Transit time distributions (TTDs) of streamflow are informative descriptors of catchment hydrological functioning and solute transport mechanisms. Conventional methods for estimating TTDs generally require model calibration against extensive tracer data time series, which are often limited to well-studied experimental catchments. We challenge this limitation and propose an alternative approach that uses the young water fraction (Fywobs), an increasingly used water age metric which represents the proportion of streamflow with a transit time younger than 2–3 months, and that can be robustly estimated with sparsely measured tracer data. To this end, we conducted a proof of concept study by modeling TTDs using StorAge Selection (SAS) functions with oxygen isotopes (δ18O) measurements for 23 diverse catchments in Germany. In a Monte-Carlo approach, we computed the (averaged) marginal TTDs of a prior parameter distribution and derived a model-based Fyw (Fywsim). We compared Fywsim with Fywobs, obtained from δ18O measurements, and constrained the prior SAS parameters distribution. Subsequently, we derived a posterior distribution of parameters and resulting model simulations. Our findings showed that using Fywobs to constrain the model effectively reduced parameter equifinality and simulation uncertainty. However, the value of Fywobs on reducing model uncertainty varied across sites, with larger values (Fywobs≥0.10) leading to simulations with a narrower uncertainty band and higher model efficiency, whilst smaller values (Fywobs≤0.05) had limited influence on reducing model output uncertainty. We discussed the potential and limitations of combining SAS functions with Fywobs, and considered broader implications of this approach for enhancing our understanding of catchment functioning and water quality status.

中文翻译：

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年轻水分数能否减少水中途时间估计中的预测不确定性？


径流的传输时间分布 （TTD） 是流域水文功能和溶质运输机制的信息描述符。估计 TTD 的常规方法通常需要根据广泛的示踪数据时间序列进行模型校准，这些时间序列通常仅限于经过充分研究的实验集水区。我们挑战了这一限制，并提出了一种使用年轻水分数 （Fywobs） 的替代方法，这是一种越来越多地使用的水龄指标，它表示穿越时间小于 2-3 个月的径流比例，并且可以使用稀疏测量的示踪数据进行稳健估计。为此，我们通过使用 StorAge Selection （SAS） 函数对德国 23 个不同集水区的氧同位素 （δ18O） 测量对 TTD 进行建模，进行了一项概念验证研究。在蒙特卡洛方法中，我们计算了先验参数分布的（平均）边际 TTD，并得出了基于模型的 Fyw （Fywsim）。我们将 Fywsim 与从 δ18O 测量中获得的 Fywabs 进行了比较，并限制了先前的 SAS 参数分布。随后，我们推导出了参数的后验分布和结果模型模拟。我们的研究结果表明，使用 Fywobs 来约束模型有效地降低了参数等定性和仿真不确定性。然而，Fywobs 在降低模型不确定性方面的价值因站点而异，较大的值 （Fywobs≥0.10） 导致模拟具有更窄的不确定性范围和更高的模型效率，而较小的值 （Fywobs≤0.05） 对降低模型输出不确定性的影响有限。 我们讨论了将 SAS 功能与 fywobs 相结合的潜力和局限性，并考虑了这种方法对增强我们对集水区功能和水质状况的理解的更广泛影响。