A Study to Suggest Monthly Baseflow Estimation Approach for the Long-Term Hydrologic Impact Analysis Models: A Case Study in South Korea

Changes in both land use and rainfall patterns can lead to changes in the hydrologic behavior of the watershed. The long-term hydrologic impact analysis (L-THIA) model has been used to predict such changes and analyze the changes in mitigation scenarios. The model is simple as only a small amount of...

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Bibliographic Details
Published inWater (Basel) Vol. 13; no. 15; p. 2043
Main Authors Lee, Hanyong, Choi, Hyun-Seok, Chae, Min-Suh, Park, Youn-Shik
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.08.2021
Subjects
Calibration
Chemical oxygen demand
Construction costs
Geographic information systems
hydrological watershed modeling
Hydrology
Impact analysis
L-THIA model
Land use
Mitigation
monthly baseflow
Precipitation
Rainfall
Runoff
Stream discharge
Stream flow
Watersheds
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Summary:Changes in both land use and rainfall patterns can lead to changes in the hydrologic behavior of the watershed. The long-term hydrologic impact analysis (L-THIA) model has been used to predict such changes and analyze the changes in mitigation scenarios. The model is simple as only a small amount of input data are required, but it can predict only the direct runoff and cannot determine the streamflow. This study, therefore, aimed to propose a method for predicting the monthly baseflow while maintaining the simplicity of the model. The monthly baseflows for 20 watersheds in South Korea were estimated under different land use conditions. Calibration of the monthly baseflow prediction method produced values for R2 and the Nash–Sutcliffe efficiency (NSE) within the ranges of 0.600–0.817 and 0.504–0.677, respectively; during validation, these values were in the ranges of 0.618–0.786 and 0.567–0.727, respectively. This indicates that the proposed method can reliably predict the monthly baseflow while maintaining the simplicity of the L-THIA model. The proposed model is expected to be applicable to all the various forms of the model.
ISSN:2073-4441
2073-4441
DOI:10.3390/w13152043