WeatherShift TM Rainfall

Transcription

1 WeatherShift TM Rainfall Risk-based Resiliency Planning Tool for Drainage Infrastructure Design and Rainfall Harvesting ASCE EWRI Conference, May 2017 Mathew Bamm, PE, Arup San Francisco Courtney King, Arup San Francisco Robert Dickinson, Argos Analytics Bridget Thrasher, Argos Analytics [ contains copyrighted material ]

2 Today s Presentation The Problem? Shifts in rainfall patterns due to climate change The Solution? Risk-based planning using WeatherShift TM Rainfall Case Studies

3 The Problem Every day in the United States, 275,000 Civil Engineers are using weather data that is decades outdated. For example: Intensity-duration-frequency (IDF) curves are used to design/size stormwater infrastructure, but they re based on historical data Image source: Source of employment data: National Council of Architectural Registration Boards and DesignIntelligence ( and US Department of Labor Bureau of Labor Statistics (

4 The Technical Approach Leverage existing tools used by civil engineers and infrastructure planners Use the latest climate projections to modify the historical rainfall data to reflect future climate conditions Manage risks to infrastructure by exploring a range of possible future climate conditions 4

5 The Solution: WeatherShift TM Rainfall Adaptive stormwater management tool utilizing FIDF (Future IDF) curves Developed through Arup Research Funds, in partnership with Argos Analytics >$200,000 invested in WeatherShift: Heat, Rainfall, & TopUp 5

6 Technical Methods: Future IDF (FIDF) Curves Global climate change models from the Intergovernmental Panel on Climate Change (IPCC) s Fifth Assessment Report (AR5) Representative concentration pathways (RCPs): 8.5 & 4.5 RCP8.5 Limited/No Global Emissions Reduction Outcomes from different climate simulations vary RCP4.5 Moderate Global Emissions Reduction

7 Technical Methods: Future IDF (FIDF) Curves Rainfall intensity offsets are derived for a variety of combinations of duration and return time for 21 global climate change models An offset is the difference between a mean value of a climatic variable for projected future time period compared to a simulated baseline (historical) period. Original Morphed P' P D Q' Q D Time (days)

8 Rainfall Intensity Technical Methods: Future IDF (FIDF) Curves Rainfall intensity offsets are derived for a variety of combinations of duration and return time for 21 global climate change models Cumulative distribution functions (CDFs) are constructed from the offset values

9 Rainfall Intensity Technical Methods: Future IDF (FIDF) Curves Cumulative distribution functions (CDFs) are constructed from the offset values Risk scenarios are represented by values extracted from the CDFs for 7 standard percentiles (5 th, 10 th, 25 th, 50 th, 75 th, 90 th, 95 th )

10 Technical Methods: Future IDF (FIDF) Curves Rainfall intensity offsets are derived for a variety of combinations of duration and return time for 21 global climate change models Cumulative distribution functions (CDFs) are constructed from the offset values Risk scenarios are represented by values extracted from the CDFs for 7 standard percentiles (5 th, 10 th, 25 th, 50 th, 75 th, 90 th, 95 th ) Future IDF curves are generated by adding these offset values to historical IDF values WeatherShift TM Rainfall hydraulic modeling analysis utilizes these Future IDF Curves for climate-ready risk management

11 Technical Methods: Future Daily Rainfall Time Series Monthly mean daily rainfall offsets are derived for 27 global climate change models Cumulative distribution functions (CDFs) are constructed from the offset values Risk scenarios are represented by values extracted from the CDFs for 7 standard percentiles (5 th, 10 th, 25 th, 50 th, 75 th, 90 th, 95 th ) Future daily rainfall time series are generated by converting these offset values to percentage changes TopUp TM Rainwater Harvesting Tool utilizes these Future Daily Rainfall Time Series for sizing rainwater tanks

12 Case Study: SFO Terminal 1 Project

13 Precipitation Events Future IDF Curves

14 Case Study Scenarios Case Descriptions GHG Emissions Pathway Year Indicative increase in rainfall intensity (%) 1 50 th Percentile Medium Climate Change Scenario RCP % 2 50 th Percentile High Climate Change Scenario RCP % 3 95 th Percentile High Climate Change Scenario RCP % Cases modeled 2 and year not considered (SFO below 100 year flood elevation) Software Used: Civil 3D 2016 Storm & Sanitary

15 Arup Civil 3D Storm & Sanitary Hydraulic Model Baseline: 5-Year Design Storm

16 WeatherShift 50th Percentile High Climate Change Scenario 5-Year Storm at RCP (~10% more rain)

17 WeatherShift 95th Percentile High Climate Change Scenario 5-Year Storm at RCP (~25% more rain)

18 Insight Summary for SFO Terminal 1 WeatherShift used to Stress Test the proposed drainage design For the 5 year design storm event: o Catch basin location / numbers reviewed to reduce surface ponding o Pipe sizes were reviewed to highlight locations where pipes could be oversized to provide additional resilience Analysis showed design was robust the limited surface flooding is caused by downstream offsite conditions Surface ponding in extreme events has limited impact on airport operations

19 TopUp : Rainwater Harvesting Tool Specific daily rainfall (and drought) record triangulated on rain gauges within a user defined search radius Tank size optimization curve and recommended tank size based on the various project inputs, e.g. daily consumption Other data analytics and resources for implementation 19

20 TopUp : Rainwater Harvesting Tool Volume Efficiency Factor Slope Cistern Volume (g) Optimization Maximize Harvest Balanced Volume and Harvesting Minimize Cost Volume Efficiency Factor: Based on the slope of the curve, TopUp calculates a volume efficiency factor giving the user an idea of how the cistern should be sized to optimize either cost or harvest. 20

21 Example: Rainwater Harvesting, TopUp (2065 RCP 8.5 at 5 th, 50 th, and 95 th percentiles)

22 WeatherShift TM Rainfall Risk-based Resiliency Planning Tool for Drainage Infrastructure Design and Rainfall Harvesting ASCE EWRI Conference, May 2017 Thank you! Any questions? Mathew Bamm, PE, Arup San Francisco Courtney King, Arup San Francisco Robert Dickinson, Argos Analytics Bridget Thrasher, Argos Analytics [ contains copyrighted material ]

23 What Else is Out There? SWMM-CAT in comparison to WeatherShift TM Rainfall Output WeatherShift (Arup/Argos) Intensity-Duration- Frequency (IDF) Data SWMM-CAT/ CREAT 3.0 (US EPA) ii Depth-Frequency Data Climate Data Source IPCC AR5 (CMIP5, 2013) IPCC AR5 (CMIP5, 2013) Global Climate Models Emissions Scenarios Risk Management 1 2 (RCP 4.5 and 8.5) Yes (7 Climate Outcomes per Emissions Scenario) 1 (RCP 8.5) Limited (2 Climate Outcomes per Emissions Scenario) Time Periods 2035 & & 2090 Rainfall Duration (Hours) 3, 6, 12, 24, Resolution ~1.0 o 0.5 o 23 Cost $480 (Starting Price) Free