Hydrogeological map of Lower Saxony 1: 50 000 — Average monthly groundwater formation 1991-2020 in July, method mGROWA22

The map shows the mean monthly groundwater formation for the month of July in the 30-year period 1991-2020. 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Service were used.These are the potential evaporation calculated on the basis of FAO grass reference evaporation (DWD, unpublished) and precipitation based on the REGNIE product (Rauthe et al, 2013) corrected by Richter (Judge, 1995).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. The map shows the mean monthly groundwater formation for the month of July in the 30-year period 1991-2020. 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.本地图展示了1991-2020年这30年周期内7月的平均月地下水补给量。地下水是一种可自我循环更新的自然资源。 地下水补给的主要来源是下萨克森州（Lower Saxony）境内入渗的降水。这一过程保障了地下储水岩层中的地下水储量得到补充。 冬季的地下水补给量尤为充沛，因为此时土壤中的大部分降雨会入渗至地下；而在较为温暖的季节，多数降水会在地表蒸发或被植物吸收。 新增地下水补给的分布范围覆盖多个区域。 地下水补给量取决于降水与蒸发的分布、土壤特性、土地利用状况（植被覆盖度、封闭程度）、地表地形起伏、人工排水措施、地下水位以及近地表岩层的性质。由于下萨克森州境内这些参数在极小空间尺度内便存在显著差异，地下水补给量也会出现较大的横向波动。 针对新增地下水补给量的测算，存在多种方法。本套地图展示了平均地下水补给量的分区标识结果，该结果通过mGROWA方法（即“月尺度大尺度水平衡”的缩写）计算得到。 mGROWA模型由于利希研究中心（Forschungszentrum Jülich）与下萨克森州采矿、能源与地质局（Landesamt für Bergbau, Energie und Geologie, LBEG）合作开发，用于大尺度水平衡模拟（Herrmann等，2013），并自2016年起针对下萨克森州进行了系统性更新。 此外，研究团队采用了一系列新的输入数据，为水资源管理规划与取水许可审批流程提供了最新的数据库支撑。 气候输入数据采用了德国气象局（Deutscher Wetterdienst, DWD）的实测逐日、逐月气候观测数据，后续经空间插值处理得到。 这些数据包括基于联合国粮食及农业组织（Food and Agriculture Organization of the United Nations, FAO）参考草本蒸发蒸腾量计算得到的潜在蒸发量（DWD，未公开数据），以及经Richter（Judge，1995）校正的、基于REGNIE降雨网格产品的降水数据（Rauthe等，2013）。 为实现更精准的区域化表达，研究团队通过双线性插值将降水与潜在蒸发量这两项气候输入参数的分辨率降至100×100米网格，以适配mGROWA22模型。 本地图展示了1991-2020年这30年周期内7月的平均月地下水补给量。地下水是一种可自我循环更新的自然资源。 地下水补给的主要来源是下萨克森州（Lower Saxony）境内入渗的降水。这一过程保障了地下储水岩层中的地下水储量得到补充。 冬季的地下水补给量尤为充沛，因为此时土壤中的大部分降雨会入渗至地下；而在较为温暖的季节，多数降水会在地表蒸发或被植物吸收。 新增地下水补给的分布范围覆盖多个区域。 地下水补给量取决于降水与蒸发的分布、土壤特性、土地利用状况（植被覆盖度、封闭程度）、地表地形起伏、人工排水措施、地下水位以及近地表岩层的性质。由于下萨克森州境内这些参数在极小空间尺度内便存在显著差异，地下水补给量也会出现较大的横向波动。 针对新增地下水补给量的测算，存在多种方法。本套地图展示了平均地下水补给量的分区标识结果，该结果通过mGROWA方法（即“月尺度大尺度水平衡”的缩写）计算得到。 mGROWA模型由于利希研究中心（Forschungszentrum Jülich）与下萨克森州采矿、能源与地质局（Landesamt für Bergbau, Energie und Geologie, LBEG）合作开发，用于大尺度水平衡模拟（Herrmann等，2013），并自2016年起针对下萨克森州进行了系统性更新。 此外，研究团队采用了一系列新的输入数据，为水资源管理规划与取水许可审批流程提供了最新的数据库支撑。 气候输入数据采用了德国气象局（Deutscher Wetterdienst, DWD）的实测逐日、逐月气候观测数据，后续经空间插值处理得到。 这些数据包括基于联合国粮食及农业组织（Food and Agriculture Organization of the United Nations, FAO）参考草本蒸发蒸腾量计算得到的潜在蒸发量（DWD，未公开数据），以及经Richter（Judge，1995）校正的、基于REGNIE降雨网格产品的降水数据（Rauthe等，2013）。 为实现更精准的区域化表达，研究团队通过双线性插值将降水与潜在蒸发量这两项气候输入参数的分辨率降至100×100米网格，以适配mGROWA22模型。