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Application of Sample Entropy on Measuring Precipitation Series Complexity in Jiansanjiang Branch Bureau of China
In order to describe the complexity characteristics of precipitation series in Jiansanjiang Branch Bureau of China, the complexities of monthly average precipitation series were measured by the sample entropy method and the regional differences of precipitation resources system complexity in the farms belonging to Jiansanjiang Branch Bureau were analyzed by utilizing the visualization function of ArcGIS technology. The measure and analysis results show that the complexities of each monthly average precipitation have obvious regional differences in Jiansanjiang Branch Bureau. The monthly average precipitation series complexities in Farm Hongwei and Farm Bawujiu are the strongest; in Farm Daxing, Farm Chuangye, Farm Qianjin, Farm Qinglongshan, Farm Yalvhe, Farm Qianfeng and Farm Shengli are in the middle; and in Farm Qindeli, Farm Qixing, Farm Honghe, Farm Qianshao and Farm Erdaohe are the weakest. Sample entropy can reflect the dynamic change degree of precipitation series and has advantages like less data needing and is stable, which provide a new way to research hydrological series complexity. The research achievements reveal the complexity and its areal variation of local precipitation resources system, and screen boundary parameters for structuring water resources optimization allocation models, and provide scientific basis for rationally utilizing and developing precipitation resources in Jiansanjiang Branch Bureau and even in the whole Sanjiang Plain of China.
Keywords
Sample Entropy, Precipitation Series, ArcGIS Technology, Jiansanjiang Branch Bureau.
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