| 09 Apr 2026
Seismic analysis of bedload discharge at Tagliamento River during flood events
Abstract. Understanding river dynamics during flood events is critical for effective hazard mitigation and water resource management, especially as extreme weather events become increasingly frequent. Environmental seismology, which consists in monitoring natural surface processes with seismic instruments, has gained considerable attention over the past two decades. During floods events continuous seismic signals, also called seismic noise in this context, are generated by the turbulent flow and the transported bedload at the riverbed. If recorded at nearby seismic stations (i.e. from the riverbank to a few hundred meters), these seismic data become an important source of information complementing traditional methods (e.g., stream gauge, bedload basket sampler) to improve models and early warning systems. Despite the increasing number of case studies worldwide, the potential of seismic monitoring to capture flood-induced natural river processes in the Alps remains underexplored, particularly regarding the opportunistic use of existing stations from permanent network(s) originally deployed for earthquake monitoring. This study investigates the potential of records from permanent seismic stations relatively far from the river (up to ∼3 km) to assess bedload discharge and river flow dynamics during flood events in one of the rare morphologically preserved alpine rivers, the Tagliamento River in northern Italy. Seismic data from three selected stations at the subwatershed scale (i.e., spaced by about 20 km at maximum) were analysed together with hydrological and meteorological measurements such as water height, rain rate, and wind velocity, hence allowing to identify specific frequency bands for which seismic amplitude timeseries correlate with weather and river components. For particular frequencies, we notably observe a hysteresis behaviour between seismic amplitudes and the rising and falling phases of flood event, suggesting seismic source mechanisms related to turbulent flow and/or the movement of coarse sediments. The study demonstrates that even stations not specifically positioned close to the riverbed can capture valuable information on flood dynamics, thereby providing an early indication of flood propagation. These findings highlight the potential for incorporating seismic monitoring into flood forecasting and river management strategies, contributing to enhanced hazard mitigation efforts in the context of increasingly frequent extreme meteorological events. More specifically, the present study also helps in gaining information about the Tagliamento catchment response and relative seismic signatures during flood events for further investigations in developing early warning systems based on seismic data.
The study presents a very interesting experiment based on real-world data — it analyzes a natural river and actual flood events. Methodologically, the work is sound; however, there are significant doubts at the level of result interpretation. At the same time, the study has high practical value. Particular attention should be given to the interdisciplinary approach, combining seismology, hydrology, and meteorology. Another important strength is the clever use of an existing seismic network, originally designed for earthquake monitoring, which demonstrates the potential of low-cost solutions in environmental research. The analysis of time lags is of considerable scientific value, as it is important from a hydrological perspective and may have predictive potential. Equally important is the distinction between classical floods and flash floods, which constitutes a meaningful contribution to the interpretation of fluvial processes. Additionally, the observation of hysteresis strengthens the credibility of the results. The greatest contribution of the study, however, is demonstrating that seismic signals can be used to monitor rivers even from relatively large distances.
One of the main issues in the study is the lack of clear separation of seismic signal sources (river vs. wind vs. rainfall). The authors assume that the river dominates at low frequencies, while wind and rainfall dominate at high frequencies. However, the results show a high correlation of wind (0.7–0.8) across the entire analyzed frequency range. Despite this, low frequencies are primarily attributed to river processes, indicating interpretative inconsistency and a lack of effective source separation.
Another concern is the assumption that the vertical component of the signal (interpreted as Rayleigh waves) directly corresponds to river processes. At distances of 2–3 km, the signal may be significantly attenuated, scattered, or mixed with other wave types (e.g., body waves) and noise. There is no direct evidence supporting this assumption, such as phase analysis or more advanced wavefield analysis.
The interpretation of the characteristic “V-shape” in spectrograms is speculative. The authors suggest two possible explanations: migration of the source (flood wave front) or changes in the size of transported material. However, no analysis is provided to distinguish between these hypotheses.
Similarly, the interpretation of time lags between seismic signals and peak water levels appears oversimplified. These delays may result not only from hydrological processes but also from the geometry of the measurement setup, spatial differences between stations, or data artifacts. The study does not include analysis that would allow these factors to be clearly distinguished.
The conclusions regarding flash floods are also questionable. The claim that the absence of a seismic signal implies the absence of sediment transport represents a logical fallacy (absence of evidence is not evidence of absence). Alternative explanations — such as insufficient signal strength, short event duration, or masking by noise — are not adequately considered.
Another important limitation is the relatively large distance between seismic stations and the river (0.4–3 km), which may lead to significant signal attenuation and hinder clear interpretation of its sources.
Additionally, the study lacks direct field data on sediment transport (e.g., in situ granulometric measurements), meaning that conclusions about bedload are indirect and not empirically validated.
Another issue is the reliance primarily on correlation analysis. Correlation does not imply causation and may result from the influence of a common variable, such as rainfall affecting both river discharge and seismic noise simultaneously. The study does not attempt to disentangle these effects.
Finally, the selected frequency range (1–40 Hz) may be limiting. Rainfall often generates signals at higher frequencies (>50 Hz), and excluding frequencies below 1 Hz may result in the loss of important information about longer-period processes.