Agent-Based Modeling and Simulation for Integrating Social and Natural Dynamics in Water Resources Management
Resumo
Water resources modelling based solely in natural dynamics may presented limitations due to neglection of social factors. This article presents an exploratory study of agent-based modeling and simulation for managing water use conflicts between farmers and regulators and among farmers. Water users’ behavior is guided by the Belief, Desire, and Intention (BDI) reasoning model, aiming at welfare, often through crop sales and income generation. Heterogeneous behavior is captured through diverse cooperation profiles linked to different compliance levels with water use rules set by the regulatory agent. The resulting framework offers insights into environmental flows and water consumption equity among users, testing opportunities for new water policies.Referências
Adamatti, D., Sichman, J., Rabak, C., Bommel, P., Ducrot, R., and Camargo, M. (2005).
Jogoman: A prototype using multi-agent-based simulation and role-playing games in water management. In Proceedings of the SMAGET-CABM-HEMA Conference.
Al-Amin, S., Berglund, E. Z., Mahinthakumar, G., and Larson, K. L. (2018). Assessing the effects of water restrictions on socio-hydrologic resilience for shared groundwater systems. Journal of Hydrology, 566:872–885.
Blair, P. and Buytaert, W. (2016). Socio-hydrological modelling: a review asking ”why, what and how?”. Hydrology and Earth System Sciences, 20:443–478.
Bratman, M. E. (1987). Intention, Plans, and Practical Reason, volume xii.
Bresciani, P., Perini, A., Giorgini, P., and Giunchiglia, F. (2004). Tropos: An agent-oriented software development methodology. AAMAS, 8:203–236.
da Silva, E. P., de Sousa, D. S., Minoti, R. T., de Maria Albuquerque Alves, C., and Vergara, F. E. (2023). Modelagem sócio-hidrológica para avaliação do efeito comportamental cooperativo em sistemas hídricos: Uma aplicação à bacia do rio formoso, tocantins. In XXV SBRH - Simpósio Brasileiro de Recursos Hídricos.
Du, E., Wu, F., Jiang, H., Guo, N., Tian, Y., and C., Z. (2023). Development of an integrated socio-hydrological modeling framework for assessing the impacts of shelter location arrangement and human behaviors on flood evacuation processes. Hydrology and Earth System Science, 27:1607–1626.
IAC (2018). Gestão de Alto Nível: Plano do Biênio (2018-2019). Instituto de Atenção às Cidades (IAC). Universidade Federal do Tocantins (IFT). Disponível em: [link]. Acessado em: 15/05/24.
Kock, B. E. (2008). Agent-based models of socio-hydrological systems for exploring the institutional dynamics of water resources conflict. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology. Cambridge, MA, EUA.
Le Page, C., Bousquet, F., Bakam, I., Bah, A., and Baron, C. (2000). Cormas: A multiagent simulation toolkit to modelnatural and social dynamics at multiple scales. In Proceedings of Workshop ”The ecology of scales”.
Liang, X., Chen, H., Wang, Y., and Song, S. (2016). Design and application of a CA-BDI model to determine farmers’ land-use behavior. SpringerPlus, 5(1):1581.
Pimentel, J. and Castro, J. (2018). piStar Tool – a pluggable online tool for goal modeling. In 2018 IEEE 26th International Requirements Engineering Conference (RE), pages 498–499.
Pouladi, P., Afshar, A., Afshar, M. H., Molajou, A., and 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.
Re, V. (2015). Incorporating the social dimension into hydrogeochemical investigations for rural development: the bir al-nas approach for socio-hydrogeology. Hydrogeology Journal, 23:1293–1304.
Sivapalan, M., Savenije, H. H. G., and Blöschl, G. (2012). Socio-hydrology: A new science of people and water. Hydrological Processes, 26(8):1270–1276.
Sousa, D., Alves, C., Vergara, F., Coelho, C., and Ralha, C. (2024). Agent-based modelling for representing water allocation methodologies in the irrigation system of the formoso river basin, brazil. Proceedings of IAHS 2022, 385:71–77.
Sousa, D. S. (2023). Modelagem baseada em agentes acoplada à modelagem hidrológica para avaliação de estratégias coletivas de alocação de água: o caso do rio urubu (to). Dissertação de Mestrado. Programa de Pós-Graduação em Tecnologia Ambiental e Recursos Hídricos, Universidade de Brasília. Brasília, DF, Brasil.
Taillandier, P., Gaudou, B., Grignard, A., Huynh, Q.-N., Marilleau, N., Caillou, P., Philippon, D., and Drogoul, A. (2019). Building, composing and experimenting complex spatial models with the gama platform. GeoInformatica, 23(2):299–322.
Taillandier, P., Thérond, O., and Gaudou, B. (2012). A new BDI agent architecture based on the belief theory. Application to the modelling of cropping plan decision-making. Int. Environmental Modelling and Software Society (iEMSs). ffhal-00714325f.
Tisue, S. and Wilensky, U. (2004). Netlogo: Design and implementation of a multi-agent modeling environment. In SwarmFest 2004.
Jogoman: A prototype using multi-agent-based simulation and role-playing games in water management. In Proceedings of the SMAGET-CABM-HEMA Conference.
Al-Amin, S., Berglund, E. Z., Mahinthakumar, G., and Larson, K. L. (2018). Assessing the effects of water restrictions on socio-hydrologic resilience for shared groundwater systems. Journal of Hydrology, 566:872–885.
Blair, P. and Buytaert, W. (2016). Socio-hydrological modelling: a review asking ”why, what and how?”. Hydrology and Earth System Sciences, 20:443–478.
Bratman, M. E. (1987). Intention, Plans, and Practical Reason, volume xii.
Bresciani, P., Perini, A., Giorgini, P., and Giunchiglia, F. (2004). Tropos: An agent-oriented software development methodology. AAMAS, 8:203–236.
da Silva, E. P., de Sousa, D. S., Minoti, R. T., de Maria Albuquerque Alves, C., and Vergara, F. E. (2023). Modelagem sócio-hidrológica para avaliação do efeito comportamental cooperativo em sistemas hídricos: Uma aplicação à bacia do rio formoso, tocantins. In XXV SBRH - Simpósio Brasileiro de Recursos Hídricos.
Du, E., Wu, F., Jiang, H., Guo, N., Tian, Y., and C., Z. (2023). Development of an integrated socio-hydrological modeling framework for assessing the impacts of shelter location arrangement and human behaviors on flood evacuation processes. Hydrology and Earth System Science, 27:1607–1626.
IAC (2018). Gestão de Alto Nível: Plano do Biênio (2018-2019). Instituto de Atenção às Cidades (IAC). Universidade Federal do Tocantins (IFT). Disponível em: [link]. Acessado em: 15/05/24.
Kock, B. E. (2008). Agent-based models of socio-hydrological systems for exploring the institutional dynamics of water resources conflict. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology. Cambridge, MA, EUA.
Le Page, C., Bousquet, F., Bakam, I., Bah, A., and Baron, C. (2000). Cormas: A multiagent simulation toolkit to modelnatural and social dynamics at multiple scales. In Proceedings of Workshop ”The ecology of scales”.
Liang, X., Chen, H., Wang, Y., and Song, S. (2016). Design and application of a CA-BDI model to determine farmers’ land-use behavior. SpringerPlus, 5(1):1581.
Pimentel, J. and Castro, J. (2018). piStar Tool – a pluggable online tool for goal modeling. In 2018 IEEE 26th International Requirements Engineering Conference (RE), pages 498–499.
Pouladi, P., Afshar, A., Afshar, M. H., Molajou, A., and 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.
Re, V. (2015). Incorporating the social dimension into hydrogeochemical investigations for rural development: the bir al-nas approach for socio-hydrogeology. Hydrogeology Journal, 23:1293–1304.
Sivapalan, M., Savenije, H. H. G., and Blöschl, G. (2012). Socio-hydrology: A new science of people and water. Hydrological Processes, 26(8):1270–1276.
Sousa, D., Alves, C., Vergara, F., Coelho, C., and Ralha, C. (2024). Agent-based modelling for representing water allocation methodologies in the irrigation system of the formoso river basin, brazil. Proceedings of IAHS 2022, 385:71–77.
Sousa, D. S. (2023). Modelagem baseada em agentes acoplada à modelagem hidrológica para avaliação de estratégias coletivas de alocação de água: o caso do rio urubu (to). Dissertação de Mestrado. Programa de Pós-Graduação em Tecnologia Ambiental e Recursos Hídricos, Universidade de Brasília. Brasília, DF, Brasil.
Taillandier, P., Gaudou, B., Grignard, A., Huynh, Q.-N., Marilleau, N., Caillou, P., Philippon, D., and Drogoul, A. (2019). Building, composing and experimenting complex spatial models with the gama platform. GeoInformatica, 23(2):299–322.
Taillandier, P., Thérond, O., and Gaudou, B. (2012). A new BDI agent architecture based on the belief theory. Application to the modelling of cropping plan decision-making. Int. Environmental Modelling and Software Society (iEMSs). ffhal-00714325f.
Tisue, S. and Wilensky, U. (2004). Netlogo: Design and implementation of a multi-agent modeling environment. In SwarmFest 2004.
Publicado
14/08/2024
Como Citar
SOUSA, D.; COELHO, C.; ALVES, C.; RALHA, C..
Agent-Based Modeling and Simulation for Integrating Social and Natural Dynamics in Water Resources Management. In: WORKSHOP-ESCOLA DE SISTEMAS DE AGENTES, SEUS AMBIENTES E APLICAÇÕES (WESAAC), 18. , 2024, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 144-149.
ISSN 2326-5434.
