An optimal water distribution model for canal systems based on water level

Area of Science:

• Agricultural Engineering
• Water Resource Management
• Optimization Algorithms

Background:

• Traditional canal water distribution models rely on flow rates, neglecting crucial water level dynamics.
• Effective irrigation requires matching water delivery to crop growth demands.
• Accurate water distribution is vital for agricultural productivity and resource management.

Purpose of the Study:

• To develop an optimal water distribution model for rotational irrigation systems.
• To incorporate upper-level canal water levels into water distribution strategies.
• To compare group-based and random distribution models for different canal levels.

Main Methods:

• Developed an optimal water distribution model for rotational irrigation.
• Established a group model for rotational irrigation.
• Utilized the Non-dominated Sorting Genetic Algorithm II (NSGA-II) for model optimization.
• Analyzed water distribution based on upper-level canal water levels.

Main Results:

• The proposed model, considering upper-level canal water levels, more accurately reflects real-world water distribution.
• Both group-based and random distribution models were developed and solved.
• The NSGA-II algorithm effectively optimized the water distribution models.

Conclusions:

• Water distribution strategies should account for upper-level canal water levels for improved accuracy.
• The developed models offer valuable insights for optimizing irrigation in various canal systems.
• This research provides a foundation for more efficient and effective irrigation water management.