Navegando por Assunto "Regionalization"

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Acesso aberto (Open Access)
Contribuição à Regionalização de Vazão Mínima de Referência na Amazônia Legal
(Universidade Federal do Pará, 2016-10-25) BARROS, Calina Grazielli Dias; PESSOA, Francisco Carlos Lira; http://lattes.cnpq.br/8031687016215046; BLANCO, Claudio José Cavalcante; http://lattes.cnpq.br/8319326553139808
Studies aimed at knowledge flows in ungauged sites, are of great importance in hydrology, because almost always the hydrometric network does not cover all areas of interest. Therefore, it is necessary to use techniques that allow the transfer of local information monitored for ungauged sites. In this context, this paper proposes mathematical models to determine the remaining flow in the Amazon, using the regionalization method of flow. The methodology was based on the minimum flow Q95% obtained from the flow duration curve plotted based on the Weibull equation, in addition to morphoclimatic characteristics of river basins, such as the drainage area (A), average annual precipitation (P) and the river length (L). The data used for regionalization belong to six hydrologically homogeneous groups analyzed in the study. With this information, and in order to define which explanatory variables (A, P and L) would be part of the models to be applied, the multi-colinearity test was performed. Thus, taking the result of the previous test, the mathematical models of regionalization of the minimum reference flow Q95% were constructed through multiple regression models (linear, potential, exponential and logarithmic).In the first analysis, the performance values (mean absolute percentage errors, determination coefficients, adjusted coefficient of determination) were unsatisfactory. For this reason, it was chosen to divide the hydrologically homogeneous groups according to the interval with the same order of magnitude of areas and flows. In this way, the results obtained in the adjustment of the models presented a better performance, which can be verified by the average absolute error below 13.78% in all groups. The models that obtained the best performance were selected for the validation, observing in this way, that the linear model was the one that presented the best results for nine of the groups and subgroups tested, standing out also the potential and logarithmic models, that simulated six of the subgroups each.Thus, from the regional equations that presented good results, both in the adjustment and in the validation, we can obtain the flow rate Q95%, in a basin without flow data according to the homogeneous regions or groups determined in the study, having as data of The physical and climatic characteristics of this basin.
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.