In-situ dissolved organic matter (DOM) monitoring frequencies have often been chosen for convenience or based on perceived wisdom, without fully assessing their impact on representation of DOM dynamics. To address this gap, we collected 5-min fluorescence data in an urban headwater and resampled it at coarser intervals to investigate the impact of monitoring frequencies on the detectability of DOM dynamics during storms. Expecting hydrometeorological conditions to modify the impact of monitoring frequency, we categorized 85 storm events into groups: Group A (low intensity, short duration), Group B (high intensity, short duration), and Group C (low intensity, long duration). Surprisingly, our analysis indicated that monitoring frequency has minimal influence on commonly used biogeochemical indexes (e.g., maximum, hysteresis and flushing index), which are employed to characterize solute behavior, regardless of storm type. To facilitate a direct comparison between monitoring frequencies, we back-interpolated coarser data into 5-min intervals and calculated mean squared errors by comparing them with original high-resolution data. Our findings indicated that in colder periods with predominately Type A and C storms, a coarser monitoring frequency (>30 min) can capture DOM dynamics. Conversely, in warmer periods when Type B storms dominate, a finer frequency (≤15 min) is necessary to capture key solute chemograph processes (e.g., first flush and dilution). Generally, we suggest a 15-min monitoring frequency as optimal for similar urban headwater systems, and advocate an adaptive approach based on seasonal variations to improve efficiency, especially when power, data transfer, and storage are constraints.

中文翻译：

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监测频率对城市河流中溶解有机物动态表示的重要性


原位溶解有机物 （DOM） 监测频率通常是为了方便或基于感知的智慧而选择的，而没有充分评估它们对 DOM 动力学表示的影响。为了解决这一差距，我们在城市源头收集了 5 分钟的荧光数据，并以较粗的间隔对其进行重新采样，以研究监测频率对风暴期间 DOM 动态可检测性的影响。预计水文气象条件会改变监测频率的影响，我们将 85 个风暴事件分为以下几组：A 组（低强度、短持续时间）、B 组（高强度、短持续时间）和 C 组（低强度、长持续时间）。令人惊讶的是，我们的分析表明，监测频率对常用的生物地球化学指标（例如最大值、滞后和冲洗指数）的影响很小，这些指标用于表征溶质行为，无论风暴类型如何。为了便于监测频率之间的直接比较，我们将较粗的数据反向插值为 5 分钟的间隔，并通过将它们与原始高分辨率数据进行比较来计算均方误差。我们的研究结果表明，在以 A 型和 C 型风暴为主的较冷时期，较粗的监测频率 （>30 min） 可以捕获 DOM 动态。相反，在 B 型风暴占主导地位的较温暖时期，需要更精细的频率 （≤15 min） 来捕获关键的溶质化学图过程 （例如，第一次冲洗和稀释）。一般来说，我们建议 15 分钟的监测频率是类似的城市源头系统的最佳选择，并倡导基于季节性变化的自适应方法以提高效率，尤其是在电力、数据传输和存储受到限制的情况下。