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“LPMLE3: A novel 1-D approach to study water flow in streambeds using heat as a tracer”. Schneidewind U, van Berkel M, Anibas C, Vandersteen G, Schmidt C, Joris I, Seuntjens P, Batelaan O, Zwart HJ, Water resources research 52, 6596 (2016). http://doi.org/10.1002/2015WR017453
Abstract: We introduce LPMLE3, a new 1-D approach to quantify vertical water flow components at streambeds using temperature data collected in different depths. LPMLE3 solves the partial differential equation for coupled water flow and heat transport in the frequency domain. Unlike other 1-D approaches it does not assume a semi-infinite halfspace with the location of the lower boundary condition approaching infinity. Instead, it uses local upper and lower boundary conditions. As such, the streambed can be divided into finite subdomains bound at the top and bottom by a temperature-time series. Information from a third temperature sensor within each subdomain is then used for parameter estimation. LPMLE3 applies a low order local polynomial to separate periodic and transient parts (including the noise contributions) of a temperature-time series and calculates the frequency response of each subdomain to a known temperature input at the streambed top. A maximum-likelihood estimator is used to estimate the vertical component of water flow, thermal diffusivity, and their uncertainties for each streambed subdomain and provides information regarding model quality. We tested the method on synthetic temperature data generated with the numerical model STRIVE and demonstrate how the vertical flow component can be quantified for field data collected in a Belgian stream. We show that by using the results in additional analyses, nonvertical flow components could be identified and by making certain assumptions they could be quantified for each subdomain. LPMLE3 performed well on both simulated and field data and can be considered a valuable addition to the existing 1-D methods.
Keywords: A1 Journal article; Sustainable Energy, Air and Water Technology (DuEL)
DOI: 10.1002/2015WR017453
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“From streambed temperature measurements to spatial-temporal flux quantification : using the LPML method to study groundwater-surface water interaction”. Anibas C, Schneidewind U, Vandersteen G, Joris I, Seuntjens P, Batelaan O, Hydrological processes 30, 203 (2016). http://doi.org/10.1002/HYP.10588
Abstract: Knowledge on groundwater-surface water interaction and especially on exchange fluxes between streams and aquifers is an important prerequisite for the study of transport and fate of contaminants and nutrients in the hyporheic zone. One possibility to quantify groundwater-surface water exchange fluxes is by using heat as an environmlental tracer. Modern field equipment including multilevel temperature sticks and the novel open-source analysis tool LPML make this technique ever more attractive. The recently developed LPML method solves the one-dimensional fluid flow and heat transport equation by combining a local polynomial method with a maximum likelihood estimator. In this study, we apply the LPML method on field data to quantify the spatial and temporal variability of vertical fluxes and their uncertainties from temperature-time series measured in a Belgian lowland stream. Over several months, temperature data were collected with multilevel temperature sticks at the streambed top and at six depths for a small stream section. Long-term estimates show a range from gaining fluxes of -291 mm day(-1) to loosing fluxes of 12 mm day(-1); average seasonal fluxes ranged from -138 mm day(-1) in winter to -16 mm day(-1) in summer. With our analyses, we could determine a high spatial and temporal variability of vertical exchange fluxes for the investigated stream section. Such spatial and temporal variability should be taken into account in biogeochemical cycling of carbon, nutrients and metals and in fate analysis of contaminant plumes. In general, the stream section was gaining during most of the observation period. Two short-term high stream stage events, seemingly caused by blockage of the stream outlet, led to a change in flow direction from gaining to losing conditions. We also found more discharge occurring at the outer stream bank than at the inner one indicating a local flow-through system. With the conducted analyses, we were able to advance our understanding of the regional groundwater flow system. Copyright (C) 2015 John Wiley & Sons, Ltd.
Keywords: A1 Journal article; Sustainable Energy, Air and Water Technology (DuEL)
DOI: 10.1002/HYP.10588
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“Determining groundwater-surface water exchange from temperature-time series : combining a local polynomial method with a maximum likelihood estimator”. Vandersteen G, Schneidewind U, Anibas C, Schmidt C, Seuntjens P, Batelaan O, Water resources research 51, 922 (2015). http://doi.org/10.1002/2014WR015994
Abstract: The use of temperature-time series measured in streambed sediments as input to coupled water flow and heat transport models has become standard when quantifying vertical groundwater-surface water exchange fluxes. We develop a novel methodology, called LPML, to estimate the parameters for 1-D water flow and heat transport by combining a local polynomial (LP) signal processing technique with a maximum likelihood (ML) estimator. The LP method is used to estimate the frequency response functions (FRFs) and their uncertainties between the streambed top and several locations within the streambed from measured temperature-time series data. Additionally, we obtain the analytical expression of the FRFs assuming a pure sinusoidal input. The estimated and analytical FRFs are used in an ML estimator to deduce vertical groundwater-surface water exchange flux and its uncertainty as well as information regarding model quality. The LPML method is tested and verified with the heat transport models STRIVE and VFLUX. We demonstrate that the LPML method can correctly reproduce a priori known fluxes and thermal conductivities and also show that the LPML method can estimate averaged and time-variable fluxes from periodic and nonperiodic temperature records. The LPML method allows for a fast computation of exchange fluxes as well as model and parameter uncertainties from many temperature sensors. Moreover, it can utilize a broad frequency spectrum beyond the diel signal commonly used for flux calculations.
Keywords: A1 Journal article; Sustainable Energy, Air and Water Technology (DuEL)
DOI: 10.1002/2014WR015994
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