Application of the NRCS-curve number method in humid tropical basins of southeastern Nigeria: a statistical analysis

Abstract

Abstract In the south-eastern region of Nigeria, the application of rainfall (P) and runoff (Q) data directly into the Natural Resources Conservation Service Curve Number (NRCS-CN) method hasn’t been thoroughly studied. This research aimed to determine representative values of the initial abstraction ratio (λ) and corresponding curve number (CN), fit the P and Q data using theoretical probability distributions, and establish confidence intervals for CN. The least squares minimization method and Kolmogorov-Smirnov test were employed on data from 129 sub-basins across 4 major basins. Findings revealed optimal initial abstraction ratio (λopt) = 0.24 and optimal CN (CNopt) = 80, with rainfall best fitted by Gamma, runoff by Weibull, and CN by Normal distributions. However, the study was limited to the available 8-year record period with 96 storm events. The 96 storm events over an 8-year period may seem limited for a humid tropical region, the available data were the most comprehensive and reliable dataset for this study area. Additional data collection over a longer time frame could enhance future studies. The localized CN value and associated confidence intervals can enhance runoff prediction accuracy for flood mitigation and water resources management in this humid tropical region, though further validation is recommended.

Keywords

• Rainfall-runoff data
• Curve number (CN) optimization
• Initial abstraction ratio
• Statistical distribution fitting
• South-eastern Nigeria