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首页> 外文期刊>Journal of hydrometeorology >Uncertainty in Future High Flows in Qiantang River Basin, China
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Uncertainty in Future High Flows in Qiantang River Basin, China

机译:钱塘江流域未来高流量的不确定性

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摘要

Uncertainties in high flows originating from greenhouse gas emissions scenarios, hydrological model structures, and their parameters for the Jinhua River basin, China, were assessed. The baseline (1961-90) and future (2011-40) climates for A1B, A2, and B2 scenarios were downscaled from the general circulation model (GCM) using the Providing Regional Climates for Impacts Studies (PRECIS) regional climate model with a spatial resolution of 50 km x 50 km. Bias-correction methods were applied to the PRECIS-derived temperature and precipitation. The bias-corrected precipitation and temperature were used as inputs for three hydrological models [modele du Genie Rural a 4 parametres Journalier (GR4J), Hydrologiska Byrans Vattenbalansavdelning (HBV), and Xinanjiang] to simulate high flows. The parameter uncertainty was considered and quantified in the hydrological model calibration by means of the generalized likelihood uncertainty estimation (GLUE) method for each hydrological model for the three emissions scenarios. It was found that, compared with the high flows in the baseline period, the high flows in the future tended to decrease under scenarios A1B, A2, and B2. The largest uncertainty was observed in HBV, and GR4J had the smallest uncertainty. It was found that the major source of uncertainty in this study was from parameters, followed by the uncertainties from the hydrological model structure, and the emissions scenarios have the smallest uncertainty contribution to high flows in this study.
机译:评估了来自中国金华河流域的温室气体排放情景,水文模型结构及其参数引起的高流量不确定性。 A1B,A2和B2情景的基准(1961-90)和未来(2011-40)的气候使用提供区域气候影响研究(PRECIS)区域气候模型和空间分布从普通环流模型(GCM)进行了缩减分辨率为50 km x 50 km。偏差校正方法应用于PRECIS得出的温度和降水。偏向校正后的降水和温度被用作三个水文模型的输入[模拟热那亚农村模型4参数新闻工作者(GR4J),Hydrologiska Byrans Vattenbalansavdelning(HBV)和新安江],以模拟高流量。在三种水文情景中,通过每种水文模型的广义似然不确定性估计(GLUE)方法,在水文模型校准中考虑并量化了参数不确定性。结果发现,与基准期的高流量相比,在方案A1B,A2和B2下,未来的高流量趋于减少。 HBV的不确定性最大,而GR4J的不确定性最小。发现本研究的不确定性的主要来源是参数,其次是水文模型结构的不确定性,而排放情景对高流量的不确定性贡献最小。

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