Estimation of entropy in Amparo de São Francisco, Sergipe – Brazil
DOI:
https://doi.org/10.33448/rsd-v10i15.22800Keywords:
Energy disorder; Rainfall daily fluctuations; Rain distribution.Abstract
The entropy proposition was used to assess the fluctuations in rainfall, trying to understand or add more rainfall information about the region. Evaluate the fluctuations of daily, monthly and annual rainfall data for Amparo de São Francisco and discuss their water availability, observing the entropy methodology for dry and rainy blocks and their standard deviations, between 1964-2020. The annual daily rainfall series were provided through the rainfall probability distribution function and the annual average of entropy, being calculated for each year through the information of this average. The “bit” unit was used to calculate the element under study, meaning binary digit and the smallest numerical unit accepted were the values of 0 or 1. The yield of information results in a reduction in entropy, and vice-versa. Entropy becomes zero when there is absolute certainty that a certain event will occur, or statistically, when all but one probability in the set is zero.
References
Alvares, C. A., Stape, J. L., Sentelhas, P. C., Gonçalves, J. L. M. & Sparovek, G. (2014). Climate classification map for Brazil. Meteorologische Zeitschrift. 22, 711–728.
Araújo, J. M. F. R. (2017). Inteligência artificial e árvore de decisão utilizando-se da entropia. Universidade Federal de Campina Grande. Departamento de Sistema e Informativa 18p.
Ferreira, D. V. S.; Silva, A. S. A.; Stosic, T.; Menezes, R. S. C.; Irmão, R. A.; Souza, W. S. (2018). Análise da variabilidade espaço temporal da chuva mensal no Estado de Pernambuco utilizando o método entropia de permutação. Revista Brasileira de Biom. v.36, n. 2, p.276-289.
Gleiser, M. (2016). Universo eterno, vida eterna? Para se adaptar ao aumento de entropia, a vida terá que mudar. Brasil Escola. http://Brasilescola.uol.com.br/fisica/a-lei-hubbleexpansão- universo.htm.
Holanda, R. M.; Medeiros, R. M.; França, M. V. (2020). Estimativa da entropia pluvial em Bom Jesus Piauí, Brasil. Research, Society and Development, v.9, n.8, e794986010, 2020. DOI: http://dx.doi.org/10.33448/rsd-v9i8.6010 .
Holanda, R. M & Medeiros, R. M. (2020). Comportamento térmico e a contribuição pluvial em Lagoa Seca, Brasil entre 1981-2019. Research, Society and Development. , v.9, p.695974815 - 30,
IPCC. (2014). Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Working Group II Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Intergovernmental Panel on Climate Change (IPCC).
Marengo, J.; Alves, L. M.; Beserra, E. A.; Lacerda, F. F. (2015). Variabilidade e mudanças climáticas no semiárido brasileiro. Recursos hídricos em regiões áridas e semiáridas. ISBN 978-85-64265-01-1. INSA. Pag. 303 – 422. Campina Grande-PB.
Medeiros R. M. (2020). Estudo Agrometeorológicos para o Estado de Sergipe. Distribuição avulsa. P.132.
Medeiros, R. M.; França, M. V.; Saboya, L. M. F.; Holanda, R. M.; Rolim Neto, F. C.; Araújo, W. P. (2020). Análise estatística das precipitações de Serra Talhada e São Bento do Una - Pernambuco, Brasil. Research, Society and Development. , v.9, p.e3909119954.
Medeiros, R. M.; Silva, V. P. R.; Gomes Filho, M. F. (2015). Aplicação da teoria da entropia no estudo da precipitação em Teresina-PI. Revista de Geografia, v.32, n.2, p.206-218.
Medeiros, R. M. (2019). Variabilidade da entropia pluvial entre os municípios São Bento do Una, Serra Talhada e Caruaru (Pernambuco – Brasil) em período de el niño (a). Revista Equador, UFPI, 8(1), 116–132.
Medeiros, R. M. (2019). Entropia pluviométrica na grande metrópole Recife-PE, Brasil. Journal of Environmental Analysis and Progress. 04(01), 031-047.
Melo, V. S.; Medeiros, R. M. (2016). Entropia da precipitação pluvial no município de Cabaceiras - PB, Brasil. Revista Brasileira de Agricultura Irrigada, v.10, n.5, p.952-964.
Nadarajah, S.; Choi, D. (2007). Maximum daily rainfall in South Korea. Journal of Earth System Science, v. 116, p. 311-320.
Noronha, G. C. D.; Hora, M. D. A. G. M.; Silva, L. P. D. (2016). Rain Anomaly Index Analysis for the Santa Maria/Cambiocó Catchment, Rio de Janeiro State, Brazil. Revista Brasileira de Meteorologia,31(1), 74-81.
Pontes, J. 2015. Determinism, chaos, selforganization and entropy. Anais da Acad. Bra. de Ciências, Rio de Janeiro. P.185.
Silva, V. P. R. (2004). Entropy on climate variability in Northeast of Brazil. Journal of Arid Environments, v.58, n.4, p.575-596.
Souza, R.; Feng, X.; Antonino, A.; Montenegro, S.; Souza, E.; Porporato, A. (2016). Vegetation response to rainfall seasonality and interannual variability in tropical dry forests. Hydrological Processes, v.30, n.20, p.3583-3595.
Westra, S.; Alexander, L. V.; Zwiers, F. W. (2013). Global in creas ingtrends in annual maximum daily precipitation. Journal of Climate, v.26, n.11, p. 3903-3918.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Manoel Vieira de França; Raimundo Mainar de Medeiros; Luciano Marcelo Fallé Saboya; Romildo Morant de Holanda; Fernando Cartaxo Rolim Neto
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.