Effect of Topographic Characteristics on Compound Topographic Index for Identification of Gully Channel Initiation Locations

Abstract

Sediment loads from gully erosion contribute to water quality problems, reduction in crop productivity by removal of nutrient-rich topsoil, and damage to downstream ecosystems. The identification of areas with high potential for gully channel development is often performed using spatially derived stream power estimates from second-order topographic indices, such as the compound topographic index (CTI). The utilization of CTI to identify where gullies develop is affected by field and local topographic characteristics and DEM resolution. In this study, the effect of overall terrain slope, local relief variance, and raster grid cell size on CTI cumulative distribution values was investigated using theoretical and observed catchment methodology. In the theoretical analysis, stochastic methods were used to generate simulated catchments to quantify the influence of overall terrain slope, local relief variance, and raster grid cell size (each considered individually). The observed methodology used three sites with distinct topographic characteristics, measured gully channels, and high-resolution topographic information. Raster grids for the three observed study sites were generated at varying raster grid cell sizes. Critical CTI values were determined through comparison of measured gully thalwegs with threshold CTI raster grids of the observed watersheds at different resolutions. Results from the theoretical investigation indicate that CTI values were linearly influenced by changes in relief variance and overall slope, while variations in raster grid cell size caused an inverse power variation in CTI values. In addition, variations in raster grid cell size, produced changes in cumulative distributions of the top 0.1% CTI values. The use of normalized CTI values (CTI n) produced merged cumulative distribution curves when varying overall slope, terrain relief variance, and to a lesser degree DEM resolution. Similar findings were obtained from the analysis of observed catchments. When DEM resolution varied, the differences in critical CTI n values in the same field were significantly reduced when compared to original critical CTI values, although differences were not fully eliminated. Normalization of the CTI cumulative distributions improved comparisons between different sites with distinct drainage area sizes and topographic characteristics, providing a possible alternative for investigations of large watersheds with more than one topographic characteristic. Results suggest that a normalized critical CTI between 1 and 2 could be used for the identification of areas with high potential for gully development. Knowing where gullies develop is important in understanding the effect of conservation practices on soil erosion through the use of field-scale and watershed-scale simulation models. Effective watershed management plans depend on this information to target the placement of conservation practices for the efficient use of available resources.

Characterization and Placement of Wetlands for Integrated Conservation Practice Planning

“…Although not within the scope of this study, the influence of DEM spatial resolution on topographic indices and their cumulative distribution functions is important (Momm et al, 2011(Momm et al, , 2013. While the effect of DEM spatial resolution on drainage area is approximately linear, its effect on terrain slope is non-linear.…”

Identifying Potential Locations for Grassed Waterways using Terrain Attributes and Precision Conservation Technologies

“…Studies have previously evaluated DEM spatial resolution for topographic attributes and subsequent model results (Kienzle, 2004;Momm et al, 2012). The topographic attribute values for a raster grid cell vary with DEM resolution, and finer DEMs were recommended for locating ephemeral gullies, as coarser DEMs present limited topographic information (Daggupati et al, 2013;Momm et al, 2013). The LiDAR data (horizontal resolution of 3 m) for the study area were collected by the Iowa Department of Natural Resources in 2008 under Iowa's LiDAR program.…”

“…The primary function of effective GWWs is to prevent ephemeral gully erosion; therefore, locating the areas prone to erosion is necessary to identify potential locations for GWWs (Fiener and Auerswald, 2003). Various studies have developed methods to detect ephemeral gully locations using terrain attributes and topographic threshold values (Moore et al, 1988;Thorne et al, 1986;Parker et al, 2007;Daggupati et al, 2013Momm et al, 2013. Pike et al (2009) developed erosion probability maps with 4 m elevation data using logistic regression and neural networks for GWW placement in Kentucky fields.…”

Evaluating functional connectivity in a small agricultural catchment under contrasting flood events by using UAV

“…This is why predicting the location of erosion trajectories by applying topographic index models from the combination of primary topographic attributes, in order to calculate an index value at each point (or pixel) of a catchment, is one of the main research insights of catchment geomorphology (e.g. Moore et al, 1988;Vandekerckhove et al, 1998;Poesen et al, 2003;Parker et al, 2007;Daggupati et al, 2013;Momm et al, 2013). Based on these models, the aligned points where the index exceeds a certain threshold value are assumed to define potential trajectories for the development of concentrated erosion (Montgomery and Dietrich, 1994).…”