Soulsby C, Birkel C, Geris J, Dick J, Tunaley C, Tetzlaff D
Northern Rivers Institute, School of Geosciences, University of Aberdeen UK.
Northern Rivers Institute, School of Geosciences, University of Aberdeen UK; Department of Geography University of Costa Rica, San Pedro Montes de Oca Costa Rica.
Water Resour Res. 2015 Sep;51(9):7759-7776. doi: 10.1002/2015WR017888. Epub 2015 Sep 26.
To assess the influence of storage dynamics and nonlinearities in hydrological connectivity on time-variant stream water ages, we used a new long-term record of daily isotope measurements in precipitation and streamflow to calibrate and test a parsimonious tracer-aided runoff model. This can track tracers and the ages of water fluxes through and between conceptual stores in steeper hillslopes, dynamically saturated riparian peatlands, and deeper groundwater; these represent the main landscape units involved in runoff generation. Storage volumes are largest in groundwater and on the hillslopes, though most dynamic mixing occurs in the smaller stores in riparian peat. Both streamflow and isotope variations are generally well captured by the model, and the simulated storage and tracer dynamics in the main landscape units are consistent with independent measurements. The model predicts that the average age of stream water is ∼1.8 years. On a daily basis, this varies between ∼1 month in storm events, when younger waters draining the hillslope and riparian peatland dominates, to around 4 years in dry periods when groundwater sustains flow. This variability reflects the integration of differently aged water fluxes from the main landscape units and their mixing in riparian wetlands. The connectivity between these spatial units varies in a nonlinear way with storage that depends upon precipitation characteristics and antecedent conditions. This, in turn, determines the spatial distribution of flow paths and the integration of their contrasting nonstationary ages. This approach is well suited for constraining process-based modeling in a range of northern temperate and boreal environments.
为了评估水文连通性中的存储动态和非线性对时变河流水龄的影响，我们使用了一份新的长期每日降水和径流同位素测量记录，来校准和测试一个简约的示踪剂辅助径流模型。该模型可以追踪示踪剂以及水流在较陡山坡、动态饱和的河岸泥炭地和深层地下水中的概念性存储之间的通量年龄；这些代表了径流产生过程中涉及的主要景观单元。地下和山坡的存储量最大，不过大多数动态混合发生在河岸泥炭地较小的存储区域。模型通常能很好地捕捉径流和同位素变化，并且在主要景观单元中模拟的存储和示踪剂动态与独立测量结果一致。该模型预测河水的平均年龄约为1.8年。在每日尺度上，这一数值在暴雨事件中约为1个月（此时来自山坡和河岸泥炭地的较年轻水流占主导）到干旱期约4年（此时地下水维持径流）之间变化。这种变化反映了来自主要景观单元的不同年龄水流通量的整合以及它们在河岸湿地中的混合情况。这些空间单元之间的连通性随存储量呈非线性变化，这取决于降水特征和前期条件。反过来，这又决定了水流路径的空间分布以及它们不同的非平稳年龄的整合情况。这种方法非常适合用于约束一系列北温带和寒带环境中基于过程的建模。
