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https://doi.org/10.1051/e3sconf/202341503025

MAMODIS - A low-cost monitoring system for debris flows
based on infrasound and seismic signals
Andreas Schimmel1* and Matteo Berti21Andreas Schimmel - Alpine Monitoring Systems, www.almosys.at, Mkt. Piesting, Austria
Dipartimento di Scienze Biologiche, Geologiche e Ambientali, University of Bologna, Bologna, Italy

2Abstract. The automatic detection of sediment related disasters like landslides, debris flows and debrisfloods, gets increasing importance for hazard mitigation and early warning. Past studies showed that suchprocesses induce characteristic seismic signals and acoustic signals in the infrasonic spectrum which canbe used for event detection. The presented system MAMODIS (MAss MOvement Detection andIdentification System) is a detection system for debris flows, debris floods and avalanches based on acombination of infrasound and seismic signals. The detection system consists of one infrasound sensor,
one geophone and a microcontroller, where a specially designed detection algorithm is executed. Thisalgorithm reliably detects events in real time directly at the sensor site. The setup can be easily installed
beside a torrent or an avalanche path and therefore can be used as a low-cost and practicable solution forearly warning. In addition, this system offers first information of the process-type and a rough estimationof the peak discharge and the total volume for debris flows and debris floods. These values are calculated
from the infrasound and seismic signals. Currently the system is installed on several test sites in Austria,
Switzerland and Italy.

1 Introduction
Automatic detection of alpine mass movements is an
important tool for protecting people and property in thefast socio-economic developing mountain areas.
Alpine mass movements like debris flows anddebris floods induce waves in the low-frequency
infrasonic spectrum and characteristically seismicwaves. These infrasound and seismic waves producedby the mass movement can be used for detecting events
before a surge passes the sensor location and tomonitor mass movements from a remote location
unaffected by the process.
There have already been several approaches forautomatic detection of debris flows based on seismic
signals (e.g. [1,2]) and also infrasound signals arecommonly used for detecting avalanches or debris
flows (e.g. [3]). Seismic and infrasound waves havedifferent advantages and disadvantages, so a
combination of both technologies can increase
detection probability and reduce false alarms (e.g. [4]).
However, up to date no system has been designed
which uses a combination of low-cost seismic andinfrasound sensors for an automatic detection of
sediment related disasters of different types. So thiswork aims to develop a reliable automatic detection
system for alpine mass movements, which is based on
one infrasound and one seismic sensor and can detect

different processes in real time directly at the sensor
site. Further, the infrasound and seismic signals areused to identify the process type and to get an
estimation of the event-magnitude.

2 System Setup
The MAMODIS system (MAss MOvement Detection
and Identification System) is based on a modular setup
to offer a inexpensive solution for different
applications, like protection of traffic lines bycontrolling a traffic light, protection of construction
sites inside the channel (e.g. for cleaning up a basin
after an event) or at regions where a temporary
protection is enough.
The infrasound sensor used for the MAMODIS
system is a modified differential pressure sensor of thetype Sensirion SDP816 with a measurement range
from -12.5 to 125 Pa. As seismic sensors, we use theSensor NL SM-6 with a sensitivity of 28.8 V/m/s and anatural frequency of 4.5 Hz. The system offers thepossibility for a second geophone input, which can beused for an estimation of the mass movement velocity.
The process velocity is calculated via cross-correlationof booth seismic signals [5]. This method is still underdevelopment and will be implemented in a futureversion of the system.

* Corresponding author: andreas.schimmel@almosys.at© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0(https://creativecommons.org/licenses/by/4.0/).

E3S Web of Conferences 415, 03025 (2023)
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https://doi.org/10.1051/e3sconf/202341503025(depending on the equipment), which makes thissystem very suitable for stand-alone stations using asolar power supply, as is typically used. A typicalsystem setup is shown in Figure 2.

The sensor signals have to be adapted for the inputof the microcontroller, which is done by a noninverting OPV circuit. This input circuit also has aband pass filtering with a lower cut-off frequency ofaround 150 mHz (for acoustic sensors) and an upper
cutoff frequency of 150 Hz (acoustic and seismicsensors). These input signals are sampled by the
microcontroller ADC (analog-to-digital converter) witha sample rate of 100 Hz.
A Texas Instruments development board with themicrocontroller TM4C129X is used for the dataprocessing and as data-logger. The software for the
microcontroller is based on the open source runtime
system FreeRTOS. The development board has two 12bit ADC modules, eight UARTs (Universal Asynchronous Receiver Transmitters), several GPIOs(General Purpose Input/Output), which can be used as
alarm outputs, and a Liquid Crystal Display (LCD)
with touchscreen function. It also offers the possibilityof an Ethernet connection. The data can be stored on amicro SD card where sizes of 8 GB, 16 GB or 32 GB
can be used, and up to eight months (32 GB, onegeophone) of data can be recorded continuously.
Besides the input of the sensor signals, the free ADCs
offer the possibility to log the flow height measured bya radar or ultrasonic gauge (input 4-20 mA), which canbe used for event verification. In addition, the power
supply voltage is monitored to check for low power. If
the test site is equipped with a standard internetconnection, the communication with the system can be
conducted via the Ethernet interface. If there is norouter available, we use a GSM module of the type
Adafruit FONA. The system is designed to send astatus message to a server every hour, whereby the dateof the event detections or error messages are included.
This server creates e-mail alerts in the case of an event.
A web-server is installed on this server as well, where
the status and events of all stations can be checked(http://mamodis.ddns.net/).
The time synchronization of the station is done byeither a connection with a time server via Ethernet or
GSM module, or by a GPS module, which is also
connected via the UART. The alarm output can bedone by Relays or via a radio link (RF-Module:
GAMMA LoRA). An overview of the hardware
components and the inputs and outputs of the system isgiven in Figure 1.

Fig. 2. System setup at the sites Kühgraben (left) andTorrente Blé (right).

The MAMODIS System is currently installed on 12
sites in the Alps (Figure 3). Nine sites are debris flow
catchments and at three sites the system is tested forsnow avalanche detection. Data and further
information of these sites are available at:
http://mamodis.ddns.net

Fig. 3. Systems installed in 2021 (blue dots: snow
avalanches, red dots: debris flow)

3 Detection Algorithm
The principle of the detection algorithm is alreadypresented in [6] so only a short summary is given
below. For the automatic detection of debris flows
based on seismic and infrasound data, a detection
algorithm had to be developed, which identifies events
as early as possible, without false alarms, in a simple
way, so that the algorithm can be used in real time
directly at the sensor location without extensive
requirements on computing effort (on a resource
limited microcontroller).
The developed detection algorithm analyses theevolution in time of the frequency content from theinfrasonic and seismic mass movement signals. To thispurpose, different frequency bands are used to analyse
the infrasound signal, whereby a 3 to 15 Hz bandcharacterises debris flows and a 15 to 45 Hz band isused for debris floods. For the seismic signals afrequency band from 10 to 30 Hz is used for both event
types. Different criteria has to be fulfilled for theDetection-Time Tdet (20 s) to identify events:
 The average infrasound and seismic amplitudes ofthe debris flow/debris flood frequency bands haveto exceed a certain threshold (to distinguishFig. 1. Overview system setup and components.

The system operates at a voltage of 5 V, provided
by a DC–DC converter, which needs a power
connection at a voltage range from 6.5 to 32 V. The
system has a power consumption between 0.7 to 1.2 W2E3S Web of Conferences 415, 03025 (2023)
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ground, geometric spreading and the influence of
topography or geology.
This analysis shows that, for peak discharge, apower curve fitting offers a good approach to find an
initial relationship between the recorded signals andthis event parameter.

between different event sizes, two limits are usedfor Level 1 and Level 2).
 The average infrasound amplitudes of the debris
flow or debris flood frequency band has to be atleast above a third (for debris flows) or a fourth(for debris floods) of the amplitudes of thefrequency band below (1-2 Hz) This can avoid
false alarms due to wind, that dominates this lowfrequency band.
 The variance of the seismic and infrasoundamplitudes have to be under a limit (to avoid false
alarms from artificial sources, since this variancein the amplitudes of the broad-banded debris flow
or debris flood signals is low, compared tonarrow-banded signals from artificial sources).
 Because bedload transport processes as well as
debris flows and debris floods can be detected, afurther criterion is needed to enable identificationof event type. For debris flow/debris flood
detection, the seismic amplitude has to rise atleast beyond the threshold used for the amplitude
criterion during the detection time.
Using the combination of the seismic and infrasoundsignals, we achieve a high detection ratio and a strong
reduction in the frequency of false alarms.

Fig. 4. Peak discharge over maximum seismic (Max GEO)
and infrasound amplitudes (Max IS) and the approximation
based on infrasound data (Pow. Approx. (IS)) and seismic
data (Pow. Approx. (GEO)).

This curve fitting provides a R2 of 0.76 for peakdischarge based on infrasound data and a R2 of 0.65
for the seismic data. The approximation for peakdischarge Qpeak (in m3/s) can be calculated based on themaximum infrasound amplitudes AIS(max) (in mPa) andthe maximum seismic amplitudes AGEO(max) (in10−7 m/s) according to Equation (1).

4 Magnitude Estimation
The system also offers a first estimation of the event
size of debris flows or debris floods based on theinfrasound and seismic data. The infrasound andseismic energy correlates passably with the dischargeof an event (e.g., [7]), so we compared the maximum
infrasound and/or seismic amplitudes with the peakdischarge of an event (Figure 4).
The values for peak discharge and total volume
used for this analysis are from Level 2 events at theLattenbach, Gadria and Illgraben test sites (Table 1)
and are calculated based on flow height measurements
and velocity estimations.

Qpeak =The peak discharge is calculated as the mean of bothrelations and this overall calculation offers a R2 of0.967. For an estimation of the total volume, we
integrate the discharge calculated with the relationshipfor peak discharge (Equation (1)) over the entire
detection time of an event. Figure 5 and 6 compares thecalculated values (vertical axis) for peak discharge andtotal volume to the observed values (horizontal axis).
The line represents the one-to-one relationship.

Table 1. Peak discharge and total volume of used events.

Test Site

Lattenbach

GadriaIllgraben

Event-Date
09.08.2015
10.08.2015
16.08.2015
10.09.2016
15.07.2014
08.06.2015
12.07.2016
22.07.2015
10.08.2015
14.08.2015
15.08.2015
12.07.2016
22.07.2016
09.08.2016

PeakDischarge[m3/s]
50
69
12158
na
na
na
17
7
73
15
50-90
29

1(0.0001019598 AIS(max) 1.982999
2+ 0.000332 AGEO(max) 1.715603 ) (1)

Total
Volume
[m3]
11500
18500
5000
46000
10500
9850
1500
8700
6100
25000
2000
10000
>10000<10000Since all monitoring stations used for this study are
rather close to the channel (between 10 and 20 m) andthe distances are nearly the same at every test site, weneglected attenuation of the signals in the air or in theFig. 5. Comparison of the calculated peak discharge to theobserved values;3E3S Web of Conferences 415, 03025 (2023)
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References
1.

2.

3.

4.

Fig. 6. Comparison of the calculated total volume to theobserved volume.

Both diagrams suggest that it is possible to obtain firstorder estimates of the peak discharge and the total
volume for debris flows and debris floods at different
sites based on the infrasound and seismic amplitudes.
The calculation of the peak discharge based on a
combination of infrasound and seismic data offers agood approximation (R2 = 0.912), for the total volume,
this method shows a larger variance (R2 = 0.880).

5.

6.

7.

5 Conclusions
This paper presents an approach for a detection
system for different kinds of alpine mass movements
based on one infrasound sensor, one co-locatedgeophone and a microcontroller. The system consistsof widespread low cost sensors and components(differential pressure sensor, standard geophone,microcontroller board) in a modular setup, so it isinexpensive, portable and easy to install and can beextended to an early warning system without much
effort. The combination of infrasound and seismic
signals can increase the detection probability andreduce false alarms. However, sensor equipment andinstallation location have to be chosen carefully andparameters of the detection algorithm may have to beadapted to the particular application and thebackground noise of the site.
Initial analyses of different event types anddifferent magnitudes have shown a dependency of thepeak frequency range on the viscosity and a relation of
the maximum infrasound and seismic amplitudes to theevent magnitude. So it is possible to estimate peakdischarge and total volume from the infrasound andseismic signals, but there are still high uncertainties. In
fact, beside the magnitude, flow velocity and thesediment concentration have also a large influence on
the seismic and infrasound amplitudes of a debris flow,
so including them in a next step in the magnitude
estimation could lead to more accurate results.

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