Projections of Selenga river runoff in the XXI century and uncertainty estimates

T. Millionshchikova
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引用次数: 2

Abstract

Abstract. The Selenga River, which originates in Mongolia, contributes nearly 50 % of the total inflow into Lake Baikal. Since 1996, the longest low-flow period has been observed. This paper focuses on the spatially distributed process-based modeling to assess possible runoff changes under climate projections in the XXI century using an ensemble of global climate models (GCMs) from ISI-MIP2 (Inter-Sectoral Impact Model Intercomparison Project, phase 2) and RCP-scenarios (Representative Concentration Pathway) as inputs. The ECOMAG hydrological model was applied to simulate possible runoff changes in the Selenga River basin. According to the simulations, the low-flow runoff into Lake Baikal will be continued throughout the XXI century under all the RCP-scenarios. Furthermore, as hydrological projections for the future are characterized by significant climate projections uncertainty, ANOVA (analyses of variance) test was used to quantify the sources of this uncertainty. The calculations showed that the contribution of the model uncertainty (differences between GCMs) is much higher than the contribution of the scenario uncertainty (variability of RCP-scenarios) although it increases at the end of the century.
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21世纪色楞嘎河径流的预估及不确定性估计
摘要发源于蒙古的色楞嘎河贡献了贝加尔湖总水量的近50%。自1996年以来,观测到最长的低流量期。本文利用ISI-MIP2 (Inter-Sectoral Impact Model intercomparonproject, phase 2)和rcp -scenario (Representative Concentration Pathway)的全球气候模式集合作为输入,重点研究了基于空间分布过程的模型,以评估21世纪气候下可能的径流变化。应用西非监测组水文模型模拟色楞格河流域可能的径流变化。根据模拟结果,在所有rcp情景下,进入贝加尔湖的低流量径流将持续整个21世纪。此外,由于未来的水文预估具有显著的气候预估不确定性,因此使用方差分析(ANOVA)检验来量化这种不确定性的来源。计算表明,模式不确定性(gcm之间的差异)的贡献远高于情景不确定性(rcp情景的变率)的贡献,尽管它在本世纪末有所增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Proceedings of the International Association of Hydrological Sciences
Proceedings of the International Association of Hydrological Sciences Earth and Planetary Sciences-Earth and Planetary Sciences (all)
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12 weeks
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