Flash drought identification from satellite-based land surface water index

作者：Jordan I. Christian, Jeffrey B. Basara, Lauren E. L. Lowman, Xiangming Xiao, Daniel Mesheske, Yuting Zhou · 发表于：Remote Sensing Applications Society and Environment · 年份：2022 · DOI：10.1016/j.rsase.2022.100770 · 被引用次数：37 · 研究领域：Hydrology and Drought Analysis、Climate variability and models、Plant Water Relations and Carbon Dynamics

Flash droughts can lead to significant agricultural and ecosystem impacts via rapid land surface desiccation. While gridded weather and climate datasets, land surface models, or widely spaced in situ observations are typically used to quantify flash drought development, coarse spatial data limits the ability to determine fine-scale spatial evolution of flash drought at landscape and ecosystem scales. In this study, a novel approach is introduced to objectively identify flash drought using the land surface water index (LSWI) derived from satellite observations. LSWI is a water-related vegetation index that represents the total water content in vegetation by using the near-infrared and shortwave infrared bands. LSWI was derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra surface reflectance (MOD09A1) with a 500 m spatial resolution and an 8-day temporal resolution. When applied to two well-established case studies , LSWI anomalies were able to capture the temporal and spatial evolution of flash drought over Oklahoma during the years of 2011 and 2012. In addition, rapid changes of LSWI during flash drought were comparable across space and time to the reanalysis-based Standardized Evaporative Stress Ratio (SESR), while negative anomalies of LSWI following flash drought corresponded with drought impacts via the United States Drought Monitor. It was found that LSWI was able to identify flash drought with a finer spatial resolution (500 m) and revealed spati...