Preliminary exploration of river process monitoring and hydrological parameter inversion based on microseismic technology
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摘要:
河流监测手段趋向遥感、智能化,传统河流监测技术费时费力,且在洪水期间面临仪器损坏和缺失数据的风险。国家地震台网分布广泛密集,微震技术具有远程无接触、低成本和24 h无间断监测的特点,正逐渐被用于河流监测中。通过野外河流微震监测试验,监测与分析河流过程的动态振动信号,获取河流湍流过程微震信号的物理特征。在此基础上,利用带通滤波的方法保留2~7 Hz频带的信号,采用Welch法计算出微震信号时频分析图上在2~7 Hz频带内1 min平均地震功率,将其转换为能量的形式,并与现场测得的河流水文数据相匹配,从而评估微震监测河流的潜力。为获取河流的水文参数,提出一个简单的线性回归模型量化平均功率谱密度(PSD)与河流湍流过程之间的关系,由此推导出反演计算河流流量的线性近似模型,模型反演结果在实测值附近波动,相对误差在10.29%以内,反演结果较为准确。本研究为野外河流微震监测试验的初步探索,研究成果可为依托国家高密度地震台站的河流洪水及常态水文遥感、智能化监测提供参考和理论依据。
Abstract:River monitoring tends to be adopt remote sensing and intelligent technologies. Traditional river monitoring techniques are time-consuming and labor-intensive, and face the risks of instrument damage and missing data during floods. Benefiting from the advantages of remote non-contact operation, low cost and 24-hour continuous monitoring, microseismic technology is increasingly applied in river monitoring. In this paper, field microseismic monitoring experiments on rivers were conducted to monitor and analyze the dynamic vibration signals of river processes. Thereby obtaining the physical characteristics of microseismic signals generated by river turbulence. On this basis, a band-pass filtering method was used to retain signals in the 2-7 Hz frequency band. The Welch method, was employed to calculate the 1-minute average seismic power within the 2-7 Hz frequency band from the time-frequency analysis diagram of microseismic signals, which was then converted energy form and matched with the field measured river hydrological data to evaluate the potential of microseismic technology in river monitoring. To acquire the hydrological parameters of the rivers, a simple linear regression model was proposed to quantify the relationship between the average power spectral density (PSD) and the river turbulence process. A linear approximation model for inverting river discharge was derived accordingly. The inversion results of the model fluctuated around the measured values with a relative errors within 10.29%, indicating high accuracy. This study is a preliminary exploration of field microseismic monitoring experiments on rivers. The research results can provide a reference and theoretical basis for remote sensing and intelligent monitoring of river floods and normal hydrology relying on the national high-density seismic network.
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图 9 试验期间河流平均流速变化(a)与SZ4微震基站通道E记录的2~7 Hz频带上的波形图(b)及时频分析图(c)
Figure 9. Correlation between the average flow velocity changes of the river during the experiment (a), waveform diagram (b) and time-frequency analysis diagram (c) of signals in the 2-7 Hz frequency band recorded by Channel E of the SZ4 microseismic station
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