Optimization of Reservoir Operation using a Bioinspired Metaheuristic Based on the COVID-19 Propagation Model

Recently, global warming problems with rapid population growth and socio-economic development have intensified the demand for water and increased tensions on water supplies. This research evolves the Multi-Objective Coronavirus Optimization Algorithm (MOCVOA) to obtain operational optimum rules of Voshmgir Dam reservoir under the climate change conditions. The climatic variables downscaled and predicted by the Bias Correction Spatial Disaggregation (BCSD) method of MIROC-ESM model, was introduced into the Extreme Learning Machine (ELM) modelto evaluate the future runoff flowing into the reservoir. The model objective functions included minimizing vulnerability and enhancing reliability indices during baseline and climate change periods. Results revealed that under climate change conditions, the river flow would decrease by 0.17%, increase the temperature up to 2°C and decrease the rainfall by 23.8%, corresponding to the baseline period. Moreover, the extent of vulnerability index variations in the baseline and climate change conditions were also determined as 20-38% and 13-40%, respectively. The reliability index changes under the baseline and climate change conditions obtained were, 57-85% and 40-91%. Therefore, the vulnerability index was also measured at 33% and 30% for baseline and climate change conditions, respectively, with 80% of reliability index. Finally, the comparison of reservoir performance in meeting the water needs of downstream lands at the Pareto point of 80% reliability under both conditions indicated that the reservoir release rate would be more in line with the demand in the climate change conditions.