Hydrogeological map of Lower Saxony 1: 50 000 — Average monthly groundwater regeneration 1971-2000 in June, method mGROWA22 (WMS service)

The map shows the mean monthly groundwater formation for the month of June in the 30-year period 1971-2000. 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. As climatic input data, daily and monthly measured and subsequently spatially interpolated climate observation data from the German Weather Service were used. These are the potential evaporation calculated on the basis of FAO grass reference evaporation (DWD, unpublished) and precipitation based on the REGNIE product (Rauthe et al, 2013) corrected by Richter (Judge, 1995). For better regionalisation, the climatic input parameters precipitation and potential evaporation with bilinear interpolation were scaled down to a 100 x 100 m grid for mGROWA22.