Influence of available data on the geostatistical-based design of optimal spatiotemporal groundwater-level-monitoring networks

Abstract

Several methodologies exist for the design of optimal groundwater monitoring networks. Those that employ geostatistical techniques are usually dependent on a variogram. In practice, different variograms for an environmental variable can be fitted depending on the number of available data, their spatial distribution, and their variability. For this reason, in most cases, it is difficult to get an adequate variogram. This report evaluates the influence of the groundwater level data available in the construction of a product-sum spatiotemporal variogram model and its consequences on a geostatistical-based methodology that uses the Kalman filter for the design of optimal spatiotemporal monitoring networks. Additionally, a sensitivity analysis is carried out to determine the variations in the optimal number of wells and monitoring frequency for the monitoring network, depending on the selected spatiotemporal variogram model. The results show the importance of getting a good quality spatiotemporal variogram when designing optimal groundwater-level monitoring networks using geostatistical-based methodologies.