Process lidar DEM for topographic analysis
Applied three smoothing techniques to 0.5 m resolution lidar DEM: polynomial fitting of grid cells, spatial smoothing using moving windows, and temporal smoothing over different time periods (0.25 to 3.25 kyr).
Quantities: 0.5 m resolution DEM, smoothing ranges from 1.5 m to 13.5 m spatial, 0.25 to 3.25 kyr temporalDuration: Data processing phaseConditions: Computational analysis
Equipment: 0.5 m lidar DEM, GIS software
Calculate topographic curvature and derivatives
Computed curvature (∇·∇η) from processed DEM using second-order derivatives. Applied diffusion equation smoothing with Kd∇·∇η where Kd is diffusion coefficient.
Quantities: Grid-based calculations across entire study areaDuration: Computational processingConditions: Multiple DEM smoothing scenarios tested
Equipment: computational software for differential equations
Calibrate hybrid model parameters
Used grid search approach to calibrate seven parameters: normalized soil depth (ho), weathering rate (Pp), mean soil thickness (h̄), curvature slope (a), topography diffusion coefficient (Kd), soil erodibility (Ks), and erosion threshold (Ethre). Parameters calibrated separately for north- and south-facing hillslopes.
Quantities: 7 parameters total, separate calibration for 2 slope aspectsDuration: Model calibration phaseConditions: Based on field measurement dataset
Equipment: computational modeling software
Perform sensitivity analysis
Applied Morris one-step-at-a-time method with 20 elementary effects per parameter. Used absolute mean value instead of mean value to avoid influence of non-monotonic effects.
Quantities: 20 elementary effects calculated per parameterDuration: Model analysis phaseConditions: Statistical analysis of parameter importance
Equipment: TOUGH2 software, statistical analysis tools