Multispectral Remotely Sensed Models for Monitoring Suspended Sediment: A Case Study of Indus River, Pakistan

Soil erosion is a widespread problem causing the deterioration of both land and water resources. The water quality and quantity “Q and Q” connection is vital for sustainable water resources development and management. The prime objective of the research work is to quantify suspended sediment concentrations in surface waters by means of ALOS and ASTER satellite data. In this research work multispectral data and optical modeling is integrated to cope with lack of ground truth data. Modeling and monitoring of suspended sediment in water bodies is complex owing to many influencing parameters. Remote sensing makes it possible to monitor the water bodies effectively and efficiently and is most successfully used as part of a multidisciplinary approach to addressing natural resource questions. The strong relationship between suspended sediments and water surface reflectance leads to develop the efficient and effective algorithms for suspended sediments assessment in water bodies. Reflectance of ALOS/AVNIR-2 Band 3 and Band 4, ASTER Band 2 and Band 3N was found to be the best predictor of suspended sediment concentration in surface waters. The developed model and monitoring system is a useful practical tool for monitoring suspended sediments on seasonal bases and during floods. The research work demonstrates the feasibility of remotely sensed data for monitoring sedimentation in water bodies with and without ground truth data.