Abstract Despite decades of research into air and stream temperature dynamics, paired air-water annual temperature signals have been underutilized to characterize watershed processes. Annual stream temperature dynamics are useful in classifying fundamental thermal regimes and can enhance process-based interpretation of stream temperature controls, including deep and shallow groundwater discharge, when paired with air signals. In this study, we investigated multi-scale variability in annual paired air-water temperature patterns using sine-wave linear regressions of multi-year daily temperature data from streams of various sizes. A total of 311 sites from two spatially intensive regional datasets (Shenandoah National Park and Olympic Experimental State Forest) and a spatially extensive national dataset spanning the contiguous United States (U.S. Geological Survey gages) were evaluated. We calculated three annual air-water thermal metrics (mean ratio, phase lag, and amplitude ratio) to deduce the influence of groundwater and other watershed processes on stream thermal regimes at multiple spatial scales. Site-specific values of the three annual air-water thermal metrics ranged from 0.69 to 5.29 (mean ratio), −9 to 40 days (phase lag), and 0.29 to 1.12 (amplitude ratio). Regional patterns in the annual thermal metrics revealed persistent yet spatially variable influences of shallow groundwater discharge and high levels of thermal variability within watersheds, indicating the importance of local hydrogeological controls on stream temperature. Furthermore, annual thermal metric patterns from the regional datasets were generally concordant with the national dataset suggesting the utility of these annual thermal metrics for analysis at multiple scales. Analysis of the national dataset showed that previously defined thermal regimes based on water temperature alone could be further refined using air-water metrics and these metrics were related to physiographic watershed characteristics such as contributing area, elevation, and slope. This research demonstrates the importance of spatial scale and heterogeneity for inferring hydrological process in streams and provides guidance for the interpretation of annual air-water temperature metrics that can be efficiently applied to the growing database of multi-year temperature records. Results from this research can aid in the prediction of future thermal habitat suitability for coldwater-adapted species at ecologically and management-relevant spatial scales with readily available data.

中文翻译：

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成对的空气-水年温度模式揭示了流域到大陆尺度河流热状况的水文地质控制

摘要 尽管对空气和溪流温度动力学进行了数十年的研究，但未充分利用成对的空气-水年温度信号来表征流域过程。年度河流温度动态可用于对基本热状况进行分类，并在与空气信号配对时增强对河流温度控制的基于过程的解释，包括深层和浅层地下水排放。在这项研究中，我们使用来自不同大小河流的多年日温度数据的正弦波线性回归研究了年度配对空气-水温度模式的多尺度变异性。来自两个空间密集型区域数据集（Shenandoah 国家公园和奥林匹克实验州立森林）和跨越美国本土（美国）的空间广泛的国家数据集的总共 311 个站点 地质调查量具）进行了评估。我们计算了三个年度空气-水热指标（平均比、相位滞后和幅度比），以推断地下水和其他流域过程对多个空间尺度的河流热状况的影响。三个年度空气-水热指标的特定地点值范围为 0.69 至 5.29（平均比）、-9 至 40 天（相位滞后）和 0.29 至 1.12（幅度比）。年度热指标的区域模式揭示了浅层地下水排放和流域内高水平热变化的持续但空间可变的影响，表明当地水文地质控制对河流温度的重要性。此外，区域数据集的年度热指标模式与国家数据集大体一致，表明这些年度热指标可用于多尺度分析。对国家数据集的分析表明，先前仅基于水温定义的热状况可以使用空气-水指标进一步细化，这些指标与自然流域特征有关，例如贡献面积、海拔和坡度。这项研究证明了空间尺度和异质性对于推断河流中的水文过程的重要性，并为解释年度空气-水温指标提供了指导，这些指标可以有效地应用于不断增长的多年温度记录数据库。