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Precondition Cloud and Maximum Entropy Principle Coupling Model-Based Approach for the Comprehensive Assessment of Drought Risk

机译:基于前提的云和最大熵原理耦合模型的综合评估干旱风险

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摘要

As a frequently occurring natural disaster, drought will cause great damage to agricultural production and the sustainable development of a social economy, and it is vital to reasonably evaluate the comprehensive risk level of drought for constructing regional drought-resistant strategies. Therefore, to objectively expound the uncertainty of a drought risk system, the precondition cloud and maximum entropy principle coupling model (PCMEP) for drought risk assessment is proposed, which utilizes the principle of maximum entropy to estimate the probability distribution of cloud drops, and the two-dimensional precondition cloud algorithm to determine the certainty degree of drought risk. Moreover, the established PCMEP model is further applied in a drought risk assessment study in Kunming city covering 1956–2011, and the results indicate that (1) the probability of drought events for different levels exhibits a slight increasing trend among the 56 historical years; and (2) both the integrated certainty degree and its component of drought risk are more evident, which will be more beneficial to determine the drought risk level. In general, the proposed PCMEP model provides a new reliable idea to evaluate the comprehensive risk level of drought from a more objective and systematic perspective.
机译:作为经常发生的自然灾害,干旱将对农业生产造成巨大损害和社会经济的可持续发展,这对建设区域干旱策略的综合风险水平至关重要。因此,客观地阐述干旱风险系统的不确定性,提出了用于干旱风险评估的前提云和最大熵原理耦合模型(PCMEP),利用最大熵原理来估计云下降的概率分布,以及二维前提云算法确定干旱风险的确定性程度。此外,建立的PCMEP模型进一步应用于昆明市的干旱风险评估研究,涵盖1956-2011,结果表明,(1)不同层次的干旱事件的可能性在56年历史较少的历史较小程度上表现出略有的趋势; (2)综合证明程度及其干旱风险的成分更为明显,这将更有利于确定干旱风险水平。一般而言,建议的PCMEP模型提供了一种新的可靠理念,以评估从更客观和系统的角度来看干旱的综合风险水平。

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