Real-Time Model for Optimal Water Allocation in Irrigation Systems during Droughts
Publication: Journal of Irrigation and Drainage Engineering
Volume 138, Issue 6
Abstract
The agricultural sector is the main victim of drought and efficient water planning, and management is the best strategy to reduce drought pressures on this sector. One operational approach is the application of real-time models to help water managers decide on mitigation measures, such as deficient irrigation or reducing cropped areas using the new incoming information (for example, recorded inflows and precipitation). The present paper introduces a real-time modeling approach for optimal water allocation during a drought. The model includes two main components: forecasting and optimization modules. The forecasting module uses a recurrent neural network technique to forecast annual inflows that is updated as monthly climate and hydrological data are introduced to the model. The optimization module allocates water among the irrigation units and their crops by considering growing stage, sensitivity to water stress at different stages, available/forecasted water, and previous decisions about water release. The model was tested for the 1999 drought of the Zayandeh Rud irrigation system. Traditional operating procedures were shown to produce 42% loss whereas the proposed method would have reduced loss to 12%.
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Acknowledgments
The authors deeply appreciate the three anonymous reviewers’ comments, which have contributed much to improving the manuscript.
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Information & Authors
Information
Published In
Journal of Irrigation and Drainage Engineering
Volume 138 • Issue 6 • June 2012
Pages: 517 - 524
Copyright
© 2012. American Society of Civil Engineers.
History
Received: May 14, 2011
Accepted: Nov 30, 2011
Published online: Dec 2, 2011
Published in print: Jun 1, 2012
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