气候变化领域集成服务门户(CCPortal): Technical note: Inherent benchmark or not? Comparing Nash-Sutcliffe and Kling-Gupta efficiency scores

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DOI	10.5194/hess-23-4323-2019
	Technical note: Inherent benchmark or not? Comparing Nash-Sutcliffe and Kling-Gupta efficiency scores
	Knoben W.J.M.; Freer J.E.; Woods R.A.
发表日期	2019
ISSN	1027-5606
起始页码	4323
结束页码	4331
卷号	23 期号:10
英文摘要	A traditional metric used in hydrology to summarize model performance is the Nash-Sutcliffe efficiency (NSE). Increasingly an alternative metric, the Kling-Gupta efficiency (KGE), is used instead. When NSE is used, NSE = 0 corresponds to using the mean flow as a benchmark predictor. The same reasoning is applied in various studies that use KGE as a metric: negative KGE values are viewed as bad model performance, and only positive values are seen as good model performance. Here we show that using the mean flow as a predictor does not result in KGE=0, but instead KGE = 1- √ 2 ∼ -0:41. Thus, KGE values greater than -0:41 indicate that a model improves upon the mean flow benchmark - even if the model's KGE value is negative. NSE and KGE values cannot be directly compared, because their relationship is non-unique and depends in part on the coefficient of variation of the observed time series. Therefore, modellers who use the KGE metric should not let their understanding of NSE values guide them in interpreting KGE values and instead develop new understanding based on the constitutive parts of the KGE metric and the explicit use of benchmark values to compare KGE scores against. More generally, a strong case can be made for moving away from ad hoc use of aggregated efficiency metrics and towards a framework based on purpose-dependent evaluation metrics and benchmarks that allows for more robust model adequacy assessment. © Author(s) 2019.
语种	英语
scopus关键词	Earth sciences; Hydrology; Coefficient of variation; Efficiency metrics; Evaluation metrics; Mean flow; Model performance; Positive value; Robust modeling; Technical notes; Efficiency; benchmarking; game theory; hydrology; model validation; numerical method; performance assessment; prediction
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159584
作者单位	Knoben, W.J.M., Department of Civil Engineering, University of Bristol, Bristol, BS8 1TR, United Kingdom, University of Saskatchewan, Coldwater Laboratory, Canmore, AB, Canada; Freer, J.E., School of Geographical Sciences, University of Bristol, Bristol, BS8 1BF, United Kingdom, Cabot Institute, University of Bristol, Bristol, BS8 1UJ, United Kingdom; Woods, R.A., Department of Civil Engineering, University of Bristol, Bristol, BS8 1TR, United Kingdom, Cabot Institute, University of Bristol, Bristol, BS8 1UJ, United Kingdom
推荐引用方式 GB/T 7714	Knoben W.J.M.,Freer J.E.,Woods R.A.. Technical note: Inherent benchmark or not? Comparing Nash-Sutcliffe and Kling-Gupta efficiency scores[J],2019,23(10).
APA	Knoben W.J.M.,Freer J.E.,&Woods R.A..(2019).Technical note: Inherent benchmark or not? Comparing Nash-Sutcliffe and Kling-Gupta efficiency scores.Hydrology and Earth System Sciences,23(10).
MLA	Knoben W.J.M.,et al."Technical note: Inherent benchmark or not? Comparing Nash-Sutcliffe and Kling-Gupta efficiency scores".Hydrology and Earth System Sciences 23.10(2019).