Use of Historical Weather Data in Planning a Diverse Water Supply System in an Uncertain Climate Future

Transcription

1 Use of Historical Weather Data in Planning a Diverse Water Supply System in an Uncertain Climate Future Presenter: Ding Chan (City West Water) Stormwater Vic Conference May 2017

2 Problem Statement How will Climate Change impact City West Water s water supply services? Specifically, can we estimate what the peak, seasonal and annual demands under a reasonable climate change scenario might be? How can a diversity of water supplies help in addressing these impacts?

3 Input Data Sources Bureau of Meteorology Population Forecasts REUMS Study 2011 DELWP Forecast (climate scenarios) PI Data (Scada) CWW Demand Assumptions Manual Western Growth Corridor

4 Modelling Excel Demand Model Development Develop a climate vs. water use model using historical data Develop a daily demand model correlating to climate variables (precipitation, temperature) Forecast water demand under a range of climate change scenarios Develop relationship with consumption vs. climate variables Determine Potable & Alternative Water overall demands Develop daily demand profile

5 Modelled Variables Temperature, Rainfall, Consumption River basin Average Daily Temperature Change relative to current climate baseline ( o C) Year 2040 Year th 50 th 90 th 10 th 50 th 90 th Low Medium High Low Medium High Werribee River basin Average annual Rainfall Change relative to current climate baseline (%) Year 2040 Year th 50 th 90 th 10 th 50 th 90 th Low Medium High Low Medium High Werribee 2.2% 2.7% 11.7% 2.4% 6.2% 21.4% Consumption Litre per day Maximum Temperature Max Temp

6 Data Preparation Gaps in BoM data Separate non-residential water usage Water Supply Zones & Billing Data

7 kl/p/qtr Climate Variance Variance of consumption based on seasonality Quarterly Consumption in Water Zones JUL OCT JAN APR JUL OCT JAN APR JUL OCT JAN APR ALTONA KEILOR EAST WERRIBEE Consumption per capita per quarter (kl) Consumption per capita per quarter (kl) Temperature ( C) Essendon Laverton Werribee Rainfall (mm) Essendon Laverton Werribee

8 Demand Profile 250 Two Step Process Validation ( ) Calibration ( ) Actual vs Modelled Base Demand Volume (litres per capita per day) Volume (litres per capita per day) Date Actual Model Actual Date Model

9 Modelled Results 400 Actual vs Modelled Total Demand Key Modelling Variables Value Optimal Value Volume (litres per capita per day) /1/2011 1/1/2012 1/1/2013 1/1/2014 1/1/2015 1/1/2016 Actual Date Model Multiple R R Square NSE Coefficient (Calibration period) Seasonal Demand NSE Coefficient (Validation period) Seasonal Demand NSE Coefficient (Total Period) Seasonal Demand NSE Coefficient (Calibration period) Base Demand NSE Coefficient (Validation period) Base Demand

10 Climate Change Impacts Total Residential Demand (GL/year) Total Residential Demand (GL) Increase impacts PW Low Demand PW Medium Demand PW High Demand RW Low Demand RW Medium Demand Existing Demand Climate Change Impact Category (lpcd)* Baseline Climate Change (10 th Climate Change (50 th Climate Change (90 th Percentile) % Max Difference (Average) Percentile) Percentile) Average daily demands % Average monthly demands (litres) 5,756 5,801 5,818 5, % Average winter (base) demands daily Average summer demands daily % Average autumn demands daily % Average spring demands %

11 Alternative Water Demands Small change in Total Water Demand Climate Change Variation Value Daily variation 88% to 87% Monthly variation 2% to 0% Annual variation 2% Method 10 th Percentile 50 th Percentile 90 th Percentile Modelled Climate % Diff Climate % Diff Climate % Diff Demand Scenario (GL) Change Change Change (GL) (GL) (GL) Low % % % Medium % % % High % % %

12 Conclusion & Next Steps Based on this methodology, the impact of climate change on overall demand is small Continue to refine model using latest data and climate change predictions Peer review the model Build dynamic Stormwater Catchment Model Optimise ewater Source Model with climate data