MSANOS: Data-Driven, Multi-Approach Software for Optimal Redesign of Environmental Monitoring Networks

Abstract

Within the recent EU Water Framework Directive and the modification introduced into national water-related legislation, monitoring assumes great importance in the frame of territorial managerial activities. Recently, a number of public environmental agencies have invested resources in planning improvements to existing monitoring networks. In effect, many reasons justify having a monitoring network that is optimally arranged in the territory of interest. In fact, modest or sparse coverage of the monitored area or redundancies and clustering of monitoring locations often make it impossible to provide the manager with sufficient knowledge for decision-making processes. The above mentioned are typical cases requiring optimal redesign of the whole network; fortunately, using appropriate stochastic or deterministic methods, it is possible to rearrange the existing network by eliminating, adding, or moving monitoring locations and producing the optimal arrangement with regard to specific managerial objectives. This paper describes a new software application, MSANOS, containing some spatial optimization methods selected as the most effective among those reported in literature. In the following, it is shown that MSANOS is actually able to carry out a complete redesign of an existing monitoring network in either the addition or the reduction sense. Both model-based and design-based objective functions have been embedded in the software with the option of choosing, case by case, the most suitable with regard to the available information and the managerial optimization objectives. Finally, two applications for testing the goodness of an existing monitoring network and the optimal reduction of an existing groundwater-level monitoring network of the aquifer of Tavoliere located in Apulia (South Italy), constrained to limit the information loss, are presented.

Optimisation of Dynamic Heterogeneous Rainfall Sensor Networks in the Context of Citizen Observatories

“…Alternatively, the optimal network can also be defined as such that minimise the maximum (min-max) interpolation variance (MKV) (Barca et al 2015) as:…”

“…Scenarios for designing of sensor networks may be categorised into three groups: augmentation, relocation and reduction (NRC 2004, Mishra and Coulibaly 2009, Barca et al 2015. Augmentation refers to the deployment of at least one additional sensor in the network, whereas Reduction refers to the opposite case, where at least one sensor is removed from the original network.…”

Assessing Spatial Scale Effects on Hydrometric Network Design Using Entropy and Multi‐objective Methods

“…Network design methods range from experience based (Moss and Tasker, 1991) to performance based (Anctil et al, 2006). Network improvements can be made through augmentation or relocation of gauges to improve performance (Barca et al, 2015), while reduction of gauges is often considered to conserve resources (Dong et al, 2005). Coulibaly (2009) andChacon-Hurtado et al (2016) provide detailed literature reviews of hydrometric network design methods.…”

Integration of electromagnetic induction sensor data in soil sampling scheme optimization using simulated annealing

“…Soil water content was used as environmental geovariable, whereas the simulated annealing was implemented by the software MSANOS (Barca et al 2011(Barca et al , 2015.…”