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Issue title: Artificial Intelligent Techniques and its Applications
Guest editors: Mahalingam Sundhararajan, Xiao-Zhi Gao and Hamed Vahdat Nejad
Article type: Research Article
Authors: Cai, Siyua; b | Lei, Xiaohuia; b; * | Meng, Xianyonga; b; * | Yi, Jia; b
Affiliations: [a] State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin & China Institute of Water Resources and Hydropower Research, Beijing, China | [b] Institute of Hydrology and Water Resources, Department of Hydraulic Engineering, Tsinghua University, Beijing, China
Correspondence: [*] Corresponding author. Xiaohui Lei and Xianyong Meng, State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin & China Institute of Water Resources and Hydropower Research, Beijing 100038, China. E-mails: [email protected] (X. Lei); [email protected] (X. Meng).
Abstract: Owing to climate change, human activities and underlying surface change in the basin, a series of hydrological factors have not only changed in the annual form, but also changed the distribution trend of monthly hydrological factors in a year. This phenomenon has seriously affected the ecological water demand in the river channel. The calculation and analysis of ecological water demand will be affected by runoff sequence after variations. This paper proposed a distribution trend model of runoff by using Gini coefficient, which was used to identify the variation points of runoff at Ga Datan station in the Da Tong River basin. Then the monthly ecological water demand in the river channel was calculated. Finally, through comparing the mean flow before and after variation, in addition to ecological water demand and broken frequency of ecological flow, the study analyzed the effects of hydrological variations on ecological flow.
Keywords: Gini coefficient, comprehensive diagnosis system, ecological flow
DOI: 10.3233/JIFS-169396
Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 2, pp. 1025-1031, 2018
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