Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

A Modelling Solution for Developing and Evaluating Agricultural Land-Use Scenarios in Water Scarcity Contexts

  • 404 Accesses

  • 4 Citations

Abstract

To meet sustainability challenges, regional water management and planning require approaches that assess the land-use visions of various stakeholders using their own evaluation criteria. Models and information systems are keystones in such integrated assessment activities. SPACSS (the SPAtial Cropping System Scenarios builder and evaluator) is a modelling solution that aims to help decision-makers evaluate normative land-use scenarios. A prototype of SPACSS was developed to explore concerns raised by a dam-building project in south-western France, specifically the relation between cropping system distribution and water uptake. This paper presents the initial steps of SPACSS development by scientists and agricultural experts and its evaluation by users through alternative scenarios of maize cropping (altering either its precocity or management to reduce irrigation). SPACSS can represent a wide range of land-use scenarios and aggregate impact indicators at several spatial and temporal scales. Although SPACSS served as a solid support for discussions with stakeholders and decision-makers, it needs modifications to represent more realistic, and thus more complex, land-use scenarios. These modifications will make SPACSS potentially valuable for dealing with a variety of issues concerning agricultural landscapes, far beyond the single question of quantitative water management.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

References

  1. Agreste (2002) Recencement Général Agricole 2000. Cartes thématiques Midi-Pyrénées. CD-Rom, Service Régional de la Statistique Agricole de Midi-Pyrénées

  2. Alcamo J (2008) Environmental futures. The practice of environmental scenario analysis. 212 pp

  3. Alkan-Olsson J, Bockstaller C, Stapleton LM, Ewert F, Knapen R, Therond O, Geniaux G, Bellon S, Correira TP, Turpin N, Bezlepkina I (2009) A goal oriented indicator framework to support integrated assessment of new policies for agri-environmental systems. Environ Sci Pol 12:562–572

  4. Barnaud C, Bousquet F, Trebuil G (2008) Multi-agent simulations to explore rules for rural credit in a highland farming community of Northern Thailand. Ecol Econ 66:615–627

  5. Becu N, Neef A, Schreinemachers P, Sangkapitux C (2008) Participatory computer simulation to support collective decision-making: potential and limits of stakeholder involvement. Land Use Policy 25:498–509

  6. Béguin P (2003) Design as a mutual learning process between users and designers. Interact Comput 15:709–730

  7. Bergez JE, Charron MH, Leenhardt D, Poupa JC (2012) MOUSTICS: a generic dynamic plot-based biodecisional model. Environ Model Softw 82:8–14

  8. Bergez JE, Debaeke P, Deumier JM, Lacroix B, Leenhardt D, Leroy P, Wallach D (2001) MODERATO: an object-oriented decision tool for designing maize irrigation schedules. Ecol Model 137:43–60

  9. Bergez JE, Garcia F, Raynal H (2010) RECORD: an integrated framework to build, evaluate and simulate cropping systems. Proceedings of AGRO2010, the XIth ESA Congress, Montpellier, 29 August to 3 September 2010, 929-930. http://www4.inra.fr/record/Publications (last access 2 March 2011)

  10. Brisson N, Mary B, Ripoche D et al (1998) STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parametrization applied to wheat and corn. Agronomie 18:311–346

  11. Clavel L, Soudais J, Baudet D, Leenhardt D (2011) Integrating expert knowledge and quantitative information for mapping cropping systems. Land Use Policy 28:57–65

  12. Deumier JM, Lacroix B, Bouthier A et al (2006) Stratégies de conduite de l'irrigation du maïs et du sorgho dans les situations de ressource en eau restrictive. Arvalis-Institut du Végétal, 10p. (http://www.irrinov.arvalisinstitutduvegetal.fr/fichiers/ressource_limitee/Article irrigation ma_357s sorgho_ avec photos.pdf, last access 10 March 2011)

  13. Dockerty T, Lovett A, Appleton K, Bone A, Sunnenberg G (2006) Developing scenarios and visualisations to illustrate potential policy and climatic influences on future agricultural landscapes. Agric Ecosyst Environ 114:103–120

  14. Doorenbos J, Kassam AH (1979) Yield response to water. Rome: Food and Agriculture Organisation of the United Nations. Available on: http://www.fao.org/landandwater/aglw/cropwater/parta.stm (last access 12 Jul 2010), 193 pp

  15. Etienne M, Le Page C, Cohen M (2003) A step-by-step approach to building land management scenarios based on multiple viewpoints on multi-agent system simulations. Jasss-the Journal of Artificial Societies and Social Simulation 6, 2, available online, http://jasss.soc.surrey.ac.uk/6/2/2.html, last access 10 March 2011

  16. Faivre R, Leenhardt D, Voltz M, Benoit M, Papy F, Dedieu G, Wallach D (2004) Spatialising crop models. Agronomie 24:205–217

  17. Greeuw S, van Asselt MBA, Grosskurth J, Storms CAMH (2000) Cloudy crystal balls. An assessment of recent European and global scenario studies and models. Environ Issues Ser 17:1–112

  18. Höll A, Andersen E (2002) Landscape impact of three agricultural policy scenarios. Danish J Geogr 3:59–75

  19. Inan HI, Sagris V, Devos W, Milenov P, van Oosterom P, Zevenbergen J (2010) Data model for the collaboration between land administration systems and agricultural land parcel identification systems. J Environ Manage 91:2440–2454

  20. Jakeman AJ, Letcher RA (2003) Integrated assessment and modelling: features, principles and examples for catchment management. Environ Model Softw 18:491–501

  21. Leenhardt D, Trouvat JL, Gonzales G, Perarnaud V, Prats S, Bergez JE (2004) Estimating irrigation demand for water management on a regional scale: I. ADEAUMIS, a simulation platform based on bio-decisional modelling and spatial information. Agric Water Manag 68:207–232

  22. Mandement A (2004) Compte-rendu et bilan du débat public de Charlas. Comission Nationale de Débat Public, Paris, p 64

  23. Maton L, Leenhardt D, Bergez JE (2007) Georeferenced indicators of maize sowing and cultivar choice for better water management. Agron Sustain Dev 27:377–386

  24. Maton L, Leenhardt D, Bergez JE (2009) Choix de précocité et pratiques de semis en maïsiculture irriguée du sud-ouest de la France: quelle diversité et comment l’expliquer ? Cahiers Agric 18:26–34

  25. Millennium Ecosystem Assessment (2005) Ecosystems and human well-being: volume 2 scenarios: Findings of the Scenarios Working Group. Island, Washington, DC, p 596

  26. Molina JL, García-Aróstegui J, Bromley J, Benavente J (2011) Integrated assessment of the European WFD implementation in extremely overexploited aquifers through participatory modelling. Water Resour Manag 25:3343–3370

  27. Mourad DSJ, Van der Perk M, Gooch GD, Loigu E, Piirimäe K, Stålnacke P (2005) GIS-based quantification of future nutrient loads into Lake Pelpsi/Chudskoe using qualitative regional development scenarios. Water Sci Technol 51:355–363

  28. Nassauer JI, Corry RC (2004) Using normative scenarios in landscape ecology. Landsc Ecol 19:343–356

  29. Pahl-Wostl C, Schlumpf C, Büssenschütt M, Schönborn A, Burse J (2000) Models at the interface between science and society: impacts and options. Integr Assess 1:267–280

  30. Passouant M, Caron P, Loyat J, Tonneau JP, Barzman M (2007) Observatoire des agricultures et des territoires : mise à l’épreuve d’une méthode de conception. In : Batton-Hubert M, Joliveau T, Lardon S (dir.). SAGEO 2007, Rencontres internationales Géomatique et territoire. CdRom. ISBN : 978-2-85710-078-2. http://www.emse.fr/site/SAGEO2007/CDROM/CQFD12.pdf (last access 10 March 2011)

  31. Poussin JC, Imache A, Beji R, Le Grusse P, Benmihoub A (2008) Exploring regional irrigation water demand using typologies of farms and production units: an example from Tunisia. Agric Water Manag 95:973–983

  32. Prost L, Lecomte C, Meynard JM, Cerf M (2007) Designing a tool to analyse the performance of biological systems: The case of evaluating soft wheat cultivars. @ctivités 4:54–76

  33. Quesnel G, Duboz R, Ramat E (2009) The Virtual Laboratory Environment—an operational framework for multi-modelling, simulation and analysis of complex dynamical systems. Simul Model Pract Theory 17:641–653

  34. Semenov MA, Barrow EM (1997) Use of a stochastic weather generator in the development of climate change scenarios. Clim Chang 35:397–414

  35. Stolte J, Ritsema CJ, Bouma J (2005) Developing interactive land use scenarios on the Loess Plateau in China, presenting risk analyses and economic impacts. Agric Ecosyst Environ 105:387–399

  36. Therond O, Belhouchette H, Janssen S et al (2009) Methodology to translate policy assessment problems into scenarios: the example of the SEAMLESS integrated framework. Environ Sci Pol 12:619–630

  37. Therond O, Hengsdijk H, Casellas E et al (2011) Using a cropping system model at regional scale: low-data approaches for crop management information and model calibration. Agric Ecosyst Environ 142:85–94

  38. Ty T, Sunada K, Ichikawa Y, Oishi S (2012) Scenario-based impact assessment of land use/cover and climate changes on water resources and demand: a case study in the Srepok River Basin, Vietnam-Cambodia. Water Resour Manage (Online First™, 10 January 2012):1–21

  39. Van Meijl H, van Rheenen T, Tabeau A, Eickhout B (2006) The impact of different policy environments on agricultural land use in Europe. Agric Ecosyst Environ 114:21–38

  40. Van Notten PWF, Rotmans J, van Asselt MBA, Rothman DS (2003) An updated scenario typology. Futures 35:423–443

  41. Veldkamp A, Fresco LO (1997) Exploring land use scenarios, an alternative approach based on actual land use. Agric Syst 55:1–17

  42. Verburg PH, Schulp CJE, Witte N, Veldkamp A (2006) Downscaling of land use change scenarios to assess the dynamics of European landscapes. Agric Ecosyst Environ 114:39–56

  43. Vinck D (1999) Les objets intermédiaires dans les réseaux de coopération scientifique. Contribution à la prise en compte des objets dans les dynamiques sociales. Rev Fr Sociol XL-2:385–414

  44. Walker DH (2002) Decision support, learning and rural resource management. Agric Syst 73:113–127

  45. Wang E, Cresswell H, Paydar Z, Gallant J (2008) Opportunities for manipulating catchment water balance by changing vegetation type on a topographic sequence: a simulation study. Hydrol Process 22:736–749

  46. Wechsung F, Krysanova V, Flechsig M, Schaphoff S (2000) May land use change reduce the water deficiency problem caused by reduced brown coal mining in the state of Brandenburg? Landsc Urban Plan 51:177–189

Download references

Acknowledgments

This study is part of the APPEAU project, funded by the French National Research Agency (ANR) as part of the Agriculture and Sustainable Development program (ADD). The Regional Council of Midi-Pyrénées and the National Institute for Agronomic Research (INRA) provided the Ph.D. fellowship of Lucie Clavel.

Author information

Correspondence to Delphine Leenhardt.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Clavel, L., Charron, M., Therond, O. et al. A Modelling Solution for Developing and Evaluating Agricultural Land-Use Scenarios in Water Scarcity Contexts. Water Resour Manage 26, 2625–2641 (2012). https://doi.org/10.1007/s11269-012-0037-x

Download citation

Keywords

  • Scenario
  • Cropping systems
  • Spatial distribution
  • Water planning
  • Land planning
  • Indicators