IDEAS home Printed from https://ideas.repec.org/p/ags/aare05/137795.html
   My bibliography  Save this paper

Policy Options for Dryland Salinity Management: An Agent-Based Model for Catchment Level Analysis

Author

Listed:
  • Bhuiyan, Shamsuzzaman

Abstract

Dryland salinity management requires the integration of hydrologic, economic, social and policy aspects into an interactive method that decision makers can use to evaluate the economic and environmental consequences of alternative land use/management practices as well as various policy choices. This requires that modelling frameworks be open and accessible to a range of disciplines as well as allowing flexibility in exploration in learning or adapting. This interactive method will present the development of a new integrated hydrologic-economic model in the context of a catchment in which land use change is the dominant factor and salinity emergence due to land use and land cover change presents a major land and water degradation problem. This model will reflect the interactions between biophysical processes and socioeconomic processes as well as to explore both economic and environmental consequences of different policy options. All model components will be incorporated into a single consistent model, which will be solved in its entirety by an agent based modelling (ABM) approach. Agent-based Modelling (ABM) will allow to incorporate features that are necessary for a realistic representation of economic behaviour and interactions among resource managers.

Suggested Citation

  • Bhuiyan, Shamsuzzaman, 2005. "Policy Options for Dryland Salinity Management: An Agent-Based Model for Catchment Level Analysis," 2005 Conference (49th), February 9-11, 2005, Coff's Harbour, Australia 137795, Australian Agricultural and Resource Economics Society.
    • Handle: RePEc:ags:aare05:137795
    DOI: 10.22004/ag.econ.137795
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/137795/files/2005_bhuiyan.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.137795?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
    ---><---

    References listed on IDEAS

    as
    1. Stefan Hajkowicz & Mike Young, 2001. "Concepts of Landscape Redesign - A Background Paper," Natural Resource Management Economics 01_002, Policy and Economic Research Unit, CSIRO Land and Water, Adelaide, Australia.
    2. Page, Scott E., 1999. "On the Emergence of Cities," Journal of Urban Economics, Elsevier, vol. 45(1), pages 184-208, January.
    3. Dawn C. Parker, Tom Evans, Vicky Meretsky, 2001. "Measuring Emergent Properties of Agent-Based Landcover/Landuse Models using Spatial Metrics," Computing in Economics and Finance 2001 261, Society for Computational Economics.
    4. Jeffery Connor & John Ward, 2004. "Trialing incentive based policy to control dryland salinity in the Bet Bet Catchment, north central Victoria," Natural Resource Management Economics 04_01, Policy and Economic Research Unit, CSIRO Land and Water, Adelaide, Australia.
    5. Tesfatsion, Leigh, 2002. "Agent-Based Computational Economics: Growing Economies from the Bottom Up," ISU General Staff Papers 200201010800001251, Iowa State University, Department of Economics.
    6. Berger, Thomas, 2001. "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 245-260, September.
    7. Rosegrant, M. W. & Ringler, C. & McKinney, D. C. & Cai, X. & Keller, A. & Donoso, G., 2000. "Integrated economic-hydrologic water modeling at the basin scale: the Maipo river basin," Agricultural Economics, Blackwell, vol. 24(1), pages 33-46, December.
    8. Morrison, David A. & Kingwell, Ross S. & Pannell, David J. & Ewing, Michael A., 1986. "A mathematical programming model of a crop-livestock farm system," Agricultural Systems, Elsevier, vol. 20(4), pages 243-268.
    9. Henriëtte S. Otter & Anne van der Veen & Huib J. de Vriend, 2001. "ABLOoM: Location Behaviour, Spatial Patterns, and Agent-Based Modelling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(4), pages 1-2.
    10. Balmann, Alfons, 1997. "Farm-Based Modelling of Regional Structural Change: A Cellular Automata Approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 24(1), pages 85-108.
    11. Hill, Christine M., 1997. "Economics for Landcare Groups: A Case Study in Dryland Salinity," 1997 Conference (41st), January 22-24, 1997, Gold Coast, Australia 136216, Australian Agricultural and Resource Economics Society.
    Full references (including those not matched with items on IDEAS)

    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. Rianne Duinen & Tatiana Filatova & Wander Jager & Anne Veen, 2016. "Going beyond perfect rationality: drought risk, economic choices and the influence of social networks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(2), pages 335-369, November.
    2. Thomas Berger & Regina Birner & Nancy Mccarthy & JosÉ DíAz & Heidi Wittmer, 2007. "Capturing the complexity of water uses and water users within a multi-agent framework," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(1), pages 129-148, January.
    3. Diego Ferraro & Daniela Blanco & Sebasti'an Pessah & Rodrigo Castro, 2021. "Land use change in agricultural systems: an integrated ecological-social simulation model of farmer decisions and cropping system performance based on a cellular automata approach," Papers 2109.01031, arXiv.org, revised Sep 2021.
    4. Pepijn Schreinemachers & Thomas Berger & Aer Sirijinda & Suwanna Praneetvatakul, 2009. "The Diffusion of Greenhouse Agriculture in Northern Thailand: Combining Econometrics and Agent‐Based Modeling," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 57(4), pages 513-536, December.
    5. Kellermann, Konrad & Balmann, Alfons, 2006. "How Smart Should Farms Be Modeled? Behavioral Foundation of Bidding Strategies in Agent-Based Land Market Models," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25446, International Association of Agricultural Economists.
    6. SeHoon Lee & Jeong Hee Hong & Jang Won Bae & Il-Chul Moon, 2015. "Impact of Population Relocation to City Commerce: Micro-Level Estimation with Validated Agent-Based Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-5.
    7. Janssen, Sander & van Ittersum, Martin K., 2007. "Assessing farm innovations and responses to policies: A review of bio-economic farm models," Agricultural Systems, Elsevier, vol. 94(3), pages 622-636, June.
    8. Happe, Kathrin & Balmann, Alfons, 2002. "Struktur-, Effizienz- und Einkommenswirkungen von Direktzahlungen," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 51(08), pages 1-13.
    9. Kellermann, Konrad & Sahrbacher, Christoph & Balmann, Alfons, 2008. "Land Markets In Agent Based Models Of Structural Change," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6647, European Association of Agricultural Economists.
    10. Dieter Pennerstorfer, 2022. "Farm exits and competition on the land market: Evidence from spatially explicit data," Economics working papers 2022-09, Department of Economics, Johannes Kepler University Linz, Austria.
    11. Xieyang Chen & Tongsheng Li, 2022. "Diffusion of Agricultural Technology Innovation: Research Progress of Innovation Diffusion in Chinese Agricultural Science and Technology Parks," Sustainability, MDPI, vol. 14(22), pages 1-23, November.
    12. Marcel Ausloos & Herbert Dawid & Ugo Merlone, 2015. "Spatial Interactions in Agent-Based Modeling," Dynamic Modeling and Econometrics in Economics and Finance, in: Pasquale Commendatore & Saime Kayam & Ingrid Kubin (ed.), Complexity and Geographical Economics, edition 127, pages 353-377, Springer.
    13. Coronese, Matteo & Occelli, Martina & Lamperti, Francesco & Roventini, Andrea, 2023. "AgriLOVE: Agriculture, land-use and technical change in an evolutionary, agent-based model," Ecological Economics, Elsevier, vol. 208(C).
    14. Tatiana Filatova & Dawn C. Parker & Anne van der Veen, 2009. "Agent-Based Urban Land Markets: Agent's Pricing Behavior, Land Prices and Urban Land Use Change," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-3.
    15. Saggau, Volker, 2012. "Viele Köche Verderben Den Brei – Agentenbasierte Simulationen Zum Föderalismusdurcheinander Während Der Ehec-Krise," 52nd Annual Conference, Stuttgart, Germany, September 26-28, 2012 133052, German Association of Agricultural Economists (GEWISOLA).
    16. Balmann, A. & Happe, K. & Kellermann, K. & Kleingarn, A., 2001. "Agricultural policy switchings – an agent-based approach," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 37.
    17. Carauta, Marcelo & Troost, Christian & Guzman-Bustamante, Ivan & Hampf, Anna & Libera, Affonso & Meurer, Katharina & Bönecke, Eric & Franko, Uwe & Ribeiro Rodrigues, Renato de Aragão & Berger, Thomas, 2021. "Climate-related land use policies in Brazil: How much has been achieved with economic incentives in agriculture?," Land Use Policy, Elsevier, vol. 109(C).
    18. Rasmussen, Svend & Damgaard, Martin, 2008. "Numerical Estimation of Agricultural Supply Functions - A Micro Economic Approach based on Mathematical Programming," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44181, European Association of Agricultural Economists.
    19. Schreinemachers, Pepijn & Berger, Thomas, 2006. "Simulating Farm Household Poverty: From Passive Victims to Adaptive Agents," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25479, International Association of Agricultural Economists.
    20. Robert Huber & Hang Xiong & Kevin Keller & Robert Finger, 2022. "Bridging behavioural factors and standard bio‐economic modelling in an agent‐based modelling framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 35-63, February.

    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:ags:aare05:137795. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaresea.html .

    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.