Abstract
Manmade reservoirs are important components of the terrestrial water balance. Thus, considering the hydro-climatic effects of reservoirs is important in water cycle studies at a river basin to global scales; yet, reservoirs are represented poorly in large-scale hydrological and climate models. Here we present a high-resolution (5 km) continental-scale reservoir storage dynamics and release scheme by enhancing existing schemes and adding critical novel parameterizations to improve reservoir storage and release simulations. The new scheme simulates river-floodplain-reservoir storages in an integrated manner considering their spatial and temporal variations. A new calibration scheme is also incorporated to better simulate reservoir dynamics considering cascade-reservoir effects. Further, since no reservoir bathymetry data are available over large domains, we use a state-of-the-art digital elevation model and reservoir extent data to derive reservoir bed elevation. The new scheme is integrated within the river-floodplain routing scheme of a continental hydrological model LEAF-Hydro-Flood. Results from the simulation of ~1,900 reservoirs within the contiguous United States suggest that the model well captures the observed reservoir storage-release dynamics. Comparison of our results with those from the existing schemes suggest a significant improvement; importantly, the new scheme reduces the excessive and frequent reservoir overfilling and underfilling. Comparison of results with satellite-based surface water data shows that the model accurately reproduces the large-scale patterns of reservoir-floodplain inundation extents. It is expected that the results of this study will inform the incorporation of reservoirs in hyper-resolution models to improve simulations of terrestrial water storage and flow and examine reservoir-atmosphere interactions over large domains.
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Shin, S., Pokhrel, Y., & Miguez-Macho, G. (2019). High-Resolution Modeling of Reservoir Release and Storage Dynamics at the Continental Scale. Water Resources Research, 55(1), 787–810. https://doi.org/10.1029/2018WR023025
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