RAINFALL INTENSITY EQUATIONS FOR THE STATE OF MARANHÃO, BRAZIL - DOI: 10.13083/1414-3984/reveng.v23n5p435-447

Authors

  • Alcinei Ribeiro Campos
  • Glenio Guimarães Santos
  • João Carlos Rocha dos Anjos
  • Diane Cristina Stefanoski
  • Jaurene Moura Fé Moraes

DOI:

https://doi.org/10.13083/reveng.v23i5.597

Keywords:

Chuvas extremas, modelos probabilísticos, período de retorno

Abstract

Studies of spatial and temporal distribution of rainfall are of extreme importance for security in planning and execution of hydraulic projects and environmental conservation, so work to determine the intensity-duration-frequency curves of rainfall are indispensable for the planning and construction of hydraulic works. Currently the state of Maranhão provides little information related to the curves of intensity-duration-frequency of rainfall, so studies are necessary to develop the curves for its various municipalities. In this context the objective of this work was to determine the parameters of the intensity-duration-frequency equation for 163 rainfall stations located in the state of Maranhão. Data were obtained from the National Water Agency database. For adjustment of intensity-duration-frequency curves the rainfall breakdown method was used, considering the probabilistic model of Gumbel for estimating the maximum values in different time durations and return period. Upon acquisition of these values the parameters K, a, b and c of the intensity-duration-frequency curves were adjusted by the least squares method. The parameters K, a, b and c of the intensity-duration-frequency curves show good adjust, with 99.7% of curves presenting r2 greater than 0.98.

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Published

2015-11-24

How to Cite

Campos, A. R., Santos, G. G., Anjos, J. C. R. dos, Stefanoski, D. C., & Moraes, J. M. F. (2015). RAINFALL INTENSITY EQUATIONS FOR THE STATE OF MARANHÃO, BRAZIL - DOI: 10.13083/1414-3984/reveng.v23n5p435-447. Engineering in Agriculture, 23(5), 435–447. https://doi.org/10.13083/reveng.v23i5.597

Issue

Vol. 23 No. 5 (2015)

Section

Agricultural Meteorology

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