Smart Management of Fresh Water Uses in Syria Using a Neural Network Model

• Majd Fater Naamah

  Department of Agricultural Economics, Faculty of Agricultural Engineering, Tishreen University, Lattakia, Syria

This study examines freshwater utilization trends in Syria from 2000 to 2022, focusing on agricultural, industrial, and domestic consumption while analyzing changes in per capita water availability and identifying the optimal usage ratio to bridge the water gap using artificial intelligence (AI) models. A descriptive analytical approach was employed to estimate time trend equations and annual growth rates based on World Bank data, while a multi-layer feed-forward neural network was used to predict the water gap. Findings indicate an overall increase in freshwater consumption for agriculture and domestic purposes, each growing at an annual rate of 0.006% (0.38%), whereas industrial water use declined by 0.07% annually. The per capita freshwater share exhibited a steady decline at -1.26% per year, with a simultaneous increase in the gap between water availability and the poverty threshold by 0.85% annually. AI-based analysis revealed that domestic water consumption has the greatest impact on widening the water gap, and an optimal reduction of 8.19% in total water use was identified as necessary to mitigate this issue. These findings highlight the need for strategic water management policies to ensure sustainable freshwater distribution across sectors.

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