Using reliable stochastic or deterministic methods, it is possible to rearrange an existing network by eliminating, adding or moving monitoring locations producing the optimal arrangement among any possible. In this paper, some spatial optimization methods have been selected as more effective among those reported in literature and implemented into a software M-Sanos able to carry out a complete redesign of an existing monitoring network. Both stochastic and deterministic methods have been embedded in the software with the option of choosing, case by case, the most suitable with regard to the available information. Finally, an application to the existing regional groundwater level monitoring network of the aquifer of Tavoliere located in Apulia (south Italy) is presented.

A software for optimal information based downsizing/upsizing of existing monitoring networks

Barca E;Passarella G;Vurro M;
2011

Abstract

Using reliable stochastic or deterministic methods, it is possible to rearrange an existing network by eliminating, adding or moving monitoring locations producing the optimal arrangement among any possible. In this paper, some spatial optimization methods have been selected as more effective among those reported in literature and implemented into a software M-Sanos able to carry out a complete redesign of an existing monitoring network. Both stochastic and deterministic methods have been embedded in the software with the option of choosing, case by case, the most suitable with regard to the available information. Finally, an application to the existing regional groundwater level monitoring network of the aquifer of Tavoliere located in Apulia (south Italy) is presented.
2011
Istituto di Ricerca Sulle Acque - IRSA
978-88-96025-12-3
Environmental monitoring
Spatial simulated annealing
Kriging
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/176227
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