poster - International Conference of Agricultural Engineering

Table 3 - Regression models that best adjusted to the minimum flow characteristics obtained
settings
Flow (*) Region Model Equation r²a E.P. F 0.05
Q 7,10
Q 90
Region I Potencial 0,72 0,313 3,5x10 -4
Region II Potencial 0,82 0,491 0,3x10 -4
Region III Potencial 0,74 0,455 4,8x10 -4
Region IV Potencial 0,92 0,367 0,0
Region I Potencial 0,84 0,228 0,2x10 -4
Region II Potencial 0,83 0,367 0,2x10 -4
Region III Potencial 0,75 0,364 4,2x10 -4
Region IV Potencial 0,93 0,330 0,0
Region I Potencial 0,81 0,259 0,5x10 -4
Region II Potencial 0,82 0,453 0,4x10 -4
Q 95
Region III Potencial 0,74 0,389 0,4x10 -4
Region IV Potencial 0,92 0,345 0,0
(*) Flows in m³ s -1 , A d in km² and P sc in mm.
Analyzing the Table 3 it can be observed that:
• The regression model that best fits the data flow has the potential. The same
behavior for the regional equations was found by Ribeiro et al. (2005) and Marques et al.
(2009) for the Doce river basin;
• The most important independent for the study was the catchment area (A d ) follow
then the average rainfall in rainy season (P sc );
• The regional equations presented for the four hydrologically homogeneous regions
defined by the methodology proposed in this study had coefficients of determination higher
than 0.70, standard error of estimate less than 0.5 and a significance level of 5% by F test.
4. CONCLUSIONS
Based on the results obtained in this paper, we can conclude that:
• A principal component analysis showed satisfactory results for the exclusion of some
variables representative for the identification of hydrological homogeneous regions.
• The first two principal components, Y1 and Y2, were responsible for 77.92% of the
total variation of the data.
• The similarity matrix of Mahalanobis and method of grouping the farthest neighbor
showed good results in the identification of hydrologically homogeneous regions for all flow
rates studied.
• We obtained four hydrologically homogeneous regions for all studied flow characteristics.
• The regionalization of equations obtained by multiple regression analysis for the
minimum characteristics flow were considered satisfactory, validating the methodology
presented in this study.
• The proposed methodology for identifying the number of homogeneous regions
showed good results, allowing the elimination of subjectivity in the identification of
hydrologically homogeneous regions.
5. ACKNOWLEDGEMENTS
The authors thank the Coordination of Improvement of Higher Education CAPES), the
Foundation for Research Support of Minas Gerais (FAPEMIG), the Viçosa Federal University
(UFV) and the National Council for Scientific and Technological Development (CNPq ), for
financing this work.
6. REFERENCES
ASSANI, A. A.; CHALIFOUR, A.; LÉGARÉ, G.; MANOUANE, C.; LEROUX, D. (2009).
Temporal regionalization of 7-day low flows in the St. Laurence watershed in Quebec
(Canada). Water Resources Management, v. 25, p. 3559-3574.
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