Using Agent-Based Modeling for Water Resources Planning and Management
Publication: Journal of Water Resources Planning and Management
Volume 141, Issue 11
Abstract
Agent-based systems have been developed for many scientific applications and simulation studies to model a group of actors and their interactions based on behavioral rules. Agent-based models and multiagent systems simulate the emergence of system-level properties based on the actions of adaptive agents that interact with other agents, react to environmental signals, and optimize decisions to achieve individual goals. In water resources planning and management, agent-based modeling has been applied to explore, simulate, and predict the performance of infrastructure design and policy decisions as they are influenced by human decision making, behaviors, and adaptations. The goal of this paper is to provide a comprehensive introduction to agent-based modeling for water resources researchers, students, and practitioners, and to explore water resources systems as complex adaptive systems that can be studied using agent-based modeling. Agent-based modeling is defined, and the characteristics of complex adaptive systems that necessitate its use are described. A literature review is presented to demonstrate research in the field that uses agent-based modeling to gain insight for water resources management. Two illustrative case studies of agent-based water resources systems models are developed and described. The case studies demonstrate the use of reactive and active (e.g., optimizing) agents for simulating water resources planning problems. The limitations in applying agent-based modeling and the insights that are expected from further investigations are summarized.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The author acknowledges support for this research provided by the North Carolina State Water Resources Research Institute. Thanks to Michael Ehsan Shafiee, Daniel Dreano, and Alireza Mashhadi Ali for their assistance with modeling and identifying data. Feedback provided by anonymous reviewers is greatly appreciated.
References
AC-ERE (Advisory Committee for Environmental Research and Education). (2009). “Transitions and tipping points in complex environmental systems.”, National Science Foundation, Arlington, VA.
Altaweel, M., Alessa, L., and Kliskey, A. (2009). “Forecasting resilience in arctic societies: Creating tools for assessing social-hydrological systems.” J. Am. Water Resour. Assoc., 45(6), 1379–1389.
An, L. (2012). “Modeling human decisions in coupled human and natural systems: Review of agent-based models.” Ecol. Model., 229, 25–36.
Athanasiadis, I. N., Mentes, A. K., Mitkas, P. A., and Mylopoulos, Y. A. (2005). “A hybrid agent-based model for estimating residential water demand.” Simulation, 81(3), 175–187.
Barreteau, O., and Bousquet, F. (2000). “Shadoc: A multi-agent model to tackle viability of irrigated systems.” Ann. Operat. Res., 94(1–4), 139–162.
Becu, N., Perez, P., Walker, A., Barreteau, O., and Le Page, C. (2003). “Agent based simulation of a small catchment water management in northern Thailand: Description of the CATCHSCAPE model.” Ecol. Modell., 170(2–3), 319–331.
Berger, T., Birner, R., Diaz, J., McCarthy, N., and Wittmer, H. (2007). “Capturing the complexity of water uses and water users within a multi-agent framework.” Water Resour. Manage., 21(1), 129–148.
Berger, T., and Ringler, C. (2002). “Trade-offs, efficiency gains and technical change—Modeling water management and land use within a multiple agent framework.” Q. J. Int. Agric., 41(1–2), 119–144.
Bharathy, G., and Silverman, B. (2013). “Holistically evaluating agent-based social systems models: A case study.” Simul. Trans. Soc. Model. Simul. Int., 89(1), 102–135.
Bohlmann, J., Calantone, R., and Zhao, M. (2010). “The effects of market network heterogeneity on innovation diffusion: An agent-based modeling approach.” J. Innov. Manage., 27(5), 741–760.
Bonabeau, E. (2002). “Agent-based modeling: Methods and techniques for simulating human systems.” Proc. Natl. Acad. Sci. U. S. A., 99(Suppl 3), 7280–7287.
Braden, J. B., et al. (2009). “Social science in a water observing system.” Water Resour. Res., 45(11), W11301.
Brill, E. D., Jr. (1972). “Economic efficiency and equity in water quality management.” Ph.D. thesis, Johns Hopkins Univ., Baltimore, MD.
Brill, E. D., Jr. (1979). “The use of optimization models in public-sector planning.” Manage. Sci., 25(5), 413–422.
Brill, E. D., Jr., Eheart, J. W., Kshirsagar, S., and Lence, B. (1984). “Water quality impacts of biochemical oxygen demand under transferable discharge permit programs.” Water Resour. Res., 20(4), 445–455.
Chu, J., Wang, C., Chen, J., and Wang, H. (2009). “Agent-based residential water use behavior simulation and policy implications: A case-study in Beijing city.” Water Resour. Manage., 23(15), 3267–3295.
Downing, T. E., Moss, S., and Pahl-Wostl, C. (2000). “Understanding climate policy using participatory agent-based social simulation.” Multi Agent Based Simul., 1979, 198–213.
Edmonds, B., and Chattoe, E. (2005). “When simple measures fail: Characterising social networks using simulation.” Social network analysis: Advances and empirical applications forum, Manchester Metropolitan Univ. Business School, Manchester, U.K.
Epstein, J. (2006). Generative social science: Studies in agent-based computational modeling, Princeton University Press, Princeton, NJ.
Fischer, J. M., and Amekudzi, A. (2011). “Quality of life, sustainable civil infrastructure, and sustainable development: Strategically expanding choice.” J. Urban Plan. Dev., 39–48.
Forrester, J. (1961). Industrial dynamics, Pegasus Communications, Waltham, MA.
Galán, J. M., López-Paredes, A., and del Olmo, R. (2009). “An agent-based model for domestic water management in Valladolid metropolitan area.” Water Resour. Res., 45(5), W05401.
Giacomoni, M., Kanta, L., and Zechman, E. M. (2013). “A complex adaptive systems approach to simulate the sustainability of water resources and urbanization.” J. Water Resour. Plan. Manage., 554–564.
Gilbert, N. (2008). Agent-based models, Sage, Los Angeles.
Gratch, J., and Marsella, S. (2004). “A domain-independent framework for modeling emotion.” J. Cognit. Syst. Res., 5(4), 269–306.
Graves, G., Hatfield, G., and Whinston, A. (1972). “Mathematical programming for regional water quality management.” Water Resour. Res., 8(2), 273–290.
Guiliani, M., and Castelletti, A. (2013). “Assessing the value of cooperation and information exchange in large water resources systems by agent-based optimization.” Water Resour. Res., 49(7), 3912–3926.
Hassan, S., Arroyo, J., Galan, J. M., Antunes, L., and Pavon, J. (2013). “Asking the oracle: Introducing forecasting principles into agent-based modelling.” J. Artif. Soc. Social Simul., 16(3), 13.
Holland, J. (1995). Hidden order: How adaptation builds complexity, Perseus Books, Reading, MA.
House-Peters, L. A., and Chang, H. (2011). “Urban water demand modeling: Review of concepts, methods, and organizing principles.” Water Resour. Res., 47(5), W05401.
Huang, D.-B., et al. (2007). “Discrete event simulation for exploring strategies: An urban water management case.” Environ. Sci. Technol., 41(3), 915–921.
Hwang, C.-L., and Masud, A. (1979). “Multiple objective decision making—Methods and applications: A state-of-the-art survey.” Lecture notes in economics and mathematical systems, M. Beckmann and H. Kunzi, eds., Vol. 164, Springer, New York.
Janssen, M., and Ostrom, E. (2006). “Empirically based, agent-based models.” Ecol. Soc., 11(2), 37.
Kanta, L., and Zechman, E. M. (2014). “Complex adaptive systems framework to assess supply-side and demand-side management for urban water resources.” J. Water Resour. Plan. Manage., 75–85.
Kotz, C., and Hiessl, H. (2005). “Analysis of system innovation in urban water infrastructure systems: An agent-based modelling approach.” Water Sci. Technol. Water Supply, 5(2), 135–144.
Liebman, J. (1976). “Some simple-minded observations on the role of optimization in public systems decision-making.” Interfaces, 6(4), 102–108.
Lopez-Paredes, A., Sauri, D., and Galan, J. M. (2005). “Urban water management with artificial societies of agents: The FIRMABAR simulator.” Simulation, 81(3), 189–199.
Macal, C. M., and North, M. J. (2010). “Tutorial on agent-based modeling and simulation.” J. Simul., 4(3), 151–162.
Mashhadi Ali, A. (2014). “An integrated framework for assessing the dynamics of population growth and climate change for urban water resources management.” M.S. thesis, North Carolina State Univ., Raleigh, NC.
Miller, J., and Page, S. (2007). Complex adaptive systems: An introduction to computational models of social life, Princeton University Press, Princeton, NJ.
Mitchell, M. (2009). Complexity: A guided tour, Oxford University Press, Oxford, U.K.
Montalto, F., et al. (2013). “Decentralized green infrastructure: The importance of stakeholder behaviour in determining spatial and temporal outcomes.” Struct. Infrastruct. Eng., 9(12), 1187–1205.
Moss, S., and Edmonds, B. (2005). “Sociology and simulation: Statistical and qualitative cross-validation.” Am. J. Soc., 110(4), 1095–1131.
Nasiri, F., Savage, T., Wang, R., Barawid, N., and Zimmerman, J. (2013). “A system dynamics approach for urban water reuse planning: A case study from the Great Lakes region.” Stochastic Environ. Res. Risk Assess., 27(3), 675–691.
Ng, T. L., Eheart, J. W., Cai, X., and Braden, J. B. (2011). “An agent-based model of farmer decision-making and water quality impacts at the watershed scale under markets for carbon allowances and a second-generation biofuel crop.” Water Resour. Res., 47(9), W09519.
Niazi, M., and Hussain, A. (2011). “Agent-based computing from multi-agent systems to agent-based models: A visual survey.” Scientometrics, 89(2), 479–499.
Pahl-Wostl, C. (1995). The dynamic nature of ecosystems: Chaos and order entwined, Wiley, New York.
Panebianco, A., and Pahl-Wostl, C. (2006). “Modelling socio-technical transformations in wastewater treatment: A methodological proposal.” Technovation, 26(9), 1090–1100.
Railsback, S. F., and Grimm, V. (2012). Agent-based and individual-based modeling: A practical introduction, Princeton University Press, Princeton, NJ.
Reeves, H. W., and Zellner, M. L. (2010). “Linking MODFLOW with an agent-based land-use model to support decision making.” Groundwater, 48(5), 649–660.
Refsgaard, J., van der Sluijs, J., Hojberg, A., and Vanrolleghem, P. (2007). “Uncertainty in the environmental modelling process—A framework and guidance.” Environ. Model. Softw., 22(11), 1543–1556.
Riegels, N., et al. (2013). “Systems analysis approach to the design of efficient water pricing policies under the EU water framework directive.” J. Water Resour. Plan. Manage., 574–582.
Rittel, H., and Webber, M. (1973). “Dilemmas in a general theory of planning.” Pol. Sci., 4(2), 155–169.
Scheffer, M., et al. (2012). “Anticipating critical transitions.” Science, 338(6105), 344–348.
Schluter, M., and Pahl-Wostl, C. (2007). “Mechanisms of resilience in common—pool resource management systems: An agent-based model of water use in a river basin.” Ecol. Soc., 12(2).
Schwarz, N., and Ernst, A. (2009). “Agent-based modeling of the diffusion of environmental innovations—An empirical approach.” Tech. Forecast. Soc. Change, 76(4), 497–511.
Shafiee, M. E., and Zechman, E. M. (2013). “An agent-based modeling framework for sociotechnical simulation of water distribution contamination events.” J. Hydroinform., 15(3), 862–880.
Siebers, P., Macal, C., Garnett, J., Buxton, D., and Pidd, M. (2010). “Discrete-event simulation is dead, long live agent-based simulation!” J. Simul., 4(3), 204–210.
Thomann, R., and Mueller, J. (1987). Principles of surface water quality modeling and control, Harper Collins, New York.
Tillman, D., Larsen, T. A., Pahl-Wostl, C., and Gujer, W. (1999). “Modeling the actors in water supply systems.” Water Sci. Technol., 39(4), 203–211.
Tillman, D., Larsen, T. A., Pahl-Wostl, C., and Gujer, W. (2001). “Interaction analysis of stakeholders in water supply systems.” Water Sci. Technol., 43(5), 319–326.
Tillman, D., Larsen, T. A., Pahl-Wostl, C., and Gujer, W. (2005). “Simulating development strategies for water supply systems.” J. Hydroinform., 7(1), 41–51.
van Oel, P., Krol, M., Hoekstra, A., and Taddei, R. (2010). “Feedback mechanisms between water availability and water use in a semi-arid river basin: A spatially explicit multi-agent simulation approach.” Environ. Model. Software, 25(4), 433–443.
Widener, M., Horner, M., and Metcalf, S. (2013). “Simulating the effects of social networks on a population’s hurricane evacuation participation.” J. Geograph. Syst., 15(2), 193–209.
Woolridge, M. (2002). An introduction to multiagent systems, Wiley, Hoboken, NJ.
Yang, Y.-C. E., Cai, X., and Stipanović, D. M. (2009). “A decentralized optimization algorithm for multiagent system-based watershed management.” Water Resour. Res., 45(8), W08430.
Zechman, E. M. (2011). “Agent-based modeling to simulate contamination events and evaluate threat management strategies in water distribution systems.” Risk Anal., 31(5), 758–772.
Zellner, M. L. (2007). “Generating policies for sustainable water use in complex scenarios: An integrated land-use and water-use model of Monroe County, Michigan.” Environ. Plan. B Plan. Des., 34(4), 664–686.
Zhang, Y., Wu, Y., Yu, H., Dong, Z., and Zhang, B. (2013). “Trade-offs in designing water pollution trading policy with multiple objectives: A case study in the Tai Lake basin, China.” Environ. Sci. Pol., 33, 295–307.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 141 • Issue 11 • November 2015
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Apr 29, 2014
Accepted: Mar 10, 2015
Published online: May 12, 2015
Discussion open until: Oct 12, 2015
Published in print: Nov 1, 2015
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.