Automatic Image‐Based Water Stage Measurement for Long‐Term Observations in Ungauged Catchments

Abstract

Small-scale and headwater catchments are mostly ungauged, even though their observation could help to improve the understanding of hydrological processes. However, it is expensive to build and maintain conventional measurement networks. Thus, the heterogeneous characteristics and behavior of catchments are currently not fully observed. This study introduces a method to capture water stage with a flexible low-cost camera setup. By considering the temporal signature of the water surface, water lines are automatically retrieved via image processing. The image coordinates are projected into object space to estimate the actual water stage. This requires high-resolution 3D models of the river bed and bank area, which are calculated in a local coordinate system with structure from motion, employing terrestrial as well as unmanned aerial vehicle imagery. A medium-and a small-scale catchment are investigated to assess the accuracy and reliability of the introduced method. Results reveal that the average deviation between the water stages measured with the camera gauge and a reference gauge are below 6 mm in the medium-scale catchment. Trends of water stage changes are captured reliably in both catchments. The developed approach uses a low-cost camera design in combination with image-based water level measurements and high-resolution topography from structure from motion. In future, adding tracking algorithms can help to densify existing gauging networks.

Photogrammetric water level determination using smartphone technology

“…The workflow is similar to the technique presented in Eltner et al. () who provided precise low‐cost expert tools to monitor river sections without gauging stations using a fixed calibrated‐camera installation. The exterior orientation was established using photogrammetric targets installed in the area surrounding the nearshore.…”

“…Compared to other camera-based gauging technologies, this method allows for flexible water gauging without the use of other referencing tools, such as staff gauges, and can be applied in regions where the permanent installation of gauging tools may be problematic. The workflow is similar to the technique presented in Eltner et al (2018) who provided precise low-cost expert tools to monitor river sections without gauging stations using a fixed calibrated-camera installation. The exterior orientation was established using photogrammetric targets installed in the area surrounding the nearshore.…”

“…A more flexible method was published by Eltner et al. () who installed low‐cost cameras in small‐ and medium‐scale catchment areas for long‐term river observation. The camera images were used to detect the prevalent water line, which were further registered with metrically scaled 3D data to derive the water level.…”

Evaluating Image Tracking Approaches for Surface Velocimetry With Thermal Tracers

“…Field data were acquired at a small stream called Wernersbach in the Tharandter Wald, Saxony, Germany (Eltner et al, ). The height of the corresponding catchment ranges between 355 and 390 m. The catchment size is about 4.6 km 2 .…”

Assessing the Influence of Temperature Changes on the Geometric Stability of Smartphone- and Raspberry Pi Cameras

“…Therefore, they are already a centrepiece in several early warning systems that are supported by volunteered geographic information with user-generated content [2,3]. Recently published water-level monitoring and flood-forecasting tools adapt well-established photogrammetric methods to smartphone-and Raspberry Pi (RPi) cameras to use them as versatile measurement instruments, e.g., [4][5][6][7][8]. To restore the collinearity between the 2D image and the related 3D object scene, i.e., to determine the linear relationships of 2D image points and 3D object points that lie on image rays with a shared origin called projection centre, knowledge about the interior orientation parameters (IOP) is required, which can be determined via photogrammetric camera calibration, e.g., [9][10][11].…”