Seasonal rainfall variability in Guinea Savanna part of Nigeria: a GIS approach

Abstract

Purpose

This paper aims to use geographical information systems kriging interpolation technique to examine and map the spatiotemporal variation in rainfall in Guinea Savanna of Nigeria.

Design/methodology/approach

Rainfall data, for the periods between 1970 and 2000, are collected from the archives of the Nigerian Meteorological Services, Oshodi Lagos. In this paper, rainfall is considered as the primary and input for crop yield. It is observed that the most important climatic element is rainfall; particularly inter‐annual variation and the spatiotemporal distribution of rainfall. Three spatial interpolation methods are chosen for this research work: inverse distance weighting method and the spline (completely regularized) as the determinist methods; and ordinary kriging as the stochastic methods. In order to analyze the interpolation quality, an evaluation by cross validation has been carried out. Ordinary kriging method was discovered suitable for this paper because it allows the sharpest interpolation rainfall data and is the most representative.

Findings

The results of the analysis show that rainfall varies both in time and space. Rainfall variability is very high in most of Northern Guinea Savanna (e.g. Yola, Minna, and Ilorin) with values of coefficient of variation (CV) between 26 and 49 percent while in Southern Guinea Savanna, the CV is very low especially, in Enugu (9 percent), and Shaki (8 percent). These anomalies (such as decline in annual rainfall, change in the peak and retreat of rainfall and false start of rainfall) are detrimental to crop germination and yield, resulting in little or no harvest at the end of the season.

Originality/value

The paper concludes that geospatial techniques are powerful tools that should be explored further for realistic analysis of the effects of seasonal variability in rainfall.

Citation

Ayanlade, A. (2009), "Seasonal rainfall variability in Guinea Savanna part of Nigeria: a GIS approach", International Journal of Climate Change Strategies and Management, Vol. 1 No. 3, pp. 282-296. https://doi.org/10.1108/17568690910977492