The objective of this work is to investigate new methods and improve existing methods based on statistical, geostatistical, and hydrogeological methods for groundwater monitoring network optimization. New approaches were formulated, and existing methods were improved, and integrated, for the spatiotemporal optimization of a groundwater monitoring network and they were tested with data set of Bitterfeld/Wolfen. Univariate and multivariate statistics were applied to the spatialtemporal optimization of the monitoring network. Geostatistical spatio-temporal algorithm was used to identify redundant wells on the basis of nearby wells offering the same information about the underlying plume in 2- and 2.5- dimensional Quaternary and Tertiary aquifers. Steady state flow and transient transport model was used to optimize possible monitoring network. Factors influencing the monitoring network optimization were analysed. In this work, it is demonstrated that the existing monitoring network could be optimized using the presented statistical, geostatistical, and hydrogeological methods, without losing any essential information from the monitoring network.