The SouthEast Asia SEA-level program (SEA2) will integrate instrumental, historical, and geological sea-level datasets in Southeast Asia with sophisticated modeling capabilities to improve the accuracy of projections of sea-level rise and extreme...
Geodesy Group - Emma Hill
Geodesy is a highly interdisciplinary science with significant application to understanding risks to society from natural hazards and climate change. It is commonly defined as the study of the Earth’s shape, size, gravity field, and how these parameters change over time.
Sources of geodetic information include tide gauges for measuring relative sea-level height, continuously operating Global Positioning System (GPS) receivers and Interferometric Synthetic Aperture Radar (InSAR) for measuring displacements of the Earth’s crust, and the GRACE satellite mission, which takes monthly snapshots of the Earth’s gravity field. These data sets together enable measurement of processes in the Earth system that include, amongst others, crustal deformation from tectonics and earthquakes, changes in sea level, volcanic deformation, melting glaciers, and changes in continental water storage.
With the advent of space-borne geodetic technologies, the quantity and spatial resolution of geodetic data have increased dramatically, and they continue to do so. Data precision has also increased dramatically, so we now need to understand not only the primary process affecting a measurement, but also many secondary processes that affect the measurements on a fine scale. For example, the gravity field at a single location can be affected by changes in nearby glaciers, hydrology, sea level, and tectonics, as well as measuring the ghosts of past ice sheets in the form of glacial isostatic adjustment.
A focus of much of our research, therefore, is to combine multiple different geodetic data sets together to help separate the different signals in the data, and to provide better-constrained models for processes such as earthquakes and sea-level change. To place emphasis on the association of uncertainties with our results, we are investigating various techniques for Bayesian combination of data and models.
One of our primary data sets is the Sumatra GPS Array (SuGAr). This is a 48-station continuous GPS network maintained by EOS, designed to monitor tectonic deformation and earthquakes along the Sumatra subduction zone. This network has recorded a huge number of large earthquakes over the last decade, and much of our recent work has focused on separating the effects of these different earthquakes in the time series, and studying their rupture histories. We are currently working on code to analyze the evolution of fault slip during the earthquakes, through inversion of high-rate (1-second sampling) GPS data.
The Myanmar-India-Bangladesh-Bhutan GPS network began operation in 2012 and now comprises 33 continuous stations across four countries, plus 113 survey stations we have added in the past several years.