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This study was conducted by analyzing data from satellite image and geographical information system (GIS) to classify water quality parameters of Euphrates River in Iraq for irrigation use.
The main purpose of this research was to develop water quality classification models for Euphrates River, Iraq, using remote sensing. The water quality parameters used in this study included total dissolved solids (TDS), chlorides (Cl-), electrical conductivity (EC), and sodium adsorption ratio (SAR). The classification models were used for spatial prediction of these four parameters to determine the water’s suitability for irriga-tion use from the satellite image.
GIS techniques were used in the beginning to project the coordinates of 16 stations along the River in LANDSAT satellite image for Iraq map. Positive strong correlations between digital numbers of the satellite image at Band 2 with the water quality parameters in December, 2009, helped to build four regression mod-els between these two variables. These models could be used to predict these four water quality parameters (TDS, Cl-, EC, and SAR) at any point along the River in Iraq from the satellite image directly.
The next stage depends on satellite image analyses for the sake of building water quality classification models for Euphrates River on the satellite image to classify each of these water quality parameters according to irrigation use. These water quality classification models can be used to manage the agriculture along the basin of the River and to discover the locations of pollution in the River.
The general objective of this research is attaining a classification model that supports the identification, characterization and monitoring of water quality parameters that have an influence in irrigation.
Classification model, Euphrates River, GIS, remote sensing, satellite image water quality
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