Seismic signatures and site characterization of an intermittent stream in dry and flood conditions. An implication for soil losses and landslide triggering

Identifying ambient noise-based (ANb) signatures of streams can help in the estimation of their erosive potential (EP) that promotes reverie landslides and soil losses in the fluvial valleys. This is particularly imperative on flooding or rainy days, leading to stronger erosion-prone conditions (colluvium and boulders) of the valley beds inferred from georadar attribute analysis. Developing such research direction can benefit the local communities, as is the case with the Cerrado region of Brazil, where these phenomena have high destructive potential with social, economic, and climatic implications. For the present study, a seasonal stream in the Federal District of Brazil was investigated by ANb monitoring supported by ground penetration radar (GPR) for site characterization. The ANb monitoring was conducted (at a safe distance) with a seismometer over several durations of dry and rainy conditions. The power spectral density (PSDs) was computed as a function of several variables, including weather conditions (rainfall, wind speed, and pressure), time-frequency spectrograms, and ambient noise displacement root mean square (RMS). This analysis also considered the single station horizontal-to-vertical spectral ratio (HVSR), where rain, wind, pressure, river flow and anthropogenic signatures were evident (at selective frequency ranges). Multi-peaks that emerged on the HVSR curve were further analyzed to identify amplitude and frequency changes, with the three peaks shifting on average to a lower position during the rainy period. The GPR amplitude and waveform variation features were attributed to the stratigraphy of the floodplain and regions susceptible to erosion, such as erosion-prone lithological spots, which provide the basis for non-destructive monitoring tools that enable the detection of "seismic signatures" and weak spots of the fluvial channels for improving environmental management.