The pollution scale weighting model in water quality evaluation based on the improved fuzzy variable theory

Abstract

Entropy weight model (EWM) is the most widely used objective weighting method for evaluating water quality. However, for the pollutant the data of which concentrate on the high polluted grade, EWM often neglects its importance, for its discrimination degree is low. To solve this problem, a pollution scale weighting model (PSWM) is proposed based on the improved fuzzy variable theory. In PSWM, the importance of the indicator is quantified by its relative membership to the vague concept: “pollution”. The higher the pollution degree is, the larger its weight is; and vice versa. And then, PSWM is applied into the water quality evaluation of Southeastern Poyang Lake. Results are as follows. (1) The relative memberships of CODMn, NH3-N, and TP to the vague concept “pollution” are 0.39, 0.33, and 0.99, respectively. And according to PSWM, their weights are 0.227, 0.193, and 0.580, respectively. (2) The comprehensive water quality indices of the Nanjishan wetland, lake region, Xin River estuary, and Rao River estuary are 36.2, 28.6, 25.7 and 21.1, respectively, all of which belong to “bad” grade. The environment of Southeastern Poyang Lake suffers serious damage, and the aquatic ecosystem faces a high threat. (3) Compared with EWM, PSWM can highlight the seriously polluted index and emphasize its practical significance in water resources management, thereby effectively improving the accuracy and rationality of water quality evaluation.