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首页> 外文期刊>Hydrology and Earth System Sciences Discussions >Monitoring snowpack outflow volumes and their isotopic composition to better understand streamflow generation during rain-on-snow events
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Monitoring snowpack outflow volumes and their isotopic composition to better understand streamflow generation during rain-on-snow events

机译:监测积雪流出体积及其同位素组成,以更好地了解雨雪赛事中的流出生成

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摘要

Rain-on-snow?(ROS) events in mountainous catchments can cause enhanced snowmelt, leading to an increased risk of destructive winter floods. However, due to differences in topography and forest cover, the generation of snowpack outflow volumes and their contribution to streamflow are spatially and temporally variable during ROS events. In order to adequately predict such flood events with hydrological models, an enhanced process understanding of the contribution of rainwater and snowmelt to stream water is needed. In this study, we monitored and sampled snowpack outflow with fully automated snowmelt lysimeter systems installed at three different elevations in a pre-Alpine catchment in central Switzerland. We measured snowpack outflow volumes during the winters of?2017 and?2018, as well as snowpack outflow isotopic compositions in winter?2017. Snowpack outflow volumes were highly variable in time and space, reflecting differences in snow accumulation and melt. In winter?2017, around 815mm of snowpack outflow occurred at our reference site (grassland 1220ma.s.l. – metres above sea level), whereas snowpack outflow was 16% less at the nearby forest site (1185ma.s.l.), and 62% greater at another grassland site located 200m higher (1420ma.s.l.). A detailed analysis of 10 ROS events showed that the differences in snowpack outflow volumes could be explained mainly by rainfall volumes and initial snow depths. The isotope signals of snowpack outflow were more damped than those of incoming rainwater at all three sites, with the most damped signal at the highest elevation site because its snowpack was the thickest and the residence times of liquid water in its snowpack were the longest, thus enhancing isotopic mixing in the snowpack. The contribution of snowpack outflow to streamflow, estimated with an isotope-based two-component end-member mixing model, differed substantially among the three lysimeter sites (i.e. between 7±4 and 91±21%). Because the vegetation in our study catchment is a mixture of grassland and forest, with elevations ranging from 1000?to 1500ma.s.l., our site-specific hydrograph separation estimates can only provide a range of snowpack outflow contributions to discharge from different parts of the study area. Thus, the catchment-average contribution of snowpack outflow to stream discharge is likely to lie between the end-member mixing estimates derived from the three site-specific data sets. This information may be useful for improving hydrological models in snow-dominated catchments.
机译:雨雪?(ROS)在山区集水区的活动可能导致增强的雪花,导致破坏性冬季洪水的风险增加。然而,由于地形和森林覆盖的差异,Snowpack流出卷的产生以及它们在流出流出的贡献在ROS事件期间在空间上和时间上变化。为了充分预测具有水文模型的这种洪水事件,需要增强的过程对雨水和融雪融入流水的贡献。在这项研究中,我们通过安装在瑞士中部阿尔卑斯州前集水区的三个不同海拔的全自动雪光型电晕系统进行了监测和采样的积雪流出。我们在2017年和2018年冬天的冬季测量了积雪流出卷,以及冬季的积雪流出同位素组合物2017年。积雪流出量在时间和空间中具有高度变化,反映了积雪积累和熔化的差异。在冬季(冬季)2017年,我们的参考网站(海拔1220ma.sl-meters)发生在大约815毫米的Snowpack Outflow中,而海上森林网站(1185ma.sl)少于16%,较大62%另一个草地遗址高200米(1420mA.SL)。对10个ROS事件的详细分析表明,积雪流出卷的差异可以主要通过降雨量和初始雪深度来解释。 Snowpack流出的同位素信号比在所有三个地点的进入雨水中更加抑制,最高升降网站上的最大阻尼信号,因为其积雪是最厚的,并且其积雪中的液体水的停留时间是最长的,因此增强积雪中的同位素混合。利用基于同位素的双组分结束元件混合模型估计的Snowpack流出到流流的贡献基本上不同于三个尿素位位点(即7±4和91±21%)中。因为我们的研究流域中的植被是草原和森林的混合,高度从1000到1000?到1500ma.sl,我们的网站特定的水文分离估计只能为从研究的不同部分提供一系列的积雪流出贡献区域。因此,积雪流出到流放电的集水区平均贡献可能位于从三个站点特定数据集导出的端构件混合估计之间。该信息对于改善雪主导地位中的水文模型可能是有用的。

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