Abstract
AbstractDirect interpolation of groundwater levels often leads to contour maps which are hydrogeological inconsistent since numerical algorithms do not consider changes in flowline patterns caused by hydrogeological heterogeneities and aquifer boundary conditions. In the present work, this issue is assessed by conducting a geostatistical analysis based on Gaussian process method, using space‐time groundwater level observations, to generate reliable spatial maps of groundwater level variability and to identify groundwater level patterns over the island of Crete, Greece. Besides, two innovative tools are employed in the process: the Manhattan distance metric to obtain spatial correlation where faults are present in the aquifer and the spatiotemporal Spartan covariance function to obtain spatiotemporal interdependence. The results show significant prediction improvement over convectional geostatistical methods. Useful information is obtained from the delivered map notifying areas under high risk of groundwater resources shortage. The developed approach could be applied to other areas with analogous hydrogeological properties. It will be especially valuable in semi‐arid areas prone to droughts, where groundwater represents the main source of water.
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