Evaluating Alternatives to Bekhma Dam: Integrated Water Resources Management for Sustainable Development in the Greater Zab Basin
DOI:
https://doi.org/10.36103/9yn1y905Keywords:
machine learning, GIS, bekhma dam, discharge forecasting, reservoir alternatives, greater zab, water scarcityAbstract
The Bekhma Dam was once proposed as a massive solution to Iraq’s growing water challenges. But after decades of political delays, environmental concerns, and engineering complications, it remains incomplete. Instead of waiting for a project of such scale, this study explores more flexible and sustainable options. Using historical discharge data from the Eski Kalak Gauge Station, machine learning (XGBoost) was applied to project future water availability under changing climate conditions. The model showed a clear downward trend in discharge, indicating a dominant dry pattern in the coming decades and reinforcing the urgency of adaptive planning. In response, four upstream dam sites were identified through GIS and DEM analysis and evaluated based on reservoir capacity, topography, and regional fit. Bekhma itself was also reconsidered this time as a scaled-down version supported by those smaller alternatives. The idea is simple: by capturing floods and sediment in the upper basin, we can reduce Bekhma’s dead storage requirement and make those construction more realistic. This integrated approach could deliver the key benefits water security, storage, flood mitigation while reducing cost, social impact, and structural risk. Importantly, the study clarifies that these alternatives are not a complete replacement for Bekhma, but rather a practical and scalable support system to strengthen resilience. The study argues that combining predictive hydrology with decentralized infrastructure offers a smarter path forward for the Greater Zab Basin. Based on these findings, the study recommends adopting the proposed upstream alternatives alongside a reduced Bekhma structure to create a flexible, climate-resilient water management system.
Received date: 14/4/2025
Accepted date: 2/7/2025
Published date: 26/1/2026
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