Inundation and water quality assessment of the Karun river before and after flooding using remote sensing

Abstract

Natural hydrological phenomena such as floods are among the most crucial hazards, damaging both urban and rural areas. River floods not only result in human and financial losses, but also alter the quality parameters and biological diversity of the river. Karun is one of the largest and wettest rivers in Iran, and its basin experiences numerous floods every year. In this work, satellite data are used to examine how floods affect the Karun River's quality. Specifically, we use NDWI (Normalized Difference Water Index), NDCI (Normalized Difference Chlorophyll Index), and NDTI (Normalized Difference Turbidity Index) data from Sentinel-2 Optical satellite to assess the water quality before and immediately after flooding. Additionally, Sentinel-1 Synthetic-aperture radar (SAR) satellite data are used to observe changes in the river bed and its inundation. This study demonstrates how Sentinel-2 and Sentinel-1 satellites could be effectively used to study variations in water quality and waterbodies at various periods. The results also show how the waterbody and water quality change before and after the flood.