scholarly journals Implementing a hydrodynamic model to complement water depth and flow velocity data for physical scale experiments of rivers and estuaries

2020 ◽  
Author(s):  
Steven A. H. Weisscher ◽  
Marcio Boechat-Albernaz ◽  
Jasper R. F. W. Leuven ◽  
Wout M. Van Dijk ◽  
Yasuyuki Shimizu ◽  
...  
Keyword(s):  
Flow Velocity ◽  
Water Depth ◽  
Hydrodynamic Model ◽  
Tidal Flow ◽  
Measured Data ◽  
Post Processing ◽  
Model Flow ◽  
Digital Elevation ◽  
Physical Scale ◽  
Spatio Temporal

Abstract. Physical scale experiments enhance our understanding of fluvial, tidal and coastal processes. However, it has proven challenging to acquire accurate and continuous data on water depth and flow velocity due to limitations of the measuring equipment and necessary simplifications during post-processing. A novel means to augment measurements is to numerically model flow over the experimental digital elevation models. We investigated to what extent the numerical hydrodynamic model Nays2D can reproduce unsteady, nonuniform shallow flow in scale experiments and under which conditions a model is preferred to measurements. To this end, we tested Nays2D for one tidal and two fluvial scale experiments and extended Nays2D to allow for flume tilting which is necessary to steer tidal flow. The modelled water depth and flow velocity closely resembled the measured data for locations where the quality of the measured data was most reliable, and model results may be improved by applying a spatially variable roughness. The implication of the experimental data-model integration is that conducting experiments requires fewer measurements and less post-processing in a simple, affordable and labour-inexpensive manner that results in continuous spatio-temporal data of better overall quality. Also, this integration will aid experimental design.

scholarly journals Complementing scale experiments of rivers and estuaries with numerically modelled hydrodynamics

2020 ◽  
Vol 8 (4) ◽  
pp. 955-972
Author(s):  
Steven A. H. Weisscher ◽  
Marcio Boechat-Albernaz ◽  
Jasper R. F. W. Leuven ◽  
Wout M. Van Dijk ◽  
Yasuyuki Shimizu ◽  
...  
Keyword(s):  
Flow Velocity ◽  
Water Depth ◽  
Tidal Flow ◽  
Measured Data ◽  
Post Processing ◽  
Model Flow ◽  
Digital Elevation ◽  
Physical Scale ◽  
Spatio Temporal ◽  
Spatially Varying

Abstract. Physical scale experiments enhance our understanding of fluvial, tidal and coastal processes. However, it has proven challenging to acquire accurate and continuous data on water depth and flow velocity due to limitations of the measuring equipment and necessary simplifications during post-processing. A novel means to augment measurements is to numerically model flow over the experimental digital elevation models. We investigated to what extent the numerical hydrodynamic model Nays2D can reproduce unsteady, nonuniform shallow flow in scale experiments and under which conditions a model is preferred to measurements. To this end, we tested Nays2D for one tidal and two fluvial scale experiments and extended Nays2D to allow for flume tilting, which is necessary to steer tidal flow. The modelled water depth and flow velocity closely resembled the measured data for locations where the quality of the measured data was most reliable, and model results may be improved by applying a spatially varying roughness. The implication of the experimental data–model integration is that conducting experiments requires fewer measurements and less post-processing in a simple, affordable and labour-inexpensive manner that results in continuous spatio-temporal data of better overall quality. Also, this integration will aid experimental design.

Supplementary material to "Implementing a hydrodynamic model to complement water depth and flow velocity data for physical scale experiments of rivers and estuaries"

2020 ◽  
Author(s):  
Steven A. H. Weisscher ◽  
Marcio Boechat-Albernaz ◽  
Jasper R. F. W. Leuven ◽  
Wout M. Van Dijk ◽  
Yasuyuki Shimizu ◽  
...  
Keyword(s):  
Flow Velocity ◽  
Water Depth ◽  
Hydrodynamic Model ◽  
Velocity Data ◽  
Physical Scale ◽  
Supplementary Material

scholarly journals Evolution Mechanism of Meandering River Downstream Gigantic Hydraulic Project I: Hydrodynamic Models and Verification

2018 ◽  
Vol 2018 ◽  
pp. 1-21
Author(s):  
Linshuang Liu ◽  
Haiqing Zhu ◽  
Chengtao Huang ◽  
Li Zheng
Keyword(s):  
Numerical Model ◽  
Flow Velocity ◽  
Hydrodynamic Model ◽  
3D Model ◽  
Measured Data ◽  
Evolution Mechanism ◽  
Meandering River ◽  
Water And Sediment ◽  
Evolution Behavior ◽  
2D Model

The evolution mechanism of meandering river is one of essential references to predict the evolution disciplines of meandering river. Jingjiang curved reaches are the typical meandering river; more specifically, they are located downstream the gigantic hydraulic project named Three Gorge Project (TGP). Because the incoming water and sediment condition have been changed by the gigantic project, the evolution behavior of Jingjiang curved reaches changes a lot, making the evolution behavior unpredictable. However, traditional two-dimensional (2D) hydrodynamic model could not simulate the transportation characteristics of unbalanced and suspended sediment, leading the predict results of 2D model are far from the measured data. This paper presents a theoretical and numerical approach that explores the evolution mechanism of meandering river downstream gigantic hydraulic project. Firstly, the evolution behavior and evolution disciplines of Jingjiang curved reaches were classified before and after the hydraulic project implement respectively. Secondly, a 2D hydrodynamic model was set up and verified according to the measured data. And then a superior three-dimensional (3D) numerical model, whose boundary conditions were simulated by the results of the 2D numerical model, considering the unbalanced water and sediment transportation properties, was developed and verified by the measured data. Research results show that the 2D model displayed a reasonable accuracy in predicting the water level, branch diversion ratio, and flow velocity; the 3D model displayed a better accuracy in predicting the water lever, vertical flow velocity, longitudinal flow velocity, sediment concentration, and sediment variable quantity. Both 2D and 3D models could be applied to study the evolution mechanism of meandering river; especially the proposed 3D model considering the sediment transport in longitudinal, transverse, and vertical directions will improve the accuracy of behavior prediction and will help decision-making for the river regulation.

Research on the Pollution Diffusion Regularity near Sewage Outlet Areas in Yuncheng Reach of the Fen River

2011 ◽  
Vol 383-390 ◽  
pp. 2430-2436
Author(s):  
Jian Hua Hou ◽  
Min Quan Feng ◽  
Xiao Peng Xing ◽  
Zhen Hua Hou
Keyword(s):  
Water Quality ◽  
Flow Field ◽  
Water Depth ◽  
Concentration Gradient ◽  
River Flow ◽  
Measured Data ◽  
Quality Model

The purpose of this paper is to find the pollution diffusion regularity near sewage outlet area of Yuncheng reach of the Fen River. A 2-D water hydrodynamic and quality model was used to simulate flow field, the water quality and contamination dispersion. The parameters of the model were calibrated with measured data of the water depth, flow and water quality in Yuncheng reach of the Fen River. According to the simulated result, the total area of pollution belt with 19 sewage outlets is 8.89km2 in normal year. And 3.89% of the reach has a worse water quality than V class in standard. The percentage of V and Ⅳ Class of water is 69.17% and 26.94%.In dry year, the total area of pollution belt with 19 sewage outlets is 8.89km2.The percentage of inferior V, V and Ⅳ Class of water is 27.80%, 69.46% and 2.74%. It was shown by the simulated results that the concentration gradient decreases with increasing distance to the outlets and the dilution and dispersion of pollutants was enhanced by a greater river flow.

An Analysis of In-Flow Fluidelastic Instability Based on a Physical Insight

2014 ◽  
Author(s):  
Tomomichi Nakamura
Keyword(s):  
Flow Velocity ◽  
Flow Instability ◽  
Pressure Sensors ◽  
Measured Data ◽  
Critical Flow ◽  
Nonlinear Phenomenon ◽  
Critical Flow Velocity ◽  
Fluid Force ◽  
Tube Arrays ◽  
Fluidelastic Instability

Fluidelastic vibration of tube arrays caused by cross-flow has recently been highlighted by a practical event. There have been many studies on fluidelastic instability, but almost all works have been devoted to the tube-vibration in the transverse direction to the flow. For this reason, there are few data on the fluidelastic forces for the in-flow movement of the tubes, although the measured data on the stability boundary has gradually increased. The most popular method to estimate the fluidelastic force is to measure the force acting on tubes due to the flow, combined with the movement of the tubes. However, this method does not give the physical explanation of the root-cause of fluidelastic instability. In the work reported here, the in-flow instability is assumed to be a nonlinear phenomenon with a retarded or delayed action between adjacent tubes. The fluid force acting on tubes are estimated, based on the measured data in another paper for the fixed cylinders with distributed pressure sensors on the surface of the cylinders. The fluid force acting on the downstream-cylinder is assumed in this paper to have a delayed time basically based on the distance between the separation point of the upstream-cylinder to the re-attachment point, where the fluid flows with a certain flow velocity. Two models are considered: a two-cylinder and three–cylinder models, based on the same dimensions as our experimental data to check the critical flow velocity. Both models show the same order of the critical flow velocity and a similar trend for the effect of the pitch-to-diameter ratio of the tube arrays, which indicates this analysis has a potential to explain the in-flow instability if an adequate fluid force is used.

An Experimental Study of Shallow Water Wave Statistics on Mild Bed Slopes

2011 ◽  
Author(s):  
Vasiliki Katsardi ◽  
Chris Swan
Keyword(s):  
Water Depth ◽  
Measured Data ◽  
Intermediate Water ◽  
Statistical Distributions ◽  
Spectral Bandwidth ◽  
Peak Period ◽  
Wave Statistics ◽  
Wave Heights ◽  
Bed Slope ◽  
Water Depths

This paper describes a new series of laboratory observations, undertaken in a purpose built wave flume, in which a number of scaled simulations of realistic ocean spectra were allowed to evolve over a range of mild bed slopes. The purpose of the study was to examine the distribution of wave heights and its dependence on the local water depth, d, the local bed slope, m, and the nature of the input spectrum; the latter considering variations in the spectral peak period, Tp, the spectral bandwidth and the wave steepness. The results of the study show that for mild bed slopes the statistical distributions of wave heights are effectively independent of both the bed slope and the spectral bandwidth. However, the peak period plays a very significant role in the sense that it alters the effective water depth. Following detailed comparisons with the measured data, the statistical distributions for wave heights in relatively deep water are found to be in reasonable agreement with the Forristall [1] and Glukhovskii [2] distributions. For intermediate water depths, the Battjes & Groenendijk [3] distribution works very well. However, for the shallowest water depths none of the existing distributions provides good agreement with the measured data; all leading to an over-estimate of the largest wave heights.

scholarly journals Validating the vertical quality of SRTM digital elevation model of the Mirim Lagoon hydrographic basin

2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Andrea Lopes Iescheck ◽  
Patricia Andréia Paiola Scalco
Keyword(s):  
Statistical Analysis ◽  
Digital Elevation Model ◽  
Precise Point Positioning ◽  
Post Processing ◽  
Srtm Dem ◽  
Hydrographic Basin ◽  
Digital Elevation ◽  
Vertical Accuracy ◽  
Elevation Model ◽  
Srtm Data

<p><strong>Abstract.</strong> This work is part of a research project that aims at the automatic determination of knickpoints and the assessment of morphometric and hypsometric parameters of Mirim Lagoon Hydrographic Basin, using Shuttle Radar Topography Mission digital elevation model (SRTM-DEM) and spatial analyses.</p><p>The analysis of geomorphologic systems is done using computational treatment of data obtained by remote sensing, especially those obtained by SRTM. These data permit the elaboration of a topographic model for the Earth surface and provide a base for studies in several units of geomorphologic analyses (geomorphologic systems), such as hydrographic basins.</p><p>The most usual technique for derivation of relief morphologic attributes is based on digital elevation models (DEMs) and digital hydrographic nets. Computational routines are applied on those data for acquisition of the hydrography and drainage anomalies. The DEMs and the hydrographic nets must have either morphologic or hydrologic consistency to validate the results obtained in the morphometric analyses.</p><p>More specifically, this study aims at describing the method and related results regarding the validation of the vertical accuracy of SRTM-DEM through a kinematic positioning based on the Global Navigation Satellite System (GNSS), in the Mirim Lagoon Hydrographic Basin region. Mirim Lagoon Hydrographic Basin is as cross-border basin located on the Atlantic coast of South America, and covers an area of 58,407.78&amp;thinsp;km<sup>2</sup>, where 47% of this area is in Brazil and 53% in Uruguay.</p><p>Several studies deal with the validation of Digital Elevation Models (DEMs) and SRTM data using different GNSS surveying methods and receivers. The innovation of this work is the methodology developed to achieve the suitable accuracy for the control points coordinates to validate the SRTM-DEM of Mirim Lagoon Hydrographic Basin. The study used the kinematic relative positioning method with a recording rate of 1 second and without reference stations for post-processing with the precise point positioning (PPP) method. This methodology allowed covering a large area with reference stations being very far from the surveyed region and with different geodetic reference systems (two countries).</p><p>The methodology entails the GNSS data acquisition and post-processing, the transformation from geometric heights into orthometric heights, the SRTM-DEM mosaic, the extraction of homologous points in the SRTM-DEM and the statistical analyses for validating the model.</p><p>The study used a GNSS receiver of dual-frequency with recording rate of 1 second to collect a total of 275,916 points with 3D coordinates. Those points were post-processed using the PPP method with the Canadian Spatial Reference System &amp;ndash; Precise Point Positioning (CSRS-PPP), and the ellipsoidal height was converted into orthometric height through the software INTPT geoid. During this work, we used the geopotential model (EGM96) to transform height differences between two countries, Brazil and Uruguay.</p><p>In order to obtain the SRTM-DEM we used 15 SRTM images, version 3, band C, with a spatial resolution of 1 arcsecond (approximately 30&amp;thinsp;m). These images were individually processed to obtain the Digital Elevation Model Hydrologically Consistent (DEMHC) and to treat the inconsistencies. Afterwards, we created a mosaic with the 15 images.</p><p>In the statistical analysis we examined the magnitude of absolute errors in the SRTM data. These errors were named discrepancies between the SRTM heights and the heights of GNSS survey points. After the post-processing and the heights conversion, the GNSS survey points were considered accurate and used as a reference for SRTM-DEM validation. The goal of the statistical analysis was to verify if the absolute vertical precision of the DEM data exceeds 16&amp;thinsp;m, according to the precision specifications of the DEM SRTM.</p><p>Results showed that the vertical mean absolute error of the SRTM-DEM vary from 0.07&amp;thinsp;m to &amp;plusmn;&amp;thinsp;9.9&amp;thinsp;m with average of &amp;minus;0.28&amp;thinsp;m. This vertical accuracy is better than the absolute vertical accuracy value of &amp;plusmn;&amp;thinsp;16&amp;thinsp;m published in the SRTM data specification and validates the SRTM-DEM. Besides that, even considering different slopes and different heights the statistics showed that SRTM-DEM could be validated, in spite of the results for lower and flat area were more accurate than the ones for a higher area with high slope.</p>

scholarly journals Unsupervised video object segmentation: An affinity and edge learning approach.

2021 ◽  
Author(s):  
Sundaram Muthu ◽  
Ruwan Tennakoon ◽  
Reza Hoseinnezhad ◽  
Alireza Bab-Hadiashar
Keyword(s):  
Optic Flow ◽  
Object Segmentation ◽  
Video Object Segmentation ◽  
Video Object ◽  
Post Processing ◽  
Multiple Objects ◽  
Temporal Features ◽  
Image Edge ◽  
Spatio Temporal ◽  
Generalization Errors

<div>This paper presents a new approach to solve unsupervised video object segmentation~(UVOS) problem (called TMNet). The UVOS is still a challenging problem as prior methods suffer from issues like generalization errors to segment multiple objects in unseen test videos (category agnostic), over reliance on inaccurate optic flow, and problem towards capturing fine details at object boundaries. These issues make the UVOS, particularly in presence of multiple objects, an ill-defined problem. Our focus is to constrain the problem and improve the segmentation results by inclusion of multiple available cues such as appearance, motion, image edge, flow edge and tracking information through neural attention. To solve the challenging category agnostic multiple object UVOS, our model is designed to predict neighbourhood affinities for being part of the same object and cluster those to obtain accurate segmentation. To achieve multi cue based neural attention, we designed a Temporal Motion Attention module, as part of our segmentation framework, to learn the spatio-temporal features. To refine and improve the accuracy of object segmentation boundaries, an edge refinement module (using image and optic flow edges) and a geometry based loss function are incorporated. The overall framework is capable of segmenting and finding accurate objects' boundaries without any heuristic post processing. This enables the method to be used for unseen videos. Experimental results on challenging DAVIS16 and multi object DAVIS17 datasets shows that our proposed TMNet performs favourably compared to the state-of-the-art methods without post processing.</div>

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