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A drought monitoring framework for data-scarce regions

机译：数据稀缺地区的干旱监测框架

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摘要

Drought monitoring is a critical activity for drought risk management; however, the lack of ground-based observations of climatological and hydrological variables in many regions of the world hinders an adequate follow-up and investigation of this phenomenon. This paper introduces a transparent framework for monitoring the spatio-temporal distribution of drought hazard based on uni- and multivariate standardized drought indices that use reanalysis datasets of hydrological variables available freely and globally. In the case study of the 2015-2017 East-Southwest drought in Mexico, the introduced framework successfully detected the spatial and temporal patterns of drought conditions, even in regions where a benchmark drought monitoring system failed to detect deficits. In addition, the ability of the introduced framework to detect drought impacts on the annual agricultural maize production in Mexico was evaluated using data of 1980-2018, yielding scores of the false alarm ratio =0.32, the probability of detection = 0.71, and the proportion correct = 0.68 for the analysis at the national scale. Currently, the framework provides a significant extension to the capabilities for national drought monitoring, and it is being used by the Mexican water authority in the decision-making process related to drought severity assessment.
机译：干旱监测是干旱风险管理的关键活动。但是，由于在世界许多地区缺乏对气候和水文变量的地面观测，妨碍了对该现象的充分跟踪和调查。本文介绍了一个透明的框架，该框架基于单变量和多变量标准化干旱指数来监测干旱危害的时空分布，该指数使用可自由和全球获得的水文变量的重新分析数据集。在墨西哥2015-2017年东-西南干旱的案例研究中，引入的框架成功地检测了干旱状况的时空格局，即使在基准干旱监测系统未能发现赤字的地区也是如此。此外，使用1980-2018年的数据评估了引入的框架检测干旱对墨西哥农业玉米年产量的影响的能力，错误警报率= 0.32，检测概率= 0.71和比例的得分。正确= 0.68（在全国范围内进行分析）。目前，该框架大大扩展了国家干旱监测的能力，墨西哥水务当局正在将其用于与干旱严重程度评估有关的决策过程。

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