wcm.02.2025.233.248

The precision of river flow management decisions depends on the applied techniques and decision support systems. In recent decades, Artificial Intelligence (AI) has emerged as a pivotal technology in decision-making. Determining the correct trends for using these applications based on a solid knowledge base requires a review of these applications and an assessment of their effectiveness in regions suffering from water scarcity and struggling with managing River’s flow, such as Iraq. This paper critically discussed the AI applications in the modeling and management of river flow with focusing on the Tigris River in Iraq as a case study. The review surveyed global and local literature on the use of AI in river systems, covering hydrology, hydraulics, river modeling, decision-making, water quality, water resources management, focus areas, and challenges, as well as, AI methods like ANNs, SVMs, and deep learning, which emphasize optimization, modeling, forecasting, and flood prediction. The findings indicated that the main challenges include data availability and quality (28%), model interpretability (22%) and system integration (20%). AI applications prioritize decision support systems (30%) and hydrological forecasting (25%), while irrigation efficiency (10%) is less emphasized. In river flow management, data availability (30%) and climate change (25%) are key issues, with flood forecasting (30%) and water quality monitoring (25%) being the most critical. The results showed that AI significantly enhances predictive capabilities, optimizes water distribution, and minimizes wastage, with critical applications in flood forecasting and water quality monitoring. The deployment of AI in Iraq needs a localized approach through improving data infrastructure enhancements. The Tigris River benefits from AI for sustainable river management even though the implementation poses various challenges to support climate change adaptation. The research shows AI has significant potential as a water resource solution for nations facing development challenges.