Quantifying the transfer of organic carbon from the terrestrial to the riverine ecosystems is of crucial importance to fully appreciate the carbon cycle at the catchment, regional and global scales. In this study, we propose a framework for modeling the flux of dissolved organic carbon (DOC) from hillslopes to stream and river networks which couples a transport model based on travel time distributions with the reactivity continuum (RC) approach to model DOC degradation. We test the model by applying it to the Plynlimon catchments (UK) exploiting both weekly and high-frequency (7-hr interval) time-series. We use information about chloride to get an independent estimate of water travel times using the framework of StorAge Selection functions. Following the RC model, the composition and the degradation of DOC along the flowpaths, and its consequent concentration in the streamflow, is described assuming that DOC is composed by a mixture of compounds that follows a continuous spectrum of reactivity. For the high-frequency data set, the model is able to reproduce DOC streamflow concentrations and to capture the complex hysteretic relation between DOC concentration and discharge. Weekly data are instead not frequent enough to properly describe DOC dynamics in this catchment. The distribution of the age of the water comprised in the streamflow proves thus a key variable to predict the quantity and the reactivity of the DOC exported from soils, and the effect of hydrologic variability on this process.

中文翻译：

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集水区溶解有机碳迁移：一种结合水流时间和反应性连续体的建模方法

量化从陆地到河流生态系统的有机碳转移对于充分了解集水区、区域和全球范围内的碳循环至关重要。在这项研究中，我们提出了一个框架，用于模拟从山坡到河流和河流网络的溶解有机碳 (DOC) 通量，该框架将基于旅行时间分布的运输模型与反应性连续体 (RC) 方法相结合，以模拟 DOC 降解。我们通过利用每周和高频（7 小时间隔）时间序列将模型应用于 Plynlimon 集水区（英国）来测试该模型。我们使用有关氯化物的信息，使用存储选择函数的框架来独立估计水的传播时间。遵循 RC 模型，沿流路的 DOC 的组成和降解，假设 DOC 由遵循连续反应谱的化合物混合物组成，则描述了其在物流中的浓度。对于高频数据集，该模型能够再现 DOC 流量浓度并捕捉 DOC 浓度和排放之间的复杂滞后关系。相反，每周数据的频率不足以正确描述该流域中的 DOC 动态。因此，溪流中包含的水的年龄分布证明是预测从土壤中输出的 DOC 的数量和反应性以及水文变化对这一过程的影响的关键变量。对于高频数据集，该模型能够再现 DOC 流量浓度并捕捉 DOC 浓度和排放之间的复杂滞后关系。相反，每周数据的频率不足以正确描述该流域中的 DOC 动态。因此，溪流中包含的水的年龄分布证明是预测从土壤中输出的 DOC 的数量和反应性以及水文变化对这一过程的影响的关键变量。对于高频数据集，该模型能够再现 DOC 流量浓度并捕捉 DOC 浓度和排放之间的复杂滞后关系。相反，每周数据的频率不足以正确描述该流域中的 DOC 动态。因此，溪流中包含的水的年龄分布证明是预测从土壤中输出的 DOC 的数量和反应性以及水文变化对这一过程的影响的关键变量。