气候变化领域集成服务门户(CCPortal): On the choice of calibration metrics for "high-flow" estimation using hydrologic models

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DOI	10.5194/hess-23-2601-2019
	On the choice of calibration metrics for "high-flow" estimation using hydrologic models
	Mizukami N.; Rakovec O.; Newman A.J.; Clark M.P.; Wood A.W.; Gupta H.V.; Kumar R.
发表日期	2019
ISSN	1027-5606
起始页码	2601
结束页码	2614
卷号	23 期号:6
英文摘要	Calibration is an essential step for improving the accuracy of simulations generated using hydrologic models. A key modeling decision is selecting the performance metric to be optimized. It has been common to use squared error performance metrics, or normalized variants such as Nash-Sutcliffe efficiency (NSE), based on the idea that their squared-error nature will emphasize the estimates of high flows. However, we conclude that NSE-based model calibrations actually result in poor reproduction of high-flow events, such as the annual peak flows that are used for flood frequency estimation. Using three different types of performance metrics, we calibrate two hydrological models at a daily step, the Variable Infiltration Capacity (VIC) model and the mesoscale Hydrologic Model (mHM), and evaluate their ability to simulate high-flow events for 492 basins throughout the contiguous United States. The metrics investigated are (1) NSE, (2) Kling-Gupta efficiency (KGE) and its variants, and (3) annual peak flow bias (APFB), where the latter is an application-specific metric that focuses on annual peak flows. As expected, the APFB metric produces the best annual peak flow estimates; however, performance on other high-flow-related metrics is poor. In contrast, the use of NSE results in annual peak flow estimates that are more than 20% worse, primarily due to the tendency of NSE to underestimate observed flow variability. On the other hand, the use of KGE results in annual peak flow estimates that are better than from NSE, owing to improved flow time series metrics (mean and variance), with only a slight degradation in performance with respect to other related metrics, particularly when a non-standard weighting of the components of KGE is used. Stochastically generated ensemble simulations based on model residuals show the ability to improve the high-flow metrics, regardless of the deterministic performances. However, we emphasize that improving the fidelity of streamflow dynamics from deterministically calibrated models is still important, as it may improve high-flow metrics (for the right reasons). Overall, this work highlights the need for a deeper understanding of performance metric behavior and design in relation to the desired goals of model calibration. © 2019 The Author(s).
语种	英语
scopus关键词	Efficiency; Flood control; Floods; Application specific; Ensemble simulation; Flood frequency estimation; Hydrologic modeling; Hydrological models; Performance metrices; Performance metrics; Variable infiltration capacity models; Frequency estimation; calibration; estimation method; flood; flood frequency; hydrological modeling; peak flow; streamflow; United States
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/159667
作者单位	Mizukami, N., National Center for Atmospheric Research, Research Application Laboratory, Boulder, CO, United States; Rakovec, O., UFZ-Helmholtz Centre for Environmental Research, Department of Computational Hydrosystems, Leipzig, Germany, Czech University of Life Sciences, Faculty of Environmental Sciences, Prague, Czech Republic; Newman, A.J., National Center for Atmospheric Research, Research Application Laboratory, Boulder, CO, United States; Clark, M.P., National Center for Atmospheric Research, Research Application Laboratory, Boulder, CO, United States, Coldwater Laboratory, University of Saskatchewan, Canmore, AB, Canada; Wood, A.W., National Center for Atmospheric Research, Research Application Laboratory, Boulder, CO, United States; Gupta, H.V., Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, United States; Kumar, R., UFZ-Helmholtz Centre for Environmental Research, Department of Computational Hydrosystems, Leipzig, Germany
推荐引用方式 GB/T 7714	Mizukami N.,Rakovec O.,Newman A.J.,et al. On the choice of calibration metrics for "high-flow" estimation using hydrologic models[J],2019,23(6).
APA	Mizukami N..,Rakovec O..,Newman A.J..,Clark M.P..,Wood A.W..,...&Kumar R..(2019).On the choice of calibration metrics for "high-flow" estimation using hydrologic models.Hydrology and Earth System Sciences,23(6).
MLA	Mizukami N.,et al."On the choice of calibration metrics for "high-flow" estimation using hydrologic models".Hydrology and Earth System Sciences 23.6(2019).