Storm water runoff studies in built-up watershed areas using curve number and remote sensing techniques

Within major city confines, floods are a major cause of worry and are mainly due to excessive urbanization encroaching on natural landscapes which would otherwise have served as areas of infiltration. The study combines the growth of urban landscape to estimate the maximum surface runoff and aimed to quantify this runoff generated and peak discharge for better urban management practices. These past five decades, the area experienced erratic expansion along with various changes in its land classification, resulting in several flood events in various parts. Runoff estimation was made using Curve Number method for the watershed. Annual rainfall deviation from mean saw an increase by 16% on an average in the past decade, with more than a 100% deviation from mean in 2017. Topographical maps generated to study the changes contributing to flood situations show a 90% increase in concretization over the past two decades and more than 50% reduction in the amount of natural vegetative cover in that same time period. Statistical analysis shows a good fit of the selected model for runoff estimation and well correlated variables. The model satisfactorily predicted runoff from the simulated data analysis with evaluation criteria NSE = 0.9945, MAE = 5.4121, r = 0.9975, R2 = 0.9949, RMSE = 6.8117 and PBias = 1.1436. The results revealed a steady increase in yearly runoff, due to topographical changes and increase in precipitation intensity over time. The study suggests intervention efforts be targeted spatially to ensure suitable flood-control structures and systems.