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Characterization of Diffuse Groundwater Inflows into Streamwater (Part I: Spatial and Temporal Mapping Framework Based on Fiber Optic Distributed Temperature Sensing)

Abstract : Although fiber optic distributed temperature sensing (FO-DTS) has been used in hydrology for the past 10 years to characterize groundwater-streamwater exchanges, it has not been widely applied since the entire annual hydrological cycle has rarely been considered. Properly distinguishing between diffuse and intermittent groundwater inflows requires longer periods (e.g., a few months, 1 year) since punctual changes can be lost over shorter periods. In this study, we collected a large amount of data over a one-year period using a 614 m long cable placed in a stream. We used a framework based on a set of hypotheses approach using thermal contrast between stream temperature and the atmosphere. For each subreach, thermal contrast was normalized using reference points assumed to lie outside of groundwater influence. The concepts and relations developed in this study provide a useful and simple methodology to analyze a large database of stream temperature at high spatial and temporal resolution over a one-year period using FO-DTS. Thus, the study highlighted the importance of streambed topography, since riffles and perched reaches had many fewer inflows than pools. Additionally, the spatial extent of groundwater inflows increased at some locations during high flow. The results were compared to the usual standard deviation of stream temperature calculated over an entire year. The two methods located the same inflows but differed in the mapping of their spatial extent. The temperatures obtained from FO-DTS open perspectives to understand spatial and temporal changes in interactions between groundwater and surface water.
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Hugo Le Lay, Zahra Thomas, Francois Rouault, Pascal Pichelin, Florentina Moatar. Characterization of Diffuse Groundwater Inflows into Streamwater (Part I: Spatial and Temporal Mapping Framework Based on Fiber Optic Distributed Temperature Sensing). Water, MDPI, 2019, 11 (11), pp.2389. ⟨10.3390/w11112389⟩. ⟨hal-02372030⟩

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