Hydrogeological map of Lower Saxony 1: 50 000 — Change of mean annual groundwater regeneration for the 30-year period 2021-2050 to 1971-2000 in the hydrological summer semester No climate protection scenario (RCP8.5)

The map shows the modeled change in the mean annual groundwater formation for the 30-year period 2071-2100 to 1971-2000 in the hydrological summer half-year (May-Oct.) in mm/a calculated with the “No climate protection” scenario (RCP8.5). Groundwater is a raw material that can regenerate and renew itself. The main supplier for the groundwater supply is precipitation water leaking in Lower Saxony. It ensures that the groundwater deposits of the storage rocks are replenished in the underground. The groundwater formation is particularly high in winter, as at this time a large part of the rainfall in the soil is leaking.In the warmer seasons, on the other hand, much of the precipitation already evaporates on the surface or is absorbed by plants. The new groundwater formation is widely distributed in different areas. It depends on the distribution of precipitation and evaporation, the characteristics of the soil, the land use (growth, degree of sealing), the relief of the land surface, the artificial drainage by drainage, the groundwater fluid level and the properties of the near-surface rocks. Since these parameters differ significantly in the smallest space in Lower Saxony, groundwater formation is also subject to large lateral fluctuations. In order to determine the new groundwater formation, there are different methods. The available maps show the area-differentiated designation of the mean groundwater formation, which was calculated using the mGROWA method (short for “monthly large-scale water balance”).The model mGROWA was developed for the large-scale simulation of the water balance at Forschungszentrum Jülich in cooperation with the LBEG (Herrmann et al. 2013) and updated methodically for Lower Saxony since 2016.In addition, a series of new input data has been used to provide an up-to-date data base for water management planning and water approval procedures. Daily and monthly climate projection data were used as climatic input data. The climate projection data represent the results of an ensemble of different climate models (the Lower Saxony climate ensemble AR5-NI v2.1 see Hajati et al.(2022)). The data was provided by the German Weather Service.The basis for this is the EURO-CORDEX Ensemble (Jacob et al., 2014). As part of the BMVI expert network, the DWD saw a downscale from a 12.5 km grid to a 5 km grid. The climate models are driven by the “No-Climate Protection” scenario (RCP8.5). This is a scenario of the IPCC, which describes a continuous increase in global greenhouse gas emissions, resulting in an additional radiative propulsion of 8.5 watts per m² compared to pre-industrial levels by the end of the 21st century. The results of all climate models are equally likely. Therefore, in addition to the mean, which shows a tendency, the upper (maximum) and lower (minimum) edge of the result bandwidth can be retrieved via the maptip. For better regionalisation, the climatic input parameters precipitation and potential evaporation with bilinear interpolation were scaled down to a 500 x 500 m grid for mGROWA22.The map shows the modeled change in the mean annual groundwater formation for the 30-year period 2071-2100 to 1971-2000 in the hydrological summer half-year (May-Oct.) in mm/a calculated with the “No climate protection” scenario (RCP8.5). Groundwater is a raw material that can regenerate and renew itself. The main supplier for the groundwater supply is precipitation water leaking in Lower Saxony.It ensures that the groundwater deposits of the storage rocks are replenished in the underground. The groundwater formation is particularly high in winter, as at this time a large part of the rainfall in the soil is leaking. In the warmer seasons, on the other hand, much of the precipitation already evaporates on the surface or is absorbed by plants. The new groundwater formation is widely distributed in different areas. It depends on the distribution of precipitation and evaporation, the characteristics of the soil, the land use (growth, degree of sealing), the relief of the land surface, the artificial drainage by drainage, the groundwater fluid level and the properties of the near-surface rocks. Since these parameters differ significantly in the smallest space in Lower Saxony, groundwater formation is also subject to large lateral fluctuations. In order to determine the new groundwater formation, there are different methods. The available maps show the area-differentiated designation of the mean groundwater formation, which was calculated using the mGROWA method (short for “monthly large-scale water balance”). The model mGROWA was developed for the large-scale simulation of the water balance at Forschungszentrum Jülich in cooperation with the LBEG (Herrmann et al.2013) and updated methodically for Lower Saxony since 2016. In addition, a series of new input data has been used to provide an up-to-date data base for water management planning and water approval procedures. Daily and monthly climate projection data were used as climatic input data. The climate projection data represent the results of an ensemble of different climate models (the Lower Saxony climate ensemble AR5-NI v2.1 see Hajati et al. (2022)). The data was provided by the German Weather Service. The basis for this is the EURO-CORDEX Ensemble (Jacob et al., 2014). As part of the BMVI expert network, the DWD saw a downscale from a 12.5 km grid to a 5 km grid. The climate models are driven by the “No-Climate Protection” scenario (RCP8.5). This is a scenario of the IPCC, which describes a continuous increase in global greenhouse gas emissions, resulting in an additional radiative propulsion of 8.5 watts per m² compared to pre-industrial levels by the end of the 21st century. The results of all climate models are equally likely. Therefore, in addition to the mean, which shows a tendency, the upper (maximum) and lower (minimum) edge of the result bandwidth can be retrieved via the maptip. For better regionalisation, the climatic input parameters precipitation and potential evaporation with bilinear interpolation were scaled down to a 500 x 500 m grid for mGROWA22.