Assessing the impacts of land use–land cover changes on direct surface runoff: a remote sensing approach in Khulna City

Abstract

The increased risks of storm flood occurrences in large cities are the result of land use changes due to rapid urbanization. This study examines the influence of land use changes in Khulna City Corporation (KCC) area on surface runoff over a period of 15 years, from 2005 to 2020. Land use–land cover (LULC) maps for 2005, 2010, 2015, and 2020 were created employing support vector machine (SVM)-based supervised image classification using time-series satellite data, and the surface runoff was determined using Soil Conservation Service-Curve Number model. The major land use change drivers of surface runoff were determined through a correlation analysis. Surface runoff was observed to follow a similar trend as that of impervious urban areas, which went up by 5.44% from 2005 to 2020 (17.00 mm increment in average runoff) and the opposite trend was found in vegetation land cover, which declined by 13.34% in areal extent throughout the study period. In comparison with other types of land use, surface runoff changes were most significantly associated with the changes in urban impervious areas and vegetation land use-land cover (LULC) class. In fast-growing cities across the world, and especially in developing nations, the results of this study may serve as a guide for urban storm flood management and urban planning efforts. HIGHLIGHTS Between 2005 and 2020, the urban area increased by 9.82%, while vegetation cover dropped by 13.24%.; During 2005–2020, the relative degree of average runoff depth on a particular day with a 100-year rainfall event rose by 5.44% (17.00 mm).; The increase in runoff depth was found to be positively and negatively correlated with the expansion of urban impervious areas and changes in vegetation land cover class, respectively.;

Keywords

• rainfall–runoff
• remote sensing
• scs-cn method
• urbanization
• watershed