Research Article // Spatial clustering of WEF-environment Nexus indicators for irrigation water operational performance: A feature-driven approach
By Rahparast et al. This study proposes a feature-driven spatial clustering framework that integrates hydraulic simulation and cross-validated indicator selection to identify key WEFE nexus drivers and reveal performance patterns in irrigation systems under varying water stress conditions.
Abstract
The technical assessment of surface water distribution among water-right holders within an irrigation district under conditions of water supply stress did not yield a comprehensive operational appraisal. The WEF–Environment nexus-assessment approach offers a holistic and pragmatic evaluation by incorporating technical assessment alongside considerations of energy and environmental trade-offs.
This study presents an innovative clustering-based WEF-Environment spatial assessment methodology that combines hydraulic simulation and data-driven feature selection. An integrated hydraulic-operation model was developed to simulate daily operations under stressed scenarios. From this, nine key indicators were generated—such as Surface Water Delivery (SWD), Energy Consumption (EC), Carbon Emissions (CE), and Energy Productivity (EP). To enhance clustering accuracy, a cross-validated feature selection approach was applied, ranking indicators according to their contribution to clustering quality.
The proposed methodology is implemented in Nekouabad Irrigation District, Iran, and the Nexus-based clustering and GIS-based spatial mapping were conducted using the selected features. Cross-validation across operational scenarios confirms the robustness of the feature-driven approach. SWD, CE, and Surface Water-Based Cultivated Area (SWCR) are key indicators that identify performance patterns. Under high stress, low-performing areas grew to cover over 90 % of the district. Environmental costs rose accordingly; in some zones, SWD dropped below 35 %, while carbon emissions exceeded 100,000 kg CO₂, indicating unsustainable operational trade-offs. Only a small portion of the district maintained balanced performance across delivery, efficiency, and emissions metrics.
The study demonstrates that integrating feature selection with spatial clustering can identify priority areas for intervention, improve nexus assessments, and provide actionable insights for water managers.
Published
03 October 2025
In
Environmental Impact Assessment Review