Development and Testing of Alternate Forecast-Based Flood Operations Rules for West Point Lake

Transcription

1 Development and Testing of Alternate Forecast-Based Flood Operations Rules for West Point Lake Dan Sheer and Sam Lebherz HydroLogics John C. Schaake NWS Ret. Wei Zeng Ga, Dept. of Natural Resources November 15, 2016 Presented at the AWRA Annual Water Resources Conference Orlando, Florida

2 Raison D Etre Work funded by the Department of Natural Resources of the State of Georgia The State of Georgia has a substantial interest in improving flood control, water supply, environmental health, power generation, recreation, and other benefits for USACE reservoirs 2

3 NOISE!!! What s good about it? Examining forecast model error (noise) is essential Helps identify what information you can count on in the forecasts Operating rules can be crafted to make best use of that information 3

4 Forecasts Do Not Produce Benefits Unless You Use Them The combination of operating rules and forecasts produces benefits Potential benefits can be evaluated in a simulation model run over the historical record (or synthetic records) Rules can be improved using simulation and/or search techniques This requires historical forecast records or hindcasts (or synthetic forecasts) 4

5 Example: West Point Reservoir Can t use the forecasts to predict how much water is coming (flood), the predictions are not right enough to use in this way Predictions can tell you that a good bit of water is coming for sure This information is very valuable, it means that the risk of not refilling storage for use during drought is very small 5

6 Project Goal Develop forecast based flood rule for West Point reservoir Minimize the flood peak during floods Don t sacrifice other objectives Water supply reliability Power generation Make rule compatible with WCM

7 Initial Forecast Strategy Use 5-day 6-hr SERFC single value inflow forecasts ( ) Predict daily inflow to West Point (calendar days for 5-days) Produce 6hr ensemble inflow forecasts for next 5 days (20 values) base on historic model error Ensemble members generated to preserve daily serial correlation structure 6hr ensemble time distribution controlled by 6hr RFC forecasts

8 10 Years of Archived Forecasts Big Floods Record Droughts 8

9 Comparison of Late September CDFs of RFC Forecasts and COE Observations RFC Daily Forecasts COE Daily Observations

10 To Be or Not To Be Were the flows high or low when the forecasts said they would be high or low at the times that the forecasts are most important?

11 Joint Distribution of RFC Forecasts and COE Observations for Day 2 (z-space) the five day inflow forecasts were far and away the most skillful exactly when they could be most important - prior to flood events

12 Joint Distributions of RFC Forecasts and COE Observations for Late September Day 2 Day 3 Day 4 Day 5

13 Incorporating the forecasts into an operating rule

14 From Ensemble Forecasts to OASIS Simulation Run Input (1) Five day forecasts were generated starting on each day of the record. To the right is a five day forecast for 1/2/2005 and the start of the next five day forecast for 1/3/2005. Each row is a 6 hour period. Each column is an ensemble member (there are 50).

15 From Ensemble Forecasts to OASIS Simulation Run Input (2) The rows were summed for various timesteps (6hr, 24hr, 48hr, etc ) so that percentile series could be created for each of the timestep sums (for example, the 3day sum s 10 th percentile, the 2day sum s 50 th percentile, etc ).

16 OASIS Model Split below Whitesburg Six hour inflows fed into the model below the split. Inflows based on 15 minute USGS gage data at Whitesburg that was shifted based on the expected travel time to West Point.

17 USACE 1984 Water Control Manual Revision for West Point Flood Ops

18 Flood Flows West Point Flood Stage 19ft 47,500cfs West West Point: 47,500 cfs Columbus: 85,000 cfs

19 The Inflow Following Rule

20 Consider the lower end of the high flow forecast Because forecasts of high flows are all but a guarantee of at least substantial flows, possible to begin releasing water earlier than existing, non-forecast based rules specify. Little risk of not being able to return to full conservation pool, if done only when reservoirs are high. Limiting such releases to no more than inflow assures that whatever flood conditions might occur downstream cannot be worse than they would be without the reservoir. Gives the rule a name, the Inflow Following Rule (IFR).

21 Inflow Following Rule - 1 Inflow following means means making releases equal to the inflow (subject to important restrictions) when the forecasts suggests the probability of refill is quite high Begin inflow following when the lower end of the forecast is still sufficiently high When the 3 day cumulative forecast is > 60k AF at the 10 th percentile then begin inflow following if we re close enough to the upper rule. Cap at 20,000 cfs for the 6 hours if we re within 1.0ft of the upper rule Cap at 40,000 cfs for the 6 hours if we re within 0.5ft of the upper rule

22 Inflow Following Rule - 2 Do not release more than the turbine capacity if the projected storage isn t close to a specified threshold. Cap release at the turbine capacity if an occurrence of the 4 day cumulative forecast at the 85 th percentile would not push the reservoir over a high storage threshold (636.5 ft). Limit the inflow following release if the additional water would flood downstream at Columbus. 22

23 Goal: Reduce the Flood Peak West Point Flood Stage 19ft 47,500cfs Reduced the peak flow of the largest flood in the 10 year record by about 15%; 6,800 cfs above flood stage at West Point (54,300 cfs total) to 3,500 cfs below flood stage (44,000 cfs total), when compared to the RiOP

24 Goal: Maintain Storage Reliability No impact on storage during drought of record No impact on exceedance curve of the lower elevations

25 Goal: Minimize the amount of water spilled Total Gen Flow (M AF) COE base Inflow Following trivially higher total flow runs through the turbines in the inflow following run.

26 Lessons Learned Investigation of forecast errors led to the conclusions: 1. Forecasts cannot provide substantial certainty concerning the potential peak magnitude of a coming flood 2. when the forecasts were for high flows, they did provide substantial certainty concerning potential minimum flows

27 Lessons Learned This rule form stands the normal consideration of use of forecasts for flood control on its head. 1. The temptation is to treat a forecast as certainty, and then to make additional releases as needed to minimize peak flow. 2. This rule form proposed does the inverse. It: a. provides for additional releases in advance of floods b. those releases are very unlikely to be detrimental to other objectives. c. It does not try to optimize for the current flood

28 End of Story - Recomendation Start using forecasts everywhere, and formalize their use in Control Manuals ROI will be enormous 28