A Bayesian Unmixing Model for Land-Use Fingerprinting Using Deltaσ5 C/N
Publication: World Environmental and Water Resource Congress 2006: Examining the Confluence of Environmental and Water Concerns
Abstract
In this study, a new unmixing model is presented for land-use fingerprinting eroded-soil using delta5N and C/N. The model is specified within the Bayesian Markov Chain Monte Carlo framework and is capable of unmixing erosion sources characterized by multiple erosion processes. A unique attribute of the formulation is the use of a truncation parameter to account for uncertainty during the erosion process. The model was applied for fingerprinting soils from forest and agriculture land-uses in Jerome Creek sub-watershed of the Upper Palouse Watershed, Northwestern Idaho. Multiple processes including upland rill erosion and floodplain headcut erosion are represented within the agriculture region of the Upper Palouse. A sensitivity analysis for the unmixing model and comparison of the model with sediment yield estimates for the land-uses add confidence to the accuracy of the model.
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Information
Published In
World Environmental and Water Resource Congress 2006: Examining the Confluence of Environmental and Water Concerns
Pages: 1 - 12
Copyright
© 2006 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
ASCE Technical Topics:
- Analysis (by type)
- Bayesian analysis
- Engineering fundamentals
- Erosion
- Geology
- Geotechnical engineering
- Infrastructure
- Land use
- Markov process
- Mathematics
- Model accuracy
- Models (by type)
- Probability
- River engineering
- River systems
- Sediment
- Sensitivity analysis
- Statistical analysis (by type)
- Stochastic processes
- Urban and regional development
- Urban areas
- Water and water resources
- Watersheds
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