Review on Developing Integrated Water Quality Management Systems Based On GIS and Remote Sensing Mechanism
DOI:
https://doi.org/10.53032/tvcr/2025.v7n2.35Keywords:
GIS, Remote Sensing, Decision Modelling, Root Mean Square Error (RMSE)Abstract
This paper examines the integration of remote sensing and GIS to monitor water quality indicators such as turbidity, chlorophyll levels, and surface temperature. It highlights how this synergy enhances the identification and management of pollution sources, supporting informed decision modelling for sustainable water resource management. Also emphasizes the need for comprehensive water quality management in river basins, addressing both point and non-point source pollutants. It proposes a distributed simulation model, utilizing GIS to assess pollutant loads based on land use and soil characteristics, aiming to predict water quality at river basin outlets.Even the accuracy of remote sensing-derived data was evaluated using statistical metrics such as Root Mean Square Error (RMSE) and the coefficient of determination (R²), ensuring reliability and robustness of the results. The paper provide valuable insights into the development and application of integrated water quality management systems using GIS and remote sensing technologies.
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