Abstract
Drought hazard is the initial inputting element of regional drought disaster risk management system, which will result in serious drought disaster loss and ecological degradation in combination with the interaction of drought disaster vulnerability factors including population, social economy and ecological environment. Additionally, drought hazard comprehensive evaluation and its variation characteristic analysis are of significant importance for implementing drought disaster resistance schemes. Therefore, given the advantages of Multi-dimensional Precondition Cloud Algorithm (MPCA) in quantifying the uncertainties of drought hazard system and Cloud Transformation Algorithm (CTA) in multivariate frequency distribution derivation, the MPCA, CTA and Copulas function were innovatively introduced to construct drought hazard comprehensive evaluation model (CTCF) aiming to conduct historical variation characteristic exploration and future drought hazard evolution trend prediction analysis. And eventually, the proposed CTCF model was further verified through its application in Anhui Province, China, and the results revealed that, (1) the frequency curve fitting result of drought hazard indicators basing on CTCF approach was effective, which had lower calculation error of RMSE as compared to the corresponding calculation results utilizing traditional normal distribution hypothesis. (2) light-type drought hazard event (Grade II) is the dominant type for the entire provincial area in the future, and the overall occurring probability of future drought hazard events will present gradually declining trend from north to south. The above results had better consistent variation properties with regional historical observed statistical data series of drought disaster system, which indicates that the proposed CTCF model is reasonable in the application of drought hazard comprehensive evaluation field, and will also be beneficial for the implement of drought disaster precaution strategies and construction of ecological environment.
Published Version
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