Impact of the Alamosa gap-filling radar on streamflow in the National Water Model - Grim, Joseph A.; Zhang, Yongxin; Gochis, David J. (Frontiers in Earth Science, 2023)
The installation of the Alamosa gap-filling radar in 2019 not only greatly improved surveillance of current precipitation in the mountain-ringed San Luis valley, but also improved estimates of rain and snow accumulation. This is particularly important for hydrological prediction in this headwaters region, as it provides vital information for potential downstream floods and reservoir storage. This study performs three experiments using the community WRF-Hydro modeling system (the core model of the National Water Model) during 2021 to estimate the effect of the new Alamosa gap-filling radar, as integrated into the National Severe Storms Laboratory (NSSL) Multi-radar Multi-sensor (MRMS) quantitative precipitation estimate (QPE) product on model-predicted streamflow. The first model experiment utilizes the MRMS data, including from the new Alamosa radar; the second utilizes a spatially-downscaled version of the NLDAS-2 precipitation field, mapped to a high resolution WRF-Hydro model grid; while the third experiment uses a combination of the two, with MRMS used in areas observed by the Alamosa radar. Emphasis is placed on analyzing the impact of the radar QPE on total seasonal runoff in the Conejos River basin and overall runoff throughout the Upper Rio Grande River basin in southern Colorado.