Use of Bathymetric and LiDAR Data in Generating Digital Elevation Model over the Lower Athabasca River Watershed in Alberta, Canada
Open Access
Abstract
The lower Athabasca River watershed is one of the most important regions for Alberta and elsewhere due to fact that it counts for the third largest oil reserve in the world. In order to support the oil and gas extraction, Athabasca River provides most of the required water supply. Thus, it is critical to understand the characteristics of the river and its watershed in order to develop sustainable water management strategies. Here, our main objective was to develop a digital elevation model (DEM) over the lower Athabasca River watershed including the main river channel of Athabasca River (i.e., approximately 128 km from Fort McMurray to Firebag River confluence). In this study, the primary data were obtained from the Alberta Environmental Monitoring, Evaluation and Reporting Agency. Those were: (i) Geoswath bathymetry at 5–10 m spatial resolution; (ii) point cloud LiDAR data; and (iii) river cross-section survey data. Here, we applied spatial interpolation methods like inverse distance weighting (IDW) and ordinary kriging (OK) to generate the bathymetric surface at 5 m × 5 m spatial resolution using the Geoswath bathymetry data points. We artificially created data gaps in 24 sections each in the range of 100 to 400 m along the river and further investigated the performance of the methods based on statistical analysis. We observed that the DEM generated using the both IDW and OK methods were quite similar, i.e., r2, relative error, and root mean square error were approximately 0.99, 0.002, and 0.104 m, respectively. We also evaluated the performance of both methods over individual sections of interest; and overall deviation was found to be within ±2.0 m while approximately 96.5% of the data fell within ±0.25 m. Finally, we combined the Geoswath-derived DEM and LiDAR-derived DEM in generating the final DEM over the lower Athabasca River watershed at 5 m × 5 m resolution.Keywords
Funding Information
- Alberta Environmental Monitoring, Evaluation and Reporting Agency (AEMERA)
- NSERC Discovery Grant
This publication has 29 references indexed in Scilit:
- Analysis and GIS Mapping of Flooding Hazards on 10 May 2016, Guangzhou, ChinaWater, 2016
- Application of a Terrestrial LIDAR System for Elevation Mapping in Terra Nova Bay, AntarcticaSensors, 2015
- Integrated River and Coastal Hydrodynamic Flood Risk Mapping of the LaHave River Estuary and Town of Bridgewater, Nova Scotia, CanadaWater, 2014
- Spatial interpolation methods applied in the environmental sciences: A reviewEnvironmental Modelling & Software, 2014
- Filtering spatial error from DEMs: Implications for morphological change estimationGeomorphology, 2011
- Assessing DEM interpolation methods for effective representation of upland stream morphology for rapid appraisal of bed stabilityRiver Research and Applications, 2010
- Comparison of LiDAR waveform processing methods for very shallow water bathymetry using Raman, near‐infrared and green signalsEarth Surface Processes and Landforms, 2010
- Influence of survey strategy and interpolation model on DEM qualityGeomorphology, 2009
- Application of airborne LiDAR in river environments: the River Coquet, Northumberland, UKEarth Surface Processes and Landforms, 2003
- Monitoring and modelling morphological change in a braided gravel-bed river using high resolution GPS-based surveyEarth Surface Processes and Landforms, 2000