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Irrigation scheduling of a classical gravity network based on the Covariance Matrix Adaptation - Evolutionary Strategy algorithm

Abstract : Irrigation scheduling is an important task that significantly influences water conservation and crop production. For most gravity irrigation networks located in semi-arid areas, irrigation scheduling is based on available water regardless of crops water needs. The objective of this study is to propose a new approach for optimizing irrigation scheduling taking into account crops water demand, based on the Covariance Matrix Adaptation - Evolution Strategy (CMA-ES) evolutionary strategy algorithm. The objective function, that must be minimized, of this optimization problem is defined as the sum of two terms. The first term is the Irrigation Priority Index (IPI) which characterizes the degree of imbalance between water stress and irrigation timing of the plot. The second one takes into account the various constraints that relate to canals capacity, tasks timing, geographical distances and canal flow rate variations. The approach was applied to an agricultural sector located at 40 km from the city of Marrakech (Morocco). Optimal schedule for the third irrigation, of the 2011-2012 agricultural season, is provided and the comparisons between schedules before and after optimization are made. The obtained results demonstrate that such approach allows reducing the proportion of late irrigated plots (from 22% to 8%) and increasing the proportion of plots irrigated at an appropriate time (from 28% to 40%). We conclude that this approach can be considered as an efficient tool for planning irrigation schedules by considering crops water needs.
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Contributor : Sylvain Mangiarotti <>
Submitted on : Thursday, September 11, 2014 - 12:29:04 PM
Last modification on : Thursday, October 15, 2020 - 3:16:02 AM
Long-term archiving on: : Friday, December 12, 2014 - 10:27:24 AM


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S. Belaqziz, S. Mangiarotti, M. Le Page, S. Khabba, S. Er-Raki, et al.. Irrigation scheduling of a classical gravity network based on the Covariance Matrix Adaptation - Evolutionary Strategy algorithm. Computers and Electronics in Agriculture, Elsevier, 2014, 102, pp.64-72. ⟨10.1016/j.compag.2014.01.006⟩. ⟨ird-01063086⟩



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