Empowering Human-Water System Analysis through ABSESpy: An Agent-Based Modeling Framework of SES
- 1Beijing Normal University, Faculty of Geography, State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing, China (songshgeo@mail.bnu.edu.cn)
- 2USFQ Data Hub, Universidad San Francisco de Quito. Diego de Robles s/n y Pampite. Quito, Ecuador.
ABSESpy emerges as an agent-based modeling (ABM) framework for socio-ecological systems (SES) research. By adeptly addressing pivotal needs in SES studies, such as decision-making complexity and data integration, ABSESpy sets a new tool for integrating human and natural subsystems, ensuring replicability and effective model coupling. Here, we demonstrate ABSESpy’s prowess in human-water systems analysis through two real-world application cases. The first delves into the impact of water management policy changes over the past fifty years on river basin water usage. This case underscores ABSESpy's proficiency in modeling policy effects and capturing human responses within water management. The second case takes a deep dive into the millennia-long evolution of human livelihood patterns, influenced by dynamic shifts in the water environment. This exploration showcases ABSESpy's capability to simulate extensive, temporal, socio-hydrological phenomena, providing profound insights into enduring human-water interplays. Our belief is firm: socio-hydrological systems, as quintessential SESs, can be effectively studied through data-driven agent-based modeling. ABSESpy is a testament to this approach, enhancing efficiency and depth in SES research.
How to cite: Song, S., Wang, S., Jiao, C., and José Mantilla, E.: Empowering Human-Water System Analysis through ABSESpy: An Agent-Based Modeling Framework of SES, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5635, https://doi.org/10.5194/egusphere-egu24-5635, 2024.
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