CAREER: Alluvial-river dynamics through watershed networks

Rivers and their tributaries form networks that integrate the far reaches of Earth's landscapes, linking our homes, farms, cities, and wilderness areas. These rivers are ever-changing, sometimes near-imperceptibly and sometimes dramatically adjusting their forms to carry the water and sediment supplied by rainfall, snow/ice melt, and erosion of the surrounding landscape. Both natural and human activities can alter the balance of water and sediment entering rivers, causing them to erode downwards into their beds when water supply outweighs sediment supply, or to deposit sediments and raise the level of their beds when sediment supply increases beyond what the water can carry. Wickert and his team will develop a theory to predict these river-system changes, and incorporate it into a computer model that includes rainfall and runoff, lakes and wetlands, and processes that shape rivers. They will test this theory and model using data from rivers in Minnesota, USA, and Salta, Argentina. These rivers' bed elevations have changed by tens to hundreds of meters during past glacial cycles and by several meters over the past 200 years in response to changing climate and land use. Controlled experiments on small-scale rivers conducted at the Saint Anthony Falls Laboratory will supplement these field-based tests. The proposed outcome of this work is an efficient, physics-based, predictive model to simulate river-network evolution in response to climate and land-use change. The project will train undergraduate students, graduate students, and postdoctoral scholars. The team will work with the Ojibwe people to broaden participation in science.

Wickert and his group will develop and test theory and models to simulate river-network response to changes in water and sediment supply. They will codify river-tributary networks into mathematical networks that additionally incorporate valleys, lakes, and the surrounding hillslopes. They will then couple and solve equations describing alluvial-river dynamics across these networks to predict the complex response of rivers to external perturbations. These equations will underlie a new numerical model, to be tested against field and laboratory data and driven by records and simulations of sediment inputs and water discharge. This model will enable us to rapidly simulate alluvial-river response to drivers of geomorphic change, thereby improving our ability to both reconstruct past river dynamics and forecast the impacts of environmental change on rivers into the future.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.