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Team 5 Proposal for Tsunami Sensor Development





Our team’s task was to propose the design of a tsunami sensor system for both Micronesia and Peru. Before tackling this problem, we needed an explanation of what exactly caused a tsunami so that we may develop appropriate sensor devices.

Tsunamis are generated by a variety of occurrences, including regional uplifting of the sea floor (earthquakes), underwater landslides, volcanoes, and localized (above water) landslides. The effects of the tsunamis generated by each of these ways vary, with underwater earthquakes and underwater landslides being the most prevalent and most damaging of the tsunami occurrences (Alaska Sea Grant 2005).

The power of a tsunami is highly dependent on two factors: seafloor morphology and tide.  The shape of the ocean floor alters the height of the tsunami by changing the ratio between the wavelength and the wave height of a tsunami.  In general, the ratio of wavelength to wave height decreases as the wave travels into shallower water, causing the tsunami to grow in size [1].

Of the ten major tsunamigenic regions in the Pacific, we are most concerned with the South American and New Guinea-Solomon I regions, which house Peru and Micronesia, respectively.  Both Peru and Micronesia are located in the equatorial humid zone, which has the highest rate of sedimentation in the Pacific.  Increased sedimentation results in higher potential for tsunami generation, causing heightened tsunami risk in both countries [2]

Both Peru and Micronesia also have heightened tsunamigenic potential because of the location of the fault lines around the respective countries.  Micronesia is bordered on three sides by tectonic plate edges, while the South American plate runs closely parallel to the Peruvian coastline. This fact results in increased potential for tsunamis caused by underwater plate activities, as regional uplifting of the seafloor is much more common along fault lines than elsewhere in the ocean [2].

Taking into account both Peru and Micronesia’s heightened tsunami risk as a result of elevated sedimentation rates and location along fault lines, it becomes obvious that we must monitor along ocean floor fault lines and in areas of heightened sedimentation in each case.

The first issue concerning Sensor System development that our team would like to address is the sensor device itself.  Our proposal is to use the sensor used in DART II with optional modifications.  The sensors can be deployed to a depth of 6000 meters and possess battery packs that can last for 4 years on the ocean bottom.  This sensor uses a Bottom Pressure Recorder (BPR) to record unprecedented changes in pressure and temperature that would indicate an event such as a tsunami.

The detection times for the sensor are dependent upon its mode. In standard mode- that is, when a tsunami is not occurring- the sensors report average water height fluctuations and tidal reports. If the sensor is “tripped” into tsunami mode, this information is sent every 15 seconds, and generally takes about 3 minutes to arrive at the warning sensor [3].

The sensor then transmits the information to a surface buoy.  The surface buoys are protected by steel, lead, and foam, and cushioned by rubber.  The buoy’s main responsibility is to relay information from the sensors, and it has two identical systems to do just that in case of a failure of either system[4]. After receiving the information, the buoy relays it in one of two ways:  either the information is then transmitted to a satellite which relays the signal to a command center, or the buoy sends a radio signal directly to the command center.  Both forms of communication have an average delivery time of 3 to 5 minutes, though radio waves are limited to short-range transmissions due to signal strength.

The next concern we would like to address is how the sensors should be deployed into their positions.
Buoy deployment occurs using A-frame structure and crane-equipped boats. The satellite transmitter should be checked before deployment if possible. All buoy components should be laid out on deck, assembled if possible and practical, and secured before boat launch. The total mooring length is 25% more than the ocean depth. The boat will utilize a buoy first, anchor last deployment strategy. The boat moves to a point two-thirds the length of mooring line downstream of the intended dropping site. The buoy is lifted off the deck using a crane and an A-frame and lowered into the water. The boat will steam upstream to a distance of one-third the mooring length upstream from the intended deployment position with no slack on the mooring rope and release the anchor using the A-frame and a crane. The bottom packages of a seismometer and the BPR/tusnameter are designed to be deployed by free-fall through the water once they are lowered to the water’s surface at a short distance from the main mooring. The boat should check satellite and communications to ensure that they are working correctly before leaving to return to shore.

Now that we know how we are able to deploy the sensors, we can compile this
information with other factors, including seafloor morphology and/or risk assessment algorithms to determine the most beneficial location of the sensors along the coasts of Micronesia and Peru. The first factor is the seafloor morphology surrounding the two countries. The position of the buoys is an important factor. The areas around Peru and

Micronesia are very different in that the continental shelves vary in size and degree.  The shelf around Peru can change very rapidly, and as a result of this it might be a little harder to place a buoy near there.  Chile has recently deployed a buoy near Peru and this one will cover the lower part of the country.  Therefore we would only need to deploy one buoy in the area and the proposed position is 8 degrees south by 85 degrees west (See: Monitoring Seafloor Morphology Changes).  This is a prime spot because it overlooks the rest of the country and also watches out for a tsunami coming in from the ocean.  It is at an area where it gives enough time for warning from a potential tsunami.

In the area of Micronesia we are proposing three buoys.  The buoys will be in locations surrounding the northwestern to the south part of the islands.  The positions of the buoys in the vicinity of Micronesia would be about 1 degree north and 161 degrees east, 11 degrees north and 152 degrees east, and 4 degrees north and 141 degrees east.  These locations are prime because they surround the island in the areas that are most prone to have earthquakes.

The locations were decided upon data that was collected from maps and professors.  The maps were both topographic and tectonic.  We also used historical evidence from these to predict where would be the most area prone to tsunamis based on the locations and magnitudes of earthquakes.

The second factor is a much more theoretical approach to determining sensor location, as it is based upon the development of risk assessment algorithms that do not currently exist for the areas in question. In one case we have studied, concerning Japanese islands, algorithms were developed that were able to determine the arrival time of tsunamis from a given point (generally a sensor) and the “ratio of excess,” providing us with information on how likely it is that a wave will exceed 5 meters when it approaches a given area of the shore in question. Obviously, this model fits the Japanese shoreline as opposed to either of the areas we are concerned with, but the variables influencing the equation- examples being time, gravity accelerator, water level lift from still water level, water depth, friction coefficient of the ocean bottom, flux in the x and y direction, and the vertical amount of seabed displacement- can be applied to Micronesia and Peru to come up with a similar working model for sensor deployment [5].







[1] Smith, D. (2005). Tsunami: A Research Perspective. Geology Today, 21 (2),

[2] Gusiakov, V. K. (2005). Tsunami Generation Potential of Different
Tsunamigenic Regions in the Pacific. Marine Geology, 215 (1-2), 3-9. 


[4] Meinig, C., S.E. Stalin, A.I. Nakamura, H.B. Milburn (2005). Real-Time Deep-Ocean Tsunami Measuring, Monitoring, and Reporting System: The NOAA DART II Description and Disclosure. www.pmel.noaa.gov/tsunami-hazard/ [5]  Sato, Hiroaki., Murakami, Hitoshi., Kozuki, Yasunori., Yamamoto, Naoaki. (2003).
Study On Simplified Method of Tsunami Risk Assessment.  Natural Hazards, 29,



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