Toward better accuracy for measurement of ocean bottom crustal deformation
Abstract
We are developing a new geodetic method of monitoring crustal deformation under the ocean. This method is based on techniques of kinematic GPS and acoustic ranging. We deploy a trio of transponders on ocean floor (a seafloor benchmark unit) within distance comparable with the depth. An ultrasonic signal is generated from a surface vessel drifting over the benchmark unit, which is received and replied by the benchmark unit. In this system, each measurement takes about ten hours and both sound speed structure and the benchmark unit positions were determined simultaneously for the each measurement using a tomographic technique. This tomographic technique was adopted on assumption that the sound speed structure is horizontally layered and changes only in time, not in space. The measurements have been conducted at four sites in two regions near the Nankai trough, where the Philippine Sea plate subducts into the Pacific plate. The two regions are Suruga Bay and the Kumano Basin. We repeatedly carried out the measurements over the two regions. After almost five years repeating measurements, for KMS site in the Kumano Basin and SNE site in Suruga bay, the horizontal precision of the benchmark location was 5 cm and its vertical precision was 10 cm through the repetitive measurements. However, this precision is not enough to research the crustal deformation in detail within the interval of our measurement (from one to a few months) because 5 cm is comparable to annual rate of the plate convergence around the Nankai trough. One of our main subjects is to develop the precision of the benchmark location. In this study, we revised the solution model in OCDASAN to achieve higher accuracy of the location based on the following concepts; 1. The configuration of the benchmarks consisting of one benchmark unit does not change. The distortion of the triangle is negligible compared with the movement of the weighted center of them. 2. Sound speed structure takes both temporal and spatial changes. We assumed a constant gradient in horizontal direction for each measurement as spatial variation. In the previous model, we analyzed the data set obtained by each measurement separately. In the each analysis, we have estimated 3 component of the location for 3 benchmarks; 9 unknown values for each data set. Under the new concept, we successively decreased number of the unknowns by solving whole the data sets for the repetitive measurements in one time. We estimated configuration of the benchmarks which must be stable through all the measurement, temporal variation of its weighted center. In this procedure, the unknown values related to the benchmark location decreased from 9 to 3 for the each measurement. As a preliminary result of this procedure, the differences of the locations between adjacent couple of measurements were within about 3 cm. We improved robustness and accuracy of the analysis by decreasing unknown parameters for each measurement as well as increasing fitness of the model to actual sound structure.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2009
- Bibcode:
- 2009AGUFM.S51D..08I
- Keywords:
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- 1222 GEODESY AND GRAVITY / Ocean monitoring with geodetic techniques;
- 4259 OCEANOGRAPHY: GENERAL / Ocean acoustics;
- 7220 SEISMOLOGY / Oceanic crust