IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-00454529.html
   My bibliography  Save this paper

Exploring regional irrigation water demand using typologies of farms and production units: an example from Tunisia

Author

Listed:
  • J.C. Poussin

    (Supersonic imagine - Supersonic Imagine)

  • A. Imache

    (Supersonic imagine - Supersonic Imagine)

  • R. Beji

    (Commissariat Régional au Développement Agricole - Ministère de l'agriculture)

  • Philippe Le Grusse

    (Supersonic imagine - Supersonic Imagine)

  • A. Benmihoub

    (Dynamique sociétés-environnements sur le temps long en Afrique périsaharienne)

Abstract

La plupart des méthodes utilisées pour prédire la consommation d'eau d'irrigation à l'échelle régionale sont fondées sur des modèles biophysiques et les assolements. Leur objectif est de fournir des estimations précises de la "demande d'eau" qui sont utiles pour la gestion des ressources en eau. Toutefois, dans le cas du libre accès à la ressource en eau, par exemple le pompage dans une nappe phréatique, il est seulement possible d'éviter la surexploitation au travers d'une "gestion" de la demande de l'eau basée sur les choix des agriculteurs et leurs comportement. Dans ce papier, nous proposons un cadre d'analyse pour représenter les activités agricoles en utilisant des typologies des exploitations agricoles et des unités de production agrégées à l'échelle régionale. Ce cadre peut être utilisé pour estimer la consommation d'eau d'irrigation et d'autres intrants, ainsi que la production agricole. Ce cadre peut également être utilisé pour évaluer les effets d'une technique, d'une mesure économique ou de changements institutionnels sur le revenu agricole, et de prévoir les conséquences de ces changements à l'échelle régionale. Nous avons utilisé cette méthode en Tunisie centrale pour estimer la demande en eau d'irrigation en 1999. Nous avons ensuite simulé les changements qui se produiraient si l'irrigation au goutte à goutte a été adoptée. Les résultats de la simulation a montré des économies d'eau et de main-d'½uvre, et une augmentation des rendements, avec une fertigation. Ainsi, l'utilisation de l'irrigation au goutte à goutte peut permettre aux agriculteurs d'étendre leurs superficies irriguées en goutte à goutte. Nous avons ensuite simulé l'adoption généralisée de l'irrigation au goutte à goutte et l'extension des zones irriguées: les résultats n'ont pas montré de baisse de besoins en eau à l'échelle régionale. Ces hypothèses ont été confirmées en 2005 en utilisant de nouvelles typologies pour évaluer la nouvelle demande en eau d'irrigation. Nous avons également simulé les effets de changements économiques sur les revenus agricoles. Une augmentation importante du coût de l'eau a touché une minorité d'exploitations, qui a consommé seulement 17% du total de l'eau d'irrigation, tandis qu'une légère diminution des prix de la pastèque et melon a touché une majorité des exploitations agricoles, qui a consommé 78% du total de l'eau d'irrigation. Les outils de gestion de la demande en eau des doivent donc se concentrer sur les effets d'une technique, des mesures économiques, ou de changements institutionnels et sur les choix des agriculteurs.

Suggested Citation

  • J.C. Poussin & A. Imache & R. Beji & Philippe Le Grusse & A. Benmihoub, 2008. "Exploring regional irrigation water demand using typologies of farms and production units: an example from Tunisia," Post-Print hal-00454529, HAL.
    • Handle: RePEc:hal:journl:hal-00454529
    DOI: 10.1016/j.agwat.2008.04.001
    Note: View the original document on HAL open archive server: https://hal.science/hal-00454529
    as

    Download full text from publisher

    File URL: https://hal.science/hal-00454529/document
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.agwat.2008.04.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Gomez-Limon, Jose A. & Riesgo, Laura, 2004. "Irrigation water pricing: differential impacts on irrigated farms," Agricultural Economics, Blackwell, vol. 31(1), pages 47-66, July.
    2. Mateos, Luciano & Lopez-Cortijo, Ignacio & Sagardoy, Juan A., 2002. "SIMIS: the FAO decision support system for irrigation scheme management," Agricultural Water Management, Elsevier, vol. 56(3), pages 193-206, August.
    3. Robert Axelrod, 1997. "Advancing the Art of Simulation in the Social Sciences," Working Papers 97-05-048, Santa Fe Institute.
    4. Maton, L. & Leenhardt, D. & Goulard, M. & Bergez, J.-E., 2005. "Assessing the irrigation strategies over a wide geographical area from structural data about farming systems," Agricultural Systems, Elsevier, vol. 86(3), pages 293-311, December.
    5. Victoria, F.B. & Filho, J.S. Viegas & Pereira, L.S. & Teixeira, J.L. & Lanna, A.E., 2005. "Multi-scale modeling for water resources planning and management in rural basins," Agricultural Water Management, Elsevier, vol. 77(1-3), pages 4-20, August.
    6. Bartolini, F. & Bazzani, G.M. & Gallerani, V. & Raggi, M. & Viaggi, D., 2007. "The impact of water and agriculture policy scenarios on irrigated farming systems in Italy: An analysis based on farm level multi-attribute linear programming models," Agricultural Systems, Elsevier, vol. 93(1-3), pages 90-114, March.
    7. Landais, E., 1998. "Modelling farm diversity: new approaches to typology building in France," Agricultural Systems, Elsevier, vol. 58(4), pages 505-527, December.
    8. Heinemann, A. B. & Hoogenboom, G. & de Faria, R. T., 2002. "Determination of spatial water requirements at county and regional levels using crop models and GIS: An example for the State of Parana, Brazil," Agricultural Water Management, Elsevier, vol. 52(3), pages 177-196, January.
    9. Philippe Le Grusse & Hatem Belhouchette & Marjorie Le Bars & Gema Carmona & Jean Marie Attonaty, 2006. "Participative modelling to help collective decision-making in water allocation and nitrogen pollution: application to the case of the Aveyron-Lere Basin," International Journal of Agricultural Resources, Governance and Ecology, Inderscience Enterprises Ltd, vol. 5(2/3), pages 247-271.
    10. Michel Tenenhaus & Forrest Young, 1985. "An analysis and synthesis of multiple correspondence analysis, optimal scaling, dual scaling, homogeneity analysis and other methods for quantifying categorical multivariate data," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 91-119, March.
    11. Kok Teo & T. Cheng & Xiaoqiang Cai & Xiaoqi Yang, 2005. "Preface," Annals of Operations Research, Springer, vol. 133(1), pages 17-20, January.
    12. Weatherhead, E. K. & Knox, J. W., 2000. "Predicting and mapping the future demand for irrigation water in England and Wales," Agricultural Water Management, Elsevier, vol. 43(2), pages 203-218, March.
    13. Wichelns, Dennis, 2003. "Enhancing water policy discussions by including analysis of non-water inputs and farm-level constraints," Agricultural Water Management, Elsevier, vol. 62(2), pages 93-103, September.
    14. Leenhardt, D. & Trouvat, J. -L. & Gonzales, G. & Perarnaud, V. & Prats, S. & Bergez, J. -E., 2004. "Estimating irrigation demand for water management on a regional scale: I. ADEAUMIS, a simulation platform based on bio-decisional modelling and spatial information," Agricultural Water Management, Elsevier, vol. 68(3), pages 207-232, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rinaudo, Jean-Daniel & Maton, Laure & Terrason, Isabelle & Chazot, Sébastien & Richard-Ferroudji, Audrey & Caballero, Yvan, 2013. "Combining scenario workshops with modeling to assess future irrigation water demands," Agricultural Water Management, Elsevier, vol. 130(C), pages 103-112.
    2. Blanco-Gutiérrez, Irene & Varela-Ortega, Consuelo & Flichman, Guillermo, 2011. "Cost-effectiveness of groundwater conservation measures: A multi-level analysis with policy implications," Agricultural Water Management, Elsevier, vol. 98(4), pages 639-652, February.
    3. Ivars Reinfelds, 2011. "Monitoring and Assessment of Surface Water Abstractions for Pasture Irrigation from Landsat Imagery: Bega–Bemboka River, NSW, Australia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(9), pages 2319-2334, July.
    4. Lucie Clavel & Marie-Hélène Charron & Olivier Therond & Delphine Leenhardt, 2012. "A Modelling Solution for Developing and Evaluating Agricultural Land-Use Scenarios in Water Scarcity Contexts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(9), pages 2625-2641, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rinaudo, Jean-Daniel & Maton, Laure & Terrason, Isabelle & Chazot, Sébastien & Richard-Ferroudji, Audrey & Caballero, Yvan, 2013. "Combining scenario workshops with modeling to assess future irrigation water demands," Agricultural Water Management, Elsevier, vol. 130(C), pages 103-112.
    2. Maton, L. & Leenhardt, D. & Goulard, M. & Bergez, J.-E., 2005. "Assessing the irrigation strategies over a wide geographical area from structural data about farming systems," Agricultural Systems, Elsevier, vol. 86(3), pages 293-311, December.
    3. Prakashan Veettil & Stijn Speelman & Guido Huylenbroeck, 2013. "Estimating the Impact of Water Pricing on Water Use Efficiency in Semi-arid Cropping System: An Application of Probabilistically Constrained Nonparametric Efficiency Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(1), pages 55-73, January.
    4. Gómez-Limón, José A. & Gutiérrez-Martín, Carlos & Riesgo, Laura, 2016. "Modeling at farm level: Positive Multi-Attribute Utility Programming," Omega, Elsevier, vol. 65(C), pages 17-27.
    5. Balali, Hamid & Khalilian, Sadegh & Viaggi, Davide & Bartolini, Fabio & Ahmadian, Majid, 2011. "Groundwater balance and conservation under different water pricing and agricultural policy scenarios: A case study of the Hamadan-Bahar plain," Ecological Economics, Elsevier, vol. 70(5), pages 863-872, March.
    6. Leenhardt, D. & Trouvat, J. -L. & Gonzales, G. & Perarnaud, V. & Prats, S. & Bergez, J. -E., 2004. "Estimating irrigation demand for water management on a regional scale: I. ADEAUMIS, a simulation platform based on bio-decisional modelling and spatial information," Agricultural Water Management, Elsevier, vol. 68(3), pages 207-232, August.
    7. Humblot, Pierre & Jayet, Pierre-Alain & Petsakos, Athanasios, 2017. "Farm-level bio-economic modeling of water and nitrogen use: Calibrating yield response functions with limited data," Agricultural Systems, Elsevier, vol. 151(C), pages 47-60.
    8. Speelman, Stijn & Buysse, Jeroen & Farolfi, Stefano & Frija, Aymen & D'Haese, Marijke & D'Haese, Luc, 2009. "Estimating the impacts of water pricing on smallholder irrigators in North West Province, South Africa," Agricultural Water Management, Elsevier, vol. 96(11), pages 1560-1566, November.
    9. George HALKOS & Georgia GALANI, 2014. "Cost Effectiveness Analysis in Reducing Nutrient Loading in Baltic and Black Seas A Review," Journal of Advanced Research in Management, ASERS Publishing, vol. 5(1), pages 28-51.
    10. Monaco, Federica & Sali, Guido, 2018. "How water amounts and management options drive Irrigation Water Productivity of rice. A multivariate analysis based on field experiment data," Agricultural Water Management, Elsevier, vol. 195(C), pages 47-57.
    11. Lorite, I.J. & Mateos, L. & Orgaz, F. & Fereres, E., 2007. "Assessing deficit irrigation strategies at the level of an irrigation district," Agricultural Water Management, Elsevier, vol. 91(1-3), pages 51-60, July.
    12. Li, Hongjun & Li, Jiazhen & Shen, Yanjun & Zhang, Xiying & Lei, Yuping, 2018. "Web-based irrigation decision support system with limited inputs for farmers," Agricultural Water Management, Elsevier, vol. 210(C), pages 279-285.
    13. Barnaud, Cécile & Bousquet, François & Trebuil, Guy, 2008. "Multi-agent simulations to explore rules for rural credit in a highland farming community of Northern Thailand," Ecological Economics, Elsevier, vol. 66(4), pages 615-627, July.
    14. Mouratiadou, Ioanna & Topp, Cairistiona & Moran, Dominic, 2008. "Modelling Agricultural Diffuse Pollution: CAP – WFD Interactions and Cost Effectiveness of Measures," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6461, European Association of Agricultural Economists.
    15. Blanco-Gutiérrez, Irene & Varela-Ortega, Consuelo & Flichman, Guillermo, 2011. "Cost-effectiveness of groundwater conservation measures: A multi-level analysis with policy implications," Agricultural Water Management, Elsevier, vol. 98(4), pages 639-652, February.
    16. Iraizoz, Belen & Gorton, Matthew & Davidova, Sophia, 2007. "Segmenting farms for analysing agricultural trajectories: A case study of the Navarra region in Spain," Agricultural Systems, Elsevier, vol. 93(1-3), pages 143-169, March.
    17. Moreno-Pérez, Olga M. & Arnalte-Alegre, Eladio & Ortiz-Miranda, Dionisio, 2011. "Breaking down the growth of family farms: A case study of an intensive Mediterranean agriculture," Agricultural Systems, Elsevier, vol. 104(6), pages 500-511, July.
    18. Ficko, Andrej & Boncina, Andrej, 2013. "Probabilistic typology of management decision making in private forest properties," Forest Policy and Economics, Elsevier, vol. 27(C), pages 34-43.
    19. Matteo Richiardi, 2003. "The Promises and Perils of Agent-Based Computational Economics," LABORatorio R. Revelli Working Papers Series 29, LABORatorio R. Revelli, Centre for Employment Studies.
    20. Mariela González-Narváez & María José Fernández-Gómez & Susana Mendes & José-Luis Molina & Omar Ruiz-Barzola & Purificación Galindo-Villardón, 2021. "Study of Temporal Variations in Species–Environment Association through an Innovative Multivariate Method: MixSTATICO," Sustainability, MDPI, vol. 13(11), pages 1-25, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-00454529. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.