Management of Irrigation Water for Cropping Pattern Using a Mathematical Linear Programming Methodology / Case Study

Maya  Al-ABDALA; Safwan ABOASSAF; Afraa SALLOWM

doi:10.14720/aas.2025.121.3.16443

Authors

Maya Al-ABDALA Socio Economic Directorate, General Commission for Scientific Agricultural Research (GCSAR), Syria
Safwan ABOASSAF Socio Economic Directorate, General Commission for Scientific Agricultural Research (GCSAR), Syria
Afraa SALLOWM Agricultural Economics, Faculty of Agriculture, University of Damascus, Syria

DOI:

https://doi.org/10.14720/aas.2025.121.3.16443

Keywords:

Water Needs, Crop Pattern, Mathematical Linear Programming, Minimization

Abstract

The main objective is to study the efficiency of using the linear programming methodology in management of irrigation water of cropping pattern in Swaida Province, Syria, through a questionnaire targeting 106 farmers during 2021-2022. In the actual crop pattern, irrigation water estimated at 5.9 million m³, while the proposed cropping pattern model reduced it by 44.86% where it estimated at 3.25 million m³. Each crop has obtained an Irrigation water requirement according to the FAO CROPAT 8.0 program. The proposed linear programming model increased in the area of: peas, Dry Broad Beans, parsley, beans, garlic, pepper, cabbage, Squash, eggplant, Cucumbers, Cauliflower about 691.96%, 656.21%, 398.72%, 277.98%, 204.51%, 175.44%, 118.21 %, 88.43 %, 61.56 %, 32.43 %, 23.82 % respectively over the actual area. and reducing the area of: Okra, watermelon, cucumber Ajour, potatoes, melon, tomato, wheat, onions by 5.14%, 12.08%, 15.24%, 18.54%, 28.66%, 83.75%, 88.32%, 90%, respectively, of the actual area. The study recommends the necessity of interfering in preparing agricultural plans for cropping pattern by relying on correct scientific methodologies and away from randomness in a manner that serves the achievement of self-sufficiency and preservation of available resources, and sustainability of natural resources that are characterized by scarcity, especially water.

Metrics

Metrics Loading ...

Downloads

Download data is not yet available.

References

Al-abdala, M., Aboassaf , S., & Sallowm, A. (2024). Using linear mathematical programming to maximization the net return per unit area for irrigated crops (case study). Palestinian Journal of Technology and Applied Sciences (PJTAS), 1(7). https://doi.org/10.33977/2106-000-007-002

Agricultural Extension Directorate, Ministry of Agriculture and Agrarian Reform. As-Swaida Department of Agriculture. Unpublished data 2020. Syria.

(AOAD) Arab Organization for Agricultural Development (2007). Workshop on modern methods of farm management. League of Arab States, Cairo, Egypt.

Bronson R, Govindasami N (1997). Schaum’s Outline of Theory and Problems of Operations Research, Schaum’s Outline Series, second Edition. McGRAW-HILL Companies. p: 460

Difallah, W., Benahmed, K., Draoui, B., & Bounaama, F. (2017). Linear optimization model for efficient use of irrigation water. International Journal of Agronomy, 5, 1-8. https://doi.org/10.1155/2017/5353648.

F Imron and Murtiningrum (2021). Optimization of irrigation water allocation by using linear programming: case study on Belitang irrigation system. IOP Conference Series: Earth and Environmental Science. 653 012023. https://doi:10.1088/1755-1315/653/1/012023

Glenn, D. I. (2012). Determining Sample Size. In University of Florida IFAS Extension. Available at Http://Edis.Ifas.Ufl.Edu.

(NAPC) National Agricultural Policy Center (2002). Report: The reality of food and agriculture in the Syrian Arab Republic. Ministry of Agriculture &Agrarian Reform Damascus, Syria.

Mohamed M.M., El-Edemy M.S. and Morsi B.M. (2019). Economics of Water Resources For Achieving The Food Safe In Egypt. Arabic University Journal of Agricultural Science (AUJAS), Ain Shams Univ., Cairo, Egypt Special Issue, 26(2D), 2141-2157.

Murthy, P. ram. (2007). Operations research (2nd ed.). New Age International (P) Ltd., Publishers.

Ren, C., Yang, J., & Zhang, H. (2019). An inexact fractional programming model for irrigation water resources optimal allocation under multiple uncertainties. PLoS ONE, 14(6), 1–17.

Render, B., Stair, R. M., & Hanna, M. E. (2012). Quantitative Analysis For Management (11th ed.). pearson.

Sejati, W., & Akbar, T. T. (2024). Optimization Study of Cropping Pattern in the Klakah Irrigation Area, Lumajang Regency, Using Linear Programming. ADI Journal on Recent Innovation, 5(2), 136–145. https://doi.org/10.34306/ajri.v5i2.999

Watnabbach, Horst (2006). Agricultural Systems in the Syrian Arab Republic, Technical Report, National Agricultural Policy Center (NAPC), Ministry of Agriculture and Agrarian Reform in Syria, in collaboration with the Food and Agriculture Organization of the United Nations (FAO).

Yamane, T. (1967). Statistics, An Introductory Analysis (2nd Ed.). A Harper International Edition Jointly Published By Harper & Row, New York, Evanston & London And John Weatherhill, Inc., Tokyo.