| Title |
A Development of Hydrological Model Calibration Technique Considering Seasonality via Regional Sensitivity Analysis |
| Authors |
이예린(Lee, Ye-Rin) ; 유재웅(Yu, Jae-Ung) ; 김경탁(Kim, Kyungtak) ; 권현한(Kwon, Hyun-Han) |
| DOI |
https://doi.org/10.12652/Ksce.2023.43.3.0337 |
| Keywords |
수문 계절성; 강우-유출 모형 보정; 전역 최적화; 민감도 분석; 군집화 Rainfall-Runoff model calibration; SCEM-UA; Regional sensitivity analysis; Clustering |
| Abstract |
In general, Rainfall-Runoff model parameter set is optimized using the entire data to calculate unique parameter set. However, Korea has a large precipitation deviation according to the season, and it is expected to even worsen due to climate change. Therefore, the need for hydrological data considering seasonal characteristics. In this study, we conducted regional sensitivity analysis(RSA) using the conceptual Rainfall-Runoff model, GR4J aimed at the Soyanggang dam basin, and clustered combining the RSA results with hydrometeorological data using Self-Organizing map(SOM). In order to consider the climate characteristics in parameter estimation, the data was divided based on clustering, and a calibration approach of the Rainfall-Runoff model was developed by comparing the objective functions of the Global Optimization method. The performance of calibration was evaluated by statistical techniques. As a result, it was confirmed that the model performance during the Cold period(November~April) with a relatively low flow rate was improved. This is expected to improve the performance and predictability of the hydrological model for areas that have a large precipitation deviation such as Monsoon climate. |