Fuzzy Hierarchy Comprehensive Evaluation of Water Quality in Different Lake Regions of Taihu Lake

Abstract

Taihu Lake can be divided into several different lake regions such as bay area, center area, lakeshore area and etc. according to the hydrodynamic characteristics and the lake morphology. In the year of 2010, water quality were measured in 17 sampling points, consisting of 8 points in the Zhushan Lake bay, 3 points in the western lakeshore area, and 6 points in the center area. The fuzzy hierarchy comprehensive evaluation model was used to assess the water quality in different lake regions on the basis of the measured data. This method is a combination of fuzzy evaluation to determine membership degree and Analytic Hierarchy Process (AHP) to determine weight. AHP can be further reduced to these steps such as the goal defining, hierarchy establishing, judgment matrix building, hierarchy single ranking, hierarchy general ranking and uniformity inspecting. The results show that water quality of Zhushan Lake bay is in class Ⅴ except for some points in class Ⅳ. Water quality of center area is between class Ⅱand Ⅳ, and that of lakeshore area is in class Ⅴ. The water quality assessment on the different lake regions by this method can more practically reflect the water environmental status of Taihu Lake. This works contributed to the improvement of water quality assessment exactness and lake eutrophication controlling in the situation of the lake with large area.

Weighting Methods and their Effects on Multi-Criteria Decision Making Model Outcomes in Water Resources Management

“…5. SMART is a useful technique since it is simple, straightforward and requires less time in decision making that is quite important for those involved in the decision-making process (Gu et al 2012). 6.…”

“…7. Using SMART in performance measures can be a better alternative than other methods (Gu et al 2012). 8.…”

“…9. SMART has been successfully applied in MCDM problems, this approach is ineffective when dealing with the inherent imprecision of linguistic valuation in the decision-making (Gu et al 2012;Chen and Hou 2004). 10.…”