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A framework to improve hyper-resolution hydrological simulation in snow-affected regions

Author:
Shen, Xinyi, Anagnostou, Emmanouil N.
Source:
Journal of hydrology 2017 v.552 pp. 1-12
ISSN:
0022-1694
Subject:
United States Geological Survey, basins, energy balance, evapotranspiration, hydrologic cycle, hydrologic models, moderate resolution imaging spectroradiometer, rain, rivers, runoff, simulation models, snow, snowmelt, stream flow, watersheds, Connecticut River
Abstract:
Snow processes in mid- and north-latitude basins and their interaction with runoff generation at hyperresolution (<1km and <hourly) pose challenges in current state-of-the-art distributed hydrological models. These models run typically at macro to moderate scales (>5km), representing land surface processes based on simplified couplings of snow thermal physics and the water cycle in the soil-vegetation-atmosphere (SVA) layers. This paper evaluates a new hydrological model capable of simulating river flows for a range of basin scales (100km2 to >10,000km2), and a particular focus on mid- and north-latitude regions. The new model combines the runoff generation and fully distributed routing framework of the Coupled Routing and Excess STorage (CREST) model with a new land surface process model that strictly couples water and energy balances at the SVA layer, imposing closed energy balance solutions. The model is vectorized and parallelized to achieve long-term (>30years) high-resolution (30m to 500m and subhourly) simulations of large river basins utilizing high-performance computing. The model is tested in the Connecticut River basin (20,000km2), where flooding is frequently associated with interactions of snowmelt triggered by rainfall events. Model simulations of distributed evapotranspiration (ET) and snow water equivalence (SWE) at daily time step are shown to match accurately ET estimates from MODIS (average NSCE and bias are 0.77 and 6.79%) and SWE estimates from SNODAS (average correlation and normalized root mean square error are 0.94 and of 19%); the modeled daily river flow simulations exhibit an NSCE of 0.58 against USGS streamflow observations.
Agid:
5705365