scholarly journals A novel permanent gauge-cam station for surface flow observations on the Tiber river

2016 ◽  
Author(s):  
Flavia Tauro ◽  
Andrea Petroselli ◽  
Maurizio Porfiri ◽  
Lorenzo Giandomenico ◽  
Guido Bernardi ◽  
...  
Keyword(s):  
Flow Velocity ◽  
Large Scale ◽  
Surface Flow ◽  
Video Data ◽  
Engineering Practice ◽  
Surface Hydrology ◽  
Flow Monitoring ◽  
Tiber River ◽  
Scale Particle ◽  
Local Water

Abstract. Flow monitoring of riverine environments is crucial for hydrology and hydraulic engineering practice. Besides few experimental implementations, flow gauging relies on local water level and surface flow velocity measurements through ultrasonic meters and radars. In this paper, we describe a novel permanent gauge-cam station for large scale and continuous observation of surface flows, based on remote acquisition and calibration of video data. Located on the Tiber river, in the center of Rome, Italy, the station captures one-minute videos every 10 min over an area oriented along the river cross-section of up to 20.6 × 15.5 m2. In a feasibility study, we demonstrate that accurate surface flow velocity estimations can be obtained by analyzing experimental images via particle tracking velocimetry (PTV). In medium illumination conditions (70–75 lux), PTV leads to velocity estimations in close agreement with radar records and is less affected by uneven lighting than large scale particle image velocimetry. Future efforts will be devoted to the development of a comprehensive testbed infrastructure for investigating the potential of multiple optics-based approaches for surface hydrology.

scholarly journals A novel permanent gauge-cam station for surface-flow observations on the Tiber River

2016 ◽  
Vol 5 (1) ◽  
pp. 241-251 ◽  
Author(s):  
Flavia Tauro ◽  
Andrea Petroselli ◽  
Maurizio Porfiri ◽  
Lorenzo Giandomenico ◽  
Guido Bernardi ◽  
...  
Keyword(s):  
Flow Velocity ◽  
Large Scale ◽  
Surface Flow ◽  
Video Data ◽  
Engineering Practice ◽  
Test Bed ◽  
Surface Hydrology ◽  
Flow Monitoring ◽  
Tiber River ◽  
Scale Particle

Abstract. Flow monitoring of riverine environments is crucial for hydrology and hydraulic engineering practice. Besides few experimental implementations, flow gauging relies on local water level and surface-flow velocity measurements through ultrasonic meters and radars. In this paper, we describe a novel permanent gauge-cam station for large-scale and continuous observation of surface flows, based on remote acquisition and calibration of video data. Located on the Tiber River, in the center of Rome, Italy, the station captures 1 min videos every 10 min over an area oriented along the river cross section of up to 20.6  ×  15.5 m2. In a feasibility study, we demonstrate that accurate surface-flow velocity estimations can be obtained by analyzing experimental images via particle tracking velocimetry (PTV). In medium illumination conditions (70–75 lux), PTV leads to velocity estimations in close agreement with radar records and is less affected by uneven lighting than large-scale particle image velocimetry. Future efforts will be devoted to the development of a comprehensive test bed infrastructure for investigating the potential of multiple optics-based approaches for surface hydrology.

Development and Testing of an Unmanned Aerial Vehicle for Large Scale Particle Image Velocimetry

2014 ◽  
Author(s):  
Christopher Pagano ◽  
Flavia Tauro ◽  
Salvatore Grimaldi ◽  
Maurizio Porfiri
Keyword(s):  
Particle Image Velocimetry ◽  
Large Scale ◽  
Field Experiments ◽  
Particle Image ◽  
Low Cost ◽  
Surface Flow ◽  
Natural Environments ◽  
Natural Stream ◽  
Image Velocimetry ◽  
Scale Particle

Large scale particle image velocimetry (LSPIV) is a nonintrusive environmental monitoring methodology that allows for continuous characterization of surface flows in natural catchments. Despite its promise, the implementation of LSPIV in natural environments is limited to areas accessible to human operators. In this work, we propose a novel experimental configuration that allows for unsupervised LSPIV over large water bodies. Specifically, we design, develop, and characterize a lightweight, low cost, and stable quadricopter hosting a digital acquisition system. An active gimbal maintains the camera lens orthogonal to the water surface, thus preventing severe image distortions. Field experiments are performed to characterize the vehicle and assess the feasibility of the approach. We demonstrate that the quadricopter can hover above an area of 1×1m2 for 4–5 minutes with a payload of 500g. Further, LSPIV measurements on a natural stream confirm that the methodology can be reliably used for surface flow studies.

scholarly journals Real-Time Measurement of Flash-Flood in a Wadi Area by LSPIV and STIV

Hydrology ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. 27 ◽  
Author(s):  
Mahmood Al-mamari ◽  
Sameh Kantoush ◽  
Sohei Kobayashi ◽  
Tetsuya Sumi ◽  
Mohamed Saber
Keyword(s):  
Large Scale ◽  
Flash Flood ◽  
Early Warning Systems ◽  
Flash Floods ◽  
Surface Flow ◽  
Unidirectional Flow ◽  
Real Time Measurement ◽  
Positive Performance ◽  
Image Velocimetry ◽  
Scale Particle

Flash floods in wadi systems discharge large volumes of water to either the sea or the desert areas after high-intensity rainfall events. Recently, wadi flash floods have frequently occurred in arid regions and caused damage to roads, houses, and properties. Therefore, monitoring and quantifying these events by accurately measuring wadi discharge has become important for the installation of mitigation structures and early warning systems. In this study, image-based methods were used to measure surface flow velocities during a wadi flash flood in 2018 to test the usefulness of large-scale particle image velocimetry (LSPIV) and space–time image velocimetry (STIV) techniques for the estimation of wadi discharge. The results, which indicated the positive performance of the image-based methods, strengthened our hypothesis that the application of LSPIV and STIV techniques is appropriate for the analysis of wadi flash flood velocities. STIV is suitable for unidirectional flow velocity and LSPIV is reliable and stable for two-dimensional measurement along the wadi channel, the direction of flow pattern which varies with time.

scholarly journals Spatial distribution of tracers for optical sensing of stream surface flow

2020 ◽  
Author(s):  
Alonso Pizarro ◽  
Silvano F. Dal Sasso ◽  
Matthew Perks ◽  
Salvatore Manfreda
Keyword(s):  
Large Scale ◽  
Optical Sensing ◽  
Surface Flow ◽  
Seeding Density ◽  
Stream Surface ◽  
Image Velocimetry ◽  
Level Of Aggregation ◽  
Scale Particle ◽  
The One

Abstract. River monitoring is of particular interest for our society that is facing increasing complexity in water management. Emerging technologies have contributed to opening new avenues for improving our monitoring capabilities, but also generating new challenges for the harmonised use of devices and algorithms. In this context, optical sensing techniques for stream surface flow velocities are strongly influenced by tracer characteristics such as seeding density and level of aggregation. Therefore, a requirement is the identification of how these properties affect the accuracy of such methods. To this aim, numerical simulations were performed to consider different levels of particle aggregation, particle colour (in terms of greyscale intensity), seeding density, and background noise. Two widely used image-velocimetry algorithms were adopted: i) Particle Tracking Velocimetry (PTV), and ii) Large-Scale Particle Image Velocimetry (LSPIV). A descriptor of the seeding characteristics (based on density and aggregation) was introduced based on a newly developed metric π. This value can be approximated and used in practice as π = ν0.1 / (ρ / ρcν1) where ν, ρ, and ρcν1 are the aggregation level, the seeding density, and the converging seeding density at ν = 1, respectively. A reduction of image-velocimetry errors was systematically observed by decreasing the values of π; and therefore, the optimal frame window was defined as the one that minimises π. In addition to numerical analyses, the Basento field case study (located in southern Italy) was considered as a proof-of-concept of the proposed framework. Field results corroborated numerical findings, and an error reduction of about 15.9 and 16.1 % was calculated – using PTV and PIV, respectively – by employing the optimal frame window.

Image-velocimetry techniques under particle aggregation for streamflow monitoring: a numerical approach

2020 ◽  
Author(s):  
Alonso Pizarro ◽  
Silvano Fortunato Dal Sasso ◽  
Salvatore Manfreda
Keyword(s):  
Large Scale ◽  
Ad Hoc ◽  
Numerical Approach ◽  
Surface Flow ◽  
Particle Aggregation ◽  
Seeding Density ◽  
Stream Flows ◽  
Flow Monitoring ◽  
Time Flow ◽  
Image Velocimetry

<p>Monitoring extreme events with high accuracy and consistency is still a challenge, even by using up-to-date approaches. On the one side, field campaigns are in general expensive and time-consuming, requiring the presence of high-qualified personnel and forward planning. On the other side, non-contact approaches (such as image velocimetry, radars, and microwave systems) have had promising signs of progress in recent years, making now possible real-time flow monitoring. This work focuses on the estimation of surface flow velocities for streamflow monitoring under particle aggregation, in which tracers are not necessarily uniformly distributed across the entire field of view. This issue is extremely relevant for the computing stream flows since velocity errors are transmitted to river discharge estimations. Ad-hoc numerical simulations were performed to consider different levels of particle aggregation, particle colour and shapes, seeding density, and background noise. Particle Tracking Velocimetry (PTV) and Large-Scale Particle Image Velocimetry (LSPIV) were used for image velocimetry estimations due to their widely used worldwide. Comparisons between the theoretical and computed velocities were carried out to determine the associated uncertainty and optimal experimental setup that minimises those errors.</p>

scholarly journals Surface flows from images: ten days of observations from the Tiber River gauge-cam station

2016 ◽  
Vol 48 (3) ◽  
pp. 646-655 ◽  
Author(s):  
Flavia Tauro ◽  
Simone Salvatori
Keyword(s):  
Video Processing ◽  
Particle Tracking Velocimetry ◽  
Radar Data ◽  
Surface Flow ◽  
Optical Methods ◽  
Flow Measurements ◽  
Flow Monitoring ◽  
Tiber River ◽  
Discharge Regime ◽  
Angle Of View

Fully remote surface flow measurements are crucial for flow monitoring during floods and in difficult-to-access areas. Recently, optics-based surface flow monitoring has been enabled through a permanent gauge-cam station on the Tiber River, Rome, Italy. Therein, a system of lasers and an internet protocol camera equipped with two optical modules afford video acquisitions of the river surface every 10 minutes. In this work, we establish a standard video-processing protocol by analyzing more than 10 Gb of footage data captured during low discharge regime from May 2nd to 11th, 2015, through particle tracking velocimetry (PTV). We show that good image-based velocity data can be obtained throughout the day – from 6 am to 8 pm – despite the challenging experimental settings (direct sunlight illumination, mirror-like river surface, and overlying bridge shadow). Further, we demonstrate that images captured with a 27° angle of view optical sensor lead to average velocity measurements in agreement with available radar data. Consistent with similar optical methods, PTV is not applicable in case of adverse illumination and at night; however, it is more robust for dishomogeneous distributions of floaters in the field of view.

scholarly journals Drone-Based Optical Measurements of Heterogeneous Surface Velocity Fields around Fish Passages at Hydropower Dams

2020 ◽  
Vol 12 (3) ◽  
pp. 384 ◽  
Author(s):  
Dariia Strelnikova ◽  
Gernot Paulus ◽  
Sabine Käfer ◽  
Karl-Heinrich Anders ◽  
Peter Mayr ◽  
...  
Keyword(s):  
Large Scale ◽  
Flow Direction ◽  
Ecological Impact ◽  
Fish Passage ◽  
Optical Measurements ◽  
Surface Velocity ◽  
Flow Conditions ◽  
Flow Monitoring ◽  
Hydropower Plants ◽  
Scale Particle

In Austria, more than a half of all electricity is produced with the help of hydropower plants. To reduce their ecological impact, dams are being equipped with fish passages that support connectivity of habitats of riverine fish species, contributing to hydropower sustainability. The efficiency of fish passages is being constantly monitored and improved. Since the likelihood of fish passages to be discovered by fish depends, inter alia, on flow conditions near their entrances, these conditions have to be monitored as well. In this study, we employ large-scale particle image velocimetry (LSPIV) in seeded flow conditions to analyse images of the area near a fish passage entrance, captured with the help of a ready-to-fly consumer drone. We apply LSPIV to short image sequences and test different LSPIV interrogation area sizes and correlation methods. The study demonstrates that LSPIV based on ensemble correlation yields velocities that are in good agreement with the reference values regarding both magnitude and flow direction. Therefore, this non-intrusive methodology has a potential to be used for flow monitoring near fish passages on a regular basis, enabling timely reaction to undesired changes in flow conditions when possible.

scholarly journals Metrics for the Quantification of Seeding Characteristics to Enhance Image Velocimetry Performance in Rivers

2020 ◽  
Vol 12 (11) ◽  
pp. 1789 ◽  
Author(s):  
Silvano Fortunato Dal Sasso ◽  
Alonso Pizarro ◽  
Salvatore Manfreda
Keyword(s):  
Water Resource Management ◽  
Large Scale ◽  
River Flow ◽  
Low Cost ◽  
A Priori ◽  
Surface Flow ◽  
Seeding Density ◽  
Unmanned Aerial Systems ◽  
Flow Monitoring ◽  
Image Velocimetry

River flow monitoring is essential for many hydraulic and hydrologic applications related to water resource management and flood forecasting. Currently, unmanned aerial systems (UASs) combined with image velocimetry techniques provide a significant low-cost alternative for hydraulic monitoring, allowing the estimation of river stream flows and surface flow velocities based on video acquisitions. The accuracy of these methods tends to be sensitive to several factors, such as the presence of floating materials (transiting onto the stream surface), challenging environmental conditions, and the choice of a proper experimental setting. In most real-world cases, the seeding density is not constant during the acquisition period, so it is not unusual for the patterns generated by tracers to have non-uniform distribution. As a consequence, these patterns are not easily identifiable and are thus not trackable, especially during floods. We aimed to quantify the accuracy of particle tracking velocimetry (PTV) and large-scale particle image velocimetry (LSPIV) techniques under different hydrological and seeding conditions using footage acquired by UASs. With this aim, three metrics were adopted to explore the relationship between seeding density, tracer characteristics, and their spatial distribution in image velocimetry accuracy. The results demonstrate that prior knowledge of seeding characteristics in the field can help with the use of these techniques, providing a priori evaluation of the quality of the frame sequence for post-processing.

scholarly journals Technical Note: Surface water velocity observations from a camera: a case study on the Tiber River

2014 ◽  
Vol 11 (10) ◽  
pp. 11883-11904 ◽  
Author(s):  
F. Tauro ◽  
G. Olivieri ◽  
A. Petroselli ◽  
M. Porfiri ◽  
S. Grimaldi
Keyword(s):  
Surface Water ◽  
Large Scale ◽  
Water Velocity ◽  
Technical Note ◽  
Surface Velocity ◽  
Video Frame ◽  
Flood Peak ◽  
Flow Monitoring ◽  
Experimental Apparatus ◽  
Tiber River

Abstract. Monitoring surface water velocity during flood events is a challenging task. Techniques based on deploying instruments in the flow are often unfeasible due to high velocity and abundant sediment transport. A low-cost and versatile technology that provides continuous and automatic observations is still not available. LSPIV (large scale particle imaging velocimetry) is a promising approach to tackle these issues. Such technique consists of developing surface water velocity maps analyzing video frame sequences recorded with a camera. In this technical brief, we implement a novel LSPIV experimental apparatus to observe a flood event in the Tiber river at a cross-section located in the center of Rome, Italy. We illustrate results from three tests performed during the hydrograph flood peak and recession limb for different illumination and weather conditions. The obtained surface velocity maps are compared to the rating curve velocity and to benchmark velocity values. Experimental findings confirm the potential of the proposed LSPIV implementation in aiding research in natural flow monitoring.

scholarly journals SURFACE FLOW VELOCITY MEASUREMENTS FROM UAV-BASED VIDEOS

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 221-226 ◽  
Author(s):  
J. Brauneck ◽  
T. Gattung ◽  
R. Jüpner
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Flow Velocity ◽  
Volumetric Flow Rate ◽  
Surface Flow ◽  
Video Data ◽  
Task Forces ◽  
Aerial Vehicles ◽  
Remotely Piloted Aircraft ◽  
The Status ◽  
Floating Objects

<p><strong>Abstract.</strong> Most measuring methods for determining the volumetric flow rate or surface flow velocity have in common that they cannot be safely used under extreme outflow conditions. Especially in catastrophic situations, it is of particular interest to determine the amount of water that flows into the hinterland as precisely as possible in order to improve hydrodynamic models. Faulty assumptions lead to misleading calculations and may result in preventable casualties. As technical improvements throughout the last decade facilitated the widespread utilization of unmanned aerial vehicles (UAV) or remotely piloted aircraft systems (RPAS), these systems are now capable to collect and transmit precise information from remote areas to task forces immediately. The usage of a UAV is possible with minimal preparation at almost every place and is suitable for improving the database for a quick assessment of the status during a catastrophic event.</p><p>In this work, the determination of surface flow velocity using unmanned aerial vehicles (UAV) and floating optical tracers is evaluated. It is also discussed, to what extent numerical methods are able to efficiently undistort and correct this data. Precision analysis of video data from field investigations was performed with R using three different approaches that calculated the true velocity of the floating objects. The results indicate similar degrees of precision for both advanced methods but calculating an ortho-corrected video is a timeconsuming process not suitable for nearly real-time applications.</p>

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