Hydrograph separation assessment is crucial to understand stormflow generation at catchments worldwide. Tracer-based methods provide robust estimations of event (or new) and pre-event (or old) water fractions as they account for external and internal catchment hydrological behavior. While models of different mathematical and computational complexity are often used in tracer-based hydrograph separation studies, direct comparisons between those models are limited. Here, we compare hydrograph separation results yielded by the simplest Two-Component Mixing Model (TCMM) and a Tracer-based Streamflow Partitioning ANalysis model (TraSPAN) assumed to provide robust results as it combines conceptual rainfall-runoff modelling with tracers’ mass balance. We carried out the analysis using high temporal frequency (sub-daily to sub-hourly) data of two tracers, Oxygen-18 and Electrical Conductivity (EC), monitored during 37 rainfall-runoff events with different hydrometeorological conditions in a high-Andean páramo catchment located at the Zhurucay Ecohydrological Observatory in southern Ecuador. Both approaches yield similar estimations of event and pre-event water fractions regardless of the tracer used as long as appropriate concentrations of event (C) and pre-event (C) water for the TCMM are determined. Although the estimate of C has little influence with one rainfall sample collected during the event being sufficient to obtain reliable results, results hinge heavily on the estimate of C. We found that the TCMM yields similar results than TraSPAN when C is represented by the stream water concentration corresponding to a sample collected prior to the beginning of each of the events. We conclude that the combination of a simple framework (TCMM) with sub-hourly EC measurements provides reliable hydrograph separation results when representative C samples are used. These findings will allow to lower the logistical and economical resources needed to adequately assess hydrograph separation and to carry out quasi-continuous assessments of flow partitioning with high accuracy in high-Andean páramo catchments.

中文翻译：

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使用电导率的简单混合模型在热带山地流域中产生稳健的水文分离


水文过程线分离评估对于了解全球流域风暴流的产生至关重要。基于示踪剂的方法提供了对事件（或新）和事件前（或旧）水分数的可靠估计，因为它们考虑了外部和内部流域水文行为。虽然不同数学和计算复杂性的模型经常用于基于示踪剂的水文过程分离研究，但这些模型之间的直接比较是有限的。在这里，我们比较了最简单的二组分混合模型 (TCMM) 和基于示踪剂的水流分区分析模型 (TraSPAN) 产生的水文分离结果，假设该模型将概念性降雨径流模型与示踪剂的质量平衡相结合，可提供稳健的结果。我们使用两种示踪剂（Oxygen-18 和电导率 (EC)）的高时间频率（次日至次小时）数据进行了分析，这些数据是在安第斯山脉高原帕拉莫高原不同水文气象条件下的 37 次降雨径流事件中监测到的流域位于厄瓜多尔南部的朱鲁凯生态水文观测站。无论使用何种示踪剂，只要确定了 TCMM 的事件 (C) 和事件前 (C) 水的适当浓度，两种方法都会对事件和事件前水分数进行类似的估计。尽管 C 的估计影响不大，在事件期间收集的一次降雨样本足以获得可靠的结果，但结果在很大程度上取决于 C 的估计。我们发现，当 C 由溪流水表示时，TCMM 产生与 TraSPAN 相似的结果与每个事件开始之前收集的样本相对应的浓度。 我们得出的结论是，当使用代表性 C 样品时，简单框架 (TCMM) 与每小时一次 EC 测量相结合可提供可靠的过程过程线分离结果。这些发现将有助于降低充分评估水位线分离所需的后勤和经济资源，并在高安第斯帕拉莫流域进行高精度的准连续水流分配评估。