A novel algorithm for delineating wetland depressions and mapping surface hydrologic flow pathways using LiDAR data
Citation:
Wu, Q. AND C. Lane. A novel algorithm for delineating wetland depressions and mapping surface hydrologic flow pathways using LiDAR data. 2017 AWRA Spring Specialty Conference on Aquatic System Connectivity, Snowbird, UT, May 01 - 03, 2017.
Impact/Purpose:
Presentation at AWRA Spring Specialty Conference in Snowbird, UT May 1-3, 2017
Description:
In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features that are seldom fully filled with water. For instance, wetland depressions in the Prairie Pothole Region (PPR) are seasonally to permanently flooded wetlands characterized by nested hierarchical structures with dynamic filling- spilling-merging surface-water hydrological processes. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution LiDAR data and aerial imagery. We proposed a novel algorithm delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost path algorithm. The resulting flow network delineated putative temporary or seasonal flow paths connecting wetland depressions to each other or to the river network at scales finer than available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow modeling and hydrologic connectivity analysis.
