Remote Sensing, Vol. 11, Pages 1960: Assessing the Remotely Sensed Evaporative Drought Index for Drought Monitoring over Northeast China (Remote Sensing)

Many existing satellite evapotranspiration (ET)-based drought indices have characterized regional drought condition successfully, but the relatively short time span of ET products limits their use in long-term climatological drought assessment. In this study, we assess Evaporative Drought Index (EDI) as a drought monitoring indicator over Northeast China through a retrospective comparison with drought-related indicators. After verifying its utility for detecting documented regional drought events and impacts of drought on crop production, we apply it to improve our understanding of the variation in dryness over Northeast China from 1982 to 2015. Our results illustrate that EDI is generally effective for characterizing terrestrial moisture condition and its standardized formula, namely, Standardized Evaporative Drought Index (sEDI) corresponds well with historical drought events and inter-annual grain crop yields over Northeast China. Although the calculation of sEDI does not directly incorporate precipitation and soil moisture, statistical analyses indicate sEDI can detect drought in accordance with the Standardized Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI), with the highest correlations found in the west part of Northeast China (R < −0.7). Further analysis illustrates sEDI is more related to commonly-used drought metrics over areas with short canopy vegetation (R < −0.5) than woodland (R < −0.2), which suggests precipitation may not be a good representative of drought condition over areas with deep-rooted vegetation. Then, we find 56.5% of Northeast China shows an upward dry trend from 1982 to 2015, which mainly concentrates in the west part of the study area. Conversely, 14.4% of Northeast China shows a significant wetted trend and most of them locate at cropland areas, due to the improved water management. This study suggests that EDI is a feasible method to monitor spatially distributed drought condition and can provide unique drought information not reflected by rainfall deficits, which also can be used to evaluate traditional precipitation-based indicators.