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The Stream Length Duration Curve: A Tool for Characterizing the Time Variability of the Flowing Stream Length

机译:流长度持续时间曲线:用于表征流量流长度的时间可变性的工具

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In spite of the importance of stream network dynamics for hydrology, ecology, and biogeochemistry, there is limited availability of analytical tools suitable for characterizing the temporal variability of the active fraction of river networks. To fill this gap, we introduce the concept of Stream Length Duration Curve (SLDC), the inverse of the exceedance probability of the total length of active streams. SLDCs summarize efficiently the effect of hydrological variability on the length of the flowing streams under a variety of settings. A set of stochastic network models is developed to link the features of the local hydrological status of the network nodes with the shape of the SLDC. We show that the mean network length is dictated by the mean persistency of the nodes, whereas the shape of the SLDC is driven by the spatial distribution of the local persistencies and their network-scale spatial correlation. Ten field surveys performed in 2018 were used to estimate the empirical SLDC of the Valfredda river (Italy), which was found to be steep and regular-indicating a pronounced sensitivity of the active stream length to the underlying hydrological conditions. Available observations also suggest that the activation of temporary reaches during network expansion is hierarchical, from the most to the least persistent stretches. Under these circumstances, the SLDC corresponds to the spatial Cumulative Distribution Function of the nodes persistencies. The study provides a sound theoretical basis for the analyses of network dynamics in temporary rivers.Key PointsThe concept of Stream Length Duration Curve is formalized and applied to a real-world case study Stochastic models are developed to link the Stream Length Duration Curve to the network structure and local hydrological properties In the Valfredda catchment (Italy), the activation of temporary reaches follows a hierarchical order
机译:尽管流网络动力学的流程,生态和生物地球化学的重要性,适用于表征河流网络活动分数的时间变异性的分析工具有限。为了填补这个差距,我们介绍了流长度持续时间曲线(SLDC)的概念,反比活动流总长度的概率逆。 SLDCs总结了水文变异性在各种设置下流动流长度的影响。开发了一组随机网络模型,以将网络节点的局部水文状态的特征与SLDC的形状联系起来。我们表明,平均网络长度由节点的平均持久性决定,而SLDC的形状由本地持久性的空间分布及其网络级空间相关的驱动。 2018年执行的十个田间调查用于估计Valfredda河(意大利)的经验SLDC,该探测器被发现是陡峭的,并定期表明活性流长度与底层水文条件的明显敏感性。可用的观察还表明,在网络扩展期间临时达到的激活是分层,从最大到最不持久的延伸。在这种情况下,SLDC对应于节点持久性的空间累积分布函数。该研究为临时河流中的网络动态分析提供了一个声音理论依据.KEY的流长持续时间曲线的概念正式化并应用于真实的案例研究随机模型,以将流长度持续时间曲线链接到网络。在Valfredda集水区(意大利)中的结构和局部水文特性,临时达到的激活遵循分层顺序

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