Evaluating the use of "goodness-of-fit" measures in hydrologic and hydroclimatic model validation
Evaluating the use of "goodness-of-fit" measures in hydrologic and hydroclimatic model validation
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DOI：
10.1029/1998wr900018
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发表时间：
1999-01-01
影响因子：
5.4
通讯作者：
McCabe, GJ
中科院分区：
文献类型：
--
作者：
Legates, DR;McCabe, GJ
基于相关和基于相关的度量（例如，确定系数）已被广泛用于评估水文和氢化气候模型的“拟合度”。这些措施对极值（离群值）过度敏感，并且对模型预测和观察之间的加性和比例差异不敏感。由于这些局限性，基于相关的度量可以表明模型是一个很好的预测指标，即使不是。在本文中，讨论了克服基于相关措施的许多局限性的有用替代性拟合优度或相对误差度量（包括效率系数和协议指数）。提出了对这些统计数据的修改，以帮助解释。可以得出结论，不应使用基于相关性和基于相关的措施来评估水文或氢化气候模型的合适性，并且其他评估措施（例如摘要统计和绝对错误指标）应补充模型评估工具。
Correlation and correlation-based measures (e.g., the coefficient of determination) have been widely used to evaluate the "goodness-of-fit" of hydrologic and hydroclimatic models. These measures are oversensitive to extreme values (outliers) and are insensitive to additive and proportional differences between model predictions and observations. Because of these limitations, correlation-based measures can indicate that a model is a good predictor, even when it is not. In this paper, useful alternative goodness-of-fit or relative error measures (including the coefficient of efficiency and the index of agreement) that overcome many of the limitations of correlation-based measures are discussed. Modifications to these statistics to aid in interpretation are presented. It is concluded that correlation and correlation-based measures should not be used to assess the goodness-of-fit of a hydrologic or hydroclimatic model and that additional evaluation measures (such as summary statistics and absolute error measures) should supplement model evaluation tools.