气候变化领域集成服务门户(CCPortal): Quantifying Uncertainty in Runoff Simulation According to Multiple Evaluation Metrics and Varying Calibration Data Length

CCPortal

DOI	10.3390/w16040517
	Quantifying Uncertainty in Runoff Simulation According to Multiple Evaluation Metrics and Varying Calibration Data Length
	Ziarh, Ghaith Falah; Kim, Jin Hyuck; Song, Jae Yeol; Chung, Eun-Sung
发表日期	2024
EISSN	2073-4441
起始页码	16
结束页码	4
卷号	16 期号:4
英文摘要	In this study, the uncertainty in runoff simulations using hydrological models was quantified based on the selection of five evaluation metrics and calibration data length. The calibration data length was considered to vary from 1 to 11 years, and runoff analysis was performed using a soil and water assessment tool (SWAT). SWAT parameter optimization was then performed using R-SWAT. The results show that the uncertainty was lower when using a calibration data length of five to seven years, with seven years achieving the lowest uncertainty. Runoff simulations using a calibration data length of more than seven years yielded higher uncertainty overall but lower uncertainty for extreme runoff simulations compared to parameters with less than five years of calibration data. Different uncertainty evaluation metrics show different levels of uncertainty, which means it is necessary to consider multiple evaluation metrics rather than relying on any one single metric. Among the evaluation metrics, the Nash-Sutcliffe model efficiency coefficient (NSE) and normalized root-mean-squared error (NRMSE) had large uncertainties at short calibration data lengths, whereas the Kling-Gupta efficiency (KGE) and Percent Bias (Pbias) had large uncertainties at long calibration data lengths.
英文关键词	uncertainty quantification; evaluation metrics; calibration data length
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Water Resources
WOS类目	Environmental Sciences ; Water Resources
WOS记录号	WOS:001172315300001
来源期刊	WATER
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/294207
作者单位	Seoul National University of Science & Technology
推荐引用方式 GB/T 7714	Ziarh, Ghaith Falah,Kim, Jin Hyuck,Song, Jae Yeol,et al. Quantifying Uncertainty in Runoff Simulation According to Multiple Evaluation Metrics and Varying Calibration Data Length[J],2024,16(4).
APA	Ziarh, Ghaith Falah,Kim, Jin Hyuck,Song, Jae Yeol,&Chung, Eun-Sung.(2024).Quantifying Uncertainty in Runoff Simulation According to Multiple Evaluation Metrics and Varying Calibration Data Length.WATER,16(4).
MLA	Ziarh, Ghaith Falah,et al."Quantifying Uncertainty in Runoff Simulation According to Multiple Evaluation Metrics and Varying Calibration Data Length".WATER 16.4(2024).