Uncertainty Propagation and Partitioning in Spatial Prediction of Topographical Factor for RUSLE

Abstract

Quantifying effect of slope length and steepness on prediction of soil erosion using the Revised Universal Soil Loss Equation (RUSLE) has become very important. In this paper, sequential indicator simulation successfully provided spatial prediction maps of these two variables based on their spatial variability from a plot data set. Uncertainty from simulation runs and semivariograms was studied to increase prediction precision. Uncertainty propagation from slope length and steepness and model parameters to predicting topographical factor LS in RUSLE was modelled using Fourier Amplitude Sensitivity Test (FAST). Spatial variance partitioning was done and uncertainty sources were identified.

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Document Details

Document Type
Technical Report
Publication Date
Jul 14, 2000
Accession Number
ADA379657

Entities

People

  • George Gertner

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Case Studies
  • Data Sets
  • Digital Elevation Models
  • Ecology
  • Indicators
  • Measurement
  • Models
  • Monte Carlo Method
  • Random Variables
  • Sampling
  • Sensitivity
  • Simulations
  • Soil Erosion
  • Spatial Distribution
  • Statistics
  • Uncertainty
  • United States

Fields of Study

  • Agricultural and Food sciences

Readers

  • Geotechnical Engineering.
  • Regression Analysis.
  • Wave Propagation and Nonlinear Chaotic Dynamics.