Data: 17/09/2014 à 19/09/2014
Local: São Paulo - Brazil
Hydrological and Meteorological Forecast Combined Systems for Flood Alerts and Reservoir Management: the Iguaçu River Basin Case (PAP014749)
Flood forecasting and early warning systems
Foz do Areia and Segredo hydro power plants operation may increase flooding risks atupstream União da Vitória, Porto União and Porto Vitória cities, on extreme weather conditions. Thisregion has a long past of flood vulnerability, even before 1980 when Foz do Areia was built, because itswatershed physical characteristics. Many structural and non-structural actions implemented at Iguaçuriver basin are focused on alerts of flood forecasts for local people, in addition to operation rules thatreduce impacts made by such events. Sophisticated equipments are then used for systematic water tablemeasurement at Foz do Areia and União da Vitória. Such data are inputs for a well-established real timereservoir management methodology, referred here as ?water level dynamic control?, meaning to lowingdown reservoir water level at critical flood situations and preventing a worst scenario at União da Vitóriaand neighborhood. Moreover, Copel keeps a quantitative precipitation and a hydrological forecastsystems for the entire river basin, both developed by SIMEPAR, which are joint operated to provide floodsalerts at the risk sites. The Quantitative Precipitation Forecast (QPF) is obtained from high horizontalresolution (9 km) simulations of the Weather Research and Forecast (WRF) model. The hydrologicalforecast system for Iguaçu river basin, named SISPSHI, applies both automated gauge network data andQPF results to estimate river flow at 21 sites along the whole watershed. SISPSHI sets multiple forecasts,using conceptual, stochastic and probabilistic approaches, especially for União da Vitória city. Suchmethodology has provided a great improvement for flood forecasts for this place. The objective of thiswork is to demonstrate how the adoption of efficient rules for reservoir operation and the consortium ofhydro-meteorological models, as well as efficient measurements, establish essential tools for decisionmakers during extreme hydrological events.