Greg Tucker

Some recent research themes in my group include:

• Developing flexible software libraries and code packages to facilitate numerical modeling of earth-surface processes (Tucker et al., 2022; Barnhart et al., 2018, 2019a, b, 2020a; Bandaragoda et al., 2019; Hutton et al., 2020; Litwin et al., 2020; Hobley et al., 2017; Shobe et al., 2017)
• Influence of landsliding on the evolution of terrain (Campforts et al., 2022)
• The role of gravel transport and abrasion in river network evolution (Gabel et al., in review)
• Morphology and evolution of steep hillslopes (Tucker et al., 2020; Tucker et al., 2011; Tucker et al., 2018; Tucker et al., 2016; Shmilovitz et al., 2023)
• Using natural experiments to test and compare landscape evolution models (Barnhart et al., 2020b,c,d)
• Long-term forecasting of erosional release of hazardous waste (Barnhart et al., 2020e)
• Role of climate, hydrology, and lithology in landscape evolution (Gray et al., 2020; Rossi et al., 2020; Shobe et al., 2018, 2020; Glade et al., 2019)

Research Example: Modeling Long-Term Erosion in the Context of Hazardous Waste

When hazardous waste material sits in a location that may be susceptible to erosion, how do we estimate the likelihood of future contaminant release? This is a question that my group recently grappled with, in the context of a former nuclear fuel reprocessing plant in western New York State. During its operational life in the late 1960s and early 1970s, the plant generated a variety of radioactive waste products; much of this material remains entombed at the site today. The plant lies atop a plateau underlain by soft late Pleistocene glacial sediments. Active erosional processes, including landsliding and gully propagation, are gradually gnawing at the plateau edges. In a project spearheaded by CIRES researcher and NSF Postdoctoral Fellow Katy Barnhart (now at USGS Landslide Hazards Group), our team undertook a computational modeling study of past and future long-term erosion at the site. We took advantage of a unique aspect of the site’s recent geologic history: the last recession of glacial ice about 13,000 years ago left behind a relatively smooth surface that has subsequently been deeply incised by stream valleys. By reconstructing this smooth post-glacial surface and running a suite of erosion models forward in time from the late Pleistocene to the present day, we were able to test and calibrate a collection of alternative models. The models were crafted using Landlab Toolkit, a Python-language modeling framework developed with NSF support as an element of the CSDMS Workbench. In addition to providing a basis for making projections of future erosion, the results shed new light on the key principles of long-term landscape evolution in this type of post-glacial environment, and yielded a new method for testing quantitative models.