Seismic Signature of Rain and Wind Inferred From Seismic Data

Seismic stations are increasingly used to monitor river activity and quantify sediment transport during flood events. In tropical regions, cyclone-induced floods often associated with heavy rain strong wind episodes, generating complex seismic records involving the simultaneous signature of water, sediment, rainfall wind. Hence, characterization is then required better decipher each process improve our understanding signature. this study, we investigate experimentally response using data recorded by geophones deployed in various soil types at different burial depth (BD), co-located meteorological instruments. Our results show that power spectral density (PSD) noise intensifies a frequency between 60 500 Hz for 5 wind, presence precipitation as low 0.025 mm/min and/or speed ≥3 m/s. PSD analysis indicates signal decreases BD value ∼2–5 dB difference 10 cm. We also observe type has its own The 4-min root mean square correlation amplitude suggests they best correlate Pearson coefficient >0.90 30 transfer function rate (or kinetic energy) shows geophone can be robust proxy these parameters.