Preliminary exploration of river process monitoring and hydrological parameter inversion based on microseismic technology

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.