Numerical models are instrumental to more effective flood forecasting and management services though they suffer from numerous uncertainty sources. An effective model calibration is hence essential. In this research work, a methodology of optimal sampling design has been investigated and developed for water drainage networks. Optimal hydrometer sensors locations along the Amato River (South Italy) have been defined by optimizing a two-objective function that maximizes the calibrated model accuracy and minimizes the total metering cost. This problem has been solved by using an enumerative search solution, run on the ENEA/CRESCO HPC infrastructure, evaluating the exact Pareto-front by efficient computational time. © 2015 Published by Elsevier Ltd.
Optimal sensors placement for flood forecasting modelling
Di Francia, G.;De Vito, S.;Buonanno, Antonio.;Lanza, B.;Guarnieri, G.;Fattoruso, G.
2015-01-01
Abstract
Numerical models are instrumental to more effective flood forecasting and management services though they suffer from numerous uncertainty sources. An effective model calibration is hence essential. In this research work, a methodology of optimal sampling design has been investigated and developed for water drainage networks. Optimal hydrometer sensors locations along the Amato River (South Italy) have been defined by optimizing a two-objective function that maximizes the calibrated model accuracy and minimizes the total metering cost. This problem has been solved by using an enumerative search solution, run on the ENEA/CRESCO HPC infrastructure, evaluating the exact Pareto-front by efficient computational time. © 2015 Published by Elsevier Ltd.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
