A percentile approach to evaluate simulated groundwater levels and
frequencies in a Chalk catchment in Southwest England
Abstract. Chalk aquifers are an important source of drinking water in the UK. Understanding and predicting groundwater levels is therefore important for effective water management of this resource. Chalk is known for its high porosity and, due to its dissolvability, exposed to karstification and strong subsurface heterogeneity. To cope with the karstic heterogeneity and limited data availability, specialised modelling approaches are required that balance model complexity and data availability. In this study we present a novel approach to simulate groundwater level frequency distributions with a semi-distributed karst model that represents subsurface heterogeneity by distribution functions. Simulated groundwater storages are transferred into groundwater levels using evidence from different observations wells. Using a newly developed percentile approach we can simulate the number of days exceeding or falling below selected groundwater level percentiles. Firstly, we evaluate the performance of the model to simulate three groundwater time series by a spilt sample test and parameter identifiability analysis. Secondly, we apply a split sample test on the simulated groundwater level percentiles to explore the performance in predicting groundwater level exceedances. We show that the model provides robust simulations of discharge and groundwater levels at 3 observation wells at a test site in chalk dominated catchment in Southwest England. The second split sample test also indicates that percentile approach is able to reliably predict groundwater level exceedances across all considered time scales up to their 75th percentile. However, when looking at the 90th percentile, it only provides acceptable predictions for the longest available time scale and it fails when the 95th percentile of groundwater exceedance levels is considered. Modifying the historic forcings of our model according to expected future climate changes, we create simple climate scenarios and we show that the projected climate changes may lead to generally lower groundwater levels and a reduction of exceedances of high groundwater level percentiles.