The influence of accuracy, grid size, and interpolation method on the hydrological analysis of LiDAR derived dems: Seneca Nation of Indians, Irving NY

Light Detection and Ranging (LiDAR) derived Digital Elevation Models (DEMs) provide accurate, high resolution digital surfaces for precise topographic analysis. The following study investigates the accuracy of LiDAR derived DEMs by calculating the Root Mean Square Error (RMSE) of multiple interpolation methods with grid cells ranging from 0.5 to 10-meters. A raster cell with smaller dimensions will drastically increase the amount of detail represented in the DEM by increasing the number of elevation values across the study area. Increased horizontal resolutions have raised the accuracy of the interpolated surfaces and the contours generated from the digitized landscapes. As the raster grid cells decrease in size, the level of detail of hydrological processes will significantly improve compared to coarser resolutions including the publicly available National Elevation Datasets (NEDs). Utilizing a LiDAR derived DEM with the lowest RMSE as the 'ground truth', watershed boundaries were delineated for a sub-basin of the Clear Creek Watershed within the territory of the Seneca Nation of Indians located in Southern Erie County, NY. An investigation of the watershed area and boundary location revealed considerable differences comparing the results of applying different interpretation methods on DEM datasets of different horizontal resolutions. Stream networks coupled with watersheds were used to calculate peak flow values for the 10-meter NEDs and LiDAR derived DEMs.