Journal
EUROPEAN JOURNAL OF AGRONOMY
Volume 36, Issue 1, Pages 21-31Publisher
ELSEVIER
DOI: 10.1016/j.eja.2011.08.003
Keywords
AquaCrop; Irrigation management; Crop planning; Decision support system; Economic optimization; Deficit irrigation
Categories
Funding
- Ministry of Science and Innovation (MCI) [CSD2006-67]
- CSIC
- European Social Fund
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Water resources used in irrigated agriculture are increasingly scarce, particularly in many countries where irrigation has undergone recent expansion. To optimize the limited resources available, optimization models provide useful tools for technical and economic analyses. One of the key inputs of these models is the yield response to water which is often simulated with empirical water production functions. At present, dynamic crop simulation models, such as AquaCrop (Steduto et al., 2009) offer alternative predictions of crop responses to different irrigation strategies as inputs to economic optimization. A model at farm scale was developed and applied to an area in South-western Spain to assist farmers in pre-season decision making on cropping patterns and on irrigation strategies. Yield predictions were obtained from the AquaCrop model which was validated for four different crops. The model simulated the impact on farm income of: (a) irrigation water constraints; (b) variations in agricultural policies; (c) changes in product and water prices; and, (d) variations in the communication to farmers of the specific level of irrigation water allocation. The applications of the models to the study area showed that currently, the changes in cropping patterns induced by the agricultural policy will encourage water savings more than an increase in water prices. Under water restrictions, the best strategy combines planting of low water use crops in part of the area to release water to grow more profitable crops with greater water needs. The model predicted a strong negative impact on farm income of delaying a decision on the level of seasonal water allocation by the water authority, reaching up to 300 ha(-1) in the case of the study area. (C) 2011 Elsevier B.V. All rights reserved.
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