Changes in Water Use under Regional Climate Change Scenarios (Project 4263) 2013 Water Research Foundation. ALL RIGHTS RESERVED.

Transcription

1 Changes in Water Use under Regional Climate Change Scenarios (Project 4263)

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3 Advances in Water Research

4 Changes in Water Use under Regional Climate Change Scenarios Project 4263

5 Presentation Overview Introduce project team and participants Summarize main study elements Regional scale climate expectations and vulnerabilities Fundamental importance of climate and weather in shaping urban demands Methods for evaluating climate change impacts for individual utilities

6 Financial Support Water Research Foundation Jennifer Warner, WaterRF Research Manager Colorado Springs Utilities

7 Project Team Hazen and Sawyer, P.C. Jack C. Kiefer, Ph.D. (Principal Investigator) John M. Clayton, Ph.D., P.E. Stratus Consulting James Henderson (Co-PI) Benedykt Dziegielewski, Ph.D. Southern Illinois University (retired)

8 Water Utility Participants Colorado Springs Utilities Tampa Bay Water San Diego County Water Authority Albuquerque/ Bernalillo County Massachusetts Water Resources Authority Regional Municipality of Durham (Ontario) Gwinnett County (GA) Southern Nevada Water Authority Las Vegas Valley Water District City of Phoenix Seattle Public Utilities

9 Background Climate and weather affect both the water supply and water demand Most studies to date have been supplycentric Few studies of potential effects of climate change on water demand IPCC identified this as a knowledge gap

10 Background Understanding demand-side impacts and adaptation opportunities is important Fundamental mission of on demand delivery of water Predictions of future (unrestricted) demand drive investment decisions Scenario planning requires consistent and simultaneous analysis of supply and demand

11 Demand-Side Perspective

12 Project Objectives 1. Develop and demonstrate demand modeling/prediction methodologies 2. Compile regionally downscaled climate projections 3. Identify and quantify potential climate change impacts 4. Evaluate demand-side adaptation opportunities and related planning and policy options

13 General Approach Assessment of Broad Regional Scale Vulnerabilities Urban + Non-urban, continental perspective Fundamental Concepts and Analytical Techniques Urban demand only Case Study Assessments Utility service area perspective

14 Regional-Scale Vulnerabilities Climate change will likely exacerbate existing demand pressures Complicating vulnerabilities High rates of population growth Competition for source supply Municipal Agriculture Power Ecological Heavy reliance on surface water sources Emerging 2050 U.S. Megaregions (Source: "Map of Emerging US Megaregions," 2009 Regional Plan Association)

15 Climate, Weather, and Urban Water Demands Reconnaissance-level regional evaluation designed to tell general story Main focus is urban water use Higher resolution data from water utilities both water use and climatic Participating utility data and collaboration Importance of climate to urban water use Water use modeling methods and needs Case studies of climate change scenarios

16 Jan-97 May-97 Sep-97 Jan-98 May-98 Sep-98 Jan-99 May-99 Sep-99 Jan-00 May-00 Sep-00 Jan-01 May-01 Sep-01 Jan-02 May-02 Sep-02 Jan-03 May-03 Sep-03 Jan-04 May-04 Sep-04 Jan-05 May-05 Sep-05 Jan-06 May-06 Sep-06 Jan-07 May-07 Sep-07 Jan-08 May-08 Sep-08 Jan-09 May-09 Sep-09 Jan-10 May-10 Sep-10 MGD, Degrees F Climate and Seasonality in Water Use MWRA 350 Massachusetts Water Resources Authority Monthly Water Supplied to Revenue Customers (MGD) 300 Water Supplied Average Maximum Daily Temperature 50 0 Water Supplied Avg Max Temp

17 Climate and Seasonality in Water Use Colorado Springs

18 Oct-91 Apr-92 Oct-92 Apr-93 Oct-93 Apr-94 Oct-94 Apr-95 Oct-95 Apr-96 Oct-96 Apr-97 Oct-97 Apr-98 Oct-98 Apr-99 Oct-99 Apr-00 Oct-00 Apr-01 Oct-01 Apr-02 Oct-02 Apr-03 Oct-03 Apr-04 Oct-04 Apr-05 Oct-05 Apr-06 Million Gallons per Day (MGD) 400 Climate and Seasonality in Water Use Tampa Bay Water Tampa Bay Water Monthly Water Deliveries (Oct Sep 2006) Apr 300 May May May May May Jun Jun Apr May May May May May May Deliveries Poly. (Deliveries)

19 Demand Variability Explained by Climate Climate typically Estimated Decomposition explains of > Variation 50% of in demand De-trended variability Monthly Water within Production a given for Selected utility Utilities Decomposition of Variation in De-trended Series Agency % Seasonal % Other San Diego County Water Authority Deliveries 58% 42% Use (includes member supplies) 86% 14% Tampa Bay Water 46% 54% Massachusetts Water Resources Authority 71% 29% Region of Durham Ontario 73% 27% Seattle 82% 18% Colorado Springs 86% 14% Gwinnett County 58% 42% Southern Nevada 96% 4% Phoenix (total sales) 93% 7%

20 Average Gallons per Capita Day Estimated Average Single-Family Water Use per Capita for Selected Regions (gallons per capita day) Phoenix and Las Vegas cool/dry winters very hot/dry summers 50 0 jan feb mar apr may jun jul aug sep oct nov dec Phoenix Southern Nevada

21 Average Gallons per Capita Day Estimated Average Single-Family Water Use per Capita for Selected Regions (gallons per capita day) Gwinnett County: much wetter year-round 50 0 Albuquerque, Colorado Springs, and Gwinnett County: cold winters/hot summers jan feb mar apr may jun jul aug sep oct nov dec Phoenix Southern Nevada Gwinnett Co. GA Colorado Springs Albuquerque

22 Average Gallons per Capita Day Estimated Average Single-Family Water Use per Capita for Selected Regions (gallons per capita day) Tampa and San Diego: Mild winters/hot summers Similar winter precipitation Opposite summer precipitation jan feb mar apr may jun jul aug sep oct nov dec Tampa Bay Water San Diego County Phoenix Southern Nevada Gwinnett Co. GA Colorado Springs Albuquerque

23 Estimated Average Single-Family Use Per Capita (gallons per capita per day) 250 Scatterplot of July Use and "Cumulative Deficit" Estimates y = x R² = Southern Nevada San Diego County Colorado Springs Albuquerque Phoenix Tampa Bay Water Gwinnett County Heat and moisture together explain large geographical differences in water use Estimated July "Cumulative Deficit" (inches)

24 Case Study Development Process

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26 Case Study Utilities Case Study Utility Pre-existing water demand model used? Pre-existing Long-term Demand Forecast Scenario? Colorado Springs Utilities (CSU) No No Durham, Ontario, CA (Durham Region) No No Massachusetts Water Resources Authority (MWRA) No No Southern Nevada Water Authority (SNWA) Yes No San Diego County Water Authority (SDCWA) Yes Yes Tampa Bay Water (TBW) Yes Yes

27 Case Study Development Process

28 Selection of Climate Scenarios Bias-Corrected Constructed Analog (BCCA) section of the World Climate Research Programme's Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset Daily time scale at 1/8 degree geographic grid resolution Projections for Tmin, Tmax, Precip Projections for 2 time slices 2055 slice: 2046 through slice: 2081 through 2100

29 Selection of Climate Scenarios Select one or more grid cells Typically grid cell(s) containing weather station(s) used for historical weather

30 Selection of Climate Scenarios Compile and analyze downscaled projections for: 9 GCM s with multiple model runs 2 GHG emissions scenarios

31 Selection of Climate Scenarios Cool/Wet Medium Hot/wet Cool/Dry Hot/dry

32 Modeling Emphasis: Portraying Variability and Uncertainty Historical record for observed weather 20-year time series of each projection time slice Ability to evaluate variability and overlap distributions of projected and historical weather

33 Case Study Development Process

34 Modeling Demand Response to Weather Several statistical estimation methods Generally involves regression analysis (linear, nonlinear) Choice of technique, time scale depends on both technical and practical factors Amount of available data Dimensions of available data (e.g., time-series, spatial, cross-sectional) Amount of time to invest in complexities of statistical inference and forecasting

35 Measures/Specifications of Temperature Precipitation ET 0 Weather and Climate Weather variable choices must consider availability and/or ability to derive from climate projections Precipitation event thresholds Spells Dry/wet Hot/cool Treatment of systematic seasonal effects Departures from normal

36 General Model Development Approach Detrend historical demand: remove base (weather insensitive) demand

37 General Model Development Approach Detrend historical demand: remove base (weather insensitive) demand

38 General Model Development Approach Model weather-sensitive demand as function of historical weather Temperature, precipitation in current and/or previous weeks (days, months) Test for nonlinearities Evaluate and account for seasonality

39 Modeling Emphasis: Temperature as an Instrument for Seasonality Breakpoint Temperature: F

40 Modeling Emphasis: Temperature as an Instrument for Seasonality Define dry periods Evaluate behavior of water use relative to temperature Fit piecewise linear functions Identify optimal breakpoints

41 Case Study Development Process

42 Range of Estimated Mean Annual Impacts: 2090 GHG Scenarios

43 Summary of Mean Estimated Changes in Annual Demand Utility Colorado Springs Utilities Durham Region (Ontario) Mean Estimated Demand 2055 Climate (%) Mean Estimated Demand 2090 Climate (%) Min Max Min Max 5.9% 23.2% 7.7% 45.0% 1.6% 4.3% 2.0% 8.3% MWRA (Massachusetts) 1.7% 5.0% 2.5% 9.1% SNWA (Nevada) 3.9% 9.4% 5.2% 15.5% San Diego County 3.5% 12.7% 9.2% 23.7% Tampa Bay Water 1.2% 5.3% 2.1% 9.9%

44 % change in demand Range of Estimated Mean Seasonal Impacts (2090 Hot/Dry) 60% 50% 40% 30% 20% 10% 0% -10% Average Changes in Demand by Season, 2090 Hot/Dry CSU Durham MWRA SNWA SDCWA TBW Winter 25.6% 0.6% -0.3% 27.2% 23.7% 8.0% Spring 54.3% 9.5% 11.1% 14.6% 24.8% 10.9% Summer 52.4% 17.8% 16.4% 11.2% 24.6% 15.3% Fall 35.3% 3.5% 6.8% 17.1% 20.8% 5.6%

45 Range of Estimated Winter (Jan-Mar) Impacts: 2090 Hot/Dry Climate Scenario Winter Season 2090 Hot/Dry Scenario Mean Temperature Mean Precipitation Mean Estimated Demand F % Inches % % Colorado Springs Utilities 15 32% % 26% Durham Region 15 45% % 1% Massachusetts Water Resources Authority 11 27% % 0% Southern Nevada Water Authority 10 15% % 27% San Diego County Water Authority 7 10% % 24% Tampa Bay Water 6 8% % 8%

46 Range of Estimated Summer (Jul-Sep) Impacts: 2090 Hot/Dry Climate Scenario Summer Season 2090 Hot/Dry Scenario Mean Temperature Mean Precipitation Mean Estimated Demand F % Inches % % Colorado Springs Utilities 18 22% % 52% Durham Region 13 17% % 18% Massachusetts Water Resources Authority 11 14% % 16% Southern Nevada Water Authority 12 12% % 11% San Diego County Water Authority 12 14% % 25% Tampa Bay Water 10 11% % 15%

47 Modeling Emphasis: Portraying Variability and Uncertainty Predicted demand under historical weather versus projected weather Wider gaps between distributions: greater statistical significance of future climate impacts

48 How does variability in future climate scenarios compare with socioeconomic uncertainty? Probabilistic tool used by Tampa Bay Water helps address this question

49 Example of Probabilistic Assessment Shift in mean of forecast distribution equivalent to ~1 standard deviation of existing interval forecast Widening of forecast distribution under 2090 Hot/Dry scenario

50 Examples of Equivalence and Offset Analyses Estimated increase in use equivalent to 16 percent increase in customers today Doubling of housing density completely offsets estimated increases in residential use 50% increase in inflation adjusted prices above forecast assumptions would offset projected increases

51 Demand-Side Adaptation New plantings that match new climate Increases in indoor efficiency Market-based factors Pricing and cost of service Land use and development characteristics Migration and production patterns Behavioral change

52 Demand-Side Adaptation Economic value of water may increase to maintain quality of life More economic benefits (and higher willingness to pay) may Justify additional supply investments Exacerbate supply pressures Lead to changes in water management policies (local and regional)

53 Summary and Conclusions Climate explains significant portion of large geographical differences in water use If climate changes then should expect changes in water demand Models based on the relationship of historical climatic data to water demand critical starting point

54 Summary and Conclusions Case studies suggest upward pressure in weather-sensitive demands Some scenarios suggest a significant alteration in climate relative to historical observations If some scenarios were to occur, significant adaptations will certainly follow

55 Recommendations Utilities should spend more resources studying and modeling climate- and weather-induced water demand More thorough understanding of the importance of historical and future climate in shaping water demands relative to longerterm socioeconomic factors

56 Recommendations More research to evaluate climate scenarios with respect to the possible duration and frequency of future droughts Low confidence in using daily climate projection data to characterize annual or multi-year droughts Lengths of projected hot/dry spells examined in this study far exceeded historical experience Suggestive of more severe and longer-lasting droughts occurring under future climate

57 Recommendations WaterRF 4263 demand-centric demonstration of methods for evaluating potential climate change impacts More research on integrated demandsupply simulations needed to address implications of drought, long-term reliability, and adaptation alternatives

58 Recommendations Continual measurement and monitoring of water demand and climate trends should become an established part of the water industry s research and development portfolio

59 Thank You! Jack C. Kiefer, Ph.D John M. Clayton, Ph.D., P.E

60 Thank You Jennifer Warner Research Manager