Establishing effective warning storage to derive optimal reservoir operation policy based on the drought condition

The conventional discrete hedging model is connected to a drought early warning system (DEWS) and a new concept called effective warning storage (ES). To prepare the desired model, an optimization model (genetic algorithm method) is connected to a simulation model to simultaneously search for threshold values (rule curves) and rationing coefficients as well as ES-related coefficients in the reservoir system of the Jarreh Dam located on the Zard River in southwestern Iran. The advantage of this method over conventional hedging models is that it responds earlier to drought periods and starts rationing earlier. With the application of the proposed rationing model, the objective function i.e., modified shortage index (MSI) in the historical period is better optimized about 6 % than the conventional rationing method, which shows the superiority of the new model in adjustment of large deficiencies and its distribution in other normal periods. The impact of the proposed method on the objective function in the future period is found to be small (about 1 %). It is mainly due to the drastic reduction of inflow to the reservoir in the future period (both in scenarios RCP4.5 and RCP8.5), so that the needs won't be fully met in most of the months. The results show that with the application of the proposed hedging policy, the objective function (MSI) in the historical period and also in the scenario of RCP4.5 and RCP8.5 is improved by 45 %, 21.3 % and 25.7 %, respectively, compared to the standard operation policy (SOP) method. Also, with the application of the hedging policy, the vulnerability of the system has been greatly improved in both the historical and future periods compared to the SOP method. System vulnerability decreases from 0.64 to 0.24 in the historical period while it changes from 0.62 to 0.44 and from 0.6 to 0.41 for the RCP4.5 and RCP8.5 scenarios.