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Introducing deficit irrigation crop techniques derived by crop growth models into a Positive Mathematical Programming model

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  • Severini, Simone
  • Cortignani, Raffaele

Abstract

There is a growing policy pressure to reduce water use in agriculture when this generates sufficiently large environmental benefits and increases the well-being of other water users. Several analysis investigate farmers’ response to water policy by means of mathematical programming models including Positive Mathematical Programming (PMP). The originals PMP methods refer only to activities observed in the reference period. However, under the pressure of new water policies, farmers can adjust not only their cropping patterns but also the irrigation techniques they use. In particular, they could introduce water deficit irrigation crop techniques that were not profitable in past conditions. This paper proposes an extension of the Röhm and Dabbert approach (2003) in order to include deficit irrigation crop techniques not observed in the reference period into a PMP model. These alternative techniques are identified by means of a crop growth model developed by FAO. The proposed methodology is applied to a Mediterranean area performing two sets of simulations considering: the increase of water cost and the reduction of water availability. The results shows that, when water availability decreases, not considering adjustments in irrigation techniques is likely to underestimate the extent of farmers’ response to the new policy scenarios. In facts, introducing deficit irrigation techniques can alleviate the negative impact of decreasing water availability on farm economic results by using more efficiently this resource. However, this is not the case for the considered water cost increases.

Suggested Citation

  • Severini, Simone & Cortignani, Raffaele, 2008. "Introducing deficit irrigation crop techniques derived by crop growth models into a Positive Mathematical Programming model," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44010, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaae08:44010
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    File URL: http://purl.umn.edu/44010
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    References listed on IDEAS

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    1. Iglesias, Eva & Garrido, Alberto & Gomez-Ramos, Almudena, 2003. "Evaluation of drought management in irrigated areas," Agricultural Economics, Blackwell, vol. 29(2), pages 211-229, October.
    2. Blanco Fonseca, Maria & Iglesias Martinez, Eva, 2005. "Modelling New EU Agricultural Policies: Global Guidelines, Local Strategies," 89th Seminar, February 2-5, 2005, Parma, Italy 240760, European Association of Agricultural Economists.
    3. Pujol, Joan & Raggi, Meri & Viaggi, Davide, 2006. "The potential impact of markets for irrigation water in Italy and Spain: a comparison of two study areas," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 50(3), September.
    4. Ottmar Röhm & Stephan Dabbert, 2003. "Integrating Agri-Environmental Programs into Regional Production Models: An Extension of Positive Mathematical Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 254-265.
    5. Bartolini, Fabio & Bazzani, Guido Maria & Gallerani, Vittorio & Raggi, Meri & Viaggi, Davide, 2005. "Water Policy and Sustainability of Irrigated Farming Systems in Italy," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24518, European Association of Agricultural Economists.
    6. Iglesias, Eva & Garrido, Alberto & Gomez-Ramos, Almudena, 2003. "Evaluation of drought management in irrigated areas," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 29(2), October.
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    Cited by:

    1. Cortignani, Raffaele & Severini, Simone, 2009. "Modeling farm-level adoption of deficit irrigation using Positive Mathematical Programming," Agricultural Water Management, Elsevier, vol. 96(12), pages 1785-1791, December.

    More about this item

    Keywords

    positive mathematical programming; water policies; deficit irrigation; Crop Production/Industries;

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