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

摘要

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.