Surface runoff responses to suburban growth: An integration of remote sensing, gis, and curve number

Abstract

Suburban growth and its impacts on surface runoff were investigated using the soil conservation service curve number (SCS‐CN) model, compared with the integrated advanced remote sensing and geographic information system (GIS)‐based integrated approach, over South Kingston, Rhode Island, USA. This study analyzed and employed the supervised classification method on four Landsat images from 1994, 2004, 2014, and 2020 to detect land‐use pattern changes through remote sensing applications. Results showed that 68.6% urban land expansion was reported from 1994 to 2020 in this suburban area. After land‐use change detection, a GIS‐based SCS‐ CN model was developed to examine suburban growth and surface runoff estimation. The developed model demonstrated the spatial distribution of runoff for each of the studied years. The results showed an increasing spatial pattern of 2% to 10% of runoff from 1994 to 2020. The correlation between runoff co‐efficient and rainfall indicated the significant impact of suburban growth in surface runoff over the last 36 years in South Kingstown, RI, USA, showing a slight change of forest (8.2% area of the total area) and agricultural land (4.8% area of the total area). Suburban growth began after 2000, and within 16 years this land‐use change started to show its substantial impact on surface runoff. We concluded that the proposed integrated approach could classify land‐use and land cover information to understand suburban growth and its potential impact on the area.