Spatial and Seasonal Distribution of Shatt Al-Arab Water Quality Using Geographic Information Systems: Variations in Salinity, Turbidity, and pH

Abstract

The current research attempted to assess the spatial and seasonal variations in some water quality parameters in Shatt Al-Arab River by applying Geographic Information System (GIS) techniques in conjunction with remote sensing technology. Landsat 8 satellite images acquired from the United States Geological Survey (USGS) database were applied to evaluate the spatial distribution of the parameters including pH, electrical conductivity (EC), total dissolved solids (TDS), and turbidity.
Twenty-nine sampling stations were set up in the River stretching from the northern station at Al-Sharash to the southern station at Al-Wasiliyah Port. The water sampling and analysis processes took place during one year from November 2024 to October 2025.
According to the results, it was found out that the pH values ranged between 7.0 and 8.6, while the monthly average varied from 7.7 to 7.9, indicating a lack of spatial variation among the stations. On the other hand, EC and TDS revealed a clear longitudinal trend. The quality of the river waters changed from slightly saline water in the northern part of the River to highly saline in the southern part, and exceeded seawater salinity in some stations of the southern part during summer and autumn seasons. Moreover, the TDS values experienced marked seasonal changes and increased gradually towards the middle and southern parts of the River.
In addition, the turbidity experienced significant spatial and seasonal variations. The minimum turbidity values were measured in autumn, whereas the maximum turbidity values were observed in summer. Using GIS for the spatial analysis made it possible to detect water quality deterioration areas. Moreover, it was shown that there is a significant deterioration of water quality in the estuarine zone in terms of salinity and turbidity.
Thus, the present research proves the applicability of GIS and remote sensing techniques in assessing the spatial and temporal variations of river water quality.