Martínez–Rojas (2026) Fuzzy Logic-Based Model for Optimizing Agricultural Water Resource Allocation

Identification

• Journal: Smart innovation, systems and technologies
• Year: 2026
• Date: 2026-01-01
• Authors: Natalia Martínez–Rojas
• DOI: 10.1007/978-981-95-1353-6_13

Research Groups

Universidad de La Salle, Bogotá, Colombia

Short Summary

This paper proposes a fuzzy logic-based model to optimize agricultural water resource allocation by dynamically updating irrigation schedules based on environmental data, crop water requirements, and soil moisture levels, demonstrating potential water savings without compromising crop yields.

Objective

• To develop and propose a fuzzy logic-based model for optimizing agricultural water resource allocation to enhance sustainability and productivity in water-scarce regions.

Study Configuration

• Spatial Scale: Field or farm-level, applicable to agricultural areas, particularly water-scarce regions.
• Temporal Scale: Real-time or short-term operational scale for dynamic irrigation scheduling.

Methodology and Data

• Models used: Fuzzy logic defining model, rule-based fuzzy inference system.
• Data sources: Environmental data, crop water requirements, soil moisture levels, weather conditions.

Main Results

• The proposed fuzzy logic model effectively updates irrigation schedules in real time, adapting to changing weather and soil conditions.
• The methodology shows potential for significant water savings in agriculture.
• Water savings are achieved without compromising crop yields, indicating the practical relevance and effectiveness of the approach.

Contributions

• Introduces a refined fuzzy logic-based modeling approach for agricultural water allocation, moving beyond prescriptive decision-making methods.
• Provides a dynamic, adaptive system for irrigation scheduling that responds to real-time environmental and crop needs.
• Offers a practical methodology for increasing water use efficiency and promoting agricultural sustainability in water-scarce regions.

Funding

• Not explicitly stated in the provided text.

Citation

@article{MartínezRojas2026Fuzzy,
  author = {Martínez–Rojas, Natalia},
  title = {Fuzzy Logic-Based Model for Optimizing Agricultural Water Resource Allocation},
  journal = {Smart innovation, systems and technologies},
  year = {2026},
  doi = {10.1007/978-981-95-1353-6_13},
  url = {https://doi.org/10.1007/978-981-95-1353-6_13}
}