Journal of
Geography and Regional Planning

  • Abbreviation: J. Geogr. Reg. Plann.
  • Language: English
  • ISSN: 2070-1845
  • DOI: 10.5897/JGRP
  • Start Year: 2008
  • Published Articles: 395

Full Length Research Paper

Analysis of rainfall distribution over Enugu during the little dry season (1990-2005)

Enete Ifeanyi Christian1* and Ebenebe Izuchukwu, N.2
1Nnamdi Azikiwe University, Awka, Nigeria. 2Nigeria Meteorological Agency, Oshodi-Lagos, Nigeria.
Email: [email protected]

  •  Accepted: 09 June 2009
  •  Published: 31 July 2009


Rainfall is highly variable in both time and space, particularly in sub-humid tropical regions like West-Africa. This paper examines the variations in rainfall distributions over Enugu metropolis during the “little dry season” from 1990-2005 for the months of June, July, August and September. Statistical techniques like Time Series charts with Trend line analysis and standard deviation were used to depict the temporal distribution of rainfall in Enugu urban. The results show that the temporal variations in rainfall for the months under consideration were not significant enough to regard it as a true little dry season. The mean annual rainfall for the period of study over Enugu urban area was found to be 4687.59 mm with a standard deviation of ±18.11 and a coefficient of variation of 6% approximately. The study further shows that 1997 was the wettest year, while 1994 was revealed to be the most rainfall deficit year. In analyzing the four months under consideration for the period of the study, a rainfall total of 3822.4 mm was recorded with 1998 recording the lowest monthly rainfall value in August of 96.2 mm. The month of August recorded the lowest total monthly rainfall value for the entire period of study. The total number of dry spell days in Enugu urban area for the period of study is 810 days. 1996 recorded the highest number of dry spell days while the lowest number of dry spell days was recorded in 1991 with 43 days.


Key words: Rainfall, dry spell days, temporal variations, time-series analysis.