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A test of Snowmelt Runoff Model (SRM) for the Gongnaisi River basin in the western Tianshan Mountains, China

机译:中国天山西部巩乃斯河流域融雪径流模型(SRM)的测试

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The Snowmelt Runoff Model (SRM) is one of a very few models in the world today that requires remote sensing derived snow cover as model input. Owing to its simple data requirements and use of remote sensing to provide snow cover information, SRM isideal for use in data sparse regions, particularly in remote and inaccessible high mountain watersheds. In order to verify the applicability of SRM in an environment of continental climate, a test of SRM is performed for the Gongnaisi River basin in thewestern Tianshan Mountains, the results show that two SRM average goodness-of-fit statistics for simulations, Nash-Sutcliff coefficient (R~2) and volume difference (Dv), are 0.87 and 0.90 percent, respectively. As compared with the application results over 80 basins in 25 different countries around the world, SRM performs well in the Gongnaisi River basin. The results also show that SRM can be a validated snowmelt runoff model capable of being applied in the western Tianshan Mountains. On the basis of snowmelt runoff simulation, together with a set of simplified hypothetical climate scenarios. SRM is also used to simulate the effects of climate change on snow cover and the consecutive snowmelt runoff. For a given hypothetical temperature increase of 4deg C. the snow coverage and snowmelt season shift towards earlier dates, and the snowmelt runoff, as a result, is changed significantly at the same time. The simulation results show that the snow cover is sensitive to changes of climate, especially to the increase of temperature, the major effect of climate change will be a time shifting of snowmelt runoff to early spring months, resulting in a redistribution of seasonally runoff throughout the whole snowmelt season.
机译:融雪径流模型(SRM)是当今世界上少数需要遥感衍生的积雪作为模型输入的模型之一。由于其简单的数据要求以及使用遥感技术提供积雪信息,SRM非常适合用于数据稀疏地区,尤其是在偏远且人迹罕至的高山流域中。为了验证SRM在大陆性气候环境中的适用性,对天山西部的贡奈斯河流域进行了SRM测试,结果表明,两个用于模拟的SRM平均拟合优度统计数据是Nash-Sutcliff系数(R〜2)和体积差(Dv)分别为0.87%和0.90%。与全球25个不同国家/地区的80多个流域的应用结果相比,SRM在贡奈斯河流域表现良好。结果还表明,SRM可以作为一种有效的融雪径流模型,可以在西天山山区应用。在融雪径流模拟的基础上,结合一组简化的假设气候情景。 SRM还用于模拟气候变化对积雪和连续融雪径流的影响。对于给定的假设温度升高4°C,积雪和融雪季节朝着较早的日期转移,结果,融雪径流同时显着变化。模拟结果表明,积雪对气候变化特别是温度升高敏感,气候变化的主要影响将是融雪径流到春季初几个月的时间偏移,从而导致整个季节的季节性径流重新分配。整个融雪季节。

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