Simulation of dynamic expansion, contraction, and connectivity in a mountain stream network
Simulation of dynamic expansion, contraction, and connectivity in a mountain stream network
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DOI：
10.1016/j.advwatres.2018.01.018
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发表时间：
2018-04-01
影响因子：
4.7
通讯作者：
Wondzell, Steven M.
中科院分区：
文献类型：
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作者：
Ward, Adam S.;Schmadel, Noah M.;Wondzell, Steven M.
源头河流网络的扩张和收缩是对河流流量变化的反应。河流网络范围的变化也受地质或地貌环境的控制-有些河段甚至在相对潮湿的条件下变干，其他河段在相对干燥的条件下保持流动。虽然这种模式是公认的，但我们目前缺乏工具来预测河流网络的范围以及大型河流网络中网络干涸的时间和位置。在这里，我们开发了一个感知模型的河流走廊在源头山区集水区，将其转化为一个降低复杂性的机械模型，并实施该模型来检查整个水年的连通性和网络范围。我们的模型与我们的观测结果相当吻合，表明在最低流量（Q（gauge）< 1 L s（-1））下，河网的范围和连通性对水文强迫最为敏感，在中等流量下，（1 L s（-1）< Q（gauge）< 10 L s（-1））网络的范围随着流量的变化而显著变化，在湿润条件下（Q（gauge）> 10 L s（-1）），网络的范围对水文强迫相对不敏感，而是由网络的拓扑结构决定。我们不期望在本研究中观察到的特定阈值可以转移到具有不同地质、拓扑或水文强迫的其他集水区。然而，我们预计，一般的模式应该是强大的：占主导地位的控制将从水文迫使地质环境流量的增加。此外，我们的方法是很容易转移的模型可以应用于最小的数据要求（一个单一的流计，数字地形模型，水文地质特性的估计），以估计流量持续时间或连接沿着未研究的流域河流走廊。随着可用信息的增加，该模型可以更好地校准，以匹配特定网站的网络范围，位置的干河段，或溶质突破曲线的观察，如本研究所示。基于低初始数据的要求和能力，后来调整模型到一个特定的网站，我们建议这个吝啬的模型，可能会被证明是有用的研究人员和管理人员的示例应用程序。(C)2018爱思唯尔有限公司版权所有。
Headwater stream networks expand and contract in response to changes in stream discharge. The changes in the extent of the stream network are also controlled by geologic or geomorphic setting - some reaches go dry even under relatively wet conditions, other reaches remain flowing under relatively dry conditions. While such patterns are well recognized, we currently lack tools to predict the extent of the stream network and the times and locations where the network is dry within large river networks. Here, we develop a perceptual model of the river corridor in a headwater mountainous catchment, translate this into a reduced-complexity mechanistic model, and implement the model to examine connectivity and network extent over an entire water year. Our model agreed reasonably well with our observations, showing that the extent and connectivity of the river network was most sensitive to hydrologic forcing under the lowest discharges (Q(gauge) < 1 L s(-1)), that at intermediate discharges (1 L s(-1) < Q(gauge) < 10 L s(-1)) the extent of the network changed dramatically with changes in discharge, and that under wet conditions (Q(gauge) > 10 L s(-1)) the extent of the network was relatively insensitive to hydrologic forcing and was instead determined by the network topology. We do not expect that the specific thresholds observed in this study would be transferable to other catchments with different geology, topology, or hydrologic forcing. However, we expect that the general pattern should be robust: the dominant controls will shift from hydrologic forcing to geologic setting as discharge increases. Furthermore, our method is readily transferable as the model can be applied with minimal data requirements (a single stream gauge, a digital terrain model, and estimates of hydrogeologic properties) to estimate flow duration or connectivity along the river corridor in unstudied catchments. As the available information increases, the model could be better calibrated to match site-specific observations of network extent, locations of dry reaches, or solute break through curves as demonstrated in this study. Based on the low initial data requirements and ability to later tune the model to a specific site, we suggest example applications of this parsimonious model that may prove useful to both researchers and managers. (C) 2018 Elsevier Ltd. All rights reserved.