Citation:
Gonzalez, L., S. Koshimura (2019), Evaluation of possible locations of bottom pressurerecorder for the Colombian north Pacific coast, using tsunami travel times and tsunami simulations,
Synopsis of IISEE-GRIPS master report.

EVALUATION OF POSSIBLE LOCATIONS OF
BOTTOM PRESSURE RECORDER FOR THE
COLOMBIAN NORTH PACIFIC COAST, USINGTSUNAMI TRAVEL TIMES AND TSUNAMISIMULATIONS
Laura Gonzalez1,21Supervisor:

Shunichi KOSHIMURA32

ABSTRACTWe evaluated the possible locations of Bottom Pressure Recorders (BPR), which provide proper time toissue tsunami warning to the populated areas in the north pacific coast of Colombia. We made apreliminary analysis assuming an arrangement parallel to the subduction trench and then an
improvement considering the technical recommendations given by the Pacific Marine Environmental
Laboratory regarding the deployment of BPR. With the final arrangement of BPRs, we conducted
Tsunami Travel Times (TTT) calculations for far-field events, and tsunami propagation simulation with
TUNAMI code. Furthermore, we evaluated the effectiveness of BPR in case of local earthquakes. We
classified the possible locations into three groups according to the lead time between tsunami detection
on the BPR and the arrival to the first virtual observation point near the most populated areas, as: (1)best, (2) good and (3) not good. We found the best location for the selected arrangement of BPR in
latitude 4.909° N, longitude 80.06° W, at the depth of 3,134 meters.
Keywords: Tsunami, Bottom Pressure Recorder, Tsunami Buoy (DART), TTT, TUNAMI.

1. INTRODUCTION
The detection of tsunami in the deep ocean has become very important for tsunami warning centers, as
they need to provide early information of the generation of a tsunami. These events may be caused byearthquakes or landslides, and can be detected through a Bottom Pressure Recorder (BPR) anchored on
the seafloor, which monitors and reports water column height. The data collected by the BPR istransmitted to the surface buoy through an acoustic modem, and then the surface unit sends thisinformation via satellite communication. After this process, the measurements are transmitted to thetsunami warning centers and to the National Data Buoy Center (NDBC) every three to six hours in
regular mode; when the BPR detects a change of 3 cm in the column of water, the event mode is activated,
and the information is sent to the surface unit every minute. DIMAR, as National Tsunami Warning
Center (NTWC) for Colombia is responsible to provide technical information about the possible impactsof tsunamis for the Colombian coasts and has implemented a network that consists of tide gauges and a
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General Maritime Directorate (DIMAR), Colombia.
IISEE-GRIPS master course student
3
Professor, International Research Institute of Disaster Science (IRIDeS), Tohoku Univ.
2

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tsunami buoy, which is capable of detecting the existence of a tsunami that is approaching the Colombian
Pacific coast.
In 2014, the tsunami buoy was installed in the Pacific Ocean of Colombia, considering theneed to give an early warning for the areas in the south of the Pacific coast of Colombia. This study aims
to evaluate some possible locations to install a BPR to improve the early warning system for the northregions of the Colombian Pacific coast in case of far-field tsunami events.

2. DATAIn this study, for tsunami simulations we used GEBCO bathymetry grid data with 1 arc-minuteresolution for near-field and also for Nicaragua and Peru scenarios. The grid dimension is 1020 x 1200,
and the temporal grid size is 3 s. For far field simulations (Kuril and Tonga) it was resampled to 10 arcminute. The grid dimension is 630 x 1140, and the temporal grid size is 3 s.
For selecting suitable locations of BPRs, we used the nautical chart for the Colombian
Pacific Ocean Panama Bay to Cabo San Francisco (Ecuador), which was compiled by the Caribbean
Oceanographic and Hydrographic Research Center (CIOH–DIMAR). The scale of the chart is
1:1,200,000 at latitude 04° 47’ 30’’N. We also used the maritime border limits provided by DIMAR.

3. ANALYSIS STAGES
3.1. Preliminary analysis
We assumed a BPR arrangement parallel to the subduction trench to conduct the inverse Tsunami Travel
Times (TTT) calculation from populated areas as tsunami source points to the 50 BPRs and Virtual
Observation Points (VOP) and evaluate whether this kind of arrangement is effective for the northPacific coast.
3.2. Improvement of BPR arrangement
We made an improvement on the BPRs arrangement based on considerations made by the Pacific
Marine Environmental Laboratory of the National Oceanic and Atmospheric Administration(PMEL-NOAA), to conduct TTT calculations and tsunami simulations considering far-field scenarios
to find the locations that gives a proper lead time from the tsunami detection until the arrival to the VOP
near the most populated areas in the north Pacific coast of Colombia. Furthermore, we evaluated theeffectiveness of the improved BPR arrangement for near-field scenarios.
3.3. TTT calculations
We used TTT software (Wessel, 2009) to calculate tsunami velocity based on an input bathymetry gridand Huygens construction to simulate the propagation of the wavefront from the epicenter to all nodesof the grid as Eq. (1).
𝑣 (𝑥, 𝑦) = √𝑔(𝑦)𝑑(𝑥, 𝑦)(1)

where v is propagation speed, g is gravitational acceleration and d is water depths. We selected sevenepicenters of far-field events as source points to conduct TTT calculations: Kuril, Aleutians, Papua New
Guinea, Tonga, Peru, Nicaragua and Japan.

23.4. Tsunami propagation simulations
For the simulations, we used TUNAMI code modified by Yanagisawa (2019). For the far-field
simulations, we used the linear long wave equations in spherical coordinate system as Eqs. (2), (3) and(4):
1  M++( N cos  ) = 0t R cos    


M
gh 
+
= fN
t R cos  (3),

N gh += − fM
t
R 

(2)

(4)

where λ and θ are latitude and longitude respectively, ƞ is water level, M and N are the discharge fluxes
in the λ and θ directions, R is the radius of the earth, t is time, g is gravitational acceleration, h is water
depth, and ƒ is Coriolis force.
For near-field tsunami propagation simulations, nonlinear long wave equations with
Manning bottom friction term were used as Eqs. (5), (6) and (7):
1  M ++( N cos  ) = 0t R cos    


(5)

M
gD 
1
 M2 1
 
MN  gn 2
2
2

 +
+
+
 cos
+ 7 3 M M + N = 0
t R cos  R cos   D  R cos  
D  D

(6)

N
gD 
1
 
N2 
1
  MN  gn 2
 cos +++N M 2 + N2 =0+t R cos  R cos  
D  R cos   D  D 7 3(7)where n is Manning coefficient, D is the total depth (= ƞ + h).
Table 1. Parameters of source models for the far-field and near-field tsunami simulation.

We used the parameters of the finite fault models described in Table 1 to calculate theinitial sea floor deformation in elastic half-space (Okada, 1985). The horizontal displacement effect on
the sea surface elevation was also included (Tanioka and Satake, 1996).

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For Nicaragua, Tonga and Kuril scenarios we used the scaling law of Papazachos et al.
(2004). The parameters of the Peru Earthquake were taken from the source model of Jimenez et al.
(2013). Near-field scenarios were determined by considering maximum magnitude calculated according
to the length of each segment of the Colombian subduction zone (INGEOMINAS, 2005). The scenario
for the south segment was taken from one of the model parameters for the 1906 Esmeraldas earthquake
rupture (Mayorga and Sánchez, 2016).

4. RESULTS AND DISCUSSION
4.1. Preliminary analysis
We selected the arrangement of BPR which provided more than 40 minutes with inverse TTT
calculations from the populated areas in the north Pacific coast of Colombia as point sources, to the
BPRs. The resulting points were the BPRs 31 to 50. Then, we considered some regional scenarios as
point sources such as the 2007 Peru earthquake and the 1992 Nicaragua earthquake. From thesesimulations we evaluated the TTT from these point sources to the VOPs, concluding that these BPRs
were effective from the scenarios from the south of Colombia, such as Peru case, but the results fromthe Nicaragua earthquake showed the same TTT for the first detection in a BPR with the Jurado VOP.
4.2. Improvement of BPR arrangement
We considered the technical recommendations made by PMEL-NOAA (Tang et al., 2008): (1) Seismic
noise: When the BPR is located too near to the seismic events that generate tsunamis, seismic noise will
be recorded by the BPR as a high-frequency signal and this fluctuation is not related to the tsunami. (2)Water depths and strong currents: The deployment must be done in a zone between 1500 and 6000
meters for the sensor to be able to communicate with the surface unit. (3) Bottom roughness: Theremight be shadowing in the transmission process due to a presence of a seamount that interrupts theacoustic communication between the BPR with the transducer in the surface buoy. (4) Border limits
between the countries.
Figure 1 shows the final
arrangement of BPRs assumed, VOPs andTsunami Buoy. The parameters of timefrom the detection in the BPR to the arrival
time of the tsunami to the coastal areas wereconsidered from the procedures of theregional tsunami warning centers: INOCAR
in Ecuador and SHOA in Chile. They havedetermined to have an appropriate response
locating their BPRs to a distance from theearthquake generation zone, which in
Ecuador case is around 130 kilometers fromthe coast and in Chile case, from 140 toalmost 320 kilometers. They provide theirtsunami warning center at least 15- minutes
lead time from the detection to the arrival of
the tsunami to the coasts.
Figure 1. Arrangement of possible locations for BPRs,
VOPs and Tsunami Buoy are also shown. The blueline represents the border limits with Panama. The dots
represent the BPRs 1 to 28 from north to south. Basemap source: NOAA by using GEBCO.

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4.3. TTT calculation
We obtained the TTT from every source
point described in Section 3.3 to thepossible locations of BPR as shown in
Figure 2 and Table 2. In six from theseven scenarios we obtained the firsttsunami arrival to BPR 28; in the Peru
source, the first detection of the tsunami
was made by BPR 26, with just oneminute difference of BPR 28. Also, we
compared the TTTs for all the far-fieldsources with the arrival time to thecurrent BPR installed near Tumaco
Figure 2. Example of calculations with TTT for Kuril(Tsunami Buoy in Table 2).
We found that for the far- epicenter.
field cases, the selected location of thisTable 2. Example of results from TTT calculation forstudy will also improve the detection
Kuril epicenter.
time in comparison with the current BPR
installed, with 20 minutes at least, except
the case of the Peru, where the detection
was first at the tsunami buoy. With theseobservations, we were able to determinethat the location of BPR 28 isappropriate, considering that at least 15
minutes are given before the arrival to
the north Pacific coasts of Colombia.
The BPR 28 also satisfy the considerations analyzed, because it is not so close to the nearest
seismic source, where a BPR can avoid seismic noise. Also, the depths were verified from the nauticalchart confirming that the depth of 3,134 meters in the location of the BPR was in the needed range, forthe consideration of the communication settings.
4.4. Tsunami propagation simulation
After TTT calculations, we confirmed the obtained results with tsunami simulations with a more realistic
tsunami source from the source models in Table 1. In each case we conducted the tsunami propagation
simulation as shown in Figure 3 and evaluated tsunami waveforms at the first BPR that register thetsunami, the first VOP near the populated areas and the tsunami buoy as shown in Figure 4. These
tsunami simulations confirm the effectiveness of the location of the BPRs in the final arrangement andwe were able to evaluate the estimated detection time for a far-field tsunami and also determine that thelead time between the detection on BPR 28 and the arrival to the VOPs was more than fifteen minutes
for all the far-field cases we simulated.
4.5. Classification to define position
According to the TTT results from the far-field sources we defined three groups of classification: (1)best (green in Figure 1), for these that will have more than 15 minutes of lead time between the firstdetection of the BPR and the arrival to the VOP near the populated areas in the north pacific coast ofColombia; (2) good (purple in Figure 1), for 15 minutes; and (3) not good (beige in Figure 1) for lessthan 15 minutes.

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Figure 3. Example of tsunami propagationof the Nicaragua scenario.

Figure 4. Example of waveforms in Nicaragua
scenario. The blue line corresponds to BPR 28. The
red and green lines are from Jurado VOP and tsunami
buoy, respectively.

5. CONCLUSIONSFor the selected far-field earthquakes, we conducted TTT calculations from point sources and tsunami
propagation simulations with a more realistic tsunami source. The results were consistent to conclude
that BPR 28 at latitude 4.909° N, longitude 80.06° W, at the depth of 3,134 meters, is the location which
provided the suitable response for north area of the Pacific coast of Colombia in most of the cases. We
also realized that the location of BPR 28 would provide more time of warning to the central and south
areas of the Pacific coast of Colombia.
From the simulations of near-field scenarios, we concluded that for the possible events that
occur in the north or central segment, there is no point from the selected locations for BPR in this study,
which could give an early detection compared to the actual tsunami arrival time for the populations.
Finally, we defined a classification of the possible locations of BPRs for the north Pacificcoast of Colombia as: “best”, “good” and “not good”, according to the resulting times of tsunami arrival
to the VOP near the populated areas in the north coast after the detection in the first station within theBPRs.
ACKNOWLEDGEMENTS
This research was conducted during the individual study period of the training course “Seismology,
Earthquake Engineering and Tsunami Disaster Mitigation” by the Building Research Institute, JICA,
and GRIPS.I want to express my gratitude to my supervisor Dr. Shunichi Koshimura, Dr. Erick Mas,
and my advisor Dr. Yushiro Fujii for their valuable support and suggestion during my study.
REFERENCES
INGEOMINAS, 2005, Instituto Colombiano de Geologia y Mineria, 49 pp.
Jimenez, C., et al., 2013, Journal of Disaster Research, 8(2), 266–273.
Mayorga, E. F., and Sánchez, J. J., 2016, Journal of South American Earth Sciences.
Okada, Y., 1985, Bulletin of the Seismological Society of America, Vol. 75, No. 4, pp. 1135-1154.
Tanioka, Y., and Satake, K., 1996, Geophysical Research Letters, 23(8), 861–864.
Papazachos, et al., 2004, Bulletin of the Geological Society of Greece, XXXVI(April), 1482–1489.
Tang, L., et al., 2008, PMEL-NOAA.
Wessel, P., 2009, Pure and Applied Geophysics, 166(1–2), 301–324.
Yanagisawa, H., 2019, IISEE Lecture note 2018-2019, IISEE/BRI.

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