Modelo de Previsão de Vazão com Informação de Precipitação Utilizando Redes Neurais

Cruz, A.L.P.; Barbosa, Carlos Roberto Hall; Figueiredo, Karla; Pacheco, Marco Aurélio Cavalcanti; Mendes, Marcos; Vellasco, Marley; Barros, Mônica Colognese; Souza, Reinaldo Castro; Contreras, Roxana; Duarte, Ulmar; Marques, Valdo

doi:10.21168/rbrh.v12n3.p69-82

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“…Due to the geomorphological and climatic characteristics of the basin, tributaries may have rapid rise of the hydrograph with very high peaks (REYNAUD; MINE; KAVISKI, 2014), posing challenges for streamflow forecasting which is sometimes performed by coupling stochastic or hydrological models to numerical weather prediction (e.g. GUILHON; ROCHA; MOREIRA, 2007;CASTANHARO et al, 2007;FIGUEIREDO et al, 2007;ARAUJO et al, 2014).…”

Section: Study Case: Lower Iguazu Basinmentioning

confidence: 99%

Real-time updating of HEC-RAS model for streamflow forecasting using an optimization algorithm

Siqueira

Sorribas

Bravo

et al. 2016

RBRH

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Real-time updating of channel flow routing models is essential for error reduction in hydrological forecasting. Recent updating techniques found in scientific literature, although very promising, are complex and often applied in models that demand much time and expert knowledge for their development, posing challenges for using in an operational context. Since powerful and well-known computational tools are currently available, which provide easy-to-use and less time-consuming platforms for preparation of hydrodynamic models, it becomes interesting to develop updating techniques adaptable to such tools, taking full advantage of previously calibrated models as well as the experience of the users. In this work, we present a real-time updating procedure for streamflow forecasting in HEC-RAS model, using the Shuffled Complex Evolution -University of Arizona (SCE-UA) optimization algorithm. The procedure consists in a simultaneous correction of boundary conditions and model parameters through: (i) generation of a lateral inflow, based on Soil Conservation Service (SCS) dimensionless unit hydrograph and; (ii) estimation of Manning roughness in the river channel. The algorithm works in an optimization window in order to minimize an objective function, given by the weighted sum of squared errors between simulated and observed flows where differences in later intervals (start of forecast) are more penalized. As a case study, the procedure was applied in a river reach between Salto Caxias dam and Hotel Cataratas stream gauge, located in the Lower Iguazu Basin. Results showed that, with a small population of candidate solutions in the optimization algorithm, it is possible to efficiently improve the model performance for streamflow forecasting and reduce negative effects caused by lag errors in simulation. An advantage of the developed procedure is the reduction of both excessive handling of external files and manual adjustments of HEC-RAS model, which is important when operational decisions must be taken in relatively short times.Keywords: River flow forecasting; HEC-RAS; Real-time updating; SCE-UA. RESUMOA atualização em tempo real de modelos de propagação do escoamento em rios é essencial para a redução de erros na previsão hidrológica. As técnicas de atualização recentes encontradas na literatura, apesar de promissoras, são complexas e geralmente aplicadas em modelos cujo desenvolvimento demanda tempo e conhecimento muito especializado, representando desafios para sua utilização em ambientes operacionais. Dado que atualmente existem ferramentas computacionais amplamente difundidas, que reduzem tempo e simplificam a preparação de modelos hidrodinâmicos, torna-se interessante desenvolver técnicas que sejam facilmente acopladas a estas ferramentas de modo a aproveitar um modelo já calibrado e a experiência dos usuários. Neste trabalho é apresentada uma metodologia de atualização em tempo real do modelo HEC-RAS para previsão de vazões,

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Section: Study Case: Lower Iguazu Basinmentioning

confidence: 99%