A near‐term drought assessment using hydrological and climate forecasting in the Mekong River Basin

Abstract

AbstractA seasonal drought forecasting approach using a high‐resolution meteorological forcing and hydrologic model was developed in the Mekong River Basin (MRB), where ground‐based observations are sparse. The Soil and Water Assessment Tool (SWAT) model was used to simulate soil moisture, runoff and evapotranspiration, which were then used to compute three drought indices for historical drought assessment (1953–2016) and seasonal forecasting of drought. In the absence of observed soil moisture data, SWAT was first calibrated with streamflow data to derive reliable soil moisture estimates, and historical drought events were validated with the available reference drought index. Based on the calibrated results, the Modified Palmer Drought Severity Index (MPDSI), Standardized Soil Moisture Index (SSI) and Multivariate Standardized Drought Index (MSDI) were estimated to evaluate the meteorological, agricultural and multivariate aspects, respectively, of drought. The total drought durations were 105–220 months, according to the reference drought index, and the estimated drought index captured 60–76% of these drought events. The three drought indices perform somewhat differently, but the 1991–1994 and 2015–2016 droughts were the worst drought events in the last 64 years based on analysis of the severity, duration and area of the meteorological and multivariate aspects of drought. The extreme droughts occurred in the Upper and Mid sections of the Lower Mekong sub‐basins and the 3S region when there were consecutive precipitation and temperature anomalies that continued for more than 2 years. Spatial variability in precipitation deficits and temperature increases were random because these variables affect soil moisture differentially. In addition, 68.4–76.1% of the areas with increased drought were explained by the areas' precipitation decrease or temperature increase. Validation of the multiple drought indices at high resolution can inform sub‐regional variability in drought conditions and hence food and water security in this important transboundary basin.