Forecasting Urban Population Growth Using Logistic and Gompertz Models in Enugu Metropolitan Area

Urban population management in the Enugu Metropolitan Area, South East Nigeria, requires reliable long-term population projections to guide infrastructure investment decisions in housing, transportation, water supply, and waste management. This study fits, compares, and applies the logistic growth model and the Gompertz growth model to historical census and intercensal population estimates for Enugu metropolis spanning 1963 to 2023, sourced from the National Population Commission. Parameters for both models are estimated using nonlinear least squares, and the two models are compared for in-sample fit using Akaike Information Criterion and Bayesian Information Criterion. Projection uncertainty is quantified by bootstrap confidence intervals on model parameters. Results indicate that the Gompertz model provides marginally superior fit to historical growth data for Enugu metropolis, achieving lower AIC by 4.3 units. The Gompertz model projects a metropolitan population of 2.1 million by 2030 and 2.9 million by 2040, with 90 percent confidence intervals of plus or minus 18 percent at the 2040 horizon. Scenario projections examine the effect of hypothetical changes in rural-urban migration intensity on the growth trajectory. Urban planners are advised that the baseline 2040 projection would require a 62 percent expansion of current water supply infrastructure capacity. Keywords: population forecasting, logistic model, Gompertz model, Enugu metropolis, urban growth.