DECADAL ANALYSIS OF TEMPORAL VARIABILITY IN RAINFALL TRENDS IN OGBOMOSO

Authors

  • Kamaldeen Olasunkanmi Suleman Department of Physics, School of Basic Sciences, Nigeria Maritime University, Okerenkoko, P.M.B. 1005, Warri, Delta State, Nigeria
  • Lukman Ayobami Sunmonu Department of Pure and Applied Physics, Faculty of Pure and Applied Sciences, Ladoke Akintola University of Technology, PMB 4000, Ogbomoso, Oyo state. Nigeria
  • George Atilade Àlàgbé Department of Pure and Applied Physics, Faculty of Pure and Applied Sciences, Ladoke Akintola University of Technology, PMB 4000, Ogbomoso, Oyo state. Nigeria
  • Akeem Lawal Sheu Department of Physics, Emmanuel Alayande College of Education, Oyo, Oyo State, Nigeria
  • Suliat Kemi Rasaq Department of Pure and Applied Physics, Faculty of Pure and Applied Sciences, Ladoke Akintola University of Technology, PMB 4000, Ogbomoso, Oyo state. Nigeria

DOI:

https://doi.org/10.4314/jfas.1214

Keywords:

Rainfall, Trend, variability, decadal, Mann-Kendall

Abstract

Ten-year (2009-2018) monthly rainfall data was obtained from the Nigerian Meteorological Agency (NIMET). The data was processed and analysed using OriginPro 8.5 software. Statistical tools such as standard deviation and Coefficient of Variation (CV) were used for data presentation while analyses were done using the Mann-Kendall and Sen’s slope of linear regression to examine variations across the months and years. Results revealed higher values around July and September while lower values were recorded around December and January. Seasonal variability shows a remarkable increasing trend with the exception of post-wet which recorded an insignificant downward trend. The Mann-Kendall and Sen’s slope estimator analyses revealed both downward and upward trends in rainfall the study period and the changes are strongly marked for certain years and less for others. This result would contribute significantly to the effective management and sustainable development of the social economic activities which are heavily rain-dependent, within the study area.

Downloads

Download data is not yet available.

References

Merabtene T, Siddique M, Shanableh A. Adv. Meteorol. 2016, 1-13. doi: 10.1155/2016/6206238.

IPCC, “Climate Change 2007 - Impacts, Adaptation and Vulnerability: Contribution ofWorking Group II to the Fourth Assessment Report of the Intergovernmental Panel, Genebra, Suíça.,” Cambridge University Press, New York, USA., 2007.

Philandras C.M., Nastos P.T, Kapsomenakis J, Douvis K.C, Tselioudis G, and Zerefos C.S., Nat. Hazards Earth Syst. Sci. 2011., 11(12), 3235-3250. doi: 10.5194/nhess-11-3235-3250.

Kumar V, Jain S K. Quat. Int. 2010, 212(1), 64-69. doi: 10.1016/j.quaint.2009.08.006.

Partal T, Kahya E. Hydrol. Process. 2006, 20(9), 2011-2026. doi: 10.1002/hyp.5993.

Taxak A K, Murumkar A R, Arya D S. Weather Clim. Extrem. 2014, 4, 50–61, doi: 10.1016/J.WACE.2014.04.005.

Osborn T J, Hulme M, Jones P D, Basnett T.A. Int. J. Climatol. 2000, 20(4), 347-364. doi: 10.1002/(SICI)1097-0088(20000330)20:4<347::AID-JOC475>3.0.CO;2-C.

Cooper P J M, Coe R. Experimental Agriculture 2011, 47(2.), 179-184. doi: 10.1017/S0014479711000019.

Challinor A, Wheeler T, Garforth C, Craufurd C.P, Kassam A. Clim. Change 2007, 83(3), 381-399. doi: 10.1007/s10584-007-9249-0.

Cooper P, Rao K P C, Singh P, Dimes J, Traore P C S, Rao K, Dixit P, and Twomlow, S J. Farming with current and future climate risk: Advancing a 'Hypothesis of Hope' for rainfed agriculture in the semi-arid tropics. J. SAT Agric. Res., 2009, 7:1-19.

Rosell S. Appl. Geogr. 2011, 31(1), 329-328. doi: 10.1016/j.apgeog.2010.07.005.

Oloruntade A J, Mogaji K O, Imoukhuede O B. Ruhuna J. Sci. 2018, 9(2), 127, 2018, doi: 10.4038/rjs.v9i2.40.

Abaje I B, Ishaya S, Usman S U. An Analysis of Rainfall Trends in Kafanchan , Kaduna State , Nigeria,” Res. J. Environ. Earth Sci. 2010, 2, 89–96.

Diagi B, Environ. Earth Sci. Res. J., 5,(3), 2018, doi: 10.18280/eesrj.050301.

Itiowe T, Hassan S M, Agidi V A. Curr. J. Appl. Sci. Technol. 2019, 34(4), 1-7. doi: 10.9734/cjast/2019/v34i430139.

Onyenechere E, Azuwike D, Enwereuzor A . African Res. Rev. 2011, 5(5), 223-241. doi: 10.4314/afrrev.v5i5.18.

Akinyemi O, Faweya O, Jide-Ashaolu E, Olajide Talabi F, Babatope Ayodele M, and Toriola A. L. J Hum Ecol. 2021, 74( 3), 1–7, doi: 10.31901/24566608.2021/74.1-3.3307.

Bibi U M, Kaduk J, Balzter H. Climate, 2(3), 206–222. doi:10.3390/cli2030206

Ukhurebor K, Abiodun I J. Appl. Sci. Environ. Manag. 2018, 22(4), 511–518. doi: 10.4314/jasem.v22i4.13.

UN, “Nigeria Population,” World Population Review, 2020. .

Ogunkan D V, Jelili M O. The influence of land use on the spatial variation of begging in Ogbomoso, Nigeria,” J. Geogr. Reg. Plan. 2013, 3(4), 73–83.

Sen P K. J. Am. Stat. Assoc. 1968, 63(324), 1379-1389. doi: 10.1080/01621459.1968.10480934.

Lettenmaier D.P, Wood E.F, Wallis J.R. J. Clim.1994, 7(4), 586-607. doi: 10.1175/1520-0442(1994)007<0586:HCTITC>2.0.CO;2.

Yue S, Hashino M. Theor. Appl. Climatol. 2003, 75(1), 15-27. doi: 10.1007/s00704-002-0717-1.

Mann H B. Econometrica 1945, 13(3), 245-259. doi:10.2307/1907187

Kendall M G, Biometrika 1957, 44(1/2), 298. doi:10.2307/2333282

Downloads

Published

2022-09-01

How to Cite

SULEMAN, K. O. .; SUNMONU, L. A. .; ÀLÀGBÉ, G. A. .; SHEU, A. L.; RASAQ, S. K. DECADAL ANALYSIS OF TEMPORAL VARIABILITY IN RAINFALL TRENDS IN OGBOMOSO. Journal of Fundamental and Applied Sciences, [S. l.], v. 14, n. 3, p. 539–547, 2022. DOI: 10.4314/jfas.1214. Disponível em: https://jfas.info/index.php/JFAS/article/view/1214. Acesso em: 25 sep. 2022.

Issue

Section

Articles