研究人员，使用2016年从新西兰Kaikōura地震的最新案例研究来模拟一条主要的辫状河的同震撕脱现象，该辫状河受到约7米的垂直偏移和约4米的水平偏移。研究证明，通过在合成(地震前)和“真实”(地震后)变形激光雷达数据集上，运行简单的二维流体动力学模型，可以高精度地再现撕脱的显著特征。
有了足够的水力输入，确定性和概率风险模型可以为断层-河流交叉点预编译，以改进多风险规划。忽略现在和潜在的未来断层变形的洪水灾害模型可能会低估大地震后洪水的范围、频率和严重程度。
据介绍，地表破裂地震会产生断层位移，突然改变既定的河流路线。断层破裂诱发的河流撕脱(FIRAs)的几个显著的例子已被记录在案，但影响这些现象的因素尚未被详细探究。
附：英文原文
Title: Coseismic river avulsion on surface rupturing faults: Assessing earthquake-induced flood hazard
Author: Erin McEwan, Timothy Stahl, Andrew Howell, Rob Langridge, Matthew Wilson
Issue&Volume: 2023-05-03
Abstract: Surface-rupturing earthquakes can produce fault displacements that abruptly alter the established course of rivers. Several notable examples of fault rupture–induced river avulsions (FIRAs) have been documented, yet the factors influencing these phenomena have not been examined in detail. Here, we use a recent case study from New Zealand’s 2016 Kaikōura earthquake to model the coseismic avulsion of a major braided river subjected to ~7-m vertical and ~4-m horizontal offset. We demonstrate that the salient characteristics of the avulsion can be reproduced with high accuracy by running a simple two-dimensional hydrodynamic model on synthetic (pre-earthquake) and “real” (post-earthquake) deformed lidar datasets. With adequate hydraulic inputs, deterministic and probabilistic hazard models can be precompiled for fault-river intersections to improve multihazard planning. Flood hazard models that ignore present and potential future fault deformation may underestimate the extent, frequency, and severity of inundation following large earthquakes.
DOI: add2932
Source: https://www.science.org/doi/10.1126/sciadv.add2932