Samuellson Lopes Cabral

Avaliação de desempenho dos modelos do CMIP5 quanto à representação dos padrões de variação da precipitação no século XX sobre a região Nordeste do Brasil, Amazônia e bacia do Prata e análise das projeções para o cenário RCP8.5

The global models of the Coupled Model Intercomparison Project Phase 5 (CMIP5) are evaluated over Northeast Brazil (NEB), the Amazon region and La Plata Basin regarding the representation of precipitation for the period 1901 to 1999. Furthermore, the projections of precipitation for scenario RCP8.5 for the XXI century are analyzed. The evaluation is performed using data from the Climatic Research Unit (CRU) and 20th Century Reanalysis V2 reanalysis of the National Oceanic and Atmospheric Administration (NOAA). The models are classified using indices that indicate how patterns of seasonal, interannual and decennial variation are represented. The evaluation identified CANESM as the best models for NEB, whereas for La Plata Basin, the French model CNRM_CM5_r1i1p1 runs were superior. For the Amazon region, the model GISS Model-E2-R_r1i1p1 exhibited the best performance. Over NEB, most models indicate largest changes during the pre-season, but differ on the sign of the anomaly. In the Amazon region the models suggest greater chances of rainfall reduction up to 20.5%, 33.6 and 39.5% for the periods 2010-2039, 2040-2069 and 2070-2099, respectively. Over the La Plata region, the, ensemble projects few changes for the 2010 to 2039 period .

Monthly streamflow forecast for National Interconnected System (NIS) using Periodic Auto-regressive Endogenous Models (PAR) and Exogenous (PARX) with climate information

This study aims to find a seasonal streamflow forecast model simultaneous to all stations of SIN using periodic autoregressive models with exogenous variables (PARX) using climate indexes. Comparing the results from PAR and PARX Models, this research analyzes the impact on forecasts by using climate information. The proposed models for streamflow forecast has been carried out using natural streamflow data from Operador Nacional do Sistema (ONS) and statistical techniques (such as multiple linear regression and stepwise method to choose explanatory variables). On 27 climate indexes utilized, 4 of them are suggested in this work. The performance analysis methodology is based on the ELECTRE method further the NASH coefficient, the mean absolute percentage error, the multi-criteria distance and correlation. Forecasts with one month lead, the PAR models present better results for most stations of SIN within seasons DJF, MAM, and JJA, while for SON season there is greater efficiency from PARX model. This kind of model shows better performance during dry season in the basins at Northern Brazil – Amazonas and Araguaia-Tocantins; Central-Eastern Brazil – Eastern Atlantic and the most rivers located in the Paraná basin.

Uncertainties and errors flow estimate using hydrological modelling and precipitation by RADAR

Esse artigo apresenta uma analise das incertezas e erros do modelo SCS-CN do Hydrologic Engineering Center - Hydrologic Modeling System (HEC-HMS), para eventos hidrologicos com dados de precipitacao observada e estimada por RADAR na bacia do rio Sao Miguel em Alagoas, que controla uma area de 296 km². Foram utilizados dados fisiograficos para as estimativas iniciais dos parâmetros do SCS-CN. Em seguida, utilizando medidas simultâneas de precipitacao e vazoes observadas, os parâmetros foram calibrados. Utilizando-se dados independentes, os parâmetros calibrados foram validados. O coeficiente de desempenho mostrou valores de Nash-Sutcliffe de 0,93 na fase de calibracao e valores entre 0,81 a 0,87 nas fases de validacao. Em seguida, o modelo foi utilizado para eventos hidrologicos passados, usando dados de precipitacao estimada por RADAR. Obteve-se coeficientes de Nash-Sutcliffe entre 0,75 a 0,79. O SCS-CN com as estimativas de precipitacao pelo RADAR representou de forma adequada o tempo das vazoes de pico, entretanto, subestimou a magnitude do pico com erros de ate 26% em alguns eventos. A metodologia mostrou-se satisfatoria para a bacia em estudo e pode ser uma ferramenta util para aplicacao em outras bacias hidrografica prevendo possiveis inundacoes.

O Intervalo de Tempo para uma Máxima Previsiblidade da Precipitação sobre o Semiarido Brasileiro

This paper presents an evaluation of the climate forecast in the upper valley of the river Jaguaribe, State of Ceara-Brazil. The forecast was performed using the global circulation model (ECHAM 4.5) boundary conditions to the regional model (RAMS 6.0). The model simulates the monthly scale rainfall in order to aggregate it in the regional rainy season (January to June). We used the Heidke Skill Score (HSS) as a metric of forecast skill. The simulations were performed for the wet season, covering the period from 1979 to 2010. The HSS was calculated for intervals of 1, 2, 10, 15, 21, 30, 45, 60, 120 and 180 days in order to find the Time Interval of Maximum Predictability (ITEMP). The obtained curve, HSS vs. time, presented a maximum HSS of 0.62 for 45 days. This result indicates that climate prediction even with its limitations (initial data of soil moisture and used parameterization) could be an important tool for the reservoir management in Brasilian Semiarid region.

Coupling the atmospheric model RAMS 6.0 /ECHAM 4.1 to hydrologic model SMA/HMS for operating a reservoir in Brazil’s semiarid

The planning and the efficiency of water resources are subject to the uncertainties of the input data of climate and hydrological models. Prediction of water inflow to reservoirs that would help decision making for the various water uses, contain uncertainties fundamentally the initial conditions assumed in the modeled processes. This paper evaluates the coupling of a regional atmospheric model with a hydrological model to make streamflow forecast for seasonal operation of Orós reservoir, Ceará State, Brazil. RAMS model, version 6.0, was forced by the ECHAM 4.5 atmospheric general circulation model over Alto Jaguaribe basin to obtain the rainfall data. To remove biases in the simulated precipitation fields was applied the probability density function (PDF) correction on them. Then the corrected precipitation data were inserted in the hydrologic Soil Moisture Account (SMA) model from the Hydrologic Modeling System (HEC-HMS). For SMA calibration, it was used the Nash-Sutcliffe objective function. Finally, decisions to water release from the Orós were evaluated using the Heidke Skill Score (HSS). The SMA model showed a satisfactory performance with Nash-Sutcliffe values of 0.92 (0.87) in the calibration (validation) phase, indicating that it is a rainfall runoff model alternative. For decisions in releasing water from the Orós reservoir, using climate predictions, obtained HSS = 0.43. The results show that the simulated rainfall coupled with a hydrological model is able to represent the hydrological operation of Brazilian semiarid reservoir.