Our research tends to focus on digital soil mapping, with special consideration of issues with spatial prediction and soil geomorphology. However, new directions are influenced by the lab team members’ individual interests and current grant funding. Please review our recent research products for examples of our recent work.
STILL OPEN! Our lab is currently seeking a dedicated and enthusiastic student starting in the fall semester of 2022 to join a project on hillslope evolution modelling. The project is supported by an NSF-CAREER grant and leverages a unique opportunity to test hillslope evolution models against statewide LiDAR datasets measured a decade apart. Successful candidates will have a background in physical geography, geomorphology, soil science, or closely related field. Valuable skills include spatial analysis as well as scripting in Python, R, and/or MATLAB.
Project Summary: Conventional agricultural practices on low relief, transport-limited landscapes are causing erosion rates that exceed the rates of soil production and threaten agricultural sustainability (Montgomery, 2007). Although climate models predict continued increases in the severity of floods and losses in crop productivity, they currently do not include the feedback loops of the impacted landscape morphology. Virtually all models predicting impacts of climate change rely on static maps of topography and/or soil. We know that assumption is incorrect, but the static data is used because it is the best data available. The ultimate goal of this project is to assemble a hillslope erosion-deposition model for low relief, regolith-based landscapes that has been validated at the regional scale. This knowledge is crucial for incorporating landscape change into models that predict impacts of climate change, such as effects on flooding and crop productivity.
The major barriers limiting the use of hillslope erosion-deposition models to predict topographic change for low relief, regolith-based landscapes are the disciplinary divides between geomorphology and soil science as well as the absence of data for full validation. Geomorphology studies tend to focus on high-relief landscapes. In contrast, soil scientists typically investigate lower relief, agricultural areas in the context of mass removed and effects on soil properties. Therefore, an integrated landscape model is needed that combines the theories of geomorphology and soil science to predict landscape change in the areas that currently experience the most active erosion and that are crucial to securing food and feed needs in the future. The PI will study hillslope erosion-deposition models and calibrate them to multiple landform regions within the USA Corn Belt. These models will be validated and evaluated through the elevation differences observed between the 2009 and 2020 LiDAR-based elevation data collected for the state of Iowa.
Prospective Graduate Students
This research group is always looking for exceptional graduate students with matching research interests. Our primary focus is on digital soil mapping and soil geomorphology. Nonetheless, funding is required for admission. Funded assistantships will be posted on this page.
Useful skills for success in our lab include some combination of the following: basic statistics, computer programming (e.g. Python, R), geographic information systems (GIS), and/or soil geomorphology. Fieldwork is frequently a component of our research activities, which makes having a driver’s license an important asset.
Graduate students working in this research group have the ability to choose from graduate programs in Soil Science, Environmental Science, and/or Sustainable Agriculture. Graduate students enjoy a strong community both within the GLSI research group and across the department and campus. Agronomy is a unique research environment, housing researchers ranging from soil to meteorology to plant sciences. This offers students the opportunity to interact with a diverse set of colleagues. Please contact Bradley if you have any questions.
Prospective Post-doctorates and Visiting Scientists
These positions will be advertised when funding allows. However, if you are interested in developing a proposal or have your own resources and would like to connect with our research group, please contact Bradley.