Early flood warning in the Itajaí-Açu River basin using numerical weather forecasting and hydrological modeling

Leandro Casagrande (), Javier Tomasella, Regina Célia Santos Alvalá, Marcus Jorge Bottino and Rochane Oliveira Caram
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Leandro Casagrande: Center of Earth System Science – CCST/INPE. Av. dos Astronautas
Javier Tomasella: Center of Earth System Science – CCST/INPE. Av. dos Astronautas
Regina Célia Santos Alvalá: National Center for Monitoring and Early Warning of Natural Disasters – CEMADEN. Estrada Doutor Altino Bondesan
Marcus Jorge Bottino: National Center for Monitoring and Early Warning of Natural Disasters – CEMADEN. Estrada Doutor Altino Bondesan
Rochane Oliveira Caram: National Center for Monitoring and Early Warning of Natural Disasters – CEMADEN. Estrada Doutor Altino Bondesan

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2017, vol. 88, issue 2, No 5, 757 pages

Abstract: Abstract In recent decades, population growth associated with unplanned urban occupation has increased the vulnerability of the Brazilian population to natural disasters. In susceptible regions, early flood forecasting is essential for risk management. Still, in Brazil, most flood forecast and warning systems are based either on simplified models of flood wave propagation through the drainage network or on stochastic models. This paper presents a methodology for flood forecasting aiming to an operational warning system that proposes to increase the lead time of a warning through the use of an ensemble of meteorological forecasts. The chosen configuration was chosen so it would be feasible for an operational flood forecast and risk management. The methodology was applied to the flood forecast for the Itajaí-Açu River basin, a region which comprises a drainage area of approximately 15,500 km2 in the state of Santa Catarina, Brazil, historically affected by floods. Ensemble weather forecasts were used as input to the MHD-INPE hydrological model, and the performance of the methodology was assessed through statistical indicators. Results suggest that flood warnings can be issued up to 48 h in advance, with a low rate of false warnings. Streamflow forecasting through the use of hydrological ensemble prediction systems is still scarce in Brazil. To the best of our knowledge, this is the first time this methodology aiming to an operational flood risk management system has been tested in Brazil.

Keywords: Natural disasters; Flooding; H-EPS; MHD-INPE (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s11069-017-2889-0

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