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Model-based impact study of forest restructuring on groundwater recharge and hydrodynamics in a waterworks catchment (Briesen, Brandenburg, Germany)

The waterworks Briesen supply drinking water for the city of Frankfurt (Oder). The catchment of the waterworks is dominated by monoculture pine forests (Pinus sylvestris). Several forest-hydrological studies found that groundwater recharge under pine forests is lowest in comparison to other forest types. Hence, the question arose if forest restructuring could contribute to secure the drinking water supply of the region in the context of climate change and decreasing groundwater recharge.

Site classes of the forestry mapping were researched for all relevant forest restructuring areas. The Ministry of Environment of the State of Brandenburg published a recommendation of tree species mixtures which are suitable for the local conditions and for resisting climate change. Based on this recommendation, five tree species were selected. The tree mixture was set as percentage of these five tree species for each forest site class in the catchment.

The groundwater recharge below five tree species was calculated in a soil-water-balance model separately. Then the groundwater recharge was calculated for the forest site classes based on the percentage tree composition of each site. Finally, several scenarios of forest restructuring were developed, considering complete and partial restructuring as well as climate change. The resulting distributions of groundwater recharge were assigned as boundary conditions in a groundwater model.

The simulations with the groundwater model show that forest restructuring can increase groundwater recharge compared to current forests by 20 - 30 % and reduce the groundwater level decline and catchment expansion which is expected in the context of climate change.

Details

Author
Franziska Mehler1, Felix Möhler1, Matthias Clausen2, Ines Schwenzer2
Institutionen
1GCI GmbH, Germany; 2FWA Frankfurter Wasser- und Abwassergesellschaft mbH, Germany
Veranstaltung
GeoBerlin 2023
Datum
2023
DOI
10.48380/69e4-eq25
Geolocation
Brandenburg, Germany