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Efficient water resources management is an issue of major importance in the field of sustainable development, especially in the agricultural sector which represents the main consumer through irrigations. Therefore irrigation management is an important and innovating area which was the subject of several research and studies. Modeling, and more particularly, the Agent-Based Modeling (ABM), allows better representing the multiplicity of these actors, the diversity of their roles and their interactions. The main reason why we chose the agent technology in the field of gravity irrigation systems, is the complexity to manage in real-time the water distribution operations those arrive asynchronously and dynamically and to be reactive and adaptive to the dynamic and unpredictable events that characterizes the field (mainly rainy advents). Our objectives are mainly located on two levels. The first one, concerns the gravity irrigation modeling by a multi-agent technology and the agent modeling through AML language. The second one focuses on the irrigations scheduling optimization using an evolutionary algorithm. Comparisons between schedules before and after optimization are made and the results shows that our approach can be considered as an efficient tool for planning irrigation schedules by considering crops water needs.

This paper presents an overview of a decade (2002-2012) of studies performed on Soil-Plant-Atmosphere processes, in semi-arid areas (Haouz plain, Morocco). In this period, fifteen in-situ experiments on the dominant irrigated crops were performed, controlling the fluxes exchanged between land surface and atmosphere. The results showed that the physically based SVATs (ICARE, SiSPAT and ISBA) provided the best estimates of surface fluxes. For operational purposes, the FAO-56 approach and SAMIR Software (Satellite Monitoring for Irrigation) give a good estimate of evapotranspiration at field and regional scales, respectively. Finally, thermal infrared data were used in conjunction with SVATs to investigate the possibility of estimating the quantity of irrigation water.