Impact of Urbanization on surface runoff using Remote Sensing and GIS technology:

a case study of Lusaka District

Abstract

Accurately assessing the hydrological impact of urbanization on surface runoff is crucial for resilient urban planning and effective water resource management. The objective of this study was to evaluate the effects of urbanization on surface runoff using Geographic Information System (GIS), Remote Sensing, and the Soil Conservation Services Curve Number (SCS CN) model. The research was conducted in Lusaka District, Zambia and involved classifying land use/land cover maps derived from Landsat TM/EMT+ imagery for the years 1984, 1994, 2004, 2013, and 2020, employing an integrated approach of remote sensing and GIS techniques. Four distinct land use classes; built-up area, vegetation, water body, and barren land, were defined. The supervised classification technique, specifically maximum likelihood pixel-based classification, was used to select training sites for each land use class by identifying representative ground features using different spectral band combinations. The resulting land use/land cover maps exhibited an overall accuracy ranging from 93.22% to 99.19%. The study further analyzed surface runoff using the SCS CN model to investigate variations in surface runoff corresponding to changes in land use. The SCS CN model considers various factors such as soil type, precipitation data, land use, soil moisture conditions, and the size and shape of the watershed. The findings revealed a notable increase in the percentage of urban areas from 28.7% in 1984 to 68.7% in 2020. The SCS CN model demonstrated an associated increase in surface runoff, with a minimum recorded runoff of 385.02 mm in 1994 and a maximum of 1082.59 mm in 2020. These results indicate a clear correlation between urbanization and heightened surface runoff. Continued monitoring and assessment of land use changes using high-resolution satellite imagery are recommended for better understanding urbanization dynamics.