Projections of Landscape Evolution on a 10, 000 Year Timescale With Assessment and Partitioning of Uncertainty Sources. Issue 12 (18th December 2020)

• Record Type: Journal Article
• Authors: Barnhart, Katherine R.; Tucker, Gregory E.; Doty, Sandra G.; Glade, Rachel C.; Shobe, Charles M.; Rossi, Matthew W.; Hill, Mary C.
• Is Part Of: Journal of geophysical research. Volume 125:Issue 12(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-18
• Subjects: erosion hazard -- erosion projection -- landscape evolution -- multi model analysis -- prediction under uncertainty; Geomorphology -- Periodicals; 551.3
• DOI: 10.1029/2020JF005795
• Languages: English
• ISSNs: 2169-9003

Abstract

Abstract: Long‐term erosion can threaten infrastructure and buried waste, with consequences for management of natural systems. We develop erosion projections over 10 ky for a 5 km 2 watershed in New York, USA. Because there is no single landscape evolution model appropriate for the study site, we assess uncertainty in projections associated with model structure by considering a set of alternative models, each with a slightly different governing equation. In addition to model structure uncertainty, we consider the following uncertainty sources: selection of a final model set; each model's parameter values estimated through calibration; simulation boundary conditions such as the future incision of downstream rivers and future climate; and initial conditions (e.g., site topography which may undergo near‐term anthropogenic modification). We use an analysis‐of‐variance approach to assess and partition uncertainty in projected erosion into the variance attributable to each source. Our results suggest one sixth of the watershed will experience erosion exceeding 5 m in the next 10 ky. Uncertainty in projected erosion increases with time, and the projection uncertainty attributable to each source manifests in a distinct spatial pattern. Model structure uncertainty is relatively low, which reflects our ability to constrain parameter values and reduce the model set through calibration to the recent geologic past. Beyond site‐specific findings, our work demonstrates what information prediction‐under‐uncertainty studies can provide about geomorphic systems. Our results represent the first application of a comprehensive multi‐model uncertainty analysis for long‐term erosion forecasting. Plain Language Summary: Erosion of ground material is a hazard to buildings and other infrastructure, and can pose an environmental risk when it occurs in areas such as radioactive waste repositories and post‐industrial sites. We make projections for erosion over the next 10, 000 years and assess uncertainty sources at a 5 km 2 watershed in New York state. Natural systems, like the study site, are not as well understood as engineered systems. However, information from studies like this one can provide useful insights to guide management decisions. Parts of the watershed experienced up to 50 m of erosion over the past 13, 000 years. The type of model used to simulate land surface evolution over thousands of years is a Landscape Evolution Model (LEM). We use a set of alternative LEMs identified by prior work as successful in simulating this watershed from 13, 000 years ago to the present. We consider uncertainty in future climate, incision of downstream rivers, the models used and their parameters, and small changes to the initial topography. We find that just under 20% of the study site will experience erosion exceeding 5 m at +10, 000 years. The most important uncertainty source varies across the watershed and increases with time. Key Points: Projections of erosion to 10 ky and uncertainty assessment demonstrate that the dominant uncertainty sources vary in space and time Two alternative approaches to model selection result in similar projections and uncertainty at 10 ky Variation across alternative models is subtle and initial conditions influence the location of gullies that drain low‐relief areas