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Hydroclimatic aggregate drought index (HADI): a new approach for identification and categorization of drought in cold climate regions

机译:水胆总会干旱指数(HADI):一种新方法,用于寒冷气候区干旱的识别和分类

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摘要

Drought identification is crucial to water resources management and planning. Different drought indices have been developed and their complexity and applicability vary. The objectives of this research are to develop a new integrated drought index with the capability of identification of drought and to further customize drought categorization for cold climate regions. Specifically, a new hydroclimatic aggregate drought index (HADI) is developed by coupling with a grid-based hydrologic model and applying the R-mode correlation-based principal component analysis. The HADI is a composite drought index, which assesses the anomalies of rainfall, surface runoff, snowmelt, and soil moisture in the root zone. Furthermore, joint probability distribution function of drought frequencies and classes as well as conditional expectation are used for drought categorization. The HADI was applied to the Red River of the North Basin (RRB) and its performance was evaluated by comparing with the Palmer Drought Severity Index (PDSI) and the U.S. Drought Monitor (USDM) products. Based on the impacts of drought on agriculture, the HADI outperformed the PDSI in identification of droughts in the RRB. Although the HADI and USDM showed a good agreement in identification of drought periods, the drought area coverages for each drought category from the two methods differed. The new customized drought categorization based on variable threshold levels accounted for the variations in both time and geographical locations. The new HADI, together with the customized drought categorization, is able to provide more accurate drought identification and characterization, especially for cold climate regions.
机译:干旱识别对于水资源管理和规划至关重要。已经开发出不同的干旱指数,其复杂性和适用性变化。本研究的目标是开发一种新的综合干旱指数,具有鉴定干旱的能力,并进一步定制冷气候区的干旱分类。具体地,通过与基于网格的水文模型耦合并应用基于R模式相关的主成分分析,开发出一种新的循环血管纤维化干旱指数(HADI)。哈迪是一种复合干旱指数,其评估了根区中降雨,表面径流,散热和土壤水分的异常。此外,干旱频率和类别的联合概率分布函数以及条件期望用于干旱分类。哈迪应用于北部盆地的红河(RRB),并通过与Palmer干旱严重性指数(PDSI)和美国干旱监测器(USDM)产品进行比较来评估其性能。基于干旱对农业的影响,哈迪优于PDSI鉴定RRB中的干旱。虽然哈迪和USDM在识别干旱期间表现出良好的一致性,但是来自两种方法的每个干旱类别的干旱地区覆盖范围不同。基于可变阈值水平的新定制干旱分类占时间和地理位置的变化。新的哈迪与定制的干旱分类一起,能够提供更准确的干旱鉴定和表征,特别是对于寒冷的气候区。

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