Watershed Delineation in the Field: Authors: Sam Noel, ABE Dennis Buckmaster, ABE Aaron Ault ECE Indrajeet Chaubey, ABE Bernie Engel, ABE Jane Frankenberger, ABE Jim Krogmeier, ECE Dennis Flanagan, ABE/USDA Try our Android app! Watershed Delineation in the Field: A New Approach for Mobile Applications Using LiDAR Elevation Data Financial Support from USDA-NIFA for Proposal Number 2011-51130-31119is acknowledged. Motivation Streamline design and decision-making processes by reducing trips back to the office to communicate with engineering staff perform computations on desktop software before reporting to the farmer High-resolution elevation data (Indiana LiDAR-based DEMs) and mobile technology enables field-scale watershed analyses to take place while on-site High-resolution data enables more detailed topographic information. Typical GIS watershed functions applied to this data did not produce reliable results at field scales Objectives Match observations: The visualized results must be verifiable while on site and should not conflict with ground observations. Handle microtopography: Since a user on-location is far more likely to be interested in their immediate surroundings rather than large-scale watersheds that could be easily delineated in the office, the algorithm must operate on high-resolution DEMs at less than 5 meter resolution. Allow modifications: The algorithm should be able to account for small-scale hydrologic modifications (tile risers, culverts, and bridges) or adjustments to the elevation data (removal of a forest, fencerow, or otherwise regrading the land). Optimized for mobile devices: Because it is aimed at field scale delineations while on location, the algorithm was designed to operate in mobile, resource- constrained environments. Handle Man-Made Drainage Features Before Tile Riser After Previously Filled Volume Current Depression Volume Current Spillover Elevation Depression Boundaries Current Flow Directions Selected Outlet Location   Omitting Tile Riser Selected Outlet Location   Tile Riser Location Including Tile Riser A visualization of sequential depression-filling. Initially two depressions existed, but one has overflowed, merging with the other into a single depression. Notice the change in flow directions, the filled elevations, and the new depression boundaries afterward. Sequential Depression-Filling Algorithms (SDFAs) Rather than implement a standard GIS “fill” function, our algorithm identifies depressions in the elevation data, their physical dimensions, and where they will spill over. Given a rainfall amount, the chronology of filling and overflowing as well as the interconnectedness of depressions may be understood. Small depressions overflow quickly while large depressions may remain hydrologically isolated depending on the rainfall event. Watersheds delineated at a Fulton, County, Indiana, USA agricultural field with varying rainfall amounts. Note that the last is equivalent to the watershed produced using a GIS “Fill” function where all depressions are filled. 0.4-Inch Rainfall (< 2-Year Storm) 3-Inch Rainfall (2-Year Storm) 5.5-Inch Rainfall (100-Year Storm) 5-Inch Rainfall (50-Year Storm) Comparison of watersheds delineated while either omitting or including a man-made drainage tile riser (shown above; notice the surrounding area forms a basin-like shape). Omitting the tile riser overestimates the contributing area whereas including it does not; it has prevented the natural depression from overflowing. Algorithm Verification A considerable amount of time was spent in the field defining usage scenarios and verifying the results produced by our SDFA. The catchments produced using methods that guarantee hydrologic connectivity by filling all depressions produce polygons that are artifacts of a chosen flow accumulation threshold and often do not correspond with . On the other hand, the perimeter of the polygons produced from our SDFA without filling all depressions can be verified in the field as topographic ridge features.