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首页> 外文期刊>Hydrology and Earth System Sciences >Beyond binary baseflow separation: a delayed-flow index for multiple streamflow contributions
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Beyond binary baseflow separation: a delayed-flow index for multiple streamflow contributions

机译:超出二进制Basplow分离:多个流流贡献的延迟流索引

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Understanding components of the total streamflow is important to assess the ecological functioning of rivers. Binary or two-component separation of streamflow into a quick and a slow (often referred to as baseflow) component are often based on arbitrary choices of separation parameters and also merge different delayed components into one baseflow component and one baseflow index?(BFI). As streamflow generation during dry weather often results from drainage of multiple sources, we propose to extend the BFI by a delayed-flow index?(DFI) considering the dynamics of multiple delayed contributions to streamflow. The DFI is based on characteristic delay curves (CDCs) where the identification of breakpoint (BP) estimates helps to avoid rather subjective separation parameters and allows for distinguishing four types of delayed streamflow contributions. The methodology is demonstrated using streamflow records from a set of 60?mesoscale catchments in Germany and Switzerland covering a pronounced elevation gradient of roughly 3000 m. We found that the quickflow signal often diminishes earlier than assumed by two-component BFI analyses and distinguished a variety of additional flow contributions with delays shorter than 60 d. For streamflow contributions with delays longer than 60 d, we show that the method can be used to assess catchments' water sustainability during dry spells. Colwell's predictability (PT), a measure of streamflow periodicity and sustainability, was applied to attribute the identified delay patterns to dynamic catchment storage. The smallest dynamic storages were consistently found for catchments between approx.?800?and 1800 m a.s.l. Above an elevation of 1800 m the DFI suggests that seasonal snowpack provides the primary contribution, whereas below 800 m groundwater resources are most likely the major streamflow contributions. Our analysis also indicates that dynamic storage in high alpine catchments might be large and is overall not smaller than in lowland catchments. We conclude that the DFI can be used to assess the range of sources forming catchments' storages and to judge the long-term sustainability of streamflow.
机译:了解总流流的组件对于评估河流的生态功能非常重要。流流的二进制或双组分分离为快速且慢速(通常称为Baspflow)分量通常基于分离参数的任意选择,并且还将不同的延迟组件合并到一个基流组件和一个基础流指数中?(BFI)。随着干燥天气期间的流出产生通常由多种来源的排水产生,我们建议通过延迟流量指数扩展BFI?(DFI)考虑到流流的多个延迟贡献的动态。 DFI基于特征延迟曲线(CDC),其中断点(BP)估计有助于避免相当主观的分离参数,并允许区分四种类型的延迟流流贡献。使用来自德国和瑞士的一组60的流出记录来证明方法学,涵盖大约3000米的明显高度梯度。我们发现,QuickFlow信号通常比双组分BFI分析的假定更早地降低,并区分了延迟短于60d的延迟的各种额外流量贡献。对于延迟超过60 d的流流贡献,我们表明该方法可用于评估干法术期间的集水区的水可持续性。 COLWOLL的可预测性(PT),流流周期性和可持续性的量度被应用于将所识别的延迟模式归因于动态集群存储器。最小的动态故障始终找到了大约在约1800米A.S.L.中的集水区。高于1800米的海拔,DFI表明季节性积雪提供了主要贡献,而低于800米的地下水资源最有可能是主要的流流贡献。我们的分析还表明,高山集水区中的动态存储可能很大,总体上不小于低地集水区。我们得出结论,DFI可用于评估形成集水区的流源范围,并判断流流的长期可持续性。

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