HS1.1.2

Salt Dilution flow measurement is relatively accurate and easy way to measure flow in turbulent waterways.  However, it’s accuracy and precision are governed by the Signal to Noise (SNR) Ratio, which can be very low in urban, sub-urban, and rural waterways due to a highly variable BackGround specific Electrical Conductivity (BG ECT) signal.  Conventionally, more salt is added to the waterway to overcome the noise in the BG ECT.  The “noise” is a combination of random noise, which is amplified by the typically high BGECT (>500 uS/cm), but also lower frequency noise that changes on the same time scale as the salt breakthrough curve.  To compensate for the changing BG ECT, we have employed a 3^rd UpStream (U/S) probe to track the BG ECT, along with algorithms to transform the signal in 3 domains: magnitude (ECT offset), time (transit time of pulse), and frequency (to compensate for storage in the waterway).  Additionally, we have tested the use of a 3^rd DownStream (D/S) probe to measure cross-channel variance when mixing is not complete in order to achieve a reasonable flow estimate.  Results are compared and discussed.

How to cite: Sentlinger, G.: The use of a 3rd U/S or D/S sensor in Salt Dilution Flow Measurements, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1558, https://doi.org/10.5194/egusphere-egu21-1558, 2021.

Over the past few years, smartphone devices have become so powerful that in your pocket, not only do you have a device which can communicate with people across the world, the sheer power of these devices has now also brought a new frontier in scientific measurements. In this presentation, we present our smartphone app 'flowonthego', a technology which allows users to determine flow velocities, in almost real-time, from simple video footage. The instantaneous velocity fields are calculated by solving the Lucas-Kanade solutions to the optical flow equations and tracking naturally occurring features. The app also harnesses the potential of augmented reality, making calibration reference and the need tape measures a thing of the past. Furthermore, the app also packs an arsenal of post-processing tools in which users can understand basic statistics. From preliminary our studies we have found 'flowonthego' is able to match the statistics of commonly used ADCP's while also providing instantaneous full vector fields allowing users to better understand dynamical processing. 

How to cite: Higham, J. and Plater, A.: `Flowonthego' - flow tracking technology on your smartphone, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5902, https://doi.org/10.5194/egusphere-egu21-5902, 2021.

The strict lockdown imposed by the Covid-19 health crisis motivated the French-speaking hydrometry network Groupe Doppler Hydrométrie (GDH) to organise a new type of hydrometric intercomparison, based on video gauging. Between 15 April and 10 May 2020, the Video Globe Challenge 2020 was run in 8 stages corresponding to 8 videos taken from the ground (5 cases) or from a drone (3 cases), each coming with a reference discharge measurement (6 ADCP gauging, 1 dilution gauging, 1 calibration curve). These eight cases present various flows, measurement conditions and operating difficulties. The data were provided by EDF, DREAL Auvergne-Rhône-Alpes, NVE (Norway) and DNRME Queensland (Mark Randall, Australia).

For each stage, around 25 competitors participated by submitting their discharge result, their surface velocity coefficient (a.k.a alpha) estimate and their parameters, with the hope of getting as close as possible to the reference discharge. Several velocimetry techniques and software tools were used: from visual spotting and manual processing, in Flowsnap (Tenevia), Excel or Barème, to specialised software, mainly Fudaa-LSPIV (EDF/INRAE) but also SSIVSuite (Photrack), PIVlab, and Opyf (EPFL/INRIA, local optical flow). The general classification (smaller sum of percentage deviations to discharge references), points classification (smaller sum of ranks), sniper classification (best visual velocimetry) and young rider classification (for students) awarded the yellow, green, polka dot and white jerseys, respectively.

The Challenge 2020 has been rich in lessons, notably by illustrating several important sources of error for video gauging and the possible parries that the user can deploy (or not...). The exercise was as useful for training and coaching the participants (often beginners) as it was for identifying the improvements to be expected in procedures and software. The results highlight some operator-related error sources which need to be minimized by developing more guided or automated parameter settings, and more robust velocimetry algorithms. They also illustrate the typical uncertainty levels of such measurements.

The cultural aspects were not left out, revealing historical facts and hydrometry-related feats about the rivers visited, e.g. Julius Caesar wading the river to join the druids in the sanctuary of Seranos, Viking Stør Åne the Blue breaking the ice cover to prevent rating shift, or Sir Herbert inventor of the anti-crocodile waders. The official history of hydrometry conceals many unsuspected mysteries that have yet to be revealed...

How to cite: Le Coz, J., Hauet, A., and Despax, A.: The Video Globe Challenge 2020, a video streamgauging race during the Covid-19 lockdown, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2116, https://doi.org/10.5194/egusphere-egu21-2116, 2021.

When two mega rivers merge the mixing of two flows results in a highly complex three-dimensional flow structure in an area known as the confluence hydrodynamic zone. In the confluence zone, substantial changes occur to the hydrodynamic and morphodynamic features which are of significant interest for researchers. The confluence of the Negro and Solimões Rivers, as one of the largest river junctions on Earth, is the study area of the present research. During the EU-funded Project “Clim-Amazon” (2011-2015), velocity data were collected using an ADCP vessel operating under high and low flow conditions in different locations at that confluence (Gualtieri et al., 2019). By applying the Entropy theory developed by Chiu (1988) for natural channels and simplified by Moramarco et al. (2014), the two-dimensional velocity distribution, as well as depth-averaged velocity, were calculated at the different transects along the confluence zone, using only the surface velocities observation. The estimated data yielded 6.6% and 6.9% error percentage for the discharge data related to high and low flow conditions, respectively, and 8.4% and 8.3% error percentage for the velocity data related to high and low flow conditions, respectively. Regardless of the flow condition, these preliminary results also suggest the potential points at the confluence zone for the maximum local scouring. The findings of the current research highlighted the potential of Entropy theory to estimate the flow characteristics at the large river’s confluence, just starting from the measure of surface velocities. This is of considerable interest for monitoring high flows using no-contact technology, when ADCP or other contact equipment cannot be used for the safety of operators and risks for equipment loss.

Keywords: Amazon River, Negro/Solimões Confluence, Entropy Theory, Velocity Distribution, Local Scouring

References

Gualtieri, C., Ianniruberto, M., Filizola, N. (2019). On the mixing of rivers with a difference in density: the case of the Negro/Solimões confluence, Brazil. Journal of Hydrology, 578(11), November 2019, 124029,

Chiu, C. L. (1988). “Entropy and 2-D velocity distribution in open channels”. Journal of Hydrologic Engineering, ASCE, 114(7), 738-756

Moramarco, T., Saltalippi, C., Singh, V.P. (2004). “Estimation of mean velocity in natural channels based on Chiu’s velocity distribution equation”. Journal of Hydrologic Engineering, ASCE, 9 (1), pp. 42-50

How to cite: Bahmanpouri, F., Barbetta, S., Gualtieri, C., Ianniruberto, M., Filizola, N., Termini, D., and Moramarco, T.: Estimating the hydrodynamic and morphodynamic characteristics using Entropy theory at the confluence of Negro and Solimões Rivers, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10330, https://doi.org/10.5194/egusphere-egu21-10330, 2021.

Floods are natural inundations affecting rivers, lakes, coasts and the open sea. Due to anthropogenic impacts those floods can be modified with pollutants. The pollutants are then transported or dislocated during flood events and can then harm humans and life, society and other. The main objective of the project is to understand the complex and non‐linear processes, effects and long‐term impacts of “Toxic Floods” including the various influences of changing natural and anthropogenic boundary conditions from past to future.

As water/environmental engineers we aim to understand flood-related dispersion of contaminants and contaminated sediment. Therefore, we have a deep look at processes concerning sediment transport, fate and load during flood events. In a further step, it is aimed to describe and quantify the anthropogenic impact in floodplains and medium size river catchments. This knowledge will help to simulate toxic floods and define different scenarios and their effect on the environment.

In collaboration with an interdisciplinary team we can synthesize all outcomes and will be able to develop e.g. smart flood monitoring plans.[CB1] 

How to cite: Brüll, C., Schüttrumpf, H., and Hollert, H.: Understanding Toxic Floods - Develop monitoring strategies for affected areas, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7513, https://doi.org/10.5194/egusphere-egu21-7513, 2021.

The world has entered an era of immense water-related threats due to climate warming and human actions.  Changing precipitation patterns, reducing snowpack, accelerating glacial melt, intensifying floods and droughts have made the need for timely hydrometric information indispensable. Climate change thus introduced requirements for adaptive management and timely water resource information at the municipal, regional and national levels. Over the last 10 years, it became evident that demands from users had moved towards best available hydrometric data in near real-time.  As with most hydrometric services around the world, the WSC was a legacy and archive-driven organization that published approved data on an annual basis.  Real-time data was an after-thought simply equated with the application of rating curves onto telemetry water levels, while hydrographers remained focused on approving data months after the facts. To address this challenge, the Meteorological Service of Canada‘s National Hydrological Services, and specifically the Water Survey of Canada (WSC) has developed a near real-time continuous data production system to meet the evolving needs of stakeholders.  To meet this challenge, WSC developed solutions where data would be improved as field-measurements were being acquired. Corrections to data and rating curves are applied within hours of field discharge measurements, allowing for near-real time publication of corrected discharge information.  Moreover, station conditions and performance are constantly monitored with “eyes-on-data” production tools that allow the program to optimize its field visits, costs and data publication. These tools were developed in-house to enable effective network time-management while communicating important information with partner agencies.  This was made possible with a cloud-based hydrometric data production system and modern telecommunications tools.  As a result of this work, the improved near real-time data became the catalyst to revamp a multi-decade approach to final data approval. This improved overall efficiency and is now leading to less delays in the approved data production cycle.  This paper describes the design and implementation of the continuous data production system adopted at WSC and highlights some of the benefits noted since program implementation. This paper also identifies future investments that could help the sustainability of this new system in the long term.

How to cite: Rainville, F., Pietroniro, A., Bouchard, A., Brown, A., and Stiff, D.: A Continuous Data Production Approach to Flow Estimation in Canada, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8897, https://doi.org/10.5194/egusphere-egu21-8897, 2021.

Urbanization is the dominant force shaping social, economic, and environmental life in the 21 century. Urban areas will become essential to achieve the Sustainable Development Goals (SDGs) established by the United Nations in their 2030 Agenda. Local governments must identify the vulnerable ecosystems to make cities inclusive, safe, and resilient (SDG 11). In Latin America, urban rivers are vulnerable ecosystems, negatively impacted by rapid urbanization. Furthermore, detailed geospatial information of urban rivers is not updated frequently, therefore available data doesn’t reflect changes occurring due to rapid urban development processes affecting the quality of water, sediments, or vegetation health. This research uses a GIS-based multicriteria decision analysis (GIS-MCDA) for the environmental assessment of the Pesqueria River as a decision tool to facilitate mitigation focused strategies. The developed method has used the pixel to pixel data from socio-economical, environmental, topographical, geological, and hydrological factors affecting the environmental health of urban rivers. Census data, geological formation or soil type were obtained from official information; reflectance indices and vegetation height were obtained using aerial photogrammetry with near-infrared and red bands; terrain and hydrological analysis used digital elevation models derived from LIDAR; land cover was created using a SENTINEL 2 image; and water quality data was obtained from field sampled raised and analyzed with traditional laboratory analysis of Chemical Oxygen Demand and validated also with official data. Results implied the generation of the thematic maps with ranges from 1 (very low quality) to 5 (very high quality) according to the environmental quality assessment. For the GIS-MCDA, the values of each map were converted to the same scale, each criterion was weighted in function of its importance according to the literature review and the objective of this research, and there were aggregated by the way of a lineal combination. The result is a map that shows the level of mitigation or conservation priority along the river. This map can offer information to the stakeholders in a relatively short time and accelerate the actions aimed to protect the quality of this important urban ecosystem. 

How to cite: Mireles Soria, D. L., Yépez Rincón, F. D., Ramírez Serrato, N. L., Ortiz Martínez, M. G., Ferriño Fierro, A. L., and Guerra Cobián, V. H.: GIS-based multicriteria decision analysis for the environmental assessment of the Pesqueria River in Northeast Mexico, using UAS and multi-spectral imagery, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10378, https://doi.org/10.5194/egusphere-egu21-10378, 2021.

The development of Airborne Infrared Thermal sensing (TIR) is an example of how technological advancements and the field that they focus on have fostered one another. The pace at which global change is occurring has fed the demand for better understanding of the thermal behaviour of rivers. In turn, the improvement of remote sensing and data processing techniques has provided researchers and managers with new tools to apprehend such aspects at ever larger scales. Still, recent studies have mostly focussed on rivers showing little human alteration, with a particular interest on groundwater–surface water interactions. Lowland streams are scarcely considered when it comes to the study of temperature despite their widespread occurrence, their relatively high degree of disturbance and the risks that they face in the light of temperature rising following climate change. Some of these streams already display critically high maximum summer temperatures and their state is likely to worsen in the future, putting all compartments of biota at risk.

The aims of this project were twofold. We first tested the applicability of airborne TIR to study lowland, slow-flowing stream reaches draining agricultural catchments, some of which being particularly narrow and sinuous. We then sought to understand the role of different environmental factors, observed in such context, on driving river temperature during the warmest days of the year. A number of anthropogenic actions such as clear-cutting of riparian trees, stream rectification and the construction of weirs are likely to influence the longitudinal temperature profile of such streams. By choosing rivers with no or limited groundwater inputs, we were able to quantify the relative role of each of the three tested factors and identify stream sections showing critically high maximum temperature over the summer.

A final step was proposed to upscale these results in order to identify sections of streams showing high risks of reaching critically high summer temperature at a regional network scale. To do so, we used a combination of high resolution land-cover data, digital elevation models and other existing databases (e.g. national inventory of weirs). Identification of the risks in relation with the relative contribution of the different factors is key to process-based river management. This type of output is valuable to river basin managers and decision makers as it can be used to implement targeted restoration initiatives or remediation actions in areas where these have higher chances of being effective.

How to cite: Marteau, B., Chandesris, A., Cernesson, F., Michel, K., Vaudor, L., and Piégay, H.: Riverscape-scale airborne TIR assessment of weirs and riparian cover effects on lowland river temperature, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7134, https://doi.org/10.5194/egusphere-egu21-7134, 2021.

We present a velocimetry method, which we refer to as Infrared Quantitative Velocimetry (IR-QIV), that uses images of thermal patterns, captured in the infrared, on the surface of rivers or other water bodies, to calculate the time-resolved instantaneous two-dimensional surface velocity field. The method works in all natural light conditions (day or night), and under most weather conditions, by tracking thermal patterns in the surface of the water, and is therefore suitable for a large range of flows and environments. The method, is a form of remote sensing and has significant advantages over traditional (visible-light) PIV (Particle Image Velocimetry) or LSPIV (Large Scale PIV) methods for non-contact measurement of water surface velocity field, as it requires no particle 'seeding' or contact with the water. 

Measurements of instantaneous water flow velocity, from which turbulence metrics are calculated, are important for advancing the understanding of river hydrodynamics beyond fundamentals such as discharge and mean velocity. However, most velocity measurement methods used in the field are capable of measuring at a point, or along a transect, but not over a two-dimensional area. Additionally, tools such as ADCPs generally require temporal and spatial averaging, and therefore can not resolve instantaneous velocities.

Image-based velocimetry methods, including IR-QIV and LSPIV, measure at the surface of the water and over a large area. However, methods that utilize visible-light imagery, such as LSPIV, require external illumination at night, and are challenged by the relatively homogeneous appearance of the water surface, often requiring either naturally occurring, or added 'seeding' particles, that are advected by the flow. Due the intermittent availability of seeding or surface texture, spatial or temporal averaging is often required, limiting the technique to mean velocity measurements.

These limitations do not apply to IR-QIV since under natural conditions a rich texture of temperature differences exist at the surface of the water due to spatially heterogeneous air/water heat exchange. IR-QIV is capable of calculating the instantaneous velocity at high accuracy and resolution, in space and time (centimeter scale, several Hz), over large areas—up to thousands of square meters. The instantaneous velocity measurements can be used to calculate metrics of turbulence to inform applications such as the study of river and other surface water dynamics; small-scale hydrodynamics near flow features such as water diversions, junctions, obstacles, and river bends; fishery management; gas transfer measurement; non-contact estimation of bathymetry, discharge and bed stress, and more.

We present instantaneous velocity and turbulence metrics measured at sites in the Sacramento River, (California, USA,) made using IR-QIV. Additionally, we discuss issues related to uncertainty analysis in velocimetry techniques using oblique camera viewing angles, and pattern tracking in images containing gradients of intensity (not discrete particles), as well as effects of camera noise. These considerations are relevant to all types of large scale image-based velocimetry, regardless of wavelength of image collection (visible-light or IR), and can be used to inform and improve measurements from both fixed and mobile platforms such, as UASs.

How to cite: Schweitzer, S. and Cowen, E.: Large-Scale, Accurate, High Resolution, Measurements of River Surface Velocity and Turbulence Metrics Using Thermal Infrared Images, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13623, https://doi.org/10.5194/egusphere-egu21-13623, 2021.

Streamflow measurement is of great importance in hydrological research, water management and water infrastructure design. Traditional measurement methods typically employ intrusive techniques, and under certain conditions, obtaining accurate streamflow data with these techniques can be challenging because of safety concerns, especially in some critical circumstances, such as during flood flows. The advent of new instrumentation and technologies, and in particular advances in digital imagery, has led to the emergence of non-intrusive novel image-based technologies that can be used to estimate surface velocity, which in turn can be used to estimate streamflow. Image based technologies, most of which are based on correlation between consecutive images, have the potential for remote and on demand measurements and can provide data when the application of other traditional methods are not possible, reliable or safe. In this study, we present a novel machine learning based optical flow algorithm for streamflow surface velocimetry estimation. The developed algorithm is tested in different flow conditions and using drone and fixed photogrammetry. This method appears to outperform all the other available image-based surface velocimetry approaches (i.e. correlation based and classical optical flow methods). Moreover, this method requires the least user involvement for velocity estimation and thus reduces the impact or arbitrary choices linked to user expertise.

How to cite: Ansari, S., Rennie, C. D., Jamieson, E. C., Seidou, O., and Clark, S. P.: Machine Learning Based Surface Velocimetry, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9825, https://doi.org/10.5194/egusphere-egu21-9825, 2021.

Unmanned Aerial Vehicles (UAV) have become a commonly used measurement tool in geomorphology due to their affordable cost, flexibility, and ease of use. They are regularly used in fluvial geomorphology, among other fields, because the high spatiotemporal resolution of UAV data makes it possible to assess the continuum rather than relying on single samples.

In this study, UAV data are used to hydro-morphologically describe three different river reaches of lengths between 150 and 1000 m. Specifically, the surface flow velocity and bathymetry of the rivers were reconstructed. The flow velocities were calculated using the Particle Tracking Velocimetry (PTV) method applied to UAV video sequences. In addition, UAV-based imagery was acquired to perform 3D reconstruction above and below the water surface using SfM (Structure from Motion) photogrammetry, taking into account refraction effects as well as frame processing to increase the visibility of underwater features. Reference data for flow velocities were generated at selected positions using current meters as well as ADCP (Acoustic Doppler Current Profiler) readings. The image-based calculated bathymetry was compared with RTK-GNSS sampling depth measurements and also ADCP data.

The developed workflow enables rapid and regular measurement of hydrological and morphological data of river channels. This ultimately enables multi-temporal assessment and significantly improves hydro-morphodynamic modelling, in particular their calibration.

How to cite: Eltner, A., Bertalan, L., and Lotsari, E.: Hydromorphological monitoring of individual river reaches with UAV-data – image-based measurement of bathymetry and flow velocity, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14276, https://doi.org/10.5194/egusphere-egu21-14276, 2021.