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International Journal of Agronomy
Volume 2017, Article ID 5353648, 8 pages
https://doi.org/10.1155/2017/5353648
Research Article

Linear Optimization Model for Efficient Use of Irrigation Water

1Laboratory of Energetic in Arid Zones (ENERGARID), Department of Electrical Engineering, Faculty of Technology, Tahri Mohammed University of Bechar, Bechar, Algeria
2Department of Mathematics and Computer Science, Faculty of Exact Sciences, Tahri Mohammed University of Bechar, Bechar, Algeria

Correspondence should be addressed to Wafa Difallah; moc.liamg@fidafaw

Received 8 May 2017; Accepted 27 June 2017; Published 26 July 2017

Academic Editor: David Clay

Copyright © 2017 Wafa Difallah et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. FAO water reports, Climate change, water and food security, Food and Agriculture Organization of the United Nations, Rome, Italy, 2011.
  2. Aqeel-ur-Rehman et al., “A review of wireless sensors and networks' applications in agriculture,” Computer Standards Interfaces, vol. 36, pp. 263–270, 2014. View at Publisher · View at Google Scholar
  3. A. Laaboudi, B. Mouhouche, and B. Draoui, “Neural network approach to reference evapotranspiration modeling from limited climatic data in arid regions,” International Journal of Biometeorology, vol. 56, no. 5, pp. 831–841, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. T. Takakura, C. Kubota, S. Sase et al., “Measurement of evapotranspiration rate in a single-span greenhouse using the energy-balance equation,” Biosystems Engineering, vol. 102, no. 3, pp. 298–304, 2009. View at Publisher · View at Google Scholar · View at Scopus
  5. Y. Yao, S. Liang, X. Li et al., “Improving global terrestrial evapotranspiration estimation using support vector machine by integrating three process-based algorithms,” Agricultural and Forest Meteorology, vol. 242, pp. 55–74, 2017. View at Publisher · View at Google Scholar
  6. D. A. King, D. M. Bachelet, A. J. Symstad, K. Ferschweiler, and M. Hobbins, “Estimation of potential evapotranspiration from extraterrestrial radiation, air temperature and humidity to assess future climate change effects on the vegetation of the Northern Great Plains, USA,” Ecological Modelling, vol. 297, pp. 86–97, 2015. View at Publisher · View at Google Scholar · View at Scopus
  7. V. Z. Antonopoulos and A. V. Antonopoulos, “Daily reference evapotranspiration estimates by artificial neural networks technique and empirical equations using limited input climate variables,” Computers and Electronics in Agriculture, vol. 132, pp. 86–96, 2017. View at Publisher · View at Google Scholar
  8. S.-F. Kuo and C.-W. Liu, “Simulation and optimization model for irrigation planning and management,” Hydrological Processes, vol. 17, no. 15, pp. 3141–3159, 2003. View at Publisher · View at Google Scholar · View at Scopus
  9. Z. X. Fang, B. Voron, and C. Bocquillon, “Dynamic programming: a model for an irrigation reservoir,” Hydrological Sciences Journal, vol. 34, no. 4, pp. 415–424, 1989. View at Publisher · View at Google Scholar · View at Scopus
  10. J. Auriol et al., “Optimization of catchment devices for simulation irrigation on mathematical models and linear programming,” in Proceedings of the Paper presented at the 9th World Congress of the ICI, Moscow, 1975.
  11. Z. Zhenmin, “Optimization of water allocation in canal systems of ChenGai irrigation area,” in Proceedings of the Paper presented at CEMAGREF-IIMI International Workshop on The Application of Mathematical Modeling for the Improvement of Irrigation canal Operation, Montpellier, France, 1992.
  12. A. Singh and S. N. Panda, “Optimization and Simulation Modelling for Managing the Problems of Water Resources,” Water Resources Management, vol. 27, no. 9, pp. 3421–3431, 2013. View at Publisher · View at Google Scholar · View at Scopus
  13. V. Azimi et al., “Optimization of deficit irrigation using non-linear programming (Case study:Mianeh region, Iran),” International journal of Agriculture and Crop Sciences, vol. 6, no. 5, pp. 252–260, 2013. View at Google Scholar
  14. S. Hong et al., “Optimization of irrigation scheduling for complex water distribution using mixed integer quadratic programming (MIQP),” in Proceedings of the the 10th International Conference on Hydroinformatics, Hamburg, Germany, 2012.
  15. P. Upadhyay et al., “Evaluating seed germination monitoring system by application of wireless sensor networks: a survey,” Advances in Intelligent Systems and Computing, vol. 411, pp. 259–266, 2016. View at Publisher · View at Google Scholar · View at Scopus
  16. K. R. Thorp, D. J. Hunsaker, A. N. French, E. Bautista, and K. F. Bronson, “Integrating geospatial data and cropping system simulation within a geographic information system to analyze spatial seed cotton yield, water use, and irrigation requirements,” Precision Agriculture, vol. 16, no. 5, pp. 532–557, 2015. View at Publisher · View at Google Scholar · View at Scopus
  17. D. Levy, W. K. Coleman, and R. E. Veilleux, “Adaptation of potato to water shortage: irrigation management and enhancement of tolerance to drought and salinity,” American Journal of Potato Research, vol. 90, no. 2, pp. 186–206, 2013. View at Publisher · View at Google Scholar · View at Scopus
  18. J. M. Barcelo-Ordinas, “A survey of wireless sensor technologies applied to precision agriculture,” in Precision agriculture 13, J. V. Stafford, Ed., Wageningen Academic Publishers, 2013. View at Google Scholar
  19. Dassanayake et al., “Water saving through smarter irrigation in Australian dairy farming: Use of intelligent irrigation controller and wireless sensor network,” in Proceedings of the Paper presented at the 18th World IMACS / MODSIM Congress, Cairns, Australia, 2009.
  20. M. Dursun and S. Ozden, “A wireless application of drip irrigation automation supported by soil moisture sensors,” Scientific Research and Essays, vol. 6, no. 7, pp. 1573–1582, 2011. View at Google Scholar · View at Scopus
  21. C. M. Angelopoulos, S. Nikoletseas, and G. C. Theofanopoulos, “A Smart system for garden watering using wireless sensor networks,” in Proceedings of the 9th ACM International Symposium on Mobility Management and Wireless Access, MobiWac'11, Co-located with MSWiM'11, pp. 167–170, usa, November 2011. View at Publisher · View at Google Scholar · View at Scopus
  22. S. Sutar et al., “Irrigation and fertilizer control for precision agriculture using wsn: energy efficient approach,” International Journal of Advances in Computing and Information Researches, vol. 1, no. 1, 2012. View at Google Scholar
  23. R. N. Kumari et al., “Microcontroller based irrigation using sensor [a smart way for irrigation],” International Journal of Research in Engineering & Advanced Technology, vol. 2, no. 2, pp. 1–3, 2014. View at Google Scholar
  24. L. Gao, M. Zhang, and G. Chen, “An intelligent irrigation system based on wireless sensor network and fuzzy control,” Journal of Networks, vol. 8, no. 5, pp. 1080–1087, 2013. View at Publisher · View at Google Scholar · View at Scopus
  25. E. Soorya et al., “Smart drip irrigation system using sensor networks,” International Journal of Scientific & Engineering Research, vol. 4, no. 2, pp. 2039–2042, 2013. View at Google Scholar
  26. Y. T. Hou, Y. Shi, and H. D. Sherali, “Rate allocation and network lifetime problems for wireless sensor networks,” IEEE/ACM Transactions on Networking, vol. 16, no. 2, pp. 321–334, 2008. View at Publisher · View at Google Scholar · View at Scopus
  27. P. Alagupandi, R. Ramesh, and S. Gayathri, “Smart irrigation system for outdoor environment using Tiny OS,” in Proceedings of the 3rd IEEE International Conference on Computation of Power, Energy, Information and Communication, ICCPEIC 2014, pp. 104–108, ind, April 2014. View at Publisher · View at Google Scholar · View at Scopus
  28. R. Bourkouche, “La consommation en eau du blé water consumption of wheat,” Revue Agriculture, pp. 205–209, 2016, http://revue-agro.univ-setif.dz/documents/numero-special/session5/bourkouche.pdf. View at Google Scholar
  29. M. Beg, “Prediction of crop water requirement: a Review,” International Journal of Advanced Technology in Engineering and Science, vol. 2, no. 1, pp. 727–734, 2014. View at Google Scholar
  30. A. Laaboudi et al., “Conceptual reference evapotranspiration models for different time steps,” Pet EnvironBiotechnol, vol. 3, no. 4, pp. 1–8, 2012. View at Google Scholar
  31. FAO document, Crop evapotranspiration - Guidelines for computing crop water requirements, Natural Resources Management and Environment Department, http://www.fao.org/docrep/X0490E/x0490e08.htm.
  32. R. G. Alen et al., albakhr nutah lilmahasil : dalil taqdir alaihtiajat almayiya “ Crop Evapotranspiration : Guidelines for Computing crop Water Requirement ”tarjama F.Aawad w M.alssueud, alnnashr aleilmi w almutabie- jamieat almalik seud, almamlakat alearabiat alssaeudia, 2006.
  33. B. J. Cosby, G. M. Hornberger, R. B. Glapp, and T. R. Ginn, “A statistical exploration of the relationships of soil moisture characteristics to the physical properties of soils,” Water Resources Research, vol. 20, no. 6, pp. 682–690, 1984. View at Publisher · View at Google Scholar · View at Scopus
  34. Raghav, “5 Important Factors Affecting the Demand of Water for Crops,” http://www.geographynotes.com/articles/5-important-factors-affecting-the-demand-of-water-for-crops/650.
  35. W. L. Powers and M. P. lewis, “Irrigation Requirement of Arable Oregon Soils, Oregon State College,” 1941, http://ir.library.oregonstate.edu/xmlui/bitstream/handle/1957/15005/StationBulletin394.pdf. View at Google Scholar
  36. C. Brouwer et al., Irrigation Water Management: Irrigation Methods,Training manual no 5, FAO Land and Water Development Division, 2001.
  37. J. R. Tiercelin and A. Vidal, Traité d'irrigation “Irrigation treaty”, 2nd edition, 2006.
  38. J. T. Ritchie, “Soil water balance and plant water stress,” in Understanding Options for Agricultural Production, vol. 7 of Systems Approaches for Sustainable Agricultural Development, pp. 41–54, Springer Netherlands, Dordrecht, 1998. View at Publisher · View at Google Scholar
  39. C. M. K. Gardner et al., Soil physical constraints to plant growth and crop production, FAO Land and water development division, 1999.
  40. M. S. Lord, “Linear Programming Optimizing the Resources,” Interdisciplinary Journal of Contemporary research in business, vol. 4, pp. 701–705, 2013. View at Google Scholar