use of intra seasonal and seasonal forecasts to reduce
play

Use of Intra Seasonal and Seasonal Forecasts to Reduce Risk in - PowerPoint PPT Presentation

Use of Intra Seasonal and Seasonal Forecasts to Reduce Risk in Regional Public Water Supply Management Chris Martinez University of Florida Agricultural and Biological Agricultural and Biological Engineering Engineering Overview Project


  1. Use of Intra ‐ Seasonal and Seasonal Forecasts to Reduce Risk in Regional Public Water Supply Management Chris Martinez University of Florida Agricultural and Biological Agricultural and Biological Engineering Engineering

  2. Overview • Project Partners • Project Background & Goals • Methods • Results • Lessons Learned • Relevance Funded by NOAA’s Climate Program Office SARP-Water program Agricultural and Biological Engineering

  3. Percentage of Background Water by Source • Current sources: 1998 • Groundwater (13 wellfields) 100% • Tampa Bypass Canal/Hillsborough River • Alafia River 11% • C.W. Bill Young off ‐ stream reservoir 2008 • Desalination Plant 28% 61% 9% (12-month moving average) 2012 Groundwater Permit Pre ‐ 1998 192 MGD 45.5% 45.5% 1998 158 MGD 2002 121 MGD Agricultural and Biological 2008 90 MGD Engineering

  4. Source Allocation Decisions • Multiple decision scales: • Water year plan (6 ‐ months prior) • Month to month adjustments • Operational decisions (weekly) • Multiple constraints: • Permitted groundwater (12 ‐ month moving average) • Minimum streamflows • Streamflow extraction ratio (maintain Fluoride limit) • Costs of different sources Agricultural and Biological Engineering

  5. Project Goals • Integrate forecast information into decision making – Multiple temporal scales – Relevant spatial scales – Integrate forecasts into suite of models used by Tampa Bay Water • System ‐ wide Decision Support – What is the system ‐ wide benefit/risk of adopting forecast information? – What is the reliability of the current system? – Value judgments under different scenarios? Agricultural and Biological Engineering

  6. Links Between Climate/Hydrologic Information and Decisions by Tampa Bay Water Required Information Decision Climate/Hydrology Time-Scale Set Prices and monthly 18 months •Estimate of initial reservoir volume Source Allocation for in advance •Scenarios of historical conditions water-year •Demand forecasts Update water-year Monthly, •Precipitation and Streamflow Allocations out to 12 forecasts months Operational Weekly, •Precipitation, Streamflow and Allocations out to 4 Demand forecasts weeks Agricultural and Biological Engineering

  7. “Typical” Water Year Reservoir Reservoir Max Min Oct --- Nov --- Dec --- Jan --- Feb --- Mar --- Apr --- May --- Jun --- Jul --- Aug --- Sep Filling Max Reservoir Groundwater Using Reservoir use Max Direct Surface Water use • Estimate of end of year reservoir level needed for plan for next water year • Greater than expected groundwater pumping impacts next water year plan • Seasonal forecasts can be used to determine expected higher/lower groundwater pumping in winter months Agricultural and Biological Engineering

  8. Different Products for Different Time ‐ Scales • Operational – Ensemble Precipitation, Streamflow and Demand forecasts derived from medium ‐ range forecast products • Monthly/Seasonal – Probabilistic Precipitation and Streamflow/Withdrawal Climate ‐ based Forecasts • Water ‐ Year – Decision Support, taking into account previous and next 12 months Agricultural and Biological Engineering

  9. Current Historical Forecast Forecast Analogs Operational Time ‐ scale • +/ ‐ 30 day search window • 100 analog forecasts • Forecast analogs using the ESRL/PSD GFS Retrospective forecast Historical Observations archive (Stations or NARR) 1 ‐ 15 day • 2.5° x 2.5 ° • • 1979 ‐ present Ensemble of • Analog selection can be Hydrologic tailored to need Forecasts http://www.esrl.noaa.gov/psd/forecasts/ Agricultural and Biological reforecast/ Engineering

  10. Precipitation Forecast Skill 0.35 Day 1 Day 2 0.3 Day 3 Day 5 CRPSS: Continuous 0.25 Day 7 Ranked Probability Skill 0.2 CRPSS Score 0.15 0.1 1 0.05 0.8 0 0.6 J F M A M J J A S O N D F(x) ‐ 0.05 0.4 Forecast 0.2 Observation 0 0.35 24 ‐ hr 48 ‐ hr 1 2 3 4 5 6 72 ‐ hr 5 ‐ day 0.3 x week ‐ 1 week ‐ 2 0.25 ∞ 2 [ ] dx ∫ = − 0.2 CRPS F(x) F (x) CRPSS o 0.15 − ∞ 0.1 CRPS 0.05 = − Forecast CRPSS 1 0 CRPS Ref Agricultural and Biological J F M A M J J A S O N D ‐ 0.05 Engineering

  11. Monthly/Seasonal Time ‐ scale • Forecast analogs using CFS retrospective forecast archive http://cfs.ncep.noaa.gov/ – Week 2 – Monthly – Seasonal • Climate ‐ based probability of exceedance streamflow forecasts Agricultural and Biological Engineering

  12. Correlation of Streamflow w/ ENSO Probability of Lagged Niñ03.4 Exceedance Streamflow Forecasts Season Posterior probability of streamflow Streamflow Forecast conditioned on predictor Streamflow Agricultural and Biological Exceedance Probability (%) Engineering

  13. Decision Support + Scenarios • Inputs: – Forecasted Demand – Forecasted Withdrawal • Outputs: – Optimized source ‐ water allocations based on preferences/constraints – End of year reservoir volume Agricultural and Biological Engineering

  14. Lessons Learned • There is a learning curve associated with using weather/climate datasets!!! (for hydrologists/engineers, at least…) • Limited number of forecasted variables archived in retrospective archives may limit usefulness Agricultural and Biological Engineering

  15. Relevance • Tools/approaches that can easily be replicated in other regions – Analog forecasts – Exceedance streamflow forecasts Agricultural and Biological Engineering

Recommend


More recommend