Optimizing a Groundwater Level Monitoring Network for Wellfield Management

This paper presents the development and application of a multi-objective geostatistical sensitivity approach to identify gaps and redundancy in a surficial aquifer's monitoring-well network. The key to this approach is the identification of areas where high surficial aquifer system (SAS) water level uncertainty coincide with high SAS water-level sensitivity to pumping in the underlying Upper Floridan Aquifer. The methodology identifies monitoring gaps and redundancies using a multi-objective approach in which an importance score of gaps is calculated. Modifications to the network are guided by geostatistics with the goal of minimizing the gap score. The development and subsequent application of the methodology to a monitoring network currently in use by a major Florida water supplier is described.