Software for the Design of Optimal Multivariate Groundwater Quality Monitoring Networks on a GIS Environment

The aim of the optimal design of groundwater monitoring networks is to obtain the maximum level of information for one or several variables (water level, physicochemical parameters, or pollutants) at minimum cost by discarding those wells that provide redundant information.
The objective of this research was to develop a software that uses a Geographic Information System (GIS) supported by a methodology that employs geostatistical tools and the static Kalman Filter to define optimal multivariate groundwater quality monitoring networks. Within the specialized literature, there are different approaches to define monitoring networks, those that include GIS usually require the application of geostatistical analyses. The adopted methodology employs the Kalman filter as the estimation method within the optimization procedure. Originally, the application of this methodology was carried out in a series of routines written in the Fortran programming language which complicates the implementation for a non-specialized user.
The software presented in this paper provides a single free-access tool that allows to facilitate the design of optimal monitoring networks with the capability of verifying final results on a friendly-user environment. It has also the capability to assign weights to each monitoring site based on the correlation and distribution of analyzed variables.
As a final result, the spatial location of the optimal set of monitoring wells is displayed along with the level of importance of each one according to the amount of information it provides in the estimation of the monitored variable(s).