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Site-Specific Sprinkler Irrigation in a Water Limited Future

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  5th National Decennial Irrigation Conference Proceedings, 5-8 December 2010, Phoenix Convention Center, Phoenix, Arizona USA  IRR10-8491.(doi:10.13031/2013.35829)
Authors:   Robert G Evans, Bradley A King
Keywords:   precision irrigation, precision agriculture, spatial variability, water management, controls, control systems, decision support, sensor systems

Available water supplies for irrigation are becoming more and more limited in the western USA and other locations around the world, and this trend is accelerating. This will entail major changes to the physical and managerial aspects as well as the designs of the water delivery and on-farm irrigation systems. Resource conservation as well as achieving environmental benefits under these conditions will likely require the adoption of non-uniform water applications, also known as site-specific irrigation. A water and energy limited future will be the catalyst that finally brings many of the existing precision agricultural technologies together for irrigated agriculture. Highly managed deficit irrigation strategies will be fundamental to managing limited water supplies, which will be enhanced by spatially managing soil water through improved irrigation timing to minimize negative effects of intentional drought stresses on yields and quality in each area of a field. Integrated management approaches involving many aspects of precision agriculture technologies will assist producers in optimally meeting particular site-specific requirements of soil water, plant growth, reduced leaching or other criteria such as agrichemical applications in different areas of a single field. The combined use of distributed wireless sensor networks, various sensors mounted on the irrigation machine structure (with continuous geo-referencing) and remotely sensed information will be indispensable in providing real time feedback for necessary integrated decision support programs. This will require integration of system hardware, sensor systems and decision support software into comprehensive management systems, which will be challenging as significant knowledge gaps exist.

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