Reducing Uncertainty in River Flood Conveyance Roughness Review
Project W5A-057 July 2003
DEFRA / Environment Agency Flood and Coastal Defence R&D Programme Roughness Review By Karen Fisher and Hugh Dawson W5A 057 DEFRA Flood Management Division and Science Directorate Ergon House Cromwell House 17 Smith Square Dean Stanley Street London SW1P 3JR London SW1P 3JH Environment Agency Rio House Waterside Drive Aztec West Almondsbury Bristol BS32 4UD July 2003
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Publishing organisation DEFRA c/o RCEG Ceres House, 2 Searby Road, LINCOLN, LN2 4DW Peter Allen Williams, R & D Coordinator, Flood Management Division, Tel: 01522 528297 (GTN 6209 224) Email: peter.allen [email protected]
© Crown Copyright July 2003 All rights reserved. No part of this document may be produced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise without the prior permission of the DEFRA and the Environment Agency. Statement of use This document provides information for DEFRA and Environment Agency Staff about consistent standards for flood defence and constitutes an R&D output from the Joint DEFRA / Environment Agency Flood and Coastal Defence R&D Programme. Contract Statement
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CONTENTS Summary vii
1. Introduction 1
2. Review of literature - methods 2 2.1 Methods considered for roughness evaluation 2 2.2 Methods traditionally used for vegetated channels 8 2.3 Other vegetation roughness relationships 12 2.4 Use of roughness coefficients for vegetation 15
3. Review of literature - data 16 3.1 Channel substrate 16 3.2 Channel features and obstructions 16 3.3 Alluvial roughness 20 3.4 Channel irregularities 24 3.5 Tidal reaches 25 3.6 Vegetative features 25 3.7 Vegetation growth and maintenance 27 3.8 Woody debris 29
4. Review of field data 31 4.1 Data availability and usefulness 31 Data gaps 33 4.2 Further data collection and research 33 4.3 Concurrent research projects 34
5. Identification of river types and vegetation morpho-types 36 5.1 River Habitat Survey hydromorphological features 36 5.2 River Habitat Survey vegetation morpho types 37 5.3 Conclusions 44
6. Roughness advisor 45 6.1 Methods and data used in the roughness advisor 45 6.2 Limitations of the proposed method 47 6.3 Definition of types 48 6.4 Vegetation growth and maintenance 63 6.5 Derivation of roughness values 63
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6.6 Upper and Lower Uncertainty bands 68 6.7 Justification of approach 68 6.8 Summary of testing of summation method 68 6.9 Use of the Roughness Advisor in the Conveyance Estimation System 70
7. River maintenance procedures 71 7.1 Basic principles of plant biology and management 71 7.2 The flowing water habitat 72 7.3 Consideration of traditional and alternative techniques 76 7.4 Weed cutting 78 7.5 Indirect control 82 7.6 Techniques used 85
8. Uncertainty 87
9. Bibliography 88
Tables Table 1 Typical examples of the effects of vegetation on water flow 9 Table 2 Summary of equations for floating/submerged vegetation 10 Table 3 Outline of methods to deal with the hydraulic effect due to groynes 20 Table 4 Grass cover retardance classes (US Soil Conservation Service, 1954) 26 Table 5 List of available field data sites and sources 31 Table 6 List of available field data sites from the RHS 32 Table 7 Types of channel and likely vegetation in those channels 38 Table 8 Description of RHS vegetation morpho types 39 Table 9 Generalised critical lower velocity for plant growth, typical mean velocity and upper washout mean in channel velocities for RHS vegetation morpho types44 Table 10 Values of roughness for different types of bed material 49 Table 11 Values of unit roughness for irregularities such as boulders and pools and riffles 51 Table 12 Values of unit roughness for irregularities such as urban trash and groyne fields 52 Table 13 Table of roughness values for aquatic vegetation by RHS morpho type 53 Table 14 Values of total channel resistance for North American channels 54 Table 15 Values of unit roughness for man made bank materials 55 Table 16 Values of roughness for bankside vegetation 56 Table 17 Values of roughness for floodplain ground material 57
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Table 18 Values of roughness for floodplain irregularities and obstructions 58 Table 19 Values of roughness for grass at different retardance classes 59 Table 20 Alternative values of roughness for grass 60 Table 21 Values of roughness for a range of different crops 60 Table 22 Values of roughness for clean and dirty hedgerows on the floodplain 61 Table 23 Values of roughness for trees and shrubs 62 Table 24 Current Control techniques for aquatic and marginal vegetation by RHS vegetation morpho type, with comments on consequences and recovery 80
Figures Figure 1 The variation in Manning’s n values for bankfull discharges in English and Northern Ireland rivers 7 1/2 Figure 2 At a site variations of (8/ f) with relative submergence if d/D 84 for four combinations of channel slope and standard deviation of bed material size distribution for boulder bed rivers (Bathurst, 1994) 18 Figure 3 Bed forms, as categorised by Simon and Richardson (1960) 23 Figure 4 Distribution of RHS channel vegetation types and species 43 Figure 5 Example of a sandbank 46 Figure 6 Variations in roughness values with depth for the River Blackwater in Northern Ireland 47 Figure 7 Example of a typical weed growth curve with and without weed cutting 79
Appendices Reference Tables of data used 134 Explanation of variation of roughness with depth 198 Full Abstracts River Flow 2002 200
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LIST OF SYMBOLS
A Channel cross sectional area (m 2) C Chezy coefficient (m 1/2 /s) D Pipe diameter (m) d Water depth (m) d16 Sediment size by which 16% by weight is finer than (mm) d35 Sediment size by which 35% by weight is finer than (mm) d50 Sediment size by which 50% by weight is finer than (mm) d84 Sediment size by which 84% by weight is finer than (mm) d90 Sediment size by which 90% by weight is finer than (mm) f Friction factor g Gravitational acceleration (m/s 2) k ks Roughness height (mm) Kva Vegetation coverage coefficient N Manning’s roughness coefficient nb Rough boundary coefficient Q Discharge R Hydraulic radius Re Reynolds number Sf Energy slope Sw Water surface slope V Mean flow velocity (m/s) U* Shear velocity Dynamic viscosity ρ Density of water (kg/m 3)
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SUMMARY Under their joint R&D programme for Flood and Coastal Defence, DEFRA/Environment Agency are funding a Targeted Programme of research aimed at obtaining better predictions of flood water levels. In order to achieve this, advances in knowledge and understanding made over the past three or four decades in the estimation of river conveyance will need to be introduced into engineering practise. The project relates particularly to water level estimation, leading to a reduction in the uncertainty in the prediction of flood levels and hence in the flood risk, and consequently facilitating better targeting of expenditure. The project will equally benefit the targeting of maintenance by providing better estimates of the effects of vegetation and its management. It is expected that the application of this knowledge from UK engineering research will have an international impact through improving the methods available to consultants. The above objectives will be achieved through two core components of the new Conveyance Estimation System (CES) that will be developed: the Conveyance Generator and the Roughness Advisor. The CES is to be designed so that new knowledge from a parallel Strategic Programme of research can be integrated into the CES in due course. This report is the designated output for Task T4 of the Targeted Programme of research. The Task objective is to gather, validate and catalogue knowledge on the boundary roughness of UK rivers. The information obtained will then be incorporated in the CES, comprising the Roughness Advisor component. The techniques and underlying assumptions used by the Roughness Advisor in determining the boundary roughness of UK rivers are described in this report. A review of the information identified in the expert paper in the Scoping Study of this project is provided. In addition a wider range of papers are reviewed including papers that have been published or sourced since the expert paper was completed. There are a number of key references where the hydraulic data available is extensive. These papers have been identified and the data within the papers forms the basis of the roughness review. Some of the data sets also have associated vegetation data and this is used alongside the hydraulic data to determine the roughness of vegetated and non vegetated channels. The report also incorporates a large body of knowledge related to vegetation in and around UK waterways and the effect of this vegetation on water flow. The various river types and vegetation morpho types have been identified along with any information provided on substrate characteristics. This roughness review document reviews the various methods and techniques of estimating roughness. The approach selected for use within the roughness advisor is based on Manning’s n roughness. A unit roughness is applied for different types across the channel and floodplain and combines them in a suitable manner within a type. The combined roughness value is then fed in to the conveyance generator. The processes
R&D ROUGHNESS REVIEW vii and justifications for selection of this technique and the data used in the roughness advisor are given. Data gaps and further research needs are suggested. In addition to the review of channel and vegetative roughness, information is also incorporated on river maintenance procedures. This includes the basic principles of plant biology and management; traditional and alternative techniques of plant control, along with advice on weed cutting. Overall this roughness review report provides the technical background information for the Roughness Advisor.
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1. INTRODUCTION This document gives the background to the papers and information accessed, collated and collected as part of the roughness review, component T4 of the project W5A 057 “Reducing uncertainty in river flood conveyance” funded by the Environment Agency (EA) and Department for Environment and Rural Affairs (DEFRA). The activities under this component of the project are to: • Review information identified in the expert paper in the Scoping Study (Fisher and Dawson, 2001) • Review other existing data sets for sites with significant vegetation and physical features • Identify morpho type groups using the RHS database and include substrate characteristics. A review of information identified in Fisher and Dawson (2001), did not include all the papers in the area of roughness but rather concentrated on the core texts, and those which could be included in the space and time constraints for that document. This document covers a wider range of papers including papers that have been published or sourced since the expert paper was completed. This roughness review includes papers from the general field of hydraulics which may not ultimately be used but have been considered and the information not used for reasons which will be given. Many of the papers under review have little hydraulic data published and the information is more descriptive. There are some key references where the hydraulic data is extensive. These papers have been identified and the data within the papers will form the backbone of the information in the roughness review. Some of the data sets have associated vegetation data and these will be used alongside the data from important reviewed papers to determine the roughness of vegetated and non vegetated channels. The sites where there is no vegetation will be used in the roughness review and the data from these sites will give a sound basis for prediction of hydraulic roughness in a variety of situations. The data and other associated information from the important papers are given on, mainly, single sheets in Appendix A. These are not a summary of the full reference rather a selection of the data used to develop the database of roughness values. Information is provided on the identification of river types and vegetative morphotypes, based on data collected for the River Habitat Survey (Raven et al, 1998). There is data on the expected river and plant types in the UK, roughness information for the different types, and where available, data on substrate materials. In addition to the information on roughness, the report also addresses the issue of river maintenance. The basics of plant biology and management are described along with a review of the various methods used to control plant and weed growth. This roughness review document reviews the data and papers covered and how they have been used. The methods, data and techniques considered are documented. The processes and justification for selection of techniques and data used in the roughness advisor is given. Data gaps and further research needed are suggested.
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2. REVIEW OF LITERATURE - METHODS This literature review (Sections 2 and 3) forms part of the requirements for the roughness review and roughness advisor in the Environment Agency/DEFRA funded project on “Reducing Uncertainty in Flood Conveyance Estimation”. This project was developed in response to work from an EPSRC funded network. Several expert papers were written from that network to look at the state of the art in roughness estimation which included a review on vegetation, Fisher and Dawson (2001). This literature review extends the previous work and investigates a wider body of knowledge, in addition to the techniques mentioned in the previous review. This review will extend and update a previous extensive bibliography of Dawson and Charlton (1988) which is incorporated in the annotated Appendix A. An international conference in 1989, Manning Centennial meeting, brought together many Manning ‘n’ practitioners and researchers, as do other annual or triennial symposia for hydraulic engineers. However freshwater ecologists use other journals particularly the European Weed Research Society triennial symposium on Aquatic Weeds to publish data relevant to this study.
2.1 Methods considered for roughness evaluation 2.1.1 Introduction A wide range of techniques has been considered for use in the roughness advisor. These include: Chezy In the past 200 years considerable research has been undertaken into the resistance to flow. Early equations were empirical, fitting only the data from which they had been derived. Chezy (1768) was the first to derive a more generally applicable equation, relating flow velocity to the channel characteristics: 2/1 2/1 V =CR Sf (1) where C = Chezy’s coefficient (m 1/2 /s) R = hydraulic radius = area/wetted perimeter Sf = energy slope Darcy Weisbach friction factor In the 19 th century Darcy and Weisbach produced an equation for pipes flowing full which was similar to Chezy’s equation taking the form: 1/2 2g 1/2 1/2 V = D Sf (2) f where D = pipe diameter (m) f = friction factor
By replacing the pipe diameter with the hydraulic radius this becomes (asuming D=4R):
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2/1 g8 /1 2 2/1 V = R Sf (3) f
This equation is in common use today and the only significant development has been in the selection of the appropriate value of friction factor f. Blasius, Nikuradse and relationship with Reynolds number Van Mises (1948, 1951, 1953), in the early 20th century, analysed the experimental data of other research workers and identified the significant parameters for the friction factor to be the Reynolds number and the roughness ratio, k s/D where k s is the roughness height and D is the pipe diameter. Blasius derived an equation, relating f, the friction factor, to the Reynolds number (for smooth pipes). .0 316 f = (4) Re 4/1 In the 1930s Nikuradse (1933) carried out experiments on a series of pipes . The experiments covered a wide range of Reynolds number and examined not only the effects of variation in the roughness ratio but also compared the roughness of pipes of different diameters with the same roughness ratio. Nikuradse revealed the relationship between friction factor and Reynolds number, which is defined in three phases. 1. Friction factor independent of pipe roughness and solely a function of the Reynolds number laminar flow region and ‘smooth’ turbulent flow 2. Friction factor solely dependent on the roughness ratio and independent of the Reynolds number viscous effects predominant; fully rough turbulent flow 3. In the transition region between the smooth turbulent pipe law and the rough turbulent pipe law the friction factor gradually departs from the value given by the smooth pipe law falling to a minimum value as the Reynolds number increases before rising to the rough turbulent value at high values of the Reynolds number. The limits of the transition zone are given by ρU k 3≤ * s ≤ 60 (5) where U * = shear velocity. Outside these limits the flow is either smooth turbulent or rough turbulent. The work of Nikuradse was not practical for engineering use as it did not use standard engineering variables such as pipe diameter, flow and hydraulic gradient. In the 1940s Moody developed a plot of friction factor against Reynolds number for commercial pipes following the work of Colebrook and White (1937, 1939). The result was the familiar friction factor versus Reynolds diagram, known as the Moody diagram.
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Colebrook and White pipe flow Colebrook and White (1937, 1939) extended the work of Nikuradse by carrying out experiments on pipes which had been artificially roughened by sand of two distinct and different sizes. The results agreed with Nikuradse in the smooth turbulent and rough turbulent regions but some of their experiments showed a different form of friction factor versus Reynolds number relationship in the transition zone. The friction factor gradually fell until it reached the rough turbulent value in contrast to falling to a minimum value and then rising up to the rough turbulent value. Based on the theoretical work that had been done by Prandtl (Prandtl, 1904) and von Kármàn (1934), Colebrook and White derived an equation which fitted the data for commercial pipes in the transition zone. At low Reynolds numbers the Colebrook White equation approaches the smooth turbulent law and at high Reynolds numbers it approaches the rough turbulent law. 1 k 2.51 = 2log s + (6) f 3.7D Re f Because of its complexity, the Colebrook White equation was slow to find favour but this disadvantage has been overcome by the development of charts and tables (HR Wallingford and Barr 1998, volumes 1 and 2). Manning’s equation In river engineering Manning’s equation is usually used to represent channel resistance and is given by the relationship: R 2/3 S 1/2 n = f (7) V where n = Manning’s roughness parameter (s/m 1/3 ) R = hydraulic radius (m) Sf = energy slope [note that in practice, where flow is approximately uniform the water surface slope S w is often used in place of S f] V = mean flow velocity (m/s) The equation provides a means of estimating discharge for steady uniform flow in open channels from: AR 2/3 S 1/2 Q = f (8) n where Q = discharge (m 3/s) A = channel cross sectional area (m 2) The main difficulty in using Manning’s equation is estimating accurately a value of the roughness parameter n. Each channel exhibits its own characteristics and the roughness parameter is dependent on the size and shape of channel, the bed substrate, the different
R&D ROUGHNESS REVIEW 4 features within the channel e.g. vegetation, boulders, and the depth of water within the channel. Field observations have shown that, at a given cross section, the Manning’s n varies with depth. Equating the Chezy and Manning equations gives: R 6/1 n = (9) C Equating the Darcy and Manning equations leads to: 2/1 6/1 f n = R (10) g8 Plotting the friction factor against k s/D for flow in the rough turbulent region indicates that: 3/1 f ∝ (k s / R) (11) In terms of the Colebrook White equation, the range of relative roughness values in which this applies is given by: R 7≤ ≤130 (12) k s In this range Manning’s n is related to the roughness height in metres by: 6/1 n = .0 038ks (13) 2.1.2 Visual comparison with photographs Barnes (1967) states that “Familiarity with the appearance, geometry and roughness characteristics will improve the engineer’s ability to select roughness coefficients for other channels.” Similarly Hicks and Mason (1991, 1998) states that “Values of roughness coefficient estimated using the ‘visual comparison’ approach can be employed in their own right in hydraulic calculations; alternatively, and preferably, they can be used to either verify, or as base values for estimates of roughness coefficients obtained by more quantitative methods”. There are a number of sources from which photographic evidence of rivers and their associated hydraulic roughness coefficients can be obtained. Chow (1959) is probably the most familiar of these sources and although the channels in Chow are all from America and the photographs are black and white, they cover a wide range of channels and a list of tables is also supplied with the photographs which provide a good initial source of roughness values. The tables are given in Appendix 1. The photographic method of estimating Manning’s n was adopted by the United States Geological Survey. Photographs of river channels of known resistance were presented by Barnes (1967),
R&D ROUGHNESS REVIEW 5 with a brief description and summary of the geometry and hydraulic parameters which define the channel. Hicks and Mason (1991) provide similar details of channels in New Zealand. All the above references are a good source of data, if no other information is available. A global estimate of roughness can be determined using these sources but care must be taken as roughness values given are not applicable for a range of discharges. Field measurement The most effective method for determining the Manning’s n roughness coefficient within a river is by measurement. This may involve field survey over an extended period of time but will enable the most accurate assessment of the roughness coefficient to be determined. At a number of sites, field measurements have been undertaken. Figure 1 shows the variation of measured Manning’s n values for bankfull discharges in English and Northern Ireland rivers with the indication of the range of values recommended by Chow (1959) for these types of rivers. Measured Roughness at different flows for eight sites within the Severn Trent Region Assessment of the roughness coefficient either from site inspection or reference books is frequently based on engineering judgement. This was recognised by the then Severn Trent Water Authority (STWA) who in 1984 commissioned a study to produce a direct measure of the Manning’s n for a range of flows up to bankfull at sixteen open channel sites in the Severn Trent Region already functioning as accurate flow measurement sites. Data from 66 measurements of bankfull discharge, water surface slope and channel characteristics at six of the sites were made available by the Severn Trent Region of the National Rivers Authority (1991). The sites had channel widths at bankfull ranging between 20m and 80m, bankfull hydraulic radii between 1m and 3.5m, water surface slopes between 1 in 300 and 1 in 3000 and bankfull discharges from 20 cumecs to 350 cumecs. Eight sites in the Severn Trent region are given in Appendix A for which roughness coefficients have been determined at bankfull flow. The pictures, cross sections, hydraulic characteristics and a description of the channels are given and they can be used to establish the roughness coefficients for similar channels.
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Figure 1 The variation in Manning’s n values for bankfull discharges in English and Northern Ireland rivers
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Measured Roughness at various sites for a range of flows and depths Hydraulic field data collected from several river sites along the River Blackwater catchment in Northern Ireland have provided valuable information on the relationship between Manning’s n and discharge and depth for a range of flows and depths. The information can be used to establish the roughness coefficients of similar channels. Data collected by the Institute of Hydrology relating to verification work on the habitat simulation model PHABSIM has been analysed and graphs showing Manning’s n roughness against flow for a range of inbank flow conditions have been established for two sites: River Wey and Mill channel. Butler et al (1978) and Richards and Hollis (1980) show details of the variation of Manning’s n with discharge for two urban streams, and for a number of gauging station positions on Scottish rivers respectively. The urban streams have typical cross sections for each site with the measured Manning’s n roughness values for a range of discharges but there are no typical cross sections or photographs given for the Scottish rivers. Cowan’s method An alternative to Chow’s method of estimating Manning’s n involves the use of a procedure, as presented by Cowan (1956) also known as the Soil Conservation Method (US Soil Conservation Service, 1963). This method involves the selection of a basic value of Manning’s n for a uniform, straight and regular natural channel. The basic value is then adjusted for the effects of surface irregularities, shape and size of channel cross section, obstructions, vegetation and flow conditions and the meandering of the channel. By this method the value of n may be calculated by: n = (n 0 + n 1 + n 2 + n 3 + n 4)m 5 (14) n0 = base value for a straight, uniform channel in natural materials. n1 = value added to n 0 to correct for the effect of surface irregularities. n2 = value for variations in shape and size of the channel cross section. n3 = value for obstructions. n4 = value for vegetation and flow conditions. m5 = correction factor for meandering of the channel. A description of the different factors is given in Table A17 in Appendix A.
2.2 Methods traditionally used for vegetated channels 2.2.1 Introduction The growth of plants in river channels is dependent on many factors, e.g. Leonov (1966). The literature on roughness due to vegetation must be considered in the light of the fact that vegetation growth is dependent on factors such as light, water quality, temperature and sediment size in addition to location and type of channel and may produce a range of effects as water plants, large and small, are to be found in all flowing waters (Table 1). Their sizes range from the large and obvious which can be expected to modify the rate of flow of waters to the smallest which grow on measuring flumes and may even enhance flow by smoothing the water flow over the ‘rough’ concrete
R&D ROUGHNESS REVIEW 8 surfaces. The principal factors that may affect flow conditions, the progressive series of structural changes through which a generalised plant passes and the phases of flow are summarised by Hydraulics Research (1985) prior to a series of flume trials.
Table 1 Typical examples of the effects of vegetation on water flow Reduce water velocity and raise water levels. Moderate the flood hydrograph Increase, progressively, the flooding or overbank spill particularly during summer when aquatic vegetation may be at its maximum (i.e. increase flood risk). Encourage the deposition of suspended sediment which may have to be removed to maintain adequate flow discharge capacity; this is supply dependent and seasonal. Change the magnitude and direction of currents within a channel causing local erosion or reducing erosion, depending on the location, extent and density of the vegetation. Interfere with the use of water for conveyance, navigation, fishing and swimming. Plants and flow may then be involved in a range of interactions which vary seasonally. Different species of vegetation can change in form and habit and these are influenced by many factors. Typical responses of species groups (see RHS vegetation morpho types, Chapter 5) include aspects such as: • Height of the emergent vegetation relative to depth of flow and its velocity reeds in channel, grass covered or tree covered plain. • Diameter, shape, surface texture, specific gravity i.e. floatation, of plant stems and leaves. • Flexibility or stiffness of stems or of whole plant stands (affecting the deflection and frequency of vibration of a stem). • Form resistance, water approach angle and dimensions of plant stand. • Distribution of stems within the plant stand, their areal or numeric density, and the degree of stem compaction caused by increasing velocity and the resulting change in stand permeability (i.e. the tendency of water to flow round rather than through stands), and • Distribution of plant stands, their frequency and pattern per unit area of watercourse. 2.2.2 Visual comparison with photographs Traditionally one of the methods used for determining the roughness of a channel with vegetation has been using photographic evidence of rivers linked with roughness, as mentioned previously. Freshwater ecologists have normally used more detailed methods. These are based on an assessment of the area occupied by vegetation, either in the water column or more often at the surface i.e. ‘cover’, either by mapping or by determining presence or absence at numerous points e.g. Dawson (1974), Ham et al. (1981). Such methods are discussed in the IBP handbook (Vollenweider and Westlake, 1980). 2.2.3 Empirical methods Many of the methods developed for determining the impact of vegetation on the roughness of the channel are based on data collected on a particular river over one season or a number of seasons. Much of this data is very valuable in allowing the large variations in roughness which vegetation can cause to be recognised.
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2.2.4 Qualitative relationships Some studies, Powell (1978) Dawson and Robinson (1984), have provided useful qualitative data on the seasonal behaviour of the vegetation and roughness. Powell (1978) measured data on the River Bain over a ten year period where Potamogeton was the predominant vegetation. Although detailed vegetation measurements were not taken the hydraulics of the channel were measured in detail over the seasons. The roughness changed substantially with discharge variations and the roughness reached a peak in July. From the measurements that Powell carried out the complex relationship between roughness and vegetation can be seen as the roughness also varies substantially with depth (or discharge). 2.2.5 Semi-quantitative relationships Other studies have shown some other interesting effects. These include the differing impacts which vegetation can have for different sizes of channel and the percentage increases in roughness when vegetation is present, Brooker et al (1978), Bakry et al, (1992), Watts and Watts (1990). Stephens et al (1963) undertook a study on flat water course in the US which suggested that floating vegetation can raise the value of Manning’s n to more than twice its clear channel value. For submerged vegetation the figure can be as high as twenty fold! Shih and Rahi (1982) discovered that during the growing season the value of n increased by 300%. Pitlo’s research on canals in the Netherlands (Pitlo 1978, 1979, 1982) showed that increases in roughness during the growing season depended on the size of the channel. In a small canal the Manning’s n value almost doubled whilst in a large canal the increase was 14%. The semi quantitative method, which is regularly used by engineers and scientists to determine the roughness of a vegetated river channel, is the US Soil Conservation Service Method (1963). As mentioned previously, the roughness is built up from a number of factors, channel shape, irregularity, substrate, obstructions, vegetation and sinuosity. 2.2.6 Quantitative relationships This relationship between the Manning’s n roughness and the product of the velocity V and the hydraulic radius R and the coverage of vegetation K va is a common theme through many of the studies undertaken. A number of the studies are mentioned in Table 2 and the relationships between the factors of roughness, velocity, hydraulic radius or depth and vegetation coverage are given. Table 2 Summary of equations for floating/submerged vegetation Authors VR (m 2/s) Discharge Q Area Equation range (m 3/s) (m 2) Pepper (1971) 0.58 to 8.46 2.4 K n = 0.06 + 0.17 va VR Wessex (1987) 0.24 to 1.3 15 43 K n = 0.032 + 0.027 va Vd Wessex (1987) 0.15 to 1.1 15 43 K n = 0.041+ 0.022 va Vd Wessex (1987) 0.15 to 1.1 15 43 K n = 0.029 + 0.022 va Vd
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Authors VR (m 2/s) Discharge Q Area Equation range (m 3/s) (m 2) Marshall and 0.24 to 1.3 0.2 1 K n = 0.1+ 0.153 va Westlake (1990) VR Larsen at al 0.025 to 0.15 0.1 0.7 K n = 0.057 + 0.0036 va (1991, 1990) VR Hydraulics 0.04 to 0.11 4 3.5 K n = 0.035 + 0.0239 va Research (1992) VR Pepper (1970) measured Manning's n values on the River Ousel over a period of a year and also made a measure of the weed growth. The results show a strong correlation between Manning's n and the ratio of weed volume to water volume in the test reach. Marshall and Westlake (1990) measured water velocities around vegetation in a chalk stream. A relationship between roughness, velocity, and depth and vegetation coverage can be found from their data. There have been some studies undertaken where no obvious relationship between flow resistance and vegetation biomass has been determined. Dawson (1978a) made measurements in the shallow upper Bere stream, a tributary of the River Piddle (Dorset), and related flow resistance to both cover and biomass. Subsequent re examination of the data in more detail did not find any clear relationship with cover as it varied by a factor of three whereas a seasonal, slightly cyclic, but clear relationship was found with biomass. Experimental studies in flumes confirm good VR to n relationships for a range of biomass for several common species but although field measurements were made, the seasonal change in plant morphology was not apparently undertaken. Discussion on the relationship of cover and biomass lead on to the bulk ratios e.g. Pepper (1971) and blockage factors e.g. Dawson & Charlton (1988), as method of assessing plant volumes, whereas stand structure may be of more importance, Dawson (1979). This method is based on the assumption that for a particular vegetation type there is a unique relationship between the Manning's n roughness coefficient and the product of the mean area velocity (V) and hydraulic radius (R), regardless of the relative values of V and R. There is little scientific justification for the n VR approach, other than it seems to “fit” many situations in Europe and further afield, Bakry (1992). Kouwen et al (1977) showed that for the same vegetation type and height, plots of Manning's n versus VR do not fall on a single line and hence this empirical approach may be seriously flawed. The practical relationship between roughness n and the product VR is unsatisfactory. The empirical relationships are not ideal in that velocity is calculated using a coefficient which itself depends on the velocity. The same values of VR may be obtained from different values of V and R and the relationship is not independent of slope, Smith et al. (1990). It is obviously not correct to assume that the Manning’s roughness should be the same for a rapid, shallow partly submerged flow and a slow, deep completely submerged flow, which have the same VR product. Kouwen and Li (1980) further claimed that the n VR method is invalid when the vegetation is short and stiff or when the slope is smaller than 0.05, which is encountered in many UK rivers prone to flood inundation.
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2.3 Other vegetation roughness relationships Those roughness relationships described above are the methods traditionally used and on the whole are based on empirical data. In more recent years there have been greater moves into the use of numerical models to describe the interactions between vegetation and water flows. The following sections outline how the roughness is assessed by different relationships, which try to describe the nature of the vegetation and its interaction with flow in a more scientific rather than descriptive or empirical manner. 2.3.1 Roughness Coefficient as a function of flow depth There have been a number of studies in the recent past where the way in which the roughness varies through the vertical column has been investigated. These studies have included channels with no or little vegetation where the roughness has been dominated by the bed form or plan form, Negri et al. (1999). Other studies have shown how the vegetation and physical characteristics can influence the variations in roughness in the vertical plane, Fisher and Knight (2002). In situations where vegetation is present, the amount of plant submerged or emerging and plant type are both important parameters in defining the relationship between roughness coefficient and flow depth. Temple (1987) observed that the roughness coefficient tends to be constant for deeply submerged vegetation. Wu et al. (1999) concluded that, under laboratory conditions, Manning’s n decreased when the plant was emergent but when the plant is completely submerged the Manning’s n significantly decreased tending to an asymptotic constant. Wilson and Horritt (2002) also observed an asymptotic relationship between roughness and depth for a fully submerged grass canopy and Wu et al. (1999) have further shown that the asymptotic constant is a function of the vegetation height. Other work carried out at the River Blackwater, Hampshire has provided extensive data on the variation of Manning’s n roughness coefficient with seasonality (Wilson & Sellin 1999, Sellin et al., 2001), and similar work on the River Cole in Birmingham, Fisher and Knight (2002). Other approaches along a similar route show the relationship between roughness and other parameters such as discharge, Green and Garton (1983). 2.3.2 Force-Equilibrium Approach and the Drag Force Approach Ree (1958) and Petryk and Bosmajian (1975) addressed the problem that the Manning’s friction coefficient is a function of flow depth and vegetation density. The latter researchers used a force equilibrium approach where they postulated that the gravity force is equal to the boundary shear and the drag forces on the emergent vegetation. For conditions where the energy losses due to vegetation dominate, Manning's n is proportional to the square root of the plant density and the drag force increases as the square of the area mean velocity. However Fathi Maghadam & Kouwen (1997), through their experimental work on non submerged pine and cedar saplings and branches, found that the relationship between drag force and flow velocity is probably linear. This was also observed by Wilson and Horritt (2002) for a flexible grass canopy and this is possibly due to these plants’ flexibility when subject to shear. Other researchers have used experimental data sets to validate a drag force approach. James et al. (2001) showed that there is a direct relationship between stem drag and vegetation resistance. Rahmeyer et al. (1996) showed that non rigid features increase the streamlining effect, reducing the drag coefficient and the momentum absorbing area. This highlights the significance of taking the rigidity of the feature into account. Knight (1988) assessed the energy losses associated with friction, eddies, and form including vegetation and combined them. Querner (1994) takes a similar approach but because of
R&D ROUGHNESS REVIEW 12 momentum, sums the forces in the longitudinal direction and equates them to zero and uses an estimate for the drag coefficient for vegetation from Li and Shen (1973) or van Ieperen and Herfst (1986). 2.3.3 Relative Roughness Height Approach Ree (1949), Kouwen, (1989), Kouwen and Li, (1980), have advocated the roughness height approach originally developed for flow in pipes lined with rigid forms of roughness, for representing the flow resistance of submerged vegetation. The deflected roughness height is related to the undeflected height of the grass, local boundary shear, flow depth and the MEI (is the product of the stem density M, stem modulus of elasticity E, and the stem areas second moment of inertia I). This was defined from laboratory experiments over flexible plastic strips of vegetation where MEI was a measurable parameter. In natural vegetation the parameter MEI is more difficult to define and quantify, and Temple (1987) undertook laboratory experiments on grasses correlating MEI to undeflected vegetation height and found a large disparity between growing and dormant grass.
2.3.4 Turbulent Structure More recent work has focused on detailed examination of the flow field and turbulence structure within a plant canopy. These studies have involved modelling vegetation as an array of rigid cylinders of the same height and diameter at regular spacing (Pasche, 1984, Tsujimoto et al., 1991, Dunn et al. , 1996, Meijer and van Velzen, 1999, Nepf, 1999). For example Nepf (1999) has tested a physically based model which links vegetation form drag, turbulence intensity and turbulent diffusion and uses Raupach and Shaw’s (1982) spatial and temporal averaging approach to account for the heterogeneous nature of the flow field and to present the problem in a 1D context. For both rigid and flexible vegetation types in emergent conditions, the Reynolds stresses within the flow are negligible and the streamwise turbulence fluctuations are found to be small. However when the vegetation becomes submerged, a horizontal shear layer forms in the surface flow region above the canopy and which also penetrates to some depth within the plants. The Reynolds’ stress profile reaches a peak at the interface and decays within and above the canopy. It seems that this characterises the flow irrespective of the vegetation being rigid or flexible (Tsujimoto et al., 1992, Dunn et al., 1996, Nepf and Vivoni, 1999, Wilson et al ., 2002). Wilson et al. (2002) examined the effect of two forms of flexible vegetation, with foliage plants and the equivalent plant without foliage, on the turbulence structure. The addition of the plant foliage at the top of the stems inhibits the turbulent mixing between the two flow regions, the canopy layer and the surface flow layer, and shifts the turbulent stress peak to a level above the canopy top surface. The sway of the vegetation affects the turbulence in flows, Murota et al . (1984). Hino (1981) investigates the ecological effects of turbulence. Organised vortices above short flexible plants were studied in 3 D both visually and in terms of velocities. This showed the intensity and stress was highest just below the top of vegetation layer (Ikeda & Kanazawa, 1996). 2.3.5 Boundary of vegetation There has been much effort made to understand the fundamental principles of momentum exchange at the boundary between vegetated and non vegetated areas, Nepf and Vivoni (1999), Dittrich et al (1999), Fukuoka and Fujita (1990). In the latter paper the authors quantitatively clarify the influence of the lateral velocity difference between flow in a vegetated and non vegetated area. The laboratory experiments lead to an
R&D ROUGHNESS REVIEW 13 expression for momentum transfer represented by a boundary mixing coefficient, which indicates the degree of mixing between the flow inside and outside the vegetation. On this theme, Fukuoka and Fujita (1993) have developed an equation of momentum that incorporates increases in resistance caused by different configurations of vegetation in a river channel. Flow in a deep open channel with vegetated banks was investigated by Hasegawa et al (1999). The principles resulting from that research show: • Where there was comparatively deep water with high vegetation density on the bank, large scale eddies which usually develop along the vegetation boundary were not found. • Near the vegetation boundary, strongly deformed velocity distributions including the maximum velocity, occurred at one third water depth from bed. • Near the vegetation boundary, the main flow velocity in the non vegetation area is reduced. • The resistance force increases due to the different components of lateral Reynolds stress on the vegetation boundary, the momentum transport and the base shear stress, in that order. 2.3.6 Higher-Dimensional Modelling Approaches More complex methods for multi dimensional flow problems have been developed by Burke and Stolzenbach (1983), Nakagawa et al. (1992), Shimizu and Tsujimoto (1994) and Lopez and Garcia (1997) using a two equation turbulence closure approach. This was first introduced by Wilson and Shaw (1977) to model atmospheric flows over plant canopies. A modified k ε turbulence closure model was used, introducing drag related sink terms into the momentum as well as into the turbulent transport equations. Laboratory experiments, conducted at Kanazawa University, Japan (Tsujimoto et al. , 1991) have been used to validate the model. Shimizu and Tsujimoto (1994) calibrated their model by adjusting two additional weighting coefficients that appear by introducing the vegetative sink into the turbulence equations, to reproduce observed mean velocities and Reynolds stresses. Lopez and Garcia (1997) numerically modelled similar test cases and modified the same weighting factors of the k ε model but reported calibrated values which differed by about 500% from those of Shimizu and Tsujimoto (1994) . More recently Lopez and Garcia (2001) again tested the k ε model and compared the k ω turbulence formulation (Wilcox, 1988) and no appreciable difference was found between the numerical performances of either turbulence model. A constant C D, the front end or form resistance value of 1.13, was used by Dunn et al. , 1996 in the drag force sink term in the momentum equations and no modifications were made to the five standard constants of the k ε model. However values for the weighting coefficients for the drag related source terms for the k and ε equations (C fk = 1.0 and C fε = 1.33) were found again to be inconsistent with those previously reported. To eliminate the calibration from the validation procedure, Fischer Antze et al. (2001) developed a similar drag force approach but only introduced sink terms into the Navier
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Stokes equations and hence made no modification to the k ε model. The turbulence closure thus used the standard values for the weighting coefficients (after Rodi, 1980) and a C D equal to unity. The model was used to simulated rigid and emergent vegetation in simple section and compound section channel arrangements (experimentally conducted by Tsujimoto et al., 1991 and Pasche, 1984 respectively) and good agreement was found between the computed and observed streamwise velocity distributions. Nao et al. (1996) were the first who have used a higher order anisotropic closure, the Reynold's Stress model (RSM), to simulate the flow through rigid submerged vegetation elements. However these higher order turbulence approaches are outside the realm of practicality for application within the field. The functional relationships and numerical methods outlined herein, with the exception of Klassen and Van Der Zwaard (1974) and Klassen and van Urk (1985), have been based on experimental investigation at a laboratory scale with simplified models of plant canopies and have not yet been upscaled and tested at field scale. Some of these methods involve the quantification of parameters that are non measurable within natural vegetation and parameters (e.g. deflected height, flexural rigidity) and which are difficult to characterise both in the laboratory and field. Furthermore, higher dimensional numerical approaches where modifications have been made to the turbulence transport equations have highlighted inconsistencies in weighting coefficient values.
2.4 Use of roughness coefficients for vegetation Roughness coefficients are used in many different places especially when the water levels for a particular discharge are required. The roughness impacts on the stage discharge relationship and the presence of vegetation can increase the roughness and the water level thereby substantially changing the stage discharge relationship, Darby and Thorne (1996), Gurnell and Midgley (1994), Turner et al, (1978) and Benovitsky et al (1990). Within channel design there has been a shift towards river restoration or rehabilitation, which requires environmentally sensitive design. The roughness characteristics and velocity distributions need to be predicted more accurately in order for the requirements for flora and fauna to be determined. In addition roughness variations will allow the water levels for flood alleviation to be predicted more accurately. The use of environmentally sensitive design can cause a conflict of interest between ecology, flood alleviation, economics and geomorphology, Dawson and Brabben (1991), Brookes (1988), Hey et al (1994). More work is required in this area to try and define the hydraulic characteristics of environmentally sensitive designs, Ferguson et al (1998), Fisher (2002).
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3. REVIEW OF LITERATURE - DATA
3.1 Channel substrate The main source of information on the roughness of channel substrate has been found traditionally in Chow (1959). The main understanding has been that the greater the relative size of the bed material the higher the roughness factor. A number of different publications have shown pictures of different rivers with a variety of substrates, Hicks and Mason (1991) and Barnes (1967) in particular. These publications are for different countries, New Zealand and US, and give the roughness for the river at a particular moment rather than just the value for the substrate. In the rivers selected, however, the substrate would have been the dominant factor. 3.1.1 Roughness, sediment and channel shape and size The relationship between roughness and sediment size and distribution of sediment has been studied and the best relationships can be shown to be between roughness and the d 84 sediment size (the sediment size equal to or exceeding that of 84 % of the stream bed particles by weight) or d w (the size obtained by assigning a weight of 0.1 to d 16 , a weight of 0.3 or d 50 and a weight of 0.6 to d 84 ), Limernos (1970). Resistance to flow is intimately related to bed configurations: ripples, dunes, antidunes, chutes, pools, Knoroz (1959). A relationship between stream power, diameter of bed material and bed configuration has been developed by Simons and Richardson (1966). Haldar et al (1981) developed a relationship between the roughness coefficient, the hydraulic radius and the material size. The resistance in fully developed turbulent flow at a constant depth increases with the square of the mean velocity when the boundary conditions remain unchanged. However, in natural rivers this is not always so, especially in sinuous channels when the free surface is disturbed due to the channel curvature, Leopold et al (1960). 3.2 Channel features and obstructions 3.2.1 Boulders The use of large scale roughness in environmental channels is generally for the creation of rock pools to improve the spawning and nursery areas for fish. The size of sediment is of a similar order of magnitude to or greater than the depth of flow of the channel in which it is placed. However, large scale roughness of this magnitude in a natural channel is usually only to be found in steep streams. Standard equations for small scale roughness do not apply to large scale roughness. Locally, the flow is nonuniform with zones of separation, acceleration, and deceleration around the roughness elements. Research by Bathurst (1978) has shown the flow resistance for channels with large scale roughness to be a function of channel shape, roughness spacing and relative roughness. Thompson and Campbell (1979) related resistance solely to relative roughness. Both approaches are presented as a means of estimating the resistance of large scale roughness, however the use of the Colebrook White formula with k s =3*d 90 or k s =3*d 85 is recommended . The determination of the size of material on the bed of a stream is based on an analysis of the relative area covered by particles of given sizes after Wolman (1954).
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Caution, however, must be expressed in proposing both the method of determination of bed material size and estimation of roughness coefficient. The former due to the artificial frequency distribution generated when large scale roughness elements are introduced into an environmental channel; the latter as the resistance equations have been derived from channels with steep slopes lined with coarse but relatively uniform bed material. Bathurst, Li and Simons (1981) investigated the effects of large scale roughness on the resistance equation where the boulders are the same order of magnitude as the depth of flow. They discovered from flume experiments that flow resistance of large scale roughness depends on the form drag of the elements and their location within the channel. The flow processes are functions of Reynold’s number, Froude number, roughness geometry and channel geometry. The equations produced are semi empirical with a basic theoretical equation but without a full mathematical quantification of the functions. Figure 2 shows examples of observed variations in flow resistance but the field data is not available in sufficient quantities to make a good calculation of resistance from the complex relationships. There is a semi logarithmic relationship from Hey (1979) given below: 1 8 2 aR = .5 75log (15) f 5.3 d84
But as the vertical logarithmic velocity relationship breaks down when there are boulders present this equation does not apply except at relative submergences of less than 1.5, Thorne and Zevenbergen (1985). At higher relative submergences the semi logarithmic relationship significantly overestimates the flow resistance coefficient as seen in Figure 2.
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1/2 Figure 2 At-a-site variations of (8/ f) with relative submergence if d/D 84 for four combinations of channel slope and standard deviation of bed material size distribution for boulder-bed rivers (Bathurst, 1994)
Bathurst (1985) suggests an empirical approach with the resistance calculated from the following equation: 1 8 2 d = .5 62log + 4 (16) f d84
This is for channel slopes in the range 0.4 4% and d/d 84 <10. As this equation is representative rather than for individual sites it tends to underestimate resistance at low flows and overestimate resistance at high flows. Jarrett (1984) gives another empirical equation where: .0 38 − .0 16 n = .0 32S f R (17) for channel slopes of 0.2 4%. Again this represents the average line through an envelope of values from a range of sites rather than individual sites. Both of the above equations from Bathurst (1985) and Jarrett (1984) can give errors of 30%. More recently Bathurst (1996) has measured in the field the drag force on individual boulders on the river bed which showed much higher values of drag coefficient, 0.36, than those measured in the laboratory, 1.1 1.5, for cubes. More tests are required to test the conditions in which the method can be used before this method can be transferred and used in a more natural environment.
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Values of roughness coefficients for gravel and cobble surfaces were related to surface cover and Reynold’s number by Gilley et al (1992) in a laboratory environment. The diameter of the cobbles extended to 25cm, which could be erring into the small boulders region. This data could be used for small boulders and is related to the coverage of the cobbles in addition to the Reynold’s number. Macro roughness simulated using marbles was investigated by Dubois and Schleiss (1999), in order to determine the relationship between the velocity and the variable parameters, such as the object size, slope of the surface, and the flow. This has led to a new relation for head loss for shallow flows over macro roughness that is valid for laminar and turbulent flows. The presence of woody debris within a channel can have a significant effect on the resistance to flow. The debris can reduce the average velocity, and locally elevate the water surface profile. The significance of the debris is scale dependent with the hydraulic effects typically being drowned out in a larger flood or large river, Gippel (1995). Shields and Gippel (1995) produced a simple technique for predicting the friction factor for river channels with varying amounts of large woody debris. In two rivers studied the removal of debris reduced the friction factor by 20 30% increasing bank top flow capacity by 5 20%. 3.2.2 Groynes Much work has been carried out to optimise the design of groynes for the purpose of providing bank protection, see for example Jansen et al (1979), McCollum et al (1987), Bhargava and Singh (1981), Ahmad (1951) and Miller et al (1983). Guidelines were developed by Seed (1997) on the geometry of groynes for river training. This work has concentrated on investigating the effect of varying the length, crest height, angle and spacing of groynes on their efficiency as bank protectors. No work has been identified which investigates the effect of current deflectors and groynes on the overall hydraulic performance of the channel. Procedures are proposed below for analysing the effect of groynes on the hydraulics of the channel. These are based solely on knowledge of river hydraulics from work done at HR Wallingford. These procedures should be used with extreme caution until they are validated against both laboratory and field data. The hydraulic effect of groynes on the channel will depend on two factors. Firstly whether there is a single groyne or whether there are a number of groynes, and, secondly the size of the groyne relative to the channel.
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Table 3 Outline of methods to deal with the hydraulic effect due to groynes Water level in Groyne width as Suggested approach relation to a function of groyne channel width Water level above Single groyne, Under these circumstances any hydraulic the groyne crest length < 20% of impact of the groyne will be localised and will the channel width have a minimal effect on the overall hydraulics of the channel. Suggested approach is to consider this as a boulder obstruction with the appropriate obstruction level of <20%. Single groyne, Under these circumstances the effect of the length >21%, < groyne on the channel hydraulics will be 50% of the significant. It is suggested that the groyne be channel width treated as a low weir, which extends across the AND complete width of the channel. Therefore it Single groyne, cannot be considered as a roughness unit and length > 50% of may be affected by backwater and a backwater the channel width calculation is required. Multiple groynes Under these circumstances the channel should be treated as a compound channel. The limit of the low flow channel should be taken as the outer limit of the groyne and the elevation of the upper stage the crest level of the groyne. The conveyance should be calculated in the conveyance generator accordingly. Water level below Single groyne Treat as an area of zero conveyance. groyne crest Multiple groynes The zone of the channel between the groynes will be dominated by recirculatory motion and will contribute little to the conveyance of the cross section. The limit of the channel should be taken as the outer limit of the groyne, and the cross section amended to take account of these effects in the conveyance generator. 3.3 Alluvial roughness 3.3.1 Introduction In channels in which sediment on the bed is mobile, the bed of the channel may be deformed by the flow resulting in so called ‘bed features’. These bed features can affect the hydraulic roughness of the bed and so influence the flow in the channel. The bed features are themselves dependent upon the flow and vary in nature and magnitude with the flow. Thus in those situations where bed forms can occur the problem of determining the hydraulic roughness becomes intertwined with that of determining the flow.
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An important aspect of alluvial resistance is the way that it varies with flow conditions. As flow conditions vary the size and shape of bed features may vary, leading to significant variations in hydraulic roughness. For fixed roughness elements it is commonly found that the effective roughness reduces with increasing discharge. In alluvial channels an increase in discharge may lead to an increase in the size and shape of bed features. This change in the bed features may lead to increased form losses and hence increased roughness. Thus in alluvial channels it is quite possible for the hydraulic roughness to increase substantially with discharge, in contrast to the normal behaviour of fixed bed roughness elements. This type of behaviour is by no means universal, for some flow conditions bed features may reduce in size with increasing discharge. This reduces form losses and leads to more rapid reductions in hydraulic roughness than one would expect for fixed bed channels. In situations where a component of the hydraulic roughness arises from alluvial resistance it is important, therefore, to be able to predict the variation of alluvial resistance with flow conditions. 3.3.2 Description of bed forms Bed forms occur on differing spatial scales ranging from tens of millimetres to thousands of metres, with the different scales of bed forms having different properties. The physical mechanisms responsible for the formation of such bed forms are not completely understood but, presumably, different physical mechanisms are involved for the different spatial scales. Definitions of the various bed forms are given below. As was indicated above, bed forms arise from a range of physical mechanisms and, as a result, behave in a variety of different ways. Unfortunately the terminology that has developed does not always distinguish precisely the different possible types of behaviour. Perhaps the most obvious example is of the use of the term ‘bars’. This can be used, as in alternate bars, to describe a system that is mobile and progresses downstream, or, as in point bars, to describe stationary features determined by the channel plan form geometry, or to describe transitory features which appear and disappear in braided rivers. Thus unfortunately the term ‘bar’ does not give a precise indication of the nature of the bed feature alluded to. For a given flow condition the type of bed feature that will be developed on the bed also depends upon the nature of the sediment on the bed and in particular its size. • Ripples: Ripples are small bed forms that are usually less than 0.3m long, in the direction of flow, and less than 0.03m in height. In longitudinal section, ripples vary from triangular to sinusoidal in shape and their size is not dependent upon flow depth. • Dunes: Dunes are intermediate in size, between bars and ripples. Their upstream slope is very shallow and their downstream slope is close to the angle of repose of the bed material. Their height is depth related, typically 10% of the depth. Any surface waves that occur are out of phase with the dunes, that is, minimum water surface elevations occur over the crests of the dunes. The flow over dunes frequently separates just downstream of the crest, resulting in a re circulation zone downstream of the dune. The flow reattaches to the upstream face of the next dune downstream. This separation and re attachment can be
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important in both the energy dissipation and hence resistance induced by the dune and also can have important implications for the movement of pollutants. • Antidunes: Antidunes occur usually in supercritical flow and form a regular, almost sinusoidal, train of bed forms. Individual antidunes migrate upstream whereas sediment movement is high and in the downstream direction. A train of surface waves occurs in phase with the antidunes. Under certain circumstances these waves break in the upstream direction. • Bars: Bars are major bed forms sometimes covering the full channel width and having lengths, in the direction of flow, usually in excess of the channel width and heights comparable with the mean depth of flow. Point bars are deposits on the inside of channel bends and alternate bars emanate from the left and right bank of the channel in sequence. Alternate bars, or parts of them, have also been referred to as unit bars, linguoid bars, side bars, transverse bars, cross channel bars and diagonal bars and riffles. • Alternate bars: In otherwise straight reaches of rivers a sequence of bars may form, known as alternate bars. Each bar is attached to the bank, with successive bars attached to opposite banks. As a result, the low flow channel follows a sinuous course from one bank to the other. • Plain bed / transitional bed: When flow conditions are in transition from subcritical to supercritical the bed forms are confused but mainly small in magnitude. The bed may be devoid of bed forms or it may display an array of low amplitude ripples and dunes or a mixture of all three. • Pool - riffle sequences: The development of alternating areas of deep (pool) and shallow (riffle) flow is characteristic of channels with coarse bed material from approximately a few millimetres upwards. Pools are frequently associated with the outside of bends while on the inside of the bends and extending downstream point bars are often found. • Steps and step pool sequences: In steep, particularly small streams the bed is formed by a sequence of steps, often with associated pools, the height of the step being in excess of the normal water depth. The sediments forming the steps are normally too large to be mobilised by the flow. This form of bed feature is common in the headwaters of many upland UK rivers. The length scales of ripples are related to the sediment size, the length scales for dunes are related to the flow depth while the length scales for bars is related to the channel width. Bars (excluding point bars), ripples and dunes all move slowly in the downstream direction. Flow conditions are usually subcritical. Simons and Richardson (1960) first categorised bed forms as shown in Figure 3.
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Figure 3 Bed forms, as categorised by Simon and Richardson (1960) In practice bed features may take a long time to develop and, in natural streams, where the flows vary continuously, the bed features are rarely in equilibrium with the instantaneous flow. However, it is useful to interpret the Simons and Richardson categories in terms of the relationship between certain types of bed feature and the corresponding steady flow. At low flows, where the tractive shear on the bed is less than that required to initiate movement of the sediment, there is no correlation between the flow and the bed forms. At flows that are high enough to cause modest sediment transport rates, the bed forms are either ripples or dunes. At higher flows washed out dunes or a plain bed situation occurs. At flows which generate very high sediment transport rates antidunes may occur in sand bed channels. The chutes and pools indicated by Simons and Richardson are mainly restricted to some steep gravel rivers and today would be referred to as pools and riffles. 3.3.3 Methods of prediction In general there are two classes of prediction for alluvial resistance. One class of methods predicts the size and shape of bed features and then uses this to determine the hydraulic resistance, see for example van Rijn (1984). Another class of methods predicts the hydraulic resistance but they do not, however, define explicitly what bed forms are present. Instead, they predict resistance based on the physics of sediment movement in terms of sediment and flow properties, see for example, Brownlie (1983), Engelund (1966 and 1967) and White et al (1982). Information on estimating roughness values for the alluvial resistance of pool riffle sequences is contained in Section 3.4. 3.3.4 Development of bed forms When bed forms develop from a plane bed there is normally no change in average bed level. Thus the volume of sediment above the average bed level in the crests of the features is compensated by the volume of the troughs below the average bed level. This
R&D ROUGHNESS REVIEW 23 has implications for the speed of development of bed features. For bed features such as dunes and ripples to develop then all that is needed is for the appropriate volume of sediment within the bed feature to be re arranged on the bed. This volume is normally quite small in comparison with the total volume of sediment transport and so changes in the size of bed features occurs rapidly, for example, during a flood event. The re arrangement of sediment on the bed still takes some time and so if the flow is changing rapidly then it may be that the equilibrium bed form is never achieved. In a laboratory the time to go from a flat bed to the fully developed dune height can be of the order of 1 hour while the development of dune length takes of the order of 2 hours (Wijbenga and Klaasen, 1981 and Klaasen et al, 1986). Van Urk (1982) reported that on the lower Rhine the time lag between flow and dune height was 4 days, with a longer period for dune length. 3.3.5 Spatial variation of alluvial resistance within a cross-section The bed form that develops depends at a particular location on the bed depends upon the local flow depth and velocity. Where conditions vary significantly across a cross section it is possible that the type and size of bed features may vary across the cross section. Thus the hydraulic roughness may vary across the cross section. 3.3.6 Conclusion The information detailed in this section on alluvial roughness is provided as a guide to understanding what alluvial roughness is. This review has not attempted to develop the roughness parameters to characterise alluvial roughness in terms of Manning’s n as the underlying understanding of bed features is an area for further research. However, some useful information has been obtained for pools and riffles and these bed features are treated separately in the following section. For more detailed information on alluvial roughness characterisation and estimation see ‘Sediment transport and alluvial resistance in rivers’, EA R&D Report (in preparation). 3.4 Channel irregularities 3.4.1 Pools and riffles Numerous research studies have been undertaken into pool and riffle sequences in river channels with the emphasis on the morphology and sediment characteristics of the bedform, e.g. Leopold et al (1964), Richards (1976), Keller and Melhorn (1978), Milne (1982) and Hey and Thorne (1986). Less emphasis has been placed on understanding and predicting the natural location and spacing of riffles and pools, e.g. Sephton (1983) and Higginson and Johnston (1989). Pools and riffles in a river channel locally cause the channel slope to deviate from the average channel slope for a reach. This results in marked changes from steep to shallow longitudinal slopes. At low river flows this change in profile can lead to shallow cascade flow over riffles leading to deeper tranquil flow in the pools. Higginson and Johnston illustrated the problems associated with determining the roughness coefficient of a pool riffle sequence using the average channel slope for a reach of river. At low river flows the calculated value of Manning's n changed markedly both with discharge and position. If low flows are important in the design of
R&D ROUGHNESS REVIEW 24 a channel this pronounced variation in roughness coefficient would need careful consideration. However, research by Higginson and Johnston in Northern Ireland, by Richards (1976) on the River Fowey in Cornwall and Pimperton and Karle (1993) has shown that as the discharge increases these changes become less marked. At higher flows, such as bankfull conditions, the bed formation has little or no effect on the Manning coefficient indicating that uniform flow may be assumed. A major design criterion for environmental channels or improvement of existing channels is the ability of the channel to convey flood flows. Determination of the flood conveyance of a channel as set out in this report is dependent upon knowledge of the roughness coefficient at bankfull flow. Data collected at ten sites on the River Blackwater (University of Ulster, 1995) was analysed to give a range of roughness values for pools, riffles and nursery areas. The range of values given is wide in range and is dependent on the discharge and depth at which the roughness coefficient is measured. At low discharges there is a great discrepancy between the roughness values along the reach. The data is also relevant to boulders within channels. 3.4.2 Other irregularities Bends are also irregularities within the channel. The resistance due to bends is dealt with in the Conveyance Estimation System and not within the roughness advisor. In non prismatic channels there is a resistance due to the form loss which is not incorporated into the conveyance calculation. This form of roughness has not been addressed in this report due to a lack of data available to make any useful contributions to the database. 3.5 Tidal reaches In tidal channels the roughness values are changing much more rapidly over a 12 hour period as the tide ebbs and flows and the water level changes. Knight (1981) demonstrated this with measurements in the Conwy estuary where the Manning’s n roughness coefficients varied significantly with stage. Over a 4m range the Manning’s roughness values varied from approximately 0.03 to 0.11. A later study, Wallis and Knight (1984), showed three main trends in the data – a strong stage dependence, a flow directional dependence due to flood or ebb dominated bed forms and a high variability with location along the estuary especially where sand banks were exposed at low water. 3.6 Vegetative features 3.6.1 Grass cover Extensive tests undertaken on grass cover Palmer (1946), Ree (1949), Ree and Palmer (1949) resulted in a Handbook of Channel Design, US Soil Conservation Service, (1954).
The result of the work has been to define a series of relationships between Manning’s n and the product VR, where V is the mean flow velocity and R is the hydraulic radius. The relationship is expressed as a family of curves, each curve defining the other
R&D ROUGHNESS REVIEW 25 principal variable, the physical characteristic of the vegetation. The main physical characteristic is judged to be the height but other factors such as density and uniformity are influential and a value judgement has to be made. Accepting that the vegetation is an organic cover of almost endless variability, the n VR relationship gives sound results in the majority of field cases, Stephens et al (1963), and experimentally, Kao and Barfield (1978). Table 4 gives guidance on retardance categories.
Table 4 Grass cover retardance classes (US Soil Conservation Service, 1954) Stand Average Length Retardance Longer than 30 inches A 11 in to 24 in B Good 6 in to 10 in C 2 in to 6 in D less than 2 in E Longer than 30 inches B 11 in to 24 in C Fair 6 in to 10 in D 2 in to 6 in D less than 2 in E Green and Garton (1983) give equations for the calculation of the Manning’s roughness coefficient in each of the retardance classes. Other publications show a similar trend in roughness characteristics with grass, Chen (1976), Fisher (2002), Graf and Chun (1976). 3.6.2 Trees and Shrubs Individual trees or stands of trees can result in a significant head loss. There have been a number of publications where this has been investigated. Petryk and Bosmajian (1975) theoretically analysed flow through trees and shrubs. In carrying out this analysis they made the following assumptions: • the velocity is small enough to prevent a large degree of plant bending; • the vegetation is relatively uniformly distributed in the lateral direction; • large variations in average velocity do not occur across the channel; • the maximum flow depth is less than or equal to the maximum height of vegetation; and • large variations in flow velocity do not occur over the flow depth. Li and Shen (1973) present an analysis of flow through tall vegetation by considering the drag due to cylinders in the flow. This study is not of direct applicability to the estimation of flow resistance due to vegetation but it does draw some conclusions which are of relevance. The most important of these is that staggered patterns of tall vegetation (trees) are much more effective in reducing the flow than any other configuration with the same number of tall vegetation. Other studies include Komora (1981).
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Klassen and Van Der Zwaard (1974) carried out laboratory experiments to investigate the effect of orchards and hedges on the roughness coefficient of vegetated flood berms. The analysis of Klassen and Van Der Zwaard considered hedges which were not submerged by the flow. Klassen and Van Urk (1985) extended this work by investigating the resistance of drowned hedges. They concluded that in order to calculate the flow through/over submerged hedges, the method of Klassen and Van Der Zwaard should be used for flow through the hedge. The flow over the hedge should be estimated using a short crested weir equation with a discharge coefficient equal to 1.0. There are some excellent publications in different countries for the practical management of trees and shrubs on floodplains: Technology Research Centre, (1994) and Environment Agency (undated). 3.6.3 Floodplains There are several methods for determining the effects of trees and grasses that can be used on the floodplains. Freeman et al (1998) produced an improved methodology for the determination of roughness values for shrubs and woody vegetation. Pasche et al (1983) and Pasche and Rouve (1985) used roughness elements in laboratory tests and investigated the flow characteristics on a vegetated floodplain. Pasche and Rouve (1985) gave particular attention to the problem of non submerged floodplain roughness. Weltz et al (1992) developed a reference table of “effective roughness” coefficients for shallow overland flow with a description of site characteristics. There was no trend apparent in effective roughness coefficient associated with type of vegetation or soil texture. Thornton et al (2000) produced a predictive expression to permit the estimation of the apparent shear stress, average velocity, and depth in both the main channel and floodplain and the blockage caused by the floodplain. 3.7 Vegetation growth and maintenance Part of the issue in assessing and controlling vegetation is the difficulty in predicting the types of vegetation which will be present in the river from season to season and year to year. Fox (1992) gives a recent general review of aquatic plant growth seasonality and ecological interactions. Vegetation maintenance is an important issue for flood defence (Robson 1968, Westlake 1968, Westlake and Dawson 1982). The re growth of vegetation after cutting has been investigated and some semi quantitative and descriptive advice can be determined from this research (e.g. Dawson 1989). The maximum biomass reached for some species in unmanaged waters may be less than in waters where the weed is cut regularly, and may be below the level at which cutting becomes necessary. If weed could be removed earlier in the year, well before the maximum is reached, this may reduce the initiating biomass, delay the time of the maximum and therefore lower the maximum biomass achieved (Dawson 1978a). The cycle of cutting and rapid regrowth is similar to that observed with the typical English lawn. If, however, taller plants and a slightly higher standing crop could be tolerated the vegetation could reach a self limiting maximum biomass. Regular plant removal continually synchronizes the growth of individual plants, causing the times of each plants maximum biomass to coincide over the whole population, Dawson (1978b). In the unmanaged situation, the natural and somewhat erratic decline in the standing crop creates less favourable conditions for regrowth in the autumn. By
R&D ROUGHNESS REVIEW 27 contrast, the removal of plant material in summer allows regrowth in the autumn, producing a higher and better adapted overwintering plant population. This leads to rapid and more advanced growth in the following season, resulting in a higher biomass at flowering times.
For emergent vegetation Haslam (1978) states: • Urtica dioica regrows quickly during the growing season and there is no long term effect of cutting; • Glyceria maxima and Typha angustifolia regrow quickly during the growing season but next year’s crop is reduced by 30%; • Phragmites communis regrowth is quick after cutting during the period of rapid growth (in spring and early summer), and there are no long term effects; • Cutting in late summer means little regrowth and a substantially lower crop in the following year. For submerged and floating vegetation this advice has been given: • no cutting required during the winter as these plants die back either partially or completely; • cutting may be required any time between late spring and early autumn when the plants grow thickly; • Early growing species in Southern England such as Ranunculus may need cutting in April, Haslam (1978); • Spring cut of Ranunculus during its growing period may in fact stimulate further growth rather than control it, Westlake (1968) ; • Spring cut of Callitriche to remove established beds would be very beneficial in its control during the growing season, Soulsby (1974); • Late growing species such as Sagittaria sagittifolia may not become dense until early July, Haslam (1968); • Guidelines given by Haslam and Wolseley (1981) indicate that for floating or submergent weeds the usual time for recovery after cutting is 2 4 weeks to replace the area cover, longer to reproduce the same biomass; • Cutting in late summer leads to little regrowth of strongly seasonal species (e.g. Potamogeton pectinatus ) although non seasonal species (e.g. Callitriche ) in suitable temperatures are unaffected by the date of cutting. The impact of maintenance on the water levels has been demonstrated on a compound channel of the River Roding, University of Bristol (1988). Stage discharge relationships were produced with and without vegetation on the berms. The stage discharge relationship for the cut berm (Manning’s n values 0.05 to 0.06) gives a bankfull discharge of 40m 3/s, whilst for the uncut berm (Manning’s values 0.05 to 0.09) the bankfull discharge is 25m 3/s. Hearne and Armitage (1993) investigated the implications of the annual macrophyte growth on habitat in rivers. During the investigation they highlighted some important issues:
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• The depth in narrow channels is more sensitive to changes in macrophyte biomass than wider channels • The influence of macrophytes on depth and velocity is not as great with steeper gradients • The discharge required to maintain a constant depth reduces by up to a third in the chalk streams monitored as macrophytes become established. Experimental work jointly undertaken by HR Wallingford and the Centre for Aquatic Plant Management (CAPM) investigated the hydraulic impact of vegetation and the impact of cutting Eloda and Potamogeton and its subsequent re growth, Smailes (1996). The results showed: • difference in the re growth rates for the different plants; and • different roughness characteristics for the different plants. Fisher (1995) assessed the impact of cutting aquatic vegetation on the hydraulic performance on two rivers, Candover Brook and the River Kennet. The results from these two sites are site specific but they do give an indication of the likely scale of hydraulic impact of a river of a similar size, shape and discharge capacity. Even though the results may not necessarily be transferable to other rivers the techniques and procedures used can be applied to other river sites. Measurements taken on the Winterbourne stream during the summer showed very high values of Manning’s n, up to values of 1.3 in the reach that was almost 100% choked with vegetation. The vegetation was cut down the centre of the channel by 30%, then 60% and then 100% of the vegetation was removed. There are some general principles that can be applied to vegetation maintenance and the quantitative impact it has on the performance on river channels, Fisher (1996): • Cutting the vegetation down the central part of the channel is hydraulically more efficient than cutting the same percentage amount from one side; • Cutting 80% of the channel vegetation gives almost the same hydraulic benefits as cutting 100% of the vegetation; • The above is generally true for most channels. For channels with a high width/depth ratio e.g. of >10, cutting 65% of the channel vegetation gives almost the same hydraulic benefits as cutting 100% of the vegetation. For channels with a small width/depth ratio e.g. <2 the difference between cutting 66% and 100% of the vegetation would double the percentage reduction in water level.
The Environment Agency in the UK publishes guidelines on aquatic weed control and the function and management of water plants (e.g. Environment Agency 1998). In addition they offer guidelines on river maintenance, which investigate the impact of maintenance on flora and fauna, Ward et al (1999).
3.8 Woody debris Large woody debris has created greater habitat and is incorporated into environmentally sensitive design. Hydraulically debris act as large roughness elements that provide a varied flow environment, reduce average velocity and locally elevate the water surface
R&D ROUGHNESS REVIEW 29 profile, Gippel (1995) and Linstead (2000). The impact of the woody debris on roughness coefficients has been investigated resulting in a method, Shields and Gippel (1995) whilst Linstead (1999) analyses the frequency and effects of such debris for the UK using data from the RHS survey (et al 1998).
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4. REVIEW OF FIELD DATA 4.1 Data availability and usefulness From the literature there are some papers where valuable data sources have been used following in the steps of Manning’s summary (1895). The data from these current papers that have been selected and used in the roughness advisor is detailed in the alphabetically arranged tables in Appendix A. These tables have been referenced before in the previous sections but the tables give a short synopsis of the paper and the data or figures which have been used to generate data for the roughness advisor. The data given is not an exclusive set of the data but it is the data that is considered as being useful for this project. In addition to the data from the literature, data from field study sites to which the authors have had access has also been used. This data has been collected for research studies or PHABSIM studies or for verification purposes for models. Table 5 shows the field data available, the type of data and the source of the data. Table 5 List of available field data sites and sources Individual readings or River and site Source of data over a season River Severn, Bewdley One day HR Wallingford/EA River Derwent One day HR Wallingford/EA River Trent One day HR Wallingford/EA River Avon One day HR Wallingford/EA River Ilam at Manifold One day HR Wallingford/EA River Tanat One day HR Wallingford/EA River Vrynwy One day HR Wallingford/EA River Severn, Montford One day HR Wallingford/EA Bawn’s Burn, NI One/two seasons University of Ulster/ MAFF Abels bridge, River Blackwater, NI One/two seasons University of Ulster/ MAFF Lisdoart Mill, River Blackwater, NI One/two seasons University of Ulster/ MAFF Lisdoart Bridge, River Blackwater, One/two seasons University of Ulster/ MAFF NI Forthill Bridge, River Blackwater, NI One/two seasons University of Ulster/ MAFF Caledon Bridge, River Blackwater, One/two seasons University of Ulster/ MAFF NI Omagh Road, River Blackwater, NI One/two seasons University of Ulster/ MAFF Burn's Bridge, River Blackwater, NI One/two seasons University of Ulster/ MAFF Oona River, NI One/two seasons University of Ulster/ MAFF River Fury, NI One/two seasons University of Ulster/ MAFF Livery Hill, River Bush, NI One/two seasons University of Ulster Conagher Bridge, River Bush, NI One/two seasons University of Ulster Stranocum Bridge, River Bush, NI One/two seasons University of Ulster Clontyfinnan, River Bush, NI One/two seasons University of Ulster Stracam, River Bush, NI One/two seasons University of Ulster Moss side, River Bush, NI One/two seasons University of Ulster Doughery Water, River Bush, NI One/two seasons University of Ulster River Noe, River Bush, NI One/two seasons University of Ulster Upper Derwent Several flow conditions University College Worcester/EA PHABSIM data River Tavy Several flow conditions University College Worcester/EA
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Individual readings or River and site Source of data over a season PHABSIM data River Cole, Birmingham Several flow conditions University of Birmingham River Tame, Birmingham Several flow conditions University of Birmingham River Cole, Swindon Several flow conditions HR Wallingford River Blackwater, Hampshire Several flow conditions University of Bristol/EA River Thames Buscot to Reading Data Mining exercise (see report) River Medway Data Mining exercise (see report) River Eden Data Mining exercise (see report) River Cherwell, Banbury to Oxford Data Mining exercise (see report) River Teme, Knighton to Bransford Data Mining exercise (see report) Bridge River Cam Data Mining exercise (see report)
These sites have been linked with RHS sites whose details are given in Table 6 Table 6 List of available field data sites from the RHS National grid National RHS site no. Distance Relative Relative reference grid ref. (nearest) from position to hydraulic nearest RHS site resistance RHS site (US/DS) Cole SP172879 6732 1564.16 DS 6.2 Cole SP175876 6732 965.91 DS 6.2 Cole SU234935 1111 1736.72 DS 3.9 Blackwater SU882549 4233 694.10 US 7.6 Blackwater SU878568 14000 1384.65 DS 3.9 Jaggers SK162867 23364 1289.51 DS 0.2 Jaggers SK162863 23364 905.12 US 0.2 Noe SK146859 381 542.02 US 7.6 Ashop SK141895 355 2416.92 DS 2.1 Ashop SK164876 355 6041.21 US 2.1 Alport SK156864 23364 238.08 DS 0.2 Alport SK162863 23364 905.12 US 0.2 Tavy 1 SX546822 21703 67.78 US 0.5 Tavy 1 SX532804 20599 326.78 US 0.8 Tavy 2 SX531803 22234 158.71 US 2.3 Tavy 2 SX509784 20646 280.79 US 0.3 Tavy 3 SX482743 21705 1050.21 DS 1.2 Tavy 3 SX466717 21536 461.39 US 2.5 Tame SP029927 692 2331.89 DS 4.8 Tame SP030925 692 2062.39 DS 4.8 Thames B SU23009810 13105 694.52 US 2.2 Thames R SU71807410 7176 1243.38 US 2.6 Medway CH TQ51704050 13721 572.47 US 0.9 Medway_coll TQ52184128 10800 1.89 DS 1.7 Eden pen TQ55201437 1395 1270.91 DS 2.5 Cherwell Ban SP45804100 6945 5763.46 DS 14.0 Cherwell Oxfd SP52100610 1078 2213.51 DS 1.1 Teme SO290724 6762 3758.16 US 0.5 Knighton Teme BransBr SO803533 6849 3104.88 US 2.7 Cam TL46605060 6866 158.78 DS 13.6
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Data gaps The gaps in data which have been identified whilst undertaking this review can be summarised by the points below. • Field data on variations with roughness with depth are lacking and this area needs further exploration; • Data on temporal variations of vegetation is lacking; • There is extensive data on some kinds of vegetation but the information on the impact of, particularly, emergent vegetation is very sparse; • Further data is required on the relationship between coverage, biomass and blockage of different types of vegetation and the roughness coefficient; • Some types of floodplain vegetation e.g. clumps of hedges and their impact downstream needs to be more widely explored; • Alternative methods for estimating roughness need to be more widely considered and backed up with field data, especially roughness due to vegetation e.g. blockage of vegetation, drag coefficients, turbulence modelling. The elements which need to be measured to gain a better understanding of roughness are as follows: • Topographic data including accurate measurement of water surface slope; • Flow and level data over a good range of inbank and out of bank conditions; • Details of vegetation including type, coverage, blockage, biomass, and sketches of locations both through the vertical and lateral axes; • Details of growth patterns of vegetation through the season and after different cutting patterns in subsequent seasons; • Details of how the growth of vegetation is affected and how the vegetation moves with the water flows including “waving” stands of floating vegetation. 4.2 Further data collection and research Further data collection is essential especially on the different vegetation types. The links between the growth of vegetation, its coverage, blockage, biomass and the form resistance of the vegetation needs much greater research which will require extensive field data collection programmes. Research into the area of floodplain vegetation and the interaction between different vegetation types is required. This would include: • Seasonal variations in floodplain vegetation • Impact of hedges and fences, and their different orientation, on head losses across a floodplain • Downstream influences due to turbulence of different types of vegetation e.g. wooded areas, shrubs, and mixed vegetation. This would include extent of influence, influence on other vegetated areas within the “wake” of the obstruction, and influence under different flow conditions • Building and other macro roughness elements on the floodplain
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• Investigation of relationship between slope, grain size distribution, size of channel and the resistance of a channel using field data. Many of the methods developed more recently have investigated the force balances within a vegetated channel. Scientifically this method is more robust than the use of the empirically developed n VR relationship. Most of the work within this area has been undertaken in the laboratory using rods to represent vegetation. The ideas should now be developed within 2D models, field data collected to verify laboratory experiments, and field trials undertaken to develop existing methods using real river data. Two dimensional models are increasingly being used in this area especially to understand the fundamental mechanisms behind the interactions of flow and vegetation. Models have been used effectively in describing and understanding the lateral momentum transfer across vegetation in different locations within the channel. Data collected in the field as described above would be useful for verification and calibration of these models. Links with sediment movement and the ability of sediment to be trapped within vegetated regions could be explored using 2D modelling techniques. Manning’s equation is used internationally for predicting roughness values in non vegetated and vegetated channels. It is difficult to determine the roughness other than by measurement and the values change with depth. It may be that we can find a more appropriate way of describing the roughness of the channel. It would be difficult to try and change a universal concept and international culture but it may be that we need to investigate a more appropriate index for the impact of vegetation The resistance of a channel to flow is due to a number of different types of resistance including skin friction and form friction. This review has concentrated on these two aspects, as they are the most significant. The skin friction is due to the bed surface and the form friction due to any obstructions such as boulders or vegetation. The Manning’s n roughness coefficient is a measure of the “total” roughness of the channel and includes elements of the skin and form friction. This report separates out the different types of friction from the “total” roughness values given in the literature. This has not been an easy task and has often been based on experience rather than on exact research that shows how each part, skin or form, contributes to the whole. The research in this area is needed to demonstrate how the overall or “total” roughness is made up from the constituent parts. 4.3 Concurrent research projects There are a number of current research projects in the area of flood plain vegetation that will provide improved information on roughness. As information from the projects has not yet been reviewed and published it has not been included in this present review. However, some information on two of the relevant EC funded research projects is provided below and it is expected that the results of these and other projects will be included in future updates of the roughness report and roughness advisor. 4.3.1 ECOBAR2 Project The EC funded ECOBAR project is currently examining: • The link between hydrology and biodiversity on flood plains;
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• The resistance of woody vegetation on flood plains; • Socio economic and institutional issues which influence biodiversity and river restoration. The project has so far shown that judicious afforestation of the catchment and flood plain has flood defence benefits. Further work is being undertaken to assess the consequences of allowing such vegetation to develop. This involves a field measurement programme, two dimensional modelling, and flume experiments. A group at Cambridge University in the Department of Geography and the Department of Plant Sciences coordinates the project. The lead contacts are Professor Keith Richards and Dr Francine Hughes. The project website can be found at: http://www flobar.geog.cam.ac.uk/members/cambridge.html 4.3.2 RIPFOR Project The EC funded RIPFOR project – ‘Hydraulic, sedimentological and ecological problems of multifunctional riparian forest management’ is a collaboration between a number of European universities and institutions including the Freie Universitaet Berlin, University of Agricultural Science Viena, and the Universitaet Karlsruhe. The project is concerned with the optimisation of Riparian Forest Management, with special emphasis on hydraulic and sedimentary problems occurring in floodplains. The influence of riparian forest vegetation on the overall flow field and sediment transportation/ deposition is being studied. Guidelines will be worked out for the implementation of new floodplain forests and the management of existing ones: retention of high floods, protection of river banks, improvement of water quality, habitats for plants and animals, recreational areas for the local population. The work is being performed in a number of stages including field studies, laboratory studies, numerical and physical modelling, and ecological fieldwork. Further information can be found on the project website at: http://www.geog.fu berlin.de/~ripfor/project.htm
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5. IDENTIFICATION OF RIVER TYPES AND VEGETATION MORPHO-TYPES Rivers and streams which are similar in their physical characteristics and their vegetation can be associated using the national data set obtained through the national survey of river habitats (River Habitat Survey, Raven et al 1998). This national assessment includes data on in channel and bank side aquatic vegetation together with flood plain land uses. Data is also available on physical parameters, substrates and in channel sediment or erosion features such as sandbars or eroding cliffs. In the absence of surveys for reaches on which hydraulic planning or assessment is required, this supporting data can be used to predict the likely type of vegetation or other features typical of the reach under consideration. It is able to do this through the detailed surveys that were performed and an extensive analysis of the common geomorphological parameters for similar types of stream or river and morphologically similar vegetation group. This data is made available in the Roughness Advisor as the basis for advice in the absence of a site survey. 5.1 River Habitat Survey - hydromorphological features The physical habitats of British rivers have been sampled on the stratified basis of random 500m river segments from within all 10 by 10 km grid squares within the UK. Surveys recorded some 25 items in cross section separated at 50m intervals. This included the predominance of flow types, bank and bed substrates, fluvial features, and any modifications. This was combined with the morphological types, aquatic vegetation, the structure of bank vegetation, and land use, together with an overall assessment of the 500m reach of the general habitat features within 100m, including channel features, management and adjacent land use. Three sites per grid square were chosen in England and Wales and the survey was undertaken in 1994 96 (totalling 4530 sites). Two sites per grid square were surveyed in Northern Ireland for 1995 96(246) and one site per grid square was surveyed in Scotland over two years 1995 96 (778). Comparisons were presented on a one site per square basis. However, since the initial survey additional surveys have continued on a regular basis although they have been targeted at particular schemes and investigations and there are now some 18,000 surveys available for reference on a national database. Grouping and classification of the physical habitats of the rivers of Britain during the development of River Habitat Survey (RHS) was considered necessary as a framework upon which to associate the probability and frequency of occurrence of their respective characteristics or typical natural physical habitats, in contrast to the results and consequences of modification. Following several attempts using a range of modern multivariate and principal component analyses and various combinations of data, a system was selected (Jeffers 1998). Thus current classification is based upon data sets for each RHS site obtainable nationally from maps which include the position, altitude, gradient, deep and surface geology. These are surrogates for the availability, quantity and timing of delivery of water, and for stream power from variables such as stream size, height of and distance from source. Analysis of the main drivers and their derivation from available data, mainly the map derived data, was analysed to give an awareness of the errors and limits of predictability within each classification system. The relative advantages and usefulness of the classification system in the development of comparative systems for habitat modification and habitat quality is still undergoing
R&D ROUGHNESS REVIEW 36 development for general applications, such as for quality classification use within the EU Water Framework Directive. In addition, two indices have been developed allowing classification of the modification of a channel and also the quality of natural features in each reach. One is the Habitat Modification Index. This is a transparent count of the numbers of modifications to each bank or the channel at each of the 10 ‘spot’ transects or in the absence of any modifications recorded then it is a check on the occupance of modification from the assessment of the full 500 m. The Habitat Quality Index (HQA) and its banded Habitat Quality Assessment (HQA), is currently based upon subjective rules of the occupance or absence of features typical of the particular type or class of river. These two indices are of use for assessing any engineering work undertaken in a section. They can be linked with the assessment of nationally funded channel modification and maintenance, which were called the MAFF Capital Works Schemes, undertaken between 1930s 1980 and mapped by Brookes at al (1983). Thus historic and probably ongoing schemes that have affected channels and changed them from near natural, with the associated typical changes to vegetation etc, can be incorporated in channel redesign schemes. There is scope to incorporate further developments to separate the re naturalisation of higher energy channels from those of lower or relatively stable channels especially those in clay and some lowland areas. 5.2 River Habitat Survey - vegetation morpho-types Vegetation was assessed by the RHS survey as the presence or extensiveness of vegetation morpho types at the time of survey i.e. late spring or early summer, in 10 regularly spaced transects of 10m in width. Vegetation cover when present represents >1% cover of the streambed in the 10m broad transect across the channel whilst extensive cover is >33%. The distribution of vegetation morpho types are expected at the national level whilst most groups are reasonably well represented by type. There are ten broad vegetation morpho types of aquatic and marginal plant species of similar form or function in the river or riparian corridor. These groups are not those with similar morphological character as described in textbooks and used for taxonomy (Table 8). For example, rooted plants elongate in form with finely divide or elongate leaves living mainly submerged and rooted in the main river bed in medium or high water flows are grouped together, but separated from those with, for example, broad leaves which float at or near the water surface in slower flows but are otherwise rooted in the main channel. In RHS, the purpose of the recording is to provide information on the range of functional habitats, which the vegetation may be providing for invertebrates and other animals (this is especially important in rivers with limited structural diversity). In the absence of surveys for a particular river reach, the prediction of the likely morpho type of vegetation typical of the reach is achieved using the PCA relationship of geomorphological driving variables (above) to determine the nearest 100 sites in this PCA space nearest the actual survey site for that 10 by 10km square, and tally the mean numbers of each morpho type of vegetation when present or extensive. This is repeated for each 10 by 10km square to give the probabilities for each vegetation morpho type group (as a percentage for each group) for all 10 by 10 km squares in the UK and
R&D ROUGHNESS REVIEW 37 incorporated in the Roughness Advisor. The southwest corner of the regular 10km divisions of the NGR map is used to mark typical values for that grid square. Initially, a complementary way of investigating the effects of vegetation had been proposed based upon a tabular system which would enable the presence of different types of vegetation known or likely at a particular site based on the RHS data and possibly linked to channel type (Table 7). The types of vegetation “a” to “i” are detailed further in Figure 4. These categories of the types of vegetation frequently found in different channel types did not have such a high probability as the aforementioned method but normally reproduced the broad picture whereby particular vegetation combinations were more closely associated with some river types and not with others. Clear divisions are not apparent and were difficult to incorporate in the table. Although more river types could be added into these tables and more dominant types represented by shading in darker colours, the use of the PCA method was clearer and closer to the best estimate, although it is more complex. Table 7 Types of channel and likely vegetation in those channels
Vegetation type Channel type a b c d e f g h i
Steep streams Mountain valley rivers Chalk rivers Lowland riffle dominated Vegetation types: a. liverworts, mosses, or lichens b. emergent broad leaved herbs c. emergent reeds, sedges, or rushes d. rooted floating leaved e. free floating f. amphibious g. submerged broad leaved h. submerged fine leaved i. filamentous algae
Future developments could extend the predictive potential to stream and river size, as there is sufficient data in the database to enable this analysis An area for further research is to look at combining the vegetation database with a chemical database to look at the effects of water quality.
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Table 8 Description of RHS vegetation morpho-types Proposed channel Description of vegetation type Occurrence Relative vegetation [based on RHS Manual with examples of type in Hydraulic morpho of typical species] UK Resistance types present/ extensive 0 None OR No vegetation present Not visible Submerged plants not visible in very turbid water. OR channel not visible (e.g. culvert) 1 Free floating Plants free floating at or under, the water 2 0.3 surface. Often in the margins or less commonly across channels in very slow flowing or near static watercourses. Not rooted to the channel bed and easily washed out but may accumulate on instream structures restricting flow. Examples include Duckweeds (Lemna spp.), Frogbit ( Hydrocharis), Hornwort (Ceratophyllum) and Water Soldier (Stratiotes). 2 Filamentous Obvious areas of filamentous alga either 32 3 algae attached to channel bed or attached or coating aquatic plants. Often easily washed out. Often in nutrient rich water. Little known about hydraulic effects on restricting flow, but algal films may possibly smooth boundaries and enhance flow. Examples include Blanketweed (Cladophora), Mole Pelt ( Enteromorpha) etc. 3 Mosses Smaller plants attached to larger more 32 3 stable substrates in channel and typical of in stream boulders in higher energy streams. Also on more vertical shaded banks in slower flowing streams. Examples include mosses (e.g. Fontinalis) , liverworts (e.g. Scapania ) and lichens (e.g. Collema ).
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Proposed channel Description of vegetation type Occurrence Relative vegetation [based on RHS Manual with examples of type in Hydraulic morpho of typical species] UK Resistance types present/ extensive 4 Amphibious Rooted at edge of river, or on the bank. 8 0.4 Shoots or leaves trail into, or across, the water. More common in slower flowing stream cp tree roots. Examples include Amphibious Bistort (Persicaria amphibium), Creeping Bent grass or Fiorin ( Agrostis stolonifera), Sweet grass ( Glyceria fluitans), Marsh Foxtail ( Alopecurus geniculatus), Water For get me not (Myosotis scorpioides). 5 Emergent Emergent narrow leaved monocotyledons 22 4 Reeds (reeds, sedges & rushes) rooted below water. Normally on channel margins and adjacent wetlands. Often inundated in floods. Occasionally overhanging in deeper water. Examples include Branched Bur reed (Sparganium erectum), Reedmace (Typha), Norfolk Reed ( Phragmites), Reed Sweet grass ( Glyceria maxima), Sedges ( Carex spp.), Rushes ( Juncus spp.) and Bulrush ( Schoenoplectus spp .). 6 Floating Plants with floating surface leaves only 3 1 leaved and rooted in the channel bed. Typified rooted by water lilies in deeper slower more turbid rivers. Can rapidly increase hydraulic resistance for small increases in flow. Examples include either broad leaved e.g. Yellow Water Lily ( Nuphar lutea), Broad leaved Pondweed (Potamogeton natans) or linear or strap like leaved e.g. Un branched Bur red (Sparganium emersum).
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Proposed channel Description of vegetation type Occurrence Relative vegetation [based on RHS Manual with examples of type in Hydraulic morpho of typical species] UK Resistance types present/ extensive 7 Emergent Broad leaved or herbaceous plants with 17 2 broad leaved leaves and flowers typically found rooted in shallower lowland rivers. Grow out of the water above normal water levels predominantly in the summer and autumn. Extending outwards from the channel margins or more centrally in the main channel if shallow, and also colonising other submerged plants. More often in managed channels or nutrient rich waters with mean flows less than 0.5 m/s. Examples include. Fool’s Water cress (Apium nodiflorum) and Water speedwell ( Veronica spp.). 8 Submerged Vegetation with underwater leaves no 5 1 broad leaved more than four times longer than they are broad. Rooted in the main riverbed. Some part of the plant, or some leaves, may reach the surface but the majority is submerged. Typical of deeper water with or slow or moderate water flow and a stable river bed which may be overlain by organic material. These channels are often managed. Examples include the submerged ‘cabbage’ leaves of Yellow Water lily ( Nuphar lutea) , Perfoliate and several other broad leaved pondweeds (Potamogeton perfoliatus, lucens, alpinus etc .) , Canadian Pondweed (E lodea canadensis ), Starworts ( Callitriche). Submerged Submerged plants with narrow, 12 3 linear leaved unbranched, laminar leaves (blade/strap/belt shaped) that are either totally submerged or have just their tips or upper parts floating on the surface, while rooted in the main river bed. The most typical examples are Unbranched Bur reed ( Sparganium emersum ) and the underwater variations in the leaves of Arrowhead ( Sagittaria) , Bulrush (Schoenoplectus spp.) and Flowering Rush ( Butomus umbellatus ).
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Proposed channel Description of vegetation type Occurrence Relative vegetation [based on RHS Manual with examples of type in Hydraulic morpho of typical species] UK Resistance types present/ extensive 9 Submerged Rooted submerged plants with fine AND 38 8 fine leaved branched leaves. Often in large stands elongated in direction of flow. Predominantly growing in spring and summer. Typical of lowland streams with moderate or high flows in summer. Examples include the feathery leaves of Milfoil ( Myriophyllum spp.), tough, short and sparse branching of Hornwort (Ceratophyllum) , and the elongate stems of most crowfoot ( Ranunculus ) species and Fennel Pondweed. ( Potamogeton pectinatus) .
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Figure 4 Distribution of RHS channel vegetation types and species a) liverworts, mosses or lichens b) emergent broad leaved herbs; c) emergent reeds, sedges or rushes; d) rooted floating leaved; e) free floating f) amphibious; g) submerged broad leaved; h) submerged fine leaved; i) filamentous algae; o = present 5%, • = 33% extensive Plant biomass changes not only seasonally, but also following flood events. It is therefore important during re design to establish at the planning stage if the velocity excess above the design level is exceeded. If it is, then this velocity should occur at a time of the year that produces only a minimal effect. Alternatively, another species with a higher velocity tolerance may be present and would cope with the conditions. Conversely, intermittent higher than normal velocities could be used as a technique to control biomass although practical problems could arise with this scenario as well as the obvious ecological ones. General values have been given for the environmental effects or tolerances of water (Butcher 1933, Westlake 1975, Lejmbach 1977), for specific studies on stressed mixed communities of instream rooted morpho types (Barrat Segretain 2001), and for a comparison of broad morpho groups (Biggs 1996). The largest data set however has been made available by further analysis of data on aquatic macrophytes collected concurrently by CEH during several thousand RHS surveys. This dataset has been partly analysed to determine the velocity requirements and tolerances for examples of
R&D ROUGHNESS REVIEW 43 the species in each RHS vegetative morpho type group. The analysis indicates that a rider should be applied to the use of seasonal data on hydraulic roughness following larger flood events (Table 9). Data for indicative levels of the critical lower velocity for plant growth, typical mean velocity and upper washout mean in channel velocity, should be applied when testing such scenarios because there may be major changes in overall channel resistance. Table 9 Generalised critical lower velocity for plant growth, typical mean velocity and upper washout mean in-channel velocities for RHS vegetation morpho-types Manning’s n roughness RHS vegetation morpho-type values lower mean Washout Not visible 0 5.0 5.0 Free floating plants typically algae or duckweeds 0 0.1 0.6 Filamentous algae attached shallow nutrient rich waters 0 0.2 0.5 Mosses etc, attached to bed or banks 0 0.5 2.0 Trailing bank side plants 0 0.3 0.6 Emergent reeds, rushes, flag and large grasses 0 0.05 [0.3] [above ground parts] Floating leaved rooted, typically water lillies in deeper 0 0.1 0.3 slower waters Emergent broad leaved rooted plants, like water cress or 0 0.3 0.5 water parsnip Submerged broad leaved, Pondweeds (0.6 1.2m) 0 0.2 0.5 Submerged fine leaved, chalk streams, shallow water 0.2 0.35 0.75 crowfoot, pondweeds 0.2 0.6m medium depth rivers 0.6 1.2m deep, regular 0.2 0.35 0.75 management medium depth rivers > 1.2m deep, some management 0.2 0.4 0.8 5.3 Conclusions For more precise determination of hydraulic resistance, exact procedures should be established to record the position and extent (density) of larger in channel plants, as plants may vary from moment in their position in the water column. Similarly, an exact methodology should be established for the depth and position of vegetated boundaries for smaller plants e.g. algae in as similar way to that for large sediments e.g. boulders.
In the future, issues such as the effects of mixed species may need to be refined for some stream or smaller river types. For instance, mixed species of similar morphotypes and mixed stands of different morphotypes of vegetation seasonally overgrow each other (e.g. water Crowfoot and Water Cress) and influence each others potential growth and thus hydraulic resistance and management requirements (Dawson at al 1978).
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6. ROUGHNESS ADVISOR 6.1 Methods and data used in the roughness advisor The method adopted in the roughness advisor is to give unit roughness values for different components in different types across the channel and to combine them in a suitable manner within a type. The combined value is then fed into a conveyance generator which divides the section representing a reach into panels, uses the roughness given in each type, and adds in factors for turbulence, secondary currents and sinuosity, especially at the interfaces between the channel, bank and floodplain zones. From the literature we can see that there are many different techniques which have been developed for the determination of roughness characteristics in channels. Many of the approaches in the literature have been developed for a particular aspect of river channels or floodplains, for example vegetation, boulders, or large scale roughness elements. There are one or two methods which try and cover and combine all different aspects of roughness (Chow 1959, and Cowans, 1956). These methods give and combine values of roughness with values for the contributions which are made by features within the channel and floodplain. Many of the measured values of roughness given in the literature are combined values of roughness. Trying to disaggregate the combined roughness values into unit components due to different features such as substrate, vegetation etc is a difficult task. Since Cowans and Chow, then there have been many more studies which give us greater insight into the roughness of different features especially vegetation. The approach within the roughness advisor for selection of unit roughness values is via a large database of roughness values based on Manning’s n roughness. The values of roughness for the database have been extracted from various sources in the literature and this is explained in more detail in Section 2 of the report. The values extracted from the literature are given as an upper and lower value also. The mid, upper and lower values cover the range of roughness values expected within these natural systems. For a channel reach, the three roughness types bed, bank and floodplain have been established. Within each type there can be subdivisions to account for differences across the type. Each type will be given a description with users able to add their own descriptions. Within each type or panel subdivision the roughness will be “made up” from the different components . For the bed and bank types the three components are material, irregularities and vegetation . The components for the floodplain will be similar with bed material being replaced by ground material. The three components have different properties which can be selected and these give a description of the channel, and the mid, lower and upper values of roughness for that roughness property. For each component a photograph will be shown to illustrate the component. For example when the component was a sand bank the picture shown in Figure 6 would be displayed:
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Figure 5 Example of a sandbank A roughness type may be divided into different panels with different roughness values if there are different features across the reach. For example, these panel divisions might be where there are areas of clear channel where the substrate is the only roughness influencing parameter and then sections where there is vegetation which is contributing to the roughness value. In the situation where there is a mixed population of vegetation present the user may split the roughness type into panels at the boundary of the vegetation type and assign different roughness values to the different panels. If the vegetation is mixed with no clear boundary laterally, the roughness value for the dominant vegetation type will be selected. Each mid roughness value given is nominally for a depth of water of 1m within that channel. This has been selected as being a representative depth for channels in the UK. The roughness within the channel varies with depth. In general, and from the data collected, the roughness increases as the depth decreases according to a power law relationship along the lines of depth = a(roughness)b (18) where a and b are constants. From Manning’s equation and the data collected in the field we get the relationship
n1 nd = 3 (19) d 2 where n 1 is the roughness value at a depth of 1m, and n b is the boundary roughness coefficient. This means that the values of a and b in the above equation are: a is the value of the roughness at 1m raised to the power of 2/3 and b is ( 2/3). Appendix B gives some of the background and data to the variation in roughness with depth.
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The upper and lower values of roughness are also varied in the same manner with depth. The variation of the roughness values with depth have been checked against measured data and Figure 6 shows the result for a reach of the River Blackwater in Northern Ireland with cobble bed river with boulders.
6
5
4
3
depth (m) depth 2
1
0 0 0.05 0.1 0.15 roughness mid lower upper Figure 6 Variations in roughness values with depth for the River Blackwater in Northern Ireland The values of roughness used in the roughness advisor are given in the following sections. These are divided into the four components of bed material, man made, irregularities and vegetation. The values given for each component in a type are unit roughness values and are therefore to be combined. The approach to be used for combining the roughness is a root mean square approach where the unit roughness values can be combined by the square root of the sum of the squares of the unit roughness values. n 5.0 2 n = ∑()n i (20) i=1 The combined value for a zone or a panel within a zone will be termed the local roughness . For example if within a type, or a panel within a type, there is a gravel bed river with 50% boulder coverage, the values of roughness for a gravel bed river and for an “irregularity” of 50% boulder coverage will be combined to give an overall roughness value for that zone.
6.2 Limitations of the proposed method The method in the roughness advisor is to give unit roughness values for different components in different zones (bed, bank and floodplain) across the channel and to combine them in a suitable manner within a zone. The combined value, which is called the zone roughness, is then fed into a conveyance generator. The conveyance generator divides the section, representing a reach, into panels, uses the roughness given in each zone or sub zone, and accounts for turbulence, secondary currents and sinuosity especially at the interfaces between the channel, bank and floodplain zones.
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The combination of the unit roughness values within a zone is still under discussion and a decision is required on the method(s) to be used. The various options are outline here. Several methods of combining unit roughness values have been considered (i) direct addition of ‘n’ values
n = n1 + n2 ..... + nn (21) This is similar to the Cowan’s method (Cowans, 1956), where the different unit values from contributions such as substrate, vegetation, irregularities, obstructions are summed. This method has merits in that it is simple to understand and apply. There are differing opinions on whether it over or under estimates the combined roughness. This may depend on the depth of water in the channel or the size of channel under investigation. It may be possible to “adjust” the unit roughness values to overcome this problem. (ii) The unit roughness values can be combined by the square root of the sum of the squares of the unit roughness values n 5.0 2 n = ∑()n i (22) i=1
(iii) Method based on the roughness being inversely proportional to the velocity, and the friction loss being related to the velocity squared
1 n 1 = (23) ∑ 2 n i=1 ni
The field data from the literature and collected by the authors or sources known to them calculates a zone roughness value or an engineering roughness value. The data has been disaggregated to give unit values and then must be summed again according to one of the methods above. The first method gives roughness values which under estimate at low flow and over estimate at high flows. It gives equal weighting to each roughness element. It was decided to discard the first method. The second method gives more priority to the most dominant roughness element and gives good matching with measured values – see Section 6.6. Method three gives high or low values if more extreme roughness values are included. Therefore Method ii) was chosen for combining unit roughness values. 6.3 Definition of types 6.3.1 Bed type
Material The values for the channel substrate roughness are based on data and information from a wide range of references. The data from these references has been extracted and collated into a consistent pattern in which all the values given in the references lie within the upper and lower bounds. The database of roughness values is given below in
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Table 10. This section will describe from where the data has been extracted to produce these values. Table 10 Values of roughness for different types of bed material Channel substrate Manning’s n roughness values (with d 50 values) Mid Lower Upper Bedrock 0.025 0.023 0.028 Cobbles (64 256mm) 0.055 0.04 0.07 Coarse Gravel 0.035 0.022 0.04 Gravel (2 64mm) 0.03 0.028 0.035 Fine gravel 0.024 0.02 0.028 Sand (0.2mm) 0.012 0.01 0.016 Sand (0.3mm) 0.017 0.015 0.022 Sand (0.4mm) 0.02 0.017 0.025 Sand (0.5mm) 0.022 0.018 0.027 Sand (0.6mm) 0.023 0.02 0.03 Sand (0.8mm) 0.025 0.023 0.032 Sand (1.0mm) 0.026 0.024 0.033 Coarse sand (1 2mm) 0.028 0.026 0.035 Silt 0.022 0.02 0.025 Clay 0.02 0.018 0.023 Peat 0.02 0.018 0.023 Earth 0.02 0.018 0.023 Firm soil 0.02 0.018 0.023 Concrete 0.02 0.018 0.022
The values in Chow (1959) form the backbone of the substrate values chosen. These values are given in the reference sheet in Appendix A. The values given are wide ranging especially for different finishes of concrete and these could be used in the roughness advisor if a more detailed description were required. Cowans (1956) also gave a description of the bed substrate and values for those substrates can be found in the reference sheet in Appendix A. Butler et al (1978), show a range of roughness values with discharge (see Appendix A) in an urban channel with a variety of substrate. The range of roughness values when the depth would have been at around 0.15m are from 0.02 to 0.06, depending on the type of substrate. The lower values fit well within the bounds in Table 10, although the value of 0.06 is much higher due to influences of other roughness factors and irregularities within the channel. The values in this paper are higher as the depth in the original study was much lower than the 1m depth for which the substrate values given above are intended. Barnes (1967) gives a wide range different river types for river channels in the USA. Roughness values range from 0.024 to 0.075 for rivers with different substrates and obstructions/irregularities. The Barnes reference sheet in Appendix A shows the values and the descriptions for the channels in this reference. In a similar way Hicks and Mason (1991) give values for rivers in New Zealand which are given in the reference sheet in Appendix A.
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Limernos (1970) measured roughness and bed material size in eleven natural streams in California. This was to test the hypothesis that the value of Manning’s roughness coefficient may be related to some characteristic size of streambed particles and to the distribution of particle size. The reference sheet for Limernos in Appendix A shows the Manning’s n roughness coefficient and the d 50 particle size for the streambed particles. In addition the type of sediment (sand, gravel etc) has been added to show the values from Limernos compare with those to be used in the roughness advisor given in Table 10. The values given in the Limernos reference show that in some instances the data would fit well with that suggested in Table 10. For sites where the roughness values measured by Limernos are higher than those in the table, the rivers may have had some boulders or other elements of roughness such as irregularities, which are not defined within the paper. Hey and Thorne (1986) obtained data from 62 stable gravel bed river reaches in the United Kingdom. The data was used to derive equations relating reach average and riffle values of width, mean and maximum depth, slope, velocity, sinuosity and riffle spacing to bankful discharge and bed and bank material characteristics. Some of the channels had some vegetation on the banks which was classified in types 1 to 4 with type1 being grassy banks with no tree cover, type 2 being 1 5% tree/shrub cover, type 3 being 5 50% tree/shrub cover and type 4 being over 50% tree/shrub cover. The reference sheet for Hey and Thorne, showing the data, can be found in Appendix A where the sediment type has been added according to the d 50 type measured.
Irregularities These values which are included in this component are those features which are in the channel naturally and cause an obstruction to the flow. Boulders can be in the channel because they have been placed there by man so the values for boulder coverage will also appear in the man made section. This component also includes pools and riffles which cause variation in the flow in a longitudinal direction and therefore have a variation from a typical flow pattern in terms of roughness. There have been various sources of data for irregularities in channels due to boulders. There are many examples within Hicks and Mason (1991) and Mason (1967), and the University of Ulster (1995) of channels with boulder coverage. Cowans (1956) gives a contribution to the overall roughness value due to boulders. Bathurst (1978) has shown the flow resistance for channels with large scale roughness to be a function of channel shape, roughness spacing and relative roughness and Thompson and Campbell (1979) related resistance solely to relative roughness. The data from these papers has been collated and values determined for the actual contribution due the boulder obstruction on the overall, combined roughness value. It is the unit roughness value due to the coverage of boulders, which has been included in Table 11 below.
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Table 11 Values of unit roughness for irregularities such as boulders and pools and riffles
Range of unit roughness values Type of Description irregularity Mid Lower Upper
Exposed 0 20% of bed covered 0.017 0.005 0.03 boulders 21 50% of bed covered 0.037 0.015 0.055 Over 50% of bed covered 0.045 0.02 0.06 Pools and riffles 0.02 0.01 0.03 The values for pool and riffle sequences given in Table 11 have been determined from the following papers: Higginson and Johnston (1989), Richards (1976) on the River Fowey in Cornwall and Pimperton, Karle (1993) and University of Ulster, (1995). Values have also been suggested as guidance for irregularities such as ripple, dunes and antidunes. The data source for these values is Simons and Richardson, 1961. In addition the values in this component are those features which are in the channel due to human interferences and cause an obstruction to the flow. The types of obstruction are urban trash and groynes of a variety of types, Table 12. The data for determining these values in virtually non existent but much work has been done on optimising the design of groynes for the purpose of providing bank protection. See for example Jansen et al (1979), McCollum et al (1987), Bhargava and Singh (1981), Ahmad (1951), and Miller et al (1983). Guidelines were developed by Seed (1997) on the geometry of groynes for river training. This work has concentrated on investigating the effect of varying the length, crest height, angle and spacing of groynes on their efficiency as bank protectors. The values given in the roughness advisor have been determined from knowledge of the how groynes perform and the impact on an obstruction on the overall roughness when compared with data on large scale roughness elements.
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Table 12 Values of unit roughness for irregularities such as urban trash and groyne fields
Range of unit roughness values Type of obstruction Description Mid Lower Upper
Urban Trash Low 0.01 0.007 0.015 Med 0.035 0.035 0.05 High 0.045 0.035 0.06 Single Groynes with <20% channel width 0.015 0.01 0.02 water level above 21% to 50% of channel width Treat as low stone weir
>50% channel width Treat as low stone weir Single Water level above groyne crest Zero conveyance – very Groyne high roughness value Multiple groynes Treat as a compound channel in CES
Alluvial roughness Values of ‘n’ for alluvial roughness are presently not included in the Roughness Advisor. Advice is provided to the user if they wish to include such information in their model and they are referred to ‘Sediment transport and alluvial resistance in rivers’, EA R&D Report (in preparation).
Vegetation ‘n’ hydraulic resistance values for aquatic vegetation have been grouped into the RHS morpho type grouping as supporting data both on national distribution and by physical dimension is available. These groups are also sufficiently detailed to match the variation and the numbers of studies available i.e. current knowledge. Seasonal data is incorporated in the Roughness Advisor. Filamentous algae when attached in shallow nutrient rich waters may be considered to reduce the resistance, if the correct standard methodology for depth measurement is used (e.g. Dackombe & Gardiner 1982). Such effects on bed roughness for larger substrates have been analysed by Nikora (2001), conversely Nikora et al (1998) report that the presence of periphyton i.e. fine non visually filamentous layer may increase the bulk flow resistance by 20 50% which may relate to increased flow heterogeneity shown from turbulence analysis.
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Table 13 Table of roughness values for aquatic vegetation by RHS morpho-type Manning’s n roughness values Aquatic vegetation by RHS morpho-type minimum mean maximum None or IF none visible Check prediction from RHS dataset 1. Free-floating plants typically algae or duckweeds medium deep drainage channel 0.01 0.03 0.04 [d = 1.1 2.5m, v = 0.1 0.6ms ] 2. Filamentous algae attached shallow nutrient rich waters d = 0.05 0.5m, low velocities 0 0.015 0.05 Mosses etc, attached to bed or banks d = ~ 1m 0 ~ 0.03 Trailing bank-side plants d = 0.5 3+ m 0 0.05 0.1 Emergent reeds , rushes, flag and large grasses 0.02 0.15 0.2 Floating-leaved rooted , typically water lillies in deeper slower waters 0.03 0.10 0.14 Emergent broad-leaved rooted plants , like water cress or water parsnip 0.05 0.15 0.5+ Submerged broad-leaved , Pondweeds (0.6 1.2m) d = 0.06 1.2m, v = .2 .9 m/s 0.02 0.1 0.2 Submerged fine-leaved shallow rivers, (chalk streams), water crowfoot, pondweeds d = 0.2 0.6m deep, v = 0.2 .0.7m/s 0.02 0.3 0.45+ Submerged fine leaved -medium depth rivers regular management d = 0.6 1.2m deep, v = 0.3 .0.8m/s 0.021 0.1 0.249 Submerged fine leaved medium to deep rivers some management d = >1.2m deep, v = 0.3 1m/s 0.01 0.08 0.12
A range of hydraulic resistances for total channel resistance for North American channels has been reported and is included for comparison with data derived from the roughness advisor, Table 14
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Table 14 Values of total channel resistance for North American channels Additional hydraulic resistance as Channel Depth Velocity Source(s) Manning’s n values Comments description m m s 1 Min Mean Max
Vegetal lining 0.30 0.5 extreme Chow 1982 range aid T5.6 to determine maximum permissible velocities Grass lined 0 1 intermittent 0.03 0.06 N.American Aken & channels grasses Higler intermittent 2001 flows Chen & Cotton Range from VR 0.04 0.4 long term Gwinn & cut to re relationship changes Ree 1980 establishment with encroachme nt of bushes Excavated or dredged channels Chow 1982 (RS & deep sluggish T5.6 C a4 realigned) 0.022 0.027 0.033 & b2 A. earth, deep sluggish 0.025 i) short grass, deep sluggish 0.030 0.030 0.040 Chow 1982 few 0.035 0.035 0.060 T5.6 C.b3 plants 0.050 Chow 1982 ii) dense T5.6 C.c2 aquatic iii) bushes on banks B. Non Chow 1982 maintained T5.6 C.e1 1 weeds and full 0.050 0.080 0.120 4 brush uncut depth i) dense weeds normal 0.040 0.050 0.080 high as flow flood 0.045 0.070 0.110 depth clean iia) flood 0.080 0.100 0.140 bushes on sides iib) brush on sides iii) dense brush C. natural Chow 1982 streams T5.6 normal 0.030 0.035 0.040 (<30m), low normal 0.035 0.045 0.050 D1.a2 8
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Additional hydraulic resistance as Channel Depth Velocity Source(s) Manning’s n values Comments description m m s 1 Min Mean Max
slope deep sluggish 0.050 0.070 0.080 1. few plants deep 0.075 0.100 0.150 2.some plants pools 3. weedy 4. very weedy or flood ways with trees and bushes 6.3.2 Bank type
Material The values given in section 6.3.1 for bed material for the channel zone are the basic values to be used in the roughness advisor if there is just a basic sand, silt, clay etc bank material. The range of man made bank materials is very extensive and the following table covers a wide range of unit roughness values. For each bank material a unit roughness value representing mid (M), lower (L), and upper (U) likely value are given. The mid value represents the average unit roughness, while the upper and lower values provide a likely range of unit roughnesses. Table 15 Values of unit roughness for man-made bank materials Bank Rock Boulder Earth Clay Sheet piling material Mid,lower, M L U M L U M L U M L U M L U upper n values 0.025 0.023 0.028 0.033 0.03 0.038 0.02 0.018 0.023 0.02 0.018 0.023 0.028 0.025 0.03 Bank Grass Bushes Trees Stone Block Hazel material hurdles
Mid,lower, M L U M L U M L U M L U M L U upper n values 0.035 0.03 0.04 0.045 0.038 0.05 0.045 0.04 0.05 0.035 0.03 0.04 0.025 0.02 0.03 Bank Gabion Concrete Rip rap Wood piling material
Mid,lower, U M L U M L U M L U M L upper n values 0.038 0.035 0.04 0.018 0.015 0.022 0.04 0.037 0.043 0.028 0.025 0.03
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Bank Matting Masonry Brick Fibrerolls material without vegetation Mid,lower, U M L U M L U M L U M L upper n values 0.023 0.019 0.027 0.025 0.017 0.03 0.015 0.012 0.018 0.022 0.018 0.026 Irregularities The values to be used for irregularities on the bank are those that are found in Tables 11 and 12 in section 6.3.1 Vegetation Table 16 Values of roughness for bankside vegetation Hydraulic Description Floodplain resistance and equivalent vegetation Depth m Manning’s n Comments & source(s) RHS land-use type value classes ‘97/’03 Min Max BANKSIDE bare stream BE banks stable earth SC cliff to stream with some mosses vegetated VP & VS point &/or side bars vegetated MI islands bankside A.1 2 year, dormant 0.01 0.025 moderate Chow 1982, bushes B. 1 year bushy, in 0.025 0.05 ly dense p107 2(c) leaf 0.025 0.05 Chow 1982, C.1 year in leaf 0.05 0.1 p107 3(c) D. I year dense Chow 1982, leafy bushes 0.05 0.1 p107 3(b) E. leafy bushes, Chow 1982, trees,etc p107 4(b) Chow 1982, p107 4(c) unmanaged channels tree seedlings 0 x 3 4 .005 e.g. willow Chow 1982, submerged height deep .01 whips p107 1(b) 0 x 2 3 0.01 moderately Chow 1982, height deep 0.025 dense cover p107 2(b) marginal WT wetlands artificial open OW water (natural/ artificial)
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6.3.3 Floodplain type The floodplain data has been divided into unit values in a similar manner to the values for the channel. The contributing factors are from the ground material, just as the bed material in the channel, but with more categories such as ploughed fields etc, irregularities, obstructions and vegetation. There is much less information on the roughness of floodplains and especially the contribution to roughness of individual items such as buildings or different crops. However the tables which have been developed for the roughness advisor contain the set of comprehensive data as given in the literature.
Material The values used for the ground material are essentially the same values that are used in the channel and are given below in Table 17
Table 17 Values of roughness for floodplain ground material Channel substrate Roughness values Mid Lower Upper Bedrock 0.025 0.023 0.028 Cobbles 64 256mm 0.055 0.04 0.07 Coarse Gravel 0.035 0.022 0.04 Gravel 2 64mm 0.03 0.028 0.035 Fine gravel 0.024 0.02 0.028 Sand, 0.2mm 0.012 0.01 0.016 Sand, 0.3mm 0.017 0.015 0.022 Sand, 0.4mm 0.02 0.017 0.025 Sand, 0.5mm 0.022 0.018 0.027 Sand, 0.6mm 0.023 0.02 0.03 Sand, 0.8mm 0.025 0.023 0.032 Sand 1.0mm 0.026 0.024 0.033 Coarse sand 1 2mm 0.028 0.026 0.035 Silt 0.022 0.02 0.025 Clay 0.02 0.018 0.023 Peat 0.02 0.018 0.023 Earth 0.02 0.018 0.023 Firm soil 0.02 0.018 0.023 Concrete 0.02 0.018 0.022 Bare ploughed soil 0.025 0.022 0.028 There are some additions to that table for different type of land cover such as ploughed fields with furrows running parallel, perpendicular or at an angle to the river. The values given are based on those given in Chow and from the experience of the authors and other individuals contacted. Turner and Chanmeersi (1984) give values for bare soil, bare crop stems and a dense crop of wheat, these values are given in the reference sheet in Appendix A and the values for bare soil have been incorporated into Table 17. Weltz, Arslan and Lane (2000) give values of hydraulic roughness coefficients for native rangelands, which are given in Appendix A. Although the vegetation is not representative of the flora found in the UK, the values for bare soil given have been used in deriving the values found in Table 17.
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Arcement and Schneider (1989) give base values of Manning’s n taken from Chow (1959), and Benson and Dalrymple (1967) and Aldridge and Garrett (1973). The data given in Appendix A show that from the two sources the values for base n do not necessarily agree. The values have been evaluated and used in deriving the values found in Tables 16 and 17.
Irregularities Irregularities on the floodplain will involve irregularities due to undulations in the ground form, hollows and depressions in the floodplain, and ridges due to ploughed fields. There has been little information found on any roughness factors due to these types of irregularities so a table has been assembled, Table 18. This table contains estimated data for different irregularities based on experience and knowledge of floodplains and from data obtained from Acement and Scheider (1989) who modified data from Aldridge and Garrett (1973). The main obstructions on the floodplain will be structures such as walls, fences, buildings, and bridges. “Soft” obstructions such as hedges will be dealt with under the section on vegetation. Behind such obstructions local area of non flow will be found, which may be classified as a deadzone. The location of the deadzone will depend on the alignment of the obstruction to the flow. The obstruction will cause a backwater effect and account should be taken of this when performing hydraulic calculations. Table 18 shows the unit roughness values which should be combined with the unit roughness values from Tables 17 to 23 in the way described in section 6.1 to give values of roughness for the floodplain. Table 18 Values of roughness for floodplain irregularities and obstructions Roughness values Irregularities Mid Lower Upper Ridges on ploughed field 0.0017 0.0015 0.002 Undulations on floodplain 0.002 0.0015 0.0025 Minor irregularities – a few dips and sloughs 0.003 0.001 0.005 Moderate irregularities more rises and dips with 0.008 0.006 0.01 some sloughs and hummocks Severe irregularities – floodplain irregular in 0.015 0.011 0.02 shape, many rises and dips/sloughs visible. Irregular ground surfaces in pasture land and furrows perpendicular to flow. Roughness values Obstructions Mid Lower Upper Negligible Few scattered obstructions which 0.002 0.001 0.004 include debris deposits, stumps, exposed roots, logs, piers or isolated boulders that occupy less than 5 percent of the cross sectional area. Minor Obstructions occupy less than 15 percent 0.0045 0.004 0.005 of the cross sectional area. Appreciable Obstructions occupy from 15 0.025 0.02 0.03 percent to 50 percent of the cross sectional area.
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Vegetation Grass cover Extensive tests undertaken on grass cover (Ree, 1949 and Ree and Palmer, 1949) resulted in a Handbook of Channel Design in 1954, (US Soil Conservation Service, 1954). The result of the work has been to define a series of relationships between Manning’s n and the product VR, where V is the mean flow velocity and R is the hydraulic radius. The relationship is expressed as a family of curves, each curve defining the other principal variable, the physical characteristic of the vegetation. The main physical characteristic is judged to be the height but other factors such as density and uniformity are influential and a value judgement has to be made. The family of curves and classification of retardance classes are given in Appendix A
Green and Garton (1983) give equations for the calculation of Manning’s roughness coefficient in each of the retardance classes. These equations are presented in Appendix A. The equations relating Manning’s n and VR developed by US Soil Conservation Service (1954) and Green and Garton (1983) are widely used and appear to be very consistent with other studies undertaken, HR Wallingford (1992) and Kouwen (1992). It is suggested therefore that the form of roughness taken for grassed floodplain follow the curves and formulae. The formulae and values have been incorporated into a table linking the retardance class and VR or Vd values, which are given below. Table 19 Values of roughness for grass at different retardance classes n values for Retardance class VR (m 2/s) A B C D E 0.025 0.3995 0.31961 0.218 0.118 0.057 0.05 0.359 0.23622 0.126 0.078 0.043 0.075 0.3185 0.1686 0.095333 0.064667 0.038333 0.1 0.278 0.1366 0.079 0.058 0.036 0.2 0.1575 0.0929 0.0535 0.044 0.03 0.3 0.120333 0.073733 0.045 0.039333 0.0275 0.4 0.10175 0.06415 0.04075 0.037 0.02625 0.5 0.0906 0.0584 0.0382 0.0356 0.0255 0.6 0.083167 0.054567 0.0365 0.034667 0.025 0.7 0.077857 0.051829 0.035286 0.034 0.024643 0.8 0.073875 0.049775 0.034375 0.0335 0.024375 0.9 0.070778 0.048178 0.033667 0.033111 0.024167 1 0.0683 0.0469 0.0331 0.0328 0.024 The Technology Research Centre in Japan gives an alternative for grass cover. The relationship is for different types of grass and the roughness is a function of the relative height of the water depth (h) and grass height (h v). The table for the values is shown in the reference for Technology Research Centre (1994) in Appendix A. The values can be used as an alternative to the table above when the product VR is difficult to estimate. The values are given in the following table:
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Table 20 Alternative values of roughness for grass Manning’s n roughness values Description Average Lower Upper Stiff grass height hv= 1.8m h/hv=1.4 0.1 0.08 0.12 Grassland height hv=1.0m h/hv=2 0.08 0.07 0.09 Stiff grass height hv=1.8m, h/hv= 2.5 0.047 0.04 0.055 Grassland height hv = 50cm, h/hv= 5 0.04 0.035 0.045 Grassland height hv = 10 20cm, h/hv= 16 0.026 0.022 0.028 Flat golf course with turf several cm high, 0.021 0.018 0.024 h/hv= 90
A difficulty with applying the VR method is that ‘V’ and ‘R’ are derived for a channel section and not a local value as applied in the conveyance generator.
Crops There are a number of publications that have details of the impact of crops in different phases of growth. Smith et al, 1990 give stage discharge relationships for different crops including different types of grass, wheat and sorghum under different conditions. These values are based on data from other sources such as Turner and Chameersi (1984) which are detailed in Appendix A. Gilley and Kottwitz (1994) give Darcy Weisbach friction factor values for different crop types: corn, cotton, sorghum, sunflowers and wheat, both parallel and perpendicular to the flow. The values have been converted to Manning’s n roughness values in Appendix A and added to the table below. Petryk and Bosmajian (1975) looked at flow characteristics for wheat, sorghum and for a range of field sites with a variety of vegetation types on the floodplain. The values for wheat and sorghum are added to the table below. Table 21 Values of roughness for a range of different crops Crop description Roughness values Mid Lower Upper Wheat in 15cm of water 0.06 Wheat in 20cm of water 0.07 Wheat in 30cm of water 0.075 Wheat in 40cm of water 0.096 Wheat in 50cm of water 0.113 Wheat Stems in 10cm of water 0.035 Wheat stems in 15cm of water 0.04 Wheat stems in 24cm of water 0.05 Wheat stems in 33cm of water 0.053 Wheat, with density of 1.2 stalks per m, in 30cm 0.11 0.1 0.125 of water Sorghum, with a density of 0.3 stalks per m, in 0.06 0.04 0.11 30cm of water Corn, rows parallel to flow 0.11 0.036 0.24 Cotton, rows parallel to flow 0.06 0.008 0.14 Sorghum, rows parallel to flow 0.12 0.019 0.26 Soybeans, rows parallel to flow 0.095 0.05 0.21
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Crop description Roughness values Mid Lower Upper Sunflower, rows parallel to flow 0.115 0.046 0.25 Corn, rows perpendicular to flow 0.05 0.012 0.134 Cotton, rows perpendicular to flow 0.045 0.017 0.082 Sorghum, rows perpendicular to flow 0.047 0.015 0.093 Soybeans, rows perpendicular to flow 0.08 0.037 0.149 Sunflower, rows perpendicular to flow 0.07 0.012 0.120 Wheat, rows perpendicular to flow 0.075 0.015 0.13 Hedges Klassen and van der Zwaard (1974) carried out laboratory experiments to investigate the effect of orchards and hedges on the roughness coefficient of vegetated flood berms. The data from the paper is shown in Appendix A. The analysis of Klassen and van der Zwaard considered hedges that were not submerged by the flow. Klassen and van Urk (1985) extended this work by investigating the resistance of drowned hedges. They concluded that in order to calculate the flow through/over submerged hedges the method of Klassen and van der Zwaard should be used for the flow through the hedge. The flow over the hedge should be estimated using a short crested weir equation with a discharge coefficient equal to 1.0. As a results of this research and the values shown in Appendix A under the Klassen and van der Zwaard reference, the values for roughness due to hedges on the floodplain, perpendicular to the flow are given in the table below where the hedge separation is in the streamwise direction. Table 22 Values of roughness for clean and dirty hedgerows on the floodplain Hedgerow Manning’s n roughness coefficient for clean or dirty separation (m) hedgerows with varying flow depths 0.25m 0.50m 1.00m 1.50m 2.00m Clean Dirty Clean Dirty Clean Dirty Clean Dirty Clean Dirty 50 0.038 0.072 0.045 0.089 0.053 0.091 0.054 0.086 0.051 0.080 100 0.032 0.053 0.032 0.064 0.042 0.067 0.042 0.063 0.041 0.060 250 0.029 0.040 0.031 0.045 0.029 0.045 0.032 0.045 0.032 0.041 500 0.028 0.035 0.028 0.036 0.029 0.037 0.027 0.036 0.029 0.034 1000 0.027 0.031 0.027 0.032 0.027 0.031 0.025 0.029 0.027 0.027
Trees and Shrubs Chow (1959) has some roughness values associated with trees and shrubs, which are summarised in the Table 23. Petryk and Bosmajian (1975) theoretically analysed flow through trees and shrubs and gave some examples from field sites, Appendix A. There are a number of other sources of data from field sites including: Kouwen and Fathi Moghadam (2000) and (1997) for coniferous trees and non rigid, nonsubmerged vegetation, Arcement and Schneider (1989) and (2002) with examples of different types of trees on floodplain, and Technology Research Centre (1994) with details of trees in
R&D ROUGHNESS REVIEW 61 different patterns. All the relevant data from these papers are detailed in Appendix A and the data has been combined to develop the table below which gives more generalised information rather than specific tree densities and types. The exception is for coniferous trees where there is more detailed data from Kouwen and Fathi Moghadam (2000). Table 23 Values of roughness for trees and shrubs
Manning’s n values Description Average Minimum Maximum
Small amounts of vegetation – supple trees saplings e.g. 0.005 0.0001 0.05 willow Scattered brush 0.02 0.015 0.03 Light brush and trees in winter 0.02 0.015 0.03 Light brush and trees in summer 0.025 0.015 0.05 Medium to dense brush in winter 0.04 0.02 0.07 Medium to dense brush in summer 0.045 0.01 0. Dense willows, summer 0.1 0.07 0.13 Cleared land with tree stumps, no sprouts 0.01 0.005 0.015 Cleared land with tree stumps, heavy growth of sprouts 0.025 0.015 0.04 Moderate to dense brush. Depth is below branches 0.06 0.05 0.1 Heavy stand of timber, a few down trees, little undergrowth, 0.07 0.05 0.13 flood stage below branches Heavy stand of timber, a few down trees, little undergrowth, 0.15 0.1 0.2 flood stage reaching branches Coniferous trees Velocity 0.1m/s. Totally submerged, total area coverage by 0.2 trees Velocity 1m/s. Totally submerged, total area coverage by 0.118 trees Velocity 2m/s. Totally submerged, total area coverage by 0.1 trees Velocity 0.1m/s. 75% submerged, total area coverage by trees 0.22 Velocity 1m/s. 75% submerged, total area coverage by trees 0.13 Velocity 2m/s. 75% submerged, total area coverage by trees. 0.12 Velocity 0.1m/s. 50% submerged, total area coverage by trees 0.28 Velocity 1m/s. 50% submerged, total area coverage by trees 0.162 Velocity 2m/s. 50% submerged, total area coverage by trees 0.14 Velocity 0.1m/s. 25% submerged, total area coverage by trees 0.4 Velocity 1m/s. 25% submerged, total area coverage by trees 0.235 Velocity 2m/s. 25% submerged, total area coverage by trees. 0.2 Velocity 0.1m/s. Totally submerged, 75% area coverage by 0.175 trees Velocity 1m/s. Totally submerged, 75% area coverage by 0.1 trees Velocity 2m/s. Totally submerged, 75% area coverage by 0.087 trees Velocity 0.1m/s. 75% submerged, 75% area coverage by trees 0.2 Velocity 1m/s. 75% submerged, 75% area coverage by trees 0.117 Velocity 2m/s. 75% submerged, 75% area coverage by trees. 0.1 Velocity 0.1m/s. 50% submerged, 75% area coverage by trees 0.245 Velocity 1m/s. 50% submerged, 75% area coverage by trees 0.145 Velocity 2m/s. 50% submerged, 75% area coverage by trees 0.12
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Manning’s n values Description Average Minimum Maximum
Velocity 0.1m/s. 25% submerged, 75% area coverage by trees 0.34 Velocity 1m/s. 25% submerged, 75% area coverage by trees 0.2 Velocity 2m/s. 25% submerged, 75% area coverage by trees. 0.175 Velocity 0.1m/s. Totally submerged, 50% area coverage by 0.14 trees Velocity 1m/s. Totally submerged, 50% area coverage by 0.08 trees Velocity 2m/s. Totally submerged, 50% area coverage by 0.07 trees Velocity 0.1m/s. 75% submerged, 50% area coverage by trees 0.16 Velocity 1m/s. 75% submerged, 50% area coverage by trees 0.095 Velocity 2m/s. 75% submerged, 50% area coverage by trees. 0.08 Velocity 0.1m/s. 50% submerged, 50% area coverage by trees 0.2 Velocity 1m/s. 50% submerged, 50% area coverage by trees 0.12 Velocity 2m/s. 50% submerged, 50% area coverage by trees 0.1 Velocity 0.1m/s. 25% submerged, 50% area coverage by trees 0.28 Velocity 1m/s. 25% submerged, 50% area coverage by trees 0.165 Velocity 2m/s. 25% submerged, 50% area coverage by trees. 0.14 Velocity 0.1m/s. Totally submerged, 25% area coverage by 0.1 trees Velocity 1m/s. Totally submerged, 25% area coverage by 0.06 trees Velocity 2m/s. Totally submerged, 25% area coverage by 0.05 trees Velocity 0.1m/s. 75% submerged, 25% area coverage by trees 0.1 Velocity 1m/s. 75% submerged, 25% area coverage by trees 0.059 Velocity 2m/s. 75% submerged, 25% area coverage by trees. 0.05 Velocity 0.1m/s. 50% submerged, 25% area coverage by trees 0.12 Velocity 1m/s. 50% submerged, 25% area coverage by trees 0.07 Velocity 2m/s. 50% submerged, 25% area coverage by trees 0.06 Velocity 0.1m/s. 25% submerged, 25% area coverage by trees 0.2 Velocity 1m/s. 25% submerged, 25% area coverage by trees 0.118 Velocity 2m/s. 25% submerged, 25% area coverage by trees. 0.1
6.4 Vegetation growth and maintenance Detailed information on vegetation growth and maintenance is contained in Chapter 7. 6.5 Derivation of roughness values This section details the exact approach taken to the selection of the values in the roughness advisor for the different components and which literature, or expert judegment or field tests were used in deriving the unit roughness values. Bed materials Bedrock Unit values used in roughness advisor: Avg Lower Upper 0.025 0.023 0.028 Values derived from literature: Chow(1959), Cowans(1956), Barnes (1967) and adjusted using expert judgement and checking against Hicks and Mason (1991).
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Cobbles (64 256mm) Unit values used in roughness advisor: Avg Lower Upper 0.055 0.04 0.07 Values derived from literature: Chow(1959), Cowans(1956), Barnes (1967), Limernos (1970) and adjusted using expert judgement and checking against Hicks and Mason (1991), Hey and Thorne (1986) Tested and checked through back calculation with data from Heathcote at Sloan Terrace, Waiwakaiho at SH3 bridge and Ngunguru at Dugmores Rock (New Zealand), Hicks and Mason (1991). Coarse gravel Unit values used in roughness advisor: Avg Lower Upper 0.035 0.022 0.04 Values derived from literature: Chow(1959), Cowans(1956), Barnes (1967), Limernos (1970) and adjusted using expert judgement and checking against Hicks and Mason (1991), Hey and Thorne (1986) Tested and checked through back calculation with data from River Trent at Drakelow (HRWallingford course data) Gravel Unit values used in roughness advisor: Avg Lower Upper 0.03 0.028 0.035 Values derived from literature: Chow(1959), Cowans(1956), Barnes (1967), Limernos (1970) and adjusted using expert judgement and checking against Hicks and Mason (1991), Hey and Thorne (1986) Tested and checked through back calculation with data from River Main, Northern Ireland, River Cole, Birmingham, River Severn, Montford Bridge, Abel’s Bridge, NI. Fine Gravel Unit values used in roughness advisor: Avg Lower Upper 0.03 0.028 0.035 Values derived from literature: Chow(1959), Cowans(1956), Barnes (1967), Limernos (1970) and adjusted using expert judgement and checking against Hicks and Mason (1991), Hey and Thorne (1986) Tested and checked through back calculation with data from Omagh Road, River Blackwater, NI Sand Values taken from literature Acrement and Schneider (1989/2002), Barnes (1967) Other bed material
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Values taken from Chow (1959) and modified from expert judgement for unit roughness
Irregularities
Boulders The values for boulders combined with different substrates were taken from Hicks and Mason (1991), Mason (1967) and Cowans (1956) and combined in table 3. These were all recorded at different depths but needed to be standardised for the roughness advisor and unit roughness for values at depths of 1.0m. Expert judgement was applied to these values and plots of roughness against depths using a relationship of the form y=ax b. A table was produced, table 11, with the range of roughness values, for a combination of channel substrate and boulders. There were some gaps in the data but these were interpolated using expert judgement. The impact of the irregularity was then separated out from the overall roughness and a unit roughness value created as shown below. The unit roughness values were then re combined with the unit roughness values for the substrate and tested for consistency against University of Ulster (1995) data. The unit roughness were refined by expert judgement and checked for consistency tested against the Northern Ireland data from the University of Ulster (1995) by back calculating roughness values and creating a stage discharge relationship using the CES methodology and comparing this with measured values. Abel’s Bridge, River Blackwater: 0 20% of bed covered Omagh Road, River Blackwater and River Main: 21 50% of bed covered Waiwakaiho at SH3 bridge (New Zealand) and River Fury: >50% of bed covered. Pools and riffles Values of roughness for pool and riffle sequences have been determined from the following papers: Higginson and Johnston (1989), Richards (1976) on the River Fowey in Cornwall and Pimperton, Karle (1993) University of Ulster, (1995) and adjusted to unit roughness values using expert judgement. Other irregularities These are urban trash and groynes. There are no references for the roughness of urban trash so these unit roughness values are based on expert judgement. For groynes there are very few references and no examples on roughness of groynes so the unit roughness values are based on expert judgement. Bank material The unit roughness values for bank materials rock, boulder, earth and clay were sourced from the same literature and references as the bed material values, see above. Values for Stone Block, Concrete, Rip rap, Masonry, Brick were taken directly from values suggested in Chow (1959). Values for Hazel hurdles, wood piling and fibrerolls were taken from the expert judgement of the advisors based on their work and the general information available within the literature.
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For bankside bushes and small trees the values with sources were used as described in Table 16. There is little information on roughness of banks. The banks make up a relatively small part of the overall cross section. For these two reasons the values suggested in Chow have not been modified by the technical advisors and have been used directly as the unit roughness values within the roughness advisor. Floodplain Ground material The values used for floodplain ground material and the sources for these values in the literature are the same as for bed material. There are number of additional substrate categories of firm soil and bare ploughed soil. These values are based on the values given in Chow (1959), Turner and Chanmeersi (1984) and Weltz, Arslan and Lane (2000). In Turner and Chanmeersi, the values are for a range of different depths and the technical advisor took these values and averaged them, comparing them with the other sources of information and making sure that the range of upper and lower limits covered the entire range of values. These engineering roughness values and the range were then modified by the technical advisors to be unit roughness values by lowering the values according to their experience and judgement of how much the turbulence and secondary flows would add to the unit roughness to be equivalent to the engineered roughness. The roughness values used were also checked against other sources in the literature Arcement and Schneider (1989), Benson and Dalrymple (1967) and Aldridge and Garrett (1973), which although they did not always agree with values selected were within the range of values in these papers. Irregularities The unit roughness values for different irregularities were based on experience of the technical advisors and knowledge of floodplains and from data obtained from Acement and Scheider (1989) who modified data from Aldridge and Garrett (1973). Vegetation The vegetation on a floodplain has been split into several different categories due to the different nature of the types of vegetation and the literature available which is more extensive perhaps than literature in the other categories. The catetgories were split into: Grass; Crops Hedges; and Trees and shrubs. Grass Roughness values were found in a number of sources: Ree, 1949 and Ree and Palmer, 1949, US Soil Conservation Service, 1954, Green and Garton,1983, HR Wallingford (1992) and Kouwen (1992), Technology Research Centre, 1994. The roughness data for grass is presented in the literature is related to length, and condition, of grass and the product of the velocity and hydraulic roughness. Data was loaded into a spreadsheet and graphs of the variations between length of grass and product of velocity and hydraulic radius were considered. Based on the literature data
R&D ROUGHNESS REVIEW 66 analysed, equations relating these factors were produced for each grass length in the form y = a+bx c where y = roughness, x is the product of velocity and hydraulic roughness and a, b and c are coefficients given from the literature. There are different conditions of the product VR and the coefficients vary with these differing conditions. These variations are included in the roughness advisor for different lengths of grass. Crops The values used in the roughness advisor are based on values in the literature from references: Turner and Chameersi (1984) and Gilley and Kottwitz (1994) who give Weisbach Darcy friction factor values for different crop types: corn, cotton, sorghum, sunflowers and wheat, both parallel and perpendicular to the flow. The values have been converted to Manning’s n roughness values. Petryk and Bosmajian (1975) looked at flow characteristics for wheat, sorghum and for a range of field sites with a variety of vegetation types on the floodplain. The values for wheat and sorghum were added to the roughness advisor. For the wheat the roughness values are for wheat in different depths of water. The roughness values given for wheat were plotted against the depth of water and then roughness values were taken from the plots and used in the roughness advisor for different depths. Hedges Data taken from the literature: Klassen and van der Zwaard, 1974 and Klassen and van Urk, 1995. The data was represented in tabular form for dirty or clean hedges, separated along the floodplain for a variety of distances in a certain depth of water. These could have been represented by equations but were identified in the roughness advisor by individual values for a range of circumstances ie the value for say a hedge in 1m of water separated by 100m form surrounding hedges has a roughness value of 0.042. The range used is the range in the table for clean or dirty hedge conditions. Trees and shrubs The trees have been divided into coniferous trees and deciduous trees under a variety of conditions. The values of roughness for the deciduous trees were taken from Chow,1959, Petryk and Bosmajian, 1975, and Technology Research Centre, 1994 with values being averaged for different conditions and ranges being used from the values in these papers. For coniferous trees the roughness values were taken from Kouwen and Fathi Moghadam (2000). These values were included and analysed in a spreadsheet where the relationships for coniferous trees under different submerged conditions and percentage ground coverage were considered. The values as given in table 23 were combined using equations relating roughness to velocity in the form of an equation: y = ax 2+bx+c where y is roughness, x is velocity and a, b and c are coefficients based on the data given in Kouwen and Fathi Moghadam, 2000 for different submergence and ground
R&D ROUGHNESS REVIEW 67 coverage of trees. These values for roughness were then included in the roughness advisor for the different conditions. 6.6 Upper and Lower Uncertainty bands
The roughness advisor gives a mid value and an upper and lower value of unit roughness. These values demonstrate that there is uncertainty in the estimation of roughness values due to a number of reasons: • Manning’s roughness values are empirical so the site and conditions may not be the same as those measured • The roughness values vary with depth, higher for lower depths and vice versa. The unit roughness values in the Roughness Advisor are for depths of water of 1.0m • Roughness values are estimated from a number of different sources • The roughness values in the literature are engineered roughness values and they have been adjusted in the roughness advisor to be unit roughness values. These sources of uncertainty can lead to roughness values with a range. The upper and lower values are intended to represent that range and unit roughness values are assumed to be within that range. The upper and lower bounds of the unit roughness values were taken from the range of values found in the literature or from known measured values for each component from sites described in Appendix A. The source of the unit roughness values are found in section 6.5. 6.7 Justification of approach The approach taken has been driven by a desire to keep the roughness advisor as simple as possible. A consistent approach was required which would use all the data available to its maximum potential. The maximum amount of data which can be extracted from the literature, field and experimental data is that which is expressed in terms of Manning’s n values in a similar manner to the values expressed in Chow. The advantages of this approach are that: • Data can be extracted from many different sources to add to the values in Chow • The data can be expressed as a unit roughness • The unit roughness values can be combined to give a type roughness value • The type roughness values can be used in the conveyance generator with values of turbulence, secondary flow parameters and sinuosity to give stage discharge relationships from which an engineering roughness can be determined • The Manning’s n value is well known and well used internationally. 6.8 Summary of testing of summation method The measured roughness from various sites given in Table 5 were compared with those predicted from the roughness advisor. In addition sites from Barnes (1967), Hicks and Mason (1991) publications and Chow (1981), were checked against those predicted from the Roughness Advisor.
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There are some limitations with doing this before having the conveyance generator. The roughness advisor splits the roughness into bed, bank and floodplain whereas the measured sites are usually for the entire channel or channel and floodplain. Some of the roughness elements are contained in the Conveyance Generator, for example the resistance due to turbulence and sinuosity. Realistically only the measured and predicted values can be checked once the Conveyance Generator has been implemented in the conveyance estimation system (CES) and the stage discharge relationship can be produced. A depth roughness relationship can therefore be calculated and checked against measured data. The main points that arose from checking of results from the Roughness Advisor against measured data were: • The roughness advisor values checked well with Chow. • For the larger rivers on the Severn Trent site, the measured values for the Severn at Bewdley were lower and outside the range of the minimum value. This may be due to the fact that the Severn is deeper than the nominal 1m for the roughness values given in the advisor. The measured value for the Tanat at Llanyblodwel were higher than the maximum value. • The comparison between values given by Barnes for US rivers and the roughness advisor was generally good with most of the values measured being close to the mid value and at least within the range of max to min. • The comparison between values measured for the River Tame and the roughness advisor was generally good with most of the values measured being close to the mid value and at least within the range of max to min. The exception to this was Brookvale Road where the measured values were much less than those predicted. This is due to the fact that the site is in an area of backwater from the bridge which means the water is deeper and the roughness less than would be predicted. In fact the Manning’s equation does not apply in this region where there is not uniform flow. • For the data from the River Blackwater in Northern Ireland, the predicted values, based on the bed information only is generally less than the measured values. This is generally to be expected as the roughness values for the banks will have an impact and until the CES is used to predict the overall roughness values these cannot be compared accurately. • The comparison between values given by Hicks and Mason, 1991, for NZ rivers and the roughness advisor was generally good with most of the values measured being close to the mid value and at least within the range of max to min. From the checks against real data, the majority of sites matched well or were within the envelope of maximum and minimum values. For sites not within this envelope there was generally a reasonable explanation which could be given. Until the sites can be fully tested using the Roughness Advisor and CES to gain a picture of the engineering roughness or total roughness, which includes contributions to resistance due to turbulence, secondary flows and bends, it is difficult to test accurately the values in the roughness advisor.
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6.9 Use of the Roughness Advisor in the Conveyance Estimation System The Conveyance Generator determines the stage discharge relationship through solution of the depth integrated Reynolds Averaged Navier Stokes (RANS) equations. These equations include four calibration coefficients; local friction f, dimensionless eddy viscosity λ, secondary flow mixing coefficient Γ and meandering coefficient Cuv (details in Interim Report 2). For the latter three, models are encoded for their approximation. However, the local friction factor is based on advice from the Roughness Advisor. The Conveyance Generator receives the local roughness n value from the Roughness Advisor. This is converted to an equivalent ks roughness value, through a simplified form of the Colebrook White rough law, associated with a depth of 1m. For the case of sediment, this ks value is similar to the sediment dimension as defined by Nikuradse (1933) in his analysis of pipe flow. For the case of vegetation, this ks value can be interpreted as an equivalent turbulence length scale. The assumption is that the value of ks does not vary with depth. This ks value is then used for solution of the Colebrook White equation at each depth, to determine for the lateral distribution of f.
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7. RIVER MAINTENANCE PROCEDURES 7.1 Basic principles of plant biology and management Aquatic plants grow and interact with their environment. The dominance of a particular species of plant or a plant community results from this interaction but this may be changed from the near natural condition as a result of human activity. Such activity has unforeseen consequences and often results in the need for continued human input e.g. dredging, to maintain this unnatural condition. Combinations of activities such as discharging waters richer in nutrients than the natural condition in combination with channel modification or abstraction elsewhere upstream may cause complex interactions with unforeseen results. Aquatic plants have basic requirements for growth, thus any plant, large or small, requires light and a source of inorganic carbon for photosynthesis to build themselves, nutrients to assist this and other life processes, a suitable environment in which to grow and also the absence of toxic compounds. Thus plants need: 1. Light at their leaf surfaces, ‘no light no growth’. Light reduction may be a result of shade by marginal vegetation, especially trees, by absorption of light passing through the river water especially by intermittently or frequently turbid water, or by the overgrowth of leaves by films of algae. Thus, the reduction of light may provide a simple method for the control of excessive growth of water plants (e.g. Dawson, 1989). Conversely, the use of nutrients to suppress plant growth would produce strong adverse reactions in the whole aquatic ecosystem, such as reduced oxygen levels, which result in fish kills. 2. Suitable water chemistry, which primarily includes inorganic carbon (carbon dioxide in solution). Plant species selection relates broadly to this. Faster growing plants are found in water with higher calcium levels and are therefore more often considered for a regime of plant management. Plants often develop more slowly in acidic waters as the source rocks in the river catchment are more resistance to dissolution and thus the water is more likely to reflect prevailing rainfall quality. 3. Availability of macro & micro nutrients such as nitrate or phosphate and iron and other trace metals which are required for healthy plant growth. They are generally never a limiting condition in rivers although excess of some metals may locally limit plant growth. 4. A suitable environment (called ‘habitat’) is needed for growth. This includes a stable area of river and suitable substrate for rooting (or attachment) and an acceptable range of water flows during much of the growth period, which allows for the normal growth form of the plant to develop. The absence of toxic compounds such as organic compounds e.g. pesticides, toxic metals etc. As plants grow they interact and modify their environment. The influence of the physical parameters, particularly the seasonal periodicity of water and substrate, is paramount in the selection of which species is potentially dominant in any river situation provided a source of the plant is present or available as seed or fragment to colonise the river reach.
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7.1.1 Water flow and the vegetation of running waters The vegetation of running waters is predominantly defined and determined by the effect and interactions of a single physical factor, water flow, which governs plant form, dominates the growth controlling factors and defines the habitat. Thus: 1. Very high or turbulent flows will directly determine the presence or absence of in stream vegetation and even light becomes subordinate to its influence. 2. For high but less extreme flows aquatic vegetation may be confined to the margins and to islands where it is in direct competition with terrestrial vegetation. 3. Very low flows allow the development of vegetation characteristic of static water bodies, i.e. pond and lakes. Between these extremes of water flow, the physical and chemical factors can control growth, and interact with fluviatile plants to regulate seasonal biomass and to create flowing water communities. Plants are still subject to the broad environmental limits of high and low temperature (Whitton, 1972). Such communities can vary during the year influenced either by seasonal changes in their physical environment, particularly by water flow, or by competition between species. The plant community at a site therefore reflects the balance achieved between the physicochemical environment and the plants’ tolerance, adaptation to or their modification of these conditions by their presence. The species present within the community reflect those available and able to colonise. The dominance of a species may occur through the rapidity of its development during favourable growth periods which may result in a change of dominant species even seasonally. The spatial variation of fluviatile aquatic vegetation is naturally high and mosaics of plant associations often result, primarily from the turbulent nature of water flows in combination with the immediate or long term history of its interaction with the bed or underlying rocks. Interaction by man, particularly mechanical 'weed' control and channel reconstruction, often increases the uniformity of the habitat and reduces the size and stability of surface substrates. Such changes may increase the recovery tolerance of the system to frequent but not to catastrophic events. The vegetation which results is more likely to be limited to the more invasive and fast growing plants and is likely to be less varied in its species composition. 7.2 The flowing-water habitat The physical interaction of plants with the energy possessed by the water flowing past them governs and selects suitable plant species through their vegetative hydraulic resistance. Thus a successful plant must be able to resist this energy. The size, form and stand structure of the plant, together with the strength of its stems and the security of its method of anchoring to the substratum, are major factors in maintaining its presence. In waters with seasonal changes in flow e.g. snow melt or tropical dry season, a herbaceous perennial growth cycle is frequently advantageous. This growth cycle is characterised by dieback of the plant or the shedding of the majority of its shoots to reduce its resistance to flow, thus avoiding the wash out of its basal stems and particularly its roots or rhizomes. The power of the flowing water is governed by gradient which in combination with the surface rocks creates the environment into which plants invade and frequently modify.
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Such interactions include the moderation of flows through growth that increases the water levels thus reducing fluviatile or stream power and the stabilisation of silt banks. However through this moderation and encroachment the plant may destroy the habitat required by the plant itself. Fluviatile habitats have growth forms but not always taxa in common. The variety of habitats is large and ranges from sources with rapid runoff such as mountain torrents, snow melt, or constantly flowing springs, through streams and rivers with slow, rapid or alternating flow, to large deep sluggish sometimes turbid rivers of enormous size. Water velocities in smaller streams are frequently more turbulent and thus appear faster than those of placid but higher flow large rivers with fully developed velocity profiles. The studies of fluviatile habitats have been undertaken in various ways and to varying degrees of detail e.g. Haslam & Wolseley (1981), Holmes (1983). There are common factors between habitats but the great variety of other interacting physical and chemical factors are frequently incidental and serve only to confuse fundamental studies of distribution, community and growth controlling factors. However, generalising about habitats can provide some insight. Thus, for example, fast flows characterised by substrates of stones or boulders are frequently colonised by the smaller plants, particularly Bryophytes. The latter are characterised by being small in size, with numerous tenacious rhizoids in mosses, flattened shoots in liverworts and thin layers in algae and aquatic lichens. Bryophytes, in particular, are very adaptable to stress and some may tolerate factors such as low light levels, drying out and freezing, abrasion by particles or the accumulation of toxic metals (Glyme & Carr 1974, Lewis 1973, Wehr & Whitton 1986). Small lowland streams originating in springs or seepages are, by contrast, frequently dominated by emergent macrophytes (Michealis 1976). At the other extreme of the habitat range, large rivers which are characteristically deeper with relatively less turbulence, allow the development of higher water velocities and more frequently have algal dominated communities. This is in part due to the length of time (retention time) available for their multiplication and development but also due to the lower light levels at the substratum through physical absorption and turbidity of the water preventing macrophyte growth. The seasonal deposition of silts or soft sediments also inhibits colonisation and affects the permanence of macrophytes. Fluviatile macrophytes having rhizomes are thus limited to the margins, backwaters or shallows, depending upon the seasonal flows and morphology of the river and its substrate. A particular fluviatile habitat is not limited to large characteristic areas but may occur spasmodically in other areas. Thus, the very high energy or mountainous torrent habitat may occur as rapids in otherwise large sluggish rivers. The fitness of a particular growth form for a particular type of habitat and the associated features of the structure of the community may reappear under recurring habitat conditions almost irrespective of the particular species present. The habitat is restricted by physical factors, particularly flow, such that at high energies only larger stones and boulders are stable and remain but at low energies in slow water, then sediment may fill the crevices but unless dramatic climatic changes have occurred boulders are unlikely to be present. Thus in summary, the volume of water flowing regulates fundamentally the parameters of width, depth, velocity and turbulence, which in combination with the constraints of surface geology determines the permissible vegetation range. The grouping or classifying of plants can lead to a better understanding of the competitive and other
R&D ROUGHNESS REVIEW 73 interrelationships of the species and identification of common growth controlling factors through an understanding of the interaction of associated plant groups with their environment. The classification of freshwater macrophyte habitats has produced a variety of systems but only the ecological zonation developed for fluviatile freshwater macrophytes by Butcher (1933) and modified by the addition of seasonal changes in discharge as the frequency and severity of spates by Westlake (1975). 7.2.1 Communities, succession and climax Fluviatile communities reflect water conditions. In the large long rivers, planktonic algal communities develop, but such rivers are also usually deep and subject to particular conditions in smaller rivers, which preclude the establishment and growth of macrophytes (Kofoid, 1908). In shallow, small, running waters the communities are more dependent for high biomass upon nutrient conditions in particular. Increasing or high nutrient status favours epiphytic algal growth or attached algal communities in preference to a submerged macrophyte community, although large rhizomatous plants with surface leaves or emergent stems may overcome this (e.g. Golterman & Kouwen, 1980). 7.2.2 Plant growth and environmental growth controlling factors Fluviatile macrophytes, in common with other plants, have certain general requirements for growth. Although several other authors have considered the general characteristics of the aquatic environment for water plants (Gluck 1905) it was left to Butcher (1933) to review them and to extend this line of approach. He introduced many of the special or particular characteristics of the fluviatile habitat, the fundamental characteristic of which is the normal existence of a continuous flow of water in one direction. Interactions with this flow lead to the selection of a community of plants that can tolerate the prevailing conditions. Butcher also outlined several topics of importance, which has been the basis of further study for half a century. The maximum biomass or crop, which fluviatile macrophytes achieve at a particular site, is the result of a balance between the conditions available for growth such as light, inorganic nutrients and carbon, water temperature and water velocity and the plants' physiological responses at its current state of growth (Westlake 1967, Mitchell 1974, Westlake et al 1998). The turbidity and light penetration of the water has been noted as particularly important (e.g. Ham et al 1981) especially during the early growth of submerged plants before they reach the surface. Plant growth also requires the supply of several other elements in suitable chemical forms in addition to inorganic carbon of an acceptable type (Raven et al. 1982). In particular, the macro nutrients nitrate, phosphate and potassium together with other minor and trace elements which are often available in the water and/or sediments (Denny 1985). The absence of toxic or growth inhibiting compounds is also a requirement. If the general growth conditions are met, then plants, either large or small, will be able to grow in the majority of aquatic sites. For example, in the smaller rivers and streams fluviatile macrophytes are more likely to be abundant in shallower locations (<3m; Dawson 1976). They may however be limited in their ability to invade, become established or remain because of an unsuitable stream bed or water flow during either the whole or part of the year at particular sites. Invasion is often by turion or by vegetative propagule, i.e. pieces of plant stem or "root", but less frequently by seed (e.g. Coffey and McNabb 1974, Castellano 1977, Sastroutomo et al. 1979). The slow flow of
R&D ROUGHNESS REVIEW 74 water may reduce the potential for spread by propagule and favour seed dispersing plants, or plants which can reinvade from the banks or marginal areas. Once established, plants may be unable to survive competition with other macrophytes or algae. Many fluviatile macrophytes overwinter as buried stems or small rhizomes as in Batrachian Ranunculacae, or as tubers in Potamogeton spp. (Dawson 1976, van Wijk 1983, Madsen 1986). Planktonic algae are favoured in downstream sections of large rivers as mentioned previously. This is partly due to increasing depth, and partly by limiting large plants through the increase of depth as river channel dimensions increase, but also because sufficient time elapses for the development of an algal population during the downstream passage of water. The length of the period available for development is also of importance to large plants for unless large food reserves are available, even fast growing plants have modest and finite growth rates (Westlake 1966). As plants increase in bulk, self shading develops and the supply of inorganic carbon and nutrients may become progressively more limited. When considering individual plant biomasses, space for growth and growth strategy may become of paramount importance (Castellano 1977, Howard Williams 1982). The biomass achieved and annual production in various aquatic sites together with errors in their determination, have been reviewed again by Westlake (1982). Seasonal cycles. Changes in biomass in the late winter or spring are often initiated by a herbaceous type development from over wintering storage organs, or by redevelopment of over wintering stems, to produce the seasonal biomass which is then acted upon by the environment. The latter has for decades been discussed by authors e.g. Butcher (1933), who have produced sets of factors which are undoubtedly likely to control plants, particularly in rivers, but few have produced quantitative evidence on single or even related factors. This work followed a detailed study of sections on two lowland English rivers and illustrated the importance of several factors to the growth of river plants and the interaction between species and the physico chemical environment. Amongst the features Butcher introduced, he particularly emphasised the persistence of some species of plants throughout the year whilst others decay in the autumn and also the impermanence of aquatic vegetation. The constant movement of vegetation to unoccupied areas, leaving other areas barren demonstrated the latter. Studies on fluviatile macrophytes have investigated the seasonal changes in the biomass of the emergent macrophyte Nasturtium officinale (Castellano 1977) and of the submerged macrophyte Ranunculus penicillatus (Dawson 1976a) and their year to year interactions in relation to discharge cycles (Dawson et al, 1978). The latter, with their seasonal variation, is probably one of the most important of the between site variables governing biomass difference. Such a relationship was also demonstrated by Brooker et al (1978), who showed an inverse relationship between the flow of water in the April June period and the intensity of plant growth. A more extreme case of discharge variation for a shaded section of a lowland chalk stream has been described by Ham et al. (1982a). The affected species were of the genera Ranunculus, Berula and Callitriche. Limited studies on the growth rate and seasonal cycle have also been undertaken in artificial systems in defined conditions to estimate the uptake of nutrients, for example
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Eichenberger (1983) estimated these conditions for Ranunculus fluitans and the effects of grazing by invertebrates. Year-to-year variation of either the mean rate of growth or the maximum biomass achieved can occur, dependent upon the time for which there is sufficient light available to the plant because of fluctuations in light penetration through the water (Westlake 1966b). The effects of rainfall and turbidity of the water are often far more prolonged in larger and deeper streams. Seasonal boat traffic also has a similar effect (Murphy and Eaton 1982). If the light levels are below the light compensation of growth balance point for extended periods, then growth is not possible and the biomass achieved by the time of flowering is reduced. Other species which develop later, or have large overwintering storage organs and short growing seasons, may become dominant if this situation continues for several years e.g. Nuphar spp in larger rivers. Even under relatively similar discharge cycles, changes occur, as shown during the 4 year monitoring of the biomass of Ranunculus calcareus in an unshaded section of a stream (Dawson 1976). The Dawson (1976) study showed that the maximum summer biomass in the four seasons declined to half that initially found, but this resulted primarily from the plants not being subjected to annual mid summer plant removal by cutting. It was suggested that the decline occurred as much from the suppression of autumnal regrowth by moribund plant material overlying the shoots giving a low overwintering biomass, as from the release from the synchronising influence of regular cutting on plant regrowth. This suggestion was confirmed by the study of Ham et al (1981), who also found a similar response to cutting. Over several seasons on this same site, different species and cycles of biomasses were found between shaded and unshaded sites. This illustrates the effects of competition between an aggressively growing species Ranunculus and other less aggressive ones Callitriche and Berula. These differences also indicate the degree of shade tolerance or adaptation amongst these species. A long term study of the biomass variations (determined by examining the total weight of weed removed from a managed river) divided the cause equally between the environment in the early part of the year, the timing and extent of management in the previous year, and the inherent growth cycle of the plant (Westlake and Dawson 1982). In a subsequent study on the river in which pre emptive removal of material in the previous autumn was undertaken, the importance of management was confirmed because reductions of up to a third were found in comparison with the expected biomass (Westlake and Dawson 1986). 7.3 Consideration of traditional and alternative techniques Conventional irrigation and drainage channels are designed and operated to transport water to and from an area of land at minimal direct cost. In consequence channels are often straight for long lengths, trapezoidal in cross section and devoid of large vegetation in the channel and on the banks. This design condition can rapidly deteriorate as sediments are deposited in the channel and as the water flow is progressively obstructed as vegetation overgrows from the banks or within the channel. Expensive
R&D ROUGHNESS REVIEW 76 vegetation removal and dredging and reshaping of the channel is required and is undertaken to varying degrees, with success judged only in terms of water supplied to the irrigated area and not by reference to regular measurement of meaningful hydraulic parameter during its passage along the channel. There is evidence that the design and construction of artificial channels can exacerbate the maintenance requirement. For example, unlined channels with moderate flows and shallower than 3 m can make excellent habitats for most aquatic vegetation. Traditional channel engineering emphasises the simplicity of form of channels in combination with the ability to produce these structures by labour or heavy machinery. The straight channel is based upon the concept that water should and will flow quickest in a straight line and that the speed is enhanced by the shortest route. Many studies have shown that flows above quite a low velocity rarely obey this premise and the initiation of mass water flow readily results in the maximum velocities moving from side to side in any straight channel. This incipient sinuosity of the channel tends to create erosion and deposition in channels and even in lined channels where sediment is available. Once alteration of flow is initiated, it is difficult, and some say unnecessary, to remedy it for a dynamically stable situation exists. The trapezoid cross sectional design requirement is primarily related to the stability of worked bank materials i.e. soils, sands etc, but such a shape is rare in nature. Near vertical slopes are most common except where erosional slumping or block fall changes create shallow shores frequently observed in low flow conditions in large rivers. Vegetated margins when allowed to develop naturally and reach a stable plant population frequently create vertical faces to the flow, except under highly variable flows. Channels are frequently designed without consideration for the development of vegetation or its associated effects e.g. seasonally enhanced siltation. The potential for changes in morphology that may moderate plant growth is related to the size and stability of the static or flowing water, although there is more scope when channels are being designed or refurbished. Morphological adaptations by themselves do not solve macrophyte problems but must be used in combination with other techniques. Morphological design criteria for environmentally sound channels which are expected to contain vegetation should primarily be based on reducing the light climate for growth which includes: 1. A minimum surface area consistent with the self balancing ratio of depth to width for the flowing water because submerged macrophyte growth is related to the water surface area (not volume). 2. A maximum water depth (within the same above constraint) because shallow water is conducive to earlier and denser macrophyte growth and may be accompanied by overgrowth of marginal or emergent macrophytes (Dawson et al. 1978). Over wide, and thus shallow, lowland rivers which are often open and unshaded, have a high potential for macrophyte growth which disproportionately increases water levels and the risk of flooding adjacent land. Seasonally early fine leaved submerged macrophyte development may also accumulate more sediments as seasonal flows moving such material are often higher early in the year (Ladle & Casey 1971, Dawson
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1976a, Onslow 1982, Welton 1980). Absolute water velocity and its rate of change during the seasons is also important, for although turbulence is high in shallow flows, water velocity is generally not as high when compared to deeper water flows. Similarly, washout in the latter may be higher (Dawson 1976a). Broad recommendations for new lowland rivers in Northern Europe which are consistent with hydraulic criteria are beginning to emphasise channel form and assume that vegetation will develop and that regular removal is undesirable. The recommendations include: 1. Variation in plan form. This requires that the natural sinuosity or curves (exhibited by natural adjusted rivers) be allowed to develop; imposed or fixed sinuosity or straight channels create problems (e.g. Brookes 1984, 1985). 2. Variation in longitudinal bed slope to match the natural development of natural sequences of pools and riffles and the associated variation in width. 3. Variation in transverse vertical section includes variation in channel width and bankslope together with asymmetric `handing' of steep and shallow slopes but should also include emergent and submerged vegetation near the margins to protect and stabilise river banks with planting of the preferred emergent bank macrophyte during its growing seasons. 4. The planting of suitable trees or bushes on the tops of flood berms (but not raised banks) to moderate plant growth on both the berms and in the water; roots will stabilise the banks. 7.4 Weed cutting Weed cutting of submerged plants is frequently undertaken when flow reduction and its associated processes, such as enhanced sedimentation, have already occurred and natural environmental controls are beginning to act. For example, a species of ‘fine leaved rooted’ submerged plant which grows in a channel, has been selected given the environment of the channel, for its ability to colonise and make better use of the initial conditions than other species, when overall conditions allow any plant growth to occur at all. In natural systems, the biological factors may include the timing of the plants growth during the season to avoid excessive flows, turbid water, excessive summer temperatures or other factors as yet unidentified. One factor frequently not considered is the size of the food storage organs, e.g. rhizomes, by which the plant carries over a good reserve of building materials from one growing season to the next. For example in Nuphar, large storage organs allow both rapid growth when turbid water conditions restrict other submerged plant growth, and the production of large surface leaves which often shade out other submerged species. The maximum biomass which is achieved at any site is the result of the combination of environmental driving variables which may act in common or in opposition. Thus light may be increasing which linearly increases gross photosynthesis but increasing water temperatures may exponentially elevate respiration reducing the net photosynthetic gain. During the seasonal growth, increased biomass increases hydraulic resistance reducing the flow capacity of the channel and also reducing the supply of inorganic carbon to the plants, slowing their growth. Higher biomass increases the proportion of
R&D ROUGHNESS REVIEW 78 self shading amongst the plants. Thus even under steady flow conditions a balance can be achieved with the prime driving variable, light. It is however unusual for water flow or discharge to be constant and in cold temperate zones it is likely to decrease significantly during summer and for a lower maximum or equilibrium biomass to be achieved. In warm temperate zones, there is likely to be little inhibition of growth in winter and maximum biomass may occur earlier in the year, e.g. spring, followed by environmental growth suppressing factors such as elevated temperatures or very low flows later in the year. Traditional weed cutting is the major factor in species selection in managed rivers and channels. It is associated with reductions in species diversity, rapid and resynchronised regrowth, elevated biomasses by comparison to natural cycles, and accentuated hydraulic effects such as increases in vegetative hydraulic resistance. One study for a species of Ranunculus indicates that regular weed cutting doubled the potential seasonal maximum biomass (Dawson 1976). Conversely, this result shows that when management ceased for this species the maximum biomass halved over a four year period. Similar but less extreme reductions in several submerged species have also been noted in natural rivers (Dawson & Kern Hansen 1979). However in the region of southern England in which this study was undertaken, there was still a significant and unacceptable risk of flooding during the two critical months in summer.
600 maximum 500 potential for growth
400 typical growth curve 300
biomass weed 200 cut 100
0
0 5 10 month Figure 7 Example of a typical weed growth curve with and without weed cutting
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Table 24 Current Control techniques for aquatic and marginal vegetation by RHS vegetation morpho-type, with comments on consequences and recovery RHS vegetation Control technique Comment and Recovery morpho-type consequences Free floating plants Rarely controlled Usually lost with Follows subsequent typically algae or (may be skimmed off if de small increases in lower flow duckweeds oxygenation and fish flow. conditions. stocks are threatened). Filamentous algae Rarely controlled (can be Usually moved Follows subsequent attached shallow skimmed off if threatening downstream with lower flow nutrient rich waters fish kills). increases in flow. conditions. Mosses Not known to be Very slow if lost. attached to bed or banks controlled. Trailing bank side plants Physical control by flail Regularly lost in Rapid but seasonal. mower or hand scythe. winter flood events. Emergent reeds, rushes, Physical control by flail Removal releases Regrowth may be in flag and large grasses mover or removal of finer sediments, and the early growing underlying sediment bank destabilises banks season but later (or herbicide). [encroachment is a regrowth is slow and Cutting of underwater river re naturalising regrowth in the next stems is most effective. process and limited season may be by balance with reduced by a third. increasing water velocities and sediment supply]. Floating leaved rooted, Physical control by weed Some sediment Effectiveness may typically water lillies in cutting boat (or herbicide). movement. increase with deeper slower waters removal in the early part of growing season. Emergent broad leaved Physical control by Suspends sediments Regrowth starts rooted plants, like water dragline or excavator. with much moving immediately after cress or water parsnip downstream. the velocities reduce. Submerged broad Physical control by weed Regrowth starts leaved, Pondweeds (0.6 cutting boats. immediately. 1.2m) Submerged fine leaved, Physical control by Often releases of Regrowth often like water crowfoot, dragline or excavator, large quantities of starts immediately pondweeds or often managed plant and silt. especially growth a) shallow streams, selectively by hand becomes 0.2 0.6m, regular [‘gardened’] in fisheries resynchronised but management e.g. chalk streams. regular cutting declines if left uncut for three years. b) medium depth rivers Regular control physical Often releases of Regrowth almost 0.6 1.2m deep, regular by weed cutting boats large quantities of starts immediately, management OR occasionally by drag plant to be collected with growth line in association with on booms and some stimulated by more maintenance dredging. silt. favourable velocity conditions. c) medium depth rivers Physical control by weed Regrowth starts >1.2m deep, some cutting boats or drag line immediately but is management in association with slow maintenance dredging.
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7.4.1 Modifications and refinements to weed cutting regimes Fine leaved submerged 1. No cutting. The initial proposal for the management of submerged vegetation in channels must be the `no cut' scenario which has been shown to produce significant reductions in maximum biomass for some species. However it cannot be considered in isolation especially in smaller channels and involves some channel redesign to allow for application. 2. Selective cutting of only part of a channel, such as the centre, reduces weed cutting effort and provides some protection for the banks by the remaining marginal bands of aquatic vegetation. Uncut plants remaining would be at a physiological disadvantage because of self shading and through the reduction of water levels, which, in turn, would reduce water flows and thus limit the supply of inorganic carbon and nutrient supplies. Conversely the remaining shoots and roots of the cut central plants would be exposed to higher than normal velocities which is also likely to restrict their growth and incidentally reduce sedimentation. Within channel water capacity would also be increased during flow and thus this technique is likely to facilitate the passage of floods. Watson (1986) tested the effects on hydraulic resistance on progressive cutting showing that removal of a quarter of the stand reduced resistance slightly but that the removal of three quarters of the stand reduced resistance disproportionately lower. 3. Pre-emptive cutting . Following determination of the growth cycle of the species of aquatic plant causing a problem, alterations to the timing of weed cutting during its growing season can be attempted. As discussed above, traditional weed cutting seeks to remove the problem once it has developed; however it is advantageous in terms of cost, labour and logistics, to pre empt the developing problem by early cutting. Thus knowledge of the biology of the species is important. For example, species of Ranunculus that have traditionally been removed as biomass grows rapidly prior to flowering time. Early cutting therefore stimulates plants to regrow to satisfy a reproductive need whereas if cutting was undertaken after flowering there is fewer tendencies to regrow. Observations by a local river engineer in Southern England who commented that light autumn dredging, with minimal disturbance to the stable riverbed, suppressed plant growth for many months was linked to the exploration of the four year effect, which is: 1. The late summer suppression of growth as plant biomass declined naturally, 2. The consequent low biomass in winter which reduced the potential for growth in the next season, and 3. The encouragement of plants adapted to maintaining a presence rather than those with capacity for more rapid regrowth. Together these observations led to trials of a weed cut late in the year to reduce overwintering biomass and thus `pre empt' growth in the subsequent season. This has been shown to be an economically advantageous improvement to accepted weed cutting practices (Westlake & Dawson 1986). When pre emptive cutting, called locally `close autumn weed cutting', was tested over three years for the Wessex Water Authority in the River Frome, it indicated that the biomass in the lower river was on average 28% lower than expected at normal cutting time. Direct assessment of plant biomass, and measurements of water level changes related to the resistance to flow offered by plants, confirmed the effect (Westlake & Dawson 1986, 1988). Detailed study of the
R&D ROUGHNESS REVIEW 81 relationship of spring plant biomass to water depth, in autumn cut and autumn uncut sections, indicates that the benefit of autumn cutting may be limited to water deeper than 0.7 m, or to only the lower half of the 50 km river (Westlake & Dawson 1986). Although the experiment required spring cutting to proceed as previously, it became progressively less necessary, and almost ceased in the third year. Immediate benefits of pre emptive control included reductions in the weed removed, and consequential reductions in the logistic problems of time and labour needed and in the need for a further summer cut. A decrease in spring flooding gave an agricultural benefit. Ecological benefits accrued through the reduction in the need for a spring cut, the encouragement of less vigorously growing plants and the `four year effect', an increase in the numbers of large plants, and a change in their form. Such changes in the structure of individual plant stands require investigation. It has been observed that few, larger plants have less hydraulic resistance than many, small ones (Dawson & Robinson 1984; Westlake & Dawson 1988). Also their removal and capture on weed removal booms may well be more effective (when cutting control is necessary). These benefits were only demonstrated for one dominant plant, a species of Ranunculus and other species may act in a different manner or indeed be selected for, by this change in management. 7.5 Indirect control 7.5.1 Direct versus Indirect macrophyte control Direct management i.e. plant removal, is effective but the results are normally only short term. It is therefore best undertaken on a local basis. Indirect management aims to produce long lasting effects and stability through modifying the environmental growth controlling factors, but is slow. Eradication of plants is not practical or ecologically desirable. Achieving this in natural water bodies would require extreme measures with far reaching consequences. Direct techniques if used, should be undertaken early in the growing season or collectively, the former requires early identification or prediction of macrophyte biomass. Such pre emptive control delays the development of plants reducing the human or machine effort needed for their cutting and removal or the amelioration of the effects of plant decomposition in the system. The timing of control operations can also be more flexible and this is ecologically beneficial just as local or selective control e.g. for fishing areas or boat passages, in contrast to the extensive clearance of large areas. 7.5.2 Alternatives to the traditional techniques of river plant management Shading by bankside vegetation. Observations of the plant biomass of open and shaded sections of streams, combined with the study showing the equal importance of terrestrial and aquatic organic material to the stream system, led to the proposal that some shade could be a useful alternative to weed cutting (Dawson 1979a & b). Field experiments demonstrated that the biomasses of three dominant and problem species of macrophyte were directly proportional to the light reaching the water surface in both artificially and naturally shaded sections of stream (Dawson & Kern Hansen 1979; Dawson 1981a). These results were refined and led to the development of a proposal for management by `half shade', with recommendations for the size of vegetation for streams and rivers of differing size (Dawson & Haslam 1983).
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The theme of half shade has been developed because marginal vegetation along a river bank does provide shade from sunlight, and therefore provides an economical way of controlling the excessive growth of water plants in water courses. However excessive shade is just as ecologically undesirable as excessive plant growth. It is likely to limit fish populations by reducing cover and invertebrate food. There are however no direct data on the correlation of fish and plants, for these interrelationships are complex. Further examinations of the management of river vegetation by shade has: 1. Developed the theme of the `riverscape' in which the role of trees alongside rivers is considered to enhance both the aesthetics and economics of lowland river management (Dawson & Haslam 1983), 2. Produced data on the transverse distribution of light across rivers under varying degrees of shade, and on the degree of shade under the major compass orientations of artificial shade. This incorporates the principle of half shade by riparian vegetation. This concept is that the height of the shade should be equal to the width of the stream when the vegetation is growing on the south bank or otherwise marginal shade should interrupt direct light in summer, and 3. The proposal that trees should be part of a planned cycle of planting and cropping to avoid tree fall to the river and to provide economic benefits.
Opaque materials One short term solution, designed particularly to control critical areas of streams and rivers, during the growth period require the development of shade by marginal vegetation, is the use of lightweight opaque material which is both strong for ease of handling and gas permeable to prevent gas accumulation (Dawson & Hallows 1983). Trials using a medium weight geo textile material sheeting indicated that the time for optimum control was around 6 weeks for areas of emergent plants with rhizomes. Shorter periods gave some control, but extended periods eradicated plants and required plants to reinvade. The build up of detritus on the surface of submerged sheets enhanced the shading effect and allowed the use of less optically dense material. A planned cycle of movement of sheets of material was most important to the technique and, in fact, made it economically competitive with other methods. This material can be applied to a variety of sites and two people can readily handle areas of 400 m. The basic problem in application is that it does not give instantaneous results (unlike weed cutting), and therefore has user resistance. There is also concern by river engineers that material could be lost downstream, be caught on hatches and lead to flooding. This has not occurred in five years of stream trials. Reduction in light penetration of water Reducing light penetration can be achieved by increasing light scatter from particles in the water (turbidity) or by absorption by compounds such as dyes. Dyes added to static waterbodies early in the growing season have proven successful. The major disadvantages include the displeasing visual effect, the fast rate at which some dyes fade, settle, or are diluted, and, the toxicity to man or fish (Dawson 1981). Suspension of other very fine materials (e.g. suitably prepared clays, Bentonite (4 µ)) if applied early in the growing season and kept in suspension for several weeks, could usefully delay plant growth. Further study of such techniques is necessary before field
R&D ROUGHNESS REVIEW 83 trials are undertaken. The choice of fine material is important because some information available indicates that phosphate absorption by clays is not unusual (Lake & MacIntyre 1977). This may be advantageous in enriched natural waters but may be undesirable loss in irrigation systems. The suspension of natural sediments, for example, stocking lakes with high densities of bottom feeding Cyprinid fish, could be assessed for use in deeper irrigation channels. In Northern Europe their use is controversial but documented evidence is limited. The common carp (Cyprinus carpio L.) is normally considered to destroy vegetation directly by uprooting plants. However, its activity is expected predominantly in shallow marginal areas which are the carp's preferred feeding and spawning habitat (Mathis, 1965, Crivelli 1983, Fletcher et al. 1985). Intermittent artificial suspension of sediments will increase turbidity but may also raise nutrient load and increase algal growth. Despite the usefulness of artificial suspension in fishponds (Huet 1972), it must be considered with caution in irrigation channels because of the potential for undesirable side effects. Large irrigation channels could be redesigned to maintain or naturally resuspend fine particles and to extend periods of suspension of fine incoming particles. Short sections of channel could be enlarged (deepened) or delta regions (widened) constructed and vegetated to enhance the settlement of coarse material but not the fine material which would pass downstream to inhibit aquatic plant photosynthesis. Obstacles only in the direction of the prevailing wind (e.g. trees) could be removed to increase wind fetch or turbulence (Thomas & Compston 1980). In Northern Europe some alternative techniques simultaneously increase light penetration and transparency to encourage the development of macrophyte communities rather than algal dominated ones and are reviewed in Dawson (1986). In conclusion, aquatic macrophytes will normally be present in natural waters if light, nutrients and suitable sites are available. Their growth depends primarily upon the intensity and duration of sunlight which they receive but also upon the physical conditions of the water, its movement, temperature, clarity and chemistry (and the absence of growth inhibiting compounds). However, as they grow in response to their environment, their growth produces changes to this environment, creating their typical habitat. Thus as growth proceeds during the season, and stands of plants develop, progressive changes in the environment occur which can adversely restrict further plant growth, e.g. reductions in water velocity with increases in depth or decreasing water transfer capacity. Their growth depends upon the daily balance between photosynthesis and respiration which they can achieve within these environmental conditions and leads to the seasonal cycles of growth, maximum biomass and eventual decline. Sudden or catastrophic changes in the plants' environment, e.g. flood or `weed cutting', can also affect plant populations, either altering them when the changes are intermittent or perpetuating them when the changes are regular. When favourable growth conditions prevail, dense macrophyte growths may occur especially in shallower water (<2 m), and reduction in biomass or weed management may be undertaken. Such direct removal of excess plant is rapid and effective but short term, as the effects of cutting can stimulate synchronised regrowth accentuating the original problem for future years.
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In the current economic climate improvements to plant control techniques are more likely to be considered, such as reduced, retimed or selective removal, or the introduction of indirect techniques which moderate biomass through growth controlling factors. Control by light is a prime example of such techniques. It is direct in effect, with a good practical chance of success, as opposed to other factors, such as water velocity or nutrient limitation, which may have disproportionate or low limiting thresholds. Thus it can be seen from the examples of natural river channels, modification of the environment required by the vegetation (e.g. such as shading, elevated water velocities, increased water depths, modification weed cutting regimes, or the introduction of environmentally aware dredging practices) can reduce maintenance budgets when used in combination with existing techniques. Environmental policies and practices can be used to minimise maintenance and to improve the channel behaviour and the benefits of their application has been discussed. However, research is still necessary to resolve the potential conflicts of interest between the requirements of transferring water inexpensively in conventionally engineered channels, and the future needs to design and construct self sustaining channels with minimal maintenance requirements.
7.6 Techniques used Current best practice guidelines for physical and chemical control are given in Aquatic weed Control Operations and concentrates on basic procedures for algae, floating leaved submerged and emergent weeds (by CAPM for Environment Agency 1998). Waterway Bank Protection: A guide to erosion assessment and management details and illustrates bank erosion and it causes, assessment, remedial work and engineering and alternative strategies, and appraisal with methodology and evaluation (Cranfield University for Environment Agency 1999). A design manual by Escarameia (1998) covers river and channel revetments. Environmental options with specifications for flood defence maintenance works are profusely illustrated in annotated diagrams which cover weed cutting, dredging, moving, bushing and some enhancements operations (Environment Agency 1997). There are many other pro environment options including Lachat (1994) Control of invasive plants is becoming as area of concern and a few species are especially invasive and alter the general riparian environment in way which are not yet not fully explored or understood. These species include: • Japanese knot weed which continues to make expansive stands of dense bushy vegetation which shades out ground cover plants which hold together bankside soils reducing erosion • Giant Hogweed which similarly produces large densely covered areas and has a phyotoxic sap causing large photosensative skin blisters. Stands of Rhodendron and Asian laurel also continue to expand. Comparisons made with natives show that in a few recent decades these few invasive plants have expanded to occupy lengths of river bank similar to native plants such as bramble (Dawson & Holland 1999). Other non native species are occasionally found but apart from Australian Swamp Stonecrop (crassula helmsii) found increasingly on and in slow
R&D ROUGHNESS REVIEW 85 flowing stream and Hydrocotyle ranunculoides a very vigorous plant of slow flowing drainage ditches, none are so far of imminent concern. Former invasive plants are now almost considered part of the normal situation in slower rivers e.g. Canadian and Nuttall Pondweed.
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8. UNCERTAINTY The context of uncertainty for rivers in the national context has been broadly discussed in ‘Learning to live with rivers’ (ICE 2001) in which many aspects of floods and their management are introduced. These vary from flood estimation, in a historic and current context, risk assessment and definition and best practice, through strategic management and catchment modelling to solutions by planning, engineering, cost and sustainability, improvements in forecasting, use of natural processes and the international perspective. Specific areas of uncertainty within the project range from the general aspects of hydraulic applications such as that of measurement of water volume and movement, physical dimension of channels, to the specifics of vegetation biology, growth variation in response to environmental driving factors to the detail simply of position in channels. A paper on uncertainty estimation in the Conveyance Estimation System, which includes issues of roughness, is currently being developed and will be included in the final project report.
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9. BIBLIOGRAPHY
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Yen, CL & Overton, D.E. (1973). Shape effects on resistance in flood plain channels. Journal of Hydraulics Division, Proceedings of the American Society of Civil Engineers 99, 219 238. Yong, K.C. (1968). Scour resistance of farm dam spillways with grass dormant. University of New South Wales, Water Research Laboratory, Report No. 104. Yong, K.C. and Stone, D.M. (1967). Resistance of low cost surfaces for farm dam spillways. University of New South Wales, Water Research Laboratory, Report No. 95. Yong, K.C. and Stone, D.M. (1967). Resistance of low cost surfaces for farm dam spillways. University of New South Wales, Water Research Laboratory, Report No. 95. Yulistiyanto B, Zech y & Graf WH (1997). Flow around a cylinder: shallow water modeling with diffusion dispersion. Journal of Hydraulic Engineering 124, 419 429. Yulistiyanto B (1997). Flow around a cylinder installed in a fixed bed open channel. PhD thesis no. 1631, Polytechnique Federale, Lausanne, Switzerland. Zieman, J.C. (1976). The ecological effects of physical damage from motor boats on turtle grass beds in Southern Florida. Aquatic Botany 10, 383 388.
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APPENDICES
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Appendix A Reference Tables of data used Acement and Schneider (1989/2002) Table A1 Base values of Manning’s n, modified from Aldridge and Garnett (1973). Bed material Median size of bed Base n value material in mm Straight uniform Smooth channel channel Sand channels Sand 0.2 0.3 0.4 0.5 0.6 0.8 1.0 Stable channels and flood plains Concrete 0.012 0.018 0.011 Rock cut 0.025 Firm soil 0.025 0.032 0.020 Coarse sand 1 2 0.026 0.035 Fine gravel 0.024 Gravel 2 64 0.028 0.035 Coarse gravel 0.026 Cobble 64 256 0.03 0.05 Boulder >256 0.04 0.07
Table A2 Data from photographs of flood plains Site Description Depth of Vegetation Cd Manning’s water on density value n value floodplain for (m) trees Cypress Creek Primarily trees with base 0.8 0.0067 12 0.1 of firm soil and slight surface irregularities Bayou de Primarily trees with base 1.1 0.0067 8.8 0.11 of firm soil and slight Loutre surface irregularities Bayou de Primarily trees with base 1.1 0.0075 7.7 0.11 of firm soil and slight Loutre surface irregularities Bayou de Primarily trees with base 1.1 0.0072 8 0.11 of firm soil and slight Loutre surface irregularities Coldwater Primarily trees with base 0.9 0.0077 10.2 0.11 of silty soil and slight river surface irregularities. Few obstructions, ground cover of short weeds and grass Coldwater Primarily trees with base 0.9 0.0090 8.6 0.11 of silty soil and slight
R&D ROUGHNESS REVIEW 134 river surface irregularities. Few obstructions, ground cover of short weeds and grass Yockanookany Primarily trees with many 1.2 0.0082 7.6 0.12 small trees (0.1 to 0.2ft river diam). Base of firm soil and slight surface irregularities Flagon Bayou Mixture of large and 0.98 0.0087 11.5 0.13 small trees. Base of firm soil and minor surface irregularities with some rise Pea Creek Mixture of large and 0.88 0.0085 15.6 0.14 small trees. Base of firm soil and minor surface irregularities, rises and depressions Tenmile Creek Mixture of large and 1.25 0.0067 14.4 0.15 small trees. Base of firm soil and minor surface irregularities, rises and depressions Sixmile Creek Large trees. Base firm 1.5 0.0084 13.3 0.18 soil and minor surface irregularities, rises and depressions Thompson Mixture of large and 0.88 0.0115 22.7 0.2 small trees. Base firm soil Creek and minor surface irregularities
Table A3 Adjustment values for factors that affect the roughness of floodplains Flood plain Manning’s Description conditions n value adjustment No irregularity 0 Smoothest, flattest floodplain attainable in given bed material Minor 0.001 0.005 A few rises and dips or sloughs visible on the flood irregularity plain Moderate 0.006 0.01 More rises and dips, sloughs and hummocks may occur Severe 0.011 0.02 Flood plain very irregular in shape. Many rises and dips or sloughs are visible. Irregular ground surfaces in pasture land and furrows perpendicular to the flow. Negligible 0.000 0.004 Few scattered obstructions which include debris obstructions deposits, stumps, exposed roots, logs, piers or isolated boulders that occupy less than 5 percent of the cross sectional area. Minor 0.004 0.005 Obstructions occupy less than 15 percent of the cross obstructions sectional area. Appreciable 0.02 0.03 Obstructions occupy from 15 percent to 50 percent of obstructions the cross sectional area. Small amount 0.001 0.01 Dense growths of flexible turf grass, such as of vegetation Bermuda or weeds growing where the average depth of flow is at least two times the height of the vegetation. Supple tree seedlings such as willow,
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cottonwood, and arrow weed growing where the average depth of flow is at least three times the height of vegetation. Medium 0.01 0.025 Turf grass growing where the average depth of flow amount of is from one to two times the height of vegetation. vegetation Moderately dense stemy grass, weeds or tree seedlings growing where the average depth of flow is from two to three times the height of the vegetation. Brushy, moderately dense vegetation, similar to 1 2year old willow trees in the dormant season. Large amount 0.025 0.05 Turf grass growing where the average depth of flow of vegetation is about equal to the height of the vegetation. 8 10 years old willow or cottonwood trees intergrow with some weeds and brush (none of the vegetation in foliage) where the hydraulic radius exceeds 0.607m. Alternatively, mature row crops such as small vegetables or mature field crops where depth flow is at least twice the height of the vegetation. Very large 0.05 0.1 Turf grass growing where the average depth of flow vegetation is less than half the height of the vegetation, or moderate to dense brush or heavy stand of timber with few fallen trees and little undergrowth where depth is below branches, or mature field crops where depth of flow is less than the height of vegetation Extreme 0.1 0.2 Dense bushy willow or heavy stands of timber, few fallen trees, depth reaching branches.
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Barnes (1967)
Table A4 Data from Barnes (1967) River name Description Manning n roughness Columbia river at Slime covered cobbles and gravel 0.024 Vernite Indian Fork below Clay bed, some grass and exposed roots 0.026 Atwood Dam on banks Champlin Creek nr Gravel and rock bed. Grass banks 0.027 Colorado City, Texas Clark Fork at St Regis Well rounded boulders, d50=135mm. 0.028 Banks of gravel/boulders with tree and brush cover Clark Fork above Bed of sand/gravel and boulders 0.03 Missoula d50=175mm. Thick undergrowth on right bank Columbia River at the Left bank –sand, gravel, boulders with 0.03 Dalles, Oreg. light brush. Right bank – basalt cliffs. Bed material graded from boulders to sand Esopus Creek at Coarse gravel bed. Banks covered with 0.03 Coldbrook trees and brush Salt Creek at Roca, Sand and clay bed, banks smooth 0.03 Nebr. Blackfoot River near Gravel and boulder d50=155mm bed and 0.031 Ovando, Mont. banks Coeur d’Alene River Bed – rock on left and gravel and boulders 0.032 near Pritchard elsewhere d50=103mm. Left bank steep bedrock. Right bank – sand/gravel with heavy growth of trees and brush Rio Chama near Sand/gravel bed. Left bank rock, right 0.032, 0.036 Chamita bank gravel. Salt River Arizona Bed and bank smooth cobbles 0.032 d50=150mm Beaver Kill at Cooks Bed – coarse gravel and cobbles with 0.033 Fall, NY scattered boulders. Light brush on both banks with a few trees Clearwater River at Bed – gravel/boulders with some exposed 0.033 Kamiah, Idaho bedrock. Banks – gravel/rock with light vegetation cover Etowah River near Bed – sand/gravel with some fallen trees. 0.041, 0.039, Dawsonville Ga Lined banks with overhanging trees/brush 0.035 West Fork Bitterroot Bed – gravel/boulders d50=172mm. Left 0.036 River near Conner, bank lined with overhanging bushes. Mont. Right bank coniferous trees Yakima River at Bed – gravel/boulders. Left bank – rock 0.036 Umtanum, Wash. riprap with bushes. Right bank has some boulders, brush and weed Middle Fork Bed – gravel and small cobbles. Banks 0.037
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Vermillion River near lined with trees and small brush Danville, Ill. Wenatchee River at Bed boulders d50=162mm. Banks lined 0.037 Plain, Wash. with trees and bushes Moyie River at Bed of gravel and small boulders. Right 0.038 Eastport, Idaho bank steep with trees and brush, left bank tree and brush cover Spokane River at Bed gravel/boulders d50=195mm. Banks 0.038 Spokane, Wash. lined trees and brush Tobesofkee Creek near Bed – sand/gravel with a few outcrops. 0.043, 0.041, Macon, Ga. Banks with overhanging trees and 0.039 underbrush Bull Creek near Ira, Bed – sand/gravel/small boulders with 0.041 Tex. scattered angular rocks. Banks are irregular and eroded with sparse cover of grass and scattered small trees Middle Fork Flathead Bed – boulders d50=142mm. Banks 0.041 River near Essex, gravel/boulders with trees/brush along Mont. tops Middle Oconee River Bed – sand/gravel with several outcrops. 0.042, 0.041, near Athens, Ga. Banks – steep and lined with trees/bushes 0.044 Beaver Creek near Bed – sand/silt. Banks irregular with 0.043 Newcastle, Wyo. thick growth of brush Catherine Creek near Bed of cobbles and small boulders. Banks 0.043 Union, Oreg lined with small trees and brush Chiwawa River near Bed of bedrock with cover of boulders of 0.043 Plain, Wash. up to 0.45m. Banks have trees along tops Esopus Creek at Bed – coarse gravel to large boulders. 0.043 Coldbrook, NY Banks lined with boulders and scattered trees/brush Grand Ronde River at Bed – boulders d50=93mm. Right bank 0.043 La Grande, Oreg. steep with dense overhanging bushes Murder Creek near Bed of sand/gravel. Banks lined with 0.045 Monticello, Ga. trees above low waterline Provo River near Bed/banks smooth rounded rocks up to 0.045, 0.073 Hailstone, Utah 0.3m diam Rolling Fork near Bed – clay/silt. Banks – overhanging trees 0.046, 0.097 Boston Ky. Sth Beaverdam Creek Bed – sand. Banks irregular with 0.052, 0.047 near Dewy Rose, Ga. trees/bushes down to waterline Deep River at Bed – coarse sand with some gravel. 3 0.049 Ramseur, NC small islands with dense stand of small birch trees. Banks steep with medium growth of brush and large trees Clear Creek near Bed/banks of angular boulders up to 0.6m 0.05 Golden, Colo. diam. Chattahoochee River Bed – rock, irregular. Banks covered with 0.051, 0.074 near Leaf, Ga. thick rhododendron and small trees South Fork Clearwater Bed – rock/boulders d50=250mm. Banks 0.051
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River near Grangeville, – boulders with trees/brush along tops Idaho Cache Creek near Bed – large angular boulders. Banks – 0.053, 0.079 Lower Lake, Calif rock, boulders and some trees East Branch Ausable Bed – gravel, rock and boulders up to 0.055 River at Au Sable 1.5m. Banks lined with boulders, small Forks, NY trees and bushes Middle Branch Bed – rocks/coarse gravel with boulders 0.056 Westfield River at up to 1.5m diam. Goss Heights, Mass. Mission Creek near Bed – angular boulders up to 0.3 diam. 0.057 Cashmere, Wash. Banks lined with overhanging bushes Haw River near Bed – coarse sand with few outcrops. 0.059 Benaja, NC Banks heavily lined with overhanging birch trees North Fork Cedar Bed – large boulders. Banks irregular 0.059 River nr Lester, Wash. lined with brush, tree stumps and roots Hominy Creek at Bed – sand/gravel, some boulders up to 0.06 Candler NC. 0.5m diam Banks – overhanging trees and bushes Rock Creek Canal near Bed/bank of boulders d50=210mm 0.06 Darby, Mont. Merced River at Happy Bed – boulders, d50=253mm. Bank 0.065 Isles Bridge near topped with trees Yosemite, Calif. Pond Creek near Bed – fine sand/silt. Banks –irregular, 0.07 Louiseville, Ky heavy growth of 5 to 20cm trees above waterline Boundary Creek near Bed – boulders, d50=210mm. Banks – 0.073 Porthill, Idaho boulders with trees/brush along top Rock Creek near Bed – boulders, d50=220mm. Banks – 0.075 Darby, Mont. boulders with trees/brush
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Bathurst (1978) Research by Bathurst has shown the flow resistance for channels with large scale roughness, ie boulders and large rocks is a function of channel shape, roughness spacing and relative roughness. The determination of the size of material on the bed of a stream is based on an analysis of the relative area covered by particles of given sizes using the technique suggested by Wolman (1954). The method applies to data for which the relative roughness R/D84 <3. If using the Bathurst equation determine the frontal concentration of the roughness elements using
D84 λ1 = 0.139 log10 1.91 (A1) R where D84 = size of median axis in sample of sediment that is bigger than or equal to 84% of median axes of sample by count (m) R = hydraulic radius (m) and λ1 = frontal concentration, the ratio of the frontal cross section area of an element to the area of boundary per element The expression for the frontal concentration in equation 3.6.3 was derived from just 2 field sites and should only be applied to other sites with caution. The frontal concentration of roughness elements is then substituted in the resistance equation /1 2 2.34 7()−0.08 8 R w λ1 = (A2) f 0.365d84 d where w = surface width of flow (m) d = mean depth of flow (m) from which the Darcy Weisbach resistance coefficient can be determined. This coefficient can then be translated into a Manning’s n value using the equation 1/2 1 6 f n R = (A3) 8g
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Butler et al (1978) Three reaches of an urban stream, Bourn Brook, were studied in part of its course between the Worcester and Birmingham canal and the Bristol Road in Birmingham. The reaches of the stream were surveyed during low and medium flows. Velocity, level and channel cross section data were used to investigate the variation of Manning’s n with flow for each reach, Figure A1
Figure A1 Variation in Manning’s n with discharge for the Bourn Brook
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Datasets at CEH Dorset (ISF) Table A5 Definition of datasets available from CEH Dorset Hydraulic NGR River/Stream Site Discharge/Depth/width/(velocity?) R.Frome Dorset ST566004 R.Frome Sandhills 73 (occ), '74(2/m), 76(1/m), 77(occ), SY624949 R.Frome Southover Br. 73 (occ),76(occ) SY700908 R.Frome Greys Br. 73 (occ), '74(2/m) SY708903 R.Frome Louds Mill Guaging weir records not held SY769909 R.Frome Woodsford Br. 73 (occ), '74(2/m) SY806893 R.Frome Morton Ford SY867868 R.Frome East Stoke Guaging weir records not held SY891868 R.Frome W.Holme Br Very seldom SY924872 R.Frome Wareham Quay R.Frome Tributaries. Dorset ST567004 Wraxall Brook Sandhills 73 (occ), '74(2/m), 76(1/m), 77(occ), 73 (occ), '74(2/m), 76(occ<1/m), ST537000 R.Hooke Hooke G.W. 77(occ) ST593976 R.Hooke At M. Newton 73 (occ), '74(2/m), 76(1/m), 77(occ) SY637947 Sydling Water Grimstone R.Br. 73 (occ), '74(2/m), 76(1/m), 77(occ), SY678935 R. Cerne Charminster (ford) 73 (occ), '74(2/m), 76(1/m), 77(occ), SY712889 S. Winterbourne Came Rd Br. 73 (occ), '74(2/m) SY770862 Tadnol Brook Road Bridge(upper) 70 72(occ) 74(2/m), 76(1/m), 77(occ) at end grass Rd SY793871 Tadnol Brook (Mill) ? 70 72(occ) 72(3/m) 73(occ), 74(2/m), 76(1/m), SY811881 Tadnol Brook Broomhill Br. 77(occ), 73 (occ), '74(2/m), 76(occ 1/m), SY827868 Win Stream Burton Cross 77(occ) R.Piddle Alton Pancras ST700024 R. Piddle (culvert) 73 (occ), '74(2/m), 76(1/m) Piddletrenthide SY705997 R. Piddle (foot Br.) 73 (occ), '74(2/m) Piddlehinton (US SY714972 R. Piddle Rd Br.) L.Waterstone (Rd SY743952 R. Piddle Br.) 73 (occ), '74(occ 2/m) Puddletown (DS Rd SY757947 R. Piddle Br.) 73 (occ), '74(2/m) SY829933 R. Piddle Throop Ford 73 (occ), '74(2/m), 76(1/m) Hyde Br. (DS Rd SY865906 R. Piddle Br.) 73 (occ), '74(occ 2/m), 76(1/m) N.Mill Wareham SY920877 R. Piddle US Foot Br. 73 (occ), '74(v. occ ), 76(v.occ) 73 (occ), '74(2/m) R.Piddle Tributaries. Dorset SY774003 Devils Brook Bramblecombe (Rd
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Br.) Dewlish Foot Br. SY777983 Devils Brook (DS) 73 (occ), '74(2/m), 76(occ<1/m) Milton Abbas ST803013 The Milbourne (cottage) 73 (occ), '74(2/m) Milbourne st ??? The Milbourne Andrew (by Rd) Ashley Barn (US ST813955 The Milbourne Rd Br) Millum Head SY835962 Bere Stream outflow Above Rd Br. In SY836961 Bere Stream Wood Above foot Br. 72(3/m) 73(occ), 74(2/m), 76(dry from SY836958 Bere Stream Holly bush June), 77(occ). Below cressb ed SY83? 957 Bere Stream inflow 73 (occ), SY851955 Bere Stream Doddings Farm 72(3/m) 73(occ), 74(2/m), 76(1/m), SY856930 Bere Stream Snatsford Br.(DS) 77(occ) BereHeath SY Bere Stream Maidenfoot weir SY859920 Bere Stream Lower Rd Br. (DS)
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Chow (1959)
Table A6 manning n values from Chow (1959) Roughness values Type of Channel and Description Minimum Normal Maximum Natural streams minor streams (top width at flood stage < 100 ft) Streams on plain clean, straight, full stage, no rifts or deep pools 0.025 0.030 0.033 same as above, but more stones and weeds 0.030 0.035 0.040 clean, winding, some pools and shoals 0.033 0.040 0.045 same as above, but some weeds and stones 0.035 0.045 0.050 same as above, lower stages, more ineffective 0.040 0.048 0.055 slopes and sections same as two up, more stones 0.045 0.050 0.060 sluggish reaches, weedy, deep pools 0.050 0.070 0.080 very weedy reaches, deep pools, or floodways 0.075 0.100 0.150 with heavy stand of timber and underbrush Mountain streams, no vegetation in channel, banks usually steep, trees and brush along banks submerged at high stages bottom: gravels, cobbles, and few boulders 0.030 0.040 0.050 bottom: cobbles with large boulders 0.040 0.050 0.070 Natural streams floodplains Pasture, no brush short grass 0.025 0.030 0.035 high grass 0.030 0.035 0.050 Cultivated areas no crop 0.020 0.030 0.040 mature row crops 0.025 0.035 0.045 mature field crops 0.030 0.040 0.050 Brush scattered brush, heavy weeds 0.035 0.050 0.070 light brush and trees, in winter 0.035 0.050 0.060 light brush and trees, in summer 0.040 0.060 0.080 medium to dense brush, in winter 0.045 0.070 0.110 medium to dense brush, in summer 0.070 0.100 0.160 Trees dense willows, summer, straight 0.110 0.150 0.200 cleared land with tree stumps, no sprouts 0.030 0.040 0.050 same as above, but with heavy growth of sprouts 0.050 0.060 0.080 heavy stand of timber, a few down trees, little 0.080 0.100 0.120 undergrowth, flood stage below branches same as above, but with flood stage reaching 0.100 0.120 0.160 branches Natural streams major streams (top width at flood stage > 100 ft); the n value is less than that for minor streams of similar descrip tion because banks offer less effective resistance
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regular section with no boulder or brush 0.025 0.060 irregular and rough section 0.035 0.100 Excavated or dredged Earth, straight, and uniform clean, recently completed 0.016 0.018 0.020 clean, after weathering 0.018 0.022 0.025 gravel, uniform section, clean 0.022 0.025 0.030 with short grass, few weeds 0.022 0.027 0.033 Earth winding and sluggish no vegetation 0.023 0.025 0.030 grass, some weeds 0.025 0.030 0.033 dense weeds or aquatic plants in deep channels 0.030 0.035 0.040 earth bottom and rubble sides 0.028 0.030 0.035 stony bottom and weedy banks 0.025 0.035 0.040 cobble bottom and clean sides 0.030 0.040 0.050 Dragline excavated or dredged no vegetation 0.025 0.028 0.033 light brush on banks 0.035 0.050 0.060 Rock cuts smooth and uniform 0.025 0.035 0.040 jagged and irregular 0.035 0.040 0.050 Channels not maintained, weeds and brush uncut dense weeds, high as flow depth 0.050 0.080 0.120 clean bottom, brush on sides 0.040 0.050 0.080 same as above, highest stage of flow 0.045 0.070 0.110 dense brush, high stage 0.080 0.100 0.140 Lined or built up channels metal Smooth steel surface unpainted 0.011 0.012 0.014 painted 0.012 0.013 0.017 Lined or built up channels nonmetal Cement neat surface 0.010 0.011 0.013 mortar 0.011 0.013 0.015 Wood planed, untreated 0.010 0.012 0.014 planed, creosoted 0.011 0.012 0.015 unplaned 0.011 0.013 0.015 plank with battens 0.012 0.015 0.018 lined with roofing paper 0.010 0.014 0.017 Concrete trowel finish 0.011 0.013 0.015 float finish 0.013 0.015 0.016 finished, with gravel on bottom 0.015 0.017 0.020 unfinished 0.014 0.017 0.020 gunite, good section 0.016 0.019 0.023 gunite, wavy section 0.018 0.022 0.025 on good excavated rock 0.017 0.020
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on irregular excavated rock 0.022 0.027 Concrete bottom float finish with sides of: dressed stone in mortar 0.015 0.017 0.020 random stone in mortar 0.017 0.020 0.024 cement rubble masonry, plastered 0.016 0.020 0.024 cement rubble masonry 0.020 0.025 0.030 dry rubble or riprap 0.020 0.030 0.035 Gravel bottom with sides of: formed concrete 0.017 0.020 0.025 random stone mortar 0.020 0.023 0.026 dry rubble or riprap 0.023 0.033 0.036 Brick glazed 0.011 0.013 0.015 in cement mortar 0.012 0.015 0.018 Masonry cemented rubble 0.017 0.025 0.030 dry rubble 0.023 0.032 0.035 Dressed ashlar 0.013 0.015 0.017 Asphalt smooth 0.013 0.013 rough 0.016 0.016 Vegetal lining 0.030 0.500 Extract of Manning’s ‘n’ roughnesses, for channels with vegetation from Chow (1981) which includes data from observations by Horton 1916 and on artificial channels from King 1954. Comment: variable use of the word weedy infers terrestrial ruderal species if on banks but sometimes normal aquatic plants when in water Table A7 Manning’s n values for different types of channel Type of channel and description Values of Manning’s n min mid max B. LINED OR BUILT-UP CHANNELS a. vegetal linings 0.030 0.500 C. EXCAVATED OR DREDGED a. Earth, straight and uniform 1. With short grass, few weeds 0.022 0.027 0.033 b. Earth, winding and sluggish 2. grass,some weeds 0.025 0.030 0.033 3. dense weeds or aquatic plants in deep channels 0.030 0.035 0.040 5. stony bottom and weedy sides 0.025 0.035 0.040 c. Dragline excavated or dredged 2. light brush ( wood bushes) on banks 0.035 0.050 0.060 e. Channels not maintained, weeds and brush uncut 1. dense weeds high as flow depth 0.050 0.080 0.120 2. clean botton, brush on sides 0.040 0.050 0.080 3. clean botton, brush on sides highest stage of flow 0.045 0.070 0.110
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4. dense brush, high stage 0.080 0.100 0.140 D NATURAL STREAMS D1. minor streams - width at flood stage <30m a. streams on plain (=low gradient or lowland) 2. clean, straight, full stage, no rifts/deep pools,some 0.030 0.035 0.040 stones & weeds 4. clean, winding, some pools & shoals, some weeds 0.035 0.045 0.050 and stones 7. sluggish reaches, weedy, deep pools 0.050 0.070 0.080 8. very weedy reaches, deep pools 0.075 0.100 0.150 or (?) floodways with heavy stand of timber and underbrush D2. Flood plains a. pasture, no brush 1. short grass 0.025 0.030 0.035 2. tall grass 0.030 0.035 0.050 b. cultivated areas 1. no crop 0.020 0.030 0.040 2. mature row crops 0.025 0.035 0.045 3. mature field crops 0.030 0.040 0.050 c brush 1. scattered brush (heavy) dense 0.035 0.050 0.070 weeds 2. light brush and trees winter 0.035 0.050 0.060 3. light brush and trees summer 0.040 0.060 0.080 4. medium to dense brush winter 0.045 0.070 0.110 5. medium to dense brush 0.070 0.100 0.160 summer d. trees 1. dense willows, summer, straight 0.110 0.0150 0.200 2. cleared land with tree stumps, 0.030 0.040 0.050 no sprouting 3. densely sprouting 0.050 0.060 0.080 4. dense stands of trees, 0.080 0.100 0.120 occasionally fallen, flood stage to below branches 5. flood stage at level of branches 0.100 0.120 0.160 D3. Major streams - width at flood stage >30m. (n values are lower than minor streams as proportionally less resistance) a. regular section without boulders or brush 0.025 0.060 b. irregular and rough section 0.035 0.100 Manning’s unit ‘n’s for vegetation ‘roughnesses’ based on the text for ‘n4’ groups for computation using the additive relationship combined and revised from Chow (1981). Comment: no natural in channel vegetation except for Bullrush. No clear indication of measurements deep, shallow etc., re. difference between UK and US rivers. ‘Brush’ assumed to be short and tall bushes
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Table A8 Effects of vegetation of unit n values Ratio of Effect of vegetation average depth of unit ‘n’s (for conditions comparable to examples): water flow : height of vegetation min max 1. Low Very deep +0.005 +0.010 a) dense growths of flexible turf 2 3 : 1 grasses or weeds (?) 3 4 : 1 b) flexible tree seedlings/whips eg willow 2. Medium deep +0.010 +0.025 a) turf grasses 1 2 : 1 b) ‘stemmy’ grasses, weeds or tree 2 3 : 1 saplings with moderate cover bankside c) bushes, moderately dense, as 1 2 year old dormant willow along channel sides, no bed vegetation and HR >0.6m 3. High Medium +0.025 +0.050 a) turf grasses 1 : 1 b) dormant 8 10 year old willow trees with weeds and brush (not in leaf), HR >0.6m c) bushy willows 1 year old, in leaf and with weeds in leaf, no bed vegetation and HR >0.6m 4. Very high shallow +0.050 +0.100 a) turf grasses <0.5 : 1 b) growing bushy willows of 1 year(?) with weeds in leaf along bankside slopes or dense growth of Bulrush ( Typha ) on channel bed with HR <3 4m c) trees, bushes and weeds in leaf and HR <3 4m
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Cowans (1956)
This method involves the selection of a basic value of Manning’s n for a uniform, straight and regular natural channel. The basic value is then adjusted for the effects of surface irregularities, shape and size of channel cross section, obstructions, vegetation and flow conditions and the meandering of the channel. By this method the value of n may be calculated by: n = (n 0 + n 1 + n 2 + n 3 + n 4)M 5 n0 is a basic value for a straight, uniform smooth channel in the natural materials involved The conditions of straight alignment, uniform cross section and smooth side and bottom surfaces should be kept in mind. The basic Manning’s n will only vary with the materials forming the sides and bottom of the channel. n1 is a value added to n 0 to correct for the effect of surface irregularities This selection is based on the degree of roughness or irregularity of the channel sides and bottom n2 is a value for variations in shape and size of the channel cross-section Selection of a modifying value for variations in shape and size of the cross section will depend primarily on the frequency with which large and small sections alternate and secondarily on the magnitude of the changes. n3 is a value for the obstructions The selection is based on the presence and characteristics of obstructions such as debris deposits, stumps, exposed roots, boulders, fallen and lodged logs. n4 is a value for vegetation and flow conditions The retarding effect of vegetation is probably due primarily to the turbulence induced as the water flows around and between the limbs, stems and foliage and secondarily to a reduction in cross section. In judging the retarding effect of vegetation, critical consideration should be given to the following: height of vegetation in relation to depth of flow; capacity of vegetation to resist bending; the degree to which the cross section is occupied or blocked out; the transverse and longitudinal distribution of vegetation of different types, densities and heights in the reach under consideration. M5 is a correction factor for meandering of channel The sinuosity of a meander is defined as the ratio of the of the length along the channel centre line (between two points) to the straight line distance between the points. Values for n 0 to n 4 and M 5 may be selected from Table below according to the given conditions.
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Channel Values condition Earth 0.02 Rock cut 0.025 Material involved n0 Fine gravel 0.024 Coarse gravel 0.028 Smooth 0.000 Degree of Minor 0.005 n1 irregularity Moderate 0.010 Severe 0.020 Variations of Gradual 0.000 channel cross Alternating occasionally n2 0.005 section Alternating frequently 0.010 to 0.015 Negligible 0.000 Relative effect of Minor 0.010 0.015 n3 obstructions Appreciable 0.025 0.050 Severe 0.040 0.060 Low 0.005 to 0.010 Medium 0.010 to 0.025 Vegetation n4 High 0.025 to 0.050 Very High 0.050 to 0.1 Minor (sinuosity 1.0 to 1.20) 1.000 Degree of Appreciable ( sinuosity = 1.2 to 1.5) M 1.150 meandering 5 Severe (sinuosity = 1.5 and greater) 1.300
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Dawson & Henville (draft paper) Hydraulic flow resistance and the fine leaved submerged plant Oenanthe fluviatilis in the lower River Piddle, Dorset, UK The mean depth, width and hydraulic roughness (as Manning `n' and equivalent sand grain roughness) before (2.1 m 3 s 1, 9 June 1986) and after (1.45 m 3 s 1 14 July 1986) removal of Oenanthe fluviatilis and in the following spring ( ≈ .68 m 3 s 1 12 May 1987) following `light' dredging in the previous autumn for sections of the lower River Piddle, Wareham, Dorset, UK and towards the end of the year with fully developed vegetation (1.13 m 3 s 1 27 October 1988). Table A10 Hydraulic flow resistance of a fine leaved submerged plant in the lower River Piddle, Dorset, UK Sections Reach X A A B C D D E 1 2 3 4 Length, m 620 230 220 520 Mean water depth: before weed cut 9.6.86 0.93 0.74 0.94 after weed cut 14.7.86 0.86 0.54 0.86 after dredging 12.5.87 0.88 0.93 0.55 0.84 0.95 0.85 0.51 0.78 Mean width: before weed cut 8.7 14.7 10.5 after weed cut 8.3 12.0 9.2 after dredging 9.0 9.0 12.2 8.4 8.5 8.2 11.3 7.8 Mean velocity: before weed cut 0.26 0.19 0.21 after weed cut 0.20 0.22 0.18 after dredging 0.34 0.30 0.48 0.41 0.14 0.16 0.20 0.19 Mannings `n' (0.070) 0.090 0.17 0.11 - 0.089 0.11 0.098 0.026 0.036 0.060 0.040 0.126 0.210 0.147 0.083 Sand Grain Roughness (1.9) 2.7 4.3 3.8 2.7 2.4 3.4 0.09 0.34 0.93 0.36 4.06 5.89 2.49 2.20
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Gilley and Kottwitz (1993)
Darcy Weisbach roughness coefficients were measured for corn, cotton, sorghum, soybeans, sunflower and wheat vegetation. Different orientations of the crops, parallel and perpendicular to the flow were tested which gave some very useful results as detailed in the tables below. A11 Darcy Weisbach roughness coefficients for rows parallel to the flow Description Friction factor values Manning’s n roughness Upper Lower Upper Lower Corn 0.081 0.0018 0.24 0.036 Cotton 0.03 0.0001 0.14 0.008 Sorghum 0.094 0.0005 0.26 0.019 Soybeans 0.059 0.005 0.21 0.05 Sunflower 0.089 0.003 0.25 0.046 Wheat 2.2 0.11 1.26 0.28
A12 Darcy Weisbach roughness coefficients for rows perpendicular to the flow Description Friction factor values Manning’s n roughness Upper Lower Upper Lower Corn 0.025 0.0002 0.134 0.012 Cotton 0.0094 0.0004 0.082 0.017 Sorghum 0.012 0.0003 0.093 0.015 Soybeans 0.031 0.0019 0.149 0.037 Sunflower 0.02 0.0002 0.120 0.012 Wheat 0.024 0.0003 0.13 0.015
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Green and Garton (1983) A13 Grass cover retardance class equations Retardance Equation Limits of VR (m 2/s) Class n = 0.44 1.62VR VR < 0.1542 A 0.0223 n = 0.046 + 0.1542 < VR VR n = 0.403 3.3356VR VR < 0.0535 0.0096 0.0535 < VR < n = 0.046 + B VR 0.1792 0.0115 n = 0.0354 + 0.1792 < VR VR 0.0046 n = 0.034 + VR < 0.0833 VR C 0.0051 n = 0.028 + 0.0833 < VR VR 0.002 n = 0.038 + VR < 0.100 VR D 0.0028 n = 0.03 + 0.100 < VR VR 0.0007 n = 0.029 + VR < 0.123 VR E 0.0015 n = 0.0225 + 0.123 < VR VR
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Hey and Thorne (1986)
A14 Data from Hey and Thorne, 1986 depth Manning’s d Veg River Location 50 Sediment type (m) n (mm) type Otter Dotton 1.58 0.03 56.5 Coarse gravel/cobbles 3 Exe Thoverton 1.46 0.028 60.6 Cobbles 2 Exe Stoodleigh 1.77 0.034 82.9 Cobbles 3 East Dart Bellever 1.07 0.05 109 Cobbles 2 Camel Denby 1.39 0.033 24 Med gravel 3 Fowey Restormel 1.46 0.027 61 Coarse gravel/cobbles 4 West Dar Dunnabridge 1.25 0.06 176 Boulders 2 Teign Preston 2.07 0.024 41 Coarse gravel 4 Erme Ermington 1.64 0.035 46 Coarse gravel 4 Neath Resolven 2.33 0.027 70 Cobbles 4 Usk Llandetty 2.5 0.027 66 Cobbles 3 Yscir Pontaryscir 1.51 0.042 67 Cobbles 3 Hirnant Rhiwaedog 1.14 0.05 60 Cobbles 4 Dyfrdwy NewInn 1.11 0.026 43 coarse gravel 2 Glaslyn Beddgelert (1) 1.06 0.032 75 Cobbles 2 Glaslyn Beddgelert (2) 1.22 0.044 71 Cobbles 2 Alwen Druid 1.18 0.031 45 Coarse gravel 2 Ceidog Llandrillo 1.23 0.032 65 Cobbles 4 Lugg Byton (1) 0.86 0.035 48 Coarse gravel 2 Lugg Byton (2) 0.96 0.047 35 Coarse gravel 1 Frome Yarkhill 1.75 0.048 19 Med gravel 4 Pinsley Brook Cholstrey Mill 0.82 0.031 14 Med gravel 4 Dove Izaak Newton 0.5 0.046 48 Coarse gravel 1 Burbage Brook Burbage 0.72 0.041 11 Med gravel 4 Manifold Hulme End (1) 1.12 0.041 43 Coarse gravel 2 Hamps Waterhouses 1.07 0.04 55 Coarse gravel/cobbles 2 Churnet Rocester 1.96 0.042 27 Med gravel 3 Broadway Foot Rye 1.68 0.034 81 Cobbles 4 (1) Broadway Foot Rye 1.9 0.033 84 Cobbles 4 (2) Snaizeholme Low Houses 0.51 0.047 55 Coarse gravel/cobbles 1 Beck (1) Snaizeholme Low Houses 0.59 0.039 86 Cobbles 1 Beck (2) Nidd Birstwith 1.92 0.031 79 Cobbles 4 Wylye Norton Bavant 0.82 0.036 17 Med gravel 2 Alwin Clennel 0.5 0.04 66 Cobbles 1 Bottoms Beck Bottom's Beck 1 0.042 68 Cobbles 4 Flume Coquet Bygate 0.87 0.07 74 Cobbles 1 Croasedale Beck Croasedale 1.29 0.04 77 Cobbles 4 Temple Eden 2.69 0.047 56 Coarse gravel/cobbles 1 Sowersby Warwick Eden 3.21 0.051 50 Coarse gravel/cobbles 1 Bridge Cropple How Esk 1.26 0.028 53 Coarse gravel/cobbles 4 (1) Cropple How Esk 1.34 0.037 28 Med gravel 2 (2)
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Glendaranmaken Threlkeld 1.22 0.037 42 Coarse gravel 2 Hindurn Wray (1) 1.73 0.042 81 Cobbles 4 Hindurn Wray (2) 1.28 0.042 91 Cobbles 1 Hodder Hodderplace 2.61 0.035 66 Cobbles 4 Irthing Greenholme 1.34 0.029 36 Med gravel 1 Kielderburn Kielder 1.05 0.06 64 Coarse gravel/cobbles 1 Mint Mint Bridge 1.62 0.048 58 Coarse gravel/cobbles 4 Rede Rede's Bridge 1.44 0.038 130 Cobbles/boulders 2 Sprint Sprint Mill 1.29 0.038 70 cobbles 3 Tarset Burn Greenhaugh 1.85 0.042 123 Cobbles/boulders 4 Teviot Hawick 2.13 0.05 71 Cobbles 3 Tweed Bokside 2.05 0.028 60 Coarse gravel/cobbles 1 Tweed Lyneford 1.47 0.028 41 Coarse gravel 2 Tweed Peebles 2.09 0.027 69 Cobbles 3 North Tyne Tarset 2.14 0.041 92 cobbles 3 Usway Burn Shillmoor 0.78 0.03 114 Cobbles/boulders 4 Yarrowater Phillip Haugh 1.75 0.036 84 cobbles 3 Asker Bridport 1.22 0.038 183 Boulders 3 Frome Loudsmill 0.65 0.025 20 Med gravel 1 Chittern Codford 0.68 0.035 23 Med gravel 2 Manifold Hulme End (2) 1.32 0.027 49 Coarse gravel 3
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Hicks and Mason (1991)
A15 Data from Hicks and Mason (1991) Hydaulic Flow radius Roughness Site Description range range range (m3/s) (m) Poutu at Ford Bed – eroded lava flow. Banks 2.31 0.28 0.36 0.015 0.017 – grasses and broom 6.36 Ngaruroro at Bed – med/fine gravel. Banks 151 563 1.69 2.01 0.015 0.019 Chesterthorpe and berms are grassed Bridge Wanganui at Te Man made channel with bed 6.75 0.81 1.04 0.018 0.022 Whaiau Canal and banks sand/gravel. Banks 13.5 have grasses and flaxes Loganburn at Bed – gravel with small 1.85 0.35 0.48 0.02 0.039 Gorge cobbles. Banks lined with 5.82 grass Wanganui at Man made channel. 6.15 0.83 1.5 0.022 0.025 Wairehu Canal Bed/banks of uniformly sized 31.9 cobbles. Broom along banks Waipaoa at Bed – fine gravel/silt. Banks 19.8 672 0.55 3.06 0.023 0.029 Kanakanaia lined with willows Waiau at Bed – large cobbles, boulders 21.5 527 1.03 3.08 0.016 0.029 Sunnyside and bedrock. Banks native brush Hakataramea Bed of cobbles with small 1.36 0.18 0.75 0.022 0.031 above main boulders. Left bank willows. 22.8 highway bridge Right bank tussock Clutha at Bed – fine gravel to boulders ~ 126 247 1.37 1.89 0.027 0.033 Lowburn 300mm diam. Banks of cobble boulder 100 to 300mm diam Maruia at Falls Bed – sand with some 69.5 511 1.58 3.12 0.026 0.029 silt/gravel. Banks of overhanging trees, dense scrub Orere at Bridge Bed – smooth boulders to 9.41 0.64 1.12 0.023 0.032 small pebbles and some sand. 50.6 Banks grassed with some scrub on right bank Grey at Dobson Bed – cobbles. Right bank – 73 3220 0.67 3.9 0.025 0.031 bedrock, cobbles and soil with sparse bush cover. Left bank – cobbles, silt and soil with thick bush cover, overhanging trees Avon at Bed – angular cobbles and 1.83 0.4 – 1.01 0.026 – 0.04 Gloucester small boulders in muddy base. 17.3 Street bridge Left bank – steep and grassed. Right bank – lower grassy berm
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Monowai below Bed – coarse gravel and 5.64 24.1 0.47 0.88 0.026 0.03 Control Gates cobbles. Banks lined with flax and overhanging willows Piako at Bed – mud and sand. Banks 2.82 18.9 0.51 1.66 0.022 0.032 Paeroa Tahuna lined with grass Bridge Waikato at Bed – sand/gravel with mud. 237 874 2.24 4.32 0.028 0.039 Ngaruawahia Banks lined with willows Cableway except for small patches of other trees and gorse Heathcote at Bed – angular cobbles and 1.22 8.21 0.37 1.27 0.028 0.034 Sloan Terrace gravel mixed with mud and silt. Banks steep with long grass Taieri below Bed – coarse gravel and small 0.78 27.1 0.3 0.96 0.02 0.047 Patearoa Power cobbles. Banks lined with Station grass. Taieri at Bed – boulders and bedrock. 0.92 14.3 0.18 0.61 0.026 0.033 MacAtamneys Banks grassy with tussocks. Few willows on each bank Ongarue at Bed – gravel/cobbles. 10.5 241 0.87 3.03 0.022 0.05 Taringamotu Farmland grasses line both banks Pomahaka at Bed – coarse gravel/large 4.58 114 0.59 1.68 0.029 0.039 Burkes Ford cobbles. Right bank – willows, left bank grass Waikohu at No. Bed – gravel to large cobbles 18.7 19.1 1.02 1.04 0.032 0.033 1 bridge with some exposed bedrock. Banks – overhanging trees Mangaheia at Bed ranges from gravel to 7 60 0.86 2.06 0.029 0.044 Willowbank large boulders. Banks grassed with overhanging willows Oakdean Canal Large man made canal with 4.9 20.5 1.77 1.85 0.027 0.037 at Oakdean bed/banks of compacted Culvert gravel/boulders with areas of silt/weeds Waiau Water Man made lined irrigation 0.33 2.52 0.18 0.38 0.027 0.045 race at Lateral 2 channel with bed of cobbles/gravel. Banks long grass
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Higginson and Johnston (1989)
The variation in Manning n through a pool riffle sequence is shown in Figure A2 to establish the range of Manning n for a range of discharges.
Figure A2 Variation in Manning’s n through a pool riffle sequence for a range of discharges
This figure shows that there is a considerable variation in n between pool and riffle at low discharges. The differences decreased with increasing discharges and the effect of the pool riffle became insignificant at higher flows. At these high flows the effect of the pool or riffle on the hydraulic mean depth became small. The Stickler formula relates the roughness properties of the channel n, to the grain roughness k s in mm by the formula
1 6 n = 0.01355ks (A4)
Higginson and Johnson related the measured values of n in the rivers assessed with the values of n calculated. The difference in n and n s, Stickler’s roughness value, can be plotted against velocity. Regression analysis of the data gave the following relationship: I0.02922 R 0.03978 n n = log (A5) s 10 0.0063 0.1025 d35 V where d 35 is the grain size in mm, I is the slope of the channel in cm per 100m of channel and n s is the Stickler’s estimated roughness value. The Higginson and Johson approach was developed in specific rivers and the technique application should only be applied to similar rivers. If the method is applied to dissimilar rivers the plan form of the channel must be considered.
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Klassen and Van Der Zwaard (1974)
Figure A3 which is reproduced from Klassen and Van Der Zwaard’s paper, shows the effect of prototype hedge spacing and water depth on the Chezy roughness coefficient. Two sets of curves are shown; one set without organic trash trapped by the hedges and one set with organic trash and a decrease in the Chezy coefficient i.e an increase in roughness. The curves presented in the figure below are for an unvegetated flood berm roughness height of 0.07m. The hedges simulated by Klassen and Van Der Zwaard were perpendicular to the flow direction.
Figure A3 Effect of prototype hedge spacing and water depth on Chezy roughness coefficient Figure A4 also reproduced from Klassen and Van Der Zwaard, illustrates the effect of tree density and prototype water depth on Chezy coefficient. The tree density, n, is defined as the number of trees per unit area. An increase in tree density results in a decrease in Chezy coefficient and thus an increase in resistance. The curves presented in Figure A4 are for an unvegetated flood berm roughness height of 0.07m.
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Figure A4 Effect of tree density and prototype water depth on Chezy coefficient The values for Chezy coefficient given in the above can be converted to Manning’s n R 6/1 using the formula n = to give the table below. C Table A16 Manning roughness coefficients for clean and dirty hedgerows
Hedgerow Manning’s ‘n’ roughness coefficient for clean or dirty separation hedgerows with varying flow depths (m) 0.25m 0.50m 1.00m 1.50m 2.00m Clean Dirty Clean Dirty Clean Dirty Clean Dirty Clean Dirty 50 0.038 0.072 0.045 0.089 0.053 0.091 0.054 0.086 0.051 0.080 100 0.032 0.053 0.032 0.064 0.042 0.067 0.042 0.063 0.041 0.060 250 0.029 0.040 0.031 0.045 0.029 0.045 0.032 0.045 0.032 0.041 500 0.028 0.035 0.028 0.036 0.029 0.037 0.027 0.036 0.029 0.034 1000 0.027 0.031 0.027 0.032 0.027 0.031 0.025 0.029 0.027 0.027
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Kouwen N and Fathi-Moghadam M (2000)
The paper investigates the friction factors for coniferous trees along rivers with the purpose of modelling the trees to help engineers estimate the Darcy Weisbach friction factor and Manning’s n for non sumerged, flexible vegetation in the vegetated zones of river cross sections. The paper gives a table of Estimated Manning’s n values for the vegetated zone of rivers and floodplains for just covered and just submerged conditions. The depth of water is 2m and the height of trees are on average 3m. The first table gives the Manning’s values for just submerged conditions with the total area covered. The subsequent tables give values for 75%, 50% and 25% submergence with full, 75% 50% and 25% area covered.
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Table A17 Manning’s n values for vegetatel zones of rivers and floodplains Total area total submergence Total area 50% submergence Manning’s n Manning’s n Velocity White Austrian Velocity White Austrian Cedar Spruce m/s pine pine (m/s) Cedar Spruce pine pine 0.1 0.19 0.201 0.198 0.208 0.1 0.268 0.284 0.280 0.294 0.2 0.162 0.171 0.169 0.178 0.2 0.229 0.241 0.239 0.252 0.3 0.148 0.156 0.154 0.162 0.3 0.209 0.220 0.218 0.229 0.4 0.138 0.146 0.144 0.151 0.4 0.195 0.206 0.204 0.214 0.5 0.131 0.139 0.137 0.144 0.5 0.185 0.196 0.194 0.204 0.6 0.126 0.133 0.131 0.138 0.6 0.178 0.188 0.185 0.195 0.7 0.122 0.129 0.127 0.133 0.7 0.172 0.182 0.180 0.188 0.8 0.118 0.125 0.123 0.129 0.8 0.166 0.176 0.174 0.182 0.9 0.115 0.121 0.12 0.126 0.9 0.162 0.171 0.170 0.178 1 0.112 0.118 0.117 0.123 1 0.158 0.166 0.165 0.174 1.1 0.11 0.116 0.114 0.12 1.1 0.155 0.164 0.161 0.170 1.2 0.107 0.114 0.112 0.118 1.2 0.151 0.161 0.158 0.167 1.3 0.105 0.111 0.11 0.115 1.3 0.148 0.156 0.156 0.163 1.4 0.104 0.11 0.108 0.113 1.4 0.147 0.155 0.153 0.160 1.5 0.102 0.108 0.106 0.112 1.5 0.144 0.152 0.150 0.158 1.6 0.101 0.106 0.105 0.11 1.6 0.142 0.149 0.148 0.156 1.7 0.099 0.105 0.103 0.109 1.7 0.140 0.148 0.146 0.154 1.8 0.098 0.103 0.102 0.107 1.8 0.138 0.145 0.144 0.151 1.9 0.097 0.102 0.101 0.106 1.9 0.137 0.144 0.143 0.145 2 0.096 0.101 0.1 0.105 2 0.135 0.142 0.141 0.148 Total area 75% submergence Total area 25% submergence Manning’s n Manning’s n Velocity White Austrian Cedar Spruce Velocity White Austrian (m/s) pine pine (m/s) Cedar Spruce pine pine 0.1 0.219 0.232 0.228 0.2401 0.1 0.38 0.402 0.396 0.416 0.2 0.187 0.197 0.195 0.2055 0.2 0.324 0.342 0.338 0.356 0.3 0.170 0.180 0.177 0.1870 0.3 0.296 0.312 0.308 0.324 0.4 0.159 0.168 0.166 0.174 0.4 0.276 0.292 0.288 0.302 0.5 0.151 0.160 0.158 0.1662 0.5 0.262 0.278 0.274 0.288 0.6 0.145 0.153 0.151 0.1593 0.6 0.252 0.266 0.262 0.276 0.7 0.140 0.148 0.146 0.1535 0.7 0.244 0.258 0.254 0.266 0.8 0.136 0.144 0.142 0.1489 0.8 0.236 0.25 0.246 0.258 0.9 0.132 0.139 0.138 0.1454 0.9 0.23 0.242 0.24 0.252 1 0.129 0.136 0.135 0.1420 1 0.224 0.236 0.234 0.246 1.1 0.127 0.133 0.131 0.1385 1.1 0.22 0.232 0.228 0.24 1.2 0.123 0.131 0.129 0.1362 1.2 0.214 0.228 0.224 0.236 1.3 0.121 0.128 0.127 0.1327 1.3 0.21 0.222 0.22 0.23 1.4 0.120 0.127 0.124 0.1304 1.4 0.208 0.22 0.216 0.226 1.5 0.117 0.124 0.122 0.1293 1.5 0.204 0.216 0.212 0.224 1.6 0.116 0.122 0.121 0.1270 1.6 0.202 0.212 0.21 0.22 1.7 0.114 0.121 0.118 0.1258 1.7 0.198 0.21 0.206 0.218 1.8 0.113 0.118 0.117 0.1235 1.8 0.196 0.206 0.204 0.214 1.9 0.112 0.117 0.116 0.1223 1.9 0.194 0.204 0.202 0.212 2 0.110 0.116 0.115 0.1212 2 0.192 0.202 0.2 0.21
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75% area total submergence 75% area 50% submergence Manning’s n Manning’s n Velocity White Austrian Velocity White Austrian (m/s) Cedar Spruce pine pine (m/s) Cedar Spruce pine pine 0.100 0.165 0.174 0.171 0.180 0.100 0.233 0.246 0.242 0.255 0.200 0.140 0.148 0.146 0.154 0.200 0.198 0.209 0.207 0.218 0.300 0.128 0.135 0.133 0.140 0.300 0.181 0.191 0.189 0.198 0.400 0.120 0.126 0.125 0.131 0.400 0.169 0.179 0.176 0.185 0.500 0.113 0.120 0.119 0.125 0.500 0.160 0.170 0.168 0.176 0.600 0.109 0.115 0.113 0.120 0.600 0.154 0.163 0.160 0.169 0.700 0.106 0.112 0.110 0.115 0.700 0.149 0.158 0.156 0.163 0.800 0.102 0.108 0.107 0.112 0.800 0.145 0.153 0.151 0.158 0.900 0.100 0.105 0.104 0.109 0.900 0.141 0.148 0.147 0.154 1.000 0.097 0.102 0.101 0.107 1.000 0.137 0.145 0.143 0.151 1.100 0.095 0.100 0.099 0.104 1.100 0.135 0.142 0.140 0.147 1.200 0.093 0.099 0.097 0.102 1.200 0.131 0.140 0.137 0.145 1.300 0.091 0.096 0.095 0.100 1.300 0.129 0.136 0.135 0.141 1.400 0.090 0.095 0.094 0.098 1.400 0.127 0.135 0.132 0.138 1.500 0.088 0.094 0.092 0.097 1.500 0.125 0.132 0.130 0.137 1.600 0.087 0.092 0.091 0.095 1.600 0.124 0.130 0.129 0.135 1.700 0.086 0.091 0.089 0.094 1.700 0.121 0.129 0.126 0.133 1.800 0.085 0.089 0.088 0.093 1.800 0.120 0.126 0.125 0.131 1.900 0.084 0.088 0.087 0.092 1.900 0.119 0.125 0.124 0.130 2.000 0.083 0.087 0.087 0.091 2.000 0.118 0.124 0.122 0.129 75% area 25% submergence 75% area 75% submergence Manning’s n Manning’s n Velocity White Austrian Velocity White Austrian (m/s) Cedar Spruce pine pine (m/s) Cedar Spruce pine pine 0.100 0.329 0.348 0.343 0.360 0.100 0.190 0.201 0.198 0.208 0.200 0.281 0.296 0.293 0.308 0.200 0.162 0.171 0.169 0.178 0.300 0.256 0.270 0.267 0.281 0.300 0.148 0.156 0.154 0.162 0.400 0.239 0.253 0.249 0.262 0.400 0.138 0.146 0.144 0.151 0.500 0.227 0.241 0.237 0.249 0.500 0.131 0.139 0.137 0.144 0.600 0.218 0.230 0.227 0.239 0.600 0.126 0.133 0.131 0.138 0.700 0.211 0.223 0.220 0.230 0.700 0.122 0.129 0.127 0.133 0.800 0.204 0.217 0.213 0.223 0.800 0.118 0.125 0.123 0.129 0.900 0.199 0.210 0.208 0.218 0.900 0.115 0.121 0.120 0.126 1.000 0.194 0.204 0.203 0.213 1.000 0.112 0.118 0.117 0.123 1.100 0.191 0.201 0.197 0.208 1.100 0.110 0.116 0.114 0.120 1.200 0.185 0.197 0.194 0.204 1.200 0.107 0.114 0.112 0.118 1.300 0.182 0.192 0.191 0.199 1.300 0.105 0.111 0.110 0.115 1.400 0.180 0.191 0.187 0.196 1.400 0.104 0.110 0.108 0.113 1.500 0.177 0.187 0.184 0.194 1.500 0.102 0.108 0.106 0.112 1.600 0.175 0.184 0.182 0.191 1.600 0.101 0.106 0.105 0.110 1.700 0.171 0.182 0.178 0.189 1.700 0.099 0.105 0.103 0.109 1.800 0.170 0.178 0.177 0.185 1.800 0.098 0.103 0.102 0.107 1.900 0.168 0.177 0.175 0.184 1.900 0.097 0.102 0.101 0.106 2.000 0.166 0.175 0.173 0.182 2.000 0.096 0.101 0.100 0.105
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50% area total submergence 50% area 50% submergence Manning’s n Manning’s n Velocity White Austrian Velocity White Austrian (m/s) Cedar Spruce pine pine (m/s) Cedar Spruce pine pine 0.100 0.134 0.142 0.140 0.147 0.100 0.190 0.201 0.198 0.208 0.200 0.115 0.121 0.120 0.126 0.200 0.162 0.171 0.169 0.178 0.300 0.105 0.110 0.109 0.115 0.300 0.148 0.156 0.154 0.162 0.400 0.098 0.103 0.102 0.107 0.400 0.138 0.146 0.144 0.151 0.500 0.093 0.098 0.097 0.102 0.500 0.131 0.139 0.137 0.144 0.600 0.089 0.094 0.093 0.098 0.600 0.126 0.133 0.131 0.138 0.700 0.086 0.091 0.090 0.094 0.700 0.122 0.129 0.127 0.133 0.800 0.083 0.088 0.087 0.091 0.800 0.118 0.125 0.123 0.129 0.900 0.081 0.086 0.085 0.089 0.900 0.115 0.121 0.120 0.126 1.000 0.079 0.083 0.083 0.087 1.000 0.112 0.118 0.117 0.123 1.100 0.078 0.082 0.081 0.085 1.100 0.110 0.116 0.114 0.120 1.200 0.076 0.081 0.079 0.083 1.200 0.107 0.114 0.112 0.118 1.300 0.074 0.078 0.078 0.081 1.300 0.105 0.111 0.110 0.115 1.400 0.074 0.078 0.076 0.080 1.400 0.104 0.110 0.108 0.113 1.500 0.072 0.076 0.075 0.079 1.500 0.102 0.108 0.106 0.112 1.600 0.071 0.075 0.074 0.078 1.600 0.101 0.106 0.105 0.110 1.700 0.070 0.074 0.073 0.077 1.700 0.099 0.105 0.103 0.109 1.800 0.069 0.073 0.072 0.076 1.800 0.098 0.103 0.102 0.107 1.900 0.069 0.072 0.071 0.075 1.900 0.097 0.102 0.101 0.106 2.000 0.068 0.071 0.071 0.074 2.000 0.096 0.101 0.100 0.105 50% area 25% submergence 50% area 75% submergence Manning’s n Manning’s n Velocity White Austrian Velocity White Austrian (m/s) Cedar Spruce pine pine (m/s) Cedar Spruce pine pine 0.100 0.269 0.284 0.280 0.294 0.100 0.155 0.164 0.162 0.170 0.200 0.229 0.242 0.239 0.252 0.200 0.132 0.140 0.138 0.145 0.300 0.209 0.221 0.218 0.229 0.300 0.121 0.127 0.126 0.132 0.400 0.195 0.206 0.204 0.214 0.400 0.113 0.119 0.118 0.123 0.500 0.185 0.197 0.194 0.204 0.500 0.107 0.113 0.112 0.118 0.600 0.178 0.188 0.185 0.195 0.600 0.103 0.109 0.107 0.113 0.700 0.173 0.182 0.180 0.188 0.700 0.100 0.105 0.104 0.109 0.800 0.167 0.177 0.174 0.182 0.800 0.096 0.102 0.100 0.105 0.900 0.163 0.171 0.170 0.178 0.900 0.094 0.099 0.098 0.103 1.000 0.158 0.167 0.165 0.174 1.000 0.091 0.096 0.096 0.100 1.100 0.156 0.164 0.161 0.170 1.100 0.090 0.095 0.093 0.098 1.200 0.151 0.161 0.158 0.167 1.200 0.087 0.093 0.091 0.096 1.300 0.148 0.157 0.156 0.163 1.300 0.086 0.091 0.090 0.094 1.400 0.147 0.156 0.153 0.160 1.400 0.085 0.090 0.088 0.092 1.500 0.144 0.153 0.150 0.158 1.500 0.083 0.088 0.087 0.091 1.600 0.143 0.150 0.148 0.156 1.600 0.082 0.087 0.086 0.090 1.700 0.140 0.148 0.146 0.154 1.700 0.081 0.086 0.084 0.089 1.800 0.139 0.146 0.144 0.151 1.800 0.080 0.084 0.083 0.087 1.900 0.137 0.144 0.143 0.150 1.900 0.079 0.083 0.082 0.087 2.000 0.136 0.143 0.141 0.148 2.000 0.078 0.082 0.082 0.086
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25% area total submergence 25% area 50% submergence Manning’s n Manning’s n Velocity White Austrian Velocity White Austrian (m/s) Cedar Spruce pine pine (m/s) Cedar Spruce pine pine 0.100 0.095 0.101 0.099 0.104 0.100 0.116 0.123 0.121 0.127 0.200 0.081 0.086 0.085 0.089 0.200 0.099 0.105 0.103 0.109 0.300 0.074 0.078 0.077 0.081 0.300 0.091 0.096 0.094 0.099 0.400 0.069 0.073 0.072 0.076 0.400 0.085 0.089 0.088 0.092 0.500 0.066 0.070 0.069 0.072 0.500 0.080 0.085 0.084 0.088 0.600 0.063 0.067 0.066 0.069 0.600 0.077 0.081 0.080 0.085 0.700 0.061 0.065 0.064 0.067 0.700 0.075 0.079 0.078 0.081 0.800 0.059 0.063 0.062 0.065 0.800 0.072 0.077 0.075 0.079 0.900 0.058 0.061 0.060 0.063 0.900 0.070 0.074 0.073 0.077 1.000 0.056 0.059 0.059 0.062 1.000 0.069 0.072 0.072 0.075 1.100 0.055 0.058 0.057 0.060 1.100 0.067 0.071 0.070 0.073 1.200 0.054 0.057 0.056 0.059 1.200 0.066 0.070 0.069 0.072 1.300 0.053 0.056 0.055 0.058 1.300 0.064 0.068 0.067 0.070 1.400 0.052 0.055 0.054 0.057 1.400 0.064 0.067 0.066 0.069 1.500 0.051 0.054 0.053 0.056 1.500 0.062 0.066 0.065 0.069 1.600 0.051 0.053 0.053 0.055 1.600 0.062 0.065 0.064 0.067 1.700 0.050 0.053 0.052 0.055 1.700 0.061 0.064 0.063 0.067 1.800 0.049 0.052 0.051 0.054 1.800 0.060 0.063 0.062 0.066 1.900 0.049 0.051 0.051 0.053 1.900 0.059 0.062 0.062 0.065 2.000 0.048 0.051 0.050 0.053 2.000 0.059 0.062 0.061 0.064 25% area 25% submergence 25% area 75% submergence Manning’s n Manning’s n Velocity White Austrian Velocity White Austrian (m/s) Cedar Spruce pine pine (m/s) Cedar Spruce pine pine 0.100 0.190 0.201 0.198 0.208 0.100 0.095 0.101 0.099 0.104 0.200 0.162 0.171 0.169 0.178 0.200 0.081 0.086 0.085 0.089 0.300 0.148 0.156 0.154 0.162 0.300 0.074 0.078 0.077 0.081 0.400 0.138 0.146 0.144 0.151 0.400 0.069 0.073 0.072 0.076 0.500 0.131 0.139 0.137 0.144 0.500 0.066 0.070 0.069 0.072 0.600 0.126 0.133 0.131 0.138 0.600 0.063 0.067 0.066 0.069 0.700 0.122 0.129 0.127 0.133 0.700 0.061 0.065 0.064 0.067 0.800 0.118 0.125 0.123 0.129 0.800 0.059 0.063 0.062 0.065 0.900 0.115 0.121 0.120 0.126 0.900 0.058 0.061 0.060 0.063 1.000 0.112 0.118 0.117 0.123 1.000 0.056 0.059 0.059 0.062 1.100 0.110 0.116 0.114 0.120 1.100 0.055 0.058 0.057 0.060 1.200 0.107 0.114 0.112 0.118 1.200 0.054 0.057 0.056 0.059 1.300 0.105 0.111 0.110 0.115 1.300 0.053 0.056 0.055 0.058 1.400 0.104 0.110 0.108 0.113 1.400 0.052 0.055 0.054 0.057 1.500 0.102 0.108 0.106 0.112 1.500 0.051 0.054 0.053 0.056 1.600 0.101 0.106 0.105 0.110 1.600 0.051 0.053 0.053 0.055 1.700 0.099 0.105 0.103 0.109 1.700 0.050 0.053 0.052 0.055 1.800 0.098 0.103 0.102 0.107 1.800 0.049 0.052 0.051 0.054 1.900 0.097 0.102 0.101 0.106 1.900 0.049 0.051 0.051 0.053 2.000 0.096 0.101 0.100 0.105 2.000 0.048 0.051 0.050 0.053
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Li and Shen (1973) Li and Shen (1973) present an analysis of flow through tall vegetation by considering the drag due to cylinders in the flow. This study is not of direct applicability to the estimation of flow resistance due to vegetation but it does draw some conclusions which are of relevance. The most important of these is that staggered patterns of tall vegetation (trees) are much more effective in reducing the flow than any other configuration with the same number of tall vegetations. This conclusion is in agreement with the estimates of Manning’s roughness coefficient made by Bruk and Volf (1967).
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Limernos (1970)
Table A18 Summary of basic data d Stream and Hydraulic Manning’s 50 Discharge sediment sediment type location radius n size 143.00 1.80 0.036 10.97 Med Gravel Austin Creek 38.79 0.82 0.036 10.97 Med Gravel nr Cazadero 24.15 0.61 0.036 10.97 Med Gravel 19.03 0.57 0.038 10.97 Med Gravel 61.73 1.30 0.02 3.96 Fine gravel Cache Creek 26.73 0.80 0.022 3.96 Fine gravel at Yolo 7.84 0.31 0.023 3.96 Fine gravel Middle Fork 254.85 1.49 0.035 14.63 Med Gravel Eel River 38.23 0.47 0.043 14.63 Med Gravel 29.73 0.65 0.071 106.68 Cobbles Kaweah River 24.61 0.59 0.067 106.68 Cobbles 11.47 0.44 0.083 106.68 Cobbles 104.49 1.13 0.064 106.68 Cobbles 103.64 1.09 0.059 106.68 Cobbles Kings River 90.61 1.06 0.064 106.68 Cobbles 69.09 1.04 0.066 106.68 Cobbles 37.94 1.10 0.044 85.34 Coarse gravel 52.10 1.10 0.035 85.34 Coarse gravel Merced River 46.72 1.06 0.036 85.34 Coarse gravel at Clarks 27.84 0.97 0.052 85.34 Coarse gravel Bridge 33.13 0.90 0.05 85.34 Coarse gravel 18.86 0.82 0.068 85.34 Coarse gravel 17.61 0.80 0.064 85.34 Coarse gravel 55.22 1.34 0.06 173.74 Cobbles/boulders 55.22 1.20 0.068 173.74 Cobbles/boulders 56.35 1.14 0.067 173.74 Cobbles/boulders 52.10 1.00 0.06 173.74 Cobbles/boulders 46.72 0.94 0.058 173.74 Cobbles/boulders Merced River 37.94 0.92 0.065 173.74 Cobbles/boulders at Happy Isles 33.13 0.88 0.066 173.74 Cobbles/boulders 27.84 0.82 0.07 173.74 Cobbles/boulders 18.86 0.75 0.087 173.74 Cobbles/boulders 17.61 0.69 0.074 173.74 Cobbles/boulders 5.97 0.48 0.1 173.74 Cobbles/boulders 430.42 3.32 0.033 16.46 Med Gravel 125.16 2.25 0.036 19.20 Med Gravel 159.71 1.83 0.035 19.20 Med Gravel 33.98 1.21 0.029 19.20 Med Gravel Outlet Creek 34.26 1.19 0.028 19.20 Med Gravel near Longvale 45.59 1.02 0.028 19.20 Med Gravel 32.00 0.98 0.025 19.20 Med Gravel 15.35 0.93 0.036 19.20 Med Gravel 9.85 0.78 0.038 19.20 Med Gravel
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84.95 1.19 0.042 97.54 Cobbles Middle Fork 55.22 1.01 0.044 97.54 Cobbles Smith River 44.46 0.92 0.047 97.54 Cobbles Van Duzen River near Bridgeville 52.10 0.84 0.039 67.06 Coarse gravel Van Duzen 150.36 1.61 0.088 94.49 Cobbles River near 101.09 1.38 0.107 94.49 Cobbles Dinsmores 71.08 1.10 0.098 94.49 Cobbles
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Petryk and Bosmajian (1975) Petryk and Bosmajian (1975) theoretically analysed flow through vegetation. In carrying out this analysis they made the following assumptions: • the velocity is small enough to prevent a large degree of plant bending; • the vegetation is distributed relatively uniformly in the lateral direction; • large variations in average velocity do not occur across the channel • the maximum flow depth is less than or equal to the maximum height of vegetation; and • large variations in flow velocity do not occur over the flow depth. Petryk and Bosmajian derived the following equation (in metric units) for Manning’s roughness coefficient:
4 R Cdr ∑Ai n = n 1+ 3 ( ) (A6) b 2 AL 2gnb where: nb is the boundary roughness coefficient R is the hydraulic radius
Cdr ΣAi/AL represents the vegetation characteristics.
The expression C dr ΣAi/AL represents the density of vegetation in the channel. C dr is the drag coefficient of the vegetation which Petryk and Bosmajian suggest is of the order of 1.0. ΣAi is the projected area of the vegetation in the streamwise direction, in a channel of length L, with a cross sectional area of flow A.
The paper also includes some examples of vegetated floodplains and the roughness values associated with them. The table below summarises these field sites where the density of vegetation is represented as described above:
Table A19 Decription of Manning n values for various field sites Manning n roughness values Description Average Upper Lower Third coverage of willows, two thirds coverage of 0.08 0.01 0.06 weeds, willows, poplars of 2.5 to 15cm diameter, vegetation density~ 0.055 per m summer, 1m depth of water Third coverage of willows, two thirds coverage of weeds, 0.11 0.14 0.08 willows, poplars of 2.5 to 15cm diameter, vegetation density 0.06 per m, summer, 2m depth of water Third coverage of willows, two thirds coverage of weeds, 0.15 0.18 0.12 willows, poplars of 2.5 to 15cm diameter, vegetation density 0.075 per m, summer, 3m depth of water Large sized growth of trees, mainly willows in full foliage – 0.055 summer, vegetation density 0.015 per m, 1.3m depth of water Large sized growth of trees, mainly willows in full foliage – 0.07 0.09 0.045 summer, vegetation density 0.02 per m, 2m depth of water Large sized growth of trees, mainly willows in full 0.12 0.15 0.1
R&D ROUGHNESS REVIEW 169 foliage – summer, vegetation density 0.035 per m, 3m depth of water Oak gum and cypress trees, very little undergrowth, summer, 0.087 0.11 0.075 vegetation density 0.03 per m, depth 1.3m Oak gum and cypress trees, very little undergrowth, summer, 0.11 0.12 0.1 vegetation density 0.03 per m, depth 2m Oak gum and cypress trees, very little undergrowth, summer, 0.155 0.17 0.14 vegetation density 0.03 per m, depth 3m Oak gum and cypress trees, very little 0.12 0.13 0.11 undergrowth, winter, vegetation density 0.03 per m, depth 2.5m Oak gum and cypress trees, very little undergrowth, winter, 0.14 0.155 0.125 vegetation density 0.03 per m, depth 3m Willow trees of 5cm to 30cm diameter, large weeds, summer, 0.065 0.08 0.055 vegetation density 0.03 per m, depth 1.3m Willow trees of 5cm to 30cm diameter, large weeds, summer, 0.078 0.085 0.07 vegetation density 0.032 per m, depth 2m Willow trees of 5cm to 30cm diameter, large weeds, summer, 0.103 0.115 0.095 vegetation density 0.035 per m, depth 3m
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Powell (1972) Table A20 Decription of data Country Exp or Catchment Length Ht above sea Times in field data area of reach level year of data collection UK Field River Bain, 1549m Fulsby weir Jan 1967 to Fulsby Lock 10.08mODN Jan 1968 Haltham Jan 1968 to 12.96m ODN Sept 1971
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Ree, Wimberly and Crow (1977) Manning’s n values for the overland flow surfaces of a grassed watershed were derived by hydrograph analysis and by using average watershed slope and overland flow length values determined by geomorphic methods. These values are compared with Manning n values from laboratory tests on channels having similar grass covers. Close agreement was found for poor grass but not for fair and good grass cover. The table below gives values for three watersheds with three cover conditions. Table A21 Manning’s n values for grassed watersheds Cover condition Watershed W1 W3 W4 Good 0.21 0.31 0.62 Fair 0.35 0.31 0.51 Poor 0.26 0.28 0.25
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Richards (1976) Richards was investigating the channel geometry in the pool riffle sequence with field observations on the River Fowey, Cornwall, UK. As part of the investigation the mean flow characteristics were recorded, as given in the table below. Table A22 Data from a field investigation of pool-riffle sequences on the River Fowey, Cornwall, UK Variable Curved pool Straight pool Curved riffle Straight riffle Depth (m) 0.42 0.41 0.15 0.19 Velocity (m/s) 0.19 0.17 0.44 0.39 Manning n 0.05 0.05 0.07 0.12 Slope * 10 3 0.3 0.2 11 18 Width (m) 4.85 5.4 5.71 5.29 Average discharge 0.38 0.38 0.38 0.38 (m 3/s)
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Sargent (1979) Survey data from five gauging sites from the Forth River Purification Board were selected. The data was combined using Manning’s equation to obtain estimates of Manning n roughness coefficients. The gauging station summary data and calculated roughness values are given in the table below. Table A23 Survey data from the Forth River Purification Board Station Gauge height (m) Discharge (m 3/s) Manning’s n River Almond at Craigiehall 1.125 17.914 0.0255 1.4 29.8 0.0209 1.713 44.007 0.01975 2.1 67.213 0.0193 Water of Leith at Murrayfield 0.878 8.15 0.0257 0.975 10.839 0.02375 1.3 19.612 0.0203 1.59 30.875 0.0193 1.981 44.714 0.02 2.133 52.214 0.0201 River Esk at Musselburgh 0.732 14.235 0.0438 0.896 22.442 0.0314 1.521 62.543 0.0275 1.829 92.258 0.0265 River Tyne at East Linton 0.75 5.943 0.049 1.045 11.745 0.043 1.219 16.697 0.0402 1.503 26.574 0.0383 1.753 35.969 0.0382 River Tyne at Spilmersford 1.14 17.035 0.0291 1.426 26.376 0.0258 1.536 28.866 0.0257 1.75 32.507 0.0254
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Severn Trent Field sites 1. River Severn at Bewdley
Figure A4 River Severn at Bewdley Bankfull hydraulic and geometric characteristics 5/1/88 see Figure A5. Manning's n roughness coefficient = 0.022 Discharge = 358m 3/s Water surface slope = 0.000203 (1:4926) Average cross sectional area = 249m 2 Average flow width = 78m (information available for xs 1 and 2) Average hydraulic radius = 3.24m Description of channel Bed material gravel at upstream end, otherwise unknown. Banks grass with scattered willow, alder and hawthorn trees; undergrowth of nettle and brambles. Left and right flood plains are short grass pasture.
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Figure A5 Plan and cross-sections, River Severn at Bewdley
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2. River Vyrnwy at Llanymynech
Figure A6 River Vyrnwy at Llanymynech Bankfull hydraulic and geometric characteristics 14/2/88 see Figure A7. Manning's n roughness coefficient = 0.026 Discharge = 167.7m 3/s Water surface slope = 0.000372 (1:2688) Average cross sectional area = 131.6m 2 Average flow width = 46.4m Average hydraulic radius = 2.25m Description of channel Bed material unknown. Right bank grass covered with scattered mature alders. Left bank lined with alder and willow. Left flood plain sown with crops, right flood plain is short grass pasture.
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Figure A7 Plan and cross-sections, River Vyrnwy at Llanymynech
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3. River Severn at Montford
Figure A8 River Severn at Montford Bankfull hydraulic and geometric characteristics 12/11/87 see Figure A9 Manning's n roughness coefficient = 0.028 Discharge = 151m 3/s Water surface slope = 0.000186 (1:5376) Average cross sectional area = 139m 2 Average flow width = 39.9m Average hydraulic radius = 3.31m Description of channel Bed material unknown. Left and right banks grass with occasional small willow trees. Flood plains of short grass pasture with hawthorn hedgerows and fences.
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Figure A9 Plan and cross-section, River Severn at Montford
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4. River Trent at Drakelow
Figure A10 River Trent at Drakelow Bankfull hydraulic and geometric characteristics 3/2/86 see Figure A11 Manning's n roughness coefficient = 0.032 Discharge = 169m 3/s Water surface slope = 0.000437 (1:2288) Average cross sectional area = 142.5m 2 Average flow width = 54m Average hydraulic radius = 2.62m Description of channel Bed material unknown. Left bank grass with horse chestnut trees at downstream limit of reach. Right bank with horse chestnut and beech trees. Left flood plain is a golf course with occasional oak, yew, hawthorn, horse chestnut and poplar tree coppice. Right bank formed by steep wooded bank lowering to flood plain at downstream limit with beech and chestnut trees with bank grass undergrowth.
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Figure A12 Plan and cross-sections, River Trent at Drakelow
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5. River Derwent at Chatsworth
Figure A13 River Derwent at Chatsworth Bankfull hydraulic and geometric characteristics 24/3/89 see Figure A14 Manning's n roughness coefficient = 0.039 Discharge = 94.5m 3/s Water surface slope = 0.000695 (1:1439) Average cross sectional area = 77.59m 2 Average flow width = 29m Average hydraulic radius = 2.42m Description of channel Bed material gravel with shallow rock step. Banks grass with mature alder, sycamore and ash trees. Left and right flood plains are short grass pastures.
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Figure A14 Plan and cross-sections, River Derwent at Chatsworth
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6. River Manifold at Ilam
Figure A15 River Manifold at Ilam Bankfull hydraulic and geometric characteristics 2/12/92 see Figure A16 Manning's n roughness coefficient = 0.042 Discharge = 52.8m 3/s Water surface slope = 0.001977 (1:506) Average cross sectional area = 35.6m 2 Average flow width = 21m Average hydraulic radius = 1.64m Description of channel Bed material is gravel and boulders. Bank vegetation of alder, ash, hazel, beech, sycamore and hawthorn traces with grass, scattered undergrowth of bramble. Flood plains of short grass pasture with hedgerows and wire fencing.
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Figure A16 Plan and cross-sections, River Manifold at Ilam
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7. River Avon at Evesham
Figure A17 River Avon at Evesham Bankfull hydraulic and geometric characteristics 30/1/86 see Figure A18 Manning's n roughness coefficient = 0.044 Discharge = 110m 3/s Water surface slope = 0.000234 (1:4274) Average cross sectional area = 147.9m 2 Average flow width = 45m Average hydraulic radius = 3.11m
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Figure A18 Plan and cross-sections, River Avon at Evesham
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8. River Tanat at Llanyblodwel
Figure A19 River Tanat at Llanyblodwel Bankfull hydraulic and geometric characteristics 15/12/86 see Figure A20 Manning's n roughness coefficient = 0.052 Discharge = 54.8m 3/s Water surface slope = 0.00298 (1:336) Average cross sectional area = 40.4m 2 Average flow width = 26.7m Average hydraulic radius = 1.45m Description of channel Bed gravel and boulders. Banks lined with mature alders, ash and willow, undergrowth of bramble, nettle, wild rose and rank grass. Left flood plain is sown with crops, right flood plain is short grass pasture. Field boundaries delimited by hedgerows.
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Figure A20 Plan and cross-sections, River Tanat at Llanyblodwel
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Technology Research Centre, 1994 Grass The results of survey results of grass on floodplain is given in the following table which has used results from Fig 2.26 of the report “Proposed guidelines on the clearing and planting of trees in rivers” Table A24 Survey results for Manning’s n roughness values for grass on a floodplain Manning’s n roughness Description Average Upper Lower Stiff grass height hv= 1.8m h/hv=1.4 0.1 0.12 0.08 Grassland height hv=1.0m h/hv=2 0.08 0.09 0.07 Stiff grass height hv=1.8m, h/hv= 2.5 0.047 0.055 0.04 Grassland height hv = 50cm, h/hv= 5 0.04 0.045 0.035 Grassland height hv = 10 20cm, h/hv= 16 0.026 0.028 0.022 Flat golf course with turf several cm high, 0.021 0.024 0.018 h/hv= 90 Trees Table A25 Survey results for Manning’s n roughness values for different tree diameters and densities Manning’s n values at different tree diameters Water depth No of (m) trees/m2 Diameter of Diameter of Diameter of 0.5m 1m 2m 0.5 1 0.022 0.043 0.086 0.5 2 0.043 0.086 0.173 1 1 0.031 0.061 0.122 1 2 0.061 0.122 0.245 1.5 1 0.037 0.075 0.149 1.5 2 0.075 0.15 0.3
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Thompson and Campbell (1979) Relates resistance solely to relative roughness. If using the Thompson and Campbell equation then the Darcy Weisbach resistance coefficient is determined from 2 12 R = f 1− k1.0 / R 2 log ()s 10 (A7) ks where ks = 4.5d, and d is the median (d 50 ) sediment size (m) determined from the frequency distribution of bed material size. The Darcy Weisbach resistance coefficient can be translated into a Manning’s n value using 2/1 6/1 f n = R (A8) g8
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Turner and Chanmeersi (1984) The shallow movement of water flowing through dense crops of wheat was studied for different crop densities and sowing patterns and ages. Using Manning’s equation and field data, values for Manning n were calculated at different depths and crop densities. The values given below are those recorded in the paper. Table A26 Manning’s n values for wheat crops Depth of water Bare Soil Stems only Wheat (cm) 10 0.035 12 0.032 15 0.04 0.06 18 0.03 0.048 20 0.028 0.07 22 0.026 24 0.025 0.05 28 0.023 0.053 0.073 33 0.053 0.079 40 0.096 42 0.1 45 0.105 48 0.11 50 0.113
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University of Ulster (1995) Data collected at ten sites on the River Blackwater was analysed to give a range of roughness values for pools, riffles and nursery areas. The table below gives the range of roughness values for seven of these sites. The range of values given is wide in range and is dependent on the discharge and depth at which the roughness coefficient is measured. At low discharges there is a great discrepancy between the roughness values along the reach. The sites given are described in more detail in Appendix 2 with photographs, dimensions and plan views of each site.
Table A27 Range of Manning’s n values for pools, riffles and nursery areas, R. Blackwater Range of Manning’s n values Pool Spawning Ground Nursery Site (Riffle) Max Min Max Min Max Min Bawn’s Burn 0.199 0.028 0.141 0.019 Abel’s Bridge 0.0481 0.0215 0.067 0.028 Lisdoart Mill 0.088 0.025 0.067 0.023 Lisdoart 0.067 0.023 Bridge Forthill Bridge 0.053 0.037 0.069 0.025 Omagh Road 0.053 0.031 0.13 0.032 0.080 0.034 River Fury 0.304 0.059 0.105 0.03
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US Soil Conservation Service (1954) The figure below shows the retardance class against flow parameter (VR) for grass cover as given by USDA (1954).
Figure A21 Graph of retardance class versus VR, USDA (1954) Experimental research on the hydraulic impact of grass cover was undertaken over a nine year period at the Stillwater Outdoor Laboratory of the US Soil Conservation Service. A general handbook was prepared in 1947, further supplemented in a revised edition in 1954. The result of the work has been to define a series of relationships between Manning’s n and the product VR, where V is the mean flow velocity and R is the hydraulic radius. The relationship is expressed as a family of curves, each curve defining the other principal variable, the physical characteristic of the vegetation. The main physical characteristic is judged to be the height but other factors such as density and uniformity are influential and a value judgement has to be made. Accepting that the vegetation is an organic cover of almost endless variability, the n VR relationship gives sound results in the majority of cases. The above figure shows the chart given in the USDA handbook of 1954, converted to metric, and the table below gives guidance to retardance catagories.
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Table A28 Grass cover retardance classes (USDA, 1954) Stand Average Length Retardance Longer than 30 inches A 11 in to 24 in B Good 6 in to 10 in C 2 in to 6 in D less than 2 in E Longer than 30 inches B 11 in to 24 in C Fair 6 in to 10 in D 2 in to 6 in D less than 2 in E
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Weltz, Arslan and Lane (1992) Data were collected from 14 different native rangeland areas in the western United States. Hydraulic roughness coefficients were calculated for surfaces ranging from smooth bare soil to gravely bare soil and sparsely to densely vegetated rangeland areas. A reference table of “effective roughness” coefficients is presented with a description of site characteristics. Table A29 Range of Manning’s n values for rangeland areas in western United States Soil texture/vegetation type Standing Manning’s n Range biomass roughness (kg/ha) value Bare soil, sand - 0.01 0.01 0.016 Bare soil, loam 0.037 Bare soil, clay loam 0.041 Bare soil, clay loam eroded 0.02 0.012 0.033 Bare soil, silt 0.043 Bare soil, clay 0.048 Gravel surface 0.02 0.012 0.03 Shrublands, Chihuahuan desert 0.03 0.2 Shrublands, Chihuahuan desert 770 0.25 0.11 0.29 Shrublands, Chihuahuan desert 0.13 0.01 0.32 Shrublands, Mohave desert 490 0.15 0.14 0.16 Shrublands, Salt Desert 1,580 0.62 0.52 1.0 Shrublands, Sagebrush 3,950 0.48 Shrublands, Sagebrush 0.51 0.01 2.6 Shrublands, Oak savanna 1,450 0.4 0.3 0.52 Shrublands, Pinyon juniper 420 0.44 0.31 0.56 Native grasslands, desert 750 0.64 Native grasslands, shortgrass 620 0.42 0.15 0.73 prairie Native grasslands, shortgrass 0.15 0.1 0.2 prairie Native grasslands, mixedgrass 1,620 0.52 0.31 0.78 prairie Native grasslands, tallgrass 3,080 0.79 0.16 0.97 prairie Native grasslands, tallgrass 0.23 0.19 0.29 prairie (burned) Pasture, Bermuda grass 0.41 0.3 0.48 Pasture, bluegrass sod 0.45 0.39 0.65 Grassed waterways, tallgrasses 0.6 0.45 0.75
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Appendix B
Explanation of variation of roughness with depth Based on empirical data from over 25 sites we collated the depth and the roughness and plotted the data as can be seen on the graph below. There is some scatter on the data but it does show a trend with the roughness decreasing as the depth increases. It is noticeable that above 1m depth the roughness decrease is quite small and the line is tending towards an asymtoptic value of 0.02 roughness which is what would be expected in a natural river system. The equation for this part of the curve can be expressed as 2 n depth = d =1 (B1) n where n is the roughness value at depth of 1m Below a value of 1m depth the roughness varies in a different way, with large increases in roughness for small decreases in depth. The relationship below 1m is 2 n 3 depth = d =1 (B2) n
6
5
4
3 depth (m) depth 2
1
0 0 0.1 0.2 0.3 0.4 0.5 roughness Figure B1 Variation in roughness with depth
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Appendix C
Full Abstracts River Flow 2002 (http://www.gc.ucl.ac.be/riverflow/home.html ) Paper 13 - Abstract Velocity profiles on vegetated flood plains Pawel M. Rowinski Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland Janusz Kubrak Faculty of Land Reclamation and Environmental Engineering Warsaw Agriculture University SGGW, Poland Numerical computations of the vertical profiles of mean streamwise velocities in the channels vegetated with trees are presented. The given model applies particularly to vegetated flood plains of a two stage channel cross section. Sensitivity of the results to the changes of the model parameters is discussed and it concerns the density of the trees, the tree diameter, bed slope of the channel and the artificially introduced parameter dividing the channel depth into two zones: one for which the mixing length is a linear function of the distance from the bed and the other one for which the mixing length is constant. The computational results are compared to the data obtained within experimentation in a compound laboratory flume. Paper 17 - Abstract The influence of floodplain width on the stage-discharge relationship for compound channels S. Atabay & D. W. Knight School of Civil Engineering, The University of Birmingham, UK. Some stage discharge relationships are presented for flow in compound channels, based on experimental results from the UK Flood Channel Facility (FCF) and elsewhere. The influence of floodplain width and main channel aspect ratio on these relationships has been examined for compound channels comprising one main river channel and one or two symmetrically disposed floodplains. Simple empirical relationships between stage & total discharge and stage & zonal discharge have been derived for all the FCF channel cases with uniform roughness and varying floodplain width ratio (B/b). The influence of the main channel aspect ratio has also been examined. The results indicate the broad effect that channel geometry has on the stage discharge relationship (H v Q) for compound channels. Paper 46 - Abstract Modeling of lateral flow distribution in compound channels Y.Guan &M.S.Altinakar Laboratoire de Recherches Hydrauliques (LRH) Ecole Polytechnique Féderale de Lausanne (EPFL),Switzerland B.G.Krishnappan
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National Water Research Institute,Burlington,Ontario,Canada A numerical model based on the longitudinal momentum conservation equation has been developed to predict the lateral variation of depth averaged longitudinal velocity for steady flows in compound channels. The model takes into account the influence of the secondary flow on the lateral momentum transfer in the interface region between the main channel and the floodplain by expressing the lateral depth averaged velocity as a percentage of the depth averaged longitudinal velocity. The model has been verified using velocity data from experiments in laboratory flumes with asymmetrical compound cross sections. Comparisons between the predicted velocity profiles and the measurements show that the proposed model provides an accurate prediction of the lateral flow distribution for compound channels. Paper 54 - Abstract Velocity Distribution and Scouring in Steep-Curved Channels R. Feurich and W. Kühner Water Resources Institute (IWI), University of Innsbruck, Austria At the Water Resources Institute of the University of Innsbruck experiments have been performed in an S shaped trapezoidal channel with two bends and a slope of S = 0,01 with both fixed and erodible beds. Gravel with a mean diameter between 4,2mm and 6,4mm was used as bed material and for sediment feeding. Velocities were measured by means of a two dimensional electromagnetic current meter. The analysis of the experiments yields a new function for the radial distribution of the depth averaged longitudinal velocities that differs from the forced vortex approach. It is also shown that in the case of an erodible bed the redistribution of flow as a consequence of the evolution of scour on the outer and deposition on the inner bank leads to completely different radial velocity distributions compared with the initial bed. Paper 56 - Abstract A practical method for predicting the total discharge in mobile and rigid boundary compound channels M.A. Haidera & E.M. Valentine University of Newcastle upon Tyne, United Kingdom Mobile boundary laboratory channels were used to develop a new method for predicting the total flow in compound channels. This method considers a compound channel between two extreme states. The first is the channel at the threshold of inundation (at relative depth of zero) and the second when the channel is inundated to a maximum level (relative depth approaches unity). At these two extremes the total flow can be calculated by the single channel method and between them this method assumes that the total flow is partially calculated by the single channel method and partially by the traditional divided channel method. The portions of flow calculated by the single and the divided channel methods rely on two adjustment factors. These factors are functions of two dimensionless parameters, the relative depth and the channel coherence and hence this method is termed the Dimensionless Total Flow Adjustment Method. The method was tested using mobile boundary and rigid boundary data and compared with Ackers’ (1993) Coherence method and the Lambert and Myers (1998) weighted divided
R&D ROUGHNESS REVIEW 201 channel method. The results show that this simpler method provides improved estimates of total discharge and it may be applied to symmetric or asymmetric channels with homogeneous or non homogeneous roughness. Paper 77 - Abstract Determination of flow resistance of vegetated channel banks and floodplains J. Järvelä Laboratory of Water Resources, Helsinki University of Technology, Finland Flow resistance due to vegetation may greatly affect the conveyance of a channel, and thus evaluating the resistance is a critical task in river engineering and restoration. Therefore, flow resistance of natural willows and sedges was studied in a laboratory flume. The aim was to investigate, how type, density and combination of vegetation, flow depth and velocity influence vegetal drag or friction losses. Friction factors, f, and vegetal drag coefficients, C'd, were determined for a selection of 170 test runs. The results showed large variations with depth of flow, velocity, Reynolds number and vegetal characteristics. E.g. the vegetal drag coefficient for the leafy willows was three to seven times that of the leafless willows. The experimental drag coefficients for the leafless willows were compared to the values predicted by four methods, which were developed based on theory and experiments on rigid cylinders. Paper 81 - Abstract Overbank flood routing analysis applying jointly variable parameter diffusion and depth-averaged flow finite element models J. B. Abril Honorary Research Fellow University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK Email: [email protected] Tel: +593 7 839593 This paper presents the joint application of two finite element models called RFMFEM and RFRFEM to the hydrodynamic analysis of floods in rivers flowing in an overbank condition. The RFMFEM model predicts the hydraulic characteristics of the river through the solution to the momentum equation for depth averaged flow. Based upon this information, the RFRFEM model then generates the wave speed and attenuation coefficients versus discharge, and accomplish the flood routing analysis through the solution to the variable parameter convection diffusion equation derived from the upwind Petrov Galerkin formulation. It includes and heuristic algorithm to reduce the numerical error and oscillations generally introduced when dealing with convection dominated problems. This finite element scheme is compared against another scheme based on the COH and MVPMC3 models, being respectively ‘coherence’ and variable parameter finite difference schemes, applied to overbank flood routing in a hypothetical river with a symmetric compound channels. Paper 99 - Abstract Reducing Uncertainty in Conveyance Estimation Dr P. G. Samuels, HR Wallingford Ltd., Howbery Park, Wallingford, Oxon OX10 8BA, UK Dr M. E. Bramley
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Environment Agency, Rio House, Waterside Drive, Aztec West, Almondsbury, Bristol, BS32 4UD, UK E. P. Evans Consultant, Care of HR Wallingford Ltd. Estimation of conveyance is a core component of flood management, water level prediction and flood defence design. All river modelling software includes one or more methods for conveyance estimation, usually based upon methods dating from research completed more than 50 years ago with little or no account taken of recent advances in knowledge and understanding. In 2001 the British Environment Agency commissioned, as a research project, a scoping study to define actions for reducing uncertainty in conveyance estimation. The paper describes some of the conclusions of that scoping study including the needs of different users, the diversity of current knowledge and the outline of the targeted programme of research that is now underway to produce an improved conveyance estimation system. Particular issues of concern are the effects of riverine vegetation, the influence of natural shaped (and re naturalised) channels and the interaction between river channels and flood plain flows. Paper 116 - Abstract Predictions of velocity and boundary shear stress in compound meandering channel P. Rameshwaran Centre for Ecology & Hydrology, Crowmarsh Gifford, Wallingford, Oxfordshire, OX10 8BB, UK K. Shiono Department of Civil and Building Engineering, Loughborough University, Loughborough, LE11 3TU, UK Predictions of depth averaged velocity and boundary shear stress in a compound meandering channel are carried out using a commercially available finite element computer code TELEMAC 2D. The TELEMAC 2D code solves the depth averaged continuity and Navier Stokes equations with the depth averaged form of the turbulence model for free surface flow. The model results are compared with the experimental data obtained from the UK Flood Channel Facility. The simulated depth averaged velocity, boundary shear stress and depth averaged turbulent kinetic energy are used to investigate the accuracy of the TELEMAC 2D prediction. The results show that the depth averaged velocity and the boundary shear stress are predicted reasonably well along the meandering channel. Paper 131 - Abstract Quasi-Three-Dimensional Computation and Laboratory Tests on Flow in Curved Compound Channels S. Ikeda Tokyo Institute of Technology, Tokyo, Japan K. Kawamura Hewlett Pakard Japan, Tokyo, Japan Y. Toda Tokyo Institute of Technology, Tokyo, Japan
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I. Kasuya Ministry of Agriculture, Forestry and Fisheries of Japan, Tokyo, Japan For curved compound channels, cross sectional secondary flow appears in the main channel, and horizontal vortices induced by shear instability are generated at the junctions of the main channel and the flood plains. A quasi three dimensional computation was performed in the present study to calculate the secondary flow and the horizontal vortices, simultaneously. The results of the computation were compared with the laboratory tests, and it was found that the present model is appropriate to simulate the entire flow field except for the inner junction of the main channel and the flood plain, at which three dimensional turbulence associated with boils is predominant. The numerical calculations were performed for various water depth, main channel width and curvature of the channel. The results show that the lateral transport of fluid momentum associated with horizontal vortices becomes relatively larger, compared with that by the secondary flow, as the water depth becomes shallower. Paper 139 - Abstract Land-form features in compound meandering channels and classification diagram of flood flows based on sinuosity and relative depth S. Okada Graduate student, Graduate School of Engineering, Hiroshima University, Higashi Hiroshima City, Japan S. Fukuoka Professor, Graduate School of Engineering, Hiroshima University, Higashi Hiroshima City, Japan Using several Japanese rivers, flow characteristics in compound meandering channels were investigated by conducting a series of experiments where sinuosity and relative depth were changed. Laboratory results were then compared with results of flood flow analysis using aerial photographs. Representative parameters governing flow characteristics were studied in order to make sense of the results of experimental channel and river flows. Landform parameters were considered from field data from 10 Japanese compound meandering rivers. Finally, classification diagram of the occurrence of the flood flows in compound meandering channels was presented on the basis of these representative parameters (such as sinuosity, relative depth, location of the maximum velocity filament and the maximum scouring depth at the meander apex section.) Paper 166 - Abstract Berm vegetation and its effect on flow resistance in a two-stage river channel: an analysis of field data R. H. J. Sellin Department of Civil Engineering, University of Bristol, UK D. P. van Beesten Department of the Environment, DEFRA, UK A two stage river channel with a managed floodplain has been studied since 1994. During this time water levels at 5 sections as well as the discharge have been measured
R&D ROUGHNESS REVIEW 204 and recorded at 15 minute intervals. Analysis of this data reveals that the resistance coefficient for this reach varies both annually and with the seasons. These variations are shown to be due to the annual cycle of vegetation growth both in the channel and on the floodplain. Some 100 storm events have been recorded in all. The results of this analysis will enable engineers to design river restoration projects with greater confidence as Manning n values are evaluated for overbank, bankfull and low flows in the channel, thus enabling a quasi quantitative relationship to be established for different flow depths as well seasonal variation. Paper 198 - Abstract Periodical turbulent structures in compound channels D. Bousmar & Y. Zech Civil and Environmental Engineering, Université catholique de Louvain, 1348 Louvain la Neuve, Belgium In a compound channel flow, periodical turbulent structures develop in the shear layer between main channel and floodplain. Those structures, which are typically horizontal vortices, generate a significant momentum transfer and, accordingly, affect considerably the channel conveyance. In this paper, such structures are investigated experimentally, analytically and numerically to quantify their periodical characteristics. Experiments were performed in an asymmetric compound channel, with the flow structures measured by Particle Tracking Velocimetry (PTV), using surface tracers. Some results from an hydrodynamic stability analysis are then reported. A numerical simulation was performed using an Unsteady RANS model to reproduce the development of the vortices in the shear layer. The estimated vortex wave lengths are similar for the three approaches. Paper 199 - Abstract Estimation of longitudinal dispersion coefficient for streams I.W. Seo Assoc. Prof., Dept. of Civil Eng., Seoul National Univ., Seoul, Korea K.O. Baek Grad. Student, Dept. of Civil Eng., Seoul National Univ., Seoul, Korea In this study, a theoretical method for predicting the longitudinal dispersion coefficient is developed based on the transverse velocity distribution in natural streams. Equations of the transverse velocity profile for irregular cross sections of the natural streams are analyzed. Among velocity profile equations tested in this study, the beta distribution equation, which is a probability density function, is considered to be the most appropriate model for explaining the complex behavior of the transverse velocity structure of irregular natural streams. The beta function can fit various types of the velocity profile, i.e., parabolic, flattened, sharp peaked and skewed distributions, whereas other empirical equations fail to fit various types of velocity distributions. The comparisons of the proposed equation, which is based on the beta function for the transverse velocity profile, with the existing equations and the observed longitudinal dispersion coefficient reveal that the proposed equation shows better agreement with the measured data than other existing equations.
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Paper 207 - Abstract Estimate of hydraulic resistance of river flow by physical modelling E.N.Dolgopolova Water Problems Institute, Russian Academy of Sciences, Moscow, Russia E.Tesaker SINTEF Civil & Environment Engineering, Trondheim, Norway Different methods of calculation of hydraulic resistance for nature flows are discussed. Two types of rivers are under consideration: (i) plane rivers with sand bottoms for which bottom roughness is much less than the depth, and (ii) shallow rivers with gravel bottom with the bottom roughness comparable with the depth. We discuss also dependence of habitat conditions on the bottom substratum and regime of hydro peaking. Paper 208 - Abstract Relevance of 1D flow modelling for compound channels with a converging floodplain Rivière N.1, Proust S.1,2, Bousmar D.3, Paquier A.2, Morel R.1, Zech Y.3 1Laboratoire de Mécanique des Fluides et d'Acoustique, UMR CNRS 5509, INSA de Lyon, France 2CEMAGREF, Lyon, France 3Unité de Génie Civil et Environnemental, Université catholique de Louvain, Louvain La Neuve, Belgium Experiments in an asymmetric compound channel with a strongly converging floodplain are presented. The results are compared to predictions given by two different 1D programmes. Each programme uses a particular method to account for the momentum transfer that occurs in compound channels, due to the velocity gradient between the main channel and the floodplain. The first one is based on the DEBORD formula, which is an empirical correction of the Divided Channel Method. The other one is based on the Exchange Discharge Model, which computes momentum and discharge exchanges at the interface between the two subsections. In the studied situation, where significant three dimensional phenomena are detected, both numerical models exhibit some weaknesses. Particularly, it is difficult to get simultaneously correct results for the water depth, the discharge distribution in the compound section, and the subsection mean velocities. The analysis of the momentum balance of the flow provides information on the additional phenomena that exist in the experimental situation. These phenomena should be taken into account in the 1D models when such strong conveyance decrease is considered. Paper 215 - Abstract On the influence of shape on resistance to flow in open channels M.Mohammadi BSc., MSc., PhD, CEng., MIRCOLD, MIAH Dept. of Civil Eng., Faculty of Eng., The University of Urmia, P O Box 165, Urmia 57169 33111, Iran. e mail: [email protected]
R&D ROUGHNESS REVIEW 206 url: http://www.urmiacity.com/Dr.mohammadi Water flow in open channels is always subject to the resistance to flow and energy dissipation. For design purposes, one of the needed variables is the hydraulic resistance coefficient. The influence of cross sectional shape together with secondary flow cells and lateral distribution of true boundary shear stress have not yet been fully explored. This paper highlights the effect of cross sectional shape on resistance to flow. A particular emphasis has been focused on a certain V shaped bottom channel with vertical walls, and its resistance coefficient evaluation. The experimental results show that albeit the channel has a smooth boundary, but the resistance coefficients cannot be applied for this channel. The difference may be arisen by the effect of shape. It can also be seen that the Darcy Weisbach friction factor, f, is more sensitive than the Manning n. A Karman Prandtl smooth pipe flow type friction formula was developed for this channel shape. Keywords: Resistance to flow, open channel, cross sectional shape, boundary shear stress, friction factor.
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Appendix D Glossary of Terms
Table E1 Glossary of terms used Term Description Accuracy The precision to which measurement or calculation is carried out; potentially, accuracy can be improved by better technology Repeat measurements can be precise and repeatable but not necessarily accurate. Conveyance Channel conveyance is a measure of the discharge carrying Q capacity of a channel K m 3/s, defined as K = S 2/1 Conveyance width Depth averaged Parameter representing the momentum exchange νt (m 2/s), defined lateral as ν = λU D which relates viscosity to the bed shear stresses. U is turbulent viscosity t * * the shear velocity, D is the depth. Discharge The volume of water that passes through a channel section per unit of time Error Errors are mistaken calculations or measurements with quantifiable differences Flow A general term for the movement of volumes of water at a speed Grid element Discretisation element for solving the conveyance equation Manning’s ne A coefficient that incorporates losses due to local friction, Cuv , shearing flows, form losses and lateral shear stresses (as listed in Ven te Chow historic/engineering ‘ n’). Derived for use in medium to large non vegetated rivers with fully developed flow profiles. Manning’s pure nl A coefficient that approximates the local friction losses due to bed features i.e. substrate/vegetation. MaximumDepth The vertical distance of the lowest point of a channel section from the free water surface. Mean Depth The average vertical depth of a channel section from the free wter surface. Measurement channel length between two consecutive cross sections Reach Morpho types See the note below and Table 8 in the main text. Non dimensional Calibration coefficient to account for lateral shear (NB in the eddy Wark equation it is termed the lateral eddy viscosity so it is viscosity actually νt) Panels Flow zones within the section e.g. inbank, out of bank etc Risk Roughness The effect of impeding the normal water flow of a channel by the presence of a natural or artificial body or bodies, biotic eg vegetation, abiotic/mineral eg bank.bed substrate Resistance As roughness but defined as flow , form , frictional or turbulent...... Stage The vertical distance of the free surface from an arbitrary or
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defined datum Sinuosity (i) ratio of the length along the channel between two sections to the linear distance between these two sections can be either of regular or irregular amplitude (ii) ratio of the length along the channel between two sections to the linear distance along the valley between these two sections Study reach The length of a study reach OR of a section underr investigation Unit conveyance Conveyance per metre width of channel k (m 2/s), defined as q k = S 2/1 Unit discharge flow rate per metre width of channel section q (m 2/s), defined as D q = ∫udz 0 Uncertainty (1) Uncertainty is defined through two terms (i) natural variability (ii) knowledge uncertainty (2) Uncertainty arises principally from lack of knowledge or of ability to measure or to calculate which gives rise to potential differences between assessment of some factor and its “true” value Note Table 8 in the main text presents a simplified form of morpho types of channel vegetation. The RHS records channel vegetation types to assess the habitat structure they provide at the time of the survey, not their morphological character as described in textbooks. The purpose of the recording is to provide information on the range of functional habitats the flora may be providing for invertebrates and other animals. This is especially important in rivers with limited structural diversity. To be recorded, the channel type must occupy at least 1% of the channel area within the 10m RHS ‘Spot’ transect.
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