This paper introduces the Special Issue (SI) “How evaluation of hydrological models influences results of climate impact assessment.” The main objectives were as follows: (a) to test a comprehensive model calibration/validation procedure, consisting of five steps, for regional-scale hydrological models; (b) to evaluate performance of global-scale hydrological models; and (c) to reveal whether the calibration/validation methods and the model evaluation results influence climate impacts in terms of the magnitude of the change signal and the uncertainty range. Here, we shortly describe the river basins and large regions used as case studies; the hydrological models, data, and climate scenarios used in the studies; and the applied approaches for model evaluation and for analysis of projections for the future. After that, we summarize the main findings. The following general conclusions could be drawn. After successful comprehensive calibration and validation, the regional-scale models are more robust and their projections for the future differ from those of the model versions after the conventional calibration and validation. Therefore, climate impacts based on the former models are more trustworthy than those simulated by the latter models. Regarding the global-scale models, using only models with satisfactory or good performance on historical data and weighting them based on model evaluation results is a more reliable approach for impact assessment compared to the ensemble mean approach that is commonly used. The former method provides impact results with higher credibility and reduced spreads in comparison to the latter approach. The studies for this SI were performed in the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP).

中文翻译：

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水文模型评估如何影响气候影响评估的结果——社论

本文介绍了特刊 (SI)“水文模型的评估如何影响气候影响评估的结果”。主要目标如下： (a) 为区域尺度水文模型测试由五个步骤组成的综合模型校准/验证程序；(b) 评估全球尺度水文模型的性能；(c) 揭示校准/验证方法和模型评估结果是否在变化信号的幅度和不确定性范围方面影响气候影响。在这里，我们简要描述了用作案例研究的流域和大片区域；研究中使用的水文模型、数据和气候情景；以及模型评估和未来预测分析的应用方法。之后，我们总结了主要发现。可以得出以下一般性结论。综合标定验证成功后，区域尺度模型更加稳健，对未来的预测与常规标定验证后的模型版本不同。因此，基于前一种模型的气候影响比后一种模型模拟的气候影响更值得信赖。对于全球尺度模型，仅使用对历史数据表现令人满意或良好的模型，并根据模型评估结果对其进行加权，与常用的集合平均法相比，是一种更可靠的影响评估方法。与后一种方法相比，前一种方法提供的影响结果具有更高的可信度和更低的差价。