Ellen Knappe

Year of Award


Document Type

Dissertation - Campus Access Only

Degree Type

Doctor of Philosophy (PhD)

Degree Name


Other Degree Name/Area of Focus


Department or School/College

Department of Geosciences

Committee Chair

Rebecca Bendick

Commitee Members

Cynthia Ebinger, W. Payton Gardner, Marco Maneta, Hilary Martens


continental deformation, geodesy, GPS, hydrologic loading, tectonics


University of Montana


The surface of the Earth deforms due to a variety of forces. Global Positioning System (GPS) provides observational constraints on surface deformation. This dissertation utilizes geodetic time series to quantify deformation due to tectonics and hydrologic loading.

In East Africa, tensional stresses cause continental rifting, which stretch and thin the lithosphere. The East African Rift System is a series of rift basins that are accommodating the divergence through varying amounts of magmatism, extension and faulting. The Turkana Depression lacks the distinctive rift structures and topography that is present in majority of the EARS. The depression additionally has a past history of rifting that has thinned the crust and left a set of pre-existing structures. Using GPS time series, I quantify extension rates in the Turkana Depression and find localized extension. By quantifying deformation in the Turkana Depression and comparing to surrounding sectors of the rift, we find that the style of deformation (localized or distributed) in the EARS is dictated by gradients in body forces.

In the Northern Rockies, seasonal shifts in water storage produce surface mass loads that deform the surface of the Earth. Quantifying water load in regions of high topographic relief, such as the Northern Rockies, is difficult and existing observational constraints are not ideal to estimate water storage in these small mountainous watersheds. However, geodetic times series record the elastic response of the surface mass loads, recording linear combination of regional and local loads. I use geodetic time series to measure the surface response and separate the regional and local signals from the time series. This research elucidates the use of GPS as an independent measure of watershed-scale hydrologic loading.

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