Monitoring the spatial changes of river water quality through the fusion of Landsat 8 images and statistical models (A case study: Sefidroud River, Northwest Iran)
نویسندگان
1 Department of Environmental Sciences and Engineering, Ardabil Branch, Islamic Azad University, Ardabil, Iran
2 Department of Environmental Sciences and Engineering, Ardabil Branch, Islamic Azad University, Ardabil, Iran.
3 Department of Environmental Sciences and Engineering, Ardabil Branch, Islamic Azad University, Ardabil, Iran
4 Department of Chemistry, Sarab Branch, Islamic Azad University, Sarab, Iran
5 Department of Environmental Sciences and Engineering, Ardabil Branch, Islamic Azad University, Ardabil, Iran
doi
10.22124/cjes.2025.8685چکیده
The present study determined the relationship between spectral reflectance of satellite images and water quality parameters (WQPs) to monitor water quality of Sefidroud River in Northwest Iran. The data of 12 WQPs were obtained from the regional water department in four hydrometric stations during 2013-2018. Principal component analysis (PCA) was used to reduce the number of WQPs. After pre-processing 19 Landsat 8 images simultaneously with WQPs sampling and fusing panchromatic band with spectral bands and increasing the band resolution to 15 × 15 m, the findings were employed to determine the relationship between spectral reflectance and band ratios. The PCA results revealed that Sum A (sum of anions), Sum C (sum of cations), TDS and EC were in the first principal component and HCO3- in the second principal component. The relationship of these five WQPs was statistically investigated with seven single spectral bands and 21 band ratios using regression models and curve estimation, thereby choosing the best regression model. Sum A, TDS and EC was correlated with band 5, Sum C with band ratio 4/3, and HCO3- with band 6 (R = 70%). Mapping spatial changes in WQPs using regression models and spectral data indicated higher values in the upstream areas prior to Manjil Dam, decreased values in the dam inflow, while increased those in its outflow. The research results highlighted the usefulness of Landsat 8 images for water quality monitoring.
