The application of Kruskal‐Wallis technique for flood prediction in the Niger Delta, Nigeria
Abstract
Purpose
To evaluate and examine human perception of causes, frequency, duration, impact, adjustment patterns and local attempts of control, protection and flood prediction in Niger Delta. This will enable rural dwellers to appreciate some local flood control measures.
Design/methodology/approach
Through questionnaires administered in reclaimed areas of urban centres and flood prone communities in the Niger Delta. The data abstracted from questionnaires were then analyzed through Kruskal‐Wallis Function. The Kruskal‐Wallis approach was used as it takes care of large data points, which consists of nominal or ordinal data.
Findings
Human perception of flooding as regards impact and local attempts at flood prediction differ among Niger Delta States. The study highlights the socio‐economic implications of flooding as regards to causes, effects, control and predictive measures.
Practical implications
Assist rural dwellers on cheaper local and emergency measures such as use of sand bars, opening up of creeks and assess, cleaning of drainages to allow free flow.
Originality/value
The paper suggests continuous enlightenment programs as a means to encourage local and emergency measures to be adopted when flooding occurs. The work is original as no such work or analysis had been carried out in the Niger Delta in the past. The paper has provided raw data and knowledge, and adds to the limited literature in the Niger Delta. On the flooding cycles of the Niger Delta. It should also raise the awareness of local dwellers on the requirements for flood emergency response and adjustment.
Keywords
Citation
Gobo, A.E., Abam, T.K.S. and Ogam, F.N. (2006), "The application of Kruskal‐Wallis technique for flood prediction in the Niger Delta, Nigeria", Management of Environmental Quality, Vol. 17 No. 3, pp. 275-288. https://doi.org/10.1108/14777830610658692
Publisher
:Emerald Group Publishing Limited
Copyright © 2006, Emerald Group Publishing Limited