27 Aug 2020
27 Aug 2020
Estimating groundwater recharge from groundwater levels using non-linear transfer function noise models and comparison to lysimeter data
- 1Institute of Earth Sciences, NAWI Graz Geocenter, University of Graz, Heinrichstrasse 26, 8010 Graz, Austria
- 2Water Management Department, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628 CN, Delft, The Netherlands
- 3JR-AquaConSol GMHB, Graz, Austria
- 1Institute of Earth Sciences, NAWI Graz Geocenter, University of Graz, Heinrichstrasse 26, 8010 Graz, Austria
- 2Water Management Department, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628 CN, Delft, The Netherlands
- 3JR-AquaConSol GMHB, Graz, Austria
Abstract. The application of non-linear transfer function noise (TFN) models using impulse response functions is explored to estimate groundwater recharge and simulate groundwater levels. A non-linear root zone model that simulates recharge is developed and implemented in a TFN model, and is compared to a more commonly used linear recharge model. An additional novel aspect of this study is the use of an autoregressive-moving average noise model so that the remaining noise fulfills the statistical conditions to reliably estimate parameter uncertainties and compute the confidence intervals of the recharge estimates. The models are calibrated on groundwater level data observed at the Wagna hydrological research station in the southeastern part of Austria. The non-linear model improves the simulation of groundwater levels compared to the linear model. The annual recharge rates estimated with the non-linear model are comparable to the average seepage rates observed with two lysimeters. The recharges estimates from the non-linear model are also in reasonably good agreement with the lysimeter data at the smaller time scale of recharge per 10 days. This is an improvement over the results from previous studies that used comparable methods, but only reported annual recharge rates. The presented framework requires limited input data (precipitation, potential evaporation, and groundwater levels) and can easily be extended to support applications in different hydrogeological settings than those presented here.
Raoul Collenteur et al.
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RC1: 'Referee's remarks', Rafael Schäffer, 12 Oct 2020
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AC1: 'Initial response to review 1', Raoul Collenteur, 28 Oct 2020
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AC1: 'Initial response to review 1', Raoul Collenteur, 28 Oct 2020
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RC2: 'Comments on “Estimating groundwater recharge from groundwater levels using non-linear transfer function noise models and comparison to lysimeter data”', Rodrigo Manzione, 04 Dec 2020
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AC2: 'Initial response to review 2', Raoul Collenteur, 05 Jan 2021
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AC2: 'Initial response to review 2', Raoul Collenteur, 05 Jan 2021
Raoul Collenteur et al.
Model code and software
Pastas v0.15 Raoul Collenteur, Mark Bakker, Ruben Caljé, and Frans Schaars https://doi.org/10.5281/zenodo.3968497
Raoul Collenteur et al.
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