the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 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.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-1534', Bernard Twaróg, 03 May 2026
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RC2: 'Comment on egusphere-2026-1534', Anonymous Referee #2, 03 Jun 2026
The submitted manuscript discuss the use of seismic stations located at distances between 0.4 and 3 km of the river to monitor flood events in the Tagliamento River (Carnic Alps). In my opinion, the manuscript is of interest, as it analyzes the potential use of permanent stations to monitor river floods, while many of the contributions on fluvial seismology are based on temporary deployments. Using a permanent stations to monitor river processes can eventually facilitates its use as alert system and makes it possible to perform long-term analysis. Besides, the authors analyze the three seismic components, discussing the polarity of the signals, a point not very common in this kind of studies. The studied area is highly instrumented with meteorological and hydrological stations, providing an excellent framework to identify the imprint of floods in the seismic data. The manuscript is in general correctly structured and clearly written and, in my opinion, deserves publication, although there are room for improvement in both text and figures.
The authors make a good work in using Spearman coefficient and their interpretation sounds, in general solid. However, I’m not convinced about their interpretation of the results for BOO; while the frequency range with high correlation around 20 Hz seems fine, the peak at 1-5 Hz is not very convincing, as it is located at the edge of the freq. range and only spans one freq. interval. I would like to see some arguments to defend the representativity of this peak or, otherwise, focus only in the higher frequency range.
Although the discrimination between seismic signals generated by wind, rain and flood is, in my opinion, very difficult to assess and depends strongly on each site, the authors make a good job in trying to identify the different origins.
The time delay between the largest PSD and water heights are quite surprising. Other studies have reported time lags between seismic and hydrological data, but, to my knowledge, not reaching six hours, as in this case. This fact has to be highlighted and more extensively discussed. As the authors stated, this could be interpreted considering that the seismic noise is generated after the beginning of the flood, when larger boulders are mobilized. However, a six hour delay seems difficult to justify.
The hysteresis discussion can be improved, in particular by discussing its counterclockwise sign and it possible interpretation.
As a lateral comment, I was a bit surprised to do not found a single seismic wiggle along the manuscript. As discussed later, I think that Fig. 3 can include, in addition to spectrograms, panels showing the seismic wiggles to better illustrate the signal analyzed.
The main conclusion of the work is that permanent stations located at few kilometers from the river bed can be used to detect large scale floods, as those generated by the Cioran storm, but fails to detect intense but shorter events. This is stated in the text, but should me clearly reminded in the Conclusions.
Detailed comments
Introduction
L 104. The use of quotation marks seems strange here
L 105: “The area is tectonically active”. If the sentence is retained, provide some indication to prove that (seismic activity, evidences for active faults, etc..)
Section 1: I think that a. comment about the steepness of the river is needed: presence of falls, steady gradient, changes along in steepness along the investigated area, riverbed width?
Figures 1 and 2: Using a topographic map instead of a satellite image as a background will make the figure more readable. In their present form, the background is very dark and features as the Fella-Sava fault are hardly visible.
The Introduction section could be rearranged: meteorological data is included in sections 1.2 and 1.3, a section discussing the geometry of the rived bed (steepness, presence of falls, width of the channel…) should be added.
I think the structure of the paper will be clearer if the information relative to seismic data and processing are presented in a different section “2. Seismic data and processing”, including the sections 1.4, 1.5, 1.6 of the submitted manuscript.
L 190: A reference for the different packages is probably needed.
L 199: “mainly” can be suppressed (microseismic peak extends form 0.05 to 1 Hz)
L 201: Obspy can be referred by a usual citation (Krischer et al 2015)
L 210: Precise the kind of meteorological time series (wind, rainfall)
L225: You could add a sentence stating that the numbers in brackets following each stations are those appearing in Fig. 2
L235: I think it can be useful to comment the distance between the seismic, meteo, and hydro stations for each set.
Results
L 279: Figure 3 shows the spectrograms, but not the PSD curves
L 287: Based on the spectrograms, stating that FUSE noise id linked to wind and rain above 30 Hz and flood at lower freq. seems nor justified. I propose to suppress this comment here and retake the discussion when commenting Fig. 7
Note that the spectrograms in the figure 3, altogether with the wind speed values and the late increase of water height suggest that most of the noise is due to wind. I propose to state in this section that spectrograms suggest a strong contribution to wind, but that the detailed analysis presented in the next section prove that flood has a clear role in explaining the noise at low frequencies.
In the previous section it has been stated that wind bursts arrived to 100 km/h, while the graphics here only show values around 15km/h. I understand that these are mean values over a time period, but still the difference is quite sticking and should be commented.
Fig. 3: As commented above, I would appreciate to include here panels showing the seismic wiggles.
Fig. 4: Although PSD and water height are compared later, you may consider to add here the water heigh curve
Section 2.3
Fig. 5: As the correlations are calculated in 5 Hz intervals overlapping intervals in steps of 1 Hz, I would suggest to label the frequency panels using simply 1,5,10,15…Hz ticks, instead of using “1-5”, “7-11” etc
As commented above, I see a difference between the low frequency correlation at BOO and MPRI. While in the later the correlation peaks at 2-6 Hz, the coefficient remain high till at least 12 Hz and then diminishes smoothly. On contrary, for BOO there is only a peak in the 1-5 Hz, that I suspect that may be due to some kind of spurious feature. I would appreciate a discussion on the real significance of the first peak at BOO
The large lag times observed, between 3 and 6 hours are quite surprising and should be highlighted in the text, indicating that their origin will be discussed later.
Fig. 8: Explicit that the observed hysteresis curves are counterclockwise and comment that the hysteresis is very clear at MPRI, less consistent FUSE and BOO (17-21) and much least evident for BO= (1-5Hz)
L 384: Several paragraphs start with “Moreover”, “furthermore” that could be suppressed
Figure 9: While two of the panels show the full backazimuth range (0-180), the two others focus on a very limited range (160-185º, 148-178º). This makes their visual comparison difficult. Use the full range for all the cases and comment that in some cases, the difference in polarization during flooding is smaller than in others
Discussion
L 405: The attenuation with distance of high frequency signals can be documented citing any general seismology book, no need to refer to contributions focused on fluvial seismology.
L409: Stating that the PSD reaches its maximum “just before peak water height” is confusing, taking into account that the observed time lags are of several hours !!
L442: The reference should be to Fig 5
L448: The reference should be to Fig.7
L449-453: AS stated before, this time lags are surprisingly large and should be discussed in further detail
Section 3.3:
Comment on the significance of the counterclockwise hysteresis direction observed. Several authors have commented the presence of clockwise and counterclockwise hysteresis in fluvial seismology and discussed its possible origin. The different degree of hysteresis observed at the 3 stations can also be discussed
Citation: https://doi.org/10.5194/egusphere-2026-1534-RC2
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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.