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Water 2017, 9(9), 632; https://doi.org/10.3390/w9090632

An Entropy-Based Investigation into Bivariate Drought Analysis in China

1,2,†,‡
,
3,‡
and
1,2,*
1
Institute of Mathematics and Science, Yangzhou University, Yangzhou 225002, China
2
Institute of Physics Science and Technology, Yangzhou University, Yangzhou 225002, China;
3
Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081, China
Current address: Institute of Mathematics and Science, Yangzhou University, Yangzhou 225002, China.
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Paulo Barbosa and Jürgen Vogt
Received: 17 June 2017 / Revised: 17 August 2017 / Accepted: 20 August 2017 / Published: 23 August 2017
(This article belongs to the Special Issue Drought Monitoring, Forecasting, and Risk Assessment)
Full-Text   |   PDF [17369 KB, uploaded 25 August 2017]   |  

Abstract

Because of the high correlation between random variables of drought duration and severity, their joint distribution is difficult to obtain by traditional mathematical methods. However, the copula method has proved to be a useful tool for analyzing the frequency of drought duration and severity. Most studies have used different marginal distribution functions to fit the drought duration and severity distributions. This requires a great deal of contrast analysis, and sometimes two or more distributions fit the data well. Based on entropy theory, however, a unified probability distribution function is derived which reduces complex contrast analysis and improves the filtering distribution function. Based on monthly precipitation data at 162 stations in China for 1961–2015, the monthly standardized precipitation index was calculated and used to extract drought duration and severity. Then the entropy distribution was used to fit the distributions of drought duration and severity, and to establish the correspondence between them. The probabilities of the interval and return periods were then determined using the copula method. An analysis of the discrepancy between the conventional and entropy-based methods indicated that the entropy distribution showed a better fit than conventional methods for drought duration distribution, although no obvious difference was found in drought severity distribution. The entropy-based results were more consistent with the empirical data, whereas conventional methods showed apparent deviation in some drought types. Hence, the entropy-based method is proposed as an alternative method of deriving the marginal distributions of drought duration and severity, and for analyzing the interval probability and return period in China. View Full-Text
Keywords: drought; entropy; copula; China drought; entropy; copula; China
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Zuo, D.; Hou, W.; Hu, J. An Entropy-Based Investigation into Bivariate Drought Analysis in China. Water 2017, 9, 632.

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