Bed load sediment transport inferred from seismic signals near a river
Bed load sediment transport inferred from seismic signals near a river
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根据河流附近的地震信号推断的底床沉积物输送
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
A. Badoux
中科院分区：
文献类型：
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作者：
D. Roth;E. Brodsky;N. Finnegan;D. Rickenmann;J. Turowski;A. Badoux
我们检查了瑞士前阿尔卑斯山埃伦巴赫溪流的宽带（5-480 Hz）地震数据，其中流量、降水和推移质输运受到独立约束。地震频谱的线性反演，利用孤立的放电或降雨事件，识别水湍流和降雨产生的信号。这使我们能够从地震谱中去除湍流和降雨的贡献，隔离推移质输运的信号。我们校准推移质输运在一个风暴的回归，然后使用此回归与降水和流量数据计算推移质输运率从2个月的地震谱。我们预测的推移质输运率与嵌入通道中的校准地震检波器的输运率有相当好的相关性（r2 ~ 0.6，p < 10−10）。我们发现，地震对降雨的响应是宽带的（~16-480 Hz），而水湍流和沉积物输送主要在较低的频率（<100 Hz）表现出地震功率，可能是由于较长的衰减路径长度。我们使用不同的衰减在每个地震仪推断，下游瀑布是水湍流信号的主要来源。我们的研究结果表明，从河流的地震频谱解构可以提供洞察水湍流，降雨和泥沙输运产生的分量信号。此外，地震谱与降水，流量和推移质输运数据的回归，为一个单一的校准周期，使运输的估计，为随后的时期，只有降水，流量和地震数据。因此，结合降水和流量数据，地震数据可以用来监测推移质泥沙输移。
We examine broadband (5–480 Hz) seismic data from the Erlenbach stream in the Swiss Prealps, where discharge, precipitation, and bed load transport are independently constrained. A linear inversion of seismic spectra, exploiting isolated discharge or rain events, identifies the signals generated by water turbulence and rainfall. This allows us to remove the contributions of turbulence and rainfall from the seismic spectra, isolating the signal of bed load transport. We calibrate the regression for bed load transport during one storm and then use this regression with precipitation and discharge data to calculate bed load transport rates from 2 months of seismic spectra. Our predicted bed load transport rates correlate reasonably well with transport rates from calibrated geophones embedded in the channel (r2 ~ 0.6, p < 10−10). We find that the seismic response to rainfall is broadband (~16–480 Hz), while water turbulence and sediment transport exhibit seismic power primarily in lower frequencies (<100 Hz), likely due to longer attenuation path lengths. We use the varying attenuation at each seismometer to infer that a downstream waterfall is the primary source of the water turbulence signal. Our results indicate that deconstruction of seismic spectra from rivers can provide insight into the component signals generated by water turbulence, rainfall, and sediment transport. Further, the regression of seismic spectra with precipitation, discharge, and bed load transport data for a single calibration period enables the estimation of transport for subsequent periods with only precipitation, discharge, and seismic data. Hence, in combination with precipitation and discharge data, seismic data can be used to monitor bed load sediment transport.