How a Computational Method Can Help to Improve the Quality of River Flood Prediction by Simulation

  • Adriana Gaudiani
  • Emilio Luque
  • Pablo García
  • Mariano Re
  • Marcelo Naiouf
  • Armando De Giusti
Part of the Progress in IS book series (PROIS)

Abstract

High performance computing has become a fundamental technology essential for computer simulation. Modelling and computational simulation provide powerful tools which enable flood event forecasting. In order to reduce flood damage, we have developed a methodology focused on enhancing a flood simulator minimizing the number of errors between simulated and observed results by using a two-phase optimization methodology via simulation. In this research, we implemented this approach to find the best solution or adjusted set of simulator input parameters. As a result of this, we achieved an improvement of up to 14 % which, for example, represents a significant difference of 0.5–1 m of water level along whole Paraná River basin. In order to find the adjusted set of input parameters, we reduced the search space using a Monte Carlo + clustering K-Means method. Therefore, an exhaustive search over the reduced search space led us to get a “good solution”. In summary, we propose add an improvement process on the classical computer model output to improve model quality.

Keywords

Flood simulation Simulator tuning Optimization methodology Parametric simulation 

Notes

Acknowledgements

This research has been supported by the MICINN Spain under contract TIN2007-64974, the MINECO (MICINN) Spain under contract TIN2011-24384 and it was partially supported by the research program of Informatics Research Institute III-LIDI, Faculty of Computer Science, Universidad Nacional de La Plata. We are very grateful for the data provided by INA and we appreciate the guidance received from researchers at INA Hydraulic Laboratory.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Adriana Gaudiani
    • 1
    • 4
  • Emilio Luque
    • 2
  • Pablo García
    • 3
  • Mariano Re
    • 3
  • Marcelo Naiouf
    • 4
  • Armando De Giusti
    • 4
  1. 1.Science InstituteUniversidad Nacional de General SarmientoBuenos AiresArgentina
  2. 2.Computer Architecture and Operating Systems DepartmentUniversidad Autónoma de BarcelonaBarcelonaEspaña
  3. 3.Hydraulic Computational ProgramHydraulic Laboratory, National Institute of WaterBuenos AiresArgentina
  4. 4.Informatics Research Institute LIDIUniversidad Nacional de La PlataBuenos AiresArgentina

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