@Article{ZhangCCLMABMSN:2018:SeRaMo,
               author = "Zhang, Rong and Cuartas, Luz Adriana and Carvalho, Luiz Valerio de 
                         Castro and Leal, Karinne Reis Deusdar{\'a} and Mendiondo, Eduardo 
                         M{\'a}rio and Abe, Narumi and Birkinshaw, Stephen and Mohor, 
                         Guilherme Samprogna and Seluchi, Marcelo Enrique and Nobre, Carlos 
                         Afonso",
          affiliation = "{Centro Nacional de Monitoramento e Alertas de Desastres Naturais 
                         (CEMADEN)} and {Centro Nacional de Monitoramento e Alertas de 
                         Desastres Naturais (CEMADEN)} and {Centro Nacional de 
                         Monitoramento e Alertas de Desastres Naturais (CEMADEN)} and 
                         {Centro Nacional de Monitoramento e Alertas de Desastres Naturais 
                         (CEMADEN)} and {Centro Nacional de Monitoramento e Alertas de 
                         Desastres Naturais (CEMADEN)} and {Centro Nacional de 
                         Monitoramento e Alertas de Desastres Naturais (CEMADEN)} and 
                         {Water Resource Systems Research Laboratory} and {Centro Nacional 
                         de Monitoramento e Alertas de Desastres Naturais (CEMADEN)} and 
                         {Centro Nacional de Monitoramento e Alertas de Desastres Naturais 
                         (CEMADEN)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "Season\‐based rainfall–runoff modelling using the 
                         probability\‐ distributed model (PDM) for large basins in 
                         southeastern Brazil",
              journal = "Hydrological Processes",
                 year = "2018",
               volume = "32",
               number = "14",
                pages = "2217--2230",
                month = "July",
             keywords = "2014/2015 water crisis, intra\‐,,annual and interannual 
                         rainfall variability, PDM\‐,,CEMADEN, seasonal calibration, 
                         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 
                         S{\~a}o Paulo and hydroelectric power generation throughout the 
                         entire country. This research considered the upstream basins of 
                         the southeastern Brazilian reservoirs Cantareira (2,279 km2; water 
                         supply) and Emborca{\c{c}}{\~a}o (29,076 km2), Tr{\^e}s Marias 
                         (51,576 km2), Furnas (52,197 km2), and Mascarenhas (71,649 km2; 
                         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 19852015. 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 NashSutcliffe efficiency and 
                         logarithmic NashSutcliffe efficiency were 0.92 and 0.93 for the 
                         calibration period 19842001, 0.87 and 0.88 for the validation 
                         period 20012010, and 0.93 and 0.90 for the validation period 
                         20102015, 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.",
                  doi = "10.1002/hyp.13154",
                  url = "http://dx.doi.org/10.1002/hyp.13154",
                 issn = "0885-6087",
             language = "en",
           targetfile = "zhang_season.pdf",
        urlaccessdate = "27 abr. 2024"
}