Agile Tuning Method In Successive Steps For A River Flow Simulator

Scientists and engineers continuously build models to interpret axiomatic theories or explain the reality of the universe of interest to reduce the gap between formal theory and observation in practice. We focus our work on dealing with the uncertainty of the input data of the model to improve the quality of the simulation. To reduce this error, scientist and engineering implement techniques for model tuning and they look for ways to reduce their high computational cost. This article proposes a methodology for adjusting a simulator of a complex dynamic system that models the wave translation along rivers channels, with emphasis on the reduction of computation resources. We propose a simulator calibration by using a methodology based on successive adjustment steps of the model. We based our process in a parametric simulation. The input scenarios used to run the simulator at every step were obtained in an agile way, achieving a model improvement up to 50% in the reduction of the simulated data error. These results encouraged us to extend the adjustment process over a larger domain region.