Importance of evaluation of global hydrological models (gHMs) before doing climate impact assessment was underlined in several studies. The main objective of this study is to evaluate the performance of six gHMs in simulating observed discharge for a set of 57 large catchments applying common metrics with thresholds for the monthly and seasonal dynamics and summarize them estimating an aggregated index of model performance for each model in each basin. One model showed a good performance, and other five showed a weak or poor performance in most of the basins. In 15 catchments, evaluation results of all models were poor. The model evaluation was supplemented by climate impact assessment for a subset of 12 representative catchments using (1) usual ensemble mean approach and (2) weighted mean approach based on model performance, and the outcomes were compared. The comparison of impacts in terms of mean monthly and mean annual discharges using two approaches has shown that in four basins, differences were negligible or small, and in eight catchments, differences in mean monthly, mean annual discharge or both were moderate to large. The spreads were notably decreased in most cases when the second method was applied. It can be concluded that for improving credibility of projections, the model evaluation and application of the weighted mean approach could be recommended, especially if the mean monthly (seasonal) impacts are of interest, whereas the ensemble mean approach could be applied for projecting the mean annual changes. The calibration of gHMs could improve their performance and, consequently, the credibility of projections.

中文翻译：

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全球水文模型评估如何有助于提高气候变化下河流流量预测的可信度

一些研究强调了在进行气候影响评估之前评估全球水文模型 (gHM) 的重要性。本研究的主要目的是评估 6 个 gHM 在模拟一组 57 个大型集水区的观测流量时的性能，应用具有月度和季节性动态阈值的通用指标，并总结它们，估计每个模型的模型性能汇总指数每个盆地。一个模型表现良好，其他五个模型在大多数盆地表现不佳或较差。在15个流域中，所有模型的评价结果​​都很差。使用 (1) 通常的集合平均方法和 (2) 基于模型性能的加权平均方法，对 12 个代表性集水区的子集进行气候影响评估补充模型评估，并对结果进行了比较。使用两种方法比较月平均和年平均排放量的影响表明，在四个流域中，差异可以忽略不计或很小，而在八个流域中，月平均、年平均排放量或两者的差异为中到大。在大多数情况下，当应用第二种方法时，点差会显着降低。可以得出的结论是，为了提高预测的可信度，可以推荐模型评估和加权平均法的应用，特别是如果对平均每月（季节性）影响感兴趣，而可以应用集合平均法来预测均值年度变化。gHM 的校准可以提高其性能，从而提高预测的可信度。使用两种方法比较月平均和年平均排放量的影响表明，在四个流域中，差异可以忽略不计或很小，而在八个流域中，月平均、年平均排放量或两者的差异为中到大。在大多数情况下，当应用第二种方法时，点差会显着降低。可以得出的结论是，为了提高预测的可信度，可以推荐模型评估和加权平均法的应用，特别是如果对平均每月（季节性）影响感兴趣，而可以应用集合平均法来预测均值年度变化。gHM 的校准可以提高其性能，从而提高预测的可信度。使用两种方法比较月平均和年平均排放量的影响表明，在四个流域中，差异可以忽略不计或很小，而在八个流域中，月平均、年平均排放量或两者的差异为中到大。在大多数情况下，当应用第二种方法时，点差会显着降低。可以得出的结论是，为了提高预测的可信度，可以推荐模型评估和加权平均法的应用，特别是如果对平均每月（季节性）影响感兴趣，而可以应用集合平均法来预测均值年度变化。gHM 的校准可以提高其性能，从而提高预测的可信度。