Integration of GIS and Geomorphic Data to Assess the Impact of Landscape Features on River Water Quality
Damanjeet AulakhAssistant Professor, Chitkara University Institute of Engineering and Technology, Centre for Research Impact and Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, Punjab, India. damanjeet.aulakh.orp@chitkara.edu.in0009-0009-4840-8228
Dr. Shashikant PatilProfessor, Department of uGDX, ATLAS SkillTech University, Mumbai, Maharashtra, India. shashikant.patil@atlasuniversity.edu.in0000-0002-8835-908X
M. Sunil KumarAssistant Professor, Department of Mechanical Engineering, Faculty of Engineering and Technology, JAIN (Deemed-to-be University), Bangalore, Karnataka, India. sunilkumar.m@jainuniversity.ac.in0000-0001-9054-4279
Uma BhardwajProfessor, Department of Biotechnology & Microbiology, Noida International University, Greater Noida, Uttar Pradesh, India. vc@niu.edu.in0000-0002-6414-9731
Keywords: Geographic information systems (GIS), Geomorphic data, River water quality, Low geomorphic relief areas (LGRA), High geomorphic relief areas (HGRA).
Abstract
Assessing the impact of landscape features on river water quality is essential for effective water organization. Geographic Information Systems (GIS) serve as valuable tools for integrating spatial data, while geomorphic characteristics offer critical insights into the hydrological processes that impact water quality. Traditional research has typically lacked a full grasp of the direct impact of certain land cover features on water quality in rivers, sometimes overlooking the complicated connections between geomorphological elements and water characteristics. As a result, this research intends to combine GIS and geomorphic data to assess the impact of landscape characteristics on river water quality. Water samples were obtained from numerous river locations, with essential characteristics, such as pH, dissolved oxygen (DO), turbidity, and temperature, to perform a thorough assessment of water quality. Geomorphic factors such as slope, elevation, and landscape pattern were also included in a GIS to spatially examine their connection to water quality indicators. The research used a comparison of water quality indicators from Low Geomorphic Relief Areas (LGRA) and High Geomorphic Relief Areas (HGRA) to investigate spatially changing correlations across areas. The findings show that water quality varies significantly between LGRA and HGRA, with landscape characteristics, such as elevation and landscape pattern, having a considerable influence on water quality indicators. This technique illustrates the efficiency of combining GIS and geomorphic data in managing and protecting river ecosystems.