Excess export of nitrate to streams has been an environmental issue attracting attention across the world. Lumped models based on StorAge Selection (SAS) functions have been used widely to investigate this export processes in terms of hydrological and chemical responses in catchment outflux – both in discharge (Q) and in evapotranspiration (ET). The validity of these models depends on the appropriate choice of water age selection preferences, i.e. the parameterization of the SAS functions of Q and ET, which are often calibrated against observed in-stream tracer data. This study attempted to assess the usefulness of in-stream nitrate (N-NO₃) concentrations for resolving the SAS functions in terms of plausibility (being physically meaningful) and parameter uncertainty, in a small agricultural catchment in central Germany that experiences strong seasonality. A spatially implicit model was built to simulate the dynamics of nitrate export. The data sets of in-stream nitrate concentrations, nitrogen surplus in the soil, and the median age of Q were used to constrain the model. The best-fit (to all data sets) results indicate high plausibility of the calibrated, temporally dynamic age selection preferences for Q for most time of a year, however, not for ET. The uncertainty analysis using a Monte Carlo approach suggests that lower uncertainty is associated with the SAS functions for Q than that for ET. The uncertainties of the SAS functions can be reduced by 60% combining the three datasets instead of using only in-stream concentration data. This study demonstrated the usefulness of combined data sets for adequately determining dynamic age selection preferences for Q, but not for ET. Better constraining selection preferences will require better in-stream concentration data for the dry period and additional data sets for ET (e.g. age of ET).

向河流中过量出口硝酸盐一直是一个引起全世界关注的环境问题。基于存储选择 (SAS) 函数的集总模型已被广泛用于从流域流出中的水文和化学响应方面研究这种输出过程 - 无论是在排放 (Q) 还是在蒸发蒸腾 (ET) 中。The validity of these models depends on the appropriate choice of water age selection preferences, ie the parameterization of the SAS functions of Q and ET, which are often calibrated against observed in-stream tracer data. 本研究试图评估河内硝酸盐 (N-NO ₃) 在德国中部一个季节性很强的小型农业集水区中，在合理性（具有物理意义）和参数不确定性方面解决 SAS 函数的浓度。建立了一个空间隐式模型来模拟硝酸盐输出的动态。河流中硝酸盐浓度、土壤中氮过剩和 Q 的中值年龄的数据集用于约束模型。最佳拟合（对所有数据集）结果表明 Q 的校准的、时间动态的年龄选择偏好在一年中的大部分时间具有很高的可信度，但不适用于 ET。使用蒙特卡罗方法的不确定性分析表明，与 ET 的 SAS 函数相比，Q 的 SAS 函数具有较低的不确定性。结合三个数据集而不是仅使用流内浓度数据，SAS 函数的不确定性可以减少 60%。这项研究证明了组合数据集对于充分确定 Q 的动态年龄选择偏好的有用性，但不适用于 ET。更好的约束选择偏好将需要更好的干旱期河内浓度数据和额外的 ET 数据集（例如 ET 年龄）。