Water (Aug 2022)
Ecological Risk Evaluation of Baihetan Dam Based on Fuzzy Hazard Quotient Model
Abstract
To evaluate the variation in ecological risk induced by pollutants from the construction of Baihetan Dam, the largest hydropower station under construction in the world, this study proposes a fuzzy hazard quotient (HQ) model designed on the basis of triangular fuzzy number (TFN) theory. The fuzzy HQ model uses hazardous TFN to evaluate the ecological risk including uncertain observation data, and the transition TFN to analyze the variation in ecological risk before and after the dam construction. The results show the following: (i) The ecological risk of ammonia nitrogen (NH3-N) showed a marked increasing trend after the construction of the dam because this activity weakened the degradation ability of the water body. The chronic hazard of NH3-N was classified as “medium” grade and its acute hazard was “low” grade. (ii) The crucial acute hazard factor for the local aquatic ecosystem was copper (Cu) and the key chronic hazard factor was lead (Pb). (iii) After the construction of Baihetan Dam, both the long-term and short-term hazardous TFNs of Cu were classified as “medium” grade. The acute hazard of Pb belonged to “low” grade with high certainty, whereas its chronic hazard classification had uncertainties. Its long-term hazardous vectors upstream were {0.000, 0.928, 0.072}, whereas its long-term hazardous vectors downstream were {0.000, 0.108, 0.892}. (iv) Both of the ecological risks of Cu and Pb showed substantial decreasing trends after the construction of Baihetan Dam because the impounding effect of Baihetan Dam promoted the settlement of heavy metals with sediment. (v) The hazardous TFN method can be applied to perform an ecological risk evaluation that accounts for uncertainties in the observation data set, and the transition TFN method can analyze the variation in ecological risk with a small sample size. Therefore, the fuzzy HQ model is effective for the evaluation of ecological risk induced by dam construction.
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