A substantial and rapid expansion beginning in the late 1990s of Siling Co, the largest endorheic lake on the central Tibetan Plateau (TP), has caused a measurable deflection in the region adjacent to the lake. Current broad-scale measuring of this flexural response is mainly derived from DInSAR processing techniques. The underlying lithospheric response to large lake loads in this region is not well understood, with the focus on either a viscoelastic or an elastic response. This thesis intends to use a more efficient LiDAR remote sensing technique to measure the deflection in the vicinity of Siling Co, and to investigate the mechanisms of the observed lithospheric response. A lake-adjacent deflection rate and Siling Co water load variations are calculated utilizing the Geoscience Laser Altimeter System (GLAS) onboard NASA’s Ice, Cloud and land Elevation Satellite (ICESat) and the joint NASA/USGS Landsat series of earth observing satellites. A downward deflection rate of ~5.6 mm/yr for the first 4 km of lake-adjacent land is determined from the GLAS instrument and this response is compared to the flexural outputs from a spherically symmetric, non-rotating, elastic, and isotropic (SNREI) Earth model in order to better understand the underlying mechanisms of the lithospheric response to the extreme change in Siling Co loads. The modeled elastic response is ~6.7 times lower than the GLAS derived flexure, thereby providing further evidence that a completely elastic lithospheric response cannot explain the deflection in this region, and that a viscoelastic response is more likely. The relationship between the modeled elastic response and the GLAS derived flexure is applied to a long-term lake load change dataset to create the longest-running flexural response curve as caused by the last ~40 years of Siling Co load variations.

The mechanisms, magnitudes, and the effects of large-scale lacustrine changes can vary drastically over both time and space. These changes can alter the surrounding lithosphere, the interconnected natural systems, as well as the ever-growing connections to human water use. The timing of these changes can occur over several decades, or in some extreme cases these lacustrine changes can occur intra-annually (e.g. seasonal reservoir fluxes) or inter-annually (e.g. initial reservoir impoundments). The first portion of this dissertation work examines the magnitudes and effects of these changes at the Grand Ethiopian Renaissance Dam (GERD) in Ethiopia. Here, the mechanisms behind these changes are related to direct anthropogenic impacts (e.g. dam building and riverine impoundment). To this end, I examine the elastic deformation (Chapter 1) and subsurficial stress responses (Chapter 2) to several different impoundment and seasonal operational cycles at the GERD. Large hydrologic loads can impart notable stress on the surrounding crust and upper mantle, and, as such, I examine these stresses at the GERD and discuss the main drivers of potential reservoir triggered seismic events. The spatial patterns and amplitudes of the stress tensors and hydrologic-induced deformation are closely linked to both the size and timing of reservoir fluxes, and an improved understanding of the magnitude and extent of the stresses and deformation provides useful information to water managers in order to better understand the effects from many different impoundment and operational strategies. Lastly, this work examines the magnitude of water level changes for all waterbodies >1 km2 within the contiguous United States (CONUS) as derived from spaceborne lidar altimeter data products (Chapter 3). Here, the mechanisms behind these changes are related to both direct and indirect anthropogenic impacts and are quite diverse across the landscape. A more thorough understanding of the spatiotemporal differences in the magnitude of these changes provides the foundation needed to appropriately assess the varying mechanisms behind, and the effects of these changes. There is a notable spatial data gap of in situ water level measurements within the CONUS. To that end, remote sensing analysis provides a means to fill in those data gaps in order to glean a better understanding of the spatiotemporal water level changes across the entirety of the CONUS.