Observing river stages using unmanned aerial vehicles

Hydrol. Earth Syst. Sci., 20, 3193–3205, 2016 www.hydrol-earth-syst-sci.net/20/3193/2016/ doi:10.5194/hess-20-3193-2016 © Author(s) 2016. CC Attribution 3.0 License. Observing river stages using unmanned aerial vehicles Tomasz Niedzielski, Matylda Witek, and Waldemar Spallek Department of Geoinformatics and Cartography, Faculty of Earth Science and Environmental Management, University of Wrocław, pl. Uniwersytecki 1, 50-137 Wrocław, Poland Correspondence to: Tomasz Niedzielski () Received: 27 January 2016 – Published in Hydrol. Earth Syst. Sci. Discuss.: 1 February 2016 Revised: 29 June 2016 – Accepted: 4 July 2016 – Published: 9 August 2016 Abstract. We elaborated a new method for observing water surface areas and river stages using unmanned aerial vehicles (UAVs). It is based on processing multitemporal five orthophotomaps produced from the UAV-taken visible light images of nine sites of the river, acquired with a sufficient overlap in each part. Water surface areas are calculated in the first place, and subsequently expressed as fractions of total areas of water-covered terrain at a given site of the river recorded on five dates. The logarithms of the fractions are later calculated, producing five samples, each consisted of nine elements. In order to detect statistically significant increments of water surface areas between two orthophotomaps, we apply the asymptotic and bootstrapped versions of the Student’s t test, preceded by other tests that aim to check model assumptions. The procedure is applied to five orthophotomaps covering nine sites of the Ścinawka river (south-western (SW) Poland). The data have been acquired during the experimental campaign, at which flight settings were kept unchanged over nearly 3 years (2012–2014). We have found that it is possible to detect transitions between water surface areas associated with all characteristic water levels (low, mean, intermediate and high stages). In addition, we infer that the identified transitions hold for characteristic river stages as well. In the experiment we detected all increments of water level: (1) from low stages to mean, intermediate and high stages; (2) from mean stages to intermediate and high stages; and (3) from intermediate stages to high stages. Potential applications of the elaborated method include verification of hydrodynamic models and the associated predictions of high flows as well as monitoring water levels of rivers in ungauged basins. 1 Introduction A key problem in assessing performance of distributed hydrodynamic models, which predict water depth across a river channel and can therefore be used to simulate flood extent, is access to up-to-date information on true inundation. There are numerous approaches used to carry out such observations of inundation. They include terrestrial observations of flood damage carried out by volunteers, who witnessed the flood, following the concept of volunteered geographic information (VGI) (e.g. Poser and Dransch, 2010), geomorphological survey and a subsequent mapping of landforms produced as a consequence of a high flow (e.g. Latocha and Parzóch, 2010), aerial photogrammetry (e.g. Yu and Lane, 2006a), use of satellite remote sensing (e.g. Smith, 1997; Kouraev et al., 2004), application of airborne light detection and ranging (lidar) measurements (Lang and McCarty, 2009) as well as use of photographs taken by unmanned aerial vehicles (UAVs) (Witek et al., 2014). However, only a few on demand solutions exist that allow for real-time acquisition of such data (e.g. Schnebele et al., 2014). One of these solutions is the integration of HydroProg, FloodMap and UAV, known hereinafter as HFU, which has been proposed by Niedzielski et al. (2015) after the initial feasibility study offered by Witek et al. (2014). The HFU approach utilizes the UAV observations carried out in near real time, i.e. when the integrated HydroProg (Niedzielski et al., 2014; Niedzielski and Miziński, 2016) and FloodMap (Yu and Lane, 2006a, b) solutions produce a real-time warning of predicted inundation. According to Niedzielski et al. (2015), the workflow of the HFU is the following: (1) HydroProg computes a hydrograph prediction based on a multimodel ensemble for 3 h into the future (this is done routinely in real time with a predefined frequency), Published by Copernicus Publications on behalf of the European Geosciences Union. 3194 T. Niedzielski et al.: Observing river stages using unmanned aerial vehicles (2) FloodMap uses the above-mentioned forecast as an input and enables mapping the hydrograph prognosis into the spatial domain (this is also done routinely in real time with the same frequency), (3) the warning is issued and the UAV team is notified (to be done only when a number of inundated raster cells exceeds a certain threshold), (4) the UAV team carries out the survey in order to take aerial photographs of the river channel (not routinely, but only after a warning has been issued). It is known that hydrodynamic models may produce incorrect simulations, and this is also likely in the case of the HydroProg–FloodMap integration. The outputs from this integration are maps of predicted extent of terrain covered by water, known also as water surface area. Thus, in order to verify such outputs we propose to compare the aforementioned maps with the orthophotomaps produced from the UAV-acquired visible light photographs taken in near real time. Although such a stepwise procedure is conceptually complete, there is no clear picture of whether it is possible to detect changes in water extent using the UAV-based orthophotomaps. This paper aims to check the meaningfulness of the UAV-based observations of water surface areas. In order to prove the aforementioned HFU concept we herein aim to verify the research hypothesis, which reads as follows: “small changes in water surface areas are observable using the UAV”. Such small changes may occur, for instance, when river stages rise from mean to high levels, which does not always produce inundation (i.e. when water does not pass embankments or river banks, but only sinks into old river channels, flows through flood shortcuts or fills the current river channel). In order to explain such changes we graphically present the difference between water extents during low and high stages (Fig. 1). Since water surface area is directly associated with river stage (Usachev, 1983; Smith, 1997), our problem of detecting the above-mentioned changes is equivalent to seeking significant transitions in river stages. In other words, our hypothesis can also read as follows: “meaningful changes in river stages are observable using the UAV”. Both flood extents and water levels of large rivers are observable from satellites. For observing water surface areas, the following satellite-acquired measurements are used: high-resolution visible light images or infrared images, passive microwave data and radar images. For observing water levels from satel (...truncated)