Agent-Based Approach on Water Resources Management: A Modified Systematic Review

Yıl 2022, Cilt: 6 Sayı: 2, 202 - 236, 25.07.2022

Kamil Aybuğa Aysel Gamze Yücel Işıldar

https://doi.org/10.31807/tjwsm.1123808

Öz

Social, economic, and ecological dimensions of water resources make water management a highly complex domain related to many intertwined human-nature systems. Therefore, the decision and implementation of sustainable policies require following the evidence-based approach. Agent-Based Modeling and Simulation is one of the latest computer-aided modeling and simulation applications widely used to understand the phenomena associated with water-related/human-oriented engineering systems. In this study, conducting a modified systematic review approach, a field-specific review of the 128 articles on water resources management with Agent-Based Modeling was presented. Application areas of Agent-Based Modeling in water resources management and examples of its use as a decision support tool were evaluated. As an integrative systematic review of Web of Science, Science Direct, and Google Scholar, this study summarizes the leading work of Agent-Based Modeling applications on water resources management. Current trends show that water research professionals have often used Agent-Based Modeling as a social simulation tool. Due to its role in facilitating interdisciplinary research, its application area is widening. However, there is a need for a comprehensible and open share of application-oriented information to guide the scientific community.

Anahtar Kelimeler

Agent-Based Modelling, ABM, Simulation, Water Resources Management, Sustainability

Kaynakça

• Aghaie, V., Alizadeh, H., & Afshar, A. (2020). Agent-Based hydro-economic modelling for analysis of groundwater-based irrigation Water Market mechanisms. Agricultural Water Management, 234. doi:10.1016/j.agwat.2020.106140
• Aghaie, V., Alizadeh, H., & Afshar, A. (2020). Emergence of social norms in the cap-and-trade policy: An agent-based groundwater market. Journal of Hydrology, 588. doi:10.1016/j.jhydrol.2020.125057
• Aguirre, R., & Nyerges, T. (2014). An Agent-Based Model of Public Participation in Sustainability Management. Journal of Artificial Societies and Social Simulation, 17(1), 7. doi:10.18564/jasss.2297
• Akhbari, M., & Grigg, N. S. (2013). A Framework for an Agent-Based Model to Manage Water Resources Conflicts. Water Resources Management, 27(11), 4039-4052. doi:10.1007/s11269-013-0394-0
• Al-Amin, S., Berglund, E. Z., & Larson, K. L. (2015). Agent-Based Modeling to Simulate Demand Management Strategies for Shared Groundwater Resources. In World Environmental and Water Resources Congress 2015 (pp. 2067-2072).
• Al-Amin, S., Berglund, E. Z., & Mahinthakumar, K. (2016). Coupling Agent-Based and Groundwater Modeling to Explore Demand Management Strategies for Shared Resources. In World Environmental and Water Resources Congress 2016 (pp. 141-150).
• Al-Amin, S., Berglund, E. Z., Mahinthakumar, G., & Larson, K. L. (2018). Assessing the effects of water restrictions on socio-hydrologic resilience for shared groundwater systems. Journal of Hydrology, 566, 872-885. doi:10.1016/j.jhydrol.2018.08.045
• Anbari, M. J., Zarghami, M., & Nadiri, A.-A. (2021). An uncertain agent-based model for socio-ecological simulation of groundwater use in irrigation: A case study of Lake Urmia Basin, Iran. Agricultural Water Management, 249. doi:10.1016/j.agwat.2021.106796
• Anthony, P., & Birendra, K. C. (2017). Improving irrigation water management using agent technology. New Zealand Journal of Agricultural Research, 61(4), 425-439. doi:10.1080/00288233.2017.1402788
• Arasteh, M. A., & Farjami, Y. (2021). New hydro-economic system dynamics and agent-based modeling for sustainable urban groundwater management: A case study of Dehno, Yazd Province, Iran. Sustainable Cities and Society, 72. doi:10.1016/j.scs.2021.103078 Athanasiadis, I. N., Mentes, A. K., Mitkas, P. A., & Mylopoulos, Y. A. (2016). A Hybrid Agent-Based Model for Estimating Residential Water Demand. Simulation, 81(3), 175-187. doi:10.1177/0037549705053172
• Aydin, M. E., & Keleş, R. (2021). A multi agent-based approach for energy efficient water resource management. Computers & Industrial Engineering, 151. doi:10.1016/j.cie.2020.106679
• Baeza, A., Bojorquez-Tapia, L. A., Janssen, M. A., & Eakin, H. (2019). Operationalizing the feedback between institutional decision-making, socio-political infrastructure, and environmental risk in urban vulnerability analysis. J Environ Manage, 241, 407-417. doi:10.1016/j.jenvman.2019.03.138
• Bahrami, N., Afshar, A., & Afshar, M. H. (2022). An agent-based framework for simulating interactions between reservoir operators and farmers for reservoir management with dynamic demands. Agricultural Water Management, 259. doi:10.1016/j.agwat.2021.107237
• Bakarji, J., O’Malley, D., & Vesselinov, V. V. (2017). Agent-Based Socio-Hydrological Hybrid Modeling for Water Resource Management. Water Resources Management, 31(12), 3881-3898. doi:10.1007/s11269-017-1713-7
• Bakhtiari, P. H., Nikoo, M. R., Izady, A., & Talebbeydokhti, N. (2020). A coupled agent-based risk-based optimization model for integrated urban water management. Sustainable Cities and Society, 53. doi:10.1016/j.scs.2019.101922
• Barreteau, O., Bousquet, F., Millier, C., & Weber, J. (2004). Suitability of Multi-Agent Simulations to study irrigated system viability: application to case studies in the Senegal River Valley. Agricultural Systems, 80(3), 255-275. doi:10.1016/j.agsy.2003.07.005
• Barreteau, O., & Abrami, G. (2007). Variable time scales, agent-based models, and role-playing games: The PIEPLUE river basin management game. Simulation & Gaming, 38(3), 364-381. doi:10.1177/1046878107300668
• Barthel, R., Rojanschi, V., Wolf, J., & Braun, J. (2005). Large-scale water resources management within the framework of GLOWA-Danube. Part A: The groundwater model. Physics and Chemistry of the Earth, Parts A/B/C, 30(6), 372-382. https://doi.org/https://doi.org/10.1016/j.pce.2005.06.003
• Bars, M. L., & Attonaty, J. M. (2001, 7-9 Nov. 2001). A multi-agent system to the common management of a renewable resource: application to water sharing. Paper presented at the Proceedings 13th IEEE International Conference on Tools with Artificial Intelligence. ICTAI 2001.
• Becu, N., Perez, P., Walker, A., Barreteau, O., & Page, C. L. (2003). Agent based simulation of a small catchment water management in northern Thailand. Ecological Modelling, 170(2-3), 319-331. doi:10.1016/s0304-3800(03)00236-9
• Belaqziz, S., Fazziki, A. E., Mangiarotti, S., Le Page, M., Khabba, S., Raki, S. E., . . . Jarlan, L. (2013). An Agent based Modeling for the Gravity Irrigation Management. Procedia Environmental Sciences, 19, 804-813. doi:10.1016/j.proenv.2013.06.089
• Berglund, E. Z. (2015). Using Agent-Based Modeling for Water Resources Planning and Management. Journal of Water Resources Planning and Management, 141(11), 04015025. doi:doi:10.1061/(ASCE)WR.1943-5452.0000544
• Bitterman, P., & Koliba, C. J. (2020). Modeling Alternative Collaborative Governance Network Designs: An Agent-Based Model of Water Governance in the Lake Champlain Basin, Vermont. Journal of Public Administration Research and Theory, 30(4), 636-655. doi:10.1093/jopart/muaa013
• Bonté, B., Farolfi, S., Ferrand, N., Abrami, G., Diallo, M. C., Dubois, D., . . . Gaudi, W. A. (2019). Building new kinds of meta-models to analyse experimentally (companion) modelling processes in the field of natural resource management. Environmental Modelling & Software, 120. doi:10.1016/j.envsoft.2019.07.011
• Bonabeau, E. (2001). Agent-based modeling: methods and techniques for simulating human systems. In Proceedings of National Academy of Sciences 99(3): 7280-7287.
• Bourceret, A., Amblard, L., & Mathias, J.-D. (2022). Adapting the governance of social–ecological systems to behavioural dynamics: An agent-based model for water quality management using the theory of planned behaviour. Ecological Economics, 194. doi:10.1016/j.ecolecon.2021.107338
• Britz, W., Ferris, M., & Kuhn, A. (2013). Modeling water allocating institutions based on Multiple Optimization Problems with Equilibrium Constraints. Environmental Modelling & Software, 46, 196-207. doi:10.1016/j.envsoft.2013.03.010
• Castilla-Rho, J. C., Rojas, R., Andersen, M. S., Holley, C., & Mariethoz, G. (2019). Sustainable groundwater management: How long and what will it take? Global Environmental Change, 58. doi:10.1016/j.gloenvcha.2019.101972
• Castonguay, A. C., Iftekhar, M. S., Urich, C., Bach, P. M., & Deletic, A. (2018). Integrated modelling of stormwater treatment systems uptake. Water Res, 142, 301-312. doi:10.1016/j.watres.2018.05.037
• Castonguay, A. C., Urich, C., Iftekhar, M. S., & Deletic, A. (2018). Modelling urban water management transitions: A case of rainwater harvesting. Environmental Modelling & Software, 105, 270-285. doi:10.1016/j.envsoft.2018.05.001
• Chen, A. (2017). Spatially explicit modelling of agricultural dynamics in semi-arid environments. Ecological Modelling, 363, 31-47. doi:10.1016/j.ecolmodel.2017.08.025
• Cheng, H., et al., 2019. A circular economy system for breaking the development dilemma of ‘ecological fragility–economic poverty’ vicious circle: A CEEPS-SD analysis. Journal of Cleaner Production, 212, 381–392. doi:10.1016/j.jclepro.2018.12.014
• Crooks, A. T., & Hailegiorgis, A. B. (2014). An agent-based modeling approach applied to the spread of cholera. Environmental Modelling & Software, 62, 164-177. doi:10.1016/j.envsoft.2014.08.027
• Daloğlu, I., Nassauer, J. I., Riolo, R. L., & Scavia, D. (2014). Development of a farmer typology of agricultural conservation behavior in the American Corn Belt. Agricultural Systems, 129, 93-102. doi:10.1016/j.agsy.2014.05.007
• Darbandsari, P., Kerachian, R., & Malakpour-Estalaki, S. (2017). An Agent-based behavioral simulation model for residential water demand management: The case-study of Tehran, Iran. Simulation Modelling Practice and Theory, 78, 51-72. doi:10.1016/j.simpat.2017.08.006
• Darbandsari, P., Kerachian, R., Malakpour-Estalaki, S., & Khorasani, H. (2020). An agent-based conflict resolution model for urban water resources management. Sustainable Cities and Society, 57. doi:10.1016/j.scs.2020.102112
• Ding, K. J., Gilligan, J. M., Yang, Y. C. E., Wolski, P., & Hornberger, G. M. (2021). Assessing food–energy–water resources management strategies at city scale: An agent-based modeling approach for Cape Town, South Africa. Resources, Conservation and Recycling, 170. doi:10.1016/j.resconrec.2021.105573
• Du, E., Cai, X., Wu, F., Foster, T., & Zheng, C. (2021). Exploring the impacts of the inequality of water permit allocation and farmers’ behaviors on the performance of an agricultural water market. Journal of Hydrology, 599. doi:10.1016/j.jhydrol.2021.126303
• Du, E., Tian, Y., Cai, X., Zheng, Y., Han, F., Li, X., . . . Zheng, C. (2022). Evaluating Distributed Policies for Conjunctive Surface Water‐Groundwater Management in Large River Basins: Water Uses Versus Hydrological Impacts. Water Resources Research, 58(1). doi:10.1029/2021wr031352
• Elhamian, S. A. B., Rakhshandehroo, G., & Javid, A. H. (2021). Quantitative and Qualitative Optimization of Water Allocation in No Bandegan Aquifer using an Agent-based Approach. Iranian Journal of Science and Technology, Transactions of Civil Engineering, 46(1), 523-534. doi:10.1007/s40996-021-00656-1
• Farhadi, S., Nikoo, M. R., Rakhshandehroo, G. R., Akhbari, M., & Alizadeh, M. R. (2016). An agent-based-nash modeling framework for sustainable groundwater management: A case study. Agricultural Water Management, 177, 348-358. doi:10.1016/j.agwat.2016.08.018
• Fleming, S. W. (2021). Scale-free networks, 1/f dynamics, and nonlinear conflict size scaling from an agent-based simulation model of societal-scale bilateral conflict and cooperation. Physica A: Statistical Mechanics and its Applications, 567. doi:10.1016/j.physa.2020.125678
• Galán, J. M., López-Paredes, A., & del Olmo, R. (2009). An agent-based model for domestic water management in Valladolid metropolitan area. Water Resources Research, 45(5). doi:10.1029/2007wr006536
• García, G. A., García, P. E., Rovere, S. L., Bert, F. E., Schmidt, F., Menéndez, Á. N., . . . Podestá, G. P. (2019). A linked modelling framework to explore interactions among climate, soil water, and land use decisions in the Argentine Pampas. Environmental Modelling & Software, 111, 459-471. doi:10.1016/j.envsoft.2018.10.013
• Giri, S., Arbab, N. N., & Lathrop, R. G. (2018). Water security assessment of current and future scenarios through an integrated modeling framework in the Neshanic River Watershed. Journal of Hydrology, 563, 1025-1041. doi:10.1016/j.jhydrol.2018.05.046
• Granco, G., Caldas, M., Bergtold, J., Heier Stamm, J. L., Mather, M., Sanderson, M., . . . Ramsey, S. (2022). Local environment and individuals’ beliefs: The dynamics shaping public support for sustainability policy in an agricultural landscape. J Environ Manage, 301, 113776. doi:10.1016/j.jenvman.2021.113776
• Guo, N., Shi, C., Yan, M., Gao, X., & Wu, F. (2022). Modeling agricultural water-saving compensation policy: An ABM approach and application. Journal of Cleaner Production, 344. doi:10.1016/j.jclepro.2022.131035
• Hampf, A. C., Carauta, M., Latynskiy, E., Libera, A. A. D., Monteiro, L., Sentelhas, P., . . . Nendel, C. (2018). The biophysical and socio-economic dimension of yield gaps in the southern Amazon – A bio-economic modelling approach. Agricultural Systems, 165, 1-13. doi:10.1016/j.agsy.2018.05.009
• Hare, M., & Deadman, P. (2004). Further towards a taxonomy of agent-based simulation models in environmental management. Mathematics and Computers in Simulation, 64(1), 25-40. doi:10.1016/s0378-4754(03)00118-6
• Head, B.W., Xiang, W.-N., 2016. Working with wicked problems in socio-ecological systems: more awareness, greater acceptance, and better adaptation. Landsc. Urban Plann. 154, 1–3.
• Huber, L., Bahro, N., Leitinger, G., Tappeiner, U., & Strasser, U. (2019). Agent-Based Modelling of a Coupled Water Demand and Supply System at the Catchment Scale. Sustainability, 11(21). doi:10.3390/su11216178
• Hyun, J.-Y., Huang, S.-Y., Yang, Y.-C. E., Tidwell, V., & Macknick, J. (2019). Using a coupled agent-based modeling approach to analyze the role of risk perception in water management decisions. Hydrology and Earth System Sciences, 23(5), 2261-2278. doi:10.5194/hess-23-2261-2019
• Iftekhar, M. S., Tisdell, J. G., & Connor, J. D. (2013). Effects of competition on environmental water buyback auctions. Agricultural Water Management, 127, 59-73. doi:10.1016/j.agwat.2013.05.015
• Isern, D., Abelló, S., & Moreno, A. (2012). Development of a multi-agent system simulation platform for irrigation scheduling with case studies for garden irrigation. Computers and Electronics in Agriculture, 87, 1-13. doi:10.1016/j.compag.2012.04.007
• Jager W., & Gotts N., (2013), Simulating social environmental systems, Steg, L., van den Berg, A. E., & de Groot, J. I. M. (Eds.). (p. 283).BPS textbooks in psychology.Environmental psychology: An introduction. BPS Blackwell.
• James, R., & Rosenberg, D. E. (2022). Agent‐Based Model to Manage Household Water Use Through Social‐Environmental Strategies of Encouragement and Peer Pressure. Earth’s Future, 10(2). doi:10.1029/2020ef001883
• Janssen, M. A. (2007). Coordination in irrigation systems: An analysis of the Lansing–Kremer model of Bali. Agricultural Systems, 93(1-3), 170-190. doi:10.1016/j.agsy.2006.05.004
• Jiménez, A.-F., Cárdenas, P.-F., & Jiménez, F. (2021). Smart water management approach for resource allocation in High-Scale irrigation systems. Agricultural Water Management, 256. doi:10.1016/j.agwat.2021.107088
• Jiménez, A.-F., Cárdenas, P.-F., & Jiménez, F. (2022). Intelligent IoT-multiagent precision irrigation approach for improving water use efficiency in irrigation systems at farm and district scales. Computers and Electronics in Agriculture, 192. doi:10.1016/j.compag.2021.106635
• Kadinski, L., Salcedo, C., Boccelli, D. L., Berglund, E., & Ostfeld, A. (2022). A Hybrid Data-Driven-Agent-Based Modelling Framework for Water Distribution Systems Contamination Response during COVID-19. Water, 14(7), 1088. Retrieved from https://www.mdpi.com/2073-4441/14/7/1088
• Kaiser, K. E., Flores, A. N., & Hillis, V. (2020). Identifying emergent agent types and effective practices for portability, scalability, and intercomparison in water resource agent-based models. Environmental Modelling & Software, 127. doi:10.1016/j.envsoft.2020.104671
• Kandiah, V. K., Berglund, E. Z., & Binder, A. R. (2019). An agent-based modeling approach to project adoption of water reuse and evaluate expansion plans within a sociotechnical water infrastructure system. Sustainable Cities and Society, 46. doi:10.1016/j.scs.2018.12.040
• Kanta, L., & Berglund, E. (2015). Exploring Tradeoffs in Demand-Side and Supply-Side Management of Urban Water Resources Using Agent-Based Modeling and Evolutionary Computation. Systems, 3(4), 287-308. doi:10.3390/systems3040287
• Koutiva, I., & Makropoulos, C. (2016a). Exploring the effects of domestic water management measures to water conservation attitudes using agent based modelling. Water Supply, 17(2), 552-560. doi:10.2166/ws.2016.161
• Koutiva, I., & Makropoulos, C. (2016b). Modelling domestic water demand: An agent based approach. Environmental Modelling & Software, 79, 35-54. doi:10.1016/j.envsoft.2016.01.005
• Koutiva, & Makropoulos. (2019). Exploring the Effects of Alternative Water Demand Management Strategies Using an Agent-Based Model. Water, 11(11). doi:10.3390/w11112216
• le bars, M., & Attonaty, J.-M. (2001). A multi-agent system to simulate water attribution among farmers.
• Li, Y., Khalkhali, M., Mo, W., & Lu, Z. (2021). Modeling spatial diffusion of decentralized water technologies and impacts on the urban water systems. Journal of Cleaner Production, 315. doi:10.1016/j.jclepro.2021.128169
• Lin, Z., Lim, S. H., Lin, T., & Borders, M. (2020). Using Agent-Based Modeling for Water Resources Management in the Bakken Region. Journal of Water Resources Planning and Management, 146(1), 05019020. doi:doi:10.1061/(ASCE)WR.1943-5452.0001147
• López-Paredes, A., Saurí, D., & Galán, J. M. (2016). Urban Water Management with Artificial Societies of Agents: The FIRMABAR Simulator. Simulation, 81(3), 189-199. doi:10.1177/0037549705053167
• Mashhadi Ali, 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. doi:10.1016/j.scs.2016.10.001
• Mariano, Dandara & Alves, Conceicao De Maria. (2020). The application of role-playing games and agent-based modelling to the collaborative water management in peri-urban communities. RBRH. 25. 10.1590/2318-0331.252020190100.
• Markowska, J., Szali´nska, W., Dąbrowska, J., Brząkała, M., 2020. The concept of a participatory approach to water management on a reservoir in response to wicked problems. J. Environ. Manag. 259, 109626.
• Mashhadi Ali, 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. doi:10.1016/j.scs.2016.10.001
• Mewes, B. (2019). Learning agents - A unique approach to combine Machine Learning and Agent-based modelling for water resource management. https://ui.adsabs.harvard.edu/abs/2019AGUFM.H52C..02M
• Mishra, V. K., Palleti, V. R., & Mathur, A. (2019). A modeling framework for critical infrastructure and its application in detecting cyber-attacks on a water distribution system. International Journal of Critical Infrastructure Protection, 26. doi:10.1016/j.ijcip.2019.05.001
• Moglia, M., Perez, P., & Burn, S. (2010). Modelling an urban water system on the edge of chaos. Environmental Modelling & Software, 25(12), 1528-1538. doi:10.1016/j.envsoft.2010.05.002
• Monroe, J., Ramsey, E., & Berglund, E. (2018). Allocating countermeasures to defend water distribution systems against terrorist attack. Reliability Engineering & System Safety, 179, 37-51. doi:10.1016/j.ress.2018.02.014
• Murphy, J. T. (2012). Exploring complexity with the Hohokam Water Management Simulation: A middle way for archaeological modeling. Ecological Modelling, 241, 15-29. doi:10.1016/j.ecolmodel.2011.12.026
• Murphy, J., Ozik, J., Collier, N., Altaweel, M., Lammers, R., Prusevich, A., . . . Alessa, L. (2015). Simulating regional hydrology and water management: An integrated agent-based approach.
• Nandi, A., Megiddo, I., Ashok, A., Verma, A., & Laxminarayan, R. (2017). Reduced burden of childhood diarrheal diseases through increased access to water and sanitation in India: A modeling analysis. Soc Sci Med, 180, 181-192. doi:10.1016/j.socscimed.2016.08.049
• Nguyen, N. P., Shortle, J. S., Reed, P. M., & Nguyen, T. T. (2013). Water quality trading with asymmetric information, uncertainty and transaction costs: A stochastic agent-based simulation. Resource and Energy Economics, 35(1), 60-90. doi:10.1016/j.reseneeco.2012.09.002
• Nhim, T., Richter, A., & Zhu, X. (2019). The resilience of social norms of cooperation under resource scarcity and inequality — An agent-based model on sharing water over two harvesting seasons. Ecological Complexity, 40. doi:10.1016/j.ecocom.2018.06.001
• Nhim, T., & Richter, A. (2022). Path dependencies and institutional traps in water governance – Evidence from Cambodia. Ecological Economics, 196. doi:10.1016/j.ecolecon.2022.107391
• Nichita, C., & Oprea, M. (2007). An agent-based model for water quality control. In V. Pleşu & P. Ş. Agachi (Eds.), Computer Aided Chemical Engineering (Vol. 24, pp. 1217-1222): Elsevier.
• Nickel, D., Barthel, R., & Braun, J. (2005). Large-scale water resources management within the framework of GLOWA-Danube—The water supply model. Physics and Chemistry of the Earth, Parts A/B/C, 30(6-7), 383-388. doi:10.1016/j.pce.2005.06.004
• Noël, P. H., & Cai, X. (2017). On the role of individuals in models of coupled human and natural systems: Lessons from a case study in the Republican River Basin. Environmental Modelling & Software, 92, 1-16. doi:10.1016/j.envsoft.2017.02.010
• Noori, M., Emadi, A., & Fazloula, R. (2021). An agent-based model for water allocation optimization and comparison with the game theory approach. Water Supply, 21(7), 3584-3601. doi:10.2166/ws.2021.124
• Nouri, A., Saghafian, B., Delavar, M., & Bazargan-Lari, M. R. (2019). Agent-Based Modeling for Evaluation of Crop Pattern and Water Management Policies. Water Resources Management, 33(11), 3707-3720. doi:10.1007/s11269-019-02327-3
• Ohab-Yazdi, S. A., & Ahmadi, A. (2018). Using the agent-based model to simulate and evaluate the interaction effects of agent behaviors on groundwater resources, a case study of a sub-basin in the Zayandehroud River basin. Simulation Modelling Practice and Theory, 87, 274-292. doi:10.1016/j.simpat.2018.07.003
• Oliva-Felipe, L., Verdaguer, M., Poch, M., Vázquez-Salceda, J., & Cortés, U. (2021). The Organisational Structure of an Agent-Based Model for the Management of Wastewater Systems. Water, 13(9). doi:10.3390/w13091258
• Palmatier, R. W., Houston, M. B., & Hulland, J. (2018). Review articles: purpose, process, and structure. Journal of the Academy of Marketing Science, 46(1), 1-5. doi:10.1007/s11747-017-0563-4
• Perello-Moragues, A., Poch, M., Sauri, D., Popartan, L. A., & Noriega, P. (2021). Modelling Domestic Water Use in Metropolitan Areas Using Socio-Cognitive Agents. Water, 13(8), 1024. Retrieved from https://www.mdpi.com/2073-4441/13/8/1024
• Poch, M., Cortes, U., Lafuente, J., Colprim, J., Baeza, J., Comas, J., . . . Rodriguez-Roda, I. R. (2002). A hybrid supervisory system to support WWTP operation: implementation and validation. Water Science and Technology, 45(4-5), 289-297. doi:10.2166/wst.2002.0608
• Ponte, B.; de la Fuente, D.; Pino, R. & Rosillo, R. (2015): “Real-Time Water Demand Forecasting System through an Agent-Based Architecture”, International Journal of Bio-Inspired Computation, vol. 7, no 3, (147-156).
• Pouladi, P., Afshar, A., Afshar, M. H., Molajou, A., & Farahmand, H. (2019). Agent-based socio-hydrological modeling for restoration of Urmia Lake: Application of theory of planned behavior. Journal of Hydrology, 576, 736-748. doi:10.1016/j.jhydrol.2019.06.080
• Ramsey, E. (2016). Use of a Household Survey in the Development of an Agent-Based Model to Support Water Demand Management in Jaipur, India. In World Environmental and Water Resources Congress 2016 (pp. 171-176).
• Rixon, A., Moglia, M., & Burn, S. (2007). Chapter 4 - Exploring water conservation behaviour through participatory agent-based modelling. In A. Castelletti & R. S. Sessa (Eds.), Topics on System Analysis and Integrated Water Resources Management (pp. 73-96). Oxford: Elsevier.
• Rojas, R., Castilla-Rho, J., Bennison, G., Bridgart, R., Prats, C., & Claro, E. (2022). Participatory and Integrated Modelling under Contentious Water Use in Semiarid Basins. Hydrology, 9(3). doi:10.3390/hydrology9030049
• Saqalli, M., Thiriot, S., & Amblard, F. (2010). Investigating social conflicts linked to water resources trhough agent-based modelling. NATO Science for Peace and security series, 75, 142-157. Retrieved from https://halshs.archives-ouvertes.fr/halshs-00918476
• Schlüter, M., & Pahl-Wostl, C. (2007). Mechanisms of Resilience in Common-pool Resource Management Systems an Agent-based Model of Water Use in a River Basin. Ecology and Society, 12(2). Retrieved from http://www.jstor.org/stable/26267867
• Schroeder, O. B., Manez, M., & Jeffrey, P. (2009). The use of multi-agent based models to support water resources management The Moroccan case study. Abingdon: Routledge.
• Schwarz, N., & Ernst, A. (2009). Agent-based modeling of the diffusion of environmental innovations — An empirical approach. Technological Forecasting and Social Change, 76(4), 497-511. doi:10.1016/j.techfore.2008.03.024
• Shafiee, M. E., & Berglund, E. Z. (2016). Agent-based modeling and evolutionary computation for disseminating public advisories about hazardous material emergencies. Computers, Environment and Urban Systems, 57, 12-25. doi:10.1016/j.compenvurbsys.2016.01.001
• Smajgl, A., Heckbert, S., Ward, J., & Straton, A. (2009). Simulating impacts of water trading in an institutional perspective. Environmental Modelling & Software, 24(2), 191-201. doi:10.1016/j.envsoft.2008.07.005
• Strickling, H., DiCarlo, M. F., Shafiee, M. E., & Berglund, E. (2020). Simulation of containment and wireless emergency alerts within targeted pressure zones for water contamination management. Sustainable Cities and Society, 52. doi:10.1016/j.scs.2019.101820
• Tamburino, L., Di Baldassarre, G., & Vico, G. (2020). Water management for irrigation, crop yield and social attitudes: a socio-agricultural agent-based model to explore a collective action problem. Hydrological Sciences Journal, 65(11), 1815-1829. doi:10.1080/02626667.2020.1769103
• Tillman, D. E., Larsen, T. A., Pahl-Wostl, C., & Gujer, W. (2005). Simulating development strategies for water supply systems. Journal of Hydroinformatics, 7(1), 41-51. doi:10.2166/hydro.2005.0005
• Thompson, J. R., Frezza, D., Necioglu, B., Cohen, M. L., Hoffman, K., & Rosfjord, K. (2019). Interdependent Critical Infrastructure Model (ICIM): An agent-based model of power and water infrastructure. International Journal of Critical Infrastructure Protection, 24, 144-165. doi:10.1016/j.ijcip.2018.12.002
• Tomičić, I., & Schatten, M. (2016). Agent-based framework for modeling and simulation of resources in self-sustainable human settlements: a case study on water management in an eco-village community in Croatia. International Journal of Sustainable Development & World Ecology, 23(6), 504-513. doi:10.1080/13504509.2016.1153527
• Van Oel, P. R., & Van der Veen, A. (2011). Using agent-based modeling to depict basin closure in the Naivasha basin, Kenya: a framework of analysis. Procedia Environmental Sciences, 7, 32-37. doi:10.1016/j.proenv.2011.07.007
• Wang, H., Zhang, J., & Zeng, W. (2018). Intelligent simulation of aquatic environment economic policy coupled ABM and SD models. Sci Total Environ, 618, 1160-1172. doi:10.1016/j.scitotenv.2017.09.184
• Wang, Y., Zhou, Y., Franz, K., Zhang, X., Ding, K. J., Jia, G., & Yuan, X. (2021). An agent-based framework for high-resolution modeling of domestic water use. Resources, Conservation and Recycling, 169. doi:10.1016/j.resconrec.2021.105520
• Watson, R., Wilson, H. N., Smart, P., & Macdonald, E. K. (2018). Harnessing Difference: A Capability-Based Framework for Stakeholder Engagement in Environmental Innovation. Journal of Product Innovation Management, 35(2), 254-279. doi:https://doi.org/10.1111/jpim.12394
• Wise, S., & Crooks, A. T. (2012). Agent-based modeling for community resource management: Acequia-based agriculture. Computers, Environment and Urban Systems, 36(6), 562-572. doi:10.1016/j.compenvurbsys.2012.08.004
• Wu, H., Bolte, J. P., Hulse, D., & Johnson, B. R. (2015). A scenario-based approach to integrating flow-ecology research with watershed development planning. Landscape and Urban Planning, 144, 74-89. doi:10.1016/j.landurbplan.2015.08.012
• Xiao, Y., Fang, L., & Hipel, K. (2018). Centralized and Decentralized Approaches to Water Demand Management. Sustainability, 10(10). doi:10.3390/su10103466
• Yang, J., Yang, Y. C. E., Chang, J., Zhang, J., & Yao, J. (2019). Impact of dam development and climate change on hydroecological conditions and natural hazard risk in the Mekong River Basin. Journal of Hydrology, 579. doi:10.1016/j.jhydrol.2019.124177
• Yang, Y. C. E., Son, K., Hung, F., & Tidwell, V. (2020). Impact of climate change on adaptive management decisions in the face of water scarcity. Journal of Hydrology, 588. doi:10.1016/j.jhydrol.2020.125015
• Yuan, S., Li, X., & Du, E. (2021). Effects of farmers’ behavioral characteristics on crop choices and responses to water management policies. Agricultural Water Management, 247. doi:10.1016/j.agwat.2020.106693
• Yuan, X.-C., Wei, Y.-M., Pan, S.-Y., & Jin, J.-L. (2014). Urban Household Water Demand in Beijing by 2020: An Agent-Based Model. Water Resources Management, 28(10), 2967-2980. doi:10.1007/s11269-014-0649-4
• Zamenian, H., & Abraham, D. M. (2020). An Agent-Based Simulation Model for Assessment of Water Consumption Patterns during Water Rate Increase Events. In Construction Research Congress 2020 (pp. 800-808).
• Zhang, P., Peeta, S., & Friesz, T. (2005). Dynamic Game Theoretic Model of Multi-Layer Infrastructure Networks. Networks and Spatial Economics, 5(2), 147-178. doi:10.1007/s11067-005-2627-0
• Zhang, Y., Wu, Y., Yu, H., Dong, Z., & Zhang, B. (2013). Trade-offs in designing water pollution trading policy with multiple objectives: A case study in the Tai Lake Basin, China. Environmental Science & Policy, 33, 295-307. doi:10.1016/j.envsci.2013.07.002
• Zhao, J., Cai, X., & Wang, Z. (2013). Comparing administered and market-based water allocation systems through a consistent agent-based modeling framework. J Environ Manage, 123, 120-130. doi:10.1016/j.jenvman.2013.03.005
• Zolfagharipoor, M. A., & Ahmadi, A. (2021). Agent-based modeling of participants’ behaviors in an inter-sectoral groundwater market. J Environ Manage, 299, 113560. doi:10.1016/j.jenvman.2021.113560