FRAMe:在公河流域的洪水抵御能力的经验知情的基于代理的建模
Wenhan Feng1, Liang Emlyn Yang1, Mei Ai1
1Department of Geography, Ludwig Maximilian University of Munich (LMU), Munich 80333, Germany.
MethodsX
|November 17, 2025
概括
基于洪水抗灾剂的模型 (FRAMe) 模拟了社区的抗洪能力. 政府援助显著缩短了恢复时间并提高了强度,而紧急救援提高了适应能力.
科学领域:
- 环境科学 环境科学
- 计算机科学 计算机科学
- 社会科学 社会科学 社会科学
背景情况:
- 对于脆弱社区来说,抗洪能力至关重要,特别是在公河等河流盆地.
- 现有的模式往往缺乏综合的社会,治理和政策动态.
- 基于代理的建模提供了一种强大的方法来模拟复杂的系统交互.
研究的目的:
- 引入 Flood Resilience Agent-Based Model (FRAMe) 以模拟社区一级的抗洪能力. 在社区层面模拟抗洪能力. 在社区层面模拟抗洪能力.
- 量化弹性作为强度和适应能力之间的平衡.
- 评估不同政策干预措施对抗洪能力的影响.
主要方法:
- 开发了一个基于空间显式代理的模型 (FRAMe),集成经验数据,贝叶斯网络和水文模拟.
- 模型代理 (家庭,政府) 和他们的网络 (社会,治理).
- 纳入决策理论 (保护动机理论) 并进行敏感性分析.
主要成果:
- 增加政府援助减少了~50%的恢复时间,并提高了~30%的稳定性.
- 增强的应急救援改善了适应能力 (~10%) 和恢复时间,轻微增强了强度.
- 更多的知识传播使适应能力增加了一倍,但增强了强度的可变性.
结论:
- 基于代理的建模为洪水抗灾动态提供了有价值的见解.
- 政策干预,特别是政府援助,可以显著提高社区的抗洪能力.
- FRAMe作为一个工具,为适应性洪水管理策略提供信息,并提高抗灾能力.
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