LiDAR-based predictions of flow channels through riparian buffer zones

Abstract

Riparian buffer zones (RBZs) are critical for protecting stream water quality. High Resolution Light Detection and Ranging (LiDAR) data provides a way to locate channels where water can flow through a RBZ and into a stream. The objectives of this study were to characterize flow channels through riparian buffer zones around Lake Issaqueena, SC, USA, using LiDAR topography models and to validate these predictions using field observations of channel presence, soil moisture content and soil temperature. A LiDAR derived digital elevation model (DEM) was utilized to define flow channels and determine forty sample locations. Analysis indicated channel locations and the presence of large forested buffers generally 10 m or greater in the study area. High flow accumulation channels can be accurately predicted by LiDAR data, but lower flow channels were less accurately estimated. Surface soil temperature measurements were relatively uniform showing no difference between predicted channel and control locations. Presented methodologies can serve as a template for future efforts to quantify riparian buffers and their effects on protecting water quality.

Regional Scale Dryland Vegetation Classification with an Integrated Lidar-Hyperspectral Approach

“…In addition, DEMs support flow accumulation modeling that can be combined with topographical information to delineate riparian zones. Topographic-based riparian delineations can be integrated into classification schemes to improve the accuracy of riparian vegetation mapping [44,45]. In this study, we focus on the use of state-of-the-art airborne lidar for improving confusion between riparian and other mesic vegetation classes.…”

Potential of time‐lapse photography for identifying saturation area dynamics on agricultural hillslopes

“…Although Dunne and Black (1970) mapped saturation areas manually, less labour-intensive methods have in the meantime been developed, such as remote sensing techniques using airborne radar and cameras (Barrette, August, & Golet, 2000;Brun et al, 1990), Lidar (de Alwis, Easton, Dahlke, Philpot, & Steenhuis, 2007;Solomons, Mikhailova, Post, & Sharp, 2015), terrestrial photography by optical (Keys, Jones, Scott, & Chuquin, 2016;Orlandini et al, 2012), and thermal cameras (Glaser et al, 2016;Pfister, McDonnell, Hissler, & Hoffmann, 2010). Also, vegetation patterns have been mapped as a surrogate for saturation (Güntner, Seibert, & Uhlenbrook, 2004;Kulasova, Beven, Blazkova, Rezacova, & Cajthaml, 2014;Rogger et al, 2012).…”

Characterizing Dryland Ecosystems Using Remote Sensing and Dynamic Global Vegetation Modeling

“…Topographic-based riparian delineations can be integrated into classification schemes to improve the accuracy of riparian vegetation mapping (Solomons et al, 2015;Tompalski et al, 2017). In this study, we focus on the use of state-of-the-art airborne lidar for improving confusion between riparian and other mesic vegetation classes.…”