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http://dx.doi.org/10.3741/JKWRA.2018.51.9.803

Evaluation of multi-objective PSO algorithm for SWAT auto-calibration  

Jang, Won Jin (Department of Civil, Environmental and Plant Engineering, Konkuk University)
Lee, Yong Gwan (Department of Civil, Environmental and Plant Engineering, Konkuk University)
Kim, Seong Joon (Department of Civil, Environmental and Plant Engineering, Konkuk University)
Publication Information
Journal of Korea Water Resources Association / v.51, no.9, 2018 , pp. 803-812 More about this Journal
Abstract
The purpose of this study is to develop Particle Swarm Optimization (PSO) automatic calibration algorithm with multi-objective functions by Python, and to evaluate the applicability by applying the algorithm to the Soil and Water Assessment Tool (SWAT) watershed modeling. The study area is the upstream watershed of Gongdo observation station of Anseongcheon watershed ($364.8km^2$) and the daily observed streamflow data from 2000 to 2015 were used. The PSO automatic algorithm calibrated SWAT streamflow by coefficient of determination ($R^2$), root mean square error (RMSE), Nash-Sutcliffe efficiency ($NSE_Q$), and especially including $NSE_{INQ}$ (Inverse Q) for lateral, base flow calibration. The results between automatic and manual calibration showed $R^2$ of 0.64 and 0.55, RMSE of 0.59 and 0.58, $NSE_Q$ of 0.78 and 0.75, and $NSE_{INQ}$ of 0.45 and 0.09, respectively. The PSO automatic calibration algorithm showed an improvement especially the streamflow recession phase and remedied the limitation of manual calibration by including new parameter (RCHRG_DP) and considering parameters range.
Keywords
Automatic calibration algorithm; Multi-objective functions; Particle swarm optimization; Python; SWAT;
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