The integrative and comprehensive analysis considering the spatial and temporal representation of the hydrological process, such as the distribution of rainfall, land cover and land use, is a challenge for the water resources management. In tropical areas, energy availability throughout the year defines the rainfall distribution and evapotranspiration rate according to vegetation heterogeneity. To quantify water balance in tropical areas including these heterogeneities in the soil-vegetation-atmosphere relationship, we developed a fully distributed hydrological model called the Rainfall Runoff Balance Enhanced Model (RUBEM). The model was developed under a physics-based process structure, using remote sensing data to represent soil-water balance patterns, such as evapotranspiration, interception, baseflow, lateral flow, recharge, and runoff. The calibration procedure was based on nine global parameters. RUBEM could represent the spatio-temporal heterogeneities (soil, land use and land cover (LULC), topography, vegetation, and climate) in three basins in a tropical area. The results showed good adherence between the processes governing the soil-vegetation-atmosphere relationship according to the humidity indicator and the runoff coefficient. Overall, RUBEM can be used to help improve the management and planning of integrated water resources under climate, land use, and land cover changes in tropical regions.

Regional climate models (RCM) are the main tools for climate change impacts assessment in hydrological studies. These models, however, often show biases when compared to historical observations. Bias Correction (BC) are useful techniques to improve climate projection outputs. This study presents a multi-criteria decision analysis (MCDA) framework to compare combinations of RCM with selected BC methods. The comparison was based on the modified Kling-Gupta efficiency (KGE’). The criteria evaluated the general capability of models in reproducing the observed data main statistics. Other criteria evaluated were the relevant aspects for hydrological studies, such as seasonality, dry and wet periods. We applied four BC methods in four RCM monthly rainfall outputs from 1961 to 2005 in the Piracicaba river basin. The Linear Scaling (LS) method showed higher improvements in the general performance of the models. The RCM Eta-HadGEM2-ES, corrected with Standardized Reconstruction (SdRc) method, achieved the best results when compared to the observed precipitation. The bias corrected projected monthly precipitation (2006-2098) preserved the main signal of climate change effects when compared to the original outputs regarding annual rainfall. However, SdRc produced significant decrease in monthly average rainfall, higher than 45% for July, August and September for RCP4.5 and RCP8.5 scenarios.

The present work provides guidelines for application of optimization and simulation models combined, in reservoir system and reservoir operation analysis. Four operation rules based on a series of critical inflows (2003-2017), are proposed for the Cantareira System (CS). The study was developed in three stages. In the first stage, a dynamic programming model (DP) was used to optimize the reservoir releases to the main demands. In the second stage, two artificial neural networks (ANR) were used to obtain the operation rules for SC, based on the results of the first stage. The DP model was solved using CSUDP software, and the ANR model was built and solved using Microsoft Excel. The operation rules were based on the reservoir's storage states or ranges. In the third stage, the operation rules were simulated for the system's historical inflow series, from 1930 to 2017, using the simulation net-flux model AcquaNet. In the last stage, reservoir operation rules were tested for the Cantareira system's historical inflow series, from 1930 to 2017, using the simulation net-flux model AcquaNet. The methodology provides relevant information for the analysis of optimization models and for operation rules in reservoir systems. The comparison of the proposed operation rules provides relevant information on the impacts of volume ranges, and of demand requirement values on long-term reservoir operation. The operation policy 1 shows best performance, providing supply of 33 m³/s to Metropolitan Region of São Paulo (MRSP) during 80% of the period, and with less failures during the historical series.

RESUMO O Sistema Cantareira (SC), um dos maiores sistemas produtores de água do Brasil, enfrentou um período de forte seca entre os anos de 2013 e 2014, o que comprometeu não só o atendimento a 9 milhões de pessoas na Região Metropolitana de São Paulo (RMSP) como também as bacias a jusante. Este estudo tem o objetivo de propor modelos de programação dinâmica (PD) para operação ótima do SC, considerando o período crítico de 2011 a 2015. Nesse contexto, foram formulados um modelo de otimização livre e um modelo de otimização baseado em uma regra de operação por faixas. Ambos os modelos apresentaram desempenho superior à operação realizada quanto ao volume armazenado e quanto ao atendimento às demandas. O modelo de otimização livre apresentou fornecimento médio de 29,40 m3.s-1 para RMSP e de 9,30 m3.s-1 e de 18,70 m3.s-1 para as bacias a jusante, representadas pelos pontos de controle Jb e Jv, respectivamente. A regra de operação por faixas forneceu vazões médias de 28,50 m3.s-1 para a RMSP, de 9,40 m3.s-1 para Jb e de 19,30 m3.s-1 para Jv.