OpenData_GroundwaterBore

Model calculations are a dataset that includes modelled depth for ground-level groundwater, ground-level groundwater, water content in the root zone and water flow in streams. The model calculations have been produced by GEUS using DK model HIP in 100 meters grid for the period since 1990. The model calculations are suitable for screening in connection with water management, climate adaptation, urban planning and more.

Probability of occurrence of R horizon predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: probability.

Machine learning and uncertainty is a data set that shows nationwide depth to ground-level groundwater in high spatial resolution (10 m-grid) for a typical summer and winter situation as well as associated uncertainties in the period 1991-2025. The calculations have been carried out by GEUS using the DK model HIP and machine learning in order to provide screening data that can support the work on water management, climate adaptation, urban planning and more.

Records wells (pozzi) as features, published by Regione Umbria's SIAT. Coverage is in Italy.

Water resources and water infrastructure in Comoros including rivers, lakes, boreholes, wells and water points. Use this layer for water access analysis, WASH programme planning, drought monitoring, flood risk assessment, and water resource management.

Water resources and water infrastructure in Botswana including rivers, lakes, boreholes, wells and water points. Use this layer for water access analysis, WASH programme planning, drought monitoring, flood risk assessment, and water resource management.