional Unaccounted- for Water Reduce transmission and storage losses from regional facilities Legal Permit. W. Rights Tech. Yield Location Overview of Approach l Identify water supply alternatives l Determine levelized unit costs to capture life- cycle costs to utility, both capital and O&M l Determine non-monetary values, benefits and impacts of each alternative using value model l Compare alternatives using value scores and levelized unit costs Value Modeling Overview l Identify objectives or criteria important in selecting preferred alternative l Define how these objectives will be measured and scored—can be simple 1-5 scale with endpoints defined. l Assign weights to the objectives l Score each alternative, or package of alternatives, and document reasoning l Determine single value score l Test sensitivity of results to weights and scores l Criterium Decision Plus (CDP) software aids in this process Political Acceptability Public Acceptability (Stakeholders) Public Trust 30 Built Environment Natural Environment Environmental Acceptability of Construction 20 Timing Reliability Leads to Other Sources Asset Reliability 20 Legal/ Regulatory 30 Ease of Source Development 45 Natural Environment Secondary Impacts and Benefits/ Sustainability Environmental Acceptability 25 System Robustness Operational Flexibility Security Asset Reliability 25 Public Trust 25 Regulatory Compliance Source Compatibility Public Health/WQ 15 Social (Lifestyles) 10 System Operation 55 Value Model SPU Water Supply System Options Value Model Criteria and Weights Value Model Contributions to Value Score 0.0 0.2 0.4 0.6 0.8 0.0 0.2 0.4 0.6 0.8 Legal/Regulatory Env. Acceptability Public Trust (Develop) Asset Reliability (Ops) Pub. Health (WQ) Asset Reliability (Dev) Others 1.0 is best outcome, with positive consequences 0.0 is worst outcome, with negative impacts [...]... $5.80 - $10.94 Lake Youngs Drawdown SF Tolt 1660 0.5 0.4 Cedar Dead Storage 0.3 North Fork Tolt Snoqualmie Aquifer 0 .2 Low Value Low Cost 0.1 Low Value High Cost 0.0 0.0 a 0.5 1.0 1.5 2. 0 2. 5 3.0 Levelized Unit Cost (PVm$/PVmgd)a Calculated assuming all sources online in 20 50 *4 mgd conservation program begins in 20 45 and phases in over a 10-year period 3.5 4.0 Preliminary Ranking of Supply Options... No Treatment (Indian Spr) 10% 5% 20 % 12% 20 % 13% Small Seawater Desalination 20 % Large Seawater Desalination Within City Wells, Treatment, Not Sustainable Within City Wells, Treatment Within City Wells, No Treatment Treatment for Inactive, Sustainable Wells Replacement Wells, No Treatment Cost Supply Legal Institutional Environment Regulatory Permitting 0.00 0.10 0 .20 0.30 0.40 0.50 0.60 0.70 0.80... 1695 0.5 Lake Youngs SF Tolt 1660 0.4 Cedar Dead Storage 0.3 Snoqualmie Aquifer NF Tolt Diversion 0 .2 0.1 Low Value Low Cost Low Value High Cost 0.0 0.0 0.5 1.0 1.5 2. 0 2. 5 3.0 3.5 Levelized Unit Cost (PVm$/PVmgd)a 4.0 a Calculated assuming all sources online in 20 50 4 mgd conservation program begins in 20 45 and phases in over a 10-year period SPU Water Supply Sources Value-Cost Tradeoff 1.0 High Value... 0.40 0.50 0.60 0.70 0.80 0.90 Climate Change Planning l l l l Downscaling of International Climate Models Up scaling of Local Hydrologic Models Used the Expertise of the University of Washington Climate Impacts Group Used Scenario Planning Because of the Uncertainties . @Risk Model vs. All High/All Low Assumptions 0 25 50 75 100 125 150 175 20 0 22 5 25 0 1995 20 00 20 05 20 10 20 15 20 20 20 25 20 30 20 35 20 40 20 45 20 50 20 55 20 60 Annual Average MGD 90th-95th 85th-90th 80th-85th 75th-80th 70th-75th 65th-70th 60th-65th 55th-60th 50th-55th 45th-50th 40th-45th 35th-40th 30th-35th 25 th-30th 20 th -25 th 15th -20 th 10th-15th 5th-10th Zero-5th Percentile Actual. and Without Programmatic Conservation after 20 05 0 20 40 60 80 100 120 140 160 180 1990 1995 20 00 20 05 20 10 20 15 20 20 20 25 20 30 20 35 20 40 20 45 20 50 20 55 20 60 GPD per Person GPD per Person WITHOUT . Person Impact of All Forms of Conservation on Past and Forecast Water Demand 0 25 50 75 100 125 150 175 20 0 22 5 25 0 1975 1980 1985 1990 1995 20 00 20 05 20 10 20 15 20 20 20 25 20 30 Annual MGD Unattributed