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Rainfall variability assessment and its temporal implications for crop production and water management in Akwa Ibom State, Nigeria


A. I. Isaiah
A. M. Yamusa
A. C. Odunze
Y. Rabiu
D. A. Joshua

Abstract

Assessing rainfall variability over a given location provides useful information for sustainable water management and crop production. The study examined temporal rainfall variability and its trend in Eket and Oron (Coastal areas) and Uyo and Ikot (Ekpene), Akwa Ibom state, Nigeria. The study was conducted in four different locations – coastal areas (Eket and Oron) and upland areas (Uyo and Ikot Ekpene). Daily rainfall data were obtained from Nigeria Meteorological Agency (NiMet) for a period of 30 years (i.e. 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017 and 2018). The standardized precipitation index (SPI) was used to evaluate drought index; and time series was also used to determine its trend. The results showed that coastal areas of Eket and Oron witnessed moderate spell condition in 1990 and 1993 respectively. Moreover, the upland areas of Uyo and Ikot Ekpene witnessed severe dry sell condition in 1990 and 1993. In addition, the upland areas of Uyo and Ikot Ekpene witnessed moderate dry spell condition in 1991 and 1995. The annual rainfall standardized anomaly index of both areas is characterized by moderate dry spell to extreme wet conditions, with increase in near normal, moderately wet, very wet and extreme wet conditions. In addition, the trend of SPI rainfall series for coastal areas shows that Eket, R2 = 0.0239 and y = 0.056x - 0.9739; Oron, R2 = 0.0306 ad y = 0.0637x - 1.0781; Uyo, R2 = 0.0575 and y = 0.0735x - 1.143; and Ikot Ekpene, R2 = 0.0568 and y = 0.082x – 1.4354. This shows that the areas witnessed very minimal occurrence of dry spell with the highest recorded in the upland areas compared to coastal areas. Therefore, Akwa Ibom state annual rainfall trend required effective monitoring to prevent flooding, erosion and economic losses. 


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print ISSN: 2006-7003