Knowledge about water flow paths is essential for understanding biogeochemical fluxes in developed agricultural landscapes, i.e., the input of nutrients into surface waters, soil erosion, or pesticide fate. Several methods are available to study rainfall-runoff processes and flux partitioning: hydrometric based approaches, chemical tracers, modeling, and stable isotope applications. In this study a multi-method approach was conducted to gain insights into the hydrological fluxes and process understanding within the complex anthropogenic-influenced catchment of the Vollnkirchener Bach, Germany. Our results indicate that the catchment responds differently to precipitation input signals and dominant runoff-generation processes change throughout the year. Rainfall-induced runoff events during dry periods are characterized by a temporarily active combined sewer overflow. During stormflow, a large contribution of fast event water is observed. At low flow conditions losing and gaining conditions occur in parallel. However, when catchment's moisture conditions are high, an ephemeral source from clay shale-graywacke dominated forested sites becomes active. The study reveals that the collection of detailed distributed hydrometric data combined with isotopic tracers, provides fundamental information on the complex catchment behavior, which can finally be utilized for conceptualizing water fluxes at a small catchment scale. OPEN ACCESSWater 2014, 6 3086

Groundwater discharge to streams can be distributed variably in space due to the heterogeneous composition of the subsurface. Fiber-optic distributed temperature sensing (DTS) has been applied to detect and quantify spatially concentrated groundwater discharge to streams. However, a systematic uncertainty assessment for this approach with respect to changing boundary conditions is missing, and limits of detection are unclear. In this study, artificial point sources with controlled inflow rates to a natural first-order stream were used to quantitatively test the approach for inflow rates in the range of <1% to approximately 19% of upstream discharge and varying temperature differences between stream water and inflowing water. Even small inflow fractions down to approximately 2% of upstream discharge could be detected with the DTS. Inflow fractions calculated from DTS-based stream temperature observations and independently measured inflow temperatures were comparable to measured inflow fractions. Average uncertainty estimation based on the error propagation calculations ranged between 9% and 22% for experiments well above the detection limits of the DTS but ranged up to 147% for experiments close to the lower end of the detectable range.

[1] Groundwater discharge to streams can be distributed variably in space due to the heterogeneous composition of the subsurface. Fiber-optic distributed temperature sensing (DTS) has been applied to detect and quantify spatially concentrated groundwater discharge to streams. However, a systematic uncertainty assessment for this approach with respect to changing boundary conditions is missing, and limits of detection are unclear. In this study, artificial point sources with controlled inflow rates to a natural first-order stream were used to quantitatively test the approach for inflow rates in the range of <1% to approximately 19% of upstream discharge and varying temperature differences between stream water and inflowing water. Even small inflow fractions down to approximately 2% of upstream discharge could be detected with the DTS. Inflow fractions calculated from DTS-based stream temperature observations and independently measured inflow temperatures were comparable to measured inflow fractions. Average uncertainty estimation based on the error propagation calculations ranged between 9% and 22% for experiments well above the detection limits of the DTS but ranged up to 147% for experiments close to the lower end of the detectable range.Citation: Lauer, F., H.-G. Frede, and L. Breuer (2013), Uncertainty assessment of quantifying spatially concentrated groundwater discharge to small streams by distributed temperature sensing, Water Resour. Res., 49,