Seasonal variations in groundwater upwelling zones in a Danish lowland stream analyzed using Distributed Temperature Sensing (DTS)

The distribution of groundwater inflows in a stream reach plays a major role in controlling the stream temperature, a vital component shaping the riverine ecosystem. In this study, the Distributed Temperature Sensing (DTS) system was installed in a small Danish lowland stream, Elverdamsåen, to assess the seasonal dynamics of groundwater inflow zones using high spatial (1 m) and temporal (3 minutes) resolution of water temperature measurements. Four simple criteria consisting of 30 min average temperature at 16:00, mean and standard deviation of diurnal temperatures, and the day–night temperature difference were applied to three DTS datasets representing stream temperature responses to the variable meteorological and hydrological conditions prevailing in summer, winter and spring. The standard deviation criterion was useful to identify groundwater discharge zones in summer and spring conditions, while the mean temperature criterion was better for the winter conditions. In total, 20 interactions were identified from the DTS datasets representing summer, 16 in winter and 19 in spring, albeit with only two interactions contributing in all three seasons. Higher baseflow to streamflow ratio, antecedent precipitation and presence of fractured clayey till in the stream reach were deemed as the vital factors causing apparent seasonal variation in the locations of upwelling zones, prompting use of DTS not only in preconceived scenarios of large diurnal temperature change but rather a long‐term deployment covering variable meteorological and hydrological scenarios.

Raw project data is available by contacting [e-mail]

河流段落中地下水入渗的分布对控制河流温度起着至关重要的作用，而河流温度是塑造河流生态系统的关键因素。在本研究中，分布式温度传感（DTS）系统被安装在丹麦一小型低地河流——埃尔维尔达姆森河中，以利用高空间分辨率（1米）和时间分辨率（3分钟）的水温测量数据，评估地下水入渗区域的季节动态变化。本研究采用了四个简单的标准，包括16:00时的30分钟平均温度、日间温度的均值和标准差，以及昼夜温差，对代表夏季、冬季和春季河流对多变气象和水文条件响应的三个DTS数据集进行分析。标准差标准在夏季和春季条件下有助于识别地下水排放区，而平均温度标准在冬季条件下更为适用。总共识别出20个来自DTS数据集的相互作用，代表夏季，16个代表冬季，19个代表春季，尽管只有两个相互作用在三个季节中都起到作用。较高的基流与河流量比率、前期降水以及河流段落中存在裂隙粘土层被认为是导致上升区域位置出现明显季节性变化的关键因素，这促使DTS不仅在预期的大日间温度变化场景中使用，而且在一个长期的部署中，覆盖了多变气象和水文场景。原始项目数据可通过联系 [e-mail] 获取。