With the climate change and the acceleration of urbanization, urban flood disaster is becoming increasingly frequent, leading to more severe impact than in the past. The traditional disaster alleviation strategies… Click to show full abstract
With the climate change and the acceleration of urbanization, urban flood disaster is becoming increasingly frequent, leading to more severe impact than in the past. The traditional disaster alleviation strategies have gradually expanded to non-engineering disaster reduction strategies. As urban public property, public facility is more available than private land, making it the preferred strategy of site selection for urban land flood diversion. However, due to the limited government finance, how to select public facilities as the multi-use detention basin to maximize the disaster reduction and external benefits is an issue that needs to be considered before planning and decision-making. This study builds an operable decision model of site selection of urban public facilities as multi-use detention basin from the perspective of environmental efficiency. The decision model analyzes the expected costs and benefits of the multi-use detention basin based on data envelopment analysis (DEA) and cross-efficiency analysis, so as to establish the optimal combination of alternative schemes of site selection. It further compares with the traditional detention basin considering only disaster reduction efficiency to summarize how to improve the strategy of selecting multi-use detention basin site within the watershed in the future. This paper uses the watershed of Dajiaxi as a case study, and finds that (I) there is a certain trade-off relationship between the optimized schemes established from the perspective of environmental efficiency and disaster reduction efficiency evaluation. The scheme with the highest disaster reduction efficiency does not necessarily increase the external benefit significantly; (II) for the inefficient schemes, the difference between the site selection schemes and the ideal efficiency value can be measured through slack variable analysis.
               
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