Crow Algorithm for Irrigation Management: A Case Study

  • Fatemeh Barzegari Banadkooki
  • Jan Adamowski
  • Vijay P. Singh
  • Mohammad EhteramEmail author
  • Hojat Karami
  • Sayed Farhad Mousavi
  • Saeed Farzin
  • Ahmed EL-Shafie


This study employed a new evolutionary algorithm namely, the crow algorithm (CA), to optimize reservoir operation and minimize irrigation water deficit. Comprehensive analysis have been carried out between the proposed CA algorithm and other algorithms such as Prticle Swarm optimization (PSO), Shark Algorithm (SA), Genetic Algorithm (GA), and Weed Algorithm (WA). In addition, in order to select the optimal optimization algorithm among all of the investigated ones, a Multi-Criteria Decision model has been utilized. The time of computation was 45 s for CA but was 65, 50, 78, and 99 s for SA, WA, PSO, and GA, respectively. The CA exhibited greater volumetric reliability and a lower vulnerability index over the other examined algorithms. Furthermore, the Root Mean Square Error (RMSE) between demand and water release was 1.11 × 106 m3 for CA compared to 2.14 × 106 m3, 3.33 × 106 m3, 3.45 × 106 m3, and 3.78 × 106 m3 for SA, WA, PSO, and GA, respectively. Using a multi-criteria decision model based on different indices, including the vulnerability index, resiliency index and volumetric reliability index, CA was ranked first.


Crow algorithm Water resources management Reservoir operation Irrigation management 



The authors are grateful to the University of Malaya, Malaysia, for supporting the study.

Funding Information

This study was funded by the University of Malaya (University of Malaya Research Grant GPF082A-2018.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Nature B.V. 2020

Authors and Affiliations

  • Fatemeh Barzegari Banadkooki
    • 1
  • Jan Adamowski
    • 2
  • Vijay P. Singh
    • 3
  • Mohammad Ehteram
    • 4
    Email author
  • Hojat Karami
    • 4
  • Sayed Farhad Mousavi
    • 4
  • Saeed Farzin
    • 4
  • Ahmed EL-Shafie
    • 5
  1. 1.Agricultural DepartmentPayam Noor UniversityTehranIran
  2. 2.Department of Bioresource Engineering, Faculty of Agriculture and Environmental SciencesMcGill UniversityQuebecCanada
  3. 3.Department of Biological and Agricultural Engineering, Zachry Department of Civil & Environmental EngineeringTexas A&M UniversityCollege StationUSA
  4. 4.Department of Water Engineering and Hydraulic Structures, Faculty of Civil EngineeringSemnan UniversitySemnanIran
  5. 5.Civil Engineering Department, Faculty of EngineeringUniversity of MalayaKuala LumpurMalaysia

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