Gaudiani, AdrianaLuque, EmilioGarcia, PabloRe, MarianoNaiouf, MarceloDe Giusti, ArmandoGómez, Jorge MarxSonnenschein, MichaelVogel, UteWinter, AndreasRapp, BarbaraGiesen, Nils2019-09-162019-09-162014https://dl.gi.de/handle/20.500.12116/25746The occurrence of flood events has become more frequent in many parts of the world over the past 30 years and, consequently, more people are exposed to flood damages. Modeling and computational simulation provide powerful tools which enable us to forecast, in order to reduce flood damages. This work is oriented to address input parameter uncertainty toward providing a methodology to tune the flood simulator and so achieve lower errors between simulated and observed results. Even a much reduced parameter set is considered to run the flood simulator, the search space is large. The results obtained by using a parametric simulation heuristic and a clustering technique are promising and a reduction of the search space was achieved, consequently we could reduce the computational cost of the search for the best scenario and the optimization scheme implemented enables us to get a better understanding of the problem.Text/Conference Paper