4.7 Article

Exploring Regional Profile of Drought History- a New Procedure to Characterize and Evaluate Multi-Scaler Drought Indices Under Spatial Poisson Log-Normal Model

期刊

WATER RESOURCES MANAGEMENT
卷 36, 期 9, 页码 2989-3005

出版社

SPRINGER
DOI: 10.1007/s11269-022-03159-4

关键词

Drought; Standardized drought indices; Spatial Poisson log-normal model; Spatial predictive distribution

向作者/读者索取更多资源

Drought is a recurrent natural hazard with complex climatic characteristics. This study proposes the simultaneous use of multiple drought measures to accurately monitor regional drought episodes.
Drought is recurrently occurring in many parts of the globe. In contrast to other natural hazards, drought has complex climatic characteristics. Several environmental factors are involved in the occurrence of drought hazards. However, the selection of an appropriate drought index may incorporate to make efficient drought mitigation policies. Moreover, the spatial distributions of extreme weather conditions (Dry/Wet) are necessary to avoid the consequences of future drought hazards. In this study, we aimed to explore and compare the regional profile of Dry/Wet episodes under various drought measures. Consequently, this research proposes a new spatial comparative procedure to assess and evaluate the spatial predictive distributions of Dry/Wet episodes under various drought measures. The study incorporates three Standardized Drought Indices (SDIs) and a spatial Poisson log-normal model to assess and evaluate the spatial predictive distributions of Dry/Wet episodes in Pakistan. Results of this study show that the segregated patterns of Dry/Wet counts are moderately consistent with the climatology of the region. However, the spatial patterns of Wet/Dry counts under various drought measures are significantly different under each index. Therefore, this research suggests the simultaneous use of multiple drought measures for accurate and precise drought monitoring at the regional level.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据