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 m orthophotomaps produced from the UAV-taken visual-light photographs of n 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 m dates. The logarithms of the fractions are later calculated, producing m samples of size n. 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 (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 produced by 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; (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 using on-demand UAV flights performed in near real-time as well as monitoring water levels of rivers in ungauged basins.
Observing river stages using unmanned aerial vehicles
