Comparison of Topographic Surveying Techniques in Streams

• Main Author: Bangen, Sara G.
• Format: Others
• Published: DigitalCommons@USU 2013
• Subjects: DEM; Fuzzy Inference System; Geomorphic Change Detection; Precision; Aquaculture and Fisheries; Geomorphology; Other Earth Sciences
• Online Access: http://digitalcommons.usu.edu/etd/1516; http://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=2532&context=etd

Fine-scale resolution digital elevation models (DEMs) created from data collected using high precision instruments have become ubiquitous in fluvial geomorphology. They permit a diverse range of spatially explicit analyses including hydraulic modeling, habitat modeling and geomorphic change detection. Yet, the intercomparison of survey technologies across a diverse range of wadeable stream habitats has not yet been examined. Additionally, we lack an understanding regarding the precision of DEMs derived from ground-based surveys conducted by different, and inherently subjective, observers. This thesis addresses current knowledge gaps with the objectives i) to intercompare survey techniques for characterizing instream topography, and ii) to characterize observer variability in instream topographic surveys. To address objective i, we used total station (TS), real-time kinematic (rtk) GPS, terrestrial laser scanner (TLS), and infrared airborne laser scanning (ALS) topographic data from six sites of varying complexity in the Lemhi River Basin, Idaho. The accuracy of derived bare earth DEMs was evaluated relative to higher precision TS point data. Significant DEM discrepancies between pairwise techniques were calculated using propagated DEM errors thresholded at a 95% confidence interval. Mean discrepancies between TS and rtkGPS DEMs were relatively low (≤ 0.05 m), yet TS data collection time was up to 2.4 times longer than rtkGPS. ALS DEMs had lower accuracy than TS or rtkGPS DEMs, but ALS aerial coverage and floodplain topographic representation was superior to all other techniques. The TLS bare earth DEM accuracy and precision were lower than other techniques as a result of vegetation returns misinterpreted as ground returns. To address objective ii, we used a case study where seven field crews surveyed the same six sites to quantify the magnitude and effect of observer variability on DEMs interpolated from the survey data. We modeled two geomorphic change scenarios and calculated net erosion and deposition volumes at a 95% confidence interval. We observed several large magnitude elevation discrepancies across crews, however many of these i) tended to be highly localized, ii) were due to systematic errors, iii) did not significantly affect DEM-derived metric precision, and iv) can be corrected post-hoc.