气候变化领域集成服务门户(CCPortal): Identification and application of the most suitable entropy model for precipitation complexity measurement

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DOI	10.1016/j.atmosres.2019.02.002
	Identification and application of the most suitable entropy model for precipitation complexity measurement
	Zhang L.; Li H.; Liu D.; Fu Q.; Li M.; Faiz M.A.; Khan M.I.; Li T.
发表日期	2019
ISSN	0169-8095
起始页码	88
结束页码	97
卷号	221
英文摘要	Precipitation complexity measurement is often overlooked in precipitation time series research. Entropy, as a measure of system complexity, can be used to diagnose the complexity of precipitation. However, it is difficult to judge the applicability of different theoretical entropy models for solving precipitation uncertainty problems. This paper introduces the distinction degree theory and the serial number sum theory to screen the optimal entropy model for precipitation complexity measurement. The optimal entropy model was used to analyze the spatiotemporal differences of monthly precipitation complexity in Heilongjiang Province, China. Possible influencing factors of precipitation complexity were also examined. The results indicated that in the complexity measurement of precipitation based on entropy theory, the stability and reliability of sample entropy was higher than those of fuzzy entropy, wavelet entropy and permutation entropy. The complexity of monthly precipitation in the selected study area significantly increased with time. The average complexity of monthly maximum precipitation, monthly average precipitation and monthly minimum precipitation were 0.665, 0.622 and 0.545, respectively, and their tendency change rates were 0.070/decade, 0.055/decade and 0.038/decade, respectively. The areas with high monthly precipitation complexity were concentrated in the central, eastern and northwest parts of the study area, and the precipitation was less predictable. Monthly precipitation in the southwest was less complex and more predictable. The highest monthly precipitation complexity was 1.012, at Hulin station, and the lowest was 0.510, at Mingshui station. The increasing complexity of monthly precipitation in the province was strongly related to local industrial and agricultural production. The superposition effects of altitude, topographic relief, change in grassland area and agricultural production formed the basic pattern of spatial differences in monthly precipitation complexity. The results may provide a scientific guidance for regional precipitation predictability measurement, effective assessment of droughts and floods, and water resources management. © 2019 Elsevier B.V.
英文关键词	Complexity measurement; Entropy theory; Impact factor; Multi-model optimization; Precipitation
语种	英语
scopus关键词	Agriculture; Precipitation (chemical); Reliability theory; Water resources; Agricultural productions; Complexity measurement; Entropy theory; Impact factor; Multi model; Precipitation time series; Stability and reliabilities; Water resources management; Entropy; entropy; measurement method; modeling; optimization; precipitation (climatology); prediction; theoretical study; China; Heilongjiang
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/162328
作者单位	School of Water Conservancy & Civil Engineering, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Key Laboratory of Effective Utilization of Agricultural Water Resources of Ministry of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Provincial Key Laboratory of Water Resources and Water Conservancy Engineering in Cold Region, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Key Laboratory of Water-Saving Agriculture of Ordinary University in Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Department of irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan
推荐引用方式 GB/T 7714	Zhang L.,Li H.,Liu D.,et al. Identification and application of the most suitable entropy model for precipitation complexity measurement[J],2019,221.
APA	Zhang L..,Li H..,Liu D..,Fu Q..,Li M..,...&Li T..(2019).Identification and application of the most suitable entropy model for precipitation complexity measurement.Atmospheric Research,221.
MLA	Zhang L.,et al."Identification and application of the most suitable entropy model for precipitation complexity measurement".Atmospheric Research 221(2019).