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  • 1
    Language: English
    In: Physical review letters, 06 November 2015, Vol.115(19), pp.194502
    Description: Helical flow leads to deformation of solute plumes and enhances transverse mixing in porous media. We present experiments in which macroscopic helical flow is created by arranging different materials to obtain an anisotropic macroscopic permeability tensor with spatially variable orientation. The resulting helical flow entails twisting streamlines which cause a significant increase in lateral mass exchange and thus a large enhancement of plume dilution (up to 235%) compared to transport in homogenous media. The setup may be used to effectively mix solutes in parallel streams similarly to static mixers, but in porous media.
    Keywords: Twisting ; Media ; Exchange ; Helical Flow ; Transport ; Plumes ; Porous Media ; Mathematical Analysis ; Plasma Physics (General) (So) ; Physics (General) (Ah);
    ISSN: 00319007
    E-ISSN: 1079-7114
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  • 2
    Language: English
    In: Water Research, Oct 15, 2015, Vol.83, p.205(12)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.watres.2015.06.032 Byline: Julia L.A. Knapp, Karsten Osenbruck, Olaf A. Cirpka Abstract: Estimating respiration and photosynthesis rates in streams usually requires good knowledge of reaeration at the given locations. For this purpose, gas-tracer tests can be conducted, and reaeration rate coefficients are determined from the decrease in gas concentration along the river stretch. The typical procedure for analysis of such tests is based on simplifying assumptions, as it neglects dispersion altogether and does not consider possible fluctuations and trends in the input signal. We mathematically derive the influence of these non-idealities on estimated reaeration rates and how they are propagated onto the evaluation of aerobic respiration and photosynthesis rates from oxygen monitoring. We apply the approach to field data obtained from a gas-tracer test using propane in a second-order stream in Southwest Germany. We calculate the reaeration rate coefficients accounting for dispersion as well as trends and uncertainty in the input signals and compare them to the standard approach. We show that neglecting dispersion significantly underestimates reaeration, and results between sections cannot be compared if trends in the input signal of the gas tracer are disregarded. Using time series of dissolved oxygen and the various estimates of reaeration, we infer respiration and photosynthesis rates for the same stream section, demonstrating that the bias and uncertainty of reaeration using the different approaches significantly affects the calculation of metabolic rates. Author Affiliation: (a) University of Tubingen, Center for Applied Geoscience, Holderlinstr. 12, 72074 Tubingen, Germany (b) Water and Earth System Science (WESS) Competence Cluster, c/o University of Tubingen, Holderlinstr. 12, 72074 Tubingen, Germany Article History: Received 10 March 2015; Revised 13 June 2015; Accepted 19 June 2015
    Keywords: Photosynthesis – Analysis ; Natural Gas – Analysis ; Plant Biochemistry – Analysis ; Tracers (Biology) – Analysis
    ISSN: 0043-1354
    Source: Cengage Learning, Inc.
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  • 3
    Language: English
    In: Journal of Hydrology, Nov 15, 2013, Vol.505, p.352(12)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jhydrol.2013.10.015 Byline: Samuel Diem, Olaf A. Cirpka, Mario Schirmer Abstract: acents We present a new model to predict oxygen (DO) consumption upon riverbank filtration. acents The DO consumption rate is allowed to depend on river temperature and discharge. acents The temperature dependence was found to be more important on a seasonal time scale. acents Consumption rate increased by a factor of 4 within the narrow window of 20-50m.sup.3/s. acents The model successfully reproduced the observed dynamics in DO consumption. Article History: Received 22 June 2013; Revised 30 September 2013; Accepted 10 October 2013 Article Note: (miscellaneous) This manuscript was handled by Peter K. Kitanidis, Editor-in-Chief, with the assistance of Jian Luo, Associate Editor
    ISSN: 0022-1694
    Source: Cengage Learning, Inc.
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  • 4
    Language: English
    In: Journal of Hydrology, February 2017, Vol.545, pp.42-54
    Description: Groundwater resources management requires operational, regional-scale groundwater models accounting for dominant spatial variability of aquifer properties and spatiotemporal variability of groundwater recharge. We test the Ensemble Kalman filter (EnKF) to estimate transient hydraulic heads and groundwater recharge, as well as the hydraulic conductivity and specific-yield distributions of a virtual phreatic aquifer. To speed up computation time, we use a coarsened spatial grid in the filter simulations, and reconstruct head measurements at observation points by a local model in the vicinity of the piezometer as part of the observation operator. We show that the EnKF can adequately estimate both the mean and spatial patterns of hydraulic conductivity when assimilating daily values of hydraulic heads from a highly variable initial sample. The filter can also estimate temporally variable recharge to a satisfactory level, as long as the ensemble size is large enough. Constraining the parameters on concentrations of groundwater-age tracers (here: tritium) and transient hydraulic-head observations cannot reasonably be done by the EnKF because the concentrations depend on the recharge history over longer times while the head observations have much shorter temporal support. We thus use a different method, the Kalman Ensemble Generator (KEG), to precondition the initial ensemble of the EnKF on the groundwater-age tracer data and time-averaged hydraulic-head values. The preconditioned initial ensemble exhibits a smaller spread as well as improved means and spatial patterns. The preconditioning improves the EnKF particularly for smaller ensemble sizes, allowing operational data assimilation with reduced computational effort. In a validation scenario of delineating groundwater protection zones, the preconditioned filter performs clearly better than the filter using the original initial ensemble.
    Keywords: Data Assimilation of Hydraulic Heads ; Ensemble Kalman Filter ; Kalman Ensemble Generator ; Groundwater-Age Tracers ; Phreatic Aquifer ; Groundwater Recharge ; Hydraulic Conductivity ; Specific Yield ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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  • 5
    Language: English
    In: Journal of Hydrology, Nov 27, 2014, Vol.519, p.3386(14)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jhydrol.2014.09.084 Byline: Zijie Liao, Karsten Osenbruck, Olaf A. Cirpka Abstract: * River-to-groundwater travel time distributions change with time. * We determine these distributions from continuous signals of electric conductivity. * Our approach does not prescribe a functional shape of the distributions. * We detrend the data prior to deconvolution. * We enforce non-negativity and smoothness in time and travel-time. Article History: Received 9 May 2014; Revised 22 August 2014; Accepted 29 September 2014 Article Note: (miscellaneous) This manuscript was handled by Peter K. Kitanidis, Editor-in-Chief, with the assistance of Jian Luo, Associate Editor
    Keywords: Electrical Conductivity -- Analysis ; Groundwater -- Analysis ; Rivers -- Analysis
    ISSN: 0022-1694
    Source: Cengage Learning, Inc.
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  • 6
    Language: English
    In: Water Research, 15 October 2015, Vol.83, pp.205-216
    Description: Estimating respiration and photosynthesis rates in streams usually requires good knowledge of reaeration at the given locations. For this purpose, gas-tracer tests can be conducted, and reaeration rate coefficients are determined from the decrease in gas concentration along the river stretch. The typical procedure for analysis of such tests is based on simplifying assumptions, as it neglects dispersion altogether and does not consider possible fluctuations and trends in the input signal. We mathematically derive the influence of these non-idealities on estimated reaeration rates and how they are propagated onto the evaluation of aerobic respiration and photosynthesis rates from oxygen monitoring. We apply the approach to field data obtained from a gas-tracer test using propane in a second-order stream in Southwest Germany. We calculate the reaeration rate coefficients accounting for dispersion as well as trends and uncertainty in the input signals and compare them to the standard approach. We show that neglecting dispersion significantly underestimates reaeration, and results between sections cannot be compared if trends in the input signal of the gas tracer are disregarded. Using time series of dissolved oxygen and the various estimates of reaeration, we infer respiration and photosynthesis rates for the same stream section, demonstrating that the bias and uncertainty of reaeration using the different approaches significantly affects the calculation of metabolic rates.
    Keywords: Reaeration ; Gas-Tracer Tests ; Whole-Stream Metabolism ; Dispersion ; Oxygen Balance of Streams ; Engineering
    ISSN: 0043-1354
    E-ISSN: 1879-2448
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  • 7
    Language: English
    In: Journal of Hydrology, 27 November 2014, Vol.519, pp.3386-3399
    Description: The travel-time distribution between rivers and groundwater observation points and the mixing of freshly infiltrated river water with groundwater of other origin is of high relevance in riverbank filtration. These characteristics usually are inferred from the analysis of natural-tracer time series, typically relying on a stationary input–output relationship. However, non-stationarity is a significant feature of the riparian zone causing time-varying river-to-groundwater transfer functions. We present a non-stationary extension of nonparametric deconvolution by performing stationary deconvolution with windowed time series, enforcing smoothness of the determined transfer function in time and travel time. The nonparametric approach facilitates the identification of unconventional features in travel-time distributions, such as broad peaks, and the sliding-window approach is an easy way to accommodate the method to dynamic changes of the system under consideration. By this, we obtain time-varying signal-recovery rates and travel-time distributions, from which we derive the mean travel time and the spread of the distribution as function of time. We apply our method to electric-conductivity data collected at River Thur, Switzerland, and adjacent piezometers. The non-stationary approach reproduces the groundwater observations significantly better than the stationary one, both in terms of overall metrics and in matching individual peaks. We compare characteristics of the transient transfer function to base flow which indicates shorter travel times at higher river stages.
    Keywords: Travel-Time Distribution ; Bank Filtration ; Non-Stationarity ; Nonparametric Inference ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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  • 8
    Language: English
    In: Journal of Hydrology, 15 November 2013, Vol.505, pp.352-363
    Description: Dissolved oxygen (DO) is an important groundwater-quality parameter, especially within the context of drinking-water production by riverbank filtration. In riverbank sediments, a strong decrease of DO over the distance of a few meters has frequently been observed. The consumption rates may vary in time, which puts the representativeness of common, sporadic DO measurements in groundwater, based on monthly or even yearly sampling, into question. We present a new modeling approach that allows efficiently estimating DO concentrations in alluvial groundwater from measured DO concentrations in the river under various temperature and discharge conditions. The model is based on the stochastic–convective reactive approach and assumes a time-invariant lognormal travel-time distribution of the stream tube ensemble connecting the river and a groundwater observation well. DO consumption, resulting from aerobic respiration, is modeled by zero-order kinetics. According to high-resolution DO time series measured in the Thur River (NE-Switzerland) and an adjacent observation well, the DO consumption rate appears to depend on river temperature and discharge. While the temperature dependence of aerobic respiration is well known, the discharge dependence is probably related to an increased trapping of particulate organic matter (POM) within the riverbed during high-discharge events, thus enhancing the POM availability and DO consumption rate. We propose an empirical equation that quantifies the dependence between discharge and the DO consumption rate. The estimated parameterization at our field site suggests that an increasing discharge within the narrow window of 20–50 m /s enhances the DO consumption rate by a factor of 4. By considering the measured DO in the river and including the dependence of the DO consumption rate on both discharge and temperature, the model was able to capture the diurnal, short-term (days to weeks), and seasonal dynamics of the observed DO within the alluvial aquifer. The temperature dependence of the DO consumption rate was found to be more important on a seasonal time scale, while the effect of discharge dominated the DO behavior during hydrological events extending over a few days to weeks. The presented modeling approach can be transferred to other riverbank-filtration systems to efficiently estimate DO concentrations in alluvial aquifers under various climatic and hydrologic conditions and, hence, assess the risk of approaching anoxic conditions in a changing climate.
    Keywords: Riverbank Filtration ; Climate Change ; Oxygen Consumption ; Stochastic–Convective Reactive Transport ; POM ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
    Source: ScienceDirect Journals (Elsevier)
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  • 9
    Language: English
    In: Journal of Hydrology, 13 February 2014, Vol.509, pp.631-631
    Keywords: Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
    Source: ScienceDirect Journals (Elsevier)
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  • 10
    Language: English
    In: Journal of Hydrology, 2010, Vol.380(1), pp.154-164
    Description: Vertical temperature profiling in the river beds of losing streams has been shown to be useful in obtaining seepage rates. We present a method for high-resolution vertical temperature profiling in surface-water sediments for detailed quantification of seepage flux over depth and time. The method is based on fiber-optic distributed temperature sensing, in which temperature profiles along an optical fiber are obtained by making use of Raman scattering. An optical fiber was wrapped around a 2 in. PVC tube and installed vertically within the streambed sediment. The wrapping transfers the spatial resolution along the fiber of 1 m to a vertical resolution of about 5 mm. The high-resolution temperature profiler was tested at a losing reach of the Swiss prealpine River Thur resulting in a 20-day long temperature time series with a temporal resolution of 10 min. The time series are analyzed by means of dynamic harmonic regression to obtain the diurnal contributions of the measured time series at all depths and time points. The time for the diurnal temperature signal to reach the observation depth and the associated attenuation of the signal are calculated from the phase angles and amplitudes of the diurnal contributions. The time shift results in an apparent celerity of diurnal temperature propagation, which is converted into an apparent seepage rate by fitting the data to the analytical solution for convective–conductive heat transfer in a semi-infinite, uniform, one-dimensional domain with a sinusoidal surface temperature. The high spatial resolution allows the location of discontinuities in the river bed which would have remained undetected if temperature had been measured only at a few individual depths to be identified. This is a particular strength of the fiber-optic high-resolution temperature profiler. The time series also give evidence of sporadic high infiltration rates at times of high water tables.
    Keywords: River–Groundwater Interaction ; Fiber-Optic Distributed Temperature Sensing ; Time Series Analysis ; Seepage Flux ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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