SPECTRAL ANALYSIS WITH PIECEWISE REGRESSION APPROACH (SAPRA) OF GRAVITY DATA FOR LITHOSPHERIC STRUCTURE IMAGING: THE LAKE TURKANA RIFT BASIN OF THE EAST AFRICAN RIFT SYSTEM

This work introduces a new quantitative approach involving piecewise regression for the identification of unique data points defining the breaks in slope of linear segments of the two-dimensional (2D) radially-averaged spectrum curves (henceforth spectrum curves) of gravity data. This new approach is referred to as the spectral analysis with piecewise regression approach (SAPRA). Linear segments of the spectrum curves of gravity data represents deeper discontinuities in the Earth interior resulting from density contrast interfaces such as the Moho and the crystalline basement. Previous approaches used for the identification of data points representing breaks in slope of linear segments of the spectrum curve have been subjective and this results in considerable inconsistency in the calculation of the depth to the Moho and crystalline basement from the gravity data. SAPRA is performed as a two-step process that is first applied to identify and isolate the data points defining the linear segment of the spectrum curves that corresponds to the Moho and second to identify and isolate those define the linear segment of the spectrum curve that corresponds to the crystalline basement. To test the effectiveness of SAPRA, this work applied this approach to the World Gravity Model 2012 (WGM 2012) to calculate the depth to the Moho and crystalline basement beneath the Lake Turkana rift basin which represents a segment of the Eastern Branch of the East African Rift System (EARS).Subsequently, results of the Moho and crystalline basement depth from the SAPRA was compared with results from 2D forward modeling of the Bouguer gravity anomalies of the WGM 2012 and results from controlled-source seismic imaging. This work found possible better imaging of the details of the topography of the Moho and crystalline basement beneath the Lake Turkana rift basin using the SAPRA. The SAPRA can be readily applied to the gravity data covering other regions in the World for imaging the Moho, given the global coverage of gravity data such as the WGM 2012.