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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Season-based rainfall-runoff modelling using the probability-distributed model (PDM) for large basins in southeastern Brazil

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Author(s):
Zhang, Rong [1] ; Cuartas, Luz Adriana [1] ; de Castro Carvalho, Luiz Valerio [1] ; Deusdara Leal, Karinne Reis [1] ; Mendiondo, Eduardo Mario [2, 1] ; Abe, Narumi [2, 1] ; Birkinshaw, Stephen [3] ; Mohor, Guilherme Samprogna [1] ; Seluchi, Marcelo Enrique [1] ; Nobre, Carlos Afonso [1, 4]
Total Authors: 10
Affiliation:
[1] CEMADEN Natl Ctr Monitoring & Early Warning Nat D, Estr Doutor Altino Bondesan 500, Sao Jose Dos Campos, SP - Brazil
[2] Univ Sao Paulo, EESC, Sao Carlos Sch Engn, Sao Carlos, SP - Brazil
[3] Newcastle Univ, Sch Civil Engn & Geosci, Water Resource Syst Res Lab, Newcastle Upon Tyne NE1 7RU, Tyne & Wear - England
[4] Natl Inst Space Res CCST INPE, Earth Syst Sci Ctr, Sao Jose Dos Campos, SP - Brazil
Total Affiliations: 4
Document type: Journal article
Source: Hydrological Processes; v. 32, n. 14, p. 2217-2230, JUL 1 2018.
Web of Science Citations: 0
Abstract

Southeastern Brazil is characterized by seasonal rainfall variability. This can have a great social, economic, and environmental impact due to both excessive and deficient water availability. During 2014 and 2015, the region experienced one of the most severe droughts since 1960. The resulting water crisis has seriously affected water supply to the metropolitan region of SAo Paulo and hydroelectric power generation throughout the entire country. This research considered the upstream basins of the southeastern Brazilian reservoirs Cantareira (2,279km(2); water supply) and EmborcacAo (29,076km(2)), Tres Marias (51,576km(2)), Furnas (52,197km(2)), and Mascarenhas (71,649km(2); hydropower) for hydrological modelling. It made the first attempt at configuring a season-based probability-distributed model (PDM-CEMADEN) for simulating different hydrological processes during wet and dry seasons. The model successfully reproduced the intra-annual and interannual variability of the upstream inflows during 1985-2015. The performance of the model was very satisfactory not only during the wet, dry, and transitional seasons separately but also during the whole period. The best performance was obtained for the upstream basin of Furnas, as it had the highest quality daily precipitation and potential evapotranspiration data. The Nash-Sutcliffe efficiency and logarithmic Nash-Sutcliffe efficiency were 0.92 and 0.93 for the calibration period 1984-2001, 0.87 and 0.88 for the validation period 2001-2010, and 0.93 and 0.90 for the validation period 2010-2015, respectively. Results indicated that during the wet season, the upstream basins have a larger capacity and variation of soil water storage, a larger soil water conductivity, and quicker surface water flow than during the dry season. The added complexity of configuring a season-based PDM-CEMADEN relative to the traditional model is well justified by its capacity to better reproduce initial conditions for hydrological forecasting and prediction. The PDM-CEMADEN is a simple, efficient, and easy-to-use model, and it will facilitate early decision making and implement adaptation measures relating to disaster prevention for reservoirs with large-sized upstream basins. (AU)

FAPESP's process: 14/50848-9 - INCT 2014: INCT for Climate Change
Grantee:Jose Antonio Marengo Orsini
Support type: Research Program on Global Climate Change - Thematic Grants