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Mayotte seismic crisis: Building knowledge in near real-time by combining land and ocean-bottom seismometers, first results



The brutal onset of seismicity offshore Mayotte island North of the Mozambique Channel, Indian Ocean, that occurred in May 2018 caught the population, authorities, and scientific community off guard. Around 20 potentially felt earthquakes were recorded in the first 5 days, up to magnitude Mw 5.9. The scientific community had little pre-existing knowledge of the seismic activity in the region due to poor seismic network coverage. During 2018 and 2019, the MAYOBS/REVOSIMA seismology group was progressively built between four French research institutions to improve instrumentation and data sets to monitor what we know now as an on-going exceptional sub-marine basaltic eruption. After the addition of 3 medium-band stations on Mayotte island and 1 on Grande Glorieuse island in early 2019, the data recovered from the Ocean Bottom Seismometers were regularly processed by the group to improve the location of the earthquakes detected daily by the land network. We first built a new local 1D velocity model and established specific data processing procedures. The local 1.66 low VP/VS ratio we estimated is compatible with a volcanic island context. We manually picked about 125,000 P and S phases on land and sea bottom stations to locate more than 5,000 events between February 2019 and May 2020. The earthquakes outline two separate seismic clusters offshore that we named Proximal and Distal. The Proximal cluster, located 10km offshore Mayotte eastern coastlines, is 20 to 50 km deep and has a cylindrical shape. The Distal cluster start 5 km to the east of the Proximal cluster and extends below Mayotte's new volcanic edifice, from 50 km up to 25 km depth. The two clusters appear seismically separated, however our dataset is insufficient to firmly demonstrate this.
Geophys. J. Int. (2022) 228, 1281–1293
Advance Access publication 2021 September 24
GJI Seismology
Mayotte seismic crisis: building knowledge in near real-time by
combining land and ocean-bottom seismometers, first results
Jean-Marie Saurel ,1Eric Jacques,1Chastity Aiken ,2Anne Lemoine ,3
Lise Retailleau,1,4Aude Lavayssi`
eane Foix,2Anthony Dofal ,1,5
ele Laurent,1Nicolas Mercury,3,6Wayne Crawford,1Arnaud Lemarchand,1
Romuald Daniel,1Pascal Pelleau,2Maxime B`
es de Berc,6Gr´
egoire Dectot,7
Didier Bertil,3Agathe Roull´
eleste Broucke,8Alison Colombain,3H´
ene Jund,8
Simon Besanc¸on,1Pierre Guyavarch,2Philippe Kowalski,1,4Micka¨
el Roudaut,2
Ronan Apprioual,2Jean Battaglia,9Soumya Bodihar,1Patrice Boissier,1,4Marie
Paule Bouin,1Christophe Brunet,1,4K´
evin Canjamale,1,4Philippe Catherine,1,4
Nicolas Desfete,1,4C´
ecile Doubre,6R´
emi Dretzen,8Tom Dumouche,1Philippe Fernagu,2
Val ´
erie Ferrazzini,1,4Fabrice R. Fontaine,1,5Arnaud Gaillot,2Louis G´
Cyprien Griot,1,4Marc Grunberg,8Emre Can Guzel,10 Roser Hoste-Colomer,3
Sophie Lambotte,6Fr´
eric Lauret,1,4F´
elix L´
eger,1Emmanuel Maros,2Aline Peltier,1,4
ome Vergne,8Claudio Satriano,1Fr´
eric Tronel,7J´
ome Van der Woerd,6
Yves Fouquet,2Stephan J. Jorry,2Emmanuel Rinnert,2Isabelle Thinon11 and
Nathalie Feuillet1
e de Paris, Institut de Physique du Globe de Paris, CNRS, F-75005 Paris, France. E-mail:
2IFREMER, Centre de Bretagne, –Unit´
eosciences Marines, 1625 Rte de Ste Anne, 29280 Plouzan´
e, France
3BRGM, French Geological Survey, Risk and Prevention Division, F- 45100 Orl´
eans, France
4Observatoire volcanologique du Piton de la Fournaise, Institut de Physique du Globe de Paris, F-97418 La Plaine des Cafres, La R´
eunion, France
eunion, Laboratoire G´
eoSciences R´
eunion, F-97744 Saint Denis, La R´
eunion, France
6ITES, Institut Terre Environnement de Strasbourg, UMR 7063, CNRS Universit´
e de Strasbourg, 5,rueRen
e Descartes, 67084 Strasbourg, France
7BRGM, French Geological Survey, Regional Division (Mayotte), F-97600 Mamoudzou, Mayotte, France
8EOST, Universit´
e de Strasbourg/CNRS, 5rue Descartes, 67084 Strasbourg Cedex, France
e Clermont Auvergne, CNRS, IRD, OPGC, Laboratoire Magmas et Volcans, F-63000 Clermont-Ferrand, France
10Istanbul Technical University, Faculty of Electrical and Electronics Engineering - Graduate School, Electronics and Communications Engineering
Department, 34469 Maslak/Istanbul, Turkey
11BRGM, French Geological Survey, Georesources, F-45100 Orl´
eans, France
Accepted 2021 September 22. Received 2021 September 14; in original form 2021 February 24
The brutal onset of seismicity offshore Mayotte island North of the Mozambique Channel,
Indian Ocean, that occurred in May 2018 caught the population, authorities and scientific
community off guard. Around 20 potentially felt earthquakes were recorded in the first 5 d,
up to magnitude Mw5.9. The scientific community had little pre-existing knowledge of the
seismic activity in the region due to poor seismic network coverage. During 2018 and 2019,
the MAYOBS/REVOSIMA seismology group was progressively built between four French
research institutions to improve instrumentation and data sets to monitor what we know now
as an on-going exceptional submarine basaltic eruption. After the addition of 3 medium-band
stations on Mayotte island and 1 on Grande Glorieuse island in early 2019, the data recovered
from the Ocean Bottom Seismometers were regularly processed by the group to improve the
location of the earthquakes detected daily by the land network. We first built a new local 1-D
velocity model and established specific data processing procedures. The local 1.66 low VP/VS
ratio we estimated is compatible with a volcanic island context. We manually picked about
The Author(s) 2021. Published by Oxford University Press on behalf of The Royal Astronomical Society. This is an Open Access
article distributed under the terms of the Creative Commons Attribution License (, which
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1282 J.-M. Saurel et al.
125 000 Pand Sphases on land and sea bottom stations to locate more than 5000 events
between February 2019 and May 2020. The earthquakes outline two separate seismic clusters
offshore that we named Proximal and Distal. The Proximal cluster, located 10 km offshore
Mayotte eastern coastlines, is 20–50 km deep and has a cylindrical shape. The Distal cluster
start 5 km to the east of the Proximal cluster and extends below Mayotte’s new volcanic edifice,
from 50 to 25 km depth. The two clusters appear seismically separated, however our data set
is insufficient to firmly demonstrate this.
Key words: Indian Ocean; Volcano seismology; Volcano monitoring; Africa; Remote sensing
of volcanoes.
Before 10 May 2018, Mayotte island, part of the volcanic Comoros
archipelago in the North Mozambique Channel of the Indian Ocean
(Fig. 1), was not considered as a significantly seismically active area
(Bertil & Regnoult 1998). The last reported widely felt earthquakes
occurred around 30 km west of Mayotte: a moment magnitude (Mw)
5.0 event on 9 September 2011 (EMS98 intensity V estimated) and a
magnitude (M) 5.2 event on 1 December 1993 (Lambert 1997) with
moderate damages (EMS98 intensity VI estimated). Together with
an unfelt M5.1 event on 23 March 1993, 80 km southwest of May-
otte, these were the only M5+earthquakes recorded within 100 km
of the island since the advent of the global seismological networks
in 1964 (Storchak et al.2017;ISC2020). As a consequence, only
one real-time seismic station (RA.YTMZ; R´
esif 1995) was installed
on the island at the onset of the 2018 seismic crisis. This station was
deployed by BRGM (Bureau de recherches g´
eologiques et mini`
the French geological survey) for the French accelerometric moni-
toring network (R´
esif-RAP, P ´
equegnat et al.2008).
On 10 May 2018, the first felt earthquake, quickly followed by
many others, surprised inhabitants. More than 130 M4+earth-
quakes were recorded in the following months, with the strongest
being a Mw5.9 on 15 May 2018 (GCMT project, Dziewonski et
om et al.2012; Lemoine et al.2020a). After about
50 d of very intense seismic activity, this unprecedented seismic
sequence continued less intensively. During the summer of 2018,
Global Navigation Satellite System (GNSS) data from the locally
continuously recording sites began to show rapid surface displace-
ments of the island (Briole 2018;Cescaet al.2020; Lemoine et al.
2020a). Their elastic modelling evidence a large regional deflation
centred east of Mayotte’s shorelines (Cesca et al.2020; Lemoine
et al.2020a). On 11 November 2018, a very low frequency tremor
was recorded worldwide (Satriano et al.2019; Cesca et al.2020;
Lemoine et al.2020a), confirming that the seismic crisis was very
likely of magmatic origin. This was later confirmed by the discov-
ery of a new submarine volcanic edifice offshore Mayotte during
the MAYOBS1 scientific expedition onboard RV Marion Dufresne
in May 2019 (Feuillet et al.2021). This large eruption began either
on June 18 (Cesca et al.2020) or on 3 July 2018 (Lemoine et al.
Since the onset of the crisis, collaborations were progressively
established between French research institutes to improve the under-
standing and knowledge of the on-going crisis. These collaborations
enhanced the seismic monitoring of the region, which included in-
stalling additional real-time sites onshore, access to real-time data
recorded by existing regional stations and offshore deployments.
During the first year of the crisis, the monitoring network thus
evolved rapidly (Lemoine et al.2020a). In March 2019, 1 month
after funding, four seismic stations were installed onshore (three
on Mayotte island and one on Grande Glorieuse island) and six
Ocean Bottom Seismometers (OBS) were deployed offshore, within
a radius of 40 km around the seismically active area. A seismol-
ogy team was created among the researchers, engineers, and stu-
dents belonging to the participating French institutions (BRGM;
Institut de Physique du Globe de Paris—IPGP; Institut Franc¸ais
de Recherche pour l’Exploitation de la Mer—IFREMER; Insti-
tut National des Sciences de l’Univers du Centre National de la
Recherche Scientifique—INSU-CNRS). In July 2019, the Mayotte
seismo-volcanic monitoring network (R´
eseau de surveillance vol-
canologique et sismologique de Mayotte—REVOSIMA) was cre-
ated with all four institutions. The aim of the team is to process
newly acquired data as quickly as possible and to obtain first hand
results in almost real-time, to improve the daily monitoring and the
knowledge of the volcano-seismic crisis.
In this paper, we review the local seismic network improvements
since the beginning of the crisis and our scientific developments. We
detail how this collaborative work was orchestrated for maximum
efficiency and how it led to an improved local velocity model and
a seismic catalogue from February 2019 up to May 2020 to better
document the Mayotte 2018-ongoing seismo-volcanic crisis.
From May 2018 to June 2019, the Mayotte local real-time seis-
mic network progressively evolved from 1 to 8 stations. Daily data
analysis protocols have also been continuously adapted in several
Institutes by our group to take advantage of the increasing number
of local stations and to produce better locations for the detected
events (see details in Section 2.2). In 2019, we also developed a
new protocol to efficiently process OBSs data during pickathons,
when, at the same place, several analysts dedicate a few days to
work together on the newly recovered data.
2.1 Development of the monitoring network
2.1.1 The in-land network
At the beginning of the seismic crisis, Mayotte’s seismicity was
monitored by the BRGM with the only local real-time seismic
station from the French R´
esif-RAP accelerometric RA network
esif 1995) and some regional stations from international
networks (IRIS/IDA, GEOFON and GEOSCOPE in Madagascar,
Kenya, Seychelles and La R´
eunion). In the Comoros archipelago,
the Observatoire Volcanologique du Karthala (OVK) monitors the
Karthala volcano (Grande Comore) since 1988. The OVK seismic
network, while located 250 km northwest from Mayotte (Fig. 1b),
was crucial for characterizing Mayotte’s seismicity, particularly at
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Mayotte seismic crisis: first results from marine and land seismic deployments 1283
Figure 1. Maps of seismological land stations and Ocean Bottom Seismometers (OBSs) used in this study with the red volcano symbol representing the
location of the new volcanic edifice (Feuillet et al.2021). (a) Map showing the regional stations contributing to the monitoring (yellow inverted triangles).
Red rectangles highlights the Comoros archipelago area shown in (b) and the Mayotte area shown in (c). (b) Map of the Comoros archipelago showing the
temporary stations used for previously-developed velocity profiles (orange squares), historical M>5,0 earthquakes close to Mayotte (white stars) and the
Karthala seismic network (yellow inverted triangles). (c) Map of the local land stations (green inverted triangles, most of them installed in 2019) and all OBSs
deployed between February 2019 and May 2020 [blue inverted triangles, the blue hue depends on the MAYOBS deployment timing as seen in (d)]. The MAYO
station (orange square) is the temporary station used by Dofal et al.(2018) receiver function study. The white dots represent the 5000 manually relocated
earthquakes. (d) Time evolution of the number of recording stations since the onset of the crisis. All regional stations (dark grey) are available in real-time.
Local stations (added to the regional stations; in grey)—significantly increased in number in 2019. The number of OBSs (added to the local and regional
stations; in light grey) varies over time depending on the MAYOBS deployment period (blue scale on bottom right numerated as the MAYOBS oceanographic
campaigns that recovered them). The dashed line represents the evolution in time of the number of real-time stations.
the beginning of the sequence. Real-time seismic data recorded at
Karthala volcano were shared during the first weeks of the crisis
via its French partner in the Indian Ocean, the Observatoire Vol-
canologique du Piton de la Fournaise (OVPF-IPGP). In June 2018, a
medium-band station was installed at a Mayotte school (ED.MCHI),
cofunded by the local representation of the ministries of environ-
ment (DEAL) and of education as well as the BRGM, within the
program Edusismo (Virieux 2000). By the end of June 2018, the
seismicity decreased after one and a half month of intense activ-
ity. At that time, the BCSF-R´
eNaSS (Bureau Central Sismologique
eseau National de Surveillance Sismique), in charge of
the macroseismic and intensity investigations on the national ter-
ritory, performed a macroseismic field survey on Mayotte (Sira et
al. 2018) and took advantage of this mission to install two Rasp-
berryShake instruments (B `
es de Berc et al.2019) from the AM
network (Raspberry Shake Community et al.2016): RAE55 and
RCBF0. RCBF0 station unfortunately failed after 2 weeks. The lo-
cal onshore network (Fig. 1) was not upgraded again until March
2019 with the installation of three stations: two Guralp CMG40T
medium-band sensors from the 1T temporary network (Feuillet, Van
der Woerd and RESIF, 2022)—MTSB and PMZI; and one Nano-
metrics Trilium120PA broad-band sensor from the QM network—
KNKL. Safety and rapid deployment on a small island, as well as
network geometry, were key criteria to choose the station sites. The
stations were therefore installed in city halls or public buildings to
ensure a stable power supply and protection from theft. In the same
time, a seismic station with triggered data transmission from the QM
network (GGLO) was installed on Grande Glorieuse, a small island
250 km northeast from Mayotte, completing the regional network in
March 2019. Finally, two RaspberryShake instruments were added
to the AM network by R´
eNaSS in June 2019 on Mayotte: R1EE2
and R0CC5 (colocated with RA.YTMZ station).
2.1.2 The OBS network
At the end of February 2019, six short-period OBSs from the
INSU-IPGP OBS facility were deployed from a barge around the
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1284 J.-M. Saurel et al.
earthquake locations that were known at the time (Bertil et al.
2019). The INSU-IPGP OBSs are free-fall instruments with 1-yr
maximum autonomy, whose sensors are a 3-channel geophone and
a broad-band hydrophone. There have been several recoveries and
redeployments of OBSs since then, but there have always been
4–16 OBSs deployed (Fig. 1d), which have greatly improved the az-
imuthal coverage of the local seismic network, as will be discussed
later in the paper. The INSU-IPGP OBSs were regularly comple-
mented with IFREMER micrOBSs or LotOBSs, hosting a similar
geophone and a short-period hydrophone but with an autonomy,
respectively, limited to 45 or 120 d maximum. After the initial de-
ployment, area specific location protocol establishment and much
more precise location of the seismicity, the OBS network geometry
remained stable and a number of positions were re-occupied during
subsequent deployments (Figs 1c and d).
Data acquisition protocol differs depending on the instruments—
land or ocean-bottom based. Data from land stations are acquired
and transferred in real-time, except the regional QM.GGLO sta-
tion from which only triggered data can be transmitted via a low-
bandwidth satellite link. The onshore data are centralized at the
IPGP data centre and then made available through the same pro-
tocol on its public SeedLink server. The three stations installed on
Mayotte in March 2019 were not equipped with internet connec-
tion during the first months of recording but were brought online
in May 2019. Their data were manually collected from the internal
storage just before the departure of the RV Marion Dufresne for the
MAYOBS1 oceanographic campaign in May 2019 (Feuillet 2019).
The OBSs are regularly serviced for maintenance and data recov-
ery (every 3–4 months for INSU-IPGP, every month for micrOBSs).
As of May 2020, nine different OBSs deployments have been con-
ducted. When the OBSs are recovered, their data are downloaded and
time-corrected for internal clock drift and converted to miniSEED
format using L-Cheapo tools (Orcutt & Constable 1996). These data
are then integrated in the main waveform database at the IPGP data
centre, along with the local and regional land station data.
2.2 Data analysis
2.2.1 Daily monitoring
For daily monitoring of the crisis, only the real-time data from land
stations can be used. Several institutes successively participated in
the day-to-day seismic data processing, using SeisComP3 (Weber et
al.2007) with slightly different setups. The BRGM office in May-
otte was involved first and maintained a seismic catalogue from the
beginning of the crisis in May 2018 (Bertil et al.2018,2019). The
events from Bertil et al.(2018,2019) were located from manu-
ally picked waveforms using the LocSAT algorithm (Bratt & Bache
1988) and a slightly modified IASPEI91 velocity model (Kennett
& Engdahl 1991). During the summer of 2019, with the addition
of new local stations available in real-time, the R´
eNaSS hosted by
the Ecole et Observatoire des Sciences de la Terre in Strasbourg
(EOST) improved the settings of its SeisComP3 automatic detec-
tion system by using STA/LTA automatic picking and grid-search
location. They took over the role of manually picking all automat-
ically detected events for the newly created R´
eseau de surveillance
Volcanologique et Sismologique de Mayotte (REVOSIMA) work-
ing group. The R´
eNaSS also used LocSAT but with the original
IASPEI91 model. In April 2020, the daily manual picking and lo-
cation duty was transferred to OVPF-IPGP in La R´
eunion, which
uses the NonLinLoc (NLL) location software (Lomax et al.2014)
and a new hybrid velocity model described in Section 3. The NLL
configuration and 1-D local velocity model used by OVPF-IPGP in
La R´
eunion were developed during MAYOBS1 campaign in 2019
(Feuillet et al.2019;Saurelet al.2019; Feuillet 2019).
While a daily manual screening of continuous waveforms with
WebObs (Beauducel et al. 2020) and identification of every event
has been performed since early 2019, the composite earthquake cat-
alogue is based on the automatic detection of events from land sta-
tions. The land stations influence the magnitude detection threshold
for two reasons. First, the land-based seismic network has evolved
since May 2018, and second, the chosen sites that offered equipment
safety are often affected by anthropogenic noise, implying a daily
variation of the magnitude detection threshold. Since the drastic
improvement of the local land network in spring 2019, the detec-
tion threshold is around M2.0 at nighttime and around M2.5 during
2.2.2 OBS integration
After each OBSs data recovery, we manually pick phases on the OBS
data and offline land stations to improve the locations in the exist-
ing earthquake catalogue during dedicated pickathons that continue
today. Adding new phase picks significantly improved the location
of the earthquakes already detected and first located only by the
land network. Since there are already a great number of events to
relocate in the existing catalogue, we do not search for new events
from the OBS data set. Searching for new events in the OBS data
set is a work in progress and will be reported in future studies.
During each pickathon, the time span of the OBSs data we need
to process is divided across three teams using the same software
setup and each team manually locates earthquakes in descending
order of magnitude (Saurel et al.2019; Fig. 2). When the OBSs
are recovered from an oceanographic research vessel, such as RV
Marion Dufresne, large enough to board a team of around 10 ana-
lysts, we divided the work in three 4-hr-shifts (i.e. 2 or 3 analysts
by shift) we can manually pick earthquakes 24/7. Otherwise, the
MAYOBS/REVOSIMA seismology group meet—either virtually
or at one of the group institutes—for 2 d to process the recently re-
covered data, produce graphics demonstrating the evolution of the
crisis, and interpret the results together. Whether the phase pick-
ing, location, and interpretation are done onboard or on land, we
use the same setup/configuration, starting database, and software
to analyse the recently recovered data. We assigned uncertainty to
each phase, from a common predefined list of values. Time un-
certainties assigned to the S-phase were always equal to or larger
than the uncertainty assigned to the P-phase. Impulsive P-phase
polarity onset is also reported for first motion source mechanisms
studies later use. We were able to locate events as small as M0.8,
but despite improvement since July 2019 and the use of more sta-
tions in the STA/LTA automatic processing, their detection is far
from complete and mainly depends on the land station daily noise
level. We estimate that the magnitude of completeness is below M
3.0 (see Section 4) whatever the time allocated to the processing
during each pickathon and the number of events processed. We
typically process around 1000 earthquakes during pickathons when
performed onboard scientific cruises and around 500 earthquakes
during pickathons conducted on land. So far, our catalogue contains
more than 5000 manually picked earthquakes from February 2019
to May 2020, relocated using combined land and OBS data.
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Mayotte seismic crisis: first results from marine and land seismic deployments 1285
Figure 2. Typical pickathon organization. After each OBS recovery, the deployment time-span is divided in three groups, that is Group 1, Group 2 and
Group 3. Each group processes the same number of events, by decreasing magnitude order, using the same software setup and the same picking guidelines
and recommendations. The daily catalogue of events, automatically detected and manually confirmed on land-based network data (BRGM then R´
eNaSS and
OVPF-IPGP), is synchronized in the pickathon database. It also feeds in real-time the REVOSIMA/MAYOBS catalogue. When OBS recovery is performed by
a research vessel, each group alternates a 4-hr day and night shift. At the end of the pickathon, the relocated events, with additional manual picks and polarities
on OBSs data, is merged within the REVOSIMA/MAYOBS database for further use for monitoring and research. The same procedure is applied to on land
pickathons, only the work is completed during 2.5 normal work days instead of 24-hr shifts.
To enable this collaborative work, we use techniques and configu-
rations developed during the last 10 yr for the daily routine process-
ing of earthquakes in IPGP volcanic and seismologic observatories.
Waveform data and event databases are held by a SeisComP3 in-
stance (Weber et al.2007). Each earthquake analyst uses their own
laptop and, regardless of their laptop’s Operating System, they run
a VirtualBox pre-configured Linux machine with the SeisComP3
Origin Locator GUI client (scolv, Weber et al.2007). We use NLL
software and the new local 1-D velocity model described in the
following section to locate the events. Magnitudes are computed
with the embedded local magnitude (ML) formula in SeisComP3
(Richter 1958). The horizontal signals are converted to a Wood-
Anderson seismometer response (Urhammer & Collins 1990)be-
fore measuring their pick amplitude. We have not yet calibrated this
magnitude as very few of the earthquakes since 2019 have been
characterized with a moment tensor magnitude by the global mon-
itoring agencies (GCMT project, Dziewonski et al.1981;Ekstr
et al.2012).
A local velocity model is essential to provide precise location of
this dense swarm seismicity. One of the first challenges in improv-
ing earthquake locations was then to build a reasonable 1-D local
velocity model, because only global models were available so far.
This was done onboard RV Marion Dufresne during the MAYOBS1
campaign (Feuillet 2019).WeusedthedataofthefirstOBSsre-
covery and of three local land stations (see Section 2). We first
produced modified Wadati diagrams (Chatelain 1978) and consid-
ered two different existing velocity profiles from the area. The first
profile, named ‘Coffin449’, is based on a P-wave velocity (VP)
profile derived from a 1980 active-seismic sonobuoy. That experi-
ment was located 100 km southeast of Mayotte (Coffin et al.1986,
instrument 449; Fig. 1b) and extended beyond 10 km depth with
a Moho interface 15 km deep (Jacques et al.2019). The second
profile, named ‘ADofal’, is based on a S-wave velocity (VS)pro-
file determined from receiver functions (Dofal et al.2018) using the
MAYO temporary station deployed on Mayotte island between 2011
and 2014 (RHUM-RUM project, doi:10.15778/RESIF.YV2011;
Fig. 1b). After adding phases from OBSs to 100 events during
an onboard pickathon, we located them with Hypo71 (Lee & Lahr
1972) and the ‘Coffin449’ model with a VP/VSratio of 1.80 ex-
trapolated from Eastern and Central Afar studies (Jacques et al.
1999; Grandin et al. 2011). The modified Wadati diagrams (Chate-
lain 1978) indicated a local (OBS and Mayotte land stations)
VP/VSratio of 1.66 and a regional VP/VSratio of 1.72 (Figs 3a
and b).
We then tested different combinations of velocity model parame-
ters (2 velocity profiles and 3 VP/VSratios) on a more complete data
set of 800 events with OBS phases, using NLL software (Lomax et
al.2014). Contrary to Hypo71, NLL allows the use of depth vari-
ations of the VP/VSratios and different velocity models depending
on the station. Its probabilistic approach (Lomax et al.2014) also
makes the reported ellipsoidal errors more meaningful and easier
to interpret than estimated horizontal and vertical errors given by
Hypo71. We first used only local stations (Mayotte land stations
and OBSs) arrivals to assess the best local 1-D velocity model.
We compared the distributions of maximum ellipsoidal error for
the 2 velocity models and 3 VP/VSratios for the 800-earthquakes
MAYOBS1 data set. The ellipsoidal error major axis ranges be-
tween 2 and 10 km, with most of the events at 4 ±2 km. The
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1286 J.-M. Saurel et al.
012 3456
tsi−tsj (sec)
tsi−tsj (sec)
tpi−tpj (sec)
tpi−tpj (sec)
20 40 60 80 100 120 140 160 1800
Wadati modifed Local data:
Wadati modifed Regional data:
ADofal, Vp/Vs=1.66
Velocity (km/s)Velocity (km/s)
Depth (km)
Depth (km)
Coffin449, Vp/Vs=1.72
Figure 3. Modified Wadati diagram of Pand Swaves arrival times for the first hundred OBSs+land relocated earthquakes. Differences in S-wave arrival times
(tsi, tsj) are plotted against differences in P-wave arrival times (tpi, tpj) for station pairs(i,j). (a) Plot for local stations only (Mayotte land stations and OBSs):
VP/VS=1.66. (b) Plot for local and regional stations: VP/VS=1.72. (c) ADofal gradient velocity model with VSfrom a Mayotte station receiver function and
1.66 VP/VSratio used for Mayotte land stations and OBSs. (d) Coffin449 velocity model with VPvelocity profile from sonobuoy experiment and 1.72 VP/VS
ratio, used for regional stations (Comoros archipelago and Grande Glorieuse).
best results (low average value and limited spreading of the ellip-
soidal errors) were obtained using the ADofal’ velocity model with
VP/VS=1.66, for which 83.5 per cent of the events had maximum
ellipsoidal errors smaller than 5 km. The ‘Coffin449’ model was a
better match for the closest regional station arrivals (Comoros and
Grande Glorieuse), with VP/VS=1.72. The AK135 velocity model
(variable VP/VS, Kennet et al.1995) in combination with ADo-
fal’ and ‘Coffin449’ gave lower residuals on global station arrivals
(Africa, Madagascar and Indian Ocean) than the IASPEI91 model.
Our final velocity model is a hybrid model (see Tables S1, S2 and
S3 for layered detailed values) composed of: the ADofal’ model
with VP/VS=1.66 (Fig. 3c) for OBSs and stations on Mayotte; the
‘Coffin449’ oceanic model with VP/VS=1.72 (Fig. 3d) for regional
stations (between 200 and 400 km from Mayotte) and the AK135
global velocity model for more distant stations. NLL also computes
aVP/VSratio for each event, based on P-andS-arrival times and
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Mayotte seismic crisis: first results from marine and land seismic deployments 1287
independent from earthquake location, using a formula described
in the HypoEllipse manual (Lahr 2012). The NLL estimation, using
the 800 events, supports the mean VP/VSratios previously estimated
for local and regional stations on the first 100 events.
With this new hybrid 1-D velocity model, the earthquake lie be-
tween 25 and 55 km depth (Figs 4a–c). They are in the mantle, below
the Moho discontinuity, which has been estimated either at 17 km
depth under Mayotte island by Dofal et al.(2018)orat15kmdepth
offshore by Jacques et al.(2019). This is very unusual compared to
other volcanoes where deep seismicity is usually sparse and of low
energy (White & McCausland 2019). To confirm our earthquake
locations, we performed further robustness tests of our hybrid 1-D
velocity model to exclude any potential depth bias, for example a
soft-sediments layer impacting S-wave arrivals as has been influ-
ential along a segment of the SW Indian Ridge (Grevemeyer et al.
2019). The earthquake depth distribution remains stable whatever
the velocity models and VP/VSratios we tested (Figs 4a and b). Only
one model, the ‘Coffin449’ oceanic crust-like model, with an unre-
alistic VP/VSratio of 1.8 (with regards to the observed ratios from
arrivals time data), gives significantly shallower depths, between
10and40km(Fig.4b, red dashed line). In this case, the mean
time residual RMS increases from less than 0.2 s for all 5 other
velocity models to 0.3 s. We then compared the depth distribution
of a high-quality subset of the MAYOBS1 catalogue, that is 149
earthquakes with at least 5 P-wave and 5+-wave arrivals picked on
the OBSs data, using different altered configurations and velocity
models. Removing S-arrivals or adding a 0.2 kms–1 S-wave slow
velocity, 200-m-thick sediment layer—consistent with soft uncon-
solidated sediments—does not change significantly the depth range
of events (Fig. 4c). The mean time residual RMS however reaches
0.34 s with the sediment layer, compared to 0.24 s with our model.
We can conclude that the addition of a reasonably dimensioned
superficial unconsolidated sediment layer would thus only have a
small effect on the depth distribution, compared to the use of our
velocity model. Using Parrivals only confirms that there is no S
arrivals related bias in our velocity model. Finally, we used both P
and Sarrivals in uniform half-space velocity models with our 1.66
VP/VSratio (Fig. 4d). For a reasonable half-space P-wave velocity
between 5 and 9 km s–1, all events are located between 20 and 60 km
depth, with an average RMS lower than 1 s and best results obtained
with VP=6kms
–1. Except in the extreme cases, earthquakes were
always located deeper than 15 km (Jacques et al.2019).
The REVOSIMA reported 30 000 events between 25 February 2019
and 10 May 2020, based on manual screening of the continuous
land data. Using NLL software and our new 1-D hybrid velocity
model within SeisComP3, we located more than 5000 of those
events, which have already been detected from the land stations
(Fig. 5;Saurelet al.2021). The mean absolute location accuracy is
around 2 km vertically (Fig. 5a) and 2.5 km horizontally (Fig. 5b).
The formal horizontal and vertical uncertainties are both lower
than 5 km with an azimuthal gap less than 175(Fig. 5c) for 95
per cent of all earthquakes. The location accuracy does not show
much variations with the different OBS network geometries and
the number of OBSs used for location (Fig. 5d). That is to say, the
OBSs network is always sufficient to reduce the azimuthal gap to
less than 175and to increase the number of phase arrivals used for
location to more than 15 phases. Because we processed the data in
descending magnitude order, we always achieved a magnitude of
completeness of 3.0 or lower (Fig. 5e). At present, we now have a
data set of nearly 125 000 manual Pand Sphases between February
2019 and May 2020 (Fig. 5f).
This relocated earthquake data set, while only comprising a part
of the recorded seismicity allows us to identify two distinct seismi-
cally active zones (Fig. 6a).
The Proximal cluster, with 90 per cent of the located earthquakes,
is situated close to the Mayotte island of Petite-Terre. In map view,
it has a circular shape (Fig. 6c) and spans depths ranging 20–50 km
(Fig. 6b). Most of the seismicity is concentrated on the eastern
side of the circle, where the highest magnitudes are located (all
M4–M5+events of the cluster). On the western side of the circle,
closer to Mayotte’s coasts, the events magnitudes are lower, and
the seismicity is more diffuse. At depth, 2 different patches can be
identified (Fig. 6d): one patch is dipping towards Petite-Terre, with
events located between 35 and 45 km depth and a second patch
is more vertical, with events located between 25 and 40 km depth.
The north–south thin (2 km wide) cross-section (Fig. 6e) also shows
2 subvertical lines of earthquakes, suggesting a cylindrical cluster
with a lower earthquake density in the centre (Fig. S3). Based on
the earthquake density, we can estimate an outer diameter of 11 km,
and an inner diameter of 3 km.
The distal cluster is located just a few kilometers to the east of
the Proximal cluster, and contains earthquakes with depths ranging
between 25 and 50 km (Fig. 6g). It is not seismically connected to
the Proximal cluster in our data set. Its seismicity is spread on a
N130E trend extending towards the new volcano edifice (NVE).
Earthquakes along its northwest part are concentrated between 35
and 50 km depth. This area concentrates most of the highest magni-
tudes events located in the distal cluster. The depths of the shallowest
earthquakes progressively decrease up to 25 km (Fig. 6g) as they
approach the NVE. Because our velocity model was built during
the MAYOBS1 cruise, during which we still had intense seismic-
ity with most of the highest magnitude earthquakes of our data set
that occurred in the Proximal cluster (Feuillet et al.2021), only a
few events were located in the Distal cluster. Our velocity model is
then mostly constrained by the Proximal events. This may explain
why the seismicity close to the NVE seems less clustered and more
loosely located.
We did not locate any earthquake with reliable depths shallower
than 20 km during the period of investigation (Fig. 6d). However, be-
cause we only relocated events that have already been automatically
detected and located using only the land stations network, we might
have missed some shallow, local and low magnitude earthquakes.
Thanks to the collaborations among several research institutions,
we, the MAYOBS/REVOSIMA seismology team, has facilitated
the deployment of multiple seismometers, as well as the collection
and interpretation of their data since early 2019. The numerous
pickathons we have held since then have improved our understand-
ing of the seismicity occurring offshore Mayotte. The seismicity
manually-picked and relocated in this study, from February 2019
to May 2020 is in agreement with the analysis of 2018 activity
(Cesca et al.2020; Lemoine et al.2020a;Table1), as seismic-
ity clusters identified in this work seems to have been active since
summer 2018. The Distal cluster correlates with the first cluster of
activity that represents rock fracturing and dyke opening from the
centre of deflation towards the volcano, leading to the creation of
the NVE (Cesca et al.2020; Lemoine et al.2020a; Feuillet et al.
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1288 J.-M. Saurel et al.
Percentage of events
Hypocentral depth (km)
ADofal velocity model
Percentage of events
Hypocentral depth (km)
Coffin449 velocity model
Percentage of events
Hypocentral depth (km)
149 best constrained events
P and S arrivals
P arrivals only
Thick sediment layer
Vp (km/s)
RMS (s)
(d) Half-space constant Vp velocity
Vp (km/s)
Hypocentral depths (km)
Vp (km/s)
Vertical error (km)
Depths robustness tests
Figure 4. Depth robustness test results. (a) Distribution of the hypocentral depths of the OBSs+land catalogue for ADofal S-velocity model and the different
tested VP/VSratios. (b) Distribution of the hypocentral depths of the OBSs+land catalogue for Coffin449 P-velocity model and the different tested VP/VS
ratios. (c) Depth distribution changes when adding an unconsolidated sediment layer below the OBSs (200-m-thick sediment layer with low S-wave velocity
of 0.2 km s–1 below each OBS—dashed red) and when using Parrivals only (dotted–dashed blue). (d) Mean and standard variation of the RMS, depth and
vertical error distributions for various P-wave velocity speeds and this study’s VP/VSratio of 1.66 using a homogeneous half-space velocity model. All tests
were performed using NLL software.
2021). However, a notable difference with our catalogue is the lack
of earthquakes in the first 20 km below the volcano. This could be
explained by a magma path towards the surface now opened and
generating only very small events not detected by the land network
while the path fracturing the crust in 2018 implied strong felt earth-
quakes (Duputel et al.2019). The Proximal cluster correlates with
seismic activity that initiated during July 2018 (Cesca et al.2020;
Lemoine et al.2020a) and became very active at the end of August
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Mayotte seismic crisis: first results from marine and land seismic deployments 1289
Vertical uncertainty
0 102030
Horizontal uncertainty
0 102030
Azimuthal gap
0 102030
Number of phases used
0 102030
Nb phases
0 102030
Percentage of events
2019/04/01 2019/07/01 2019/10/01 2020/01/01 2020/04/01
Nb phases
Cumulated number of phases
Locations accuracies over time
Figure 5. Distributions (left-hand panels) and time evolution (right-hand panels) for the 5174 earthquakes manually picked and relocated with OBSs data
between 25 February 2019 and 10 May 2020, processed during the pickathons. The dashed line on each graph represents the minimum or maximum threshold
reach for all the data set as described in this study. (a) Vertical uncertainties, mostly below 3 km. (b) Horizontal uncertainties, mostly below 4 km. (c) Azimuthal
gaps, mostly below 175. (d) The number of P- and S-wave phases used for each event, mostly above 15. (e) The local magnitudes of all events, with maximum
magnitude of completeness at approximately 2.80. (f) The cumulative number of manual phases picked over time. Light and dark grey bands represent the
different OBSs deployments over time. Italic numbers are the deployment IDs and relates to Fig. 1(d) indication. Bold numbers are the number of OBS
instruments used for each deployment. Four denser deployments of 8 and 16 OBSs (including IFREMER micrOBS instruments) allows to significantly reduce
the azimuthal gap. There are small gaps in the catalogue, which are due to the few days necessary to maintain and redeploy the OBS.
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1290 J.-M. Saurel et al.
Figure 6. Earthquake location distributions. (a) Map of Mayotte earthquakes from 25 February 2019 to 10 May 2020 located using OBS data and (b) their
distribution along a N113E cross-section: the two active seismic clusters are seemingly disconnected. (c) Proximal cluster zoom showing its round shape and
(d) 2-km-wide east/west cross-section and (e) 2-km-wide north/south cross-section suggesting a tube-like shape with subvertical alignments. More seismicity
is visible in the eastern part of the cluster where there are all the M>4.0 earthquakes (orange). The more diffuse seismicity on the west side is limited between
35 and 40 km depth within a vertical alignment dipping towards Mayotte island. (f) Distal cluster zoom showing the alignment of seismicity along a N130E
direction towards the NVE and (g) the N130E cross-section showing seismicity depth variation. Thick dashed black boxes: locations of the Proximal and
Distal cluster zooms; thin blue boxes: earthquake selection for the three cross-sections; green lines: associated topographic profiles; red triangles: location of
the new volcanic edifice.
Tab l e 1 . Comparison of cluster names from this study (Cesca et al. 2020; Lemoine et al. 2020a), and REVOSIMA monthly bulletins.
This study Lemoine et al. (2020a) Cesca et al. (2020) REVOSIMA monthly bulletins, 2019–2020
Distal cluster Cluster 1 and Cluster 2 Dyke volcano-tectonic (VT, blue, cyan, purple) Secondary
Proximal cluster Cluster 3 Sagging volcano-tectonic (VT, red, green) Primary
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Mayotte seismic crisis: first results from marine and land seismic deployments 1291
2018. This correspond to the beginning of the island subsidence
and eastward displacement as recorded in GNSS data, inferred to
be due to the drainage of an at least 30 km deep magma chamber
(Briole 2018; Cesca et al.2020; Lemoine et al.2020a; Feuillet et
al.2021). This proximal cluster appears not connected to the Distal
cluster in our data set and this seems to have been the case since
the beginning of the crisis. The Proximal cluster cylindrical shape
match existing interpretations of a slowly sagging caldeira piston
(Cesca et al.2020; Feuillet et al.2021), but it could also be an an-
cient fault zone re-activated by the massive changes in lithosphere
constraints due to the eruption. Further detailed interpretation of
the Proximal cluster seismic activity requires results from ongoing
studies (lithosphere structure studies, high-resolution relocations,
source mechanisms).
The 2 local and regional velocity models used in this study with
their respective VP/VSratios are consistent with the two main ge-
ological setting interpretations of the area. The ‘Coffin449’ model
upper low velocity layer and rapid increase up to a Moho at 15 km
depth is compatible with an oceanic crust. Its averaged VP/VSratio
can explain an oceanic crust or mixed oceanic and continental crust
at regional scale. The ADofal’ model smooth velocity changes and
the low local VP/VSratios can be associated with an heterogenous
volcanic island context: hot material and presence of gas or fluid-
filled fractured rock. This low VP/VSratio is also consistent with
the Hkstacking from receiver functions performed by Dofal et al.
(2021) and could support their interpretation of a continental crust
with underplating similar to the magmatic continental domain of the
southeastern coast of Madagascar (Rindraharisaona et al.2017).
In terms of monitoring, the regular recovery and deployment of
OBSs and the subsequent and immediate data analysis have been es-
sential to monitor the Mayotte sismo-volcanic crisis. The wide col-
laboration between many scientists, engineers, and students, from
different institutes and universities, during the pickathons continues
to bolster rapid earthquake processing and has also fostered discus-
sions on the evolution of the seismicity with the most up-to-date
data. The magnitudes distribution over time (Fig. 5e) show that the
seismic activity seems to have decreased in 2019, until October
2019 since when the magnitudes distribution is stable. This evolu-
tion can then be compared with the bathymetry surveys indicating
the eruption is still ongoing at lower emission rates (REVOSIMA
2019). Onboard the monitoring cruises, information from this rapid
processing is used to prioritize operations (bathymetry survey) and
focus on the areas of interest and/or crisis. With each pickathon,
we progressively increased our knowledge of the area, which in
turn also feeds the hazard and risk assessment studies that will
help the authorities with the decision-making process. For exam-
ple, the Proximal cluster, while it does not seem directly linked to
the magma emission at the new volcano is of particular concern
since it is much closer to the island and even slightly expands be-
low Mayotte. Tsunami modeling studies (Lemoine et al. 2020b;
Poulain et al. 2021), up to impact mapping, were conducted with
tsunamigenic sources derived from this improved knowledge of the
The resulting high-quality data set of manually picked arrivals is
now used in several detailed on-going studies (lithosphere structure
investigations, seismicity time and space evolution, seismic sources
studies, high-resolution locations) that will better constrain the seis-
micity, active structures and geological setting of the area. Various
non-earthquake signals, such as hydro-acoustic or seismic waves
not clearly associated to earthquakes, have been discovered during
routine data screening and are currently being investigated. While
REVOSIMA has reported more than 30 000 events for the period
covered by the catalogue after daily manual screening of the contin-
uous land stations data, our refined 5000 earthquake locations and
1-D velocity model ascertained by using OBSs data provides a solid
foundation for future studies. Our anticipation is that our improved
earthquake location catalogue, coupled with geodetic modelling,
petrological studies of rock samples and geochemical analysis of
fluids in the water column, will bring understanding of the Mayotte
sismo-volcanic crisis and regional tectonics. On-going work using
machine learning picking algorithms should provide a much more
complete catalogue of the seismicity.
RA network (R´
esif 1995) YTMZ and MILA stations data avail-
able from R´
esif data centre ( ED net-
work MCHI station data is available upon request at EduSismo.
1T (Feuillet, Van der Woerd and RESIF, 2022) land stations are
from the R´
esif-Sismob pool of instruments and data available upon
request at R´
esif data centre (P´
equegnat et al.2021).
The INSU-IPGP pool of OBS is managed and operated by IPGP
and CNRS (https://parc-obs.insu.cnrs.f r/). MicrOBS and LotOBS
are operated by IFREMER/Ressources physiques et Ecosyst`
de fond de Mer/d´
epartement de G´
eosciences Marines/service de
Cartographie et Traitement de Donn´
ees d’Instrumentation. Data
are available upon request at IPGP data centre (http://datacenter.ipg
AM network (Raspberry Shake Community et al.2016) R0CC5,
R1EE2 and RAE55 stations data are acquired by Raspberry Shake
SA company and made available from IRIS data centre and Rasp-
berry Shake SA data centre.
ObsPy (Beyreuther et al.2010) was used to convert NonLinLoc
results into QuakeML files. GMT (Wessel et al.2019)wasusedfor
fig. 1 and fig. 6. Matlab was used for fig. 4 and fig. 5.
NonLinLoc software was used for earthquake locations with OBS
data. Hypo71 software was used for preliminary earthquake loca-
tions of the first MAYOBS1 data set. VirtualBox software was used
on all analyst’s computer to run SeisComP3 graphical user interface
Lcheapo software (
was used to pre-process OBS data (clock correction and conversion
to miniSEED).
Past felt earthquakes statistics on Mayotte from SisFrance
Map bathymetry from Mayobs1 (doi:10.17600/18001217), part
of the Mayobs set of cruises (doi:10.18142/291). Data available
upon request at SISMER.
The Tellus SISMAYOTTE project (broad-band land stations and
first OBSs, MAYOBS1, doi:10.17600/18001217) was funded by
INSU,CNRS and the Ministry of Environment (minist`
sition ´
ecologique et solidaire—MTES). Since June 2019, all activi-
ties on Mayotte are monitored by REVOSIMA (R´
eseau de surveil-
lance volcanologique et sismologique de Mayotte) and funded by
the Minist`
ere de la Transition Ecologique (MTE), the Minist`
de l’Enseignement Sup´
erieur, de la Recherche et de l’Innovation
(MESRI), the Minist`
ere des Outre-Mer (MOM) and the Minist`
de l’Int´
erieur (MI) with the support of the DIRMOM (Direction
erielle aux Risques Majeurs en Outremer).
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1292 J.-M. Saurel et al.
All marine operations are performed as part of the MAYOBS set
of cruises (Feuillet et al.2019).
The MCHI station (Sismo `
a l’Ecole,
was installed by Didier Bertil and Alison Colombain, with funding
from BRGM, DEAL-Mayotte and Rectorat de Mayotte.
The RaspBerry Shake instruments were installed by Maxime B`
de Berc, Marc Grunberg, Christophe Sira and Antoine Schlupp.
The Mayotte stations were installed by Maxime B`
es de Berc,
ome van der Woerd, C´
eleste Broucke, Alison Colombain, H´
Jund and Gr´
egoire Dectot. The Grande Glorieuse station was in-
stalled by Aline Peltier and Philippe Kowalski. They are main-
tained by CNRS/EOST/IPGS, BRGM and OVPF-IPGP through the
OBS are deployed, recovered, maintained and data pre-processed
by Romuald Daniel, Simon Besanc¸on, Wayne Crawford and J´
MicrOBS are deployed, recovered, maintained and data pre-
processed by Pascal Pelleau, Pierre Guyavarch and Micka¨
JMS wrote the first draft of the manuscript and led the editing
work. All co-authors discussed and corrected the manuscript. CA
and WC provided English language check and editing. EJ compiled
geological information and bibliography to establish candidate ve-
locity models, and made figures. CS gave NonLinLoc and Python
support and expertise. All co-authors participated either in station
maintenance and deployment, in routine manual earthquake analy-
sis from land network or in the different pickathons to manually pick
the earthquakes. NF, YF, SJ, ER and IT led the different Mayobs
cruises and helped for data interpretation.
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Tab l e S 1 : ADofal gradient velocity layer model.
Tab l e S 2 : Coffin449 constant velocity layer model.
Tab l e S 3 : ak135 constant velocity layer model.
Figure S1a: MOCE (centre) station showing delay of approximately
0.5 s.
Figure S1b: MONE (northeast) station in the abyssal plain, showing
delay of approximately 1 s.
Figure S1c: MONN (north) station, showing delayof approximately
0.5 s.
Figure S1d: MONO (northwest) station, showing delay of approx-
imately 0.75 s.
Figure S1e: MOSE (southeast) station, showing delay of approxi-
mately 0.5 s.
Figure S1f: MOSO (southwest) station, showing a complex conver-
sion response with possible multiple conversions and a first delay
of 0.5s.
Figure S2: (a) and (b): Map and cross-section of this study catalogue
(OBS locations with hybrid ADofal velocity model). (c) and (d):
Map and cross-section of the same earthquakes from Lemoine et
al.(2020a) catalogue with land-based seismic stations.
Figure S3: map of the log10 density of earthquakes. Density calcu-
lated using QGis heatmap plugin, a 0.01radius and uniform kernel.
The Proximal cluster, which has a donut shape, appears to have a
high density of events in its northeast side.
Please note: Oxford University Press is not responsible for the con-
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authors. Any queries (other than missing material) should be di-
rected to the corresponding author for the paper.
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... Those two clusters are still active as of October 2022 [REVOSIMA, 2022]. We refer to them as the proximal and distal clusters, relative to Mayotte, following Saurel et al. [2022] (Figures 1c and 3). ...
... We used the regional velocity model of this work and the database of P and S pickings [Lemoine et al., 2020a. The results were compared to the well-constrained hypocentral locations of the corresponding events from Saurel et al. [2022] ( Figure S2). Despite the challenging geometry of the onshore network, uncertainties are similar for both catalogs, remaining below 5 km along horizontal and vertical axes for most of the events. ...
... These uncertainties are less than 1 km for the 2211 relative locations (77% of the catalog) (see Section 3.4; Figure 3). The depth of our locations may be compared to those of Saurel et al. [2022] who use a local OBS network. Regarding the hypocentral depths, our lo-cations within the proximal cluster appear to be 3.7 km shallower than theirs, while the depth differences between the locations belonging to the distal cluster are lower than the 2 km vertical uncertainties of Saurel et al. [2022]. ...
From 10 May 2018 to 1 November 2022 (time of writing), an unprecedented seismic activity is observed east of Mayotte Island (France), related to the largest submarine eruption ever recorded with offshore geophysical studies. Using signals from regional and local seismic stations, we build a comprehensive catalog of the local seismicity for the first ten months of the sequence. This catalog includes a total of 2874 events of magnitude (Mlv) ranging from 2.4 to 6.0, with 77% of them relocated using a double difference location procedure. The hypocentral locations over this period are highly dependent on the small seismic network available. Therefore we compare the locations of later events using a similar network and those estimated from a local ocean bottom seismometer (OBS) network installed since March 2019. Based on the time space evolution and characteristics of the seismicity, five distinct phases can be identified, corresponding to the successive activation of two deep seismic swarms, related to the lithospheric-scale magma ascent up to the seafloor, along with progressive deepening of the seismicity interpreted as decompression of a 40 km deep reservoir.
... Many efforts are made to monitor the activity by a reinforced land network of seismic stations and oceanographic cruises (REVOSIMA, 2021), to understand the current volcanic activity as well as past activity. Amongst these methods, OBS stations are regularly installed and their data analyzed (Saurel et al., 2022). Multi-Beam Echo Sounder (MBES) measurements are also performed to study the building of the volcanic structure (Deplus et al., 2019). ...
... The continuous records were manually scanned to identify hydro-acoustic events by the REVOSIMA seismology group during a pickathon (Saurel et al., 2022). These events are characterized by a short and impulsive signal, and several seconds time-delay between stations (Figure 1) due to the slow propagation of the hydro-acoustic waves through water at~1500 m/s. ...
Full-text available
The majority of Earth volcanism takes place in the deep ocean. Deep-sea volcanoes are particularly complicated to study due to their remoteness. Very different methods can be used and their combination can lead to crucial information about submarine volcanoes behavior. In Mayotte, Comoros archipelago, efforts have been made to study and monitor the deep volcanic activity (∼3000 m) currently occurring east of Mayotte through various methods and campaigns on land and at sea. In October 2020, a line of 10 Ocean Bottom Seismometers was deployed during 10 days, leading to a hand-picked catalog of more than a thousand of hydro-acoustic signals, which have been associated with reactions between hot lava and deep cold ocean waters. During the same period, repeated swath bathymetry surveys were performed over an active lava flow field. We compare the time evolution of the hydro-acoustic events locations and bathymetry differences observed between each survey. While bathymetric information gives absolute location of new lava flows, hydro-acoustic events give detailed relative time variations leading to short-term spatial evolution. Bathymetric information thus provides snapshots of the eruptive area evolution at specific times, when hydro-acoustic signals show its continuous evolution. By combining both complementary analyses we are able to clearly define the detailed evolution of the lava flows pattern in the short time period of 10 days. Applied to the data already acquired on Mayotte since 2019, this method could allow us to estimate more precisely the volcano effusion rate and its evolution, giving further insights on the feeding system.
... Since May 2018, the island of Mayotte has registered intense seismic activities related to the birth of a large new submarine volcano 50 km offshore Petite Terre, with a volume estimated to be around 5 km 3 . The epicenters of the seismic swarms are located between 5 and 15 km east of Petite Terre for the proximal swarm ( Figure 1) and from 25 km to 50 km east of Petite Terre for the distal swarm [Lemoine et al., 2020a, Saurel et al., 2022. Perturbations in the water column associated with plumes likely linked to magmatic activity were reported in the new volcano area and in the vicinity of the seismic swarm closest to Petite Terre . ...
... Perturbations in the water column associated with plumes likely linked to magmatic activity were reported in the new volcano area and in the vicinity of the seismic swarm closest to Petite Terre . Although variations in the frequency of earthquakes and their distribution have been observed since the start of the eruption in early July 2018 [Cesca et al., 2020, Lemoine et al., 2020a, Mercury et al., 2020, Saurel et al., 2022, persistence of continuous seismicity could generate earthquakes of magnitudes close to Mw4, or even higher, that would be widely felt by the population. Since May 10, 2018, 2054 earthquakes with magnitudes greater than 3.5 have been recorded, including 36 with recorded magnitudes greater than 5 (REVOSIMA bulletin no. ...
Full-text available
Since May 2018, Mayotte Island has been experiencing seismo-volcanic activities that could trigger submarine landslides and, in turn, tsunamis. To address these hazards, we use the HySEA numerical model to simulate granular flow dynamics and the Boussinesq FUNWAVE-TVD numerical model to simulate wave propagation and subsequent inundations. We investigate 8 landslide scenarios (volumes from $11.25 \times 10^6~\text{m}^3$ to $800 \times 10^6~\text{m}^3$). The scenario posing the greatest threat involves destabilization on the eastern side of Mayotte’s lagoon at a shallow depth and can generate sea-surface deformations of up to 2 m. We show that the barrier reef surrounding Mayotte plays a prominent role in controlling water-wave propagation and in protecting the island. The tsunami travel time to the coast is very short (a few minutes) and the tsunami is not necessarily preceded by a sea withdrawal. Our simulation results provide a key to establishing hazard maps and evacuation plans and improving early-warning systems.
... In addition to using the above-mentioned equipment to measure changes in seabed topography, instruments such as ocean bottom seismometers (OBS) can also be used for monitoring, providing information on the timing and nature of slope failure. Mayotte Island, north of the Mozambique Channel, and the Indian Ocean, OBS, were used to monitor the submarine earthquakes [30]. The attenuation of the light waves and electromagnetic waves is serious, and the propagation distance is very limited. ...
Full-text available
Submarine landslides have attracted widespread attention, with the continuous development of ocean engineering. Due to the recent developments of in-situ investigation and modelling techniques of submarine landslides, significant improvements were achieved in the evolution studies on submarine landslides. The general characteristics of typical submarine landslides in the world are analyzed. Based on this, three stages of submarine landslide disaster evolution are proposed, namely, the submarine slope instability evolution stage, the large deformation landslide movement stage, and the stage of submarine landslide deposition. Given these three stages, the evolution process of submarine landslide disaster is revealed from the perspectives of in-situ investigation techniques, physical simulation, and numerical simulation methods, respectively. For long-term investigation of submarine landslides, an in-situ monitoring system with long-term service and multi-parameter collaborative observation deserves to be developed. The mechanism of submarine landslide evolution and the early warning factors need to be further studied by physical modelling experiments. The whole process of the numerical simulation of submarine landslides, from seabed instability to large deformation sliding to the impact on marine structures, and economizing the computational costs of models by advanced techniques such as parallel processing and GPU-accelerators, are the key development directions in numerical simulation. The current research deficiencies and future development directions in the subject of submarine landslides are proposed to provide a useful reference for the prediction and early warning of submarine landslide disasters.
Full-text available
Geophysical and geological data from the North Mozambique Channel acquired during the 2020–2021 SISMAORE oceanographic cruise reveal a corridor of recent volcanic and tectonic features 200 km wide and 600 km long within and north of Comoros Archipelago. Here we identify and describe two major submarine tectono-volcanic fields: the N’Droundé province oriented N160°E north of Grande-Comore Island, and the Mwezi province oriented N130°E north of Anjouan and Mayotte Islands. The presence of popping basaltic rocks sampled in the Mwezi province suggests post-Pleistocene volcanic activity. The geometry and distribution of recent structures observed on the seafloor are consistent with a current regional dextral transtensional context. Their orientations change progressively from west to east (${\sim }$N160°E, ${\sim }$N130°E, ${\sim }$EW). The volcanism in the western part appears to be influenced by the pre-existing structural fabric of the Mesozoic crust. The 200 km-wide and 600 km-long tectono-volcanic corridor underlines the incipient Somalia–Lwandle dextral lithospheric plate boundary between the East-African Rift System and Madagascar.
Teleseismic receiver-functions and Rayleigh-wave dispersion curves are jointly inverted for quantifying $S$-wave velocity profiles beneath the active volcanic zone off Mayotte. We show that the lithosphere in the east-northeast quadrant is composed of four main layers, interpreted as the volcanic edifice, the crust with underplating, the lithospheric mantle, and the asthenosphere, the latter two presenting a main low-velocity zone. The depths of the old (10–11 km) and new Moho (28–31 km) coincide with the two magma reservoirs evidenced by recent seismological and petrological methods. We propose that the main magma reservoir composed of mush with an increasing amount of liquid extends down to 54 km depth. This magma storage develops from a rheological contrast between the ductile lower and brittle upper lithospheric mantle and accounts for most of the volcanic eruption-related seismicity. Finally, the abnormally small thickness of the lithospheric mantle (33 km) is likely a result of a thermal thinning since the onset of Cenozoic magmatism.
Full-text available
A multichannel seismic reflection profile acquired during the SISMAORE cruise (2021) provides the first in-depth image of the submarine volcanic edifice, named Fani Maore, that formed 50 km east of Mayotte Island (Comoros Archipelago) in 2018–2019. This new edifice sits on a 140 m thick sedimentary layer, which is above a major, volcanic layer up to 1 km thick and extends over 120 km along the profile. This volcanic unit is made of several distinct seismic facies that indicate successive volcanic phases. We interpret this volcanic layer as witnessing the main phase of construction of the Mayotte Island volcanic edifice. A 2.2–2.5 km thick sedimentary unit is present between this volcanic layer and the top of the crust. A complex magmatic feeder system is observed within this unit, composed of saucer-shape sills and seal bypass systems. The deepest tip of this volcanic layer lies below the top-Oligocene seismic horizon, indicating that the volcanism of Mayotte Island likely began around 26.5 Ma, earlier than previously assumed.
Full-text available
The “Fani Maoré” eruption off the coasts of Mayotte has been intensively monitored by applying methods similar to those used for subaerial eruptions. Repeated high-resolution bathymetric surveys and dredging, coupled with petrological analyses of time-constrained samples, allowed tracking the evolution of magma over the whole submarine eruptive sequence. Indeed, after one year of direct ascent (Phase 1), basanitic magma switched to a different pathway that sampled a tephri-phonolitic subcrustal reservoir (Phase 2). Later, the magma pathway shifted again in the crust resulting in a new eruption site located 6 km northwest of the main edifice (Phase 3). The petrological signature of lava flows reveals both an evolution by fractional crystallization and syn-eruptive mixing with a tephri-phonolitic magma.We demonstrate that high-flux eruption of large volumes of basanitic magma from a deep-seated reservoir can interact with shallower reservoirs and remobilize eruptible magma. This has significant hazards implications with respect to the capacity of such large eruptions to reactivate shallow-seated inactive reservoirs from a transcrustal magmatic system that could be located potentially at a distance from the high-flux eruptive site.
Seismology is one of the main sciences used to monitor volcanic activity worldwide. Fast, efficient, and accurate seismicity detectors are crucial to assess the activity level of a volcano in near-real time and to issue timely warnings. Traditional real-time seismic processing software uses phase onset pickers followed by a phase association algorithm to declare an event and estimate its location. The pickers typically do not identify whether the detected phase is a P or S arrival, which can have a negative impact on hypocentral location quality and complicates phase association. We implemented the deep-neural-network-based method PhaseNet to identify in real time P and S seismic waves on data from one- and three-component seismometers. We tuned the Earthworm binder_ew associator module to use the phase identification from PhaseNet to detect and locate the events, which we archive in a SeisComP3 database. We assessed the performance of the algorithm by comparing the results with existing catalogs built to monitor seismic and volcanic activity in Mayotte and the Lesser Antilles region. Our algorithm, which we refer to as PhaseWorm, showed promising results in both contexts and clearly outperformed the previous automatic method implemented in Mayotte. This innovative real-time processing system is now operational for seismicity monitoring in Mayotte and Martinique.
Full-text available
Population information is a fundamental issue for effective disaster risk reduction. As demonstrated by numerous past and present crises, implementing an effective communication strategy is, however, not a trivial matter. This paper draws lessons from the seismo-volcanic “crisis” that began in the French overseas department of Mayotte in May 2018 and is still ongoing today. Mayotte's case study is interesting for several reasons: (i) although the seismo-volcanic phenomenon itself is associated with moderate impacts, it triggered a social crisis that risk managers themselves qualified as “a communication crisis”, (ii) risks are perceived mostly indirectly by the population, which poses specific challenges, in particular to scientists who are placed at the heart of the risk communication process, and (iii) no emergency planning or monitoring had ever been done in the department of Mayotte with respect to volcanic issues before May 2018, which means that the framing of monitoring and risk management, as well as the strategies adopted to share information with the public, has evolved significantly over time. Our first contribution here is to document the gradual organization of the official response. Our second contribution is an attempt to understand what may have led to the reported “communication crisis”. To that end, we collect and analyze the written information delivered by the main actors of monitoring and risk management to the public over the last 3 years. Finally, we compare its volume, timing, and content with what is known of at-risk populations' information needs. Our results outline the importance of ensuring that communication is not overly technical, that it aims to inform rather than reassure, that it focuses on risk and not only on hazard, and that it provides clues to possible risk scenarios. We issue recommendations for improvement of public information about risks, in the future, in Mayotte but also elsewhere in contexts where comparable geo-crises may happen.
Full-text available
Since May 2018, Mayotte Island has been experiencing seismo-volcanic activities that could trigger submarine landslides and, in turn, tsunamis. To address these hazards, we use the HySEA numerical model to simulate granular flow dynamics and the Boussinesq FUNWAVE-TVD numerical model to simulate wave propagation and subsequent inundations. We investigate 8 landslide scenarios (volumes from $11.25 \times 10^6~\text{m}^3$ to $800 \times 10^6~\text{m}^3$). The scenario posing the greatest threat involves destabilization on the eastern side of Mayotte’s lagoon at a shallow depth and can generate sea-surface deformations of up to 2 m. We show that the barrier reef surrounding Mayotte plays a prominent role in controlling water-wave propagation and in protecting the island. The tsunami travel time to the coast is very short (a few minutes) and the tsunami is not necessarily preceded by a sea withdrawal. Our simulation results provide a key to establishing hazard maps and evacuation plans and improving early-warning systems.
Full-text available
Volcanic eruptions shape Earth’s surface and provide a window into deep Earth processes. How the primary asthenospheric melts form, pond and ascend through the lithosphere is, however, still poorly understood. Since 10 May 2018, magmatic activity has occurred offshore eastern Mayotte (North Mozambique channel), associated with large surface displacements, very-low-frequency earthquakes and exceptionally deep earthquake swarms. Here we present geophysical and marine data from the MAYOBS1 cruise, which reveal that by May 2019, this activity formed an 820-m-tall, ~5 km³ volcanic edifice on the seafloor. This is the largest active submarine eruption ever documented. Seismic and deformation data indicate that deep (>55 km depth) magma reservoirs were rapidly drained through dykes that intruded the entire lithosphere and that pre-existing subvertical faults in the mantle were reactivated beneath an ancient caldera structure. We locate the new volcanic edifice at the tip of a 50-km-long ridge composed of many other recent edifices and lava flows. This volcanic ridge is an extensional feature inside a wide transtensional boundary that transfers strain between the East African and Madagascar rifts. We propose that the massive eruption originated from hot asthenosphere at the base of a thick, old, damaged lithosphere. An ~5 km³ volcanic edifice offshore Mayotte formed between May 2018 and May 2019 by rapid magma intrusion through the entire lithosphere, according to an analysis of marine observations and geophysical data.
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On May 10th, 2018, an unprecedented long and intense seismic crisis started offshore, east of Mayotte, the easternmost of the Comoros volcanic islands. The population felt hundreds of events. Over the course of one year, 32 earthquakes with magnitude greater than 5 occurred, including the largest event ever recorded in the Comoros (Mw = 5.9 on May 15th, 2018). Earthquakes are clustered in space and time. Unusual intense long lasting monochromatic very long period events were also registered. From early July 2018, Global Navigation Satellite System stations and Interferometric Synthetic Aperture Radar registered a large drift, testimony of a large offshore deflation. We describe the onset and the evolution of a large magmatic event thanks to the analysis of the seismicity from the initiation of the crisis through its first year, compared to the ground deformation observation (GNSS and InSAR) and modelling. We discriminate and characterise the initial fracturing phase, the phase of magma intrusion and dike propagation from depth to the sub-surface, and the eruptive phase that starts on July 3rd, 2018, around fifty days after the first seismic events. The eruption is not terminated two years after its initiation, with the persistence of an unusual seismicity, whose pattern has been similar since summer 2018, including episodic very low frequency events presenting a harmonic oscillation with a period of ∼16 s. From July 2018, the whole Mayotte Island drifted eastward and downward at a slightly increasing rate until reaching a peak in late 2018. At the apex, the mean deformation rate was 224 mm yr−1 eastward and 186 mm yr−1 downward. During 2019, the deformation smoothly decreased and in January 2020, it was less than 20 per cent of its peak value. A deflation model of a magma reservoir buried in a homogenous half space fits well the data. The modelled reservoir is located 45 ± 5 km east of Mayotte, at a depth of 28 ± 3 km and the inferred magma extraction at the apex was ∼94 m3 s−1. The introduction of a small secondary source located beneath Mayotte Island at the same depth as the main one improves the fit by 20 per cent. While the rate of the main source drops by a factor of 5 during 2019, the rate of the secondary source remains stable. This might be a clue of the occurrence of relaxation at depth that may continue for some time after the end of the eruption. According to our model, the total volume extracted from the deep reservoir was ∼2.65 km3 in January 2020. This is the largest offshore volcanic event ever quantitatively documented. This seismo-volcanic crisis is consistent with the trans-tensional regime along Comoros archipelago.
Full-text available
Volcanological observatories have common needs and often common practical issues for multi-disciplinary data monitoring applications. Real-time access to integrated data, technical metadata, modeling and estimation of uncertainties are fundamental for an efficient interpretation. But in fact, the heterogeneity of instruments or acquisition systems and the inherent problems to produce rapid models using real-time data lead to difficulties that may hinder crisis management. In an attempt to globally address these questions, the French volcanological and seismological observatories have developed a specific operational software system over the past 19 years. Based on GNU/Linux open source tools and a Web interface, the WebObs system mainly offers: (1) a modular database for equipment network management; (2) a dozen of evolving dedicated periodic tasks for each monitoring technique like seismology, deformations and geochemistry that use standard data formats with automated execution of periodic tasks that produce high-quality graphs on preset moving time intervals, data exports, optional event notifications including e-mail alerting, instruments status controls based on their data validity; (3) web-form interfaces for manual data input/editing and export; (4) a user request form to adjust the tasks parameters for a single execution and to produce customized graphs and data exports. This system hence constitutes a web-based tool that performs integrated, centralized and automated real-time volcano monitoring. It has therefore become a strong support for data analysis and exchange between researchers, engineers, and technicians during periods of unrest as well as periods of long-term quiescence. WebObs is also widely open for development of interdisciplinary modeling and enhanced data processing. This allows scientists to test new methods with real-time data flux and to instantaneously share their results in the community.
Full-text available
The dynamics of magma deep in the Earth’s crust are difficult to capture by geophysical monitoring. Since May 2018, a seismically quiet area offshore of Mayotte in the western Indian Ocean has been affected by complex seismic activity, including long-duration, very-long-period signals detected globally. Global Navigation Satellite System stations on Mayotte have also recorded a large surface deflation offshore. Here we analyse regional and global seismic and deformation data to provide a one-year-long detailed picture of a deep, rare magmatic process. We identify about 7,000 volcano-tectonic earthquakes and 407 very-long-period seismic signals. Early earthquakes migrated upward in response to a magmatic dyke propagating from Moho depth to the surface, whereas later events marked the progressive failure of the roof of a magma reservoir, triggering its resonance. An analysis of the very-long-period seismicity and deformation suggests that at least 1.3 km3 of magma drained from a reservoir of 10 to 15 km diameter at 25 to 35 km depth. We demonstrate that such deep offshore magmatic activity can be captured without any on-site monitoring. Recent seismicity near Mayotte in the Indian Ocean is due to dyke propagation from and drainage of a 25–35 km deep magma reservoir, according to an analysis of earthquake and deformation data.
Full-text available
The depth of earthquakes along mid-ocean ridges is restricted by the relatively thin brittle lithosphere that overlies a hot, upwelling mantle. With decreasing spreading rate, earthquakes may occur deeper in the lithosphere, accommodating strain within a thicker brittle layer. New data from the ultraslow-spreading Mid-Cayman Spreading Center (MCSC) in the Caribbean Sea illustrate that earthquakes occur to 10 km depth below seafloor and, hence, occur deeper than along most other slow-spreading ridges. The MCSC spreads at 15 mm/yr full rate, while a similarly well-studied obliquely opening portion of the Southwest Indian Ridge (SWIR) spreads at an even slower rate of ~8 mm/yr if the obliquity of spreading is considered. The SWIR has previously been proposed to have earthquakes occurring as deep as 32 km, but no shallower than 5 km. These characteristics have been attributed to the combined effect of stable deformation of serpentinized mantle and an extremely deep thermal boundary layer. In the context of our MCSC results, we reanalyze the SWIR data and find a maximum depth of seismicity of 17 km, consistent with compilations of spreading-rate dependence derived from slow- and ultraslow-spreading ridges. Together, the new MCSC data and SWIR reanalysis presented here support the hypothesis that depth-seismicity relationships at mid-ocean ridges are a function of their thermal-mechanical structure as reflected in their spreading rate.
Starting in May 2018, a volcano-tectonic crisis occurred in the vicinity of Mayotte, a volcanic island in the Comoros Archipelago in the Mozambique Channel. The origin of the volcanism but also the subsurface architecture and nature of the crust, remain unknown. Here, based on receiver function analyses that provide S-wave velocity profiles, we determine the depth of Mohorovičić discontinuity (Moho) and VP/VS ratios for volcanic islands in the Mozambique Channel. We propose that the crust beneath Mayotte and Juan de Nova islands is of continental nature, while it appears to be of oceanic origin beneath Europa and Grande Glorieuse islands. Our results suggest that Mayotte edifice grew on an isolated continental block abandoned during the Gondwana breakup and the opening of the Mozambique Channel. The continental crust is underlain by a thick (9–10 km) and fast layer, interpreted as magmatic underplating which may result from the 20-Myr-long duration of the volcanism. The new velocity model determined from the seismic station on Mayotte can be used to relocate the seismicity related to the ongoing volcano-tectonic crisis.