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Direct 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. Plain Language Summary: A space‐time data analysis was conducted to generate reliable spatial maps of groundwater level variability and to identify groundwater level patterns over the island of Crete, Greece. Two innovative tools were applied to find the optimal distance and interdependence between observations where hydro‐geological discontinuities are present in the aquifer system. The first is an alternative to common distance metric, which in everyday language is called the taxi‐cab distance and the second is a function that identifies the number of the connected observations within the same distance creating a number of pairs with similar characteristics under a series of mathematical parameters that can model the increments and/or decrement of the physical variable values at that points. The outcome is a map that presents the variability of groundwater level in the entire island notifying areas under high risk of groundwater resources shortage. The presentation of groundwater level status in the entire island strengthens water resources planning and management and connection to hydro meteorological effects. The proposed methodology will be especially valuable in semi‐arid areas where groundwater is the primary source of water. Key Points: Hydrogeological discontinuities by means of faults are bypassed using the Manhattan distance metricA Bayesian based approach such as Gaussian Process provides improved geostatistical analysis results compared to conventional methodsSpatiotemporal Spartan covariance function obtains successfully groundwater level variations interdependence [ABSTRACT FROM AUTHOR]