Article ID: | iaor20162468 |
Volume: | 30 |
Issue: | 9 |
Start Page Number: | 3027 |
End Page Number: | 3042 |
Publication Date: | Jul 2016 |
Journal: | Water Resources Management |
Authors: | Xu Jinchao, Jin Juliang, Zhao Jun, Zhu Jiezhong, Hang Qingfeng, Chen Yaqian, Han Donghao |
Keywords: | allocation: resources, management, risk, simulation, decision, planning |
In order to fully protect water resources and govern water pollution, a water resources risk assessment model based on the subjective and objective combination weighting methods is studied in this paper. The model takes risk indices in water resources system as research object, and extracts the different index information from various angles. In this study, firstly, according to system evaluation standard, it constructs the judgment matrix by the subjective judgment and objective calculation method. Secondly, it applies the improved analytic hierarchy process with accelerating genetic algorithm for modifying the consistency of judge matrix to calculate the single sample weight and sample set weight. Thirdly, it uses water resources type of evaluation index and the level of sample evaluation index values to determine the combination weights. After that, the systematic comprehensive evaluation index can be obtained by taking a weighted Average of these combined weights and the consistent‐dimensionless sample values for each evaluation index. Then, it classifies and sorts the samples by the comprehensive evaluation value. Finally, on the basis of risk level, it puts forward the suitable planning for water resources development with reference to the real condition. This study takes Hanjiang Basin for example. After risk assessment model establishment, validation and application between the actual and simulated data, the results show that the trend of water resources risk is considered to be controlled at a certain level. This is matched with the fact. The model is feasible in scientific method, and reasonable in conclusion, which can be applied to water resources risk assessment research.