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A compound cloud model for harmoniousness assessment of water allocation
- Wang, Mei, Tang, Deshan, Bai, Yifan, Xia, Zhongbang
- Environmental earth sciences 2016 v.75 no.11 pp. 977
- case studies, economic development, models, water allocation, China
- Water allocation plays an important role in water resources management. Faced with continuously rapid economic growth, as well as an accompanying, ever-increasing demand for water, harmonious water allocation is a new strategy to address existing water problems. In order to assess water allocation, this study proposes an index system that adopts 15 basic indicators from four dimensions (flexibility, efficiency, health and development) and a harmony index (HI) to measure the harmony level of water allocation. For the calculation of HI, a compound cloud model (CCM) that takes advantage of the features of the cloud model is presented and combined with a weight cloud module, a qualification cloud module and a comprehensive assessment module. The weight cloud module is employed to calculate the weights of the indicators and criteria. The qualification cloud module is used to transform the attribute values of the indicators to evaluation values. The comprehensive assessment module is used to integrate the overall performance to obtain the HI value. The CCM was applied to Nanjing city in China. The results showed that water allocation in Nanjing was in the improving stage between 2006 and 2013, increasing from grade III (generally harmonious) to grade IV (moderately harmonious); and that Nanjing performed noticeably well in the flexibility dimension, less well in the development dimension and worst in the health dimension. The CCM accounts for both randomness and fuzziness in the calculation of weights and the unification of attribute values of the indicators, and this model has been verified as feasible and effective by the results of the case study. A harmoniousness assessment of water allocation provides a support tool to give decision-makers a better sense of past water allocation strategies such they can adjust accordingly in the future.