1. 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
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Watershed Delineation in the Field:
A New Approach for Mobile Applications
Using LiDAR Elevation Data
Financial Support from USDA-NIFA for Proposal Number is 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.