Optimization of artificial recharge of groundwater system based on parallel genetic algorithm - a case study in the alluvial fan of Yongding River in Beijing
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Abstract:
Artificial r echar ge is one o f t he most efficient appro aches to increase the aquifer g ro undwater sto rag e. In o rder to eval2 uate t he max imum recharg e rate o f t he artificial r echar ge sy stem to g ro undwater , an optimization mo del o f ar tificial recharg e sy stem was dev elo ped for the alluvial fan in the Yongding river of Beijing, where gr oundw ater is o ften ov er extr acted. Mean2 w hile, a gr oundw ater flow mo del w as integ rated into t he optimization mo del to predict the r esponse o f g ro undw ater to the artifi2 cial scheme. T he g ro undwater model r esult s w ere used as the co nstr aint co ndit ions in t he o ptimizat ion model, which was solved by the g enet ic alg or ithm( GA) . Roulette w heel selectio n was used for GA, and penalty functio n method w as used to so lve the co nstr aints of the optim izat ion pr oblem. T he optima l results indicated that the o ptimal artificial r echar ge system can incr ease the aquifer gr oundwat er stor age effectively . T he aquifer stor age can increase from 127. 42@ 106 m3 and 243. 48 @ 106 m3 to 140. 46@ 106 m3 and 275. 55@ 106 m3 under tw o r echarg e schemes w ithout ex ceeding the upper limit of gr oundwat er level, and g roundw a2 ter lev el can incr ease 26 m after the optimization. The pro po sed optimizatio n model is able to determine the o ptimal recharg e scheme effectively.
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