Osman Mahmoud, Zaitchik Benjamin, Otkin Jason, Anderson Martha
Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, MD, USA.
Irrigation and Hydraulics Department, Cairo University, Cairo, Egypt.
Sci Data. 2024 Sep 4;11(1):965. doi: 10.1038/s41597-024-03809-9.
Flash droughts, characterized by rapid onset and development, present significant challenges to agriculture and climate mitigation strategies. Operational drought monitoring systems, based on precipitation, soil moisture deficits, or temperature anomalies, often fall short in timely detection of these events, underscoring the need for customized identification and monitoring indices that account for the rapidity of flash drought onset. Recognizing this need, this paper introduces a global flash drought inventory from 1990 to 2021 derived using the Soil Moisture Volatility Index (SMVI). Our work expands the application of the SMVI methodology, previously focused on the United States, to a global scale, providing a tool for understanding and predicting these rapidly developing phenomena. The dataset encompasses detailed event characteristics, including onset, duration, and severity, across diverse climate zones. By integrating atmospheric variables through their impact on soil moisture, the inventory offers a platform for analyzing the drivers and impacts of flash droughts, and serves as a large, consistent dataset for use in training and evaluating flash drought prediction models.
骤发干旱以快速发生和发展为特征，给农业和气候缓解策略带来了重大挑战。基于降水量、土壤水分亏缺或温度异常的业务干旱监测系统，在及时检测这些事件方面往往存在不足，这凸显了需要有定制的识别和监测指标来考虑骤发干旱发生的快速性。认识到这一需求，本文介绍了一个1990年至2021年的全球骤发干旱清单，该清单是使用土壤水分波动指数（SMVI）得出的。我们的工作将此前专注于美国的SMVI方法应用扩展到了全球范围，提供了一个理解和预测这些快速发展现象的工具。该数据集涵盖了不同气候区详细的事件特征，包括开始时间、持续时间和严重程度。通过整合大气变量对土壤水分的影响，该清单提供了一个分析骤发干旱驱动因素和影响的平台，并作为一个大型、一致的数据集用于训练和评估骤发干旱预测模型。
