The Water Residence Time distribution is the equivalent of the impulse response of a linear system allowing the propagation of water through a medium, e.g. the propagation of rain water from the top of the mountain towards the aquifers. We consider the output aquifer levels as the convolution between the input rain levels and the Water Residence Time, starting with an initial aquifer base level. The estimation of Water Residence Time is important for a better understanding of hydro-bio-geochemical processes and mixing properties of wetlands used as filters in ecological applications, as well as protecting fresh water sources for wells from pollutants. Common methods of estimating the Water Residence Time focus on cross-correlation, parameter fitting and non-parametric deconvolution methods. Here we propose a 1D full-deconvolution, regularized, non-parametric inverse problem algorithm that enforces smoothness and uses constraints of causality and positivity to estimate the Water Residence Time curve. Compared to Bayesian non-parametric deconvolution approaches, it has a fast runtime per test case; compared to the popular and fast cross-correlation method, it produces a more precise Water Residence Time curve even in the case of noisy measurements. The algorithm needs only one regularization parameter to balance between smoothness of the Water Residence Time and accuracy of the reconstruction. We propose an approach on how to automatically find a suitable value of the regularization parameter from the input data only. Tests on real data illustrate the potential of this method to analyze hydrological datasets.
Water temperature can be used as a tracer for the interaction between river water and groundwater, interpreting time shifts in temperature signals as retarded travel times. The water temperature fluctuates on different time scales, the most pronounced of which are the seasonal and diurnal ones. While seasonal fluctuations can be found in any type of shallow groundwater, high-frequency components are more typical for freshly infiltrated river water, or hyporheic groundwater, and are thus better suited for evaluating the travel time of the youngest groundwater component in alluvial aquifer systems. We present temperature time series collected at two sites in the alpine floodplain aquifers of the Brenno river in Southern Switzerland. At the first site, we determine apparent travel times of temperature for both the seasonal and high-frequency components of the temperature signals in several wells. The seasonal signal appears to travel more slowly, indicating a mixture of older and younger groundwater components, which is confirmed by sulphate measurements. The travel times of the high-frequency component qualitatively agree with the groundwater age derived from radon concentrations, which exclusively reflects young water components. Directly after minor floods, the amplitude of temperature fluctuations in an observation well nearby the river is the highest. Within a week, the riverbed is being clogged, leading to stronger attenuation of the temperature fluctuations in the observation well. At the second site, very fast infiltration to depths of 1.9 m under the riverbed could be inferred from the time shift of the diurnal temperature signal. A key parameter used in the assessment of bank filtration is the travel time of the infiltrated river water during the passage through groundwater. We analyze time series of electrical conductivity (EC) in the river and adjacent groundwater observation wells to investigate travel times of young hyporheic groundwater in adjoining channelized and restored sections of River Thur in North-East Switzerland. To quantify mixing ratios and mean residence times we perform cross-correlation analysis and non-parametric deconvolution of the EC time series. Measurements of radon-222 in the groundwater samples validate the calculated residence times. A simple relationship between travel time and distance to the river has not been observed. Therefore, we speculate that the lateral position and depth of the thalweg as well as the type of bank stabilization might control the infiltration processes in losing rivers. Diurnal oscillations of EC observed in the river and in nearby observation wells facilitate analyzing the temporal variation of infiltration. The diurnal oscillations are particularly pronounced in low flow situations, while the overall EC signal is dominated by individual high-flow events. Differences in travel times derived from diurnal and overall EC signals thus reflect different infiltration regimes. Summary We study the temporal variability of water transfer through the infiltration zone of a karst aquifer by estimating the impulse response of the system using cross-correlogram analyses between rainfall and piezometric level time series. We apply a sliding-window cross-correlation method, which calculates cross-correlograms on partially superposed short time series windows. We apply this method for rainfall and piezometric level time series at six boreholes in a fractured karstic aquifer located in Burgundy, France. Based on cross-correlogram functions, we obtain a time series of response time. At most of the boreholes, the cross-correlation functions change over time, and the response times vary seasonally, being shorter during the summer. This unusual structure can be partly explained by the seasonal variability in rainfall intensity, which is higher during the summer (May–September), inducing the seasonal behaviour of the epikarst. During the summer, when rainfall intensity is higher, the epikarst is more easily and quickly saturated. This induces an increase in lateral water transfer within the epikarst and an increase in concentrated fast flows. We also show that the response time seems to tend towards a limit which represents the maximum saturation of the epikarst. Wells placed next to surface-water bodies to induce infiltration have come under scrutiny because of the presence of the potential pathogens in surface water. Removal of pathogens and other contaminants by bank filtration is assumed, but regulatory agencies question the effectiveness of this process. To investigate transport processes of biological constituents, advective groundwater traveltimes to production wells under the influence of surface water need to be established first to determine appropriate water-quality sampling schedules. This paper presents the results of a study of bank filtration at a well field in southwestern Ohio. Field parameters such as water level, specific conductance, and water temperature were measured at least hourly at a streamflow gaging station and at five monitoring wells each at two separate sites, corresponding to two nearby production wells. Water-quality samples also were collected in all wells and the streamflow gaging station. Specific conductance is directly related to concentration of chloride, a chemically conservative constituent. Cross-correlation methods were used to determine the average traveltime from the river to the monitoring wells. Traveltimes based on specific conductance ranged from approximately 20 h to 10 days at one site and 5 days to 3 months at the other site. Calculated groundwater flow velocities ranged from 2.1 £ 10 23 to 6.0 £ 10 23 cm s and 3.5 £ 10 24 to 7.1 £ 10 24 cm s at the two sites. Data collected when a production well is continuously pumping reveal shorter and more consistent traveltimes than when the same well is pumped intermittently. q 2002 Elsevier Science B.V. All rights reserved.