Chang Young Ha

Chang Young Ha


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 August 2023 in Water
Verified
Journal Article
Open access
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CHChang Young Ha
Chang Young Ha
BKBeomjin Kim
Beomjin Kim
JLJaenam Lee
Jaenam Lee
BKByunghyun Kim
Byunghyun Kim
In this study, the sensitivity of the parameters was analyzed using PEST (Parameter ESTimation) to improve the accuracy of the runoff and flooding analysis in urban areas. Using four parameters (watershed width, roughness coefficient of impervious and pervious areas, and Manning’s roughness coefficient for conduits) with high sensitivity, six scenarios were created according to the number of parameters considered, and a PEST-SWMM (Storm Water Management Model) combined simulation was performed. The scenarios were applied to the Seocho 3, 4, 5, Yeoksam, and Nonhyun drainage basins in which inundation damage occurred due to the heavy rain on 21 July 2013. The sensitivity of the four parameters was in the order of Manning’s roughness coefficient for conduits, the roughness coefficient of the impervious area, the watershed width, and the roughness coefficient of the pervious area. When the PEST–SWMM coupled analysis for each scenario was performed using the analyzed sensitivity results, the RMSE (Root Mean Square Error) decreased by up to 2.37 cm and the RPE (Relative Peak Error) decreased by 22.04% compared to the SWMM alone. When the accuracy of each scenario was analyzed, similar or better accuracy was obtained as far as the parameters were considered. However, the further consideration of less sensitive parameters tends to reduce the accuracy. In this study, it was found that a more efficient simulation in terms of accuracy and calculation time could be obtained when constructing scenarios by considering only highly sensitive parameters. Additionally, when combining two-dimensional (2D) flood analysis with other rainfall events, it can help study real-time flood forecasting in urban areas.