Quantitative Assessment of Cropland Exposure to Agricultural Drought in the Greater Mekong Subregion

Accurate and reliable information on the spatiotemporal characteristics of agricultural drought is important in understanding complicated drought processes and their potential impacts. We proposed an integrated approach for detecting agricultural droughts and their cropland exposure using remote sensing data over the Greater Mekong Subregion (GMS) collected from 2001 to 2020. The soil moisture (SM) dataset (0.05°) was first reconstructed based on an ESACCI SM dataset using a random forest (RF) model. Subsequently, the standardized soil moisture index (SSMI) was used to identify the agricultural droughts by a three-dimensional (latitude-longitude-time) identification method. In addition, the cropland’s exposure to agricultural droughts was evaluated. Results showed that: (1) the reconstructed SM data achieved spatial continuity and improved spatial resolution. The verified consequences showed that the reconstructed SM data agreed well with the in situ SM data. Additionally, the SSMI based on reconstructed SM had good correlations with the standardized precipitation evapotranspiration index (SPEI) calculated from station observations. (2) Twenty agricultural drought events lasting at least 3 months were identified over the GMS region. The averaged durations, areas, and severity were 7 months, 9 × 105 km2, and 45.6 × 105 month·km2, respectively. The four worst drought events ranked by severity were the 2019–2020 event, the 2015–2016 event, the 2009–2010 event, and the 2004–2005 event. (3) Based on the 20 identified agricultural drought events, cropland exposure was high in Myanmar, Thailand, and Cambodia. On average, the cropland exposure over the GMS was 1.71 × 105 km2, which accounts for 34% of the total cropland. Notably, the four severest drought events swept over 80% of the total cropland area. This study enriched our understanding of the development process of agricultural droughts from a space-time perspective, which was pivotal for assessing drought impacts and managing agricultural water resources.