4.7 Article

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

期刊

JOURNAL OF HYDROLOGY
卷 552, 期 -, 页码 1-12

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jhydrol.2017.05.048

关键词

CREST; Distributed hydrological model; Snow process; Hyper-resolution; Flood

资金

  1. Connecticut Department of Energy and Environmental Protection
  2. Natural Science Foundation of China (NSFC) [41471430]
  3. Eversource Energy

向作者/读者索取更多资源

Snow processes in mid- and north-latitude basins and their interaction with runoff generation at hyper-resolution (<1 km and 5 km), 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 (100 km(2) to >10,000 km(2)), 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 (>30 years) high-resolution (30 m to 500 m and subhourly) simulations of large river basins utilizing high-performance computing. The model is tested in the Connecticut River basin (20,000 km(2)), 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 streamfiow observations. (C) 2017 Elsevier B.V. All rights reserved.

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