OCCASION: New Planning Tool for Optimal Climate Change Adaption Strategies in Irrigation
Publication: Journal of Irrigation and Drainage Engineering
Volume 136, Issue 12
Abstract
To sustain productive irrigated agriculture with limited water resources requires a high water use efficiency. This can be achieved by the precise scheduling of deficit irrigation systems taking into account the crops’ response to water stress at different stages of plant growth. Particularly in the light of climate change with rising population numbers and increasing water scarcity, an optimal solution for this task is of paramount importance. We solve the corresponding complex multidimensional and nonlinear optimization problem, i.e., finding the ideal schedule for maximum crop yield with a given water volume by a well tailored approach which offers straightforward application facilities. A global optimization technique allows, together with physically based modeling, for the risk assessment in yield reduction considering different sources of uncertainty (e.g., climate, soil conditions, and management). A new stochastic framework for decision support is developed which aims at optimal climate change adaption strategies in irrigation. It consists of: (1) a weather generator for simulating regional impacts of climate change; (2) a tailor-made evolutionary optimization algorithm for optimal irrigation scheduling with limited water supply; and (3) mechanistic models for rigorously simulating water transport and crop growth. The result, namely, stochastic crop-water production functions, allows to assess the impact of climate variability on potential yield and thus provides a valuable tool for estimating minimum water demands for irrigation in water resources planning and management, assisting furthermore in generating maps of yield uncertainty for specific crops and specific agricultural areas. The tool is successfully applied at an experimental site in southern France. The impacts of predicted climate variability on maize are discussed.
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Acknowledgments
We wish to thank Jean Claude Mailhol from Cemagref (Montpellier) for kindly providing us with data for the research project. Data have been provided through the PRUDENCE data archive, funded by the E.U. through Contract No. EUEVK2-CT2001-00132.
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Published In
Journal of Irrigation and Drainage Engineering
Volume 136 • Issue 12 • December 2010
Pages: 836 - 846
Copyright
© 2010 ASCE.
History
Received: Jun 25, 2009
Accepted: May 13, 2010
Published online: May 21, 2010
Published in print: Dec 2010
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