Time-lapse monitoring of climate effects on earthworks using surface waves
Time-lapse monitoring of climate effects on earthworks using surface waves
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DOI：
10.1190/geo2015-0275.1
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发表时间：
2016-03-01
期刊：
影响因子：
3.3
通讯作者：
Donohue, Shane
中科院分区：
文献类型：
--
作者：
Bergamo, Paolo;Dashwood, Ben;Donohue, Shane
英国的交通网络由关键的岩土资产(路基/路堤/大坝)支持，这些资产需要可持续的、具有成本效益的管理，同时保持适当的服务水平，以满足社会、经济和环境需求。最近极端天气对这些岩土资产的影响突出了它们对气候变化的脆弱性。我们已经评估了面波数据描述粘土填充的铁路路基的力学特性随气候变化的潜力。2013年7月至2014年11月，沿着英格兰西南部一处传统铁路路堤的顶部，每两个月采集一次地震数据。对于每一次采集，首先对收集的数据进行处理，以获得参考相同空间位置的一组瑞雷波频散和衰减曲线。然后对这些数据进行分析，以确定其空间和时间变异性的一致趋势。对于实验数据的不确定性，还验证了观测到的时间变化的相关性。最后，利用最小二乘横向约束反演方法，对面波频散数据集进行了反演，重建了路堤结构的S波速度时移模型。反演过程的一个关键点是估计合适的初始模型和选择适当的空间正则化水平。在处理所有可用的数据集的整个过程中，初始模型和空间平滑的强度保持不变，以确保程序的同质性和获得的V-S切片之间的可比性。确定了面波数据的连续和相干的时间模式，从而识别了重建的V-S模型的时间模式。这种模式与降水的季节分布和现场测得的土壤水分有关。
The UK's transportation network is supported by critical geotechnical assets (cuttings/embankments/dams) that require sustainable, cost-effective management, while maintaining an appropriate service level to meet social, economic, and environmental needs. Recent effects of extreme weather on these geotechnical assets have highlighted their vulnerability to climate variations. We have assessed the potential of surface wave data to portray the climate-related variations in mechanical properties of a clay-filled railway embankment. Seismic data were acquired bimonthly from July 2013 to November 2014 along the crest of a heritage railway embankment in southwest England. For each acquisition, the collected data were first processed to obtain a set of Rayleigh-wave dispersion and attenuation curves, referenced to the same spatial locations. These data were then analyzed to identify a coherent trend in their spatial and temporal variability. The relevance of the observed temporal variations was also verified with respect to the experimental data uncertainties. Finally, the surface wave dispersion data sets were inverted to reconstruct a time-lapse model of S-wave velocity for the embankment structure, using a least-squares laterally constrained inversion scheme. A key point of the inversion process was constituted by the estimation of a suitable initial model and the selection of adequate levels of spatial regularization. The initial model and the strength of spatial smoothing were then kept constant throughout the processing of all available data sets to ensure homogeneity of the procedure and comparability among the obtained V-S sections. A continuous and coherent temporal pattern of surface wave data, and consequently of the reconstructed V-S models, was identified. This pattern is related to the seasonal distribution of precipitation and soil water content measured on site.