The movement of solutes in a watershed is a complex process with multiple interactions and feedbacks across spatial and temporal scales. Modeling the dynamics of solute transport along diverse hydrologic pathways within watersheds – from hillslopes to stream channels and in and out of the hyporheic zones – is challenging but critically important, as these processes integrate and contribute to the biogeochemical functioning of the river corridor up to the river network scale. Here we use results from a long-term network-scale tracer test at the H.J. Andrews experimental forest in western Cascade Mountains, Oregon, USA to inform a multiscale framework for transport in stream corridors. The framework uses a Lagrangian-based subgrid model to represent the effects of hyporheic exchange flow and advective transport at stream network scales. The spatially and temporally resolved stream discharge needed for the transport model is imputed across the river system by an entity-aware long short-term memory network. Modeled concentrations show good agreements with the observations and exhibit power scaling laws indicative of a very wide range of timescales over which hyporheic exchange flow occurs. Our results demonstrate a data-informed modeling framework that links dynamical processes occurring at small scales to a network context to help understand how changes at reach scale cascade into network-scale effects, providing a useful tool for sustainable river basin management.

中文翻译：

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山间溪流中溶质迁移的水文连通性和动力学：长期示踪剂测试和机器学习提供的多尺度迁移模型的见解


流域中溶质的运动是一个复杂的过程，在空间和时间尺度上存在多种相互作用和反馈。对流域内从山坡到河道以及进出潜流区的不同水文路径的溶质运移动态进行建模具有挑战性，但至关重要，因为这些过程整合并有助于河流走廊的生物地球化学功能河网规模。在这里，我们使用在美国俄勒冈州喀斯喀特山脉西部 HJ 安德鲁斯实验森林进行的长期网络规模示踪剂测试的结果，为河流走廊中的运输提供多尺度框架。该框架使用基于拉格朗日的子网格模型来表示河流网络规模下的潜流交换流和平流输送的影响。运输模型所需的空间和时间解析的河流流量由实体感知的长短期记忆网络估算在整个河流系统中。模拟浓度与观察结果显示出良好的一致性，并表现出功率缩放定律，表明潜流交换流发生的时间尺度非常广泛。我们的结果展示了一个基于数据的建模框架，该框架将小规模发生的动态过程与网络环境联系起来，以帮助理解河段规模的变化如何级联成网络规模效应，为可持续流域管理提供有用的工具。