Teses em Engenharia de Recursos Naturais da Amazônia (Doutorado) - PRODERNA/ITEC

URI Permanente para esta coleçãohttps://repositorio.ufpa.br/handle/2011/4045

O Doutorado Acadêmico inicou-se em 2006 e pertence ao Programa de Pós-Graduação em Engenharia de Recursos Naturais da Amazônia (PRODERNA) do Instituto de Tecnologia da UFPA (ITEC) da Universidade Federal do Pará (UFPA).

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Avaliação de potencial hidrocinético à jusante de centrais hidrelétricas
(Universidade Federal do Pará, 2017-12) HOLANDA, Patrícia da Silva; MESQUITA, André Luiz Amarante; http://lattes.cnpq.br/1331279630816662; SECRETAN, Yves; BLANCO, Claudio José Cavalcante; http://lattes.cnpq.br/8319326553139808
The maximization of the performance of hydropower projects by taking advantage of the remaining energy downstream of dams via the installation of hydrokinetic turbines is feasible. In this context, two case studies of the hydroelectric power plants are presented, one of large Tucuruí in the Tocatins river, Amazonia, and another of medium size Bariri in the Tietê river, in the Southeast of Brazil.In central hydrokinetic projects, the design of the rotor diameter and velocity of the water are fundamental and depend on the depth and velocity of the river, respectively. Thus, the Saint-Venant model has been applied to these areas of studies. The calibration of the model was performed by linear regression of the measured and simulated flow rates for both, resulting in a correlation of 0.99. Validation was performed for a point on the Tocantins river using velocities measured with an acoustic Doppler current profiler (ADCP). The measured velocities are comparable to the velocities simulated by the model. Thus, a power curve was generated for the measured flow rates and the simulated velocities for the point at which the velocities were validated, thus obtaining a correlation of 0.96. This same curve was used for estimates of velocity, calculation of the energy density, and defining a design velocity for Tucuruí HPP equal to 2.35 m/s and Bariri 2.25 m/s. After the design was velocity defined, 10 points were selected Tucuruí and 1 point Bariri for the location of hydrokinetic turbines. The velocities of these points were determined with the same method used for the validation of the velocities. The points were selected based on the channel downstream of the reservoir and at the end of the Bariri dissipation basin, with the largest depth and velocity, which are characteristics favorable for greater power generation. Considering the rivers depth and available manufacturing technology, the rotor diameter was defined for the large study in 10 m and for the medium 2.1 m. After the design velocity was defined, the rotor design was implemented using the blade element method (BEM Blade Element Momentum), allowing for the definition of an installed power curve of the turbine as a function of the river velocity. In terms of generated energy, the 10 turbines can generate 2.04 GWh/year. These numbers demonstrate the potential for utilizing the remaining energy of hydroelectric plants.
Acesso aberto (Open Access)
Desenvolvimento de metodologia para regionalização de curvas de permanência de vazões na Amazônia legal
(Universidade Federal do Pará, 2015-03-30) PESSOA, Francisco Carlos Lira; BLANCO, Claudio José Cavalcante; http://lattes.cnpq.br/8319326553139808
The absence or failure of hydrometric data with long and reliable series, by factors of physical and / or economic order, is one of the main challenges faced in hydrological studies. In order to work around this problem, in this thesis, the application of regionalization method of flow duration curve was proposed. In this context, the main idea was to divide the region of the Amazon in homogeneous regions defined by the methods of hierarchical cluster analysis of Ward and diffuse Fuzzy C-Means, and for each, formulate regional models of flow duration curves. For both methods of the Euclidean distance cluster analysis was used as a similarity measure, and the explanatory variables the flow (drainage area, mean annual precipitation, length and slope of the river), as input data. We obtained four homogeneous regions through the Ward method and 14 regions by Fuzzy C-Means. Duration curves were constructed for each of the 214 gauged stations distributed in their respective regions, and calibrated according to 6 mathematical models (linear, power, exponential, logarithmic, quadratic and cubic). For each homogeneous region formed by cluster analysis methods, a regional model of flow rates of duration curves using multiple regression analysis was formulated, relating the parameters of the best model calibrated with the physical characteristics (drainage area, length and slope of the river) and climate (average annual precipitation) basins. The obtained regional models were validated by the method Jack-Knife cross validation. The performance indices found – values of NASH ≥ 0,75 in over 62% of cases, standing in the performance range from acceptable to good – showed that the Fuzzy C-Means method was the most suitable for the formation of homogeneous regions of flow. The regional models developed for each of the regions formed, are presented as a good option for modeling of flow duration curve for medium and small basins without flow data in the Amazon region.
Acesso aberto (Open Access)
Metodologia para estimativa do valor da externalidade perda na atividade pesqueira em usinas hidrelétricas
(Universidade Federal do Pará, 2019-04-22) CARVALHO, Evelyn Gabbay Alves; BLANCO, Claudio José Cavalcante; http://lattes.cnpq.br/8319326553139808; DUARTE, André Augusto Azevedo Montenegro; http://lattes.cnpq.br/1135221873341973
Acesso aberto (Open Access)
Modelagem chuva-vazão-produção de sedimentos via problemas inversos
(Universidade Federal do Pará, 2023-10-05) TORRES FALCÓN, Cindy; ESTUMANO, Diego Cardoso; http://lattes.cnpq.br/5521162828533153; https://orcid.org/0000-0003-4318-4455; BLANCO, Claudio José Cavalcante; http://lattes.cnpq.br/8319326553139808; https://orcid.org/0000-0001-8022-2647
The development of mathematical models and direct methods has made it possible to predict hydrological phenomena such as rainfall-runoff-sediment yield. In order to complement the simulation model, inverse problems can be used to determine the properties of these phenomena and estimate parameters that cannot be measured directly. Therefore, this study was carried out in a small catchment in the Amazon with precipitation data and parameters estimated using the Kineros2 (K2) / direct model (DM). The study proposes solutions to the inverse problem (IP) characterized by the rainfall-runoff-sediment yield phenomenon for events with scarce data, with the aim of estimating the inflow rate, estimating the physical parameters, the runoff depth and the sediment yield of the basin analyzed. The sediment yield data comes from the sediment gauge station in the small catchment. For a more precise and detailed analysis of the model's behavior, combinations of information from observations and the K2 model were also carried out simultaneously with IP. The main scientific contribution is the application of the inverse problem method (Bayesian inference together with a Fourier series) to estimate the parameters of the kinematic wave model and the mass balance, and to estimate the runoff depth and sediment yield for a small watershed in the Amazon. The results showed a good fit between the observed and predicted data via IP, as Nash-Sutcliffe coefficients above 0.70 and RMSE between 0.27 and 1.99 were obtained in the calibration and validation of the rainfall-runoff-sediment yield model. The simulation of the runoff depth and sediment yield showed a 95% degree of reliability, which is consistent with the observed data.
Acesso aberto (Open Access)
Modelagem numérica-experimental da produção de sedimentos de pequenas bacias hidrográficas da Amazônia
(Universidade Federal do Pará, 2021-04-22) BARBOSA, Ana Júlia Soares da Silva; BLANCO, Claudio José Cavalcante; http://lattes.cnpq.br/8319326553139808; https://orcid.org/0000-0001-8022-2647
Erosion is a process of direct impact in urban and rural environments. The understanding of this process requires the use of models and techniques of geoprocessing and field, for approximate estimation of the realized one, since it is a phenomenon with many variables to be taken into account. For the present study, two models were used to generate data in a small Amazon basin. The USLE (universal soil loss equation) and also the modified MUSLE version. For both models, the common factors (K, LS, C and P) were determined. For USLE, the calibration occurred for rain erosivity, which is the differential factor of this model. After USLE application with calibrated R factor, the model was applied to the study area with an average soil loss of 1.99 ton. ha-1.year-1, for a period of 21 years. For MUSLE, the differential variables are the hydrological variables (Q and qp) were determined by analyzing the hydrographs observed with the aid of a digital filter. Two methods of calibration and validation have been done for MUSLE. Method 1 calibrated the factors ɑ and b, with sediment production data measured from 62 flood events from 2012 to 2014. The values found for factors ɑ and b were equal to 19.90 and 0.60, respectively. MUSLE was validated with sediment production data measured from 62 flood events in the years 2014 and 2015. The validated MUSLE equation represented in a satisfactory way, in more than 70%, the data of soil loss observed in the hydrographic basin of the Igarapé da Prata. Method 2 calibrated only the value of a, using the solid discharge curve with potential regression for the years 2012 and 2013, which showed R² of 0.70 and 0.68, respectively. The value of ɑ obtained was 17.25, and was applied to MUSLE, keeping the value of b at 0.56, the original value of the model. The validation for the latter method proved to be adequate, with an R² of 0.69. These results validate the empirical models for the region with experimental activities, which corroborates for the production of sediment information in the Amazon region, as a way of maturing and the search for new research, for the understanding of the impacts arising from the transport of soil between areas and in the water environment.
Acesso aberto (Open Access)
Modelo de gerenciamento de usos múltiplos da água: um estudo de caso para a bacia hidrográfica do rio Tapajós
(Universidade Federal do Pará, 2016-02) FIGUEIREDO, Nelio Moura de; BLANCO, Claudio José Cavalcante; http://lattes.cnpq.br/8319326553139808
This work deals with a model for management of multiple uses of water, for the mitigation of conflicts of use related to the operation of reservoir systems in hydroelectric power plant of water catchment area. The model SOUMA – "system optimization of multiple uses of water", which consists of a stochastic optimization model based on nonlinear programming, was developed and structured in GAMS (General Algebraic Modeling System) with the use of solver MINOS. The SOUMA is composed of two modules. The first is a module for forecasting of water levels, which consists of a stochastic model of type ARIMA (Auto Regressive Integrated Moving Average). The second is a module for forecasting of streamflow, which is a stochastic model of rainfall-streamflow the RNA type. The ARIMA model calibration and validation presented average R² above 0.93 and RMSE below 0.08, capturing in a satisfactory manner the behavior of water levels. The rain-flow model that was used in the composition of influent flow to the reservoir, with the use of RNA architecture, presented average R² 0.954 and of 0.098 RMSE. The SOUMA model was applied to Tapajós River basin for the future hydroelectric power plant of São Luiz do Tapajós, Itaituba, PA. Six scenarios were created to be used as parameters in optimizing and mitigation of conflicts. The reservoir tributaries streamflow were obtained and simulated for dry, medium and moist hydrological scenarios and for El Niño, La Niña and Neutral climatic scenarios. For the power generation and navigation depth uses, considering the tributaries streamflow of the dry, medium and moist hydrological scenarios, the SOUMA showed, in relation to the reference levels of the low, medium and high navigation scenarios, the occurrence of depths below the minimum, for generations averages below 2,411 MW, 2,939 MW and 3,586 MW, respectively. For power generation and cargo capacity, considering the tributaries streamflow of the dry, medium and moist hydrological scenarios, the SOUMA showed, in relation to the low, medium and high reference levels of the navigation scenarios, that generations averages above 2,869 MW, 3,508 MW and 4,740 MW, respectively, do not generate earnings of cargo capacity and that medium generations below 1,344 MW, 2,056 MW and 1,622 MW, respectively, make the river transport of cargo infeasible. For power generation and flood dimension, considering the tributaries streamflow of the dry, medium and moist hydrological scenarios, the SOUMA showed, in relation the reference levels low, medium and high of the flood control, the occurrence of floods downstream to generations above average 4,978 MW, 6,057 MW and 7,390 MW, respectively. Consumptive withdrawals are meaningful only in the period from June to October. Considering the monthly average consumptive demands (145 m ³/s), to tributaries streamflow of the dry, medium and moist hydrological scenarios, the SOUMA showed a monthly loss in power generation of 50 MW, 47 MW and 44 MW, respectively. The measured results show that the models developed are important tools to operational optimization of reservoir systems with multiple uses, allowing the optimization of generations and defluente flow in the hydroelectric power plant of water catchment area, in periods of flood and drought and large energy demands, with maintenance of navigation conditions downstream from dams, through sustainable operational simulations that minimize usage conflicts.
Acesso aberto (Open Access)
Modelo de inteligência artificial para estimativa do desmatamento considerando a rede de transporte rodoviário do estado do Pará
(Universidade Federal do Pará, 2022-01-10) NEVES, Patrícia Bittencourt Tavares das; BLANCO, Claudio José Cavalcante; http://lattes.cnpq.br/8319326553139808; https://orcid.org/0000-0001-8022-2647; DUARTE, André Augusto Azevedo Montenegro; http://lattes.cnpq.br/1135221873341973; https://orcid.org/0000-0003-4586-1587
Since the decade of 1950s the Amazonian and Brazilian transportation complex prioritized the model of road transport. Past studies point that the regular roadway system that is integrated to a clandestine roadway complex is strongly related to the Amazon forest deforestation. Thus, in this work we performed a quantitative analysis of the variables related to the process of deforestation of the Amazon forest, a natural resource of great environment and economic significance, and the socioeconomic development of the region in the period between 1988 and 2018. The geographical study area is the state of Pará, located in the Oriental Amazon, the second largest state of Brazil in territorial extension and the most devastated. We used machine learning in the modeling of the quantitative variables related to the transportation infrastructure, social variables and economic variables, e.g., the devastated area. The random forest model presented the best performance with the generated function (using least squares method). It was estimated the devastated area for the years of 2020, 2030, 2040 and 2050. Sensitivity analysis was used to evaluate the devastated area after the implementation of the roads BR-163 and BR-210 in the north of Pará. The results show that given the current scenario the devastation tends to continue intensively in the next three decades, with a 25.77% increase over the current region albeit with decreasing ten-year rates of forestation loss, and the estimation of the deforested area caused by the implementation of federal roadway networks goes from 4,703.43 km2 to 6,567.48 km2 .
Acesso aberto (Open Access)
Regionalização e estimativa de chuvas do estado do Pará
(Universidade Federal do Pará, 2014-04-25) GONÇALVES, Mariane Furtado; BLANCO, Claudio José Cavalcante; http://lattes.cnpq.br/8319326553139808
In Amazon region, a factor which prevents the most comprehensive knowledge of water resources is the lack of hydrological data (flow and precipitation) of small and medium-sized watersheds. This is mainly due to size of the region, which increases the costs of implementation and operation of the network. In this context, this work aims to develop a model of regionalization and estimated rainfall for the state Pará For this, we applied a methodology for delineation of homogeneous regions of precipitation through the cluster analysis was then determined probability of rain for some point rainfall homogeneous region obtained with the cluster analysis by applying probability functions, and finally was given estimates of rainfall heights, using multiple. For every step we used annual and monthly averages precipitation of a time series of 31 years (period 1960-1990), obtained at the Center for Climatic Research, Department of Geography, University of Delaware, Newark site, DE, USA. Among the analyzed years, years were selected with the occurrence of El Niño and La Niña. Using the agglomerative hierarchical Ward method, having as similarity measure the Euclidean distance for annual and monthly rainfall averages six homogeneous regions of precipitation were found, except for monthly averages for rainfall series with the occurrence of El Niño and La Niña, who has four and five homogeneous regions, respectively. After the definition of homogeneous regions, probability models (Normal, Gumbel and Exponential) were fitted to determine the heights of the three sequences of rainfall time series, applied the chi-square test for this check. After the calibration step to annual rainfall, it was found that the model is best fit normal distribution the probability of exceedance observed, since average monthly precipitation for the Gumbel distribution model got better grip frequencies of exceedance. The above models were validated using the rainfall series of 12 stations of the Agência Nacional de Água (ANA), considered as target stations. At this stage, it was observed that to mean annual rainfall occurred adherence of the data to all the rainfall stations targeted because they presented the results of applying the chi-square test less than 3.84 (for normal distribution functions). And it was also found that for average monthly rainfall, there was adherence of the data to all the rainfall stations target. To simulate rainfall heights were tested for calibration models of power, according to Power and Linear model by means of multiple regression. As a criterion of performance models, the percentage relative error was used. For time series containing series every year and with the occurrence of La Niña, the model showed a lower relative. As for series with the occurrence of El Niño, the model of power had minor errors. As for the probabilistic models, the calibration results of the multiple regression models were validated with the use of rainfall stations of the ANA. In the validation step for series containing every year the percentage errors ranging from 0.2 to 39.2%, as when used in El Niño years there has been an increase in error ranging from 1.9 to 54.8%, and La Niña years from 8.5 to 55.9%. Although some estimates have had considerable errors, above 50%. The results of applying this methodology are important for a better understanding of rainfall in the state of Pará and the Amazon, and can serve as a tool for better planning and management of water resources in the region.

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