To understand the water balance and other environmental impacts under climate change condition, hydrological models are used to simulate the hydrological cycle and predict future scenarios by using general circulation models (GCMs) outputs. Due to the mismatch of the spatial resolution, different downscaling techniques are usually applied to GCMs outputs to generate higher resolution data for the use with the hydrological models. It is known that there are many uncertainties with hydrological models which lead to inaccuracy and unreliability of the predictions. The uncertainty associated with climate change has been described as irreducible and persistent, and downscaling GCM outputs using downscaling methods also lead to considerable uncertainties. The purpose of this study is to propose a method to quantify the propagation effects of uncertainties from statistical downscaling to hydrological modeling. A case study has been provided in this study to demonstrate the feasibility of the proposed method. Statistical downscaling model (SDSM) was applied to downscale H3A2a (A2 emission scenario in Hadley Centre Coupled Model 3) outputs, and the downscaled results were used as inputs to a distributed hydrological model - the soil and water assessment tool (SWAT). The surface runoff prediction has been made for 2016 ~ 2020 by using downscaled precipitation and temperature. The uncertainty associated with statistical downscaling has been quantified through the evaluation of surface runoff simulation from the application of the hydrological modeling study.

中文翻译：

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在降水和温度统计降尺度到水文建模过程中不确定性传播效应的量化

为了了解气候变化条件下的水平衡和其他环境影响，水文模型用于模拟水文循环并通过使用一般循环模型 (GCM) 输出预测未来情景。由于空间分辨率的不匹配，不同的降尺度技术通常应用于 GCM 输出，以生成更高分辨率的数据，供水文模型使用。众所周知，水文模型存在许多不确定性，导致预测不准确和不可靠。与气候变化相关的不确定性被描述为不可减少和持久的，使用缩减方法缩减 GCM 输出也会导致相当大的不确定性。本研究的目的是提出一种量化不确定性从统计降尺度到水文建模的传播效应的方法。本研究提供了一个案例研究，以证明所提出方法的可行性。将统计降尺度模型 (SDSM) 应用于降尺度 H3A2a（哈德利中心耦合模型 3 中的 A2 排放情景）输出，并将降尺度结果用作分布式水文模型 - 土壤和水评估工具 (SWAT) 的输入。利用降尺度降水和温度对2016~2020年地表径流进行了预测。与统计降尺度相关的不确定性已通过应用水文建模研究对地表径流模拟的评估进行量化。