RAINFALL VARIABILITY, LAND USE CHANGES AND URBAN GROWTH IN OSOGBO, NIGERIA: A DECISION SUPPORT SYSTEM FOR CLIMATE RESILIENT URBAN PLANNING

Abstract

Osogbo faces challenges from rainfall variability, rapid urbanization, and shifting land use. These pressures compromise the resilience of cities, infrastructure, and communities. Addressing them requires sophisticated urban planning that integrates rainfall variability and risk-mitigation strategies. Data were sourced from rainfall records by the Nigeria Meteorological Agency (NiMet) and land-use classifications from Landsat and Sentinel satellites. Analyses employed GIS platforms and regression and correlation analyses. The study revealed that April and October have higher annual rainfall in Osogbo, with the maximum in 2010 with 1700mm and the lowest in 2001 with 1000mm. The land-use data from 1990 to 2025 shows significant ups and downs across all categories. Agriculture and total land area change a lot without a clear pattern. Bare land and built-up areas grew significantly at times, suggesting city growth or land damage. Forest and water areas increased in the late 1990s and early 2000s but have since mostly decreased, which could harm the environment The multiple regression analysis conducted in this study revealed shortcomings in both the data and model dependability. While the model explains a substantial proportion of variance (R Square = 0.75), the negative Adjusted R Square, non-significant F-statistic, and uniformly high p-values for all predictors indicate a lack of statistical significance and soundness. The presence of errors in certain variables and the very small sample size further undermine the credibility and acceptability of the findings.The decision-support system targets regional vulnerabilities to land-use change and rainfall variability, aiming to guide policy and planning for greater urban climate resilience.