A Decision-Support Framework for Performance Assessment and Rehabilitation of Pressurized Irrigation Systems under Water Scarcity

Climate change is intensifying water scarcity and increasing uncertainty in water availability, placing growing pressure on irrigated agriculture, which accounts for nearly 70% of global freshwater withdrawals. In response to these challenges, many irrigation districts have transitioned from open channels to pressurized distribution systems to improve efficiency. However, despite substantial investments, operational performance often lags expectations due to hydraulic constraints, uneven pressure distribution, and limited capacity to diagnose system behavior under variable demand conditions. Addressing these challenges requires integrated approaches that combine field observations with hydraulic simulation to support targeted rehabilitation and enhance system resilience.

This study presents an integrated diagnostic–simulation framework for the performance assessment and rehabilitation of pressurized irrigation systems, applied to District 10 of the Capitanata irrigation scheme (southern Italy) as a representative case study. The district covers approximately 2,000 ha (317 hydrants) and is supplied by a storage reservoir. The proposed methodology couples extensive field-surveys with stochastic hydraulic modeling to capture system behavior under peak and uncertain demand conditions.

Field surveys including infrastructure layout, water delivery rules, design parameters, cropping patterns, and registered irrigation volumes, were utilized to parameterize the simulation. Hourly discharge data was analyzed to identify the critical 10-day peak demand period, representing the most demanding operating conditions. Upstream discharges were estimated using the Clément model and validated against empirical data to ensure consistency.

Hydraulic performance was assessed at two complementary levels using the ICARE and AKLA simulation models, based on 1,000 randomly generated operating configurations of hydrant demand (simultaneous operation and discharge), from which the resulting pressure conditions were computed to explicitly account for demand uncertainty. ICARE quantified network-scale performance through Indexed Characteristic Curves, expressing the percentage of configurations satisfying minimum pressure requirements. AKLA evaluated hydrant-level performance using relative pressure deficit (RPD) and reliability, defined as the frequency with which a hydrant meets the required pressure.

Diagnostic results under peak conditions revealed an overall network performance of only 62%, with significant localized pressure deficits. Based on these findings, we developed a targeted rehabilitation strategy that prioritized existing infrastructure, allowing pipe diameter to increase only where strictly necessary to minimize costs. Post-rehabilitation simulations demonstrated a critical performance shift: the operating set-point improved to 100% satisfaction, with all hydrants meeting minimum pressure requirements.

The proposed framework demonstrates that integrating field diagnostics with stochastic simulation can drive cost-effective rehabilitation, ensuring the resilience of pressurized irrigation networks against the growing threat of climatic uncertainty.