The delineation of groundwater discharge areas based on Distributed Temperature Sensing (DTS) data of the streambed can be difficult in soft‐bedded streams where sedimentation and scouring processes constantly change the position of the fibre optic cable relative to the streambed. Deposition‐induced temperature anomalies resemble the signal of groundwater discharge while scouring will cause the cable to float in the water column and measure stream water temperatures. DTS applied in a looped layout with nine fibre optic cable rows in a 70 × 5 m section of a soft‐bedded stream made it possible to detect variability in streambed temperatures between October 2011 and January 2012. Detailed monthly streambed elevation surveys were carried out to monitor the position of the fibre optic cable relative to the streambed and to quantify the effect of sedimentation processes on streambed temperatures. Based on the simultaneous interpretation of streambed temperature and elevation data, a method is proposed to delineate potential high‐groundwater discharge areas and identify deposition‐induced temperature anomalies in soft‐bedded streams. Potential high‐discharge sites were detected using as metrics the daily minimum, maximum and mean streambed temperatures as well as the daily amplitude and standard deviation of temperatures. The identified potential high‐discharge areas were mostly located near the channel banks, also showing temporal variability because of the scouring and redistribution of streambed sediments, leading to the relocation of pool‐riffle sequences. This study also shows that sediment deposits of 0.1 m thickness already resulted in an increase in daily minimum streambed temperatures and decrease in daily amplitude and standard deviation. Scouring sites showed lower daily minimum streambed temperatures and higher daily amplitude and standard deviation compared with areas without sedimentation and scouring. As a limitation of the approach, groundwater discharge occurring at depositional and scouring areas cannot be identified by the metrics applied.

Raw project data is available by contacting ctemps@unr.edu