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Using LiDAR to model rating curves
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Egen tryckning , 2012.
National Category
Physical Geography
Research subject
Physical Geography
URN: urn:nbn:se:su:diva-84292OAI: diva2:579522
2012-03-12, William Olsson, Stockholms universitet, Geovetenskapens Hus, Stockholm, 11:29 (English)
Available from: 2012-12-22 Created: 2012-12-20 Last updated: 2012-12-22Bibliographically approved
List of papers
1. Modelling rating curves using remotely sensed LiDAR data
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2012 (English)In: Hydrological Processes, ISSN 0885-6087, E-ISSN 1099-1085, Vol. 26, no 9, 1427-1434 p.Article in journal (Refereed) Published
Abstract [en]

Accurate stream discharge measurements are important for many hydrological studies. In remote locations, however, it is often difficult to obtain stream flow information because of the difficulty in making the discharge measurements necessary to define stage-discharge relationships (rating curves). This study investigates the feasibility of defining rating curves by using a fluid mechanics-based model constrained with topographic data from an airborne LiDAR scanning. The study was carried out for an 8m-wide channel in the boreal landscape of northern Sweden. LiDAR data were used to define channel geometry above a low flow water surface along the 90-m surveyed reach. The channel topography below the water surface was estimated using the simple assumption of a flat streambed. The roughness for the modelled reach was back calculated from a single measurment of discharge. The topographic and roughness information was then used to model a rating curve. To isolate the potential influence of the flat bed assumption, a ‘hybrid model’ rating curve was developed on the basis of data combined from the LiDAR scan and a detailed ground survey. Whereas this hybrid model rating curve was in agreement with the direct measurements of discharge, the LiDAR model rating curve was equally in agreement with the medium and high flow measurements based on confidence intervals calculated from the direct measurements. The discrepancy between the LiDAR model rating curve and the low flow measurements was likely due to reduced roughness associated with unresolved submerged bed topography. Scanning during periods of low flow can help minimize this deficiency. These results suggest that combined ground surveys and LiDAR scans or multifrequency LiDAR scans that see ‘below’ the water surface (bathymetric LiDAR) could be useful in generating data needed to run such a fluid mechanics-based model. This opens a realm of possibility to remotely sense and monitor stream flows in channels in remote locations.

Hydrology, Krycklan Catchment, LiDAR, Modelling Rating Curves, Remot Sensing, Stream Flow
National Category
Oceanography, Hydrology, Water Resources
urn:nbn:se:su:diva-74892 (URN)10.1002/hyp.9225 (DOI)000302795100015 ()
Krycklan Catchment Study (KCS)
Available from: 2012-03-29 Created: 2012-03-29 Last updated: 2016-02-24Bibliographically approved

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