关键词: 地下水, 污染源反演, 粒子群算法, Hooke-Jeeves算法, 逆问题

Abstract: Identification and estimation of the groundwater contaminant source based on the obtained monitoring data is a groundwater inverse deduction problem. These problems can be defined as optimization problems which the location and strength of contaminant sources are taken as the decision variables. In this study, a new method named hybrid Hooke-Jeeves attraction and repulsion particle swarm optimization method (HJ-ARPSO), based on the hybrid HookeJeeves particle swarm optimization method, is proposed and incorporated with the contaminant transport model MT3DMS to identify the location and strength of groundwater contaminant source. In HJ-ARPSO method, the population diversity is guaranteed by combined with repulsive operator in ARPSO. Afterwards, HJ-ARPSO method, HJ-PSO method, and GA method are adopted to identify two source identification cases (under known source position and under unknown source position). Under both cases, HJ-ARPSO method achieved high optimization rate (100 percent and 90 percent respectively); while the optimization rate of HJ-PSO method (without coupling the repulsive operator) is reduced to 60 percent under unknown source position case; among these three methods, the efficiency of the GA method achieved the lowest efficiency. The results indicate that HJ-ARPSO is applicable to groundwater contaminant source identification.

Key words: groundwater, contaminant source identification, particle swarm optimization, Hooke-Jeeves search method, inverse analysis