investigation of data mining method in optimal operation of eyvashan earth dam reservoir based on pso algorithm

investigation of data mining method in optimal operation of eyvashan earth dam reservoir based on pso algorithm

today,  metaheuristic  algorithms  are  considered  one  of  the  most  important  and  appropriate  methods  to achieve good solutions and optimization. in this research, a particle swarm optimization (pso) algorithm with a nonlinear objective function has been used to optimize the reservoir water allocation of the eyvashan earth dam based on the reservoir water balance for irrigation periods (2014-2020).

the results show that the highest agricultural  demand  downstream  of  the  dam  in  june  was  8.96  (mcm).  the  amount  of  reservoir  release calculated by the model to meet the water requirement downstream of the dam (37.80mcm) is much more optimal  than  the  total  amount  of  downstream  needs  (41.03mcm).

also,  the  minimum  amount  of  water shortage due to severe drought while controlling floods is easily possible due to the reservoir's useful volume and the reservoir's annual flow. according to the pso model, in each period of operation of eyvashan earth dam, about 7.9% can be saved in the reservoir release for the needs of downstream agriculture in the months of high water consumption in summer.