Abstract
This paper presents a modeling framework for real-time decision support for irrigation scheduling using the National Oceanic and Atmospheric Administration’s (NOAA’s) probabilistic rainfall forecasts. The forecasts and their probability distributions are incorporated into a simulation-optimization modeling framework. In this study, modeling irrigation is determined by a stochastic optimization program based on the simulated soil moisture and crop water-stress status and the forecasted rainfall for the next 1–7 days. The modeling framework is applied to irrigated corn in Mason County, Illinois. It is found that there is ample potential to improve current farmers’ practices by simply using the proposed simulation-optimization framework, which uses the present soil moisture and crop evapotranspiration information even without any forecasts. It is found that the values of the forecasts vary across dry, normal, and wet years. More significant economic gains are found in normal and wet years than in dry years under the various forecast horizons. To mitigate drought effect on crop yield through irrigation, medium- or long-term climate predictions likely play a more important role than short-term forecasts. NOAA’s imperfect 1-week forecast is still valuable in terms of both profit gain and water saving. Compared with the no-rain forecast case, the short-term imperfect forecasts could lead to additional 2.4–8.5% gain in profit and 11.0–26.9% water saving. However, the performance of the imperfect forecast is only slightly better than the ensemble weather forecast based on historical data and slightly inferior to the perfect forecast. It seems that the 1-week forecast horizon is too limited to evaluate the role of the various forecast scenarios for irrigation scheduling, which is actually a seasonal decision issue. For irrigation scheduling, both the forecast quality and the length of forecast time horizon matter. Thus, longer forecasts might be necessary to evaluate the role of forecasts for irrigation scheduling in a more effective way.
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Acknowledgments
The authors are grateful to two anonymous reviewers, especially for the detailed, insightful comments and suggestions from one reviewer, which have led to considerable improvement to the early version of the manuscript. This study was supported by the National Aeronautics and Space Administration (NASA) grant NASANNX08AL94G and the National Science Foundation (NSF) grant NSFCMMI-0825654.
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Information & Authors
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Published In
Journal of Water Resources Planning and Management
Volume 137 • Issue 5 • September 2011
Pages: 391 - 403
Copyright
© 2011 American Society of Civil Engineers.
History
Received: Nov 10, 2009
Accepted: Sep 29, 2010
Published online: Sep 29, 2010
Published in print: Sep 1, 2011
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