期刊
WATER
卷 13, 期 12, 页码 -出版社
MDPI
DOI: 10.3390/w13121709
关键词
model calibration; objective function; Kling and Gupta efficiency; Nash and Sutcliffe efficiency; multiple criteria; land surface model; long-term streamflow
资金
- National Research Foundation of Korea (NRF) - Korean government (MSIT) [2017R1A2B4005232]
- National Research Foundation of Korea [2017R1A2B4005232] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Long-term streamflow simulations using Land Surface Models are crucial for understanding hydrological responses to climate change. Model calibration is necessary to improve simulation performance and stability. The study introduced an adjusted Kling and Gupta Efficiency (aKGE) to achieve a more balanced optimal solution, demonstrating improved simulation accuracy in high and average flow while maintaining a slightly lower correlation compared to traditional criteria.
Long-term streamflow simulations of the Land Surface Models (LSMs) are necessary for the comprehensive evaluation of hydrological responses to climate change. The high complexity and uncertainty in the LSM modelling require the model calibration to improve the simulation performance and stability. Objective functions are commonly used in the calibration process, and the choice of objective functions plays a crucial role in model performance identification. The Kling and Gupta Efficiency (KGE) has been widely used in the hydrological model calibration by the measure of the three components (variability, bias, and correlation) decomposed from the Nash and Sutcliffe Efficiency (NSE). However, there is a clear tendency of systematic errors in the peak flow and/or water balance of streamflow time series optimized by the KGE calibration when the correlation between simulations and observations is relatively low. For a more balanced optimal solution of the KGE, this study has proposed the adjusted KGE (aKGE) by substituting the normalized correlation score in the KGE. The proposed aKGE was assessed by long-term daily streamflow simulation results from the Common Land Model (CoLM) for the calibration (2000-2009) and validation (2010-2019) periods in the Nakdong River Watershed, Korea. The case study demonstrated that the aKGE calibration can improve the simulation performance of high flow and annual average flow with a slightly inferior correlation of flows compared with the KGE and NSE criteria.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据