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http://dx.doi.org/10.17663/JWR.2019.21.1.001

An Optimization of distributed Hydrologic Model using Multi-Objective Optimization Method  

Kim, Jungho (Cooperative Institute for Research in the Atmosphere (CIRA), Colorado State University)
Kim, Taegyun (Department of Landscape Architecture, Gyeongnam National Univ. of Science & Tech.)
Publication Information
Journal of Wetlands Research / v.21, no.1, 2019 , pp. 1-8 More about this Journal
Abstract
In this study, the multi-objective optimization method is attemped to optimize the hydrological model to estimate the runoff through two hydrological processes. HL-RDHM, a distributed hydrological model that can simultaneously estimate the amount of snowfall and runoff, was used as the distributed hydrological model. The Durango River basin in Colorado, USA, was selected as the watershed. MOSCEM was used as a multi-objective optimization method and parameter calibration and hydrologic model optimization were tried by selecting 5 parameters related to snow melting and 13 parameters related to runoff. Data from 2004 to 2005 were used to optimize the model and verified using data from 2001 to 2004. By optimizing both the amount of snow and the amount of runoff, the RMSE error can be reduced from 7% to 40% of the simulation value based on the initial solution at three SNOTEL points based on the RMSE. The USGS observation point of the outflow is improved about 40%.
Keywords
distributed model; multi-objective optimization; MOSCEM; snow modeling; parameter estimation;
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