A top-down modeling approach to assess regional scale groundwater vulnerability: a case study for Berlin-Brandenburg

Regional scale groundwater vulnerability models are urgently needed to cope with the challenges presented by climate change. Traditional modeling approaches in hydrology and hydrogeology however often require detailed process understanding, and geological information to reliably simulate the hydrological system. In this study we present an alternative, top-down model development framework, starting from the big picture of the hydrology of the region, then focusing on the smaller details and complexities in a gradual way.

Groundwater vulnerability of the Brandenburg region is assessed by investigating the response of the groundwater table to different weather patterns. In order to achieve this a regional dataset for Brandenburg is prepared, using monthly groundwater and surface water data from the time period 1990-2022. This data is then reflected to weather timeseries taken from the Central European Refined analysis dataset, a gridded climate reanalysis dataset for the same time period. The datasets are aggregated on a subcatchment scale, which allows closing the water balance for the individual hydrological response units. Both water balance, linear regression and non-linear regression models are used with automatic calibration, because of the large number of modelled subcatchments.

Due to the big-data nature of the modeling approach, the interpretation of the results is also done in an automatized way. We delineate regions of different vulnerability characteristics by unsupervised methods based on their response dynamics. We also try to identify major turning points in the climatic water balance timeseries. The presented framework produces models that can be used towards deriving actionable insights for groundwater management.