Adaptive Evaluation of Proportional–Integral (PI) Automatic Controller Effects on Distribution Performance in Surface Water Operation Systems under Supply Instability

Document Type : Research Paper

Authors

1 PhD. Candidate, Dept. of Water Engineering, Faculty of Agricultural Technology (Aburaihan), University College of Agriculture & Natural Resources, University of Tehran, Tehran, Iran

2 Dept. of Water Engineering, Faculty of Agricultural Technology (Aburaihan), University College of Agriculture & Natural Resources, University of Tehran, Tehran, Iran

10.22059/jwim.2026.405547.1272

Abstract

In this study, the performance of the Nekouabad Irrigation Network was evaluated under two operating systems: the conventional manual operation and an automated operation based on a Proportional–Integral (PI) controller, in response to consecutive inflow shortage scenarios. Using a hydraulic simulation model and performance indicators of adequacy and sustainability, the network behavior was analyzed across seven levels of hydrological stress, ranging from normal conditions to inflow deficits exceeding 40%. The results revealed that the PI-based system significantly enhanced the level of water service, reduced temporal and spatial fluctuations, and improved the equity of water distribution. Compared with the manual operation, the PI controller increased mean adequacy by up to 40% and reduced mean variability (instability) by 39%, indicating a higher degree of stability and resilience across the network. Statistical, distributional, and spatial analyses confirmed that the PI control system prevented functional collapse under critical conditions and transformed the network into a more coordinated, predictable, and equitable system. The reduced coefficient of variation, synchronized regulator responses, and spatial uniformity of performance demonstrated the controller’s capacity to absorb disturbances and prevent the propagation of fluctuations throughout the network. These features facilitate a transition from reactive management toward predictive regulation, enabling more accurate planning, reduced dependence on groundwater resources, and enhanced resilience to climate variability. The findings support the applicability of comprehensive assessment frameworks—such as sustainability evaluation frameworks based on the Water–Food–Energy Nexus and risk-based system failure assessment—for future studies.

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