Daily spectrograms during the 2013 snowmelt season. The graph shows how the energy of the signal is distributed according to its frequency. Reddish colors correspond to the maximum energy values reached by the signal recorded by the seismometer. Credit: Jordi Díaz

A team of researchers at Institute of Earth Sciences Jaume Almera of the Spanish National research Council (ICTJA-CSIC) has analysed the seismic signals generated by the variations in water flow of the Aragón river due to the snow melting in its upper basin. In the study, which has been published in the journal PLOS ONE, the researchers describe identifying snowmelt episodes from the temporal variation patterns in the seismic data.

The authors of the study used the data recorded from 2013 to 2016 with a seismometer located in the Laboratorio Subterráneo de Canfranc (LSC) in the Central Spanish Pyrenees, at about 400 m of the Aragón river channel. They calculated the daily spectrograms from the available data sets registered by the seismic broad band station. Spectrograms are graphics where the energy of the signal is represented in function of the frequency.

"During the snowmelt episodes, we have been able to identify with a characteristic spectrogram which allowed us to differentiate them from other seismic sources that were present in the background of the record," explains Jordi Díaz, researcher at ICTJA-CIC and first author of the study.

Afterward, the researchers designed an algorithm to make a hierarchical classification of the signal spectra to find common patterns. In this way, they could identify the days with snowmelt episodes as well as the intensity of these processes. The researchers conclude that, in general, the snowmelt episodes are concentrated in the months of April and May. In some particular cases, such as in 2013, the researchers were even able to identify river rises derived from snowmelt at the beginning of July.

"Our results show a great variability among the different studied years, which is due to the variations in the atmospheric parameters like temperature, heat and precipitations," explains Jordi Díaz.

The authors have shown that can be used to make automatic daily estimates of snowmelt intensity. The rise in due to snowmelt has a daily cycle that starts at the beginning of the afternoon after a few hours of insolation. According to this study, when the snow fusion intensity ranges between weak and moderate, the rise in flow features a sensible reduction toward the end of the night hours. During the most intense episodes, the river flow is more stable along the day, but is still more intense during the afternoon.

"Under good circumstances, that is, with low noise level caused by human activities, seismic records can be a useful tool to study and monitor this kind of hydrological phenomena in the long-term scale and can contribute, for instance, to understand the outcomes of climate change," concludes Jordi Díaz.

More information: Jordi Díaz et al. Hierarchical classification of snowmelt episodes in the Pyrenees using seismic data, PLOS ONE (2019). DOI: 10.1371/journal.pone.0223644

Journal information: PLoS ONE