Strong evidence of changing weather patterns and risk of extreme events in the Lower Mekong Basin have a cascading impact on the natural ecosystem, agricultural productivity, and food production, pushing the region's resources to the brink of disaster. Recurring drought in the region has resulted in the need of a monitoring system for assessing the intrinsic nature of drought. Therefore, the objective of this study is to test an integrated modeling system that simulates the hydrological variables, drought characteristic, and crop yield over the Lower Mekong Basin. This study uses a coupled hydrologic and crop modeling framework- Regional Hydrologic Extremes Assessment System (RHEAS) over Cambodia in Lower Mekong Basin, which provides different drought severity measures and end-of-season crop yield estimates for 2000-2016. Gridded meteorological data were forced to the hydrologic model at a spatial resolution of 0.25° to estimate the fundamental drought characteristics, whereas the outputs from the hydrologic model were further used as forcing for the crop model. The validation of the RHEAS outputs was done using more than 3 years of soil moisture data from the SMAP mission. A good correlation (r=0.8) was obtained between the simulated RHEAS-based surface soil moisture data and the SMAP data over Cambodia, providing confidence to the model performance. For the crop model performance, yield estimates were compared against the observed rice yields from FAO. The simulated yield and observed yield also exhibited a good correlation (R²=0.83) for years 2008-2016, while the initial simulation years (2000-2008) showed a substantial bias between observed and model estimates. The yield differences can be attributed to the mismatch of crop cultivars and management practices used in RHEAS, making it difficult for the model to capture the trend. We envisage that RHEAS will improve the management of drought-related risks on agriculture in the Lower Mekong Basin countries for better decision making.
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