建立美国本土剪切波速深度模型，提升地震危害评估精度
Parametric modeling of shear wave velocity profiles for the conterminous U.S
- 用参数化函数描述全美近地表剪切波速随深度变化
- 基于9000+现场测量数据校准模型，实现高分辨率预测
- 适合地震模拟与灾害评估研究者使用
地震地面运动及破坏受近地表土层显著影响。准确的地震危险性预测需要连续的土体刚度模型，通常以剪切波速度（VS）表示。现有区域性研究如美国地质调查局的国家地壳模型，侧重深层岩性速度结构，简化了近地表土层速度变化，且空间分辨率较低。本研究定义了一种函数形式，用于描述美国本土剪切波速随深度的变化。通过整合超过9000个现场岩土测量数据对函数参数进行校准，结合地理空间机器学习方法，可实现全美近地表地质层剪切波速-深度的高分辨率一致预测，补充国家地壳模型，支持物理驱动的地动模拟与同震灾害评估等应用。
原文摘要 · Abstract (English)
Earthquake ground motions and the related damage can be significantly impacted by near-surface soils. Accurate predictions of seismic hazard require depth-continuous models of soil stiffness, commonly described in terms of shear-wave velocity (VS). For regional-scale studies, efforts to predict VS remotely, such as the U.S. Geological Survey's National Crustal Model, tend to emphasize deeper lithologic velocity structures, thus simplifying important near-surface soil velocity variations, and tend to be produced at relatively coarse geospatial resolution for one geographic area. In this study, we define a functional form to describe VS-with-depth across the conterminous U.S. We calibrate the parameters of the function using a national compilation of more than 9,000 in-situ geotechnical measurements. By coupling the parametric framework with geospatial machine learning, the model can be leveraged to provide consistent, high resolution VS-depth predictions of the near-surface geotechnical layer across the U.S., complementing the National Crustal Model and supporting applications such as physics-based ground motion simulations and coseismic hazard assessments.
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