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Optimized Flood Control in the Columbia River Basin for a Global Warming Scenario Se-Yeun Lee1, Alan F. Hamlet 1,2, Carolyn J. Fitzgerald3, Stephen J. Burges1 1. Dept. of Civil and Env. Engineering, UW, 2. CSES Climate Impacts Group, UW, 3. U.S. Army Corps of Engineers, Seattle District Calibration Results In comparison to current flood control curves for 20th century climate (20th_ Scen_CurFC), HEC-PRM derived flood control curves for 20th century climate (20th_Scen_HecFC) show lower storage deficits for major dams in Columbia River Basin and lower flood risks at flood check points: Bonners Ferry, Columbia Falls and The Dalles 1,000 b) 20th Cent_Cur FC a) 3000 Current Climate Sep Sep Arrow Grand Coulee Hungry Horse Libby 40 30 20 10 20th_Cent_CurFC 20th_Cent_HecFC -1 0 1 2 3 4 Storage (KAF) 1,000 1,000 Two penalty functions in the optimization model are calibrated for the 20th century flow regime using the procedure outlined in right figure. The objective function is then held fixed and optimized flood control curves for a climate change scenario are created. Nov Dec Jan 20th_Cent_CurFC 20th_Cent_HecFC -1 0 1 2 3 4 1,000 500 0 Oct Nov Dec Jan Feb Mar Apr May Jun Jul 1200 Aug Sep Month 20th Century 500 200 20th_Cent_CurFC 20th_Cent_HecFC -1 0 1 2 3 4 5 Extreme Value Type I Distribution Reduced Variate, Y 0 Dec Jan Feb Mar Apr Month May Jun Jul Aug Dec Jan Feb Mar Apr May Jun Jul Sep b) Climate Change Scenario 7,000 Apr 6,000 6,000 5,000 5,000 Apr 4,000 3,000 3,000 2,000 2,000 1,000 1,000 0 0 Nov Dec Jan Feb Mar Apr May Jun Jul Oct Nov Dec Jan Feb Mar Apr May Jun Jul Months Simulation Results 3500 3000 2500 2000 1500 1000 500 0 0 500 1000 1500 2000 2500 3000 HH Apr-Jul Flow volume (KAF) Hungry Horse Apr-Jul Flow Volume >2.0 MAF 4,000 3500 Below figures show a) Simulated Storage Deficits for major dams in Columbia River Basin and Flood Frequency Curves at b) Bonners Ferry, c) Columbia Falls and d) The Dalles for simulated 20th century climate using current flood control curves (20th_Cent_CurFC) and the climate change scenario climate using current flood control curves (CC_Secn_CurFC) and HEC-PRM derived flood control curves (CC_Scen_HecFC). 3,000 a) 1,000 0 Oct Nov Dec Jan Feb Mar Apr May Jun Jul Months c) July 31 Average Storage Deficit (KAF) 2,000 b) 2,000 20th Cent_Cur FC CC_Scen_CurFC 1,500 CC_Scen_HecFC 1,000 500 60 50 40 30 20th_Cent_CurFC CC_Scen_CurFC 20 CC_Scen_HecFC 10 0 Mica Arrow Grand Coulee Hungry Horse -2 Libby d) 40 30 20 20th_Cent_CurFC 10 -1 0 1 2 3 4 5 Extreme Value Type I Distribution Reduced Variate, Y 50 Flow at Columbia Falls (kcfs) Maximum Flood Space (KAF) 4,000 Months The flow volumes differ markedly at the two sites. Nov Nov 300 -2 5 400 Oct Oct Jul Months 7,000 400 Climate Change Scenario 800 Jun a) 20th Century Climate The Dalles Left figures show average reservoir inflows to Dworshak and Libby dams corresponding to the historical record and the climate change scenario. Peak flows under the climate change scenario are reduced and occur earlier in the Dworshak spring in comparison with the 20th century climate. Climate Change Scenario May Libby storage (Libby Apr-Aug flow volume >5.5 MAF) A simple climate change scenario was developed using VIC model (See right figure) to test the effectiveness of the approach for developing new flood rule curves that are appropriate for altered streamflow timing. The climate change scenario was created by removing the historic monthly temperature trends from the daily time step forcing data and then increasing temperature to approximately 2° C. The precipitation in each year is assumed to be identical to the unperturbed historical meteorological forcing data. These altered streamflows are then used to drive the reservoir optimization and simulation models. 1,500 Apr 600 To develop continuous flood control curves, the maximum flood space for each water year is determined using the optimization model results. This is then expressed as a non linear function of seasonal flow volume occurring in each water year (see right upper figure). The overall seasonal shape of the rule curve and the typical refill timing at each project was established from the optimized results (with a monthly time resolution) by examining the 50th percentile value, and the nearest end of month date for the initiation of refill was used in the simulations (see right lower figure). This seasonal shape was then scaled to produce the maximum flood space required for each flow condition. 20th Century Mar 5 Creating New Flood Control Curves 2,000 Feb Months Oct 2,500 2,000 1,500 Oct 100 Extreme Value Type I Distribution Reduced Variate, Y Libby 2,500 1,500 Extreme Value Type I Distribution Reduced Variate, Y d) Inflow (KAF) Decrease flood penalties or increase storage penalties 2,000 20 -2 Columbia Falls -2 Inflow (KAF) The U.S. Army Corps of Engineers Hydrologic Engineering Center’s Prescriptive Model (HEC-PRM) is used as an existing monthly time step optimization model for the Columbia basin. Of all penalties representing all purpose of the Columbia River Basin, only flood Set up flood-and storage-related penalty functions control and reservoir refill penalty functions are used here to solve the water allocaRun optimization tion problem in terms of a balance Infer flood control rule curves from optimization run between flood control and reservoir (Optimized FCs) refill. A monthly time step reservoir simulation model for Columbia Apply Optimized FCs into simulation model River Basin (ColSim) is used to test the performance of the new flood Compare simulated flood risks and storage deficits using Optimized FCs with those using Current FCs control curves inferred from optimization runs. No 2,500 3,000 30 Climate Change Scenario Decrease storage penalties or increase flood penalties 3,000 10 Dworshak 0 Tool and Method Stop Mica 3,500 40 Storage (KAF) Jul Aug Jun Aug Apr May Mar Jan Feb Jul Dec Oct Jun May Apr Mar Feb Jan Dec Nov Oct Nov 0 No 0 50 Storage (KAF) 4000 1000 Yes 250 50 2000 Do Optimized FCs show higher storage deficits than Current FCs? 500 Flow at The Dalles (kcfs) 5000 c) Flow at Columbia Falls (kcfs) Reservoir Inflow 6000 Yes 3,500 Bonners Ferry Mar Apr o 7000 Do Optimized FCs show higher flood risk than Current FCs? 750 4,000 4,000 Flow at Bonners Ferry (kcfs) 8000 20th Cent_Hec FC b) Climate Change Scenario 600 Flow at The Dalles (kcfs) Storage o a) 20th Century Climate 60 Flow at Bonners Ferry (kcfs) o Dworshak storage (Dworshak Apr-Jul flow volume >2.6 MAF) Storage (KAF) Average Monthly Storage Deficit (KAF) Anticipated future temperature patterns will cause reduced spring snow pack, earlier melt, earlier spring peak flow and lower summer flow in transient rainsnow and snowmelt areas. In the context of managed flood control, these systematic changes are likely to disrupt the balance food control and reservoir refill in existing reservoir systems . 30000 For example, right figure shows : Current Climate conceptual diagram of operational : + 2.25 C No adaption : + 2.25 C plus adaption changes associated with stream25000 flow timing shifts for a hypothetical dam located on the west slop of the Cascade Mountains. Without 20000 adjustment of refill schedules, the + 2.25 C hypothetical dam does not refill for the altered streamflow timing 15000 simulated for a warming scenario. : By moving the refill timing one 10000 month earlier, however, the hypothetical dam successfully refills for the altered flow regime. This illustration shows that refill timing and evacuation requirement for flood control may need to be modified to adapt to these hydrologic changes associated with global warming. This work poses a significant systems engineering problem especially for large water systems. To solve this problem, there is a need to develop an objective and well-defined method to maintain or improve the current Level of system performance for climate change scenarios for complex flood control system. Using the Columbia River basin (shown in left figure) as an example, an optimization-simulation procedure is used for restoring the balance between flood control and reservoir refill in complex, multi-objective reservoir systems in response to streamflow timing shifts under a simple global warming The Columbia River Basin scenario. Optimization Results Storage (KAF) Overview CC_Scen_CurFC CC_Scen_HecFC 500 400 300 20th_Cent_CurFC 200 CC_Scen_CurFC CC_Scen_HecFC 100 0 -2 -1 0 1 2 3 4 Extreme Value Type I Distribution Reduced Variate, Y 5 -2 -1 0 1 2 3 4 5 Extreme Value Type I Distribution Reduced Variate, Y Conclusions Optimization studies provide an objective method for rebalancing flood control and refill objectives in complex reservoir systems in response to hydrologic changes. The changes in flood control rule curves are different for different projects, corresponding to different changes in flow volume and timing associated with warming in each sub basin. Optimized flood control rule curves show reduced flood evacuation and earlier refill timing; up to one month earlier for a climate change scenario, compared with 20th century climate. For the climate change scenario, optimized flood rule curves decrease storage deficits while providing comparable levels of local and system-wide flood protection in comparison to the current flood control rule curves.