River discharge modelling based on surface flow velocity estimations

Abstract

Rivers have long since exceeded their natural purpose of discharging excess water, by becoming subject to many practical applications demanded by present day society [61]. In order to comply withthis variety of needs and demands, the necessity for proper water management arises, which in turn requires data and knowledge of hydrological parameters like water levels, water quality and river dis-charge [50]. This research focuses on the hydrological data demand and specifically on the measurement of riverdischarge. Discharge is generally estimated with intrusive measurement methods [64], this means that the measurement device is in physical contact with the water which can be difficult in strong current or high discharges and even dangerous during floods . Furthermore, in remote and low-resource settings, collecting discharge data is compromised by accessibility problems and difficulties maintaining and acquiring monitoring equipment. When numerous measurements are performed, it is common practice to establish a stage-discharge relationship [66] to facilitate discharge determination, i.e. by shifting to stage measurements. However, due to the empirical character of the method and the sporadic occurrence of high discharges, the relationship can contain considerable uncertainties for these higher discharges [67]. The aim of this research is to provide a sustainable and low-cost data collection and processing method in order to establish a rating curve based on a three dimensional hydraulic modelling approach. One of the main processing methods is Large-Scale Particle Image Velocimetry (LSPIV). LSPIV is a computer based technique that computes flow velocities at the river surface based on video images. Hence, with the development of such a model a more physically based stage-discharge relationship can be determined based on non-intrusive measurements, meaning that measurements can be taken during safe (low flow) conditions in a restricted amount of time. Furthermore, due to the sole use of relatively simple methods and the limited amount of observations needed, this method is particularly suitable for remote and low resource settings. The study is based on data collected during a two month field trip at the Luangwa river in Zambia. The dataset consists of point clouds collected with the aid of photogrammetry, sonar and RTK GPS which are used to create a bathymetric chart, videos recorded with a drone for the computation of the surface flow velocities, surface flow velocities measured with a current meter for LSPIV validation and discharges measured with an ADCP. The bathymetric chart is used as bed level for the three dimensional discharge model created with Delf3D D-Flow FM which is calibrated with the surface flowvelocities (LSPIV) and ADCP discharge measurements. The discharge model represents approximately 9.2 kilometres of the Luangwa river in length and can reach a maximum width of about 390 metres. The model is calibrated at a discharge of 191 m3/s by minimising the difference between measured and simulated values of ten surface flow velocities and five water levels. This resulted eventually in a Manning friction coefficient of푛= 0.014 s/m1/3. The calibrated model resembles the actual river in location, depth, width and surface flow velocity. The LSPIV velocities are approached to a mean average deviation of 0.07 m/s (1.1 m/s average) and the water level deviates 0.06 m at the research area (1.3 m average). The model is used to establish a stage-discharge relationship which is subsequently compared to two existing relationships, one based on a similar approach using a 1D model and one based on stage-discharge data measured at a conventional gauging station. The three stage-discharge relationships are in the same order of magnitude although the geometry of the river at all sites is likely to be different. Since a stage-discharge relationship is heavily dependent on the geometry [66] this comparison is only a rough indication of the accuracy. Ideally, the discharge, water level, and surface flow velocity should be measured for different discharges and compared (using the model) to the established relationship. The stage-discharge relationship could, if needed, be adjusted based on the new measurements.