scholarly journals Comments on “Estimating groundwater recharge from groundwater levels using non-linear transfer function noise models and comparison to lysimeter data”

2020 ◽  
Author(s):  
Rodrigo Manzione
Keyword(s):  
Transfer Function ◽  
Groundwater Recharge ◽  
Groundwater Levels ◽  
Linear Transfer Function ◽  
Non Linear ◽  
Noise Models

scholarly journals Estimating groundwater recharge from groundwater levels using non-linear transfer function noise models and comparison to lysimeter data

2020 ◽  
Author(s):  
Raoul Collenteur ◽  
Mark Bakker ◽  
Gernot Klammler ◽  
Steffen Birk
Keyword(s):  
Transfer Function ◽  
Groundwater Recharge ◽  
Linear Model ◽  
Zone Model ◽  
Research Station ◽  
Parameter Uncertainties ◽  
Groundwater Levels ◽  
Linear Transfer Function ◽  
Non Linear ◽  
Recharge Rates

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.

scholarly journals Estimation of groundwater recharge from groundwater levels using nonlinear transfer function noise models and comparison to lysimeter data

2021 ◽  
Vol 25 (5) ◽  
pp. 2931-2949
Author(s):  
Raoul A. Collenteur ◽  
Mark Bakker ◽  
Gernot Klammler ◽  
Steffen Birk
Keyword(s):  
Transfer Function ◽  
Groundwater Recharge ◽  
Nonlinear Model ◽  
Noise Model ◽  
Zone Model ◽  
Research Station ◽  
Parameter Uncertainties ◽  
Groundwater Levels ◽  
Nonlinear Transfer ◽  
Recharge Rates

Abstract. The estimation of groundwater recharge is of paramount importance to assess the sustainability of groundwater use in aquifers around the world. Estimation of the recharge flux, however, remains notoriously difficult. In this study the application of nonlinear transfer function noise (TFN) models using impulse response functions is explored to simulate groundwater levels and estimate groundwater recharge. A nonlinear 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 nonlinear model improves the simulation of groundwater levels compared to the linear model. The annual recharge rates estimated with the nonlinear model are comparable to the average seepage rates observed with two lysimeters. The recharges estimates from the nonlinear model are also in reasonably good agreement with the lysimeter data at the smaller timescale of recharge per 10 d. This is an improvement over 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.

Estimation of groundwater recharge from time series modeling of groundwater levels in non-linear systems

2020 ◽  
Author(s):  
Raoul Collenteur ◽  
Steffen Birk ◽  
Gernot Klammler ◽  
Mark Bakker
Keyword(s):  
Time Series ◽  
Groundwater Recharge ◽  
Linear Systems ◽  
Impulse Response ◽  
Impulse Response Functions ◽  
Time Series Modeling ◽  
Response Functions ◽  
Groundwater Levels ◽  
Non Linear ◽  
Non Linear Systems

<p>Groundwater recharge remains a notoriously difficult flux to estimate, despite ongoing scientific efforts. In recent years, time series modeling using impulse response functions has gained popularity to simulate groundwater levels and is quickly becoming a common tool for hydrogeologists. Several approaches have been developed to estimate recharge from time series models for both linear and non-linear systems (e.g., [1], [2], and [3]). In this study, we introduce a novel approach to estimate groundwater recharge from observed groundwater levels in nonlinear systems (i.e., twice the precipitation does not necessarily lead to twice the recharge). We extend a time series model using impulse response functions with a non-linear unsaturated zone module that simulates recharge. The model parameters are estimated by fitting the simulated to the observed groundwater levels, with the groundwater recharge as an intermediate model result. </p><p>The method is tested on a time series of groundwater levels observed in Southeastern Austria (Wagna), where lysimeter data of seepage to the groundwater is available for model validation. The simulated groundwater recharge suggests an event-based recharge behavior, with most recharge occurring shortly after larger precipitation events. This finding agrees with the behavior observed in the lysimeter data. The estimated recharge fluxes show a high correlation with the observed seepage on time scales from years to months or weeks, while daily recharge rates show larger errors. Advantages of the method include limited data requirements (only precipitation, potential evapotranspiration, and groundwater time series are required) and the possibility to correct for other factors causing groundwater level fluctuations (e.g., pumping, river levels). This makes it possible to apply the method in locations where little system knowledge (e.g., soil profiles) is available.</p><p><strong>References:</strong><br>[1] Besbes, M. and De Marsily, G. (1984) From infiltration to recharge: use of a parametric transfer function, Journal of Hydrology.<br>[2] Peterson, T.J. and Fulton, S. (2019) Joint estimation of gross recharge, groundwater usage, and hydraulic properties within HydroSight, Groundwater.<br>[3] Obergfell, C., Bakker, M. and Maas, K. (2019) Estimation of average diffuse aquifer recharge using time series modeling of groundwater heads, Groundwater.</p>

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