Abstract
This paper presents a comparative analysis of System Dynamics Modelling (SDM) and Object-Oriented Bayesian Networks (OOBN). Both techniques are extensively used for water resources modelling due to their flexibility, effectiveness in assessing different management options, ease of operation and suitability for encouraging stakeholder involvement. Conversely, both approaches have several important differences that make them complementary. For example, while SDM is more suitable for simulating the feedback dynamics of processes, OOBN modelling is a powerful tool for modelling systems with uncertain inputs (or outputs) characterised by probability distributions. This comparative analysis is applied to the Kairouan aquifer system, Tunisia, where the aquifer plays an essential role for socio-economic development in the region. Both models produced comparable results using baseline data, and show their complementarity through a suite of scenario tests. It is shown that reducing pumping of groundwater to coastal cities may prove the key to reducing the current aquifer deficit, though local demand reduction must be considered to preserve the agricultural economy. It is suggested that water management assessment should be tackled using both approaches to complement each other, adding depth and insight, and giving a more coherent picture of the problem being addressed, allowing for robust policy decisions to be made.
Similar content being viewed by others
References
Arnell NW, Livermore MJL, Kovats S, Levy PE, Nicholls R, Parry ML, Gaffin SR (2004) Climate and socio-economic scenarios for global-scale climate change impact assessments: Characterising the SRES storylines. Glob Environ Chang 14:3–20
Bromley J, Jackson N, Clymer O, Giacomello A, Jensen F (2005) The use of Hugin to develop Bayesian Network as an aid to integrated water resource planning. Environ Model Softw 20:231–242
Cain J (2001) Planning Improvements in Natural Resources Management. Centre for Ecology and Hydrology, Wallingford, UK
Castelletti A, Soncini-Sessa R (2007) Bayesian Networks and participatory modelling in water resource management. Environ Model Softw 22:1075–1088
Chahed J, Hamdane A, Besbes M (2008) A comprehensive water balance of Tunisia: Blue water, green water, virtual water. Water International 33:415–424
Chenini F, Huibers FP, Agodzo SK, van Lier JB, Duran A (2003) Use of wastewater in irrigated agriculture. Country studies from Bolivia, Ghana and Tunisia. vol. 3. Wageningen, WUR, Tunisia. ISBN 90-6754-703-4
Chung G, Lansey K, Blowers P, Brooks PW, Stewart S, Wilson P (2008) A general water supply planning model: Evaluation of decentralized treatment. Environ Model Softw 23:893–905
Falkenmark M, Molden D (2008) Wake up to realities of river basin closure. International Journal of Water Resource Development 24:201–215
Farmani R, Jørgen Henriksen H, Savic D (2009) An evolutionary Bayesian belief network methodology for optimum management of groundwater contamination. Environ Model Softw 24(3):303–310
Ford A (1999) Modelling the environment: An introduction to system dynamics modeling of environmental systems. Island Press, Washington, DC
Forrester J (1961) Industrial dynamics. Pegasus Communications, Waltham, MA
Han J, Hayashi Y, Cao X, Imura H (2009) Application of an integrated system dynamics and cellular automata model for urban growth assessment: A case study of Shanghai. China Landscape and Urban Planning 91:133–141
Henriksen HJ, Barlebo HC (2007) Reflections on the use of Bayesian networks for adaptive management. J Environ Manag. doi:10.1016/j.jenvman.2007.05.009
Henriksen HJ, Rasmussen P, Bandt G, von Bulow D, Jensen FV (2007) Public participation modelling using Bayesian networks in management of groundwater contamination. Environ Model Softw 22:1101–1113
Jensen FV (1996) An introduction to Bayesian networks. UCL Press, London
Khan S, Yufeng L, Ahmad A (2009) Analysing complex behaviour of hydrological systems through a system dynamics approach. Environ Model Softw 24:1363–1372
Kojiri T, Hori T, Nakatsuka J, Chong T-S (2008) World continental modelling for water resources using system dynamics. Phys Chem Earth 33:304–311
Le Goulven P, Leduc C, Salah Bachta M, Poussin J-C (2009) Sharing scarce resources in a Mediterranean river basin: Wadi Merguellil in central Tunisia. Societies, Environments, and Development, River Basin Trajectories, pp 147–170
Leduc C, Ben Ammar S, Favreau G, Beji R, Virrion R, Lacombe G, Tarhouni J, Aouadi C, Zenati Chelli B, Jebnoun N, Oi M, Michelot JL, Zouari K (2007) Impacts of hydrological changes in the Mediterranean zone: Envrionmental modifications and rural development in the Merguellil catchment, central Tunisia. Hydrol Sci J 52:1162–1178
Luc JP (2005) Blue and green water accounting: The Merguellil River basin, Report for the Comprehensive Assessment of Water Management in Agriculture. International Water Management Institute. p. 78.
Martinez-Santos P, Henriksen HJ, Zorrilla P, Martinez-Alfaro PE (2010) Comparative reflections on the use of modelling tools in conflictive water management settings: The Mancha Occidental aquifer. Spain Environmental Modelling and Software 25:1439–1449
Molina JL, Bromley J, García-Aróstegui JL, Sullivan C, Benavente J (2010) Integrated water resources management of overexploited hydrogeological systems using Object-Oriented Bayesian Networks. Environ Model Softw 25:383–397
Molina JL, Farmani R, Bromley J (2011) Aquifers management through evolutionary bayesian networks: The Altiplano case study (SE Spain). Water Resources Management. doi:10.1007/s11269-011-9893-z
Muetzelfeldt R (2010) Extended System Dynamics modelling of the impacts of food system drivers on food security, livelihoods and the environment, Report for the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), p. 27
Muetzelfeldt R, Massheder J (2003) The Simile visual modelling environment. Eur J Agron 18:345–358
Mulligan M, Wainwright J (2004) Modelling and model building. In: Wainwright J, Mulligan M (eds) Environmental modelling: Finding simplicity in complexity: West sussex. England, UK, pp 7–73
Ordóñez Galán C, Matías JM, Rivas T, Bastante FG (2009) Reforestation planning using Bayesian Networks. Environ Model Softw 24(11):1285–1292
Pearl J (1988) Probabilistic reasoning in intelligent systems. Morgan Kaufmann, San Mateo, CA
Ribarova I, Assimacopoulos D, Jeffrey P, Daniell K, Inman D, Vamvakeridou-Lyroudia LS, Melin T, Kalinkov P, Ferrand N, Tarnacki K (2011) Research-supported participatory planning for water stress mitigation. J Environ Plan Manag 54:283–300
Ross A, Martinez-Santos P (2010) The challenge of groundwater governance: Case studies from Spain and Australia. Reg Environ Chang 10:299–310
Simonovic S (2002) World water dynamics: Global modelling of water resources. Journal of Environmental Modelling 66:249–267
Stave KA (2003) A system dynamics model to facilitate public understanding of water management options in Las Vegas. Nevada Journal of Environmental Management 67:303–313
Sterman JD (2000) Business dynamics, systems thinking and modeling for a complex world. Irwin/McGraw-Hill, New York
Sušnik J, Vamvakeridou-Lyroudia LS, Savić DA, Kapelan Z (2012) Integrated system dynamics modelling for water scarcity assessment: Case study of the Kairouan region. Sci Total Environ 440:290–306. doi:10.1016/j.scitotenv.2012.05.085
Tidwell VC, Passell HD, Conrad SH, Thomas RP (2004) System dynamics modeling for community-based water planning: Application to the Middle Rio Grande. Aquat Sci 66:357–372
Unlu M, Kanber R, Koc LD, Tekin S, Kapur B (2011) Effects of deficit irrigation on the yield and yield components of drip irrigated cotton in a Mediterranean environment. Agric Water Manage 98(4):597–605
Vamvakeridou-Lyroudia, LS, Leduc C, Savic DA (2008) System Dynamics Modelling: The Merguellil valley water system, Report No.2008/04, Centre for Water Systems, School of Engineering, Computing and Mathematics, University of Exeter, Exeter, U.K., 98p, (accessible at www.ex.ac.uk/cws).
Vamvakeridou-Lyroudia LS, Inman D, Ribarova I, Savić DA (2009) Modelling water saving in the upper Iskar region, Proc. 10th Int. Conf. on Computing and Control for the Water Industry CCWI 2009, 1–3 Sept. 2009 University of Sheffield, UK, 767–773
Varis O, Kuikka S (1999) Learning Bayesian decision analysis by doing: Lessons from environmental and natural resources management. Ecol Model 119:177–195
World Water Assessment Programme (WWAP) (2009) The United Nations World Water Development Report 3: Water in a Changing World. Paris: UNESCO, and London: Earthscan.
Acknowledgements
The SDM work presented here was partially funded by the EU FP7 project WASSERMed (European Framework Project Number 244255, www.wassermed.eu). JS, LVL, ZK and DS acknowledge the sharing of data by WASSERMed partners, particularly INAT (Institut National Agronomique de Tunisie; especially Z. Lili-Chabaane, H. Chakroun and I. Oueslati) and IRD (Institut de Recherche pour le Développement; especially C. Leduc and A. Ogilvie). We thank the Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Italy for the rainfall forecast.
JLM acknowledges the contributions of: Dr. T. Jakeman (Integrated Catchment Assessment and Management Centre (iCAM)), for support in this research line. The study for OOBN has been partially supported by the European Community FP7 project GENESIS (226536) and from the subprogram Juan de la Cierva (2010) of the Spanish Ministry of Science and Innovation as well as from the Plan Nacional I + D + i 2008–2011 of the Spanish Ministry of Science and Innovation (CGL2009-13238-C02-01 and CGL2009-13238-C02-02).
We thank two anonymous reviewers for suggesting considerable improvements to the manuscript.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Sušnik, J., Molina, JL., Vamvakeridou-Lyroudia, L.S. et al. Comparative Analysis of System Dynamics and Object-Oriented Bayesian Networks Modelling for Water Systems Management. Water Resour Manage 27, 819–841 (2013). https://doi.org/10.1007/s11269-012-0217-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-012-0217-8