Group method of data handling to forecast the daily water flow at the Cahora Bassa Dam

• Autorzy: Souza, Danilo P. M. , Martinho, Alfeu D. , Rocha, Caio C. , Christo, Eliane da S. , Goliatt, Leonardo
• Języki publikacji: EN

Abstrakty

EN

The Zambezi watershed is essential for water supply, irrigation, fishing activities, and river transport of the populations of Southern Africa. The importance and variability of these water resources make it necessary to develop studies that may help understand and manage them. Despite this need, water resources studies for this region are still scarce. Therefore, the present work aims to present a strategy for forecasting the daily water flow of the Zambezi River in the Cahora Bassa dam, located in Mozambique, an important energy producer in the country and the fourth largest dam in Africa. Historical rainfall, evaporation, and humidity records collected from 2003 to 2011 are used for training and testing a model that forecasts water flow using the Group Method of Data Handling algorithm. The results achieved were compared, through error metrics, with those of other models to prove the effectiveness of the assembled model. They revealed that the proposed model achieves a satisfactory performance for the forecast horizon and could become a helpful tool in monitoring hydrographic basins and forecasting their daily streamflow values.

Słowa kluczowe

PL

obsługa danych modelowania grupowego; prognozowanie przepływu wody; dorzecze Zambezi; nauczanie maszynowe

EN

Group Modeling Data Handling; water flow forecasting; Zambezi basin; machine learning

• Czasopismo: Acta Geophysica
• Rocznik: 2022
• Tom: Vol. 70, no 4
• Strony: 1871--1883
• Opis fizyczny: Bibliogr. 45 poz.

Twórcy

autor

Souza, Danilo P. M.

• Computational Modeling Program, UFJF, Juiz de Fora, Minas Gerais 36036-900, Brazil,
• Federal University of Juiz de Fora, Rua José Lourenço Kelmer, Juiz de Fora, Minas Gerais 36036-900, Brazil

autor

Martinho, Alfeu D.

• Computational Modeling Program, UFJF, Juiz de Fora, Minas Gerais 36036-900, Brazil,
• Federal University of Juiz de Fora, Rua José Lourenço Kelmer, Juiz de Fora, Minas Gerais 36036-900, Brazil

autor

Rocha, Caio C.

• Computational Engineering Program, UFJF, Juiz de Fora, Minas Gerais 36036-900, Brazil,
• Federal University of Juiz de Fora, Rua José Lourenço Kelmer, Juiz de Fora, Minas Gerais 36036-900, Brazil

autor

Christo, Eliane da S.

• Department of Production Engineering, Fluminense Federal University, Avenida dos Trabalhadores, Volta Redonda, Rio de Janeiro 27255-125, Brazil,

autor

Goliatt, Leonardo

• Computational Modeling Program, UFJF, Juiz de Fora, Minas Gerais 36036-900, Brazil,
• Federal University of Juiz de Fora, Rua José Lourenço Kelmer, Juiz de Fora, Minas Gerais 36036-900, Brazil

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).

Identyfikatory

DOI

10.1007/s11600-022-00834-3