| Title | Data-driven and multi-approach sampling scheme optimization: the Alimini Lakes aquifer case |
| Abstract | Due to the high wells drilling cost, monitoring sites are usually selected among existing wells; nevertheless, the resulting monitoring network must assure a good assessment of the main characteristics of the considered aquifer. Groundwater managers, need to find a good balance between two conflicting objectives: maximizing monitoring information and minimizing costs. In this paper, a couple of groundwater monitoring optimization methods are presented, related to the local shallow aquifer of the Alimini Lakes, located in Apulia (South-Eastern Italy) where a large number of existing wells have been pinpointed and the need of optimally reducing exists. The proposed methods differ each other for the required amount of prior information. The first proposed method, namely Greedy Deletion, just requires the geographical position of the available sites, while the second, the Simulated Annealing, also requires the knowledge of the spatial law of the considered phenomenon. The managerial need was to halve the number of monitoring sites minimizing the information loss. |
| Source | GRASPA 2015, Bari, 15-16 giugno 2015GRASPA Working Papers Special Issue, pp. 29–32 |
| Keywords | Monitoring networks; Shallow aquifers; Greedy deletion; Spatial simulated annealing |
| Journal | GRASPA Working Papers |
| Editor | GRASPA - Gruppo di Ricerca per le Applicazioni della Statistica ai Problemi Ambientali, S.l., Italia |
| Year | 2015 |
| Type | Contributo in atti di convegno |
| Authors | E. Barca, M.C. Caputo, L. De Carlo, R. Masciale, G. Passarella |
| Text | 331502 2015 Monitoring networks; Shallow aquifers; Greedy deletion; Spatial simulated annealing Data driven and multi approach sampling scheme optimization the Alimini Lakes aquifer case E. Barca, M.C. Caputo, L. De Carlo, R. Masciale, G. Passarella E. Barca 1 , M.C. Caputo 1 , L. De Carlo 1 , R. Masciale 1 , G. Passarella 1 1 Water Research Institute of the National Research Council, Department of Bari, Viale F. De Blasio, 5 70123 Due to the high wells drilling cost, monitoring sites are usually selected among existing wells; nevertheless, the resulting monitoring network must assure a good assessment of the main characteristics of the considered aquifer. Groundwater managers, need to find a good balance between two conflicting objectives maximizing monitoring information and minimizing costs. In this paper, a couple of groundwater monitoring optimization methods are presented, related to the local shallow aquifer of the Alimini Lakes, located in Apulia South Eastern Italy where a large number of existing wells have been pinpointed and the need of optimally reducing exists. The proposed methods differ each other for the required amount of prior information. The first proposed method, namely Greedy Deletion, just requires the geographical position of the available sites, while the second, the Simulated Annealing, also requires the knowledge of the spatial law of the considered phenomenon. The managerial need was to halve the number of monitoring sites minimizing the information loss. Proceedings of the GRASPA2015 Conference A. Fasso and A. Pollice Published version http //meetings.sis statistica.org/index.php/graspa2015/graspa2015/paper/viewFile/3288/590 E. Barca, M.C. Caputo, L. De Carlo, R. Masciale, G. Passarella 2015 Data driven and multi approach sampling scheme optimization the Alimini Lakes aquifer case. In A. Fasso and A. Pollice Editors . Proceedings of the GRASPA2015 Conference, Bari, 15 16 June, 2015. Special issue of GRASPA Working Papers. ISSN 2037 7738. Special Issue GRASPA 2015 Bari 15 16 giugno 2015 Internazionale Contributo Data driven and multi approach sampling scheme optimization the Alimini Lakes aquifer case 3288_7030_1_PB.pdf Contributo in atti di convegno GRASPA Gruppo di Ricerca per le Applicazioni della Statistica ai Problemi Ambientali 2037 7738 GRASPA Working Papers GRASPA Working Papers GRASPA Working Papers Working Papers. GRASPA Gruppo di Ricerca per le Applicazioni della Statistica ai Problemi Ambientali 2037 7738 GRASPA Working Papers GRASPA Working Papers GRASPA Working Papers Working Papers. giuseppe.passarella PASSARELLA GIUSEPPE mariaclementina.caputo CAPUTO MARIA CLEMENTINA emanuele.barca BARCA EMANUELE rita.masciale MASCIALE RITA lorenzo.decarlo DE CARLO LORENZO TA.P04.005.008 Integrazione di metodologie per il monitoraggio e la modellizzazione per la gestione delle risorse idriche |
