Developing a pan-European high-resolution groundwater recharge map - Combining satellite data and national survey data using machine learning
article
Groundwater recharge quantification is essential for sustainable groundwater resources management, but typically limited to local and regional scale estimates. A high-resolution (1 km × 1 km) dataset consisting oflong-term average actual evapotranspiration, effective precipitation, a groundwater recharge coefficient, and the resulting groundwater recharge map has been created for all of Europe using a variety of pan-European and seven national gridded datasets. Asaninitial step, the approachdeveloped for continentalscale mappingconsists ofa mergedestimate of actual evapo transpiration originating from satellite data and the vegetation controlled Budyko approach to subsequently estimate effective precipitation. Secondly, a machine learning model based on the Random Forest regressor was developed for mapping groundwater recharge coefficients, using a range of covariates related to geology, soil, topography and climate. A common feature of the approach is the validation and training against effective precipitation, recharge coefficients and groundwater recharge from seven national gridded datasets covering the UK, Ireland, Finland,Denmark, the Netherlands, France and Spain, representing a wide range of climatic and hydrogeological conditions across Europe. The groundwater recharge map provides harmonised high-resolution estimates across Europe and locally relevant estimates for areas where this information is otherwise not available, while being consistent with the existing national gridded datasets. The Pan-European groundwater recharge pattern compares well with results from the globalhydrological modelPCR-GLOBWB2. At country scale,the results were compared to a German recharge map showing great similarity. The full dataset of long-term average actual evapotranspiration, effective precipitation, rechargecoefficients and groundwaterrechargeis available throughthe EuroGeoSurveys'openaccess EuropeanGeological Data Infrastructure (EGDI).
TNO Identifier
1034591
Source
Science of the Total Environment, 822, pp. 1-15.
Article nr.
153464
Pages
1-15