Modelling rating curves using remotely sensed LiDAR data

Abstract

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. Copyright © 2012 John Wiley & Sons, Ltd.

Can Low-Resolution Airborne Laser Scanning Data Be Used to Model Stream Rating Curves?

“…For this second case, it should be noted that a horizontal line was assumed to extend from the lowest available ALS topography point, thereby defining an apparently flat stream bottom, to facilitate subsequent hydraulic rating curve modeling. Nathanson et al [38] demonstrated that the impact of such a flat bottom assumption was minimal at this location. This was because most of the information with regard to the stream channel's overall shape (particularly, as it is expressed at higher flows) and geometry is measured with the ALS data.…”

“…This allowed for initial classification of the higher intensity ground echoes reflecting the region's relatively smooth ground surface topography and the lower intensity vegetation echoes. This information was then used to filter based on the identification of backscatter signatures caused by surface vegetation, which can be identified relative to backscatter signatures caused by ground topography (see [38] for more details). After filtering ground from non-ground echoes, the set of ALS data covering the 90-m stream segment considered in this study consisted of over 45,000 ground echoes (Figure 1).…”

“…The thinned ALS and non-thinned ALS data (e.g., the low-resolution and high-resolution elevation data, respectively) were used to implement the hydraulic model of Kean and Smith [44] as outlined in Nathanson et al [38]. Note that for the high-resolution, non-thinned case, we use the ALS survey augmented by the bathymetric profile survey data, since this provides an absolute best case scenario for the rating curve modeling.…”

“…Figure 2b shows an example cross-section of the stream at the position where the representative rating curves were extracted for the non-thinned and thinned survey-augmented data. Boundary (bed) roughness, specified in terms of a roughness height zo for every point on a two-dimensional curvilinear grid of the stream channel within the modeling domain, was back calculated by using a single measurement of low flow discharge and the corresponding water surface slope [38,45]. Vegetation densities on the banks and floodplain, which supply a drag force on flows, were measured in the field.…”

“…Abu-Aly et al [36] offered a divergent methodology to utilize LiDAR data employing the approach from Katul et al [37] to quantify hydraulic roughness as a function of vegetation height and water depth via a 2D hydraulic model. Nathanson et al [38] demonstrated that high-resolution ALS data (more than 2 points/m 2 ) can contain enough information on the stream channel geometry to model stage-discharge relationships (rating curves) under certain conditions for relatively simple channel geometries. The rating curve is the functional relationship that allows for stream discharge monitoring based on direct observation of water height (stage) in a stream channel.…”