Linga et al. (2026) Optimizing irrigation gate operations using evolutionary algorithms: Talibon SRIS case study

Identification

• Journal: Agricultural Water Management
• Year: 2026
• Date: 2026-01-06
• Authors: Seth Nathaniel Linga, Ahmed M. El-Naggar, László G. Hayde, Assela Pathirana
• DOI: 10.1016/j.agwat.2025.110104

Research Groups

• Land and Water Department, IHE Delft Institute for Water Education, Delft, The Netherlands
• Coastal and Urban Risk & Resilience Department, IHE Delft Institute for Water Education, Delft, The Netherlands

Short Summary

This study developed an optimization model integrating SWMM and an evolutionary algorithm (SWMM5-EA) to improve irrigation gate operations in the Talibon small reservoir irrigation system, Philippines. The optimized gate schedules significantly reduced overall irrigation deficits by 89.7% and conserved 1.95 million cubic meters of water, leading to more equitable and efficient water distribution.

Objective

• To develop and apply an optimization model to improve gate operations in the Talibon small reservoir irrigation system, Philippines, with the objective of minimizing irrigation deficits and achieving adequate and equitable water delivery across turnout sections.

Study Configuration

• Spatial Scale: Talibon Small Reservoir Irrigation System (SRIS), Talibon, Bohol, Philippines. The main canal extends 8.02 kilometers and serves 1229 hectares of land (1008.47 hectares firmed-up service area).
• Temporal Scale: Monthly simulations for the 2021 wet season (May–September), representing system behavior with a single operational day per month.

Methodology and Data

• Models used: Storm Water Management Model (SWMM), SWMM5-EA (an evolutionary algorithm-based optimization tool), Genetic Algorithm (GA).
• Data sources: Existing engineering plans for structural measurements, modal water depths observed during the 2021 wet season (May–September), monthly irrigation water requirements (IWR) derived from the NIA Region VII cropping calendar for 2021, and personal communication with NIA Region VII.

Main Results

• The traditional gate operation resulted in excessive upstream withdrawals and significant downstream deficits.
• Optimized gate operations reduced the total system irrigation deficit from 2.17 million cubic meters to 0.23 million cubic meters, representing an 89.7% reduction in unmet demand.
• This optimization led to a total water saving of 1.95 million cubic meters across the season by preventing over-irrigation.
• Irrigation durations were adjusted proportionally to the size of the serviced area, ensuring water supply ceased once demands were met.
• Upstream over-irrigation was minimized, with Relative Water Supply (RWS) values in previously over-irrigated turnouts (e.g., MC-Z, MC-2, MC-3, MC-3B) reduced from 3-4 to the target of 1.
• Improved downstream allocation ensured adequate RWS across most sections, with laterals F, G, and H at the canal's end meeting their irrigation demands with minimal surplus.
• The irrigated area achieving adequate supply (within ±20% of IWR) increased from 147 hectares (19%) to 755 hectares (97%), and the full 780 hectares target area was irrigated.

Contributions

• Presents a novel integration of SWMM and SWMM5-EA for optimizing gate operations in irrigation systems, specifically for the Talibon SRIS.
• Offers a scalable decision-support tool for practitioners to balance equity and efficiency in irrigation water allocation, particularly relevant for infrastructural modernization efforts.
• Provides an operational strategy to maximize the benefits of gate automation and offers actionable insights for irrigation modernization programs.
• Formulates a modeling framework transferable to other open-channel irrigation systems, enabling diagnosis of inefficiencies and testing of alternative operational strategies without extensive field experimentation.
• Establishes an empirical basis for informing project appraisal by linking system performance indicators (e.g., distribution efficiency, water savings, potential expansion of irrigated areas) to broader policy objectives.

Funding

• Department of Science and Technology - Foreign Graduate Scholarship
• National Irrigation Administration
• National Irrigation Administration - Regional Office VII

Citation

@article{Linga2026Optimizing,
  author = {Linga, Seth Nathaniel and El-Naggar, Ahmed M. and Hayde, László G. and Pathirana, Assela},
  title = {Optimizing irrigation gate operations using evolutionary algorithms: Talibon SRIS case study},
  journal = {Agricultural Water Management},
  year = {2026},
  doi = {10.1016/j.agwat.2025.110104},
  url = {https://doi.org/10.1016/j.agwat.2025.110104}
}