Enhancing Streamflow Drought Simulation through Calibration and Surface Data-Assimilation for the US Drought Monitor

Droughts are considered to be the most detrimental natural hazard of the 20th century, impacting a variety of sectors spanning across society. It has been argued that droughts are the most complex and least-understood natural hazards. The US Drought Monitor (USDM) is the state-of-the-art drought information system, which produces weekly drought maps for the entire US. Given the limits of current USDM inputs, the water demand aspect of the hydrological drought is not well represented. Here we present a hydrologic modeling framework that leverages the WRF-Hydro routing structure, based on the NOAA National Water Model configuration (including calibration and regionalization methods), combined with the NASA Land Information System data-assimilation capabilities. We calibrate this coupled system and perform surface data assimilation of snow and leaf area index (LAI). The utility of this broader coupled model structure has been demonstrated in previous work, where snow assimilation was able to improve streamflow hydrology. In this presentation, we will present our preliminary findings from calibration and data assimilation, for the simulation of historic drought events. A contiguous US scale implementation of this hydrologic modeling framework will be incorporated into new USDM blended products for stakeholders.