The role of agent-based modeling and multi-agent systems in flood-based hydrological problems: a brief review
Flood problems are complex phenomena with a direct relationship with the hydrological cycle; these are natural processes occurring in water systems, that interact at different spatial and temporal scales. In modeling the hydrological phenomena, traditional approaches, like physics-based mathematical...
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Veröffentlicht in: | Journal of water and climate change 2020-12, Vol.11 (4), p.1580-1602 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Flood problems are complex phenomena with a direct relationship with the hydrological cycle; these are natural processes occurring in water systems, that interact at different spatial and temporal scales. In modeling the hydrological phenomena, traditional approaches, like physics-based mathematical equations and data-driven modeling (DDM) are used. Advances in hydroinformatics are helping to understand these physical processes, with improvements in the collection and analysis of hydrological data, information and communication technologies (ICT), and geographic information systems (GIS), offering opportunities for innovations in model implementation, to improve decision support for the response to societally important floods impacting our societies. This paper offers a brief review of agent-based models (ABMs) and multi-agent systems (MASs) methodologies' applications for solutions to flood problems, their management, assessment, and efforts for forecasting stream flow and flood events. Significant observations from this review include: (i) contributions of agent technologies, as a growing methodology in hydrology; (ii) limitations; (iii) capabilities of dealing with distributed and complex domains; and (iv), the capabilities of MAS as an increasingly accepted point of view applied to flood modeling, with examples presented to show the variety of system combinations that are practical on a specialized architectural level for developing and deploying sophisticated flood forecasting systems. |
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ISSN: | 2040-2244 2408-9354 |
DOI: | 10.2166/wcc.2019.108 |