Advanced Demand Forecasting Methods for Water System Master Planning 2016 NCAWWA-WEA Annual Conference Raleigh, NC Tina F. Whitfield, Ronan Igloria, Chris Behr 2016 HDR, Inc., all rights reserved.
Overview Applications of Risk Based Forecasting Forecasting Methods What is Risk Based Forecasting? Benefits of Risk Based Forecasting
Overview
Overview Demand forecasts commonly prepared for water and wastewater utilities o Assist in long-range planning of capital facilities o Decisions on acquisition of new water supplies A variety of methods are used in the water industry to forecast demands. Recent developments in forecasting methods address uncertainties and risk.
Our utilities need flexible tools to evaluate water demand and determine their best fit capital investments. What s Changing in North Carolina? What Isn t? Per Capita Water Demands are Decreasing Industry Water Use Trends are Changing o Reduced High-Water Use Industries including Textiles Droughts and Climate Change Impacts to Water Supply Planning and Reservoir Operations Infrastructure Dollars are Harder to Come By and Justify o What to Build? o When to Build it? o How Big?
Overview of Forecast Methods
Simple Planning Models Per Capita Models Extrapolate demand based primarily on population growth o Hold other factors constant Straightforward to compute and limited data needs Does not take into account change o Changing Demographics o Changing Water Use Behaviors o Consumption and Peaking Changes o Industrial Drivers Assumes Consumption/Population Growth is Constant over Time
More Complex Forecasting Methods Disaggregated Numerical Models Examines Water Use Sectors Separately o Residential o Commercial o Industrial o Wholesale Permits Different Assumptions about Future Conditions 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 $/ CCF PUB COM NPRO MFH SFH IRR IND 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
Complex Demand Forecasting is a Combination of Art and Science Perform a statistical analysis of demands Identifies variables with high correlation Converts uncertainty to probability and quantity of impact Promotes confidence and communication in forecasting City of Santa Monica Water Master Plan, 2014
What is Risk-Based Forecasting?
Understand the Uncertainty Typical demand forecasts are an estimate of what future demand will be. To understand the uncertainty of future values, it s useful to develop a range of future demand including: o Changing Demographics o Water Use Factors (Per Capita Water Use) o Peaking Factors
What is Risk Based Forecasting? Start with Baseline Demand Forecast o Only an estimate of what future demand might be. Uncertainty Analysis o Develop range of possible future demand o Including Demographic Changes Peaking Factors Water Use Factors o Monte Carlo algorithms to determine overall uncertainty range for demand
What is Risk Based Forecasting?
Benefits of Risk-Based Forecasting
Benefits of Risk Based Forecasting Allows Utilities to Evaluate Various Water Use Scenarios o Water Conservation o Climate o Timing of Growth Improves Understanding of Water Demands for Various Water Use Categories Improves Understanding of Dynamic Trends and How Trends May Change in Future
Benefits of Risk Based Forecasting Wide Application for both Water Supply Planning, Utility Master Planning, and Reservoir Operations Tool to Analyze Alternative Future Scenarios Identifies Data Gaps and Sources of Uncertainty
Applications of Risk- Based Forecasting
Oregon Water Supply and Conservation Initiative Statewide Water Demand Forecasting Tool Objectives Understand water demands for various water use categories in different regions. Understand trends and future uses. Develop tool to examine alternative future scenarios. Identify data gaps and sources of uncertainty. Statewide Demand Assessment Storage Opportunities Oregon Water Supply and Conservation Initiative Conservation Inventory Water Resources Planning Grant Program
Oregon Water Supply and Conservation Initiative Statewide Water Demand Forecasting Tool Water Use Sectors - Municipal and domestic - Industrial - Irrigated agriculture - Other instream (not discussed here) Forecast to 2050 Forecast by county and by basin
Oregon Water Supply and Conservation Initiative Forecast Variables Table 1: Parameters that can be Adjusted for Scenarios Municipal Systems and Domestic Wells Self-Supplied Industry Irrigated Agriculture Initial population Growth rate Indoor per capita water use Outdoor per capita water use Total use in the initial year Percent change over time Initial Irrigated acreage Change in acreage by crop Consumptive use by crop Irrigation efficiency Conveyance efficiency Spatial distribution of irrigated acreage
Oregon Water Supply and Conservation Initiative Statewide Water Demand Forecasting Tool Developed Best Estimate Reference Forecast Evaluated Uncertainty in Input Variables Assessed Effects of Climate Change on Key Variables - Increased outdoor per capita water use; crop consumptive use Assessed effects of a range of water conservation savings over time - Decreased total per capita water usage; increased efficiency (irrigation/conveyance) Demand (acre-feet) 12,000,000 10,000,000 8,000,000 6,000,000 4,000,000 2,000,000 Figure ES-1. Demand Forecast by Water Use Category - Reference Forecast 0 2007 2010 2015 2020 2025 2030 2035 2040 2045 2050 Year Municipal Systems Domestic Wells Industrial Agricultural
Oregon Water Supply and Conservation Initiative Statewide Water Demand Forecasting Tool Forecast scenarios and the forecasting tool are useful for: - Estimating the current magnitude and distribution of water demands - Understanding demand trends for policy discussions Demand (Acre-Feet) 12,000,000 10,000,000 8,000,000 6,000,000 4,000,000 2,000,000 0 Mean Statewide Demand with Uncertainty for All Sectors by Scenario 2010 2015 2020 2025 2030 2035 2040 2045 2050 Years BASE SCENARIO CLIMATE CHANGE SCENARIO CONSERVATION SCENARIO Findings Water conservation significantly reduces water demands in all water use categories Water savings modeled requires substantial changes in how the public uses water, as well as significant investments Climate change was assumed to have a moderate to fairly extreme effect on water use factors
City of Olympia Water System Plan Demand Forecast Uncertainty Analysis Objectives Provides uncertainty range for forecasted demand. Uncertainties evaluated included: Demographics Peaking Factor Water Use Factors Monte Carlo computational algorithms for 50- year forecast
Figure 1. Baseline Demand Forecast Methodology
City of Olympia Water System Plan Demand Forecast Uncertainty Analysis Methodology PERT (Program Evaluation and Review Technique) probability distribution function (pdf) to define uncertainty in key drivers of water demand. Define Range of Values from Historical Data, Utility and Planning Input Most Likely Value Low Values High Values
City of Olympia Water System Plan Output Range of Demands in Planning Horizon with Confidence Intervals 5 th Percentile 50 th Percentile 95 th Percentile Average Day and Maximum Day Demands for 50-Year Planning Window Demand (mgd) 30.0 25.0 20.0 15.0 10.0 5.0 0.0 Actual Forecasted 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050 2052 2054 2056 2058 2060 2062 2064 Year Average Day Demand Maximum Day Demand 95% 5% 95% 5% MDD Baseline Forecast ADD Baseline Forecast
City of Hillsboro Water Demand Analysis 3.50% 3.00% 2.50% 2.00% 1.50% 1.00% 0.50% 0.00% -0.50% -1.00% -1.50% Oregon Metro Base Estimate Oregon Metro 5% Estimate Oregon Metro 95% Estimate 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Objectives Baseline water demand forecast. Statistical model to identify key drivers for several major account categories Uncertainty analysis Develop water demand forecasts per account type as well as total consumption and production
City of Hillsboro, OR Forecast of Total Production Expected total consumption could grow to about 7.6 M CCF (15.6 M MGD) by 2020, but with an 80% uncertainty range (between dashed lines) from about 7 to 9M CCF (14.3 to 18.4 M MGD) Production variability, estimated from data, adds to demand variability Results suggest that annual production is expected to be about 3% higher than consumption from year to year 28
Is Advanced Demand Forecasting the Right Solution?
Challenges to Advanced Demand Forecasting Methods High Data Needs o Past Consumption by Sector o Past and Forecasted Values for: Demographics, Economic and Housing Indicators Water Production, Water Rates Weather Indicators Conservation Data Estimation Complexity Forecasted Margin of Error Grows over Forecast Horizons Requires Familiarity with Risk Analysis Software and Simulation Techniques
Benefits of Advanced Demand Forecasting Greater Statistical Validity and Higher Accuracy Converts Uncertainty to Probability and Quantity of Impact Promotes Confidence and Communication in Forecasting Provides a More Transparent Framework for the Utility Planning Process and Forecasting Capital Investments CAPITAL IMPROVEMENT PROGRAM DEVELOPMENT DEMAND FORECASTING HYDRAULIC MODELING ANALYSIS
Questions and Discussion Acknowledgements: Co-authors: Ronan Igloria and Christopher Behr, HDR