Heat has been widely applied to trace groundwater‐surface water exchanges in inland environments, but it is infrequently applied in coastal sediment where head oscillations induce periodicity in water flux magnitude/direction and heat advection. This complicates interpretation of temperatures to estimate water fluxes. We investigate the convolution of thermal and hydraulic signals to assess the viability of using heat as a tracer in environments with tidal head oscillations superimposed on submarine groundwater discharge. We first generate sediment temperature and head time series for conditions ranging from no tide to mega‐tidal using a numerical model (SUTRA) forced with periodic temperature and tidal head signals. We then analyze these synthetic temperature time series using heat tracing software (VFLUX2 and 1DTempPro) to evaluate if conventional terrestrial approaches to infer fluxes from temperatures are applicable for coastal settings. We consider high‐frequency water flux variability within a tidal signal and averaged over tidal signals. Results show that VFLUX2 analytical methods reasonably estimated the mean discharge fluxes in most cases but could not reproduce the flux variability within tidal cycles. The model results further reveal that high‐frequency time series of water fluxes varying in magnitude and direction can be accurately estimated if paired temperatures and hydraulic heads are analyzed using numerical models (e.g., 1DTempPro) that consider both dynamic hydraulic gradients and thermal signals. These results point to the opportunity to incorporate pressure sensors within heat tracing instrumentation to better assess sub‐daily flux oscillations and associated reactive processes.

中文翻译：

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利用热量追踪沉积物中同时发生潮汐抽水和地下水排放的垂直水通量

热量已广泛应用于内陆环境中的痕量地下水与地表水交换，但很少用于沿海沉积物中，在这种沉积物中，水头振荡会引起水通量/方向和热对流的周期性。这使对温度的解释变得复杂，以估计水通量。我们调查热和水力信号的卷积，以评估在潮汐水头振荡叠加在海底地下水排泄物上的环境中，使用热作为示踪剂的可行性。我们首先使用强制周期性温度和潮头信号的数值模型（SUTRA）生成从无潮到超潮的条件下的沉积物温度和水头时间序列。然后，我们使用伴热软件（VFLUX2和1DTempPro）分析这些合成温度时间序列，以评估从温度推断通量的常规地面方法是否适用于沿海环境。我们考虑了潮汐信号内的高频水通量变异性，并将其平均化为潮汐信号。结果表明，VFLUX2分析方法可在大多数情况下合理估算平均排放通量，但无法再现潮汐周期内通量的变化。该模型结果进一步表明，如果使用考虑了动态水力梯度和热信号的数值模型（例如1DTempPro）来分析成对的温度和水头，则可以准确估算出幅度和方向变化的水流量的高频时间序列。