An empirical method to improve the prediction limits of the GLUE methodology in rainfall–runoff modeling
An empirical method to improve the prediction limits of the GLUE methodology in rainfall–runoff modeling
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DOI：
10.1016/j.jhydrol.2007.10.029
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发表时间：
2008-01
影响因子：
6.4
通讯作者：
L. Xiong;K. M. O'Connor
中科院分区：
文献类型：
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作者：
L. Xiong;K. M. O'Connor
广义似然不确定性估计（GLUE）方法是研究水资源与环境模型中不确定性的最常用方法之一。然而，一些研究发现，在许多情况下，落在GLUE提供的预测限内的观测值的百分比远低于用于产生这些预测限的给定确定性水平。导致包络效率如此之低的一个可能原因是，由于GLUE方法不加区别地接受水文模型的模拟输出作为其输入，水文模型模拟输出中的误差将直接反映在GLUE方法提供的预测限值中。因此，建议在本文中修改原来的GLUE方法，通过应用一个新的程序，旨在至少部分地纠正水文模型的模拟/预测之前，在每个时间步的预测限制的推导，试图提高GLUE预测限制的效率，在包围现实世界的观察。为了检验这个简单的概念，无论是原来的GLUE和建议修改后的GLUE方法已被用来产生两个不同的集水区的径流预测限制。在包含率方面，即由相应的径流预测限值包围的观测数据的百分比，修改后的GLUE方法在校准和验证期间均显示出比原始方法有实质性的改进。
The generalized likelihood uncertainty estimation (GLUE) method is one of the most widely used methods for investigating the uncertainties in the water resources and environmental modeling. However, some researches have found that the percentage of the observations falling within the prediction limits provided by the GLUE is much lower than the given certainty level used to produce these prediction limits in many cases. One possible reason contributing to such a low enveloping efficiency is the fact that, as the GLUE method indiscriminatingly accepts the simulation output of the hydrological model as its input, the errors in the simulation output of the hydrological model will be directly reflected in the prediction limits provided by the GLUE method. So, it is suggested in this paper to modify the original GLUE methodology by applying a new procedure designed to at least partially correct the simulation/prediction of the hydrological model prior to the derivation of the prediction limits at each time step, in an attempt to improve the efficiency of the GLUE prediction limits in enveloping the real-world observations. To test this simple concept, both the original GLUE and the suggested modified GLUE methods have been employed to produce the prediction limits of runoff on two different catchments. In terms of the containing ratio, i.e. the percentage of the observed data bracketed by the respective runoff prediction limits, the modified GLUE method has shown substantial improvements over the original method, in both the calibration and the verification periods.