TUgis Conference 2019

A time-consuming and labor-intensive task of floodplain modeling is reconciling the detailed geometry of a studied stream with its greater stream network and watershed. The hydrology and watershed of the studied reach can be adequately determined with lower-resolution DEMs, but the corresponding hydraulics and floodplain extents necessitates higher-resolution DEM data. That is, the streamline of the studied reach must match not only aerial imagery but also high-resolution lidar. As higher and higher resolution DEMs become available, the effort required to produce a high-quality streamline also becomes higher and higher. Readily available National Hydrography Dataset (NHD)+ Hi Res streamline data contains important reach connectivity information, but often fails to match the resolution of the best-available lidar. Even the best lidar typically hydro-enforces bridges, but not culverts or dams. Although hydro-connectors resolve this issue, this data is not always available, and to create them using only visual inspection is a tedious, time-consuming, and expensive task. High-quality DEMs also come at the cost of longer and more intensive computing requirements. Fortunately, there are a multitude of tools, algorithms, and GIS platforms that can reduce both human and computing cost. Newer versions of Esri's ArcMap Desktop and ArcMap Pro offer more complex flow direction algorithms in addition to faster processing speeds. GRASS (Geographic Resources Analysis Support System) and Whitebox offer similar capabilities, but do not require expensive licenses. These free, open-source softwares also include hydrology-tailored toolboxes that rival or even surpass that of the well-known Esri ArcHydro toolbox. This presentation will outline some of these tools and compare and contrast the algorithms, processing time, and output quality associated with each of them. This analysis can help floodplain modelers devise a cost-effective strategy for automating streamline generation across a variety of terrains.