B41B-0422
Soil Biogeochemical Properties and Erosion Source Prediction Model Summary for the Buffalo Bayou Watershed, Houston, Texas
Soil Biogeochemical Properties and Erosion Source Prediction Model Summary for the Buffalo Bayou Watershed, Houston, Texas
Thursday, 17 December 2015
Poster Hall (Moscone South)
Abstract:
We draw conclusions on the research output and findings from a 4-year multidisciplinary USDA-CBG collaborative program in sustainable integrated monitoring of soil organic carbon (SOC) loss prediction via erosion. The underlying method uses the state-of-the-art stable isotope science of sediment tracing under uncertain hydrologic influences. The research finds are rooted in the (i) application of Bayesian Markov Chain Monte Carlo statistical models to assess the relationship between rainfall-runoff and soil erosion in space and time, (ii) capture of the episodic nature of rainfall events and its role in the spatial distribution of SOC loss from water erosion, (iii) stable isotope composition guided fingerprinting (source and quantity) of eroded soil, and (iv) the creation of an integrated watershed scale statistical soil loss monitoring model driven by spatial and temporal correlation of flow and stable isotope composition. The research theme was successfully applied on the urbanized Buffalo Bayou Watershed in Houston, Texas. The application brought to light novel future research conceptual outlines which will also be discussed in this deliverable to the AGU meeting. These include but not limited to: regional rainfall cluster research, physics of muddy river-bank soil and suspended sediment interaction, and friction & mobility that together make up the plasticity of soil aggregates that control erosion processes and landscape changes in a riparian corridor.
Fox, J.F. and Papanicolaou, A.N. (2008). An un-mixing model to study watershed erosion processes. Advances in Water Resources, 31, 96-108.