scholarly journals Flow Resistance in Lowland Rivers Impacted with Distributed Aquatic Vegetation

2021 ◽  
Author(s):  
Saeid Okhravi ◽  
Radoslav Schügerl ◽  
Yvetta Velísková
Keyword(s):  
Cross Sections ◽  
Flow Resistance ◽  
Aquatic Vegetation ◽  
Roughness Coefficient ◽  
Sources Of Resistance ◽  
Lowland Rivers ◽  
Lowland Streams ◽  
Resistance Factors ◽  
Seasonal Flow ◽  
Bed Roughness

Abstract The study addresses the research concern that the employment of fixed value for bed roughness coefficient in lowland rivers (mostly ‌sand-bed rivers) is deemed practically questionable in the presence of a mobile bed and time-dependent changes in vegetation patches. To address this issue, we set up 45 cross-sections in four lowland streams to investigate seasonal flow resistance values within a year. The results first revealed that the significant sources of boundary resistance in lowland rivers with lower regime flow are bed forms and aquatic vegetation. Then, the study uses flow discharge as an influential variable reflecting the impacts of the above-mentioned sources of resistance to flow. The studied approach ended up with two new flow resistance predictors which simply connect dimensionless unit discharge with flow resistance factors, Darcy-Weisbach (f) and Manning (n) coefficients. A comparison between the computed and measured flow resistance values indicates that 87-89% of data sets were within the ±20% error bands. The flow resistance predictors are also verified against large independent sets of field and flume data. The obtained predictions using the developed predictors may overestimate flow resistance factors to about 40% for other lowland rivers. From a different view of this research, the findings on seasonal variation of vegetation abundance hint at the augmentation in flow resistance values, both f, and n, in low summer flows when the vegetation covers river bed and side banks. The highest amount of flow resistance was observed during the summer period, July-August.

Impact of vegetation on flow in a lowland stream during the growing season

Biologia ◽  
2017 ◽  
Vol 72 (8) ◽  
Author(s):  
Yvetta Velísková ◽  
Renáta Dulovičová ◽  
Radoslav Schügerl
Keyword(s):  
Water Depth ◽  
Flow Resistance ◽  
Aquatic Vegetation ◽  
Growing Season ◽  
Water Levels ◽  
Roughness Coefficient ◽  
Flow Conditions ◽  
Channel Network ◽  
Vegetation Impact ◽  
The Subject

AbstractVegetation growing in the water along watercourses has been the subject of several studies since it was recognized that it could have a significant impact on the water flow. It may increase resistance to flow and cause higher water levels. Also, it has an effect on the velocity profiles. Previous investigations on the flow of water through emergent vegetation have shown different results. The purpose of this paper is to investigate, and determine how aquatic vegetation influences flow resistance, water depth and discharge in the Chotárny channel at the Žitný Ostrov area. This area is part of the Danube Lowland (south-west of Slovakia). The channel network at the Žitný Ostrov region was built up for drainage and also to provide irrigation water. The Chotárny channel is one of three main channels of this network. Measurements performed during six years at this channel were used for an evaluation of vegetation impact on flow conditions. The roughness coefficient was used as one way of quantifying this impact. The results show variation of this parameter during the growing season. Vegetation causes resistance to flow; it reduces flow velocities, discharge and increases water depth.

scholarly journals Mayfly response to different stress types in small and mid-sized lowland rivers

ZooKeys ◽  
2020 ◽  
Vol 980 ◽  
pp. 57-77
Author(s):  
Marina Vilenica ◽  
Mladen Kerovec ◽  
Ivana Pozojević ◽  
Zlatko Mihaljević
Keyword(s):  
Aquatic Invertebrates ◽  
Aquatic Vegetation ◽  
Freshwater Ecosystems ◽  
Catchment Scale ◽  
Lowland Rivers ◽  
Lowland Streams ◽  
Taxa Richness ◽  
Study Sites ◽  
High Share ◽  
Cloeon Dipterum

Freshwater ecosystems are endangered worldwide by various human pressures, resulting in dramatic habitat and species loss. Many aquatic invertebrates respond to disturbances in their habitat, and mayflies are among the most sensitive ones. Therefore, we investigated mayfly response to anthropogenic disturbances at 46 study sites encompassing slightly to heavily modified small and mid-sized lowland streams and rivers. Mayfly nymphs were sampled between April and September 2016 using a benthos hand net. A total of 21 species was recorded, with Cloeon dipterum (Linnaeus, 1761) being the most frequently recorded one. Nevertheless, the taxa richness was rather low per site, i.e., between zero and nine. Assemblage structure had a high share of lower reaches and lentic (potamic and littoral) elements, and detritivores (gatherers/collectors and active filter feeders). This indicates that hydromorphological alterations lead to assemblage “potamisation” in small and mid-sized rivers. More mayfly species were related to higher oxygen concentration and lower water temperature, abundance of aquatic vegetation and total organic carbon. Additionally, the assemblage diversity and abundance were negatively associated with increasing intensive agriculture area at the catchment scale. This study confirms mayfly bio-indicative properties, i.e., their sensitivity to alterations of their habitat and pollution, but also provides new data related to mayfly response to the impacted environment. Those data can be used for management and protection activities of lowland rivers and their biota according to the requirements of the European Water Framework Directive.

scholarly journals Computation of Normal Depth in Parabolic Cross Sections Using The Rough Model Method

2014 ◽  
Vol 8 (1) ◽  
pp. 213-218
Author(s):  
Bachir ACHOUR
Keyword(s):  
Friction Coefficient ◽  
Aspect Ratio ◽  
Cross Section ◽  
Cross Sections ◽  
Flow Resistance ◽  
Open Channel ◽  
Roughness Coefficient ◽  
Model Method ◽  
Rough Model ◽  
Resistance Coefficients

A new method is applied to calculate the normal depth in an open channel of parabolic cross section. This is the rough model method whose main particularity is to ignore the flow resistance coefficients, such as Chezy’s coefficient and manning’s roughness coefficient. The method is applied to a referential rough model, whose friction coefficient is constant, which explicitly express the hydraulic and geometric characteristics of the model such as aspect ratio. By means of a non-dimensional correction factor, the normal depth is explicitly deduced. The rough model method is applicable to the entire domain of turbulent flow.

scholarly journals Estimation of Vegetation-Induced Flow Resistance for Hydraulic Computations Using Airborne Laser Scanning Data

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1864
Author(s):  
Peter Mewis
Keyword(s):  
Laser Scanning ◽  
Flow Resistance ◽  
Laser Scanner ◽  
Airborne Laser Scanning ◽  
Density Parameter ◽  
Vegetation Density ◽  
Airborne Laser Scanner ◽  
Airborne Laser ◽  
Bed Roughness ◽  
Available Information

The effect of vegetation in hydraulic computations can be significant. This effect is important for flood computations. Today, the necessary terrain information for flood computations is obtained by airborne laser scanning techniques. The quality and density of the airborne laser scanning information allows for more extensive use of these data in flow computations. In this paper, known methods are improved and combined into a new simple and objective procedure to estimate the hydraulic resistance of vegetation on the flow in the field. State-of-the-art airborne laser scanner information is explored to estimate the vegetation density. The laser scanning information provides the base for the calculation of the vegetation density parameter ωp using the Beer–Lambert law. In a second step, the vegetation density is employed in a flow model to appropriately account for vegetation resistance. The use of this vegetation parameter is superior to the common method of accounting for the vegetation resistance in the bed resistance parameter for bed roughness. The proposed procedure utilizes newly available information and is demonstrated in an example. The obtained values fit very well with the values obtained in the literature. Moreover, the obtained information is very detailed. In the results, the effect of vegetation is estimated objectively without the assignment of typical values. Moreover, a more structured flow field is computed with the flood around denser vegetation, such as groups of bushes. A further thorough study based on observed flow resistance is needed.

scholarly journals Overland Flow Resistance Law under Sparse Stem Vegetation Coverage

Water ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1657
Author(s):  
Jingzhou Zhang ◽  
Shengtang Zhang ◽  
Si Chen ◽  
Ming Liu ◽  
Xuefeng Xu ◽  
...  
Keyword(s):  
Flow Resistance ◽  
Overland Flow ◽  
Vegetation Coverage ◽  
Dominant Factor ◽  
Roughness Coefficient ◽  
Hydraulic Parameters ◽  
Slope Condition ◽  
Manning Roughness ◽  
The Relationship ◽  
Manning Roughness Coefficient

To explore the characteristics of overland flow resistance under the condition of sparse vegetative stem coverage and improve the basic theoretical research of overland flow, the resistance characteristics of overland flow were systematically investigated under four slope gradients (S), seven flow discharges (Q), and six degrees of vegetation coverage (Cr). The results show that the Manning roughness coefficient (n) changes with the ratio of water depth to vegetation height (h/hv) while the Reynolds number (Re), Froude number (Fr), and slope (S) are closely related to vegetation coverage. Meanwhile, h/hv, Re, and Cr have strong positive correlations with n, while Fr and S have strong negative correlations with n. Through data regression analysis, a power function relationship between n and hydraulic parameters was observed and sensitivity analysis was performed. It was concluded that the relationship between n and h/hv, Re, Cr, Q, and S shows the same law; in particular, for sparse stem vegetation coverage, Cr is the dominant factor affecting overland flow resistance under zero slope condition, while Cr is no longer the first dominant factor affecting overland flow resistance under non-zero slope condition. In the relationship between n and Fr, Cr has the least effect on overland flow resistance. This indicates that when Manning roughness coefficient is correlated with different hydraulic parameters, the same vegetation coverage has different effects on overland flow resistance. Therefore, it is necessary to study overland flow resistance under the condition of sparse stalk vegetation coverage.

Effects of aquatic macrophytes on physico-chemical conditions of three contrasting lowland streams: a consequence of diffuse pollution from agriculture?

2001 ◽  
Vol 43 (5) ◽  
pp. 163-168 ◽  
Author(s):  
R. J. Wilcock ◽  
J. W. Nagels
Keyword(s):  
Aquatic Macrophytes ◽  
Aquatic Vegetation ◽  
Submerged Macrophytes ◽  
Third Stream ◽  
Lowland Streams ◽  
Riparian Plants ◽  
Agricultural Catchments ◽  
Physico Chemical ◽  
Photosynthetic Production ◽  
Chemical Conditions

Three lowland streams in developed pasture catchments with different farming intensities exhibited contrasting summer diurnal variations in pH, DO and temperature. These are ascribed to differences in dominant aquatic vegetation and their respective effects on shade, and on photosynthetic production and respiration within each stream. The stream dominated by submerged macrophytes had the greatest amplitude swings in DO and pH, and DO levels of 86–128% saturation. Floating marginal macrophytes reduced photosynthetic inputs while providing additional organic loading for respiration, with consequent flat DO and pH curves and conditions not conducive to healthy stream ecosystems. The third stream was shaded by riparian plants, which inhibited photosynthetic effects on DO and pH so that diurnal variation was intermediate between the other two streams. The interaction between nutrients and increased insolation in agricultural catchments, in stimulating aquatic plants, needs to be better understood for managing the sustainability of stream habitats and ecosystems.

Blockage and sheltering effects of vegetation in turbulent flow

2020 ◽  
Author(s):  
Wei-Jie Wang
Keyword(s):  
Drag Coefficient ◽  
Flow Resistance ◽  
Aquatic Vegetation ◽  
Reynolds Numbers ◽  
Viscous Boundary Layer ◽  
Vortex Streets ◽  
Karman Vortex ◽  
Viscous Boundary ◽  
Sheltering Effect ◽  
Blockage Effect

<p>The interaction between aquatic vegetation and water flow is investigated here focusing on the drag coefficient. Compared with the standard drag coefficient of isolated cylinder, the phenomena of "blockage effect" and "sheltering effect" are put forward for vegetation clusters with different vegetation densities and Reynolds numbers. "Blockage effect" occurs when the drag coefficient of vegetation cluster is greater than the standard drag coefficient of isolated cylinder. The reason is that viscous boundary layer attached to the surface of vegetation items, resulting that the effective flowing width between adjacent vegetation items is less than the spacing of them, which brings a greater flow resistance and the drag coefficient of vegetation array is greater than the standard drag coefficient. On the other trend, "sheltering effect" is formed when the drag coefficient of vegetation array is less than the standard drag coefficient. This effect usually occurs for flow with large Reynolds numbers. In this case, Karman vortex streets forms and these vortexes are filled in the vegetation interval, thus causing the drag coefficient of vegetation cluster to be less than the standard drag coefficient of isolated cylinder.</p>

Reconstructing a hydraulic model for historic flood levels in the city of Bath, United Kingdom

2020 ◽  
Author(s):  
Ioanna Stamataki ◽  
Thomas Kjeldsen
Keyword(s):  
United Kingdom ◽  
Cross Sections ◽  
Flood Risk ◽  
Hydraulic Model ◽  
Water Levels ◽  
Roughness Coefficient ◽  
Documentary Evidence ◽  
Flood Events ◽  
Historical Evidence ◽  
The City

<p>Assessing the risk of future flood events and the implications for flood risk in cities is an economically and socially costly problem. In this research, we assess the utility of documentary evidence of past flood events for contemporary flood risk assessments to reduce the uncertainty in flood frequency estimation due to the interpolation from short annual maximum series (AMS) records.</p><p>The historical city of Bath, United Kingdom, developed in close relation to the River Avon, and evidence of flooding in the city of Bath can be traced back to Roman occupation. For this research a particularly rich record of historical evidence was chosen occurring from the 19<sup>th</sup> century onwards with flood marks on buildings through-out the city as well as documentary evidence in contemporary newspapers and technical reports. The earliest flood mark found in the city of Bath dates to 1823 with 15 more extreme floods after that marked as well. The extensive flooding in 1947 initiated work on what eventually became the present-day Bath flood protection scheme (BFS) which was implemented after the 1960 catalyst flood event.</p><p>Using an existing one-dimensional hydraulic model representing the current hydraulic system of the River Avon in Bath, a historical survey of how the river and its management has changed over time was conducted. The model was developed using historical evidence (e.g. maps, flood marks, photographs, newspaper articles etc), surveyed river cross sections, recorded and design hydrographs from National datasets.</p><p>The 1960 flood is reconstructed numerically using all available data, from flood marks to old surveyed river cross sections.  The resulting hydraulic model is used to investigate the effect of the Bath Flood Defence Scheme. Sensitivity studies with different values for the roughness coefficient are also presented in order to assess the uncertainty on water levels during extreme events. Finally, the numerically reconstructed historical peak flood discharge is compared with the results obtained using a simple Manning equation approach to assess the two methods. This paper demonstrates how hydraulic modelling can be applied to historical data and offers considerable potential to further investigations in the improvement of design flood flows.</p>

scholarly journals Using Optimisation Meta-Heuristics for the Roughness Estimation Problem in River Flow Analysis

2021 ◽  
Vol 11 (22) ◽  
pp. 10575
Author(s):  
Antonio Agresta ◽  
Marco Baioletti ◽  
Chiara Biscarini ◽  
Fabio Caraffini ◽  
Alfredo Milani ◽  
...  
Keyword(s):  
Cross Sections ◽  
Computational Models ◽  
River Flow ◽  
Heuristic Algorithms ◽  
Flow Analysis ◽  
Differential Evolution Algorithm ◽  
Optimal Estimation ◽  
Evolution Strategy ◽  
Computational Time ◽  
Roughness Coefficient

Climate change threats make it difficult to perform reliable and quick predictions on floods forecasting. This gives rise to the need of having advanced methods, e.g., computational intelligence tools, to improve upon the results from flooding events simulations and, in turn, design best practices for riverbed maintenance. In this context, being able to accurately estimate the roughness coefficient, also known as Manning’s n coefficient, plays an important role when computational models are employed. In this piece of research, we propose an optimal approach for the estimation of ‘n’. First, an objective function is designed for measuring the quality of ‘candidate’ Manning’s coefficients relative to specif cross-sections of a river. Second, such function is optimised to return coefficients having the highest quality as possible. Five well-known meta-heuristic algorithms are employed to achieve this goal, these being a classic Evolution Strategy, a Differential Evolution algorithm, the popular Covariance Matrix Adaptation Evolution Strategy, a classic Particle Swarm Optimisation and a Bayesian Optimisation framework. We report results on two real-world case studies based on the Italian rivers ‘Paglia’ and ‘Aniene’. A comparative analysis between the employed optimisation algorithms is performed and discussed both empirically and statistically. From the hydrodynamic point of view, the experimental results are satisfactory and produced within significantly less computational time in comparison to classic methods. This shows the suitability of the proposed approach for optimal estimation of the roughness coefficient and, in turn, for designing optimised hydrological models.

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