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

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 São Paulo and hydroelectric power generation throughout the entire country. This research considered the upstream basins of the southeastern Brazilian reservoirs Cantareira (2,279 km 2 ; water supply) and Emborcação (29,076 km 2 ), Três Marias (51,576 km 2 ), Furnas (52,197 km 2 ), and Mascarenhas (71,649 km 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-touse model, and it will facilitate early decision making and implement adaptation measures relating to disaster prevention for reservoirs with large-sized upstream basins. KEYWORDS 2014/2015 water crisis, intra-annual and interannual rainfall variability, PDM-CEMADEN, seasonal calibration, southeastern Brazil

Secas E Os Impactos Na Região Sul Do Brasil

“…O SSFI mostrou seca excepcional desde janeiro de 2020, de acordo com a classificação da Tabela 2. Observa-se que, o segundo período mais crítico para a bacia da UHE Itaipu foi 2014/2015, coincidente com a grande seca da região Sudeste (COELHO et al, 2015;CUNHA et al, 2019a;DEUSDARÁ-LEAL et al, 2020;NOBRE et al, 2016;ZHANG et al, 2018). No período de junho de 2001 a setembro de 2004 as séries de SPI e SSFI não apresentam correlação (r = -0,26), uma vez que os índices indicaram, respectivamente, período de neutralidade e de seca.…”

Doce River Large-Scale Environmental Catastrophe: Decision and Policy-Making Outcomes

“…Intra-annual rainfall variability is remarkably high in the centre and southeastern Brazil. According to Zhang et al (2018) around 80% of annual rainfall occurs in the SE wet season (November to March), with 68% of annual river discharges produced between December to April. Annual rainfall variability has been 0.6 to 1.4 times the climatological mean, with 0.3 to 2.0 times the river discharge mean.…”

Linkages between Water and Forests in South American Watersheds under Restoration

“…Moreover, several river basins were selected for hydropower production, representing ca. 87% of all the energy demand in Brazil [40].…”

“…Regarding Table 1, drainage areas of reservoirs Emborcação, Três Marias, Furnas, and Mascarenhas, which are essential for hydroelectric power generation, irrigation, and water supply, have less than 30% of native forest cover [40]. The Emborcaçao reservoir is the most affected with high deforestation rates (only 6% of the original cover remains).…”