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.
Highlights
Urbanization and suburban growth increase challenges to the surface water bodies, including flooding, channel erosion, water quality degradation, biodiversity, and climate [1,2]
We developed an integrated approach using a remote sensing (RS) and geographic information system (GIS)-based soil conservation service curve number (SCS-curve number (CN)) model to assess suburban growth influences in surface runoff
The combined effort of RS-GIS confirms it to be an efficient tool for suburban growth analysis
Summary
Urbanization and suburban growth increase challenges to the surface water bodies, including flooding, channel erosion, water quality degradation, biodiversity, and climate [1,2]. Land-use changes associated with urban development, vegetation, and hydrologic conditions are the major factors that affect urban flooding in many ways [10], leading to environmental degradation [8,11]. During the second stage of urbanization, houses, commercial buildings, streets, culverts, and parking lots increase imperviousness, thereby, affecting and changing the water balance This stage increases storm flows and runoff depth and degrades surface and groundwater quantity and quality in urban and suburban areas. Since most of the surface runoff modeling and landcover detection parameters are geographic data, integration of RS and GIS techniques is expected to be more effective in evaluating the impacts of urban LULC. TThhiiss ssttuuddyy ininccluluddeeddaanninitnetgergartaetdedapapprporaocahchtoteosteismtiamteattehethseursfuacrefarcuenroufnf oafnfdaenxdaemxaimneinseusbuubrubrabnagnrgorwotwhtehffeefcfetsctosnonLULULCLCpaptattetrenrnchcahnangeg.e.TThheemmaaininoobbjejeccttiviveessaarree::((aa)) ttoo detect suburbann LLUULLCCcchhaannggeessuussininggssaatetellliltieteRRSSananddGGISISanadndtotostustduydsypsaptiaatliaplapttaetrtnersnosf osuf bsubrbuarnbagnrogwrotwh;th(b; )(bt)otoexeaxmaminienethteheefeffefcetctoof fssuucchhssuubbuurrbbaannggrroowwtthh on surface rruunnooffff generation; and (c) to detect the most aaffffeecctteedd aarreeaa wwiitthhiinn tthhee uurrbbaann wwaatteerrsshheedd
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