WATER SALINITY MAPPING OF KARUN BASIN LOCATED IN IRAN USING THE SVR METHOD

Abstract

Water salinity is a complex issue in coastal and estuarine areas. Currently, remote sensing techniques have been widely used to monitor water quality changes, ranging from river to oceans. The salinity of Karun River has been increasing due to some critical factors, therefore, This study aimed at building regression models to ascertain the water salinity through the relationship between the reflectance of the Landsat-8 OLI and In situ measurements. A total of 102 observed samples were divided into 70% training and 30% test from June 2013 to July 2018 along the Karun River. Spectral signature analysis showed that band 1 - Coastal/Aerosol (0.433–0.453 μm), band 2 - Blue (0.450–0.515 μm) and band 3 - Green (0.525–0.600 μm) are sensitive to salinity . Furthermore, to have a comprehensive investigation, the Support Vector Regression (SVR) method was applied. The outcomes related to the quality of the SVR depend on several factors e.g. proper setting of the SVR meta-parameters, therefore, to deal with this issue Genetic Algorithm (GA) was applied. The SVR model resulted in values of R2 and RMSE for test data which are respectively obtained to be 0.7 and 390 μs cm−1. Eventually, Karun water salinity maps were prepared by SVR method to demonstrate the Karun water salinity on 1 February 2015 and 5 September 2018.