**Author details**

sion channels. Smoothing removes artifacts resulting from differences in plant residue heights perpendicular to the direction of travel by farm machinery. These differences can ac‐ tually cause the terrain analysis flow models to incorrectly rout water along the direction of travel. While smoothing produced better results in this chapter, the method of smoothing with ArcGIS TopoToRaster was not efficient and cannot be used over large areas. More work is needed to determine computationally efficient smoothing algorithms for terrain

Conservation planners and GIS analysts should be able to accurately identify erosion fea‐ tures with the D8, D∞, FD8, and DEMON flow direction algorithm. This is important be‐ cause previous work was based on TAPES G which is no longer being supported. Further TauDEM can utilize very large blocks of memory to cover extensive land areas, and can also operate on high performance computers. It is important to note that the choice flow algo‐ rithm will change the model parameters so it is important that they use the correct model. We recommend the TauDEM software program which uses the D8 and D∞ procedures be‐ cause it works on 64 bit machines, allows the use of multiple core processer, and works with

All analyses performed in this study were based on with 4-m DEMs. Efforts are necessary to better understand the impact of the scale of terrain models on the quality of erosion model predictions. It may also be possible to expand the inference space of these models by includ‐

D8, deterministic eight-neighbor; FD8, fractional deterministic eight-neighbor; DEMON, digital elevation model networks; DEM, Digital Elevation Model; TauDEM, Terrain Analy‐ sis Using Digital Elevation Models; TAPES, Grid-Based Terrain Analysis Programs for the Environmental Sciences; GIS, geographic information systems; RTK, Real Time Kinematic

We appreciate the generosity of Mike Ellis in providing us access to his grassed waterway datasets and Mike, Bob, and Jim Ellis for allowing us to conduct this research on their farm. We are also grateful for the assistance of Randall Rock, Jack Kuhn, Danny Hughes from the NRCS. We would like to thank Steve Workman from the UK college of Agriculture for sup‐ port from the SB-271 Water Quality Funding. We also wish to express our appreciation to Photo Science president Mike Ritchie for providing us the complementary LiDAR data used

ing erosion parameters in the analyses obtained from soil surveys.

analysis that minimize artifacts.

60 Research on Soil Erosion Soil Erosion

DEMs up to 4 GB in size.

**5. Nomenclature**

GIS, Geographic Information System.

**Acknowledgements**

in this chapter.

Adam Pike1 , Tom Mueller2\*, Eduardo Rienzi2 , Surendran Neelakantan2 , Blazan Mijatovic2 , Tasos Karathanasis2 and Marcos Rodrigues3

