Engineers are increasingly called to deal with practical problems related to water resources management, risk analysis, environmental engineering and water pollution. Providing a way forward to solve the above questions requires setting up mathematical models that are affected by uncertainty, that in many cases is relevant. In fact, the theories that are employed for providing solutions to engineer’s problems are not exact sciences: even if it is methodologically rigorous, it is incapable of producing precise results, for the presence of inherent randomness that translates in indeterminacy and therefore uncertainty. To cope with uncertainty is a challenge for scientists and practitioners, that requires the application of proper procedures for model identification, parameter calibration, hypothesis testing, model testing (also called model validation) and finally uncertainty assessment. As a matter of fact, uncertainty estimation in hydrological surface and subsurface modelling is today one of the most important subfields of hydrology, according to the numerous contributions presented by the recent scientific literature.
Freni, G., Mannina, G., Montanari, A. (2012). Uncertainty in environmental and hydrological mathematical modelling. PHYSICS AND CHEMISTRY OF THE EARTH, 42-44(42), 1-2 [10.1016/j.pce.2012.03.001].
Uncertainty in environmental and hydrological mathematical modelling
MANNINA, Giorgio;
2012-01-01
Abstract
Engineers are increasingly called to deal with practical problems related to water resources management, risk analysis, environmental engineering and water pollution. Providing a way forward to solve the above questions requires setting up mathematical models that are affected by uncertainty, that in many cases is relevant. In fact, the theories that are employed for providing solutions to engineer’s problems are not exact sciences: even if it is methodologically rigorous, it is incapable of producing precise results, for the presence of inherent randomness that translates in indeterminacy and therefore uncertainty. To cope with uncertainty is a challenge for scientists and practitioners, that requires the application of proper procedures for model identification, parameter calibration, hypothesis testing, model testing (also called model validation) and finally uncertainty assessment. As a matter of fact, uncertainty estimation in hydrological surface and subsurface modelling is today one of the most important subfields of hydrology, according to the numerous contributions presented by the recent scientific literature.File | Dimensione | Formato | |
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