贝叶斯空间时空随机局部微分方程用于高分辨率地震强度测绘:适用于印度尼西亚苏门答腊岛
Dila Fitriani Azuri1, I Gede Nyoman Mindra Jaya1, Yudi Rosandi2
1Statistics Department, Universitas Padjadjaran, Jl. Raya Bandung Sumedang km 21 Jatinangor, Sumedang 45363, Indonesia.
MethodsX
|July 21, 2025
概括
本研究使用随机局部微分方程 (SPDE) 方法对未测量的印尼地区的地震风险进行建模. 由SPDE帮助开发地震预警系统和减轻地震风险的高分辨率地图.
科学领域:
- 地质物理学 地质物理学
- 计算地震学计算地震学
- 空间统计的空间统计.
背景情况:
- 由于印度尼西亚位于主要构造板块上,因此具有很高的地震易感性,特别是在苏门答腊.
- 准确的地震风险评估对于减轻损害和生命损失至关重要,特别是在缺乏地震数据的地区.
- 早期预警系统对于灾难准备至关重要,但需要准确的地震活动估计.
研究的目的:
- 为了估计印尼未测量的地区的地震强度潜力.
- 开发高分辨率的地震风险地图,以加强预警系统.
- 应用先进的空间插值技术进行地震危险评估.
主要方法:
- 使用随机局部微分方程 (SPDE) 方法进行空间插值.
- 通过三角化将连续的高斯场 (GF) 转换为计算效率高的高斯马尔科夫随机场 (GMRF).
- 应用了SPDE,空间范围为10公里,标准偏差为0.1,用于详细的风险映射.
主要成果:
- 为未测量的地区生成高分辨率的地震风险地图.
- 证明了SPDE方法在克服传统GF模型的"大问题"方面的有效性.
- 为开发有效的地震预警系统提供了关键数据.
结论:
- SPDE方法提供了一种计算效率高且准确的方法,用于估计未测量的地区的地震活动.
- 产生的风险地图是为印尼的地震风险减缓战略提供信息的宝贵工具.
- 这项研究有助于提高地震易发地区社区的抵御力.
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