A large-scale simulation model to assess karstic groundwater recharge over Europe and the Mediterranean
- 1Department of Civil Engineering, University of Bristol, Bristol, UK
- 2Civil Engineering, McGill University, Montreal, Canada
- 3Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany
- 4Department of Physical Geography, Utrecht University, Utrecht, the Netherlands
Abstract. Karst develops through the dissolution of carbonate rock and is a major source of groundwater contributing up to half of the total drinking water supply in some European countries. Previous approaches to model future water availability in Europe are either too-small scale or do not incorporate karst processes, i.e. preferential flow paths. This study presents the first simulations of groundwater recharge in all karst regions in Europe with a parsimonious karst hydrology model. A novel parameter confinement strategy combines a priori information with recharge-related observations (actual evapotranspiration and soil moisture) at locations across Europe while explicitly identifying uncertainty in the model parameters. Europe's karst regions are divided into four typical karst landscapes (humid, mountain, Mediterranean and desert) by cluster analysis and recharge is simulated from 2002 to 2012 for each karst landscape. Mean annual recharge ranges from negligible in deserts to > 1 m a−1 in humid regions. The majority of recharge rates range from 20 to 50% of precipitation and are sensitive to subannual climate variability. Simulation results are consistent with independent observations of mean annual recharge and significantly better than other global hydrology models that do not consider karst processes (PCR-GLOBWB, WaterGAP). Global hydrology models systematically under-estimate karst recharge implying that they over-estimate actual evapotranspiration and surface runoff. Karst water budgets and thus information to support management decisions regarding drinking water supply and flood risk are significantly improved by our model.