IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v268y2013icp48-54.html
   My bibliography  Save this article

Application of Bayesian networks for sustainability assessment in catchment modeling and management (Case study: The Hablehrood river catchment)

Author

Listed:
  • Keshtkar, A.R.
  • Salajegheh, A.
  • Sadoddin, A.
  • Allan, M.G.

Abstract

Catchment management is a process which increases the sustainable development and management of all catchment resources in order to maximize the balance among socioeconomic welfare and the sustainability of vital ecosystems. The increase of anthropogenic activities within river catchments causes degradation and serious problems for stakeholders and managers, particularly in arid and semi-arid regions. Although there are many techniques for solving these problems, it is not easy for catchment managers to apply them. An integrated Bayesian network model framework was applied to evaluate the sustainability of a semi-arid river catchment located in the Iranian Central Plateau river basin encompassing 32.6km2 area on the Hablehrood river catchment, located in the northern part of the Iranian Central Plateau river basin. The research illustrated the assessment of the relevant management problems, the model framework, and the techniques applied to extract input data. Results for the study area implementation and a suggestion for management are described and discussed.

Suggested Citation

  • Keshtkar, A.R. & Salajegheh, A. & Sadoddin, A. & Allan, M.G., 2013. "Application of Bayesian networks for sustainability assessment in catchment modeling and management (Case study: The Hablehrood river catchment)," Ecological Modelling, Elsevier, vol. 268(C), pages 48-54.
    • Handle: RePEc:eee:ecomod:v:268:y:2013:i:c:p:48-54
    DOI: 10.1016/j.ecolmodel.2013.08.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380013003967
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2013.08.003?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Uusitalo, Laura, 2007. "Advantages and challenges of Bayesian networks in environmental modelling," Ecological Modelling, Elsevier, vol. 203(3), pages 312-318.
    2. Barton, D.N. & Saloranta, T. & Moe, S.J. & Eggestad, H.O. & Kuikka, S., 2008. "Bayesian belief networks as a meta-modelling tool in integrated river basin management -- Pros and cons in evaluating nutrient abatement decisions under uncertainty in a Norwegian river basin," Ecological Economics, Elsevier, vol. 66(1), pages 91-104, May.
    3. Batchelor, Charles & Cain, Jeremy, 1999. "Application of belief networks to water management studies," Agricultural Water Management, Elsevier, vol. 40(1), pages 51-57, March.
    4. Ahmed Said, 2006. "The Implementation of a Bayesian Network for Watershed Management Decisions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(4), pages 591-605, August.
    5. Carmona, Gema & Varela-Ortega, Consuelo & Bromley, John, 2009. "Stakeholder involvement in water management using Object-oriented Bayesian networks and economic models in Spain," 2009 Conference, August 16-22, 2009, Beijing, China 49897, International Association of Agricultural Economists.
    6. Sadoddin, A. & Letcher, R.A. & Jakeman, A.J. & Newham, L.T.H., 2005. "A Bayesian decision network approach for assessing the ecological impacts of salinity management," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 69(1), pages 162-176.
    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. Pečarič Mirko, 2020. "Regulatory Cybernetics: Adaptability and Probability in the Public Administration’s Regulations," NISPAcee Journal of Public Administration and Policy, Sciendo, vol. 13(1), pages 133-156, June.
    2. Moe, S. Jannicke & Haande, Sigrid & Couture, Raoul-Marie, 2016. "Climate change, cyanobacteria blooms and ecological status of lakes: A Bayesian network approach," Ecological Modelling, Elsevier, vol. 337(C), pages 330-347.
    3. Ropero, R.F. & Aguilera, P.A. & Rumí, R., 2015. "Analysis of the socioecological structure and dynamics of the territory using a hybrid Bayesian network classifier," Ecological Modelling, Elsevier, vol. 311(C), pages 73-87.
    4. Jumeniyaz Seydehmet & Guang Hui Lv & Ilyas Nurmemet & Tayierjiang Aishan & Abdulla Abliz & Mamat Sawut & Abdugheni Abliz & Mamattursun Eziz, 2018. "Model Prediction of Secondary Soil Salinization in the Keriya Oasis, Northwest China," Sustainability, MDPI, vol. 10(3), pages 1-22, February.
    5. Mulazzani, Luca & Manrique, Rosa & Malorgio, Giulio, 2017. "The Role of Strategic Behaviour in Ecosystem Service Modelling: Integrating Bayesian Networks With Game Theory," Ecological Economics, Elsevier, vol. 141(C), pages 234-244.
    6. You, L. & Li, Y.P. & Huang, G.H. & Zhang, J.L., 2014. "Modeling regional ecosystem development under uncertainty – A case study for New Binhai District of Tianjin," Ecological Modelling, Elsevier, vol. 288(C), pages 127-142.
    7. Jim Lewis & Kerrie Mengersen & Laurie Buys & Desley Vine & John Bell & Peter Morris & Gerard Ledwich, 2015. "Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-21, 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. Barton, David N. & Benjamin, Tamara & Cerdán, Carlos R. & DeClerck, Fabrice & Madsen, Anders L. & Rusch, Graciela M. & Salazar, Álvaro G. & Sanchez, Dalia & Villanueva, Cristóbal, 2016. "Assessing ecosystem services from multifunctional trees in pastures using Bayesian belief networks," Ecosystem Services, Elsevier, vol. 18(C), pages 165-174.
    2. Kragt, Marit Ellen & Bennett, Jeffrey W., 2009. "Integrating economic values and catchment modelling," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 47956, Australian Agricultural and Resource Economics Society.
    3. Saravanan, V.S., 2010. "Negotiating participatory irrigation management in the Indian Himalayas," Agricultural Water Management, Elsevier, vol. 97(5), pages 651-658, May.
    4. Moe, S. Jannicke & Haande, Sigrid & Couture, Raoul-Marie, 2016. "Climate change, cyanobacteria blooms and ecological status of lakes: A Bayesian network approach," Ecological Modelling, Elsevier, vol. 337(C), pages 330-347.
    5. Jose-Luis Molina & Jose García-Aróstegui & John Bromley & Jose Benavente, 2011. "Integrated Assessment of the European WFD Implementation in Extremely Overexploited Aquifers Through Participatory Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(13), pages 3343-3370, October.
    6. Kleemann, Janina & Celio, Enrico & Fürst, Christine, 2018. "Reprint of “Validation approaches of an expert-based Bayesian Belief Network in northern Ghana, West Africa”," Ecological Modelling, Elsevier, vol. 371(C), pages 101-118.
    7. Zhang, Lu & Cui, Li & Chen, Lujie & Dai, Jing & Jin, Ziyi & Wu, Hao, 2023. "A hybrid approach to explore the critical criteria of online supply chain finance to improve supply chain performance," International Journal of Production Economics, Elsevier, vol. 255(C).
    8. Di Zhang & Xinping Yan & Zaili Yang & Jin Wang, 2014. "An accident data–based approach for congestion risk assessment of inland waterways: A Yangtze River case," Journal of Risk and Reliability, , vol. 228(2), pages 176-188, April.
    9. Zhang, Quanzhong & Wei, Haiyan & Liu, Jing & Zhao, Zefang & Ran, Qiao & Gu, Wei, 2021. "A Bayesian network with fuzzy mathematics for species habitat suitability analysis: A case with limited Angelica sinensis (Oliv.) Diels data," Ecological Modelling, Elsevier, vol. 450(C).
    10. Jim Lewis & Kerrie Mengersen & Laurie Buys & Desley Vine & John Bell & Peter Morris & Gerard Ledwich, 2015. "Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-21, July.
    11. Nicholson, Ann E. & Flores, M. Julia, 2011. "Combining state and transition models with dynamic Bayesian networks," Ecological Modelling, Elsevier, vol. 222(3), pages 555-566.
    12. Meineri, Eric & Dahlberg, C. Johan & Hylander, Kristoffer, 2015. "Using Gaussian Bayesian Networks to disentangle direct and indirect associations between landscape physiography, environmental variables and species distribution," Ecological Modelling, Elsevier, vol. 313(C), pages 127-136.
    13. Michail Tsagris, 2021. "A New Scalable Bayesian Network Learning Algorithm with Applications to Economics," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 341-367, January.
    14. Mostafa Shaaban & Carmen Schwartz & Joseph Macpherson & Annette Piorr, 2021. "A Conceptual Model Framework for Mapping, Analyzing and Managing Supply–Demand Mismatches of Ecosystem Services in Agricultural Landscapes," Land, MDPI, vol. 10(2), pages 1-19, January.
    15. De Iuliis, Melissa & Kammouh, Omar & Cimellaro, Gian Paolo & Tesfamariam, Solomon, 2021. "Quantifying restoration time of power and telecommunication lifelines after earthquakes using Bayesian belief network model," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    16. Abbas Roozbahani & Ebrahim Ebrahimi & Mohammad Ebrahim Banihabib, 2018. "A Framework for Ground Water Management Based on Bayesian Network and MCDM Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 4985-5005, December.
    17. Dayong Li & Zengchuan Dong & Liyao Shi & Jintao Liu & Zhenye Zhu & Wei Xu, 2019. "Risk Probability Assessment of Sudden Water Pollution in the Plain River Network Based on Random Discharge from Multiple Risk Sources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(12), pages 4051-4065, September.
    18. McVittie, Alistair & Norton, Lisa & Martin-Ortega, Julia & Siameti, Ioanna & Glenk, Klaus & Aalders, Inge, 2015. "Operationalizing an ecosystem services-based approach using Bayesian Belief Networks: An application to riparian buffer strips," Ecological Economics, Elsevier, vol. 110(C), pages 15-27.
    19. Tiller, Rachel Gjelsvik & Hansen, Lillian & Richards, Russell & Strand, Hillevi, 2015. "Work segmentation in the Norwegian salmon industry: The application of segmented labor market theory to work migrants on the island community of Frøya, Norway," Marine Policy, Elsevier, vol. 51(C), pages 563-572.
    20. Leonel Lara-Estrada & Livia Rasche & L. Enrique Sucar & Uwe A. Schneider, 2018. "Inferring Missing Climate Data for Agricultural Planning Using Bayesian Networks," Land, MDPI, vol. 7(1), pages 1-13, January.

    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:eee:ecomod:v:268:y:2013:i:c:p:48-54. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    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.