Monitoring the Water Quality of Iraq Tigris River During the Winter and Spring Seasons Using Remote Sensing and Situ Measurements

Abstract

This article contrasts situ measurements with data from remote sensing (RS) and geographic information systems (GIS) used to monitor the water quality parameters of the Tigris River in Wasit Governorate, Iraq. RS and GIS are essential for measuring and monitoring water quality parameters. The study examines seasonal differences between winter and spring in water quality parameters like temperature, pH, electrical conductivity (EC), dissolved oxygen (DO), BOD₅, total dissolved solids (TDS), total suspended solids (TSS), turbidity, total hardness (T.H), nitrate, phosphate, total organic matter (TOM), and chlorophyll-a. Station 12 had the highest mean water turbidity value in spring, exceeding the WHO critical limit. Chlorophyll-a concentrations varied, with the lowest mean value in winter and the highest in spring.  The study used Landsat-9 data and Multiple Linear Regression (MLR) to predict certain water quality parameters, showing a strong correlation between Landsat-9 spectral reflectance data and selected parameters like turbidity, TOM, TDS, TSS, and chlorophyll-a. Landsat-9 spectral sensors can detect changes in water quality based on spectral reflectance characteristics. For turbidity, a significant correlation was observed with (SWIR1_L9, MNDWI, NDMI, C_L9/B_L9, B_L9/G_L9, and R_L9/B_L9) in winter and (NDMI, C_L9/B_L9, C_L9/G_L9, and B_L9/C_L9) In spring, achieving an R² value of 96% in winter and 53% in spring. For TDS, TSS, TOM, and chlorophyll-a, high R² values were also achieved in both seasons, with R² values ranging from 63% to 97% across different variables and parameters.