Uncertainty analysis of impact factors of eco-environmental vulnerability based on cloud theory. (March 2020) - Zhang, Hongyang; Wang, Tongtong; Ding, Zelin; Zhang, Xianqi; Han, Liwei
Highlights: Constructed the cloud model scale criterion and calculated the weight of the cloud model. The results were got by calculating the Ex, the En and the He of the cloud model. Use the expert scoring mechanism to ensure the objectivity of the scoring results. The numerical features combine the randomness and ambiguity of the evaluation results. Abstract: This paper studied water source area of the Central Line Project of South-to-North Water Diversion. It built an assessment indicators system on eco-environmental vulnerability of water source area which includes four levels target layer, effect layer, state layer and response layer. Aiming at the uncertainties of experts score on effect layer, state layer and response layer in the analysis and evaluation of eco-environmental vulnerability in water source areas, it built a cloud model-based scale criterion for eco-environmental vulnerability analysis of water source areas based on the index scale. The discreteness, ambiguity and randomness were considered in the calculation process. The cloud model weights, a calculation results of the ecological environment vulnerability analysis in the water source area, were calculated by constructing matrix that is a two-by-two judgment matrix through using the cloud scale criterion. The results were got by calculating three numerical characteristics which includes the Expected Value( Ex ), the Entropy( En ) and the Hyper Entropy( He ) of the cloud model. The results showed that the six factors of the Ex is 0.058–0.282, the En is 0.081–0.297 and the He is 0.081–0.297 where they stayed in the state layer in the evaluation index system of ecological environment vulnerability in the water source. Then, the results showed that the sixteen factors of the Ex is 0.008–0.177, the En is 0.013–0.171 and the He is 0.013–0.171 where they stayed in the response layer. The dense and relative small data showed that all these factors are micro-sensitive factors which indicated that the impact of a single factor on eco-environmental vulnerability of water source area is not obvious. And the consequence was caused by the long-term interaction of multiple factors. The algorithm provided a new idea for the assessment of eco-environmental vulnerability in water source areas.