Preprints
https://doi.org/10.5194/hess-2022-291
https://doi.org/10.5194/hess-2022-291
 
31 Aug 2022
31 Aug 2022
Status: this preprint is currently under review for the journal HESS.

Estimating karst groundwater recharge from soil moisture observations – A new method tested at the Swabian Alb, Southwest Germany

Romane Berthelin1, Tunde Olarinoye1, Michael Rinderer1, Matías Mudarra2, Dominic Demand3, Mirjam Scheller1, and Andreas Hartmann4,1 Romane Berthelin et al.
  • 1Chair of Hydrological Modeling and Water Resources, Freiburg University, Freiburg, 79098, Germany
  • 2Department of Geology and Center of Hydrogeology of the University of Málaga, Faculty of Science, E-29071, Málaga, Spain
  • 3Chair of Hydrology, Freiburg University, Freiburg, 79098, Germany
  • 4Institute of Groundwater Management, Technical University of Dresden, 01069 Dresden, Germany

Abstract. Understanding groundwater recharge processes is important for sustainable water resource management. Experimental approaches to study recharge in karst areas often focus on analysing the aquifer response using a disintegration of its outlet signals, but only a few directly investigate the recharge processes that occur at the surface of the system. Soil moisture measurements have a high potential to investigate water infiltration to deeper soil depth or epikarst with an easy and not too intrusive installation. They can yield long-term measurements with high temporal resolution. Using these advantages, we developed and tested a method to estimate recharge based on soil moisture measurements. The method consists of the extraction of linked events in rainfall-, soil moisture and discharge time series and a subsequent fitting of the parameters of a simple drainage model to calculate karst recharge from soil moisture metrics of individual events. The fitted parameters could be interpreted in physically meaningful terms and were related to the properties of the karstic system. The model was tested and validated in a karst catchment located in Southwest Germany with hourly precipitation, soil moisture, and discharge data of eight years duration. The soil moisture measurements were distributed among grassland (n = 8) and woodland areas (n = 7) at 20 cm depth. A threshold of about 35 % (±8 %) of volumetric water content was necessary to initiate effective infiltration. Soil moisture averaged during the wetting period of each event was the best metric for the prediction of recharge. The model performed reasonably well estimating recharge during single rainfall events. It was also capable to simulate 88 % of the average annual recharge volume despite considerable differences in the performance between years. The event-based approach is potentially applicable to other karstic systems where soil moisture and precipitation measurements are available to predict karst groundwater recharge.

Romane Berthelin et al.

Status: open (until 26 Oct 2022)

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  • RC1: 'Comment on hess-2022-291', Michael Stewart, 12 Sep 2022 reply

Romane Berthelin et al.

Romane Berthelin et al.

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Short summary
Karstic recharge processes have mainly been explored using discharge analysis despite the high influence of the heterogeneous surface on hydrological processes. In this paper, we introduce an event-based method, which allows for recharge estimation from soil moisture measurements. The method was tested at a karst catchment in Germany but can be applied to other karst areas with precipitation and soil moisture data available. It will allow a better characterization of karst recharge processes.