Using agent-based modeling to simulate the effect of price scenarios and free branching on water demand

Document Type : Original Article

Authors

1 Ph.D. Candidate of Economics, Ferdowsi University of Mashhad

2 Assistant Professor, Department of Economics, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Iran

3 Associate Professor, Department of Economics, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Iran

4 Assistant Professor, Department of Social Sciences,, Ferdowsi University of Mashhad, Iran

Abstract

Growing population of the cities along with the desire for better welfare and health has increased the water demand. On the other hand, many cities are located in the arid and semi-arid regions with the low rainfall and renewable water resources. Therefore it causes the water crisis. Shiraz is one of the metropolises that is facing this problem and in the warm seasons of the year experiences the drop in water pressure and water outages. Increasing the water supply, regardless of demand management, will exacerbate the crisis. Water pricing has been also one of the most important concerns of policymakers in demand management. Given the importance of this issue and also the role of social interactions among the consumers and the neighboring community network on the water consumption behavior, the present study concentrates on providing an agent-based framework for examining the water demand and changes in consumption behavior (diffusion process). The model has been calibrated for domestic water consumption in Shiraz for the years 2005-2019. Price increase scenarios (for all or only part of the consumers) as well as granting free branches have been simulated for the years 2020-2032. The results show that small increases in water prices do not have significant effect on consumption and cooperative behavior trend. Also, giving free branching to some consumers will intensify non-cooperative behavior among other consumers and increase the consumption sharply.

Keywords


خلیلی عراقی، م. و میرزایی قزانی، م .1393. روش‌های مدل‌سازی تطوری در اقتصاد (با تأکید بر عناصر مشترک سازنده آن‌ها). فصلنامه برنامه­ریزی و بودجه. 19 (2): 72-47.
Akhbari, M. 2012. Models for Management of Water Conflicts: A Case Study of the San-Juaquin Watershed, California. Ph.D. dissertation. Colorado State.
Akhbari, M. and Grigg, N.S. 2013. A Framework For an Agent-based Model to Manage Water Resources Conflicts. Water Resour Manage. 27 (11): 4039-4052.
Akhbari, M. and Grigg, N.S. 2015. Managing Water Resources Conflicts: Modelling Behavior in a Decision Tool. Water Resour Manage. 29 (14): 5201-5216.
Alimashhadi, A., Shafiee, M.E, Berglund, E. Z. 2017. Agent-based modeling to simulate the dynamics of urban water supply: Climate, population growth, and water shortages. Sustainable Cities and Society. 28: 420-434.
Anderson, P. W., Arrow, K. J. and Pines, D. (Eds.) .1988. The Economy as an Evolving Complex System II. Addison-Wesley. Reading. MA.
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.
Barthelemy, O., Moss, S., Downing, T. and Rouchier, J. 2001. Policy modelling with ABSS: The case of water demand management. Centre for Policy Modelling. Manchester Metropolitan University. Manchester. CPM Report.
Bepple, J. 2016. The application of agent based modeling to simulate residential water use responses to urban growth, regulation, and social influence in Kelowna British Columbia. Canada. (T). University of British Columbia.
Bernedo, M., Ferraro, P.J. and Price, M. 2014. The Persistent Impacts of Norm-Based Messaging and Their Implications for Water Conservation. Jounal of Consum Policy. 37(3): 437-452.
Chu, J., Wang, C., Chen, J. and Wang, H.  2009. Agent-based residential water use behaviour simulation and policy implications: A case-study in Beijing city. Water resources management. 23(15): 3267-3295.
Darbandsari, P., Kerachian, R. and Malakpour Estalaki, S. 2017. An Agent-based Behavioral Simulation Model for Residential Water Demand Management: A Case-Study of the Tehran City. Simulation Modelling Practice and Theory. 78:51-72.
Di Baldassarre, G., Wanders, N., AghaKouchak, A., Kuil, L., Rangecroft, S., Veldkamp, T. I. E. and Van Loon, A. F. 2018. Water shortages worsened by reservoir effects. Nature Sustainability. 1(11): 617-622.
Ding, N., Erfani, R., Mokhtar, H. and Erfani, T. 2016. Agent Based Modelling for Water Resource Allocation in the Transboundary Nile River. Water. 8(4): 139.
Downing, T.E., Moss, S. and Pahl-Wostl, C. 2000. Understanding Climate Policy Using Participatory Agent-Based Social Simulation. Lect Notes Comput Sci 1979:198–213
Edwards, M., Ferrand, N., Goreaud, F. and Huet, S. 2005. The relevance of aggregating a water consumption model cannot be disconnected from the choice of information available on the resource. Simul. Model. Pract. Theory. 13 (4): 287-307.
Epstein, J. M. and Axtell, R L. 1996.  Growing Artificial Societies: Social Science from the Bottom Up. The MIT Press.
Ernst, A., Schulz, C., Schwarz, Nina. and Janisch, S. 2005. Shallow and deep modeling of water use in a large. Spatially explicit coupled simulation system. 3rd Conference of the European Social Simulation Association (ESSA). Koblenz. Germany.
Farhadi, S., Nikoo, M.R., Rakhshandehroo, Gh. R., Akhbari, M. and Alizadeh, M.R. 2016. An agent-based-nash modeling framework for sustainable groundwater management: A case study. Agricultural Water Management. 177: 348-358.
Ferraro, P.J., Miranda, JJ. And Price, MK. 2011. The Persistence of Treatment Effects with Norm-Based Policy Instruments: Evidence from a Randomized Environmental Policy Experiment. American Economic Review. 101 (3): 318-22.
Holland, J.H. and Miller, J. H. 1991. Artificial adaptive agents in economic theory. American Economic Review. 81(2): 365-371.
House-Peters, L. a. and Chang, H. 2011. Urban water demand modeling: Review of concepts, methods, and organizing principles. Water Resources Research. 47(5): 5.
Jackson, MO. and Yariv, L. 2007. Diffusion of Behavior and Equilibrium Properties in Network Games. American Economic Review. 97 (2): 92-98.
Jaeger, C.M. and Schultz, P. W. 2017. Coupling social norms and commitments: Testing the under detected nature of social influence, Journal of Environmental Psychology. 51: 199-208.
Linkola, L., Andrews, C.J. and Schuetze, T.  2013. An Agent Based Model of Household Water Use. Water. 5(3): 1082-1100.
Madani, K., AghaKouchak, A. and Mirchi, A. 2016. Iran’s Socioeconomic Drought: Challenges of a Water-Bankrupt Nation. Iranian Studies. 49(6): 997-1016.
Moss, S. and Edmonds, B. 2005. Sociology and Simulation: Statistical and Qualitative cross validation. American Journal of Sociology. 110(4): 1095–1131.
 Otaki, Y., Ueda, K. and Sakura, O. 2017.  Effects of feedback about community water consumption on residential water conservation. Journal of Cleaner Production. 143: 719-730.
Rixon A., Moglia, M. and Burn, S. 2007. Exploring water conservation behaviour through participatory agent-based modelling .Topics on System Analysis and Integrated Water Resources Management.  73-96.
Schelling, T.1971. Dynamic models of segregation. Journal of Mathematical Sociology. 1: 143-186.
Tembata, K. and Takeuchi, K. 2018. Collective decision making under drought: An empirical study of water resource management in Japan. Water Resources and Economics. 22: 19-31.
Thaler, R.H. and Sunstein, C.R. 2008. Nudge: Improving Decisions about Health, Wealth, and Happiness. New Haven: Yale University Press.
Wilensky, U., and Rand, W. 2015. An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo. Cambridge, MA: MIT Press.
World Bank. 2017. Iran Economic Monitor, spring 2017: Oil-Driven Recovery. Washington, DC.
Young, H.P. 1999. Diffusion in Social Networks. Work. Pap. 2, Brookings Inst. Washington D.C.
Yuan, X.C., Wei, Y.M., Pan, S.Y. and Jin, J.L. 2014. Urban household water demand in Beijing by 2020: an agent-based model. Water Resour Manage. 28 (10): 2967-2980.
Zhao, J., Cai, X. and Wang, Z. 2013. Comparing administered and market-based water allocation systems through a consistent agent-based modeling framework. Journal of Environmental Management. 123: 120-130