<b>Raw Datasets for </b><b>Spatially Explicit Model for Assessing the Impacts of Groundwater Protection Measures in the Vicinity of the Hranice Abyss</b>

The daset presents data from the paper, that presents a spatially explicit model for quantification of the impacts of groundwater protection measures in a specific karst territory. The impacts were studied with regards to Storm Water Retention improvement and Land Surface Temperature cooling. The method for the evaluation is a combination of assessment of vulnerable areas using multicriteria analysis, hydrological modelling and Random Forest prediction model that downscales temperature data on 1x1 m surface. The model uses remote sensing with high resolution, namely LiDAR (50pt/m) point clouds, modelling of retention characteristics, quantification of vegetation and LANDSAT 8 satellite images to determine surface temperature. Land-use / Land cover (LULC) serves as a predictor for the model. Evaluation of changes is based on developing three hypothetical scenarios assuming LULC change upon which the effect of the change is verified in three parameters: protection of ground waters and mineral waters, capacity of retaining stormwater, and capacity of mitigating heat waves. The main finding is that the measures that aim primarily at groundwater protection affect also other parameters – surface temperature and retention capacity, while improving each of these parameters. In case of the retention capacity, it is by up to 32 % and in case of temperature it is a maximum of 8 %. As per the surface temperature, a significant variability has been found depending on the presence of field crops, and the model explains it. The model allows for prioritization of changes on the level of spatial units – in our case microbasins, thus allowing also for more precise targeting of the measures.