This article reviews the current global and Iraqi investigations on the application of Remote Sensing (RS), Geographic Information Systems (GIS), Water Quality Index (WQI) and Artificial Intelligence (AI) methods for the monitoring of water quality of Euphrates River in Iraq. The research is connected with the evaluation of the efficiency of satellite imaging, geographical analysis and machine learning algorithms to identify river pollution and environmental conditions evaluation. We studied the multiple satellite platforms (Landsat, Sentinel) for critical indicators of water quality, including turbidity, salinity, dissolved solids, suspended particles, sulfate and heavy metals. Research also studied the application of sophisticated AI models like Random Forest and Artificial Neural Networks to increase the prediction accuracy of water contamination characteristics. The research investigated showed that the quality of the water of the Euphrates River has degraded dramatically especially in the urban and industrial downstream sections. The primary contamination markers were high turbidity, TDS, sulfate, hardness and heavy metals. The results revealed that sewage disposal, industrial pollution, agricultural runoff and low river flow are the major drivers of environmental degradation. Moreover, the integration of RS , GIS and AI techniques proved highly successful for mapping pollution , prediction of WQI and environmental monitoring . The results indicated that the present satellite-based and intelligent monitoring technologies provide a reliable, accurate, and economical platform for sustainable water quality assessment and environmental management in the Iraqi river systems.