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Portions of this document may be illegible in electronic image products. Images are produced from the best available original document. Norwegian University of Department of Hydraulic and Science and Technology Environmental Engineering NTNU

SEDIMENT PROBLEMS IN RESERVOIRS Control of sediment deposits

By Tom Jacobsen

A dissertation Submitted to the Faculty of Civil Engineering, the Norwegian University of Science and Technology, in partial fulfilment of the requirements for the degree of Doctor Engineer

Trondheim, Norway, November 1997 IVB Report B2-1997-3 Summary

SUMMARY

Water is stored in reservoirs for a number of purposes such as hydropower generation, irrigation, water supply, flood control, recreation and navigation. When a reservoir is formed on a river, the river will tend to lose its sediment transporting capacity, and sediment will deposit in the reservoir. The sediment load in many rivers, in particular in regions with arid, semi-arid or monsoon climate, is of such magnitude that it severely limits any reservoir development. Estimates of annual sediment deposition in the world ’s reservoirs vary from 60 - 120 km3, or 1 - 2 % of the total water storage capacity. The objectives of this study were therefore to study the problem of reservoir sedimentation and to investigate methods of removing of sediment from reservoirs.

Various aspects of reservoir sedimentation are discussed. Anthropogenical impacts seem to have a major influence on the erosion processes and it is estimated that 50 % of all erosion is accelerated. It is concluded that temporal distribution is uneven, mainly because of the important role of the very large flood events. A world map showing the Reservoir Capacity: Annual Sediment Inflow ratio (CSR) for reservoirs with volume equal to 10 % of annual inflow has been prepared. Comparison with reported cases shows acceptable agreement. The map shows that regions where sedimentation problems generally are severe include western parts of North and South America, eastern, southern and northern Africa, parts of Australia and not least, most of Asia. In particular, the development of medium-sized reservoirs is difficult, and sometimes not feasible at all. Medium-sized reservoirs in this context are defined as reservoirs with a capacity of between 3 and 30 % of annual water inflow. The reason that medium­ sized reservoirs, in which water can be stored with limited social and ecological impacts, cannot be built is that they are too large for conventional flushing techniques, and too small to store the sediment that accumulates in the course of the economic lifetime of the reservoir.

A key benefit of a numerical model is its ability to simulate fine-sediment behaviour. As physical modelling of fine sediment is difficult, such models may be the only option other than direct measurement in assessing fine sediment behaviour. A 2D/3D numerical model, SSIIM, was applied to a case study of two flood drawdown trials in Lake Roxburgh, New Zealand. The sediment computation was carried out per size fraction (non-uniform modelling), which allowed changes in bed grain size distribution to be modelled. Actual bed levels,

l Summary

grain size distributions, water levels and inflows were used as input to the model. Good results were obtained in modelling erosion and deposition in the reservoir as well as sediment outflows during the two events. It has been shown that SSIIM can be used for trap efficiency calculation, as an alternative to well-established empirical methods.

Two techniques that permits controlled suction of sediment and water into a pipe have been developed, the Slotted Pipe Sediment Sluicer (SPSS) and the Saxophone Sediment Sluicer (SSS). The techniques exploit the inflow pattern through a slot in a pipe. An equation describing this inflow pattern was derived and verified experimentally. The SPSS is fixed near the reservoir bed and sediment that deposits on top of it is removed in the sluicing process. The SSS, on the other hand, sluices sediment from the surface of the sediment deposits. Both techniques are characterised by that they can sluice sediment at a concentration close to the sediment transport capacity of the outlet pipe, without causing the pipe to block. They are suitable for sediment removal, as the sediment can be transported out of the reservoir through a pipe, using the natural head as the driving force. The techniques are simple. Both the SPSS and the SSS can be manufactured from circular pipes and the only movable part is the valve on the outlet pipe. Laboratory experiments, field experiments and field experience all show that the SPSS and SSS can meet the requirements listed below: 1. Sluicing of sediments should be possible without interrupting water supply from the reservoir. 2. The technique should be reliable and simple to implement and operate. The chances of maloperation causing severe problems, such as blocking of the pipeline, should be small. 3. A minimum of water should be required for the transport of sediment out of the reservoir, and the necessary investment should be low. 4. It should be possible to operate the system without any input of external energy if the head between the water surface and the outlet is sufficient. 5. It should be possible to use sediment for construction, for land reclamation, as a soil improver in irrigation water or for regaining the natural sediment regime in the river.

To obtain efficient removal of sediment through a pipe or an open channel it is crucial to know the behaviour of the sediment-water mixture. Hydraulic transport of sediment in pipes is widely used and several methods for computation of such flow exist. Three methods for computation of limit deposit velocity and two for

u Summary

computation of headless were studied and found to compare reasonably well with laboratory and field experiments. However, when hypothetical slurries were studied, considerable differences between the methods were discovered. Transport of sediment in open channels is a field in which relatively little work has been done. Unlike sediment transport in pipes, no method for computing open-channel sediment transport seems to be generally accepted. An experiment was performed where a sediment-water mixture, which properties could be controlled, was tested simultaneously in a pipe and an open channel. It was found that the energy gradient required in the open channel was less than 2/3 of that in the pipe. On the basis of the experiments, methods for computing limit deposit velocity and head loss in open channels have been derived.

The applications for which the SPSS and SSS were developed, removal of sediment from reservoirs and bypass of sediment are described. The sediment transport capacity of pipelines and open channels has been computed for different sizes of conduits and flow situations. It has been shown that sediment deposits theoretically can be removed at a rate of 64,000 m3 per hour through a 1.5 metre- diameter pipe. Due its simplicity it is suggested that the SPSS can be used in hoppers and pressurised sand traps. An experiment was performed, which demonstrated that coarse sediment (e.g. for construction purposes) can be extracted from a pipe carrying a sediment-water mixture.

Some technical and economic conditions affecting the economics of sediment removal from reservoirs have been identified and studied. It is concluded that the benefits from increased dry-season power production can justify removal of sediment from a medium-sized reservoir. However, of more importance is the finding that the economics of such an undertaking are highly dependent on a number of these conditions. The removal of sediment from small reservoirs is discussed, and it is argued that this can be highly beneficial, because of the frequency with which the reservoir volume is used. Several additional benefits apart from the purely economical aspects are likely to be obtained, adding to the arguments for implementing a sediment removal system.

m

Preface

PREFACE

This report gives a summary of studies on sediment problems in reservoirs and a series of experiments undertaken to develop methods for removal of sediment from reservoirs. The work was undertaken during the years from 1993 to 1997, when I was enrolled as a doctoral student at the Norwegian University of Science and technology (NTNU), Department of Hydraulic and Environmental Engineering. Scholarship for the doctoral studies has been financed by NTNU. Thanks also go to to the research fund financed by NORAD and handled by the international office at NTNU, Veidekke and the Norwegian Research Council (NFR) for financing. A number of persons have been of invaluable help in this work, and my gratitude is hereby expressed to

- the employees of Butwal Power Company (BPC) and BPC Hydroconsult in Nepal for welcoming me and helping me in every possible way to perform field experiments at Jhimruk Hydropower Plant. - the Kristiansund project office, Stolt Comex Seaway ASA. The onshore test and the offshore use of the Saxophone Sediment Sluicer provided valuable knowledge and experience. - the employees of the National Institute of water and atmospheric Research (NIWA) in Christchurch, New Zealand, for welcoming me and making my five month stay such a valuable experience. In particular I want to thank Jeremy M. Walsh for the co-operation during and after my stay. Tanks are also due to Contact Energy ltd, for providing excellent reservoir data. - Nils Reidar Olsen at SINTEF, who developed and helped me using SSIIM. - Marimette Rynning at Titania AS for providing data for pipeline sediment transport at the Titania mines at Tellnes. - friends and colleges at the Department of Hydraulic and Environmental Engineering, NTNU, for making it such a good place of work and Svend Halstadtrp and Hans Frisvold, for construction of the experimental equipment which was always better than promised. - my advisor Professor Dagfinn K. Lysne and my co-advisor Professor II Torkild Carstens, both at the Department of Hydraulic and Environmental Engineering, NTNU. I want to thank them in particular, for their support, fruitful discussions, encouragement and belief in my work. - my parents, who introduced me to the joy of playing with sand and water, Berit, for the way she shared my fate during these years and Jakob, for the two happiest years of my life.

v vi Table of content

TABLE OF CONTENT

ABSTRACT...... i

PREFACE...... v

NOMENCLATURE...... xi

1. INTRODUCTION...... 1 1.1 General ...... 1 1.2 Background ...... 2 1.2.1 World water balance and water storage capacity...... 2 1.2.2 Deposition of sediments in reservoirs...... 3 1.2.3 Regional differences...... 3 1.2.4 Increase in number of reservoirs affected...... 5 1.3 About the study ...... 6 1.3.1 Objectives and scope...... 6 1.3.2 Limitations...... 6 1.3.3 Organisation of the thesis...... 7

2. SOME ASPECTS OF RESERVOIR SEDIMENTATION.... 9 2.1 Introduction ...... 9 2.2 Erosion and sediment yield...... 9 2.2.1 Erosion...... 9 2.2.2 Sediment delivery ratio...... 11 2.2.3 Trap efficiency...... 13 2.3 Temporal variability ...... 13 2.3.1 The anthropogenic impact...... 13 2.3.2 Examples...... 15 2.4 Spatial distribution ...... 16 2.4.1 Definition of reservoir lifetime...... 16 2.4.2 Global distribution of reservoir sedimentation...... 17 2.4.3 Observed sedimentation ratios...... 22 2.4.4 Discussion...... 22 2.5 Variability of sediment inflow ...... 23 2.6 Operation of reservoirs ...... 25 2.6.1 Capacity-Inflow Ratio...... 25 2.6.2 Capacity-Sedimentation ratio...... 25 2.6.3 Examples...... 26

vii Table of content

2.7 Consequences of reservoir sedimentation ...... 27 2.8 Strategies for coping with reservoir sedimentation ...... 28 2.9 Conclusions ...... 28

3. MODELLING OF RESERVOIR FLOOD DRAWDOWN WITH 2D SSHM...... 29 3.1 Introduction ...... 29 3.2 General Description ...... 30 3.3 Description of the reservoir drawdown strategy...... 32 3.4 Model description ...... 33 3.5 Model Representation ...... 35 3.5.1 The grid...... 35 3.5.2 Bed Roughness...... 36 3.5.3 The sediment...... 37 3.5.4 Model Boundary Conditions...... 39 3.5.5 The Water Flow...... 40 3.6 Sediment modelling of drawdown events ...... 40 3.6.1 Selection of timesteps and number of inner iterations...... 41 3.6.2 Modelled bed changes for the two flood drawdown events...... 42 3.6.3 Comparing uniform with non uniform sediment modelling...... 43 3.6.4 Discussion of results...... 44 3.7 Trap Efficiency ...... 45 3.7.1 Empirical Methods...... 45 3.7.2 Use of the SS1IM model for trap efficiency calculations...... 46 3.8 Conclusions ...... 47

4. THE SLOTTED PIPE SEDIMENT SLUICER...... 49 4.1 Introduction ...... 49 4.2 Description ...... 49 4.3 Experiments with inflow through a slot...... 50 4.3.1 Introduction...... 50 4.3.2 Theoretical considerations...... 50 4.3.3 Experimental setup...... 52 4.3.4 Experimental results...... 54 4.3.5 Discussion...... 55 4.4 Laboratory experiments with suction of sand ...... 56 4.4.1 Introduction...... 56 4.4.2 Experimental setup...... 56 4.4.3 Experimental procedure 58 4.4.3 Experimental results...... 59 4.4.5 Discussion...... 62 4.5 Field experiments ...... 64

viii Table of content

4.5.1 Location...... 64 4.5.2 Experimental setup...... 66 4.5.3 Sediment properties...... 67 4.5.4 Experimental procedure...... 67 4.5.5 Results...... 68 4.5.6 Discussion...... 71 4.6 Conclusions ...... 72

5. THE SAXOPHONE SEDIMENT SLUICER...... 73 5.1 Introduction ...... 73 5.2 Description ...... 74 5.3 Laboratory experiments ...... 75 5.3.1 Introduction...... 75 5.3.2 Experimental setup...... 75 5.3.3 Initial experiments with transport in a pipe...... 78 5.3.4 Experimental results...... 79 5.3.5 Optimisation of suction capacity...... 80 5.4 Field experiments in Nepal ...... 83 5.4.1 Introduction...... 83 5.4.2 Experimental setup...... 83 5.4.3 Experimental results...... 86 5.4.4 Sluicing by local staff...... 88 5.5 Removal of stones in the North Sea...... 89 5.5.1 introduction...... 89 5.5.2 Onshore experiment...... 90 5.5.3 Offshoreexperience ...... 91 5.6 Conclusions ...... 92

6. HYDRAULIC SEDIMENT TRANSPORT...... 93 6.1 Introduction ...... 93 6.2 Sediment transport in pipes ...... 93 6.2.1 Introduction...... 93 6.2.2 Types of flow...... 94 6.2.3 Methods for computation of limit deposit velocity...... 95 6.2.4 Methods for computing head loss...... 101 6.3 Sediment transport in open channels ...... Ill 6.3.1 Introduction...... Ill 6.3.2 Methods for computing sediment transport in open channels...... Ill 6.3.3 Experimental setup...... 114 6.3.4 Experimental procedure...... 117 6.3.5 Comparison between limit deposit velocity pipe and in open channel...... 118 6.3.6 Comparison between head loss in pipe and in open channel...... 119

IX Table of content

6.3.7 Proposede method for computing open-channel sediment transport...... 121 6.4 Conclusions ...... 126

7. APPLICATIONS AND ECONOMIC ASPECTS...... 127 7.1 Applications ...... 127 7.1.1 Introduction...... 127 7.1.2 Sediment transport capacity of pipes and open channels...... 127 7.1.3 Removal from reservoirs...... 130 7.1.4 Sediment modelling 132 7.1.5 Sediment bypass...... 132 7.1.6 Sand traps and desilting basins...... 133 7.1.7 Extraction of coarse sediment from pipes...... 135 7.1.8 Discussion...... 137 7.2 Economic aspects ...... 138 7.2.1 Introduction...... 138 7.2.2 Calculation of sediment transport capacity in a pipeline...... 139 7.2.3 Features of the hypothetical reservoir studied...... 139 7.2.4 Calculation for a basic case...... 140 7.2.5 Sensitivity to variation of input data...... 142 7.2.6 Discussion...... 145 7.2.8 Conclusions...... 147

8. CONCLUSIONS AND RECOMMENDATIONS ...... 149 8.1 Conclusions ...... 149 8.2 Recommendations for future work...... 150

REFERENCES...... 151

APPENDIX A: RESERVOIR DATA 159

APPENDIX B: MEASURING METHODS...... 161

APPENDIX C: EXPERIMENTAL RESULTS...... 163 Nomenclature

NOMENCLATURE

Latin letters:

A cross sectional area A, cross-section of the upper layer (Eq. 6-14) A2 cross-section of lower layer (Eq. 6-14) A^ cross-sectional area of flow in the open channel (Eq. 6-24) Ar Archimedes number, CDRep 2 (Eq. 6-6) a reference level (Eq. 3-1) a shortest axis of sediment particle B slot width Bf bed load as fraction of suspended load b medium axis of sediment particle b K width of water surface in open channel (Eq. 6-24) C average total sediment concentration, (parts per million, ppm) C flow resistance factor (conductivity), = V/(gHS)0,5 (Eq. 6-20) C, concentration in upper layer (Eq. 6-15) C2 concentration in lower layer (Eq. 6-15) Cc contact load concentration (Eq. 6-17) CD drag coefficient CDi drag coefficient of fraction x (Eq. 6-12 and 6-13) CDm average drag coefficient of sediment particles. (Eq. 6-12) Cf mean in situ concentration of fines < 0.74 p (Eq. 6-3) Cr mean in situ concentration Cv sediment concentration, by volume Cvf volumetric concentration of fine particles contributing to “equivalent liquid vehicle" (Eq. 6-5) C„ concentration by weight, decimal fraction (Eq. 6-18) CIR Reservoir Capacity: Annual Water Inflow Ratio CSR Reservoir Capacity: Annual Sediment Inflow Ratio c sediment concentration (Eq. 3-2) c longest axis of sediment particle cb sediment concentration at a reference level, a, above the bed (Eq. 3-1) c. concentration given by the formula (Eq. 3-3) cieff the resulting effective concentration for each size fraction (Eq. 3-3) D pipe diameter

xi Nomenclature

Dh hydraulic diameter = 4Rh d sediment grain size d mean grain diameter of sample (Eq. 6-20) dmra largest grain size dx grain diameter for which x % by weight of a sample is finer d50 median grain size E annual erosion (t-km ^yr 1) f Darcy-Weisbach friction factor F Fronde number Fl dimensionless limit deposit velocity (Eq. 6-1) Flg dimensionless limit deposit velocity in Gillies’ correlation (Eq. 6-2) FLoc dimensionless limit deposit velocity in open channel (Eq. 6-22) Fs average shape factor, = a / Vbc f. fraction of the i’th size in the bed material (Eq. 3-3) g acceleration due to gravity H flow depth (Eq. 6-20) h ’ dimensionless pressure head difference, = h/h 0 h 0 pressure head difference across pipe wall at position x = 0 h A observed water level in tube connected to point A h B observed water level in tube connected to point B hr hour h x pressure head difference across pipe wall at position x (m H20) i energy gradient of clear water in pipe (m H20/m) im energy gradient of sediment-water mixture in pipe (m H2G/m) imm energy gradient of sediment-water mixture in pipe, measured as metre sediment-water mixture per metre. (Eq. 7-1) K constant in the Durand-Condolios equation (Eq. 6-7) Km constant in the Durand-Condolios equation modified for open channel flow (Eq. 6-23 and 6-24) K entrance loss factor for slot kg kilogram km kilometre 1A B distance between points A and B on the outlet pipe. L Length of pipe through reservoir M Manning ’s M, 1/n Mt million tonnes m metre

Xll Nomenclature

masl metres above sea level mg milligram n Manning ’s n, 1/M P wetted perimeter ppm parts per million, mg sediment per kg sediment-water mixture R annual runoff (mm) Rep Reynolds particle number (Eq. 6-6) Rh hydraulic radius S channel slope S0 channel slope at which velocity with clear water is equal to velocity at slope S with sediment-water mixture (Eq. 6-23) SLeq density ratio of equivalent liquid, p Lcq/p w (Eq. 6-13) Sm energy gradient in open channel as m H20 per m (Eq. 6-23 and 6-24) S, relative density of sediment, p/p w s second T throughput, tonnes per hour (Eq. 6-18) t tonnes td thickness of sediment deposits (m) V velocity V, velocity in the upper layer (Eq. 6-14) V2 velocity in the lower layer (Eq. 6-14) VL limit deposit velocity in pipe (Eq. 6-1) VLoc limit deposit velocity in open channel. (Eq. 6-22) Vsampie volume of sample Vc critical velocity in pipe, at minimum head loss Vp Q velocity in a slotted pipe at x = 0 Vp x velocity in a slotted pipe at position x vs,0 velocity through the slot at x = 0 vs,x velocity through the slot at position x WB S+w weight of container with water and sand WB w weight of container with water ws fall velocity of particles x position along slotted pipe axis x’ dimensionless distance from the beginning of slot x. volume fraction of particles with Cdi (Eq. 6-12) y^ depth of open channel (Eq. 6-21) yr year

xiu Nomenclature

Greek letters:

9 dimensionless bed shear stress, HS/[(Ss-l)d] (Eq. 6-20) 6cr critical Shields parameter adj usted for slope (Eq. 6-20) 8 ci0 critical Shields parameter (F,q. 6-20) K von Karman constant p. w viscosity of water p L viscosity of liquid (Eq. 6-6) p f viscosity of “equivalent ” liquid vehicle (Eq. 6-5) p r relative viscosity, p/p w (Eq. 6-5) viscosity of the equivalent liquid vehicle (Eq. 6-5 and 6-13) v viscosity of water p D dry density of sediment deposits p f density of fluid and fines < 0.74 pm (Eq. 6-3) p L density of liquid (Eq. 6-6) p Lcq density of equivalent liquid vehicle (Eq. 6-13) p m unit weight of sediment-water mixture (Eq. 6-18) p s density of sediment p w density of water T0 bed shear stress Tr critical bed shear stress at the threshold of motion AH Head between water surface and outlet of pipe transporting sediment 0 dimensionless excess headless (Eq. 6-7) 0k dimensionless excess head loss in open channel (Eq. 6-23 and 24) 0 transport parameter; Cv V R / ((Ss-l)d503-g)0,5 (Eq. 6-19) 0 dimensionless sediment transport rate, qb /[g(Ss-l)d3]0'5 (Eq. 6-20) r diffusion coefficient (Eq. 3-2) Y Durand-Condolios group of independent variables (Eq. 6-7) tF0C modified Durand ’s group for open channel (Eq. 6-23 and 24) \|/ shear intensity parameter; (Ss-l)-d30 / S R (Eq. 6-19) $ US$, 1997 1. Introduction

1. INTRODUCTION

1.1 General Water is stored in reservoirs for a number of purposes such as hydropower generation, irrigation, water supply, flood control, recreation and navigation. When a reservoir is formed on a river, the river will tend to lose its sediment transporting capacity, and sediment will deposit in the reservoir. The sediment load in many rivers is of such magnitude that it severely limits reservoir development. In particular, the development of medium-sized reservoirs is difficult, and sometimes not feasible at all. Medium-sized reservoirs in this context are defined as reservoirs with a capacity of between 3 and 30 % of annual water inflow. (Lysne et al, 1995, Rooseboom and Basson, 1996) The reason that medium-sized reservoirs, in which water can be stored with limited social and ecological impacts, cannot be built is that they are too large for conventional flushing techniques, and too small to store the sediment that accumulate in the course of the economic lifetime of the reservoir.

Figure 1-1: The upper reaches of the Kulekhani reservoir in Nepal, the country ’s only providing seasonal water storage. An estimated 4-5 million m3 of sediment accumulated in this 85 million m3 reservoir due to a single flood in 1993.

1 1. Introduction

Sites for construction of reservoirs tire a limited resource. Construction of new reservoirs when an increase in water-storage capacity is needed is therefore often not feasible. At the same time, it is generally accepted that the world is heading towards a water crisis, which will especially affect the arid and semi-arid regions. (Bruk, 1996) These, together with the regions of monsoon climate, are regions in which runoff is seasonal and sedimentation problems are often severe. Control of sediment deposition in reservoirs in these regions is therefore imperative to meet the demand for storage and supply of water.

1.2 Background

1.2.1 World water balance and water storage capacity The natural runoff of rivers will always vary and water storage reservoirs have therefore been created by building dams, from the times of the earliest civilisations until the present day. It is seen from Table 1-1 that of the total precipitation on land only 11 % becomes available as natural, stable runoff.

Table 1-1 World water balance in 1973. (km3) From Van der Leeden (1990)

Precipitation on land 110,300 100% Evaporation 71,470 65 % Flood river runoff 24,820 22% Stable runoff from reservoirs (1973) 1,840 2% Natural stable runoff 12,170 11 %

There has been a surge in dam and reservoir construction during the past 100 years, and this activity has really boomed world-wide in the past 50 years. According to ICOLD the number of dams higher than 15 metres increased from 5,000 in 1950 to more than 36,000 in 1986 (Bruk, 1996).

It can be seen from Table 1-2 that the estimates of the world’s water storage capacity in reservoirs vary among 4,000 and 6,000 km3. As 4,560 km3 is the volume of 486 reservoirs, the total volume is likely to be closer to 6,000 km3. More interesting, however, is the fact that if this estimate is accepted, nearly 60 % of the world's water storage capacity is found to be in the 52 reservoirs larger than 25 km3. It is also noteworthy that Mahmood (1987) estimates the storage capacity of all reservoirs smaller than 5 km3 to be 810 km3.

2 1. Introduction

Table 1-2: Estimates of world water storage capacity in reservoirs

SOURCE SOURCE CITED YEAR VOL. (km3) Mahmood (1987) UNESCO (1978) 1978 4,900 (1) Bruk (1996) Margot (1995) 1995 4,000 (2) Bruk (1996) Shiclomanov (1996) 1996 6,000 (2) W. P & D. C. (1996) 1996 Yearbook 1996 4,560 (3)

(1) : Including reservoirs larger than 5 km3 plus an additional 20 %. (2) Information on how these figures were calculated was not available. (3) : The 486 reservoirs where one of the following criteria is met are included: Dam height > 150 m or dam volume > 15 • 106 m3 or reservoir >25 TO9 m3 or installed capacity > 1000 MW. Includes reservoirs under construction. Some obvious errors in the Water Power Yearbook are corrected.

1.2.2 Deposition of sediment in reservoirs Estimates of annual deposition of sediment in reservoirs vary. Mahmood ’s estimate (1987) of 1 % annual storage loss is often cited. Bruk (1996) estimates the annual loss of storage capacity to be 1 - 2 %. In USA, estimates of the ratio of sediment deposition in reservoirs to the annual transport to oceans is 1.6:1 (Vanoni, 1975) and 2.7:1 (Van der Leeden, 1990) Similar rates world-wide yields annual depositions in reservoirs of approximately 24 and 40 km3, as the annual suspended sediment transport to oceans world-wide is estimated to be approximately 15 km3 (20 • 109 1) (Walling, 1996).

1.2.3 Regional differences The stable runoff, the reservoir storage capacity and the rate of sediment transport are not evenly distributed. There are large regional differences that affect the availability of water and the water storage capacity. The regional distribution of stable runoff per capita is shown in Figure 1-2, whereas the distribution of sediment runoff from major rivers is shown in Figure 1-3. The distribution of water storage capacity between the regions and the rate of construction is shown in Figure 1-4. Figure 1-4 is based on a study of the reservoirs of 486 major dams and hydropower plants. These hydropower plants fulfil one of the following criteria: dam height > 150 m, dam volume > 15 • 106 m3, reservoir volume > 25 km3 or installed capacity > 1000 MW. (W.P. & D C., 1996).

3 1. Introduction

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Figure 1-2: Distribution of stable Figure 1-3: Distribution of sediment runoff per capita. Based on runoff runoff from major rivers from data from 1973 (van der Leeden, different continents (Data from Van 1990) and 1995 world population der Leeden, 1990)

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Figure 1-4: Distribution of current reservoir volume and reservoir volume under construction in major dams and hydropower plants. (W.P. & D C. 1996)

4 1. Introduction

Some interesting observations can be made from Figure 1-2, 1-3 and 1-4: • Asia has the lowest stable runoff per capita, 1,200 m3 annually. (1995) • 64 % of the sediment transport from major rivers takes place in Asia. • The total water storage in Asia (excluding the former Soviet Union) is 888 km3, including projects under construction. Excluding projects under construction the present water storage capacity of major dams and hydropower plants in Asia is 316 km3 • Outside Asia 21 km3 of reservoir storage volume is reported to be under construction. This is only 0.6 % of the present water storage volume outside Asia, indicating a major decline in construction of new (large) reservoirs. Asia, where more than 50 % of the world's population lives, is clearly the region where water supply and the problem of reservoir sedimentation is of the greatest concern. A more thorough study of the spatial distribution of reservoir sedimentation is presented in Chapter 2.

1.2.4 Increase in number of reservoirs affected The world's population is increasing by more than 90 million people every year, and will pass 6 thousand million in 1998. As a result of increasing economic growth, the need for power, irrigation and water supply, the need for water and water storage is likely to increase even faster than the population itself. New reservoirs will be built on increasingly difficult sites, because the best sites have already been developed. The number of existing reservoirs seriously affected will also increase as volume is lost to sedimentation every year. Figure 1-5 shows how reservoir volume affected by sedimentation will increase over the next few decades in India.

CUM. GROSS VOL OF RESERVOIRS AFFECTED BY 50 % STORAGE LOSS

YEAR 2000 17 RESERVOIRS YEAR 2020 AFFECTED 27 RESERVOIRS CAP. = 11 KM5 AFFECTED CAP. = 39 KM3

2000 2020 2040 2060 YEAR Figure 1-5: Reservoir volume in India affected by sedimentation as a function of time. (From Kothyari, 1996)

5 1. Introduction

1.3 About the study

1.3.1 Objectives and scope To develop and operate medium-sized reservoirs on sediment carrying rivers in a sustainable way, the problem of reservoir sedimentation will have to be solved. A solution to the problem may be found if a portion of the water can be used to transport sediment out of the reservoir while water level and supply are kept at a normal level. The ability to model sediment movement and deposition within the reservoir, and understanding of the consequences of different operational procedures are crucial to any project. Knowledge of the economic aspects of sediment removal is important, not least when a solution to the problem has to be selected. On this background the objectives of the study are: • Identification of the extent and magnitude of the problem on a global and regional scale. This is achieved by a study of existing data in the literature. • Verification of a numerical model which can be used to model sediment movement, deposition and redistribution within reservoirs. This is done by remodelling a reservoir case where time series of flow and water levels, and information of actual bed changes are available. • Development and investigation of techniques for suction of sediment from reservoir deposits into pipelines and study of flow of sediment-water mixtures in pipes and open channels. This is achieved through laboratory and field experiments and via a study of the literature. • Investigation of the economic aspects of removal of sediment from reservoirs using the techniques developed, and existing and new knowledge of the sediment transport capacity of pipes and open channels.

1.3.2 Limitations Reservoir sedimentation is a large field that covers many disciplines. Even when limited to removal of sediment from reservoirs it is a too large a field for everything to be included within the frame of one thesis. It therefore important to observe that a number of topics are not dealt with here, or if included are given only a very brief presentation: • The process of sediment transport from the source of erosion to the reservoir. Sediment transport in rivers is a field in which much work has been done over the years, and an extensive literature exists. • All environmental impacts from reservoir sedimentation and from removal of sediment from reservoirs, including upstream and downstream consequences.

6 1. Introduction

• A number of ways by which deposition in reservoirs can be reduced or controlled including: Soil conservation measures, reservoir drawdown and sluicing, density current venting, flushing, bypassing of sediment-laden flows, removal of sediment by conventional dredging or excavation and storage of sediment in large reservoirs.

1.3.3 Organisation of the thesis Each chapter in the thesis is self-contained, except for a list of reservoir cases, description of measurements and experimental results which are found in the appendix.

Chapter 1 provides an introduction to the problem of reservoir sedimentation. Some aspects of storage of water in reservoirs are described. The objective, scope, limitations and organisation of the thesis are set out. Chapter 2 deals with various aspects of reservoir sedimentation, such as erosion and sediment yield, the temporal and spatial distribution of the problem and the unpredictability of sediment inflow. Possible measures for dealing with reservoir sedimentation are described briefly. Chapter 3 describes a specific case in which the numerical model SSIIM was used to model two reservoir drawdown events. Actual timeseries of inflow and downstream water levels were modelled, and the observed bed changes compared with those predicted by the model. Trap efficiency was also modelled. Chapter 4 describes a new technique for the suction of sediment-water mixtures into a pipe. The Slotted Pipe Sediment Sluicer (SPSS), which is stationary, is self-regulating so the sediment concentration is always close to the maximum that can be transported by the pipe. Chapter 5 describes the Saxophone Sediment Sluicer (SSS). This is suction head connected to a pipe. Similar to the SPSS, the technique is new and sediment can be sluiced at close to maximum concentrations. Chapter 6 deals with the hydraulic transport of sediment in both pipes and open channels. Relevant methods for computing sediment transport are examined and a new method of computing open-channel sediment transport is proposed. Chapter 7 deals with applications of the techniques described in Chapter 4 and Chapter 5. Some economic aspects in applying the methods are discussed and the sensitivity to variations in individual factors is examined.

7 8 2. Some aspects of reservoir sedimentation

2. SOME ASPECTS OF RESERVOIR SEDIMENTATION

2.1 Introduction There will always be variations in the flow of any river. In some cases these variations will be extreme, with the maximum flood discharge being 100 times the average discharge or more. Large differences between minimum and maximum river discharge are found in regions with a monsoon or a semi-dry climate as well as in cold regions where winter precipitation falls as snow. The intensity of floods combined with the dry season effect on vegetation in the monsoon and semi-dry climates, are major factors that contribute to the mobilisation and transport of sediment in rivers. Other factors add to the transport of sediment in these regions. The rate of weathering is increased when the climate is warm. The absence of glaciers during the last ice age has left deep profiles of weathered material and weak rock that are easily erodible. Not least, there are dense populations and intensive use of land in parts of these regions. The consequence is that regions where water storage is essential because of the variability of runoff are often the very regions where reservoir sedimentation problems are most pronounced.

2.2 Erosion and sediment yield The rate of sedimentation in a reservoir will depend on the following factors: • Erosion in the river basin, that is the amount of mobilised solids. • Sediment delivery ratio, in this context defined as the proportion of eroded sediment that reaches the reservoir. • Trap efficiency of the reservoir. The severity of reservoir sedimentation depends, among other factors, on the ratio between the runoff and the sedimentation rate. This is discussed in sections 2.4 and 2.6.

2.2.1 Erosion Erosion is a large field, and can only be treated briefly in this context. (A discussion of human induced temporal changes in erosion rates is provided in section 2.3.) Erosion rates may vary from less than 1 fkm'1,yf 1 (in some rivers in

9 2. Some aspects of reservoir sedimentation

Poland and on the Kola Peninsula in Russia) to 53,500 t-km'^yr" 1 (in Huangfuchuan in the Yellow River basin in China). Estimates of the annual erosion may vary between 50 to 75-109 t-yf *. Estimates for total suspended sediment transport to the oceans vary between 8.3 and 51.l-lO9 1 yr 1 with 20-109 t-yr' 1 being accepted as the most likely figure. (Walling and Webb, 1996) Erosion may be caused by water, wind, glaciers and chemical dissolution. Of these factors land erosion by water, defined as fluvial and interfluvial erosion of solid material, is the dominant one. Factors that determine the degree of erosion and thus the sediment yield into rivers include climate, relief, soil, vegetation and man ’s activities (Jansson, 1982). The highest erosion rates (which are in the Yellow River drainage basin) are thus found in areas where the following factors are present: • High-intensity rains • Seasonal rain • High topographical relief • High credibility • Sparse natural vegetation • Intense cultivation Erosion may be assessed from soil loss equations such as the Universal Soil Loss Equation, USLE. This equation was originally designed for more or less homogeneous fields, but several attempts have been made to adapt the USLE for use in small drainage basins. When basins are considered, weighting of individual factors must be introduced. However, the weighting is linear whereas the factors may be non-linear. Furthermore, slope; length is roughly estimated in a catchment, even though sediment yield from a drainage basin is very dependent on how far the detached material is transported. Some researchers have correlated sediment yield from catchments with different climatic and hydrological variables. (Jansson, 1982) Erosion can also be assessed from deterministic models based on knowledge of fundamental erosion processes.

A tool in assessing erosion is erosion maps or maps of suspended sediment runoff. Jansson (1982) and Walling and Webb (1996) are useful references in this respect. The early global maps of suspended sediment runoff by Fournier, Strakhov and UNESCO (published in 1960, 1967 and 1974 respectively) are based on few monitoring stations and are therefore inaccurate (Jansson, 1982). Later maps include those of Walling and Webb and Lvovitch. (Walling and Webb, 1996) The map of Walling and Webb is based on data from nearly 2000 river monitoring stations. Despite the major expansion in available data, many regions of the world remain unrepresented or poorly represented, and uncertainty still remains on the variations within many river basins. A major drawback is that

10 2. Some aspects of reservoir sedimentation

bed load is not included in these maps. Bed load may play an important role in the sediment transport process, especially in steep rivers. Even where data are available important uncertainties may exist because of lack of information regarding the source of information, short records, differing periods of record, non stationary river behaviour and not least, data reliability. Monitoring of sediment transport in general, and bed load transport in particular, during extreme floods can be difficult or even impossible. However, extreme floods play a major role in that they carry large parts of the total sediment load, as shown in section 2.5. Regional maps are normally based on a denser data net within the particular region than global maps, and must therefore be regarded as providing a more reliable picture of sediment yield conditions. However there are comparatively few regional sediment yield maps. This lack of information may arise from shortage of sediment yield data in combination with the fact that erosion varies vividly even within small areas. (Jansson, 1982)

2.2.2 Sediment delivery ratio Delivery ratio is the percentage of eroded material that is delivered from an erosion source to a downstream location. The downstream location in this context is the reservoir and the section of the river affected by the reservoir. The delivery ratio is affected by factors such as: (Jansson, 1982) • Land use and vegetation • Amount of overland flow • Size of transported material • Channel density (which affects proximity to streams) • Relief and depositional areas • Catchment size

1.00 1 0.50

I 0.20

i 0.10 I I 0.05 I 0.02

0.01 0.01 0.1 1.0 10 100 1000 Drainage area (square miles) Figure 2-1: Relationship between size of drainage basin and sediment delivery ratio, catchments in USA. From Vanomi (1975)

11 2. Some aspects of reservoir sedimentation

An inverse relationship between specific sediment yield and drainage basin area (as shown in Figure 2-1) has been widely reported. The inverse nature of the relationship is usually accounted for in terms of the increased opportunity for deposition of transported sediment as it moves through the fluvial system.

(a) 100CH 1 GreaterYenisei 2 Abakan 3 Amchun 4 Ussuri

5 Chusovaya 6 Malka 7 Biya, upper Ob

E 0------1------1 i I i I : i ! I S 0 20000 40000 60000 80000 100000

8 Shaiyo 9 Khemad 10 Rositsa M 100-= 11 Ogosta 12 Raba

10000 Eiasin area (km2)

Figure 2-2 Relationships between specific suspended sediment yield and basin area documented by Dedkov and Moz;zherin. (a) Evidence of positive relationship (b) Evidence of negative relationship (From Walling and Webb, 1996)

Walling and Webb (1996) however mentions a number of recent studies questioning this simple relationship. Dedkov and Mozzherin suggest that river systems will be characterised by either a positive or negative relationship between specific sediment yield and catchment area, according to the relative importance of channel and slope erosion (see Figure 2-2). Where channel erosion is dominant erosion rates will increase downstream as a result of greater entrainment and transport of sediment. Where slope erosion (i.e. sheet and gully erosion) constitutes the dominant sediment source, a portion of the mobilised sediment will be deposited during transport titirough the system. It is thus important to question whether some of our commonly accepted assumptions reflect the preponderance of studies based on regions such as the USA which are heavily impacted by human activity, rather than a more general feature of the global system. (Walling and Webb, 1996)

12 2. Some aspects of reservoir sedimentation

2.2.3 Trap efficiency The trap efficiency of reservoirs is found to depend mainly on the size of the reservoir compared to the annual inflow of water. (Brune, 1953) The trap efficiency will also depend on factors such as sediment grain size, shape of reservoir and mode of reservoir operation. A well known and much used method for estimating trap efficiency is use of Brune ’s trap efficiency curve shown in Figure 2-3. (Brune, 1953) Other methods for estimation of trap efficiency include those of Brown, Chen and Buttling, Churchill and Shaw (Graf, 1984) Trap efficiency may also be modelled numerically. An example of this is provided in Chapter 3, where modelling of the trap efficiency of Lake Roxburgh in New Zealand is described.

____ Median curve for. ** —narmal ponded

^Envelope curve • Normal ponded reservoirs i_for normal ponded o Normal ponded reservoirs i reservoirs with sluicing or venting operations in effect o Desitting basins

0.001 2 3 5 7 0.01 2 3 5 7 0.1 5 7 1 Capacity Inflow Ratio, CIR Figure 2-3: Brune ’s relationship between Reservoir Capacity : Annual Inflow Ratio (CIR) and trap efficiency for reservoirs. Modified from Brune. (1953)

2.3 Temporal variability

2.3.1 The anthropogenic impact Transport of sediment in rivers is and will always be a natural phenomenon. (St0le, 1993) However, human impact may alter natural conditions in ways that change (usually increases) the rate of erosion and thus sediment transport in rivers. It has been assumed that 50 % of all erosion is accelerated or anthropogenically induced. Walling and Webb (1996) states: “It is well known that soil erosion rates increase by an order of magnitude or more under cultivation and other agricultural activity. When it is recognised that that area of the earth ’s surface given over to crop production and livestock grazing has increased by a factor of more than five over the past 200 years, it is clear that

13 2. Some aspects of reservoir sedimentation

such changes must have produced increases in the sediment loads transported by the world ’s rivers.” Long-term records for sediment transport are lacking for most areas of the world. However, evidence of such changes is found in other sources, such as geological records of sediment deposition in lakes and in the sea (Walling and Webb, 1996):

• Long-term rates of Holocene (9000 BC to present) sedimentation rates in the Yellow and East China Seas (which receive sediment from the Yellow River) indicate that the sedimentation has increased by an order of magnitude since the early and middle Holocene. The change is believed to be caused by land clearance and agricultural development in loess regions of the Middle Yellow River basin. • Reconstruction of changing sediment delivery rates to the Black Sea suggests that sediment delivery has increased by a factor of about three over the past 2000 years as result of deforestation and agricultural development. • From analysis of sediment deposits in small lakes it is widely documented that catchment areas disturbed by human activity have experienced increases in sedimentation in ranges from five to ten times the original sedimentation.

Dedkov and Mozzherin (1996) found that human economic activities increased the suspended sediment load by an average factor of 3.5 for large rivers and by a factor of 8 for small rivers. Figure 2-4 illustrates how logging and roads can increase the number of landslides and thus sediment transport. Figure 2-5 illustrates how agriculture may affect erosion.

Figure 2-4: Distribution of 725 Figure 2-5: Erosion from vegetation landslides in Oregon after 1964/65 plots relative to dense forest or floods. From Jansson (1982) culture with thick straw mulch. From Jansson (1982)

14 2. Some aspects of reservoir sedimentation

2.3.2 Examples Several reservoirs have experienced changing sedimentation rates, both increasing and decreasing. The Ringlet reservoir is a lake created by the construction of a 40 m high dam on Sungai Bertam in the Cameron highlands in Malaysia. The reservoir has a total volume of 6.5-106 m3, is 3 km long and has a total catchment of 183 km2. Took Kun (1997) describes how the annual sedimentation rate has increased from around 30,000 m3-yr _1 in the sixties and early seventies to approximately 250,000 m3-yr" 1 in 1996, see figure 2-6. The increase in sedimentation rates is generally believed to be caused by factors as deforestation, (uncontrolled) farming and urban development.

Walling and Webb (1996) cites a study by Abemethy, based on an analysis of reservoir sedimentation data for a number of reservoirs in Southeast Asia. These reservoirs had been impacted by land use change during the twentieth century, (see Figure 2-7) and annual rates of increase in sediment yield were within the range of 2.48 - 6.02 %. It was suggested that the annual increase in sediment yield was closely linked to annual increase in population.

On the other hand, there are also examples of annual sediment yields decreasing with time, as in southern Africa. The average load for the major rivers in the region fell by more than 50 % during the period 1929 - 1979. The decrease has been attributed to over-exploitation of part of the catchment and removal of readily erodible top-soils. (Rooseboom and Basson, 1996)

240000 20000

5 200000 • - 10000 Cilutimg, Java 4.47 %yr 3 160000 Ambuktao. H 120000 -- Phiipines Paeal. Java 6.02 % yr* 2.85 % yr 1 80000

< 40000

1960 1970 1980 1990 2000 Year (middle of measured period) Year Figure 2-6: Increase in sedimentation Figure 2-7: Trends of increasing in Ringlet reservoir. From Fok Kun sediment yield during this century in (1997) selected reservoir catchments in Southeast Asia. From Walling and Webb (1996)

15 2. Some aspects of reservoir sedimentation

The Guarding reservoir on the Yongcling river in China controls a catchment area of 43,400 km2. From the 1950s to the 1970s the annual runoff was reduced by more than 50 % and the sediment load by more than 80 %. This reduction is due to upstream reservoirs (41 %), soil conservation (12 %) and irrigation and warping (47 %). (Warping is diversion of sediment-laden water with the purpose of forming and cultivating arable land) Sanmenxia on the Yellow River has experienced a similar decline in runoff and sediment load.. From the 40’s to the 70’s and 80 ’s the reduction in runoff of was 38 % and the reduction in sediment load is 54 %. The change has been attributed to climatic variations, water resources development and soil conservation. (Zhide, 1996a)

■ Quanting 40 -- Sanmenxia 20 -- Thungabadra

10 year period of measurement

Figure 2-8: Reduction in sediment loads entering one Indian and two Chinese reservoirs over the past decades. From Zhide (1996a)

2.4 Spatial distribution

2.4.1 Definition of reservoir lifetime Sedimentation and subsequent reduction in performance is a gradual process where no sudden, non-functional stage is reached, therefore no strict definition of reservoir lifetime exists. Sedimentation and consequent reduction in capacity and reservoir performance can be classified in the following phases: (Central Water Commission, 1996)

Phase I: The reservoir suffers no adverse effects of sedimentation and is able to deliver the full planned benefits.

16 2. Some aspects of reservoir sedimentation

Phase II: The reservoir delivers progressively smaller benefits, but its continued operation is for the reduced benefits is economically beneficial. Phase III: The sedimentation causes difficulties in operation such as jamming the passage of flows in canals or through turbines. Phase IVA: The benefits reduce to such an extent that it is no longer beneficial to operate the reservoir. Phase IV: The phase III difficulties become so serious that operation becomes impossible.

In the present concept phase I is called the full service period, and phase II is called the feasible service period. The beginning of phase IV (A) will depict the end of the reservoir ’s economical life and the beginning of phase IV depicts the end of its physical life.

Few reservoirs will reach phase IV (A) or IV because modifications in operating rules and/or modifications to the dam or reservoir will be beneficial during phase II or Phase III. Therefore, the following definition of reservoir lifetime with respect to sedimentation is proposed:

“The lifetime of a reservoir is the time it can be operated according to original rules without any major modifications being necessary for physical, environmentalor economical causes related to sedimentation ”

2.4.2 Global distribution of reservoir sedimentation In comparing sedimentation problems between different regions the definition of reservoir lifetime proposed in the previous section is difficult use because it is specific to each single reservoir. It was therefore chosen to use the Reservoir capacity: Annual sediment inflow ratio (CSR) for a typical medium sized reservoir as a measure on sedimentation problems. CSR, in other words, is the time it takes for the reservoir to fill completely if all incoming sediment deposits in the reservoir.

A world map of reservoir sedimentation has been prepared. The map shows reservoir sedimentation as the CSR of a medium sized reservoir. The map was constructed by combining a world map of suspended sediment yield with a map of average annual runoff. The map of suspended sediment yield used is prepared by Walling and Webb (1996) and shows suspended sediment yield from

17 2. Some aspects of reservoir sedimentation

intermediate-sized drainage basins, i.e. 1000 - 10,000 km2. The map of annual runoff used is from the Water Encyclopedia (Van der Leeden, 1990).

The global pattern of suspended sediment yield map was transformed into the same projection as the map of average annual runoff. The maps could then be compared and values for the lifetime of reservoirs computed. Preparation of the map was based on the following:

1. A reservoir with Reservoir Capacity: Annual Inflow Ratio (CIR) of 10 % was selected to represent a typical medium-sized reservoir. Medium sized reservoirs may be defined as reservoirs in which CIR is between 3 and 30 %. (Lysne et al, 1995) A more detailed discussion of reservoir size with respect to sedimentation is given in section 2.6.1. 2. CSR for reservoirs with CIR = 10 % was chosen as a measure of reservoir sedimentation intensity. This value is related to annual runoff of water and sediment only, and is therefore suitable when sediment problems in different regions are to be compared. 3. The dry density of trapped sediment deposits, p D, is assumed to be 1325 kg/m3. This equals a volume fraction of sediments of 0.5, provided a sediment density = 2650 kg/m3. Dry density may vary depending on grain size and to what degree sediment deposits are submerged. Values may vary from 416 kg/m3 for always submerged clay to 1550 kg/m3 for sand. (Graf, 1984) 4. The bed load is assumed to be 20 % of the suspended load. Dedkov and Mozzherin (1996) found that the bed-load percentage of the suspended load ranged from 7 % in plain regions to 28 % in mountain regions. The value of 20 % was chosen because major floods carry a large portion of the total sediment load and because the bed load fraction is found to increase with increasing flow (Bulgurlu, 1977). Bed load is very difficult or impossible to measure during heavy floods, and is therefore often underestimated.

The value of CSR depends on the dry density of sediment deposits and on the bed load fraction. These values vary depending on river and sediment properties. Round figures that are believed to represent a typical average were therefore chosen. As the map shows there is a wide range of the values of CSR. The selection of dry density and bed load fraction will not therefore affect the appearance of the map significantly.

It is important to note that values of CSR found on the map do not represent the real lifetime of a reservoir with CIR = 10%. Some sediment will always pass the reservoir, and some of the sediment may deposit in the river upstream of the reservoir. On the other hand, a reservoir will face serious problems long before it

18 2. Some aspects of reservoir sedimentation

is completely full of sediment. According to the definition proposed in section 2.4.1, the lifetime of a reservoir with a relatively high trap efficiency will be typically be less than the value of CSR.

The Capacity - Sediment inflow ratio of a reservoir is:

(2-1)

E annual erosion (t-km"2-yr"!) R annual runoff (mm) Bf bed load as fraction of suspended load CIR Reservoir capacity: Annual inflow ratio p D dry density of sediment deposits (kg-m3) Bf = 0.20, CIR = 0.10 and p D = 1325 kg-m"3 yields:

CSR = RE -110.4 (2-2)

The average total sediment concentration, measured as parts per million (ppm) is:

Cppm=(l + Bf)^-1000 (2-3)

The map shown in Figure 2-11 has a resolution far too low to be used for detailed planning. However, in an early phase it may provide some information on what kind of sedimentation problems that may be expected. An example of how the map is used will therefore be provided:

A reservoir with the following characteristics is considered:

Reservoir volume: 41-106m3 mean annual flow: 10 mV1

The reservoir has thus a CIR = 41-106/(10-31.5-106) = 0.13 From the map shown in Figure 2-11 it is found that CSR for a reservoir with CIR = 0.10 is 25 - 50. CSR for the present reservoir is therefore estimated to be: (0.13/0.10) 25 - (0.13/0.10) 50 =32-65. The reservoir is expected to have a trap efficiency of 90 %. Serious sedimentation problems are expected when the reservoir is 30 % full of sediment, which is in: (0.3/0.9) 32 - (0.3/0.9) 65 = 11 -22 years .

19 2. Some aspects of reservoir sedimentation

1 permanent ice

Figure 2-9: Map of annual suspended sediment load from medium-sized catchments. (Walling and Webb, 1996)

Figure 2-10: Map of annual runoff. Modified from Van der Leeden. (1990) The map is simplified compared to the map used in the present study.

20 2. Some aspects of reservoir sedimentation

Figure 2-11: World map of Capacity: Sediment inflow Ratio (CSR) when Capacity-Inflow Ratio (CIR) is 10 %.

21 2. Some aspects of reservoir sedimentation

2.4.3 Observed sedimentation ratios Sedimentation data from 36 reservoirs have been used to calculate CSR for reservoirs with CIR = 10 % at each location. These values of CSR are compared with the CSR found from the world map shown in Figure 2-11. The reservoirs are listed in Appendix A.

30

Resevoirs where CSR are 25 within the predicted range

20 - I Reservoirs where Resevoirs where 1 , CSR is overestimated CSR is underestimated 15 - (Sedimentation is more (Sedimentation is less

-3 -2-10123

Deviation from predicted CSR

Figure 2-12: Comparison of observed sedimentation ratios with values predicted from the map shown in Figure 2-11. The numbers on the x-axis refer to number of ranges the actual sedimentation deviates from the predicted.

Figure 2-12 show how the observed sedimentation ratios (listed in Appendix A) compare with values predicted from (he map shown in Figure 2-11. An example is provided to fully explain the figure: If the predicted CSR is in the range of 25 - 50 and the actual CSR is within the range of 10 - 25, CSR is overestimated by one range. In this case actual sedimentation is more severe than predicted.

2.4.4 Discussion It must be strongly emphasised that the map shown in Figure 2-11 is a world map with a very limited resolution, and must therefore be used accordingly. Both runoff and suspended sediment transport may vary by many orders of magnitude within small areas, but such details have to be left out on a world map.

22 2. Some aspects of reservoir sedimentation

In the preparation of the map it was found that CSR in very dry areas was difficult to calculate because of the sensitivity to small absolute changes in runoff. Also, areas with high suspended sediment transport proved to be difficult because 1000 t-km'2 was the highest limit on the map of suspended sediment transport (Figure 2-9). Suspended sediment transport rates higher than 10,000 t-km 2 have been reported numerous places. (Walling and Webb, 1996)

The cases with which the map can be compared are found in the literature. All relevant cases available to the author have been included. It is seen in Figure 2-12 that the observed sedimentation ratios compare well with the ratios predicted from the map. The sedimentation rates predicted from the map seem to be slightly underestimated, as more sedimentation rates are underestimated overestimated. However several factors that affect such a conclusion should be noted: • Cases presented in the literature are likely to be those in which sedimentation problems are specially severe. The reservoir sedimentation cases studied here may therefore not be representative for the average reservoir sedimentation cases within an area or region. • Reservoirs are likely to be built on sites or on rivers where sedimentation problems are small. This may lead to the opposite conclusion, i.e. that only reservoirs on “good ” rivers are selected because only those exist. • Sedimentation may not be correctly assessed. Deposition in the river channel upstream of the reservoirs may not be included or underestimated, thus yielding low deposition rates. The trap efficiency, which was assessed from Brune ’s relationship (Figure 2-3), may not be correct. • Temporal changes may cause earlier estimates of sediment transport to be wrong as sediment transport may have either increased or decreased. • There will be variations in the dry density of the sediment deposits depending on sediment properties, the residence time and operational strategies of the reservoir. However, a constant value of 1,325 t/m3 was used in this study.

2.5 Variability of sediment inflow Although the average annual sedimentation rate in a reservoir can be assessed, large variations in actual annual values are likely to occur. Examples where single floods have carried several years of average sediment load include: • Khulekani reservoir in Nepal is the country ’s only seasonal water storage reservoir. The original water storage capacity was 85 million m3, which equals 55 % of the annual runoff. An unprecedented rainfall and flood hit the watershed on 19 - 20 July 1993. The rainfall, recalculated after the flood, had a return period of 90 years. The sedimentation rate according to surveys was 5.2

23 2. Some aspects o f reservoir sedimentation

million m3 between March and December 1993, whereas the average annual sedimentation from 1979 to 1995 was 0.9 million m3. (Sthapit, 1996) • Rock Creek reservoir on North Fork Feather river in California has an average annual sediment delivery estimated at 1 million tonnes. During the highest flood on record (in 1986) the sediment yield was estimated at 10 million tonnes. (Harrison, 1996) • Lake Roxburgh on the Clutha river on the South Island of New Zealand trapped an average of 1.5 million m3 annually between 1961 and 1989. After a flood in 1978 the reservoir was surveyed, and it was found that the rate of deposition was 4.7 million m3 in seven months. (Webby et al, 1996) Five floods larger than the 1978 flood have occurred over a period of nearly 120 years, and it is thus estimated that the flood had a return period of approximately 20 years. • Over a period of 31 years 75 % of the sedimentation in the Miwa Reservoir in Japan occurred in the four years with the largest floods in that period. In the year with the largest flood the sediment accumulation was nearly seven times the annual average (Ando, 1994). Figure 2-13 and Figure 2-14 show how sedimentation in reservoirs is related to the return period of the largest flood in each year.

10000

o 1000

Return period Return perid

Figure 2-13: Return period of floods Figure 2-14: Flood size distribution and observed sedimentation rates in at Miwa dam in Japan. Data from Miwa reservoir. Values for Ando (1994) Kulekhani, Roxburgh and Rock Creek are also shown. Data from Ando (1994) Harrison (1996) Sthapit (1996) and Webby et al (1996)

24 2. Some aspects of reservoir sedimentation

2.6 Operation of reservoirs Two empirical indices can be used in preliminary evaluations to decide the mode of operation for sediment control: • Volume of the reservoir relative to the volume of annual inflow (Capacity.Inflow Ratio, CIR) • Volume of the reservoir relative to the volume of annual sediment inflow (Capacity: Sediment-inflow Ratio, CSR)

2.6.1 Capacity-Inflow Ratio The CIR has a major impact on the operation of a reservoir as it is a measure of its size and the amount of water available for flushing/sluicing operation or reservoir drawdown. Reservoirs may be divided in three groups according to CIR (Lysne et al 1995)

CIR > 0.3: Many reservoirs in this category will be able to store the incoming sediment loads within the economic life of the reservoir. In some cases density current venting may be applied. 0.03 < CIR < 0.3 Many reservoirs in this category will be affected by sedimentation within their economic lifetime, but they are normally too big to effectively employ flushing. Drawdown of reservoir during flood season and density current venting may be possible. CIR < 0.03 Sediment inflow can be large compared to reservoir size, but flushing of sediment deposits and drawdown during floods is often possible.

2.6.2 Capacity-Sedimentation ratio Many reservoirs are designed to last for 50 or 100 years. (Basson and Rooseboom, 1996) Reservoir sedimentation problems however, occur long before the reservoir is completely filled with sediment. Therefore a CSR equal to 100 does not mean the reservoir will last 100 years, although the unit of CSR is year. An example of this is the Tarbela reservoir in Pakistan which is facing serious problems after 20 % of its original volume has become filled with sediment (Fox and Tariq, 1996)

25 2. Some aspects of reservoir sedimentation

2.6.3 Examples An example of a small reservoir is Ltike Roxburgh on Clutha in New Zealand. Its original CIR is 0.007 (which equals a retention time of 2.5 days). More than 50 % of its original volume has been filled with sediment since commissioning in 1956. (Webby et al, 1996) Its CSR is 60 years. No special drawdown or flushing strategies were applied until 1994, when a flood drawdown strategy was applied to redistribute sediment within the reservoir. The drawdown strategy is effective in redistributing sediment within the reservoir, although it is not intended to remove sediment completely from the reservoir.

An example of a medium-sized reservoir (although its absolute size is large) is the Tarbela reservoir in Pakistan, in which CIR originally was 0.21 and CSR 43. After 22 years of operation the minimum pool elevation now has to be raised to control delta advance towards intake and dam, although measures have been taken to reduce sediment deposition during monsoon periods (Fox and Tariq, 1996). Available reservoir capacity has been lost both because of sedimentation and because the minimum pool level had to be raised.

a 10000

oAswan

oFargegensee oL. Mead

-oThree Gorges - oL. Roxburgh oKulekhani oRoseires* oTarbela Xinqiao oTedzen oZhenzilian

0.001 Capacity - inflow Ratio, CIR (yr)

Figure 2-15: CSR plotted against CIR for a number of reservoirs. Modified from Zhide (1996b) and Basson and Rooseboom (1996)

Yet another medium sized reservoir is Roseires dam on the Blue Nile in the Sudan. Its CIR is 0.06 and CSR 43. After 10 years of operation serious problems occurred when sediment and debris s tarted to enter the intake. Increasing sluicing capacity and lowering of the pool level will only be considered if Sudan can reduce its dependence on the Roseires Power Plant by having an adequate backup power supply (Pemberton, 1996). The latter illustrates a conflict that often hinders sustainable operation of reservoirs.

26 2. Some aspects of reservoir sedimentation

A large reservoir and probably the best known reservoir in the world is Lake Nasser behind the Aswan High Dam on the River Nile in Egypt. Lake Nasser has a CIR of almost 2 and a CSR of 1700. (El-Moattassem and Shalaby, 1996) Although sediment deposition is a very serious concern in Egypt and the present solution is not sustainable, Lake Nasser will be able to serve as a reservoir for many hundreds of years. It is worth noticing that the average sediment concentration in the River Nile is 10 times the average sedimentation ratio in Clutha river entering Lake Roxburgh. The much higher value of CSR for Lake Nasser (See Figure 2-15) is due to the fact that Lake Nasser can store 285 times the volume of Lake Roxburgh, relative to the annual runoff of the respective rivers.

2.7 Consequences of reservoir sedimentation Sedimentation can have many consequences. An obvious one is that water- storage capacity is lost and that the reservoirs therefore lose their ability to supply water in periods when water demand is higher than the inflow. The economic impacts are perhaps most easily seen when water is used for hydropower where both the quantity and price of the product are known. When water has other uses such as water supply and irrigation it is more difficult to asses the losses caused by reservoir sedimentation. In the cases where reservoir capacity is used for flood control, the consequences of reservoir sedimentation may not be seen before a major flood strikes. Recreation and navigation may also be affected by reservoir sedimentation. One of the most general environmental impacts of reservoir sediments is the role they play in water quality dynamics, as they act both as sources and sinks of the chemical and organic constituents of reservoir water. Contaminants, in particular such as plant nutrients and toxic pollutants, are of concern here. Both bottom sediment and suspended sediment contribute to these water-quality impacts.

Sedimentation is likely to have consequences both upstream and downstream of a reservoir. Deposition of sediment in the river upstream of the reservoir can increase flood levels. (Rooseboom and Basson, 1996 and Webby et al, 1996). Wind-blown sediment which is carried out of the reservoir has also in some cases been a serious problem. Downstream of a reservoir subjected to sedimentation the sediment equilibrium in the river is disrupted. Since the flow that leaves the reservoir carries little sediment, the bed and banks of the river tend to become eroded. With bed and bank material becoming coarser the resultant changing habitat can have far-reaching consequences. (Rooseboom and Basson, 1996)

27 2. Some aspects of reservoir sedimentation

2.8 Strategies for coping with reservoir sedimentation Basson and Rooseboom (1996) divides strategies for dealing with reservoir sedimentation into four groups which will are briefly described below. 1) MINIMISE SEDIMENT LOADS ENTERING THE RESERVOIR • Soil and water conservation programme. • Upstream trapping of sediment (debris dams or vegetation screens). 2) MINIMISE DEPOSITION IN RES ERVOIRS • Drawdown and sluicing: passing sediment-laden flows through the reservoir by means of drawing down the water level. • Density current venting. • Bypassing of high sediment loads. (Bypass tunnel or channel, or off-stream storage that allows floods to be passed in the river). 3) REMOVAL OF ACCUMULATED SEDIMENT DEPOSITS • Flushing by drawing down the water level (in many cases emptying the reservoir) during floods or in the rainy season. Flushing is most efficient for reservoirs with CIR < 0.05 (Basson and Rooseboom, 1996). • Mechanical excavation or dredging. • Conventional hydraulic dredging. • Hydraulic dredging by use of gravity. (Transport of sediment in pipeline or by free surface flow in channel or tunnel). 4) ACCEPT DEPOSITION OF SEDIMENT • Compensate for reservoir sedimentation by raising the dam. • Abandon or decommission the silted reservoir and construct a new reservoir. • Import water from elsewhere.

2.9 Conclusions A number of factors are found to determine the rate at which sediment accumulates in a reservoir. The most important is the erosion rate, but the sediment delivery ratio and the trap efficiency of a reservoir are also of importance. Studies show that sedimentation can increase many-fold because of anthropogenic impacts, and 50 % of all erosion is assumed to be accelerated. It is shown that the inflow of sediment to reservoirs can vary up to ten-fold from year to year, because of the importance of large floods. A world map was produced, showing CSR when CIR = 10 %. It shows that regions where sedimentation problems generally are severe include western parts of North and South America, eastern, southern and northern Africa, parts of Australia and not least, most of Asia.

28 3. Modelling of reservoir flood drawdown with 2D SSIIM

3. MODELLING OF RESERVOIR FLOOD DRAWDOWN WITH 2D SSIIM

This chapter is written in co-operation with Jeremy M. Walsh, researcher at National Institute of Water and Atmospheric Research (NIWA), Christchurch, New Zealand. It is written during and after a five month stay at NIWA in 1996/97. The data is used, courtesy of Contact energy Limited.

3.1 Introduction This chapter presents as a case study, the numerical modelling of two flood drawdown trials within Lake Roxburgh, a hydro-reservoir situated on the Clutha River in New Zealand ’s South Island. Deposition of sediment has caused flood levels to increase within the reservoir, threatening the township of Alexandra, located near the upstream end of the reservoir. A drawdown strategy has been applied during floods, with the intention of mobilising coarse sediment deposits and moving these further into the reservoir. Thereby, with continued operation of the strategy, the flood risk to the township will be mitigated over time.

A non-uniform sediment model is used, based on data from the two flood drawdown trials. Further, the non-uniform-sediment model is used to estimate a trap-efficiency by sediment-size relationship for Lake Roxburgh over a range of flow conditions. The study has utilised the SSIIM model, a program developed at the Division of Hydraulic Engineering of the Norwegian Institute of Technology, Trondheim.

An advantage of numerical modelling in general and non-uniform sediment modelling especially is the ability to simulate the behaviour of the fine sediment fraction. This is important, in respect to reservoir modelling both for trap efficiency computation and for estimating sediment outflow concentration. Since physical modelling of fine sediment is difficult, such models may provide the only way of assessing fine sediment behaviour.

In non-uniform sediment modelling, the sediment transport computation is carried out per size-fraction. In such models, the bed can be represented as a thin active surface layer overlying thick parent layer. At each timestep, if the bed aggrades, the deposited sediment is uniformly mixed with sediment in the active layer to produce a new active layer sediment composition. Conversely, when the bed degrades, sediment from the parent layer is uniformly mixed with that in the

29 3. Modelling of reservoir flood drawdown with 2D SSIIM

active layer to maintain the active layer thickness. By this process, non-uniform sediment models can account for both spatial and temporal changes in sediment grain size. This is an important advantage, when modelling sedimentation in reservoirs over long time-scales or when rapid erosion is occurring, such as during sediment flushing.

3.2 General Description The Clutha River drains a 15875 km2 catchment on the eastern side of the Main Alpine Divide of New Zealand ’s South Island. With an annual runoff of 16.7 • 109 m3, it has the highest mean flow of any river in New Zealand. The Clutha was first dammed in 1956, at Roxburgh, creating Lake Roxburgh, a narrow hydro ­ reservoir (vol. = 117-106 m3) , approximately 150 m wide and 35 km long, confined predominantly in the steep Roxburgh gorge. The river was dammed again in 1992 at Clyde forming Lake Dunstan (vol.= 218-10 6 m3) upstream of Lake Roxburgh.. The township of Alexandra is located approximately 28 km upstream of Roxburgh Dam, and 12 km downstream of Clyde Dam. Figure 3-1 shows a location plan of the Clutha ca tchment.

Flow in the Clutha River at Roxburgh is sourced mostly from three lakes (Lakes Wakatipu, Wanaka and Hawea) which drain the eastern side of the Southern Alps. Whereas these 3 lakes contribute 83% of the mean flow at Roxburgh, their contribution to the sediment load is virtually nil. Minor tributaries account for the remaining 17% of the mean flow and almost all of the sediment load.

The long term mean flow at Roxburgh is 530 mV1. In comparison the mean annual flood and 1:100 annual exceedance probability event are estimated as 1500 mV1 and 2800 m3s"\ respectively.

Suspended sediment is source mostly from the Kawarau River which flows from Lake Wakatipu to a confluence with the Clutha approximately 20 km upstream of the Clyde Dam. This sediment is predominantly from a single tributary, the Shotover River, which drains a 1088 m2 sub-catchment close to the main-divide. Jowett and Hicks (1981) estimated the contributions of sediment to Lake Roxburgh from various sources based on daily sampling of suspended sediment over a 21 month period (1977-1979) for the pre-Clyde Dam situation. They reported that 88% of suspended sediment is sourced from the Kawarau, 8% from the Clutha River above the Kawarau-Clutha confluence and 4% from the catchment downstream of the confluence to Roxburgh. From various methods, they also estimated that bedload was in the range 10-30% of the total sediment load.

30 3. Modelling of reservoir flood drawdown with 2D SSIIM

The long-term mean sediment load of the Clutha at Roxburgh is estimated to be 2.5-3.2 Mt/yr. Prior to the formation of Lake Dunstan in 1992 behind the Clyde Dam Lake Roxburgh was trapping much of this sediment. As a result, a sediment delta has progressively been built-up by successive flood events leading to a reduction of storage volume within the reservoir of approximately 54% (1956- 1994). Backwater effects due to the advancing delta have also progressively increased the flood risk to the township of Alexandra located near the head of the reservoir (Fig 3-2).

With the commissioning of the Clyde Dam, Lake Dunstan is now trapping most of the incoming sediment load. Also because of its larger storage volume, and consequent higher trap efficiency, sediment that is fine enough to pass through Lake Dunstan, generally passes through Lake Roxburgh, as well. Further sediment deposition within Lake Roxburgh is, therefore, now greatly reduced.

Compared to the inflow of water Lake Roxburgh is a small reservoir, with a present reservoir capacity - annual inflow ratio (CIR) of 0.003. Originally, the CIR was 0.007

Pacific Ocean

Figure 3-1: Clutha catchment

31 3. Modelling of reservoir flood drawdown with 2D SSIIM

1979 ---- 1970

Distance Upstream of Dam (km)

Figure 3-2: Lake Roxburgh minimum bed level profiles

3.3 Description of the reservoir drawdown strategy In January 1994, a moderate flood event in the Clutha and Manuherikia rivers caused flooding to a level of 140.0 m around Alexandra township and significantly affected water supply and sewage treatment facilities. This occurred at the peak of the summer vacation period. The flood was estimated to have had a peak flow of 2400 m3/s with a 1:30 AEP. Peak flood levels were 1.6 m higher than for the same flow in a 1978 event.

Following a sediment transport model study, a reservoir drawdown strategy was implemented from April 1994 onwards with the objective of mitigating the flood risk at Alexandra by promoting sediment erosion of the delta. The strategy involved drawing the reservoir down to a fixed level (between 4.5 and 6.5m below normal operating level) during flood flows exceeding 850 mV1. For comparison, the long term mean flow for the Clutha at Roxburgh is 530 mV1.

Although reservoir drawdown is more normally used to promote sediment flushing, this was not the objective here. Rather, the objective was to promote sediment movement while maintaining coarse sediment, as much as possible, within the reservoir. With downstream usage of outflow water for irrigation and salmon farming, an increase in the coarse sediment fraction of the outflow suspended sediment load was considered undesirable.

The first full-scale drawdown trial was initiated in November 1994, when the Clutha River experienced a flood event with a peak discharge of 1300 mV1. The reservoir was drawn down 4.5-6.5 m below normal operating level for a period of

32 3. Modelling of reservoir flood drawdown with 2D SSIIM

approximately 3.5 weeks. The reservoir drawdown strategy continued to be applied over short durations for minor flood events during 1995. The second major drawdown trial was initiated in December 1995 when a very large event occurred (Qp = 3350 mV1) with the reservoir partially drawn down. This event was the largest in 66 years of record and probably the second largest in living memory.

In this study, both the November 1994 and December 1995 events are simulated. Figure 3-8 shows the record of computed lake inflow and headwater level for both events.

3.4 Model description This study has utilised the SSIIM model, a program developed at the Division of Hydraulic Engineering of the Norwegian Institute of Technology, Trondheim. SSIIM is a 2D/3D model which was developed primarily to simulate sediment movement in general river/channel geometries. It has been successfully utilised in other reservoir sedimentation / erosion studies as well as for 3D modelling of water -flow. (Olsen et al 1994, Olsen 1994, 1995)

HYDRO-DYNAMIC CALCULATION The SSIIM program solves the Reynolds averaged Navier-Stokes equations with a k-epsilon model on a three-dimensional almost general structured grid. The equations are discretisised using a finite-volume approach in which a power-law or second-order upwind scheme is used for the discretisation of the convective terms. The equations are solved implicitly.

SEDIMENT FLOW CALCULATION SSIIM calculates sediment transport by size fraction. Sediment concentration at a reference level near the bed is first estimated using an equilibrium bed load transport formula. Sediment continuity of cells above the bed is then enforced through solution of the advection-dispersion equation.

In this study, the Van Rijn (1987) formula has been adopted:

1.5 1 H r4 4' „ cb =0.015- 0.1 (3-1) a (p 5~Pw> P.v"

33 3. Modelling of reservoir flood drawdown with 2D SSHM

cb sediment concentration at a reference level, a, above the bed t0 bed shear stress tc critical bed shear stress at the threshold of motion p„ density of water p, density of sediment v viscosity of water g acceleration of gravity

The reference level, a, is taken as 1.5% of the water depth.

Van Rijn ’s approach considers sediment to be transported either in suspension or as bedload, depending on the relative magnitude of the bed shear velocity and the particle fall velocity. Bed load is considered to be transported by rolling and saltation at a rate which is linearly related to the saltation height above the bed. The Van Rijn formula is derived by equating suspended sediment concentration and bed load concentration at a near bed reference level. The constant, 0.015, was determined by empirically fitting the relationship using flume and field data.

Sediment concentration in cells above the bed is determined by solving the convection-diffusion equation: dc 9c f 9c ) 9 ( 9c — h U : —------h W c — — — r —— (3-2) 9t J 9xj (9xz J 9xj ^ 9xj c sediment concentration ws fall velocity of a sediment particle, T diffusion coefficient which is taken as equal to the turbulent viscosity.

This equation is not solved for the cells closest to the bed. Instead, the near bed concentration, as calculated by the Van Rijn equation, is “forced” on these near ­ bed cells. Sediment continuity for these cells is therefore not usually satisfied. The discrepancy in continuity is used to calculate changes in the bed levels.

When simulating multiple size fractions, the resulting effective concentration for each size fraction, cii6ff, is given by:

(3-3)

34 3. Modelling of reservoir flood drawdown with 2D SSIIM

fi fraction of the i’th size in the bed material Cj concentration given by the formula

A budget method is used to calculate the change in bed grain size distribution.

MODEL GRID The geometrical data are given in a file which describes the grid for the computations. The grid is three-dimensional, but is generated from a two- dimensional projection in the horizontal plane. For each grid intersection in the projected two-dimensional grid the x and y coordinates are required. Also the z coordinate for the bed level is needed. The grid x, y and z coordinates can be generated on the basis of geometrical data from the prototype. During transient sediment calculation the bed of the model is updated throughout the simulation to account for the changes in bed levels.

3.5 Model Representation

3.5.1 The grid A 32 km reach, from Roxburgh Dam to 4.2 km upstream of Alexandra (measured from Alexandra Bridge), has been modeled. The grid is made up of 250 -7-4 (1-w-h) cells. The shape of the initial bed bathymetry is based on 63 cross sections, obtained from a February 1994 survey. An example of a cross section through the grid is presented in Figure 3-3.

In fitting the grid to the reservoir bathymetry, some simplifications were necessary: 1. The sides of the reservoir are modelled as vertical due to model requirements. The error introduced is believed to be small, because of the steep bank topography along the reservoir. 2. The model is simplified in that only the wetted portion of the bed is included. Some banks that are inundated during high flows are therefore not included in the model. 3. Plan-form channel geometry is assumed to be unimportant. The reservoir has therefore been represented as a straight (i.e. one-dimensional) channel.

Flow is modelled two-dimensionally for the two drawdown events and for the trap efficiency calculations. As a control, trap efficiency was calculated three- dimensionally for a discharge of 1300 m3-s’1 and a water level of 130 m.

35 3. Modelling of reservoir flood drawdown with 2D SSHM

Figure 3-3: Example of cross-section through the grid, at 808 metres upstream of Roxburgh dam. The grid is divided longitudinally into 250 cells.

3.5.2 Bed Roughness The model was calibrated to match observed flood levels at Alexandra occurring during moderate flood events for which the flood drawdown strategy was in operation. A constant Manning number, M=27 was found to give reasonable results and has been applied throughout. (Note that the Manning number is defined as the reciprocal of Manning ’s n i.e. M=l/n). The calibration was further tested by running steady-state fixed bed simulations to determine simulated water surface profiles for comparison against two measured water surface profiles:

1. the December 1995 flood peak profile, measured from flood marks. An assumed constant flow of 3,350 m3/s was used with the headwater level at the dam drawn down; 2. a water level profile measured over the period January 15-17, 1996 during the January 1996 cross-section survey. Flow was in the range 1,010 - 1,160 mV1 with the headwater level in the noimal operating range.

Figure 3-4 shows the comparison between the observed and modelled water surface profiles for these two events. Considering the second event first, the roughness calibration for flows within the range 1,010 - 1,160 mV1 appears reasonable. The calibration, at the December 1995 flood peak, however, is less acceptable. In this case an almost flat water surface is evident from the Dam to approximately 18 km upstream, which distorts the longitudinal water surface profile through the reservoir. It is calculated that a Manning ’s n of approximately 0.015 is needed within this part of the reach to achieve a satisfactory fit to the measured data. This suggests the presence of an upper-regime plain-bed under peak flow conditions. We have not yet attempted to model this. However, we expect that due to the short duration of the flood peak (48 hours above 2,000 m3s" 1) compared to the 14 day drawdown period, most sediment transport will have occurred both before and after the peak, at flows ranging between 1,000 and 2,000 mV1 for which the roughness calibration is expected to be reasonable.

36 3. Modelling of reservoir flood drawdown with 2D SSHM

146 1 i 1 L ♦ Dec 95 Flood Peak survey (Q=3350 m3/s) 144 ------Modelled Dec 95 Flood Peak, Jan 96 bed 142 ------Modelled Dec 95 Flood Peak, pre Dec95 bed a 15-17 Jan 1996 Survey (1010-1160 m3/s) 140 I ------15-17 Jan 1996 (Modelled) LLl 138

136 1 . ,«AAA»AA» cn 134 4 M#JV' 1 132

130 ♦ * * + I 128 10 15 20 25 35 Distance Upstream of Dam (km)

Figure 3-4: Comparison of Modelled and Measured Water Surface Profiles in Lake Roxburgh

3.5.3 The sediment Surface bed sampling was undertaken at 15 sections between Roxburgh Dam and Alexandra in June 1994 using a combination of Dietz Grab and USBM-54 samplers. The Dietz was used over the bottom 17 km reach of the lake. Above 17 km, currents were stronger and the USBM-54 sampler performed better due to its greater weight ( 45 kg), and was used for the remaining sections. Both samplers took a sample from approximately the top 100 mm of bed material.

The model bed was divided longitudinally into seven sections. An initial bed material particle-size distribution was then derived for each of the seven sections based on the June 1994 surface bed sampling results. The density of sediment particles used in the model is 2650 kg-m'3 and the volume fraction of sediments used is 0.5, which is the program default. The dry density of sediment deposits used is thus 1325 kg-m"3.

Initial runs with the original bed material grain size distributions indicated too much erosion in the downstream regions of the reservoir. The reason for this is believed to be that cohesive forces are not being modelled. To correct for this, increased sediment sizes for the two finest fractions, represented by 0.056 mm and 0.25 mm particle size, were chosen on the basis of the Hjulstrpm ’s experiment (Vanoni, 1977). Hjulstrpm ’s graph, shown in Figure 3-5, shows that the stream velocity needed to erode fine particles equals that of coarser particles. Thus, 0.056 mm particles where modelled as 0.5 mm particles, and 0.113 mm

37 3. Modelling of reservoir flood drawdown with 2D SSHM

particles where modelled as 0.25 mm particles. In both cases the former particle size is assumed to have cohesive properties and the latter non-cohesive properties. The fall velocity of the particles was not increased, so that suspended sediment transport is still modelled correctly. Figure 3-6 shows the original bed material particle size distributions (dashed lines) and the modified distributions (full lines) for the seven longitudinal sections.

Mean sediment size, mm Figure 3-5: Hjulstrpm ’s graph. From Vanoni (1977)

The modelled sediment median grain-size profile is presented in Table 3-1. This profile is consistent with the observed increase in the median grain size from medium silts (0.05 mm) at Roxburgh Dam to medium gravels (10-20 mm) at the upstream end of the modelled reach, from the June 1994 survey. Figure 3-7 shows a comparison of the modelled and observed (June 1994) median grain size profile along the model reach.

Grain size (mm)

Figure 3-6: Grain size distributions used in the model. The original distributions, not adjusted according to Hjulstrpm ’s graph, is shown.

38 3. Modelling of reservoir flood drawdown with 2D SSIIM

Table 3-1: Longitudinal distribution of grain size (uniform model) and median grain size (non-uniform model)

From To dso Reference to (km from dam) (km from dam) (mm) Figure 3-6 0.00 4.88 0.07 a 4.88 14.96 0.21 b 14.96 16.97 0. 29 c 16.97 18.88 0. 77 d 18.88 21.00 4.6 e 21.00 26.86 5.1 f 26.86 32.55 10.9 g

100

10 ------size used in model (D50) E £ 1

* 0 *

10 15 20 25 30 35 Distance from dam (km)

Figure 3-7: Longitudinal distribution of the d50 grain size in the reservoir. Both measured (June, 1994) and modelled grain sizes are shown.

3.5.4 Model Boundary Conditions The hydrodynamic boundary conditions for the model are time-series of lake inflows and headwater levels at Roxburgh Dam. Values at 12 hour intervals were given. The model interpolates between these linearly.

Further, a no sediment inflow boundary condition is assumed. The assumption of zero sediment input is reasonable for three reasons: 1. sediment supply from the predominant sediment source (the Shotover River) has been curtailed with the commissioning of the Clyde Dam in 1992. Lake Dunstan, behind the Clyde Dam, is now trapping all of the incoming coarse

39 3. Modelling of reservoir flood drawdown with 2D SSIIM

sediment transported by the river. Further since Lake Dunstan has a higher trap efficiency than Lake Roxburgh, most sediment passing Clyde, is likely to pass Lake Roxburgh as well; 2. from recent experience, the reach from Clyde to Alexandra is stable. Therefore sediment supply from erosion of the river channel upstream of the model boundary should not be significant; 3. the contributing catchment to Lake Roxburgh downstream of Clyde is semi- arid with mean annual rainfall in the range 350-450 mm. Sediment inflows from the immediate catchment and tributary streams are therefore not significant.

3.5.5 The Water Flow

135 133 131 129 127 125 123 121 119 I 117 Nov 94 Dec 95 115

Figure 3-8: Discharge and downstream water levels for both drawdown events The water flow is modelled two-dimensionally for the two flood drawdown events and the trap efficiency calculations. As a control, trap efficiency was calculated three-dimensionally for a discharge of 1300 mV1 and a water level of 132 m. This needed 18 days to converge on a pentium 100 PC. The difference between 3D and 2D trap-efficiency calculations however, was less than 1 %.

3.6 Sediment modelling of drawdown events The two main flood drawdown events, the first occurring in November 1994 and the second in December 1995, have been modelled. Two small flood drawdown events occurring in March 1995 and October 1995 did not contribute significantly

40 3. Modelling of reservoir flood drawdown with 2D SSHM

to bed-material movement in the reservoir (pers. comm. J. Walsh, 1997) and have been neglected. The first drawdown was performed between 7. November and 13. December 1994, and the second between 6. and 24. December 1995. Figure 3-8 shows a compressed record of computed lake inflows and headwater levels for both events combined, in which data between the events have been removed. Normal lake level is at 132.0 m.

3.6.1 Selection of timesteps and number of inner iterations A period of 4.6 days of the first event was modelled using successively shorter timesteps to determine a suitable timestep for the simulations. Bed cumulative volume change was calculated as a function of distance from the upstream end of the reservoir by integrating the change in cross-section area for each model section by distance along the reach. The maximum cumulative bed volume change was then used as a test statistic (Figure 3-9). It was found that using a timestep of 200 seconds the modelled maximum cumulative bed volume change was 98.8 % of that obtained using 50 second timesteps. We therefore decided to adopt a timestep of 200 s.

A further analysis was made to determine a suitable number of inner iterations, that is, the number of iterations of the hydrodynamic and sediment transport equations to apply at each timestep in order to achieve suitably low velocity or sediment flux residuals. It was found that increasing the number of inner iterations for water flow from 10 to 16 and the number of iterations for sediment calculations from 6 to 10 only increased the computed maximum cumulative bed volume change by 1.7 %. It was therefore decided to use 10 inner iterations for water flow calculations and 6 inner iterations for sediment calculations.

Timestep (seconds)

Figure 3-9: Modelled maximum cumulative bed volume change as a function of the length of timesteps used.

41 3. Modelling of reservoir flood drawdown with 2D SSIIM

3.6.2 Modelled bed changes for the two flood drawdown events Figure 3-10 shows longitudinal profiles of average bed levels through the reservoir. The starting profile is derived from a February 1994 cross-section survey. The modelled profile, after both flood drawdown events, is compared to a profile derived from a January 1997 survey, see Figure 3-10

The changes in the reservoir bed geometry can also be presented as cumulative volume change. Cumulative volume change is a function of distance from the upstream end of the reservoir and can be interpreted as the total volume of sediment deposited (or eroded for negative values) in the reach upstream of a specific cross-section.

130 -■

------before events (Feb 94 survey) ——After both events (modelled) After events (Jan 96 survey)

Distcince upstream of dam

Figure 3-10: Modelled bed changes. Average bed levels before and after both flood drawdown events.

Figure 3-11 compares the modelled and measured cumulative volume changes for the first event and for the two events combined Most sediment is only redistributed within the reservoir, as seen in Figure 3-10. However, according to the model, some 3 million m3 of sediment is transported out of the reservoir during the two flood drawdown events. This sediment is mostly very fine (d50=0.06 mm, dmax=0.15 mm). The modelled grain size distribution of the removed sediments, shown in Figure 3-12, was derived from the sediment budget of the model after modelling of both events.

42 3. Modelling of reservoir flood drawdown with 2D SSHM

- - Computed, Nov 94 - Dec 94 - - Computed, Nov 94 - Jan 96 —Actual, 94-95 —Actual, 94-96

Distance from dam (km)

Figure 3-11: Cumulative volume change for the November/December 1994 event and for the two events together. Modelled and measured values are shown.

20 -- -

0.038 Grain size (mm)

Figure 3-12 Modelled grain size distribution of the suspended sediment outflow

3.6.3 Comparing uniform with non uniform sediment modelling Several previous researchers have highlighted the importance of accounting for sediment size-fractions in reservoir sediment modelling (Basson et al, 1996). To demonstrate this, a period of 7.6 days was modelled with a constant discharge of 880 mV1 using both a uniform and non-uniform sediment model. In the uniform sediment model the bed material was assumed to be represented by the d50 grain- size at each of the seven longitudinal sections over which sediment distributions had been calculated.

43 3. Modelling of reservoir flood drawdown with 2D SSIIM

The results of this simulation are presented in Figure 3-13, which compares the cumulative volume change for the uniform sediment case with that obtained for the non-uniform sediment case. The uniform sediment model predicts a higher maximum cumulative volume change which is a reflection of an over-prediction of sediment transport rates. This aspect is discussed in more detail in the next section.

-1.0 •- O Q> Non-uniform sediments Uniform sediments

-2.0 ■-

Distance upstream of Roxburgh dam (km)

Figure 3-13: Comparison of cumulative volume change from: the uniform sediment model; the non- uniform sediment model; and cross-section surveys. A constant discharge of 880 mV1 for a period of 7.6 days is modeled.

3.6.4 Discussion of results The non-uniform sediment model shows good agreement, in terms of cumulative volume change with that calculated from cross-section surveys (Figure 3-11). For the two events combined, the maximum quantity of bed material eroded at 7.8 * 106 m3 over-estimates that measured by just 11%. An important aspect is that, except for adjustments in the two finest sediment fractions, this result was obtained without calibration of the sediment transport rate. It is seen from Hjulstr0m’s graph (Figure 3-5) that the two finer fractions could have been modelled even coarser. According to the graph, 0.056 mm particles should have been represented by 1 mm particle size and 0.113 mm particles by 0.5 mm particle size. Using these particle sizes would probably have further improved the results.

Maximum cumulative volume change predicted with the uniform sediment model is 14 % higher than that predicted with the non-uniform sediment model, over the 7.6 day period of the simulation. The difference in sediment outflow modelled is

44 3. Modelling of reservoir flood drawdown with 2D SSIIM

nearly 100 %. The difference in modelled cumulative volume change is achieved in spite of the relatively uniform grain size distributions modelled (d^/dio = 2.5 - 3 in the lower reaches of the reservoir). The lower bed volume changes that occur in the non-uniform sediment case can be explained by the ability of the model to armour the upper (surface) layer of the bed, thereby limiting sediment supply. The benefit of using multiple size fractions to represent the bed material is therefore demonstrated.

The model shows that only sediment finer than 0.15 mm is flushed out of the reservoir during flood drawdown conditions. For comparison, an average of 4 depth-integrated sediment gaugings , taken during the December 1995 flood event at Millers Flat, approximately 10 km downstream of Roxburgh Dam, indicates that 90% of the suspended sediment load is finer than 0.125 mm and 93% is finer than 0.25 mm (pers. comm. J. Walsh). The model result is, within reason, consistent with the observations.

Only the two flood drawdown events have been modelled. There may have been bed changes occurring in between these events. However, the effect of 34 years of normal operation has been to accumulate sediment in the reservoir. With the low sediment input regime now operating, after completion of the Clyde Dam, bed changes are now mostly a function of the capacity of the flow to move the existing deposits. It is believed that significant erosion will only occur now during reservoir drawdown operation. Only two small flood drawdown event of 3.5 days total duration have occurred between the two events. Therefore bed changes between the two main events are believed to be small.

3.7 Trap Efficiency

3.7.1 Empirical Methods Two empirical methods are commonly applied to estimate the trap efficiency of reservoirs. Brune (1953) determined an empirical relationship for trap efficiency dependent on the ratio of reservoir capacity to mean annual inflow using data from more than 40 reservoirs. Another method was presented by Churchill (1948). This method relates the percentage of incoming material passing through the reservoir with a sedimentation index, which is the ratio of the period of retention ( defined as the reservoir capacity at mean operating pool level divided by the average daily inflow) to mean flow velocity through the reservoir. Chen (1975) presented a series of curves for various particle sizes relating trap efficiency to the ratio of basin area to outflow. He was able to demonstrate that

45 3. Modelling of reservoir flood drawdown with 2D SSIIM

both Brune's and Churchill ’s methods tend to underestimate trap efficiency for coarse material, and over-estimate for finer material. For a more detailed description of these methods, see Borland (1975) or Vanoni (1977).

3.7.2 Use of the SSIIM model for trap efficiency calculations The well established empirical methods of Brune and Churchill mostly give unreliable results. The SSIIM model, or similar non-uniform sediment models, provide the potential to better assess reservoir trap efficiency. Also, from such models, a relationship between inflow, particle-size and trap efficiency can be determined. If this relationship is known, it is possible to determine a long-term or event sediment budget for the reservoir, with flow and sediment concentration data at just one flow station (either at ihe reservoir outlet or at the inflow station).

To demonstrate use of the SSIIM model for trap efficiency calculation, steady state simulations were run for three discharges at both normal operating level (132 m above m.s.l.) and with 5 m drawdown (to 127 m above m.s.l.). Sediment inflows were modeled using equal amounts by mass of 10 grain-sizes ranging from 0.01 - 1mm. In all cases, the reservoir bed was assumed to be fixed. The bed bathymetry is modeled as the latest January 1996 survey. Trap efficiency is thus obtained for each of the 10 particle sizes for 6 different flow conditions. The modelled trap efficiency is presented in Figure 3-14.

100 .

0.010 Particle size (mm)

Figure 3-14: Modelled trap efficiency as a function of particle size. For each of the water levels of 127.0 and 132.0 masl three different inflows (550,1300 and 2850 mV1) has been modelled.

46 3. Modelling of reservoir flood drawdown with 2D SSIIM

Comparison of the trap efficiency curves at normal lake level with those under drawdown, indicates that, assuming a fixed bed, drawdown has little influence on the trap efficiency. If erosion of the bed had been allowed, the trap efficiency for all particle sizes would have been significantly reduced under drawdown conditions.

3.8 Conclusions 1. The SSIIM model has been applied to a case study of two flood drawdown trials in Lake Roxburgh, New Zealand. Good results were obtained in modelling erosion of the bed during the two events using a non-uniform sediment model. By comparison, a uniform sediment model has been shown to predict higher bed erosion. Both models utilise the Van Rijn (1987) sediment transport equations. An important aspect of this study is that, except for adjustments on the two finest sediment fractions to allow for cohesion, the results have been obtained without calibration of the sediment transport equations. 2. The case study demonstrates the importance of accounting for sediment transport by size-fraction in reservoir sediment modelling. The lower bed erosion observed in the non-uniform sediment model can probably be explained by the ability of the model to armour the upper (surface) layer of the bed, thereby limiting sediment supply. 3. A key benefit of a non-uniform sediment model is its ability to simulate fine- sediment behaviour. As physical modelling of fine-sediment is difficult, such models may provide the only option other than direct measurement in assessing fine sediment behaviour. The good match between modelled and observed sediment outflows from the reservoir during the two flood drawdown trials in Lake Roxburgh demonstrates the ability of the model to simulate the fine-sediment behaviour. 4. Use of the SSIIM model for trap efficiency calculation as an alternative to the well-established empirical methods of Brune (1953) and Churchill (1948) is demonstrated. The empirical methods mostly give unreliable results. We believe that the mathematical modelling approach provides a more robust alternative for trap efficiency estimation.

47 48 4. The Slotted Pipe Sediment Sluicer

4. THE SLOTTED PIPE SEDIMENT SLUICER

4.1 Introduction Sediment can be removed from a reservoir by hydraulic transport through a pipeline. Examples of this are provided by Bruk, (1985), and studies include those of Hotchkiss and Huang (1995) and Eftekharzadeh (1987). The natural head between the water surface of the reservoir and the outlet of the pipeline can be use as the driving force, eliminating the need for an external power input. An important aspect of removing sediment from a reservoir through a pipeline is to feed the pipeline with a sediment-water mixture of optimum concentration. Too high a concentration will result in reduced velocity and partial or total blocking of the pipeline, while too low a concentration will result in a low output and unnecessary use of water.

A technique called the Slotted Pipe Sediment Sluicer (SPSS) has been developed to facilitate suction of sediment-water mixture of the desired concentration into a pipeline. The idea was conceived and a simple laboratory model of the SPSS tested in July 1993. This and later laboratory experiments and a field experiment proved its efficiency at sluicing sediment into a pipeline at high concentrations, but without exceeding the transport capacity of the pipeline. A high degree of reliability was found as none of the several hundred experimental runs has resulted in total blocking of the pipeline.

4.2 Description The SPSS can be described as a pipe with a continuous, longitudinal slot or row of slots along its lower surface. It is fixed close to the original reservoir bed and connected to a pipe whose outlet is downstream of the dam, as shown in Figure 4-1. The upstream end is raised so that it is always higher than the sediment deposits. The SPSS is operated in two phases:

1. Sediment is allowed to deposit on top of the slotted pipe until the thickness of the sediment deposit is sufficient for flushing. Because the slots are on the bottom side sediment will not accumulate inside the pipe. Water can thus flow freely through the slotted pipe and out of the outlet pipe. 2. The valve on the outlet pipe is opened, and flushing of sediment starts. Water is drawn through the slots and picks up sediment close to where the slotted

49 4. The Slotted Pipe Sediment Sluicer

pipe emerges. As the sediment is sluiced the suction point moves downstream until all sediment that cover the slo tted pipe has been removed.

A balance between the suction capacity and the sediment transport capacity of the outlet pipe is achieved as an increase in sediment concentration in the outlet pipe reduces the velocity, which in turn will decrease the suction capacity. Likewise, a decrease in sediment concentration will increase the velocity which will produce an increase in suction capacity.

Figure 4-1: Sediment suction with the SPSS 1: Slotted Pipe 2: Suction point where a water and sediment mixture is drawn into slotted pipe 3: Outlet pipe 4: Sediment 5: Sediment sliding down to suction area 6: Removed sediment

4.3 Experiments with inflow through a slot

4.3.1 Introduction The functioning of the SPSS depends on the inflow pattern through the slot. The first laboratory experiments with suction of sand indicated that much of the sand and water entered the slotted pipe at the beginning of the slot. (The beginning of the slot is where the slotted pipe emerges from the sediment.) An experiment was therefore performed to determine the inflow pattern through a slot in the pipe.

50 4. The Slotted Pipe Sediment Sluicer

4.3.2 Theoretical considerations Consider a submerged pipe with an infinitely long slot in the bottom. The slotted pipe is connected to an outlet pipe which outlet is lower than the water surface above the slotted pipe. Water drawn into the slotted pipe flows through the slot and out through the outlet pipe. Initial experiments confirmed that the flow direction through the slot was perpendicular to the slotted pipe. Theoretical considerations have been made to predict the inflow through the slot, and equation 4-5 for velocity distribution and equation 4-6 for pressure distribution have been derived. An experiments has been performed to verify the equations obtained. The basic features of a slotted pipe are shown in Figure 4-2.

— a hB—1 Slot width x = 0 x

Figure 4-2: Sketch of flow through infinitely long slot into a pipe, with definitions: B: Slot width A: Cross sectional area x: Position along the pipe axis vp 0: Velocity in the pipe at x = 0 vp x: Velocity in the pipe at position x vs 0: Velocity through the slot at x = 0 vs x: Velocity through the slot at position x h 0: Pressure head difference across pipe wall at position x = 0 (m H20) h x: Pressure head difference across pipe wall at position x (m H20)

The velocity through the slot at position x is:

(4-1)

Ks entrance loss factor for slot, Ks = -1

51 4. The Slotted Pipe Sediment Sluicer

It is assumed that pressure head difference at any position x > 0 is a function of the velocity in the pipe, Vp x and entrance loss factor, Ks:

P.X (4-2) 2-g

Combining equation 4-1 and equation 4-2 yields:

V,.x =Vp,; (4-3)

The continuity is valid for the whole slot:

B-dx = A dvp, (^4)

Combining equation 4-3 and equation 4-4 yields a differential equation. Its solution gives the velocity both through the slot and in the slotted pipe as a function of the distance from the start of the slot:

—Bx v»,x =Vp,Q-e A (4-5)

The pressure head difference between the inside and outside the slotted pipe is proportional to the square of the velocity, so:

-2-B-xA ^s,x hs,o "e A ) (4-6)

4.3.3 Experimental setup The experiments were performed at the hydraulic laboratory of the Department of Civil and Environmental Engineering, Norwegian University of Science and Technology (NTNU). The data are recorded manually on forms made specially for the experiment. The data are treated and the graphs are created on Excel 5.0 worksheets.

EXPERIMENTAL APPARATUS A flume, 0.5 m wide, 0.6 m high and 11m long was used. The water level in the flume was kept at a constant level. An acrylic pipe, 1.50 m long and with an internal diameter of 56 mm was mounted inside the flume, with an unobstructed distance of more than 150 mm in all directions. The pipe was equipped with 100 mm long longitudinal slots, starting; 150 mm from the downstream end and

52 4. The Slotted Pipe Sediment Sluicer

separated by 17 mm long ribs. The width of the slots was adjustable from 5 to 31 mm. Thin plastic pipes were connected from the slotted pipe to a scale to allow monitoring of the pressure inside the pipe. A 5 m long 44 mm diameter acrylic pipe, with adjustable outlet elevation was connected to the slotted pipe. The experimental setup is shown in Figure 4-3.

Outlet pipe -i - Slotted pipe

100 40 60 100 200 A-A B-B C-C fl i-A li -B 1 6 ,-C II ot)0 56 LB : : LC :

------H------H------H- 100 17 100 17 100 17 Effective slot with -

Figure 4-3: Experimental apparatus for measurement of pressure head difference along a slotted pipe. All numbers are in mm.

EXPERIMENTAL PROCEDURE The experiments were performed by selecting a specific slot width. The flow through the slotted pipe was adjusted by adjusting the outlet elevation. The internal pressure in the slotted pipe was measured at six points along the slotted pipe by observing the water level in transparent plastic tubes attached to pressure taps on the slotted pipe. The flow, and thus velocity, was measured by the “volume - time method ”, explained in Appendix B.

53 4. The Slotted Pipe Sediment Sluicer

4.3.4 Experimental results DISTRIBUTION OF PRESSURE HEAD DIFFERENCE Experiments were performed on a 56 mm diameter slotted pipe with slot widths of 5, 7, 10, 12, 15, 20 and 31 mm. Each slot width was tested at three velocities. The pressure head difference was measured at x = 0, 40, 100, 200 and 400 mm along the slotted pipe, where x is the distance from the beginning of the slot. The total number of pressure measurements was thus 105. It should be noted that it was not the true piezometric head that was measured, because of the dynamic pressure from the flow through the slot. However, the measured pressure head difference was proportional to the square of the flow velocity, and no error was thus introduced.

Dimensionless pressure head difference, h ’ = h/h 0, and dimensionless distance from the beginning of the slot, x’ = x-B/A, were plotted against theoretical pressure head difference to verify equation 4-6. It can be shown that the theoretical dimensionless pressure head difference, h ’ = e'2x.

—Theoretical dimesionless 0.8 pressure head difference + Measured dimensionless 0.6 - pressure head difference

0.4 --

0.2 -

Dimensionless position, x1 = x-B/A

Figure 4-4: Measured dimensionless pressure head difference h ’ = h/h 0 in the slotted pipe at different dimensionless positions x’ = x-B/A. Theoretical pressure head difference is h ’ = e"2x.

54 4. The Slotted Pipe Sediment Sluicer

MEASUREMENT OF ENTRANCE LOSS FACTOR An ejector pump was used to increase the energy gradient in the outlet pipe for one third of the experiments. In these experiments the velocities were not measured because of the extra water introduced in the outlet pipe. For the remainder of the experiments, however, the entrance loss factor for the slotted pipe, Ks was measured. Entrance loss was found by measuring the pressure head difference 100 mm downstream of the slots on the slotted pipe and the discharge.

The measured entrance loss coefficients presented in Figure 4-5 have been corrected for the friction loss in the 100 mm long closed section of the pipe. It was found that the average entrance loss coefficient was 1.04. The results indicate a slight decline as slot width increases. This may be attributed to the increase in the ratio of slot width to pipe wall thickness, as the pipe wall itself was 3 mm thick.

1.2 : * >: ! 1.0 'o 1 0.8 0.6

0.4 ♦ Entrance loss measured at x = -100 8 (Corrected for pipe friction loss in the I 0.2 closed section of the pipe) C LU 0.0 , ...... ! ______0 5 10 15 20 25 30 35

Slot width (mm)

Figure 4-5: Entrance loss coefficients for slotted pipe when at x = -100 mm, and corrected for friction loss in the closed section of the pipe.

4.3.5 Discussion The average of the difference between theoretical and measured pressure head is 0.9, the standard deviation being 1.7 mm H20. These variations are well within what can be expected from visual readings of water levels in clear plastic tubes. Equation 4-6 is thus verified through the laboratory experiment, which implies that equation 4-5 is also correct. The equations explain the concentrated inflow of water, and thus the ability of the slotted pipe to sluice sediment.

55 4. The Slotted Pipe Sediment Sluicer

4.4 Laboratory experiments with suction of sand

4.4.1 Introduction In order to identify various factors important to the functioning of the SPSS a laboratory experiment was performed. The experimental setup is described in section 4.4.2.

Results from an experiment described in chapter 6 (Transport of sediment in pipes and flumes) are also presented. The purpose of this experiment was to compare transport of sediment in pipes and flumes. To allow full control of the flow of a sediment-water mixture through a pipe, an SPSS was used. The slotted pipe was equipped with a water inlet immediately downstream of the slot. The inflow of “extra” water through this inlet could be adjusted by a valve. The results are shown in Figure 4-13.

4.4.2 Experimental setup EXPERIMENTAL APPARATUS The same flume as described in section 4.3.3 was used for the experiments and the same acrylic slotted pipe with internal diameter of 56 mm was also used. In addition, one slotted pipe with a 44 mm internal diameter and one slotted pipe with a 71 mm internal diameter were used. All the slotted pipes had adjustable slot widths.

Outlet pipe - I- 1000 H - Slotted pipe Valve—j

100 17 100 17 Effective slot with

Figure 4-6: Apparatus for experiments with suction of sand with a SPSS.

56 4. The Slotted Pipe Sediment Sluicer

A total of 232 experimental runs were performed, combining different heads, slot widths and slotted pipe diameters. Most of these experiments were performed by Mohammed Magzoub, at the time a student on the M.Sc. Hydropower course at the Department of Hydraulic and Environmental Engineering at NTNU (Magzoub, 1995)

For all experiments a 5 m long acrylic pipe with internal diameter of 44 mm was used as an outlet pipe. The outlet pipe was equipped with 4 pressure taps, one metre apart, to measure the energy gradient in the outlet pipe. The total head between the water level in the flume and the lowest possible level of the outlet was approximately 1.2 m. The experimental apparatus is shown in Figure 4-6.

SEDIMENT PROPERTIES The sand had already been utilised in similar experiments. It is therefore unlikely that loss of fines throughout the experiments could cause a change in the sediment properties. The grain size distribution is shown in Figure 4-7. The unit weight of sand was found to be 2700 kg/m3.

Grain size (mm)

Figure 4-7: Grain size distribution for sand used in experiments with SPSS.

The flow was measured by the “volume-time method", energy gradient by the “pressure tap method ” and sediment concentration by the “constant volume - weight difference method". All methods are described in Appendix B. The outlet pipe was made of transparent acrylic plastic through which the kind of flow (i.e. deposition, sliding bed or heterogeneous transport) could easily be observed.

REPEATABILITY OF EXPERIMENTS Due to the nature of the experiments, there will be variations in the experimental results. The velocity and concentration will vary because the sediment slides

57 4. The Slotted Pipe Sediment Sluicer

unevenly down towards the suction area. The grain size distribution of the sediment must also be expected to vary slightly within space.

The repeatability of two experimental series was repeated, one with the 56 mm slotted pipe and the slot width set to 31 mm, and one with the 71 mm slotted pipe and the slot width set to 37 mm. Each series consisted of eight experimental runs with different energy gradients and sediment concentrations, as shown in Figure 4-8. The standard deviations and average differences (measured as per cent) are shown in table 4-1.

Table 4-1: Average difference and standard deviation when two experiments are repeated. All values are per cent. Measured variable 56 mm 71 mm Combined slotted pipe slotted pipe Energy gradient Av. diff. -0.5 -0.6 -0.5 Std. dev. 6.1 2.4 4.6 Velocity Av. diff. 4.5 1.4 3.0 Std. dev. 4.3 1.9 3.6 Concentration Av. diff. 3.0 2.4 2.7 Std. dev. 13.1 3.7 9.6

4.4.3 Experimental procedure Approximately 300 kg of sand was used. The SSPS was covered with 3 - 400 mm of sand before the experiments started, leaving only the upstream end clear. One slotted pipe was tested at a time. The desired slot width was selected and the energy gradient was set by positioning the outlet at a fixed elevation. The downstream valve was opened, and once the flow had stabilised a sample was collected and the energy gradient was recorded. When the energy gradient had been adjusted a new sample was collected and the energy gradient was recorded once again. Once all the energy gradients had been tested (one series) the slot width was changed, the sand recycled and the procedure repeated. A total of 232 experimental points were recorded. Three pipe diameters (44, 56 and 71 mm) were tested, each with five different slot widths. In each series, eighth different energy gradients, ranging from 3% to a maximum of 14 % were tested. Some of the experimental series were also repeated.

58 4. The Slotted Pipe Sediment Sluicer

4.4.4 Experimental results Energy gradient, pipe diameter and slot width were varied to study the following: • Sediment concentration by volume, Cv. • Velocity in the outlet pipe. • Kind of flow. At low velocities there will be a stationary bed of sediment in the outlet pipe (flow with bed). At high velocities all sediment will be in suspension; this is called heterogeneous flow. For some of the experiments the transition between flow with bed and heterogeneous flow was observed as flow with a sliding, compact bed layer.

ENERGY GRADIENT The energy gradient in the outlet pipe was found to have a major influence on the sediment concentration that could be sluiced. A smaller diameter slotted pipe gave a somewhat higher concentration. It can be seen from Figure 4-8 that the flow had a stationary bed for a slotted pipe diameter of 44 mm and for the 56 mm slotted pipe when the energy gradient is less than 0.09.

* 44 mm slotted pipe, flow with bed □ O #56 mm slotted pipe, flow with bed n □ 56 mm slotted pipe, heterogenous flow □ E A 71 mm slotted pipe, heterogenous flow > 0.06

I 0.04 ♦

8 002 ♦ 0 0 0.025 0.05 0.075 0.1 0.125 0.15

Energy gradient in outlet pipe (m water per m)

Figure 4-8: Sediment concentration plotted against energy gradient in the outlet pipe. From experiments where medium sand (d50 = 0,6 mm) is sluiced with different slotted pipes and transported through a 44 mm outlet pipe. Ratios of slot width to slotted pipe diameter are between 0.52 and 0.57.

The rate of sediment transport is found to be even more dependent on the energy gradient than the concentration, as the velocity increases with energy gradient as well. The rate of sediment transport as a function of energy gradient is shown in Figure 4-9.

59 4. The Slotted Pipe Sediment Sluicer

800 ♦ 44 mm slotted pipe, flow with bed a 700 ■ 56 mm slotted pipe, flow with bed a 600 □ 56 mm slotted pipe, heterogenous flow a Ao 500 a 71 mm slotted pipe, heterogenous flow 4b 400 E € °0 300 i k 1 200 4 ■f 100 A# ", I- 0 0 0.025 0.05 0.075 0.1 0.125 0.15

Energy gradient in outlet pipe (m water per m)

Figure 4-9: Rate of sediment transport plotted against energy gradient in the outlet pipe.

VELOCITY IN THE SLOTTED PIPE The sluiced sediment concentration can be plotted against the velocity in the slotted pipe. The velocity is the average velocity calculated from the flow and the slotted pipe cross-section. The real velocity was higher when some of the slotted pipe was filled with stationary sediment that reduced the cross-section.

<5 o Slotted pipe diameter = 44 ■ I ■ Slotted pipe diameter = 56 ■ 1 1 A Slotted pipe diameter = 71 0.06 0 H 0.04 f**

0.02 *-v <

0.20 0.40 0.60 0.80 1.00

Velocity in slotted pipe (m/s)

Figure 4-10: Dependence of velocity in slotted pipe and sluiced sediment concentration

It is interesting to notice that for energy gradients between 0.05 and 0.12, the highest concentrations were obtained using the 44 mm slotted pipe, whereas the highest outputs in terms of kg/hour were obtained with the 71 mm slotted pipe. This is because the velocity is significantly higher when using the 71 mm slotted pipe. In Figure 4-11 the velocity is plotted against energy gradient measured for the different slotted pipe diameters. It was found that the velocity in the outlet pipe varied significantly with slotted pipe diameter.

60 4. The Slotted Pipe Sediment Sluicer

* 44 mm slotted pipe, flow with bed _ ■ 56 mm slotted pipe, flow with bed □ 56 mm slotted pipe, heterogenous flow /A a 71 mm slotted pipe, heterogenous flow A % ^ t o

& D S

♦ •

♦ *

0 0.05 0.1 0.15 Energy gradient in outlet pipe

Figure 4-11: Effect of slotted pipe diameter on velocity in outlet pipe. The ratio of slot width to slotted pipe diameter is between 0.52 and 0.57.

SLOT WIDTH

♦

* a

E *" n c ° *1 ■ s . ■ ■A 2 " § L& A 8 A » D=4 4, flow with Ded 6 ■ D=£6, flow with sed t □ D=56, heterogenous flow 8 A D=71, heterogenous flow

Dimensionless slot width, B/D

Figure 4-12: Effect of varying slot width. From experiments with energy gradients between 0.08 and 0.10.

The experiments where energy gradient were between 0.08 and 0.10 have been studied. The measured sediment concentrations are plotted against relative slot width, B/D, as shown in Figure 4-12. The general trend is for sediment concentration to increase with increasing slot width. For the 56 mm slotted pipe one can see that sediment concentration is lower when there is flow width stationary bed in the outlet pipe.

61 4. The Slotted Pipe Sediment Sluicer

INLET OF “EXTRA WATER” DOWNSTREAM OF SLOT The following results are from an experiment where a coarse sand (d50 =1.2 mm) was sluiced with a 75 mm SPSS into a 60 mm pipe (see Chapter 6). In order to allow control of the sediment concentration a water inlet was fitted immediately downstream of the slot. The inlet was equipped with a valve, so the inflow of extra water could be adjusted. This proved to be an efficient method for control of the sediment suction capacity. When the valve was opened extra water entered the slotted pipe. This both reduced the suction of sediment and diluted the sediment-water mixture, thus reducing the sediment concentration.

1.6 ir

;* Velocity in outlet pipe ii Concentration- flow with bed > Concentration- sliding bed a Concentration- heterogenous flow

Opening for extra water (% of fully open valve)

Figure 4-13: Measured concentration and velocity in the 60 mm outlet pipe when an inlet for extra water immediately downstream of the slot is used.

4.4.5 Discussion It has been shown in section 4.3 that the inflow of water and the pressure head difference are concentrated within a short section of the slot immediately upstream of where the slot starts (x = 0). When a part of the slotted pipe is covered with sediment, the starting point of the slot is where the slotted pipe emerges from the sediment. Water that is drawn into the slotted pipe picks up sediment and new sediment slides down towards the suction area. As sediment is removed the starting point of the slot, and thus the suction area, moves downstream until all sediment covering the slotted pipe are removed.

62 4. The Slotted Pipe Sediment Sluicer

The flow stabilises at a certain concentration because of the feedback mechanism where an increase in concentration produces higher flow resistance in the outlet pipe, lower velocity and thus reduced sediment suction. This ensures that the sluiced concentration is nearly constant and that the outlet pipe will not block. The sluiced concentration depends on five factors:

1. The energy gradient in the outlet pipe: An increase in the energy gradient will cause an increase in sluiced concentration, as shown in Figure 4-8. 2. The ratio of slotted pipe diameter to outlet pipe diameter: A slotted pipe with a large diameter compared to that of the outlet pipe will sluice relatively low concentrations because the velocity in the slotted pipe is lower than the velocity in the outlet pipe. The velocity in the outlet pipe is relatively high because of the low sediment concentration. However, for a number of experiments the total output in terms of kg-hour' 1 was found to be highest for the 71 mm slotted pipe, whereas the concentration was highest for the 44 mm slotted pipe. Experimental results are shown in Figure 4-8, 4-9 and 4-11. 3. Width of the slots in the slotted pipe: The slot width seems to be of some importance, probably because the suction area is shorter and more concentrated when the slot is wide. The highest effect is measured for the 71 mm slotted pipe. Experimental results are shown in Figure 4-12. 4. Inlet of extra water downstream of the slots: An inlet allowing extra water to enter downstream of the slots can be used to reduce suction capacity, and thus obtain sufficient velocity in the outlet pipe. Experimental results are shown in Figure 4-13. 5. Sediment properties: No experiment was performed to directly compare the effect of changing sediment properties. However, it has been shown that a sediment concentration equal to the maximum transport capacity of the outlet pipe can be sluiced. Fine sediment is generally easier to transport in a pipe than coarse. It is therefore most likely that an SPSS can sluice fine sediment at a higher concentration than coarse sediment if all other variables are equal. A field experiment will be described in section 4.5.5. It shows that the SPSS was able to sluice fine sand (d50 = 0.12 mm) at a concentration of 10 % by volume when the energy gradient in the 125 mm pipe was less than 3 %. Transport of sediment in pipes is further described in Chapter 6.

63 4. The Slotted Pipe Sediment Sluicer

A number of questions remain to be studied. In some of the experiments it was observed that the sediment was drawn into the slotted pipe at the very downstream end of the slot, while the sediment covering the upstream section of the slotted pipe remained in place. It therefore seems obvious that the sediment deposits that overlie the slotted pipe must be of a certain thickness. There are indications that this thickness needs to be more than the pressure head difference (measured as height of H20), but this was not studied in detail. Another question of interest is the possibility of sediment being forced through the slot by the surrounding pressure, and thus clogging up the SPSS while it is not in operation. The question is discussed briefly, and it was suggested that this is unlikely (pers. comm, Department of Geotechnical Engineering, NTNU, 1995). However, no thorough study has been made so far. It is also important to note that the experiments described in section 4.4 is performed with medium to coarse sand, and only with 44 and 60 mm outlet pipes. Experiments with SPSS of other sizes and with different sediment is likely to provide additional information.

4.5 Field experiments

4.5.1 Location Experiments were performed at Jhimruk Hydropower plant in Nepal during the monsoon season in 1994. Jhimruk Hydropower plant is situated in the Middle mountains in Western Nepal, about 200 km west of Kathmandu, the capital of Nepal. Jhimruk Khola tends to meander in the relatively wide valley of Jhimruk. The river slopes approximately 1:150 on a river bed of alluvial deposits dominated by silt, gravel and cobbles. The power plant, commissioned in 1994, exploits the head between the two rivers Jhimruk Khola and Mardi Khola. The plant is a run-of-he-river plant with a small intake reservoir. Jhimruk Khola has a flow that varies widely with the seasons, and for many days each year the flow is less than the design discharge. Storing water for production during peak hours is therefore an interesting option. The dam creating the reservoir is 200 m long and 2.5 m high. Much of the reservoir is filled with sediment, mostly silt and fine sand. A peak volume of 80,000 m3 is obtained in the dry season by installing flash boards. Jhimruk Hydropower Plant has been described by Stple (1993).

64 4. The Slotted Pipe Sediment Sluicer

Table 4-2: Specifications of Jhimruk hydropower plant JHIMRUK KHOLA: Catchment area 645 km2 Long-term average flow 25,3 mV Estimated minimum daily flow, (T=100 years) 0.44 mV1 Design flood (T = 1000 years) 1800 mV1 Estimated annual sediment transport 1.6 * 106t-yr -1 DAM: Dam height 2.5 m Dam length 255 m Crest level 738.0 masl Min. Z max. reservoir level, with flashboards 737.5 - 738.8 masl Intended reservoir volume 100,800 m3 (4 hr full load) Desander Serpent Sediment Sluicing System POWER PLANT: Design Discharge 7 mV1 Headrace tunnel 1,050 m, 5.5 m2 Inclined underground penstock 380 m Head 205 m Installed capacity 12 MW

Figure 4-14: The intake at Jhimruk Hydropower Plant. The area of experiments with the SPSS is marked with a white circle. In the foreground one can see the desilting basins equipped with the Serpent Sediment Sluicing System.

65 4. The Slotted Pipe Sediment Sluicer

An area close to the dam crest was chosen for the field tests. Mapping of the area revealed deposits of fine sand and sill: with thickness ranging from zero to a little more than one metre in thickness. Th e sediment was slightly cohesive and fairly well compacted because of repeated impounding and drawdown during the testing and commissioning of the power plant. Underlying layers of gravel and stones that could not be penetrated by a steel rod indicated the thickness of the fine sediment.

4.5.2 Experimental setup The location was ideal for experiments of this kind as they were performed during the testing and commissioning of the power plant. As a consequence the water level could be adjusted on request, allowing both survey and equipment to be installed while the water level was down.

5.85 - 30/45

Figure 4-15 Experimental setup for field experiments with the SPSS at Jhimruk Hydropower Plant in Nepal. 1: SPSS 4: Sediment deposits 2: Outlet pipe 5: Removed sediment 3: Dam 6: Original reservoir bed

An area with sediment deposits more one metre in thickness was chosen for the experiment. A trench, 1.0 m deep and 9 m long, was excavated in which the SPSS was installed. After installation the trench was filled with the excavated material so that the whole of the slotted pipe was covered with sediment, except for the upstream end. After impounding of the peaking reservoir the sediment were left to consolidate for 24 hours. The setup of the field experiment is shown in Figure 4-15.

66 4. The Slotted Pipe Sediment Sluicer

The SPSS used was made at the site from HD-PE (High density polyethylene) pipe. The parts were cut and shaped with hand tools and welded together in a simple way: a steel plate heated on a kerosene stove was used to melt the pipe flanges before they were joined. The joints endured considerable strain during transport without showing any sign of weakness. The total length of the slotted pipe was 8 m, the inner diameter 150 mm and the slot width 30 mm. At the downstream end a conical contraction joined a short 110 mm inner diameter pipe to the slotted pipe. The downstream (110 mm) end of the slotted pipe was connected to a 30 or 45 m long, 125 mm inner diameter flexible pipe with its outlet downstream of the dam. The flexible pipe passed the dam through a hole in a stoplog. The flexible pipe was commissioned from India, and was of the type normally used for pumping up irrigation water from rivers. The total head from water surface to outlet of the pipe was limited to 2.0 - 2.1 m.

4.5.3 Sediment properties The sediment was mostly fine sand and silt, but also included occasional stones up to the size of small potatoes. Grain size distribution is shown in Figure 4-16.

Grain size (mm)

Figure 4-16: Grain size distribution of sediment sluiced with the SPSS in the field experiment. Some small stones up to the size of small potatoes were also sluiced.

4.5.4 Experimental procedure The 125 mm flexible pipe was not equipped with a valve, so prior to the experiment the outlet was elevated above the water level of the intake pond to prevent water from flowing through the system. Sluicing was started simply by lowering the outlet to a level approximately 2 m below the water level of the intake pond. The natural head then forced water and sediment into the slotted pipe and out of the flexible pipe.

67 4. The Slotted Pipe Sediment Sluicer

FIRST EXPERIMENT The first experiment was conducted on 4 August 1994 using a 30 m long flexible pipe. No velocities were measured during this experiment. Three samples were collected in buckets, and the volumes of each sample and of the sediment were recorded. Towards the end of the experimental run the flow decreased suddenly, leaving only a trickle of relatively clear water flowing. It turned out that part of the flexible pipe had collapsed, leaving a very small opening through which the water could flow. Inspection revealed that both the slotted pipe and the flexible pipe had been totally cleaned of sediment during the low flow of water.

SECOND EXPERIMENT Before the second experiment the sand deposits above the SPSS were surveyed. The survey was repeated after the experiment so that the volume removed could be calculated. Velocities in the outlet pipe were measured during the run, by inserting an otmeter into the outlet of the flexible pipe. Although this is an inaccurate method it provided valuable information on the velocities in the pipe. The temporal changes throughout the experiments and the differences between clear water flow and flow with sediment-water mixtures could be measured.

Samples were collected in buckets throughout the experiment. Concentrations were measured by weighing. The sediment deposits were surveyed before and after sluicing in order to obtain the total amount of sediment deposits removed.

4.5.5 Results The results of the two experimental runs can be summarised as follow:

1. During the two experiments no clogging occurred, and stones small enough to pass the slots were sluiced without any problems. 2. The sluicing lasted for 26 minutes and approximately 7 m3 of sediment deposits were sluiced in both experiments. This gives a capacity of 16 m3 of sediment deposits per hour. 3. Average concentration Cv, for both experiments was measured at approximately 10 %.

Velocity in the outlet pipe was measured at between 1.7 and 1.9 ms"1. Measurements were made of flow with clear water in the flexible pipe, both with and without the Slotted Pipe Sediment Sluicer. The entrance loss factor was found to be 3.5, including the one metre long section with an inner diameter of

68 4. The Slotted Pipe Sediment Sluicer

110 mm. On the basis of these experiments the energy gradient in the outlet pipe was found to be 2.6 - 3.0 % for the flow of the sediment-water mixture.

Table 4-3: Results from the second field experiment with the SPSS.

FIRST EXPERIMENT (30 m pipe)

Head Concentration 1.70 0.109

SECOND EXPERIMENT (45 m pipe) Minutes Sediment Energy from start Head Velocity concentration gradient 0 2.10 4 2.07 1.77 5 2.06 0.062 0.030 10 2.03 1.74 12 2.01 0.100 0.030 14 2.00

20 1.98 1^8 22 1.97 0.107 0.026 26 1.95 Average, second exp. 2.02 1.80 0.090 0.028

69 4. The Slotted Pipe Sediment Sluicer

Figure 4-17: SPSS before the second field experiment. During the experiment the water level was approximately 0.5 m above the sediment.

Figure 4-18: After the second field experiment in which 7 m3 of sediment were removed in 26 minutes.

70 4. The Slotted Pipe Sediment Sluicer

0 sz

0

-0.5

1 2 3 4 5 6 L J l I L L Distance from dam axis (m)

Figure 4-19: Cross-sections before and after sluicing. The cross-sections are three m apart, the uppermost at the upstream end of the horizontal part of the SPSS.

4.5.6 Discussion The field experiment proved the SPSS’s ability to function under realistic conditions. It is worth noticing that the total head between the water surface and outlet of the flexible pipe was only 2.1 m, and that the energy gradient in the pipe was therefore as low as 3 % or less.

During the experiments it was observed that cohesive forces in the sediment deposits caused sediment to slide down to the suction area at a lower rate than desired. Some time after sluicing had finished it was observed that sediment was covering the slotted pipe to a thickness of approximately 20 centimetres. It is believed that the SPSS would have functioned even better if sediment deposits above had been thicker. The suction point would then have moved more slowly along the slotted pipe, allowing more time for sediment to slide down to the suction area.

71 4. The Slotted Pipe Sediment Sluicer

4.6 Conclusions A technique that permits controlled suction of sediment and water into a pipe, the Slotted Pipe Sediment Sluicer (SPSS) has been developed. It has been shown that the inflow of water through a slot in a pipe is concentrated at a short section of the slot, and Equations 4-5 for velocity distribution and Equation 4-6 for pressure head difference distribution has been derived and verified experimentally. Laboratory experiments have shown that this principle can be used in the SPSS to draw sediment into a pipe at a concentration equivalent to the sediment transport capacity of the pipe. From the laboratory experiments it was found that the suction capacity of the SPSS can be controlled by three factors: 1. The diameter of The slotted pipe relative to the diameter of the outlet pipe. 2. An opening in the suction head immediately before the connection to the outlet pipe, allowing inflow of "extra" water. 3. To a certain degree, the width of the bottom slots. By varying these factors the suction capacity can be adjusted to obtain optimum transport conditions in the outlet pipe.

The SPSS is fixed close to the original reservoir bed and is therefore suitable for preserving reservoir capacity. Both the laboratory experiments and the successful field experiments at Jhimruk Hydropower plant in Nepal indicate that the SPSS can meet the requirements listed below:

1. Sluicing of sediment should be possible without interrupting water supply from the reservoir. 2. The technique should be simple in implementation and operation, and can be operated by non-technical staff after a short period of training. The chances of maloperation causing severe problems as clogging of the pipeline seem very small. 3. A minimum of water should be required for the transport of sediment out of the reservoir, and the necessary investment low. 4. It should be possible to operate the: system without input of external energy if the head between the water surface and the outlet is sufficient. 5. It should be possible to use sediment for construction, for land reclamation, as fertiliser in irrigation water or for regaining the natural sediment regime in the river.

Sediment is released from a pipeline and can therefore be used for construction, irrigation, land reclamation or for regaining the natural sediment regime in the river.

72 5. The saxophone Sediment Sluicer

5. THE SAXOPHONE SEDIMENT SLUICER

5.1 Introduction Sediment can be removed from a reservoir by hydraulic transport through a pipeline. Examples of this are provided by Bruk, (1985), and studies include those of Hotchkiss and Huang (1995) and Eftekharzadeh (1987). The natural head between the water surface of the reservoir and the outlet of the pipeline can be use as the driving force, thus excluding the need for any external power input. A major aspect in removing sediment from a reservoir through a pipeline is to feed the pipeline with a sediment-water mixture of optimum concentration. A too high concentration will result in reduced velocity and partial or total blocking of the pipeline. A too low concentration will produce a low output and unnecessary use of water.

This chapter describes a technique called the Saxophone Sediment Sluicer (SSS). As the SSS sluices sediment from the surface of the deposits in a reservoir it can be used to regain lost reservoir capacity as well as to maintain reservoirs subject to sedimentation. The two main features of the SSS are: 1. Sediment can be removed without lowering the water level or interrupting the water supply from the reservoir. 2. The energy head between the water surface and the outlet is the driving force, eliminating the necessity for an external source of power. The SSS was developed to facilitate the suction of sediment-water mixture with the desired concentration into a pipeline. The first laboratory model was tested in September 1993, shortly after the idea was conceived. A laboratory experiment intended to map factors affecting the suction capacity of the SSS was subsequently performed. It gave answers to several questions, not least that none of the experiments resulted in blocking of the outlet pipe. Two field experiments in Nepal are described here. These proved the efficiency of the SSS in sluicing sediment under realistic conditions, and during the five days of the final experiment the SSS was operated entirely by local staff. The last part of this chapter describes how the SSS was tested and used to remove stones covering seabed structures on an oil-field in the North Sea. The maximum size of the stones removed was greater than 150 mm.

73 5. The saxophone Sediment Sluicer

5.2 Description The SSS consists of a saxophone shaped suction head (for short the suction head) mounted on a pipeline. The outlet of the pipeline is downstream of the reservoir. The head of water can therefore be the driving force, causing the sediment-water mixture to flow through the pipeline, and excluding the necessity of pumping equipment. It is operated from the water surface, for example a raft. The suction head will stand on the sediment deposits by its own weight. Due its design a sediment-water mixture whose concentration corresponds to the transporting capacity of the pipeline will be sluiced. No monitoring or continuous manoeuvring are thus necessary in order to obtain suction of sediment. The operation of the SSS is therefore very simple and can be described as follows: 1. The suction head is placed on the sediment deposits where sediment is to be removed. 2. The valve on the pipeline is opened, and flushing of sediment starts. A sediment water mixture is drawn through the slots and into the pipeline through which it is transported out of the reservoir. 3. When the crater formed has the desired depth, the SSS is shifted to another location and sluicing continues. The procedure is repeated until the desired amount of sediment is removed. A balance between the suction capacity and the sediment transport capacity of the outlet pipe is obtained. An increase in sediment concentration in the outlet pipe reduces the flow velocity, which in turn results in a decrease in the suction capacity. Likewise, a decrease in sediment concentration produces an increase in velocity which increases the suction capacity.

As the name indicates, this suction head looks something like a saxophone. The main feature of the suction head is that it draws water from two places. At the bottom is a row of slots, called the “bottom slots”. During normal operation most of the water and all the sediment are drawn through the bottom slots. The upper opening will always be above the sediment deposits. In the event of sediment slides covering the bottom slots, “balancing ” water will be drawn from the upper opening and prevent blocking of the pipeline. Due to the lower pressure inside the suction head sediment will still be drawn from the bottom slots, which eventually will be reopened, and normal suction will resume as shown in Figure 5-1. Because of the length of the inclined bottom part the suction head is not sucked down into soft sediment deposits. Suction only takes place over a part of the inclined bottom part, allowing the suction head to rest on the deposits.

74 5. The saxophone Sediment Sluicer

Figure 5-1: Three modes of operation: A Normal operation B Bottom slots are covered with sediment C Reopening of bottom slots

1: Outlet pipe 4: Flow of “balancing ” 2: “Saxophone ” suction head 3: Bottom slots 5: Opening for “extra” water 6: Sediment deposits

5.3 Laboratory experiments

5.3.1 Introduction To determine factors important to the functioning of the SSS a laboratory experiment was performed. The experiments were performed at the hydraulic laboratory at the Division of Civil and Environmental Engineering at SINTEF (The Foundation for Scientific and Industrial Research, Trondheim, Norway). The data were recorded manually.

5.3.2 Experimental setup EXPERIMENTAL APPARATUS A tank, 1.0 m wide, 1.2 m long and 1.5 m high was used for the experiments. One side of the tank was transparent so the suction of sediment could be observed. The tank was raised, with the water surface 3.2 m above floor level. The saxophone suction head was made of transparent acrylic pipe and it was possible to adjust the width of the bottom slots. The suction head was connected to the outlet pipe through a flexible pipe. The outlet pipe was a transparent acrylic pipe so the flow of sediment could be observed. The outlet pipe was horizontal and

75 5. The saxophone Sediment Sluicer

was either 10 m long or consisted of two 10 m parts connected by a flexible pipe. The sediment-water mixture was discharged into a basin of approximately 2 m3. When all the sediment in the tank had been used the basin was drained and the sand mixed to achieve a homogeneous grain size distribution before it was moved back into the tank. The test rig, equipped with a 20 m long outlet pipe, is shown in Figure 5-2.

■60/70/80

Figure 5-2: Test rig for laboratory experiments with a 2x10 m outlet pipe.

EXPERIMENTAL PROCEDURE For each experimental run the suction head with the desired settings was placed in the tank. The valve on the outlet pipe was opened and suction was allowed to take place for some time, so that a s able sluicing condition was obtained. Each experimental run lasted for 10 minutes. Once a minute the flow was read, and 5- 7 litres of sediment water mixture was collected and poured into a 70 litre bucket. Each run thus resulted in 10 flow readings and a 50 - 70 litre sample of the sediment water mixture. Forms designed especially for the experiments were used. Data were treated and graphs are created on Excel 5.0 worksheets.

The flow, and thus velocity in the pipe, is measured by an electromagnetic flowmeter, energy gradient by the “pressure tap method ” and sediment concentration by the “constant volume - weight difference method ”. These methods are described in Appendix B. The outlet pipe is made of acrylic plastic and is therefore transparent. The kind of flow (i.e. deposition, sliding bed or heterogeneous transport) could easily be observed.

76 5. The saxophone Sediment Sluicer

THE SEDIMENT The sediment used for a majority of the experiments was a natural sand of alluvial origin. Approximately two tonnes of sand were sieved to achieve a maximum grain size of 7 mm. The median grain size, d50 of the sand was 1.17 mm. The average shape factor, Fs for 18 particles ranging from 3.3 - 7.25 mm was 0.56. Shape factor is defined in appendix B.

The sand was also washed so that very little fines were left. (The fines in this case are particles that do not settle in the 2 m3 collecting tank.) Changes in sediment properties due to washing out of fines are therefore believed to be very slight, although the sand was used several times.

Grain size (mm)

Figure 5-3: Grain size distribution of coarse sediment.

A finer sand was also used for some of the experiments. This sand had a maximum grain size of 1.4 mm and d50 of 0.7 mm.

Grain size (mm)

Figure 5-4: Grain size distribution of fine sediment.

77 5. The saxophone Sediment Sluicer

5.3.3 Initial experiments with transport in a pipe Initial tests were performed to find the conditions for sediment transport in the outlet pipe used in the experiments. The objective was to find the rate of transport at different velocities and gradients. This experiment is part of an experiment which is fully described in chapter 6, and which was performed in order to compare flow in a pipe and an open channel.

At each of the energy gradients 3, 4.5, 6 and 7.5 % several combinations of velocity and concentrations were measured. As expected, it was found that low velocities resulted in deposition in the pipe, whereas at higher velocities all the sediment moved in suspension. In between there is a transition zone with a sliding bed in the pipeline. At low energy gradients the highest concentration is obtained with low velocities and deposition in the pipeline. At higher gradients the highest concentration is obtained with velocities in the transition zone. Transport with a stationary bed, however, is unstable, and it is therefore believed that the optimum transport condition for all gradients studied is transport with a sliding bed. With an energy gradient of 5 % it was found that a velocity of 1.5 m-s'1 gave the best transport conditions in the outlet pipe.

0.030

i = 7.5 % _____ ■ ■ B ** — 0.025 0 ■ o A isrfi.O % 0.020 6

o 0.015 % A 3 i = 4.5 % S* A

0.010 e « * o 1 = 3.0% o slat, bed 0.005 ■ sliding bed 6 het. flow 0.000 0.0 0.5 1.0 1.5 2.0 2.5

Velocity in pipe

Figure 5-5: Sediment concentrations in a pipeline at different gradients and velocities. Sediment with d50 =1.2 mm is transported in a 60 mm pipe.

78 5. The saxophone Sediment Sluicer

2.0 o SSS; stationary bed 1.8 ■ SSS; sliding bed a SSS; het. flow 1-6 * Opt vel; fig 5.6 !------K ------Optimum velocity 3- 1.4 4*dB o

§ > Y > 1.2 o

1.0 X*

0.8 0 0.02 0.04 0.06 0.08

Energy gradient in pipe (m water / m)

Figure 5-6: Optimum velocity as a function of energy gradient as found from Figure 5-5. Data from experiments with SSS are included for comparison.

5.3.4 Experimental results ENERGY GRADIENT As for the Slotted Pipe Sediment Sluicer (SPSS) the SSS will adjust its suction of sediment to the transport capacity of the outlet pipe. The SPSS is described in Chapter 4. Experimental results where the same saxophone suction head was tested with different energy gradients in the outlet pipe are shown in Figure 5-7.

0.015

0.010

0.005

o.ooo

Energy gradient in outlet pipe

Figure 5-7: Sediment concentration sluiced at different energy gradients in a outlet pipe. A 60 mm Suction head is used.

79 5. The saxophone Sediment Sluicer

STABILITY OF FLOW When the sediment was transported at low velocities in the outlet pipe a stationary bed was formed. The flow also became more unstable with fluctuating velocities and sediment concentrations. As each experiment consisted of 10 velocity measurements it was possible to calculate the sample standard deviation. These are shown in Figure 5-8, plotted against the velocity in the outlet pipe. A distinction is made between flow with stationary bed and heterogeneous flow, and as expected it was found that the standard deviation was higher for flow with a stationary bed. A distinction is also made between experiments with the coarse sand (dmax = 7 mm) and medium sand (dmax =1.4 mm), and it is seen that velocity fluctuations are smaller when the medium sand is transported.

0.5 •! *het, 1.2 mm .5 0.4 ■ het,0.6mm I A a bed, 1.2 mm -g 0.3 □ bed, 0.6 mm i I 0-2 >> o 0.1 -d*- > 0 1.20 1.40 1.60 1.80 Average velocity in outlet pipe

Figure 5-8: Standard deviation for velocity measurements plotted against velocity in the outlet pipe.

5.3.5 Optimisation of suction capacity The average maximum sediment concentration that can be sluiced with a SSS can never exceed the transport capacity of the outlet pipe. The maximum concentration that can be transported i n a pipe depends on a number of factors: 1. Sediment properties (grain size, grain shape and unit weight) 2. properties of transporting fluid 3. Pipe (diameter, shape, and roughness and inclination) 4. Energy gradient in pipe The SSS can be operated at different heads and sluice different kinds of sediment without being modified, and still work satisfactorily. Initial experiments confirmed that a wide range of designs can be used, and that blocking of the

80 5. The saxophone Sediment Sluicer

pipeline will in no case take place. However, it is desirable to optimise suction capacity so that a maximum of sediment can be sluiced with a minimum of water. The ideal suction capacity is obtained when the optimum transport velocity in the pipeline is obtained, as explained in section 5.3.3. The purpose of this experiment was to find how the suction head can be designed so that suction capacity matches the sediment transport capacity of the outlet pipe. It was believed that the suction capacity of the saxophone suction head was influenced by four factors: 1. The diameter of suction head compared to the diameter of the outlet pipe. 2. An opening in the suction head immediately before the connection to the outlet pipe, allowing inflow of “extra” water. 3. The width of the bottom slots. 4. Shape of suction head.

SUCTION HEAD DIAMETER AND OPENING FOR “EXTRA” WATER Experiments were performed with saxophone suction heads with inner diameters of 60, 70 and 80 mm. The saxophone suction heads had openings for “extra” water that could be adjusted from 0 - 75 % of the cross section area of the saxophone. These experiments revealed that both ways are efficient in achieving a suction capacity corresponding to the sediment transport capacity of the outlet pipe. Experimental results are shown in Figure 5-9.

Velocity with clear water

1.80 -

1.60 Q

1.40 -

1.20 - ♦ 60 mm saxophone

1.00 - □ 70 mm saxophone g80 mm saxophone

Opening for "false" water, as % of saxophone cross section

Figure 5-9: Experimental results, energy gradient = 0.045 - 0.052. Suction capacity of the SSS can be adjusted in two different ways: 1. By varying the diameter of the suction head 2. By changing the area through which extra water can enter the suction head

81 5. The saxophone Sediment Sluicer

SLOT WIDTH An experiment was performed with an 80 mm suction head in which the slot width was varied between 5 and 65 mm. The experiments were performed using medium sand, d50 = 0.7 mm. This experiment shows that the suction capacity is influenced only when slot width is reduced to less than 20 mm.

2.0

* o * ► E 1.5 0

Figure 5-10: Effect of varying the slot: width of the saxophone.

It is thus found that the suction capacity of the saxophone suction head is influenced by three factors: 1. A larger suction head diameter will result in a relatively lower velocity in the suction head, and thus lower suction capacity. 2. An opening in the suction head immediately before the connection to the outlet pipe, allowing inflow of “extra” water, will reduce the flow and thus the velocity in the suction head. In addition to reduced suction capacity the sediment-water mixture will be further diluted by the extra water. 3. The width of the bottom slots may have some influence on suction capacity as narrow slots will force suction to take part over a longer stretch of the bottom slots. This is likely to reduce suction capacity.

Some initial experiments with different suction head shapes indicated that various designs can be used successfully. The present design was chosen because it is believed that the inclined bottom part will prevent the suction head from burying into soft sediment deposits. It is argued that a longer inclined bottom section will reduce the possibility of suction taking place over the whole length, thus allowing a part of saxophone suction head to rest on the sediment deposits. However, as soft sediment such as silt could not be used in the experiments (due to lack of desilting facilities) this could not be studied further.

82 5. The saxophone Sediment Sluicer

5.4 Field experiments in Nepal

5.4.1 Introduction Field experiments were performed in August 1994 and in June 1995 at Jhimruk Hydropower plant. The plant is situated in the Middle Mountains in Western Nepal, about 200 km west of Kathmandu. Jhimruk Khola tends to meander in the relatively wide valley of Jhimruk. The river slopes approximately 1:150 on a river bed of alluvial deposits dominated by silt, gravel and cobble, and carries an estimated 1.6 million tonnes of sediment annually. The plant is a run-of-the-river- plant with a small reservoir, formed by a 2.5 m high and 250 m long dam. A more detailed description of the river and the power plant is provided in chapter 4.

Figure 5-11: The dam and intake arrangements. The area where experiments were performed is marked with a white circle.

5.4.2 Experimental setup TEST AREA An area close to the dam crest was chosen for the field tests. Mapping of the area (Figure 5-12) revealed deposits of fine sand and silt ranging from zero to a little more than one metre thick. The sediment was slightly cohesive and fairly well

83 5. The saxophone Sediment Sluicer

compacted because of repeated impounding and drawndown during the testing and commission of the power plant. Underlying layers of gravel and stones that could not be penetrated by a steel rod indicated the thickness of the fine sediment.

Figure 5-12: Map of test area in the reservoir, before field tests in 1994. td is thickness of sediment deposits, in metres.

SEDIMENT The sediment sluiced was mostly fine sand with d50 of around 0.12 mm. Small stones with sizes up 40 - 60 mm were also present, and were sluiced without any problems. Twigs and other plant material that occasionally stuck in the bottom slots could easily be removed. Figure 5-13 shows the grain size distribution.

Grain size (mm)

Figure 5-13: Grain size distribution of sediment sluiced with the SSS.

84 5. The saxophone Sediment Sluicer

THE SAXOPHONE SUCTION HEAD The saxophone suction head used was made at the site, from HD-PE (high density poly-ethylene) pipe. The parts were cut and shaped with hand tools and welded together in a simple way: a steel plate heated on a kerosene stove was used to melt the pipe flanges before they were joined.

For manoeuvring a two metre long bamboo pole was fitted to the suction head. Sand was filled between the two steel plates and a 20 litre drum filled with air was attached to the bamboo stick, as shown in Figure 5-14. In this way the suction head was kept standing in an upright position.

Bamboo stick Outlet pipe

20 I. drum d, = 145

A-A:

Steel plates —

B- B:

Figure 5-14: The saxophone suction head used in field experiments.

A flexible pipe with inner an diameter of 125 mm was used for the experiments. Three pipe sections, each 15 m long, could be joined so that pipe lengths of 15, 30 and 45 m were available. The pipe was of a standard type normally used for pumping up irrigation water from rivers. A 100 mm valve attached to the outlet of the pipe was used for the experiments in 1995. This substantially eased the priming of the pipeline.

LAYOUT OF EXPERIMENT Sediment was sluiced in areas close to the dam. The water was mostly shallow, in most places less than half a metre deep. As the water was too shallow to navigate a raft, the operators had to walk on the deposits while operating the SSS. The SSS was operated as a siphon, that is the pipeline was placed above the dam crest. Priming of the pipeline was necessary before sluicing of sediment could start. While sediment sluicing took place, the actual head and length of outlet pipe were noted. Samples of sediment water mixture were collected. The sediment concentration was found by weighing sediment submerged in a known

85 5. The saxophone Sediment Sluicer

volume of water, as described in section 5.3.2. A less accurate scale was used, but compared to other uncertainties, such as the temporal variation of sediment concentration, it was believed to be sufficient.

removed sediment Saxophone suction head outlet pipe

max ca. 1.0 m; :sediment deposits 2.0 m

, (Aboriginal reservoir bed ° °

Figure 5-15: The experimental setup

5.4.3 Experimental results Table 5-1: Records of sediment removal during the field experiments

Date Hours Volume Concentrations Total head Operator(s) sluiced removed (m3) (Cv. %) (m) 31.07.94 2.5 10 (S) - 1.3 Author 05.08.94 3 12 (S) - "

07.08.94 2 5 (S) - 2.0 "

10.08.94 3 3 (S) - " " 14.08.94 2 6 O) - 15.08.94 1 6 O) 1.8/5.8/4.9 1.3 16.08.94 5 22 (S) - 2.0 Local staff 17.08.94 3 12 (A) - “ Total 1994 21.5 76 25.06.95 3 13.5 (C) 4.7/2.1 2.1 Local staff 26.06.95 2.75 11.5 (C) 2.3 / 2.7 2.0 27.06.95 3.0 15.2 (C) 2.7 / 3.3 2.0 28.06.95 3.0 14 (A) - 1.9 29.06.95 5.4 26.9 (C) 4.4/1.9 2.2 “ Total 1995 17.15 81.3

(A): Removed volume is assessed on the basis of the time used (S): Removed volume was found by surveying the sediment deposits in the reservoir before and after sluicing. (C): Removed volume was found by measuring the sediment concentration of the sediment water mixture removed and the velocity in the outlet pipe.

86 5. The saxophone Sediment Sluicer

Experiments were conducted over a period of three weeks in 1994 and during one week in 1995. The SSS has been operated on 13 days and for a total of 39 hours. Out of this, local, non-technical staff account for 25 hours, including absolutely all operation in 1995. The capacity was measured 1) by measuring sediment concentration of samples collected continuously throughout the run 2) by surveying the area where sediment was removed.

MEASURED CAPACITIES For four experimental runs in 1994 and three in 1995, sediment concentrations were measured, as well as the energy gradient in the outlet pipe. All of these experiments were performed with an unmodified suction head (see next section) It is important to note that the measured concentrations represent average concentrations over periods of approximately 30 minutes. The maximum instantaneous concentration was higher, but frequent changes in the suction head position reduced the average output.

0.020 0.040 0.060 0.080 Energy gradient in outlet pipe (m water/m)

Figure 5-16: Measured capacity as a function of energy gradient.

MODIFICATIONS TO THE SAXOPHONE SUCTION HEAD It was attempted to modify the suction head to increase its suction capacity. Two different modifications were tested; a reduction in the cross-section of the upper opening and an increase in the width of the bottom slots. The energy gradient in the outlet pipe was between 0.039 and 0.043 in all experiments. The modifications are listed in Table 5-2.

87 5. The saxophone Sediment Sluicer

Table 5-2: Modifications to suction head Modification Slot width Upper cross-section Comment A 60 16.5 • 103 mm2 Original design B 60 8.3 • 103 mm2 modified C 60 4.1 • 103 mm2 " D 100 4.1 • 103 mm2 " E 100 16.5 • 103 mm2 "

0.04 --

0.03 - -

0.02 - -

0.01 -■

ABODE

Figure 5-17: Measured capacity with different modifications of the suction head. These experiments seem to indicate th at a decrease in upper opening and increase in slot width cause a slight increase in suction capacity. However, it should be noted that the outcome of this experiment may have been affected by increasing experience of the operators. Changing conditions in the sediment deposits may also have affected the results.

5.4.4 Sluicing by local staff Much of the sluicing with the SSS was performed by local, non-technical staff employed on a temporary basis. The author did not operate the SSS at all in 1995. It should also be mentioned that communication was difficult due to the somewhat limited knowledge of English of the local staff. It is therefore verified that the SSS can be operated under realistic conditions, and by local, non ­ technical staff after only a short period of training.

88 5. The saxophone Sediment Sluicer

Figure 5-18: One of the local staff, Podam Acharya, demonstrates that a substantial amount of sediment (6 m3) can be removed in one hour.

The main conclusion of the field experiments is that the SSS can be operated under realistic conditions. Little training is needed for the operators and blocking of the pipeline does not seem to pose a problem. The sluiced sediment concentrations varied, but could be close to the maximum transporting capacity of the pipeline. It was found that the SSS functioned best where the sediment deposits were thick, because a deeper crater provided a larger area from which the sediment could slide down to the suction head.

5.5 Removal of stones in the North Sea

5.5.1 introduction A huge number of well-heads and other types of equipment are installed on the seabed on the oil fields in the North Sea, at depths of up to several hundred metres. These installations and the pipes, cables and umbilicals connecting them to the oil platforms have to be protected, e.g. against trawls that are dragged along the seabed. To do so it is normal to apply a cover of coarse gravel or stones on and around the installations. The thickness of the cover can range from 0.5 - 4 m, and may consist of stones up to more than 150 mm.

89 5. The saxophone Sediment Sluicer

As maintenance-free installations exist only in theory, a problem occurs when the installations have to be repaired or replaced. This is what happened in 1996, when electrical cables connecting well-heads to the platform on the Draugen oil field had to be replaced. It was believed that the stones could be removed by using a SSS. As this was a new technique, a full-scale onshore experiment was performed. The equipment used in the on-shore experiment was the same as that intended to be used off-shore.

5.5.2 Onshore experiment A saxophone suction head with a shape approximately equal to what is described in previous sections was manufactured. The inner diameter of the suction head was 300 mm. The four bottom slots were 170 by 170 mm. The suction head was connected to a 10 m long flexible pipe with an inner diameter of 250 mm, attached to a pumping unit at the downstream end.

110 130 150

Figure 5-19: Grain size distribution of gravel sluiced with a 300 mm SSS.

For the onshore experiment the suction head was suspended from a mobile crane. A diver monitored the suction of stones and helped manoeuvring the suction head if necessary. The gravel had a grain size distribution intended to be same as for gravel used offshore. The grain size distribution is shown in Figure 5-19.

90 5. The saxophone Sediment Sluicer

Figure 5-20: Picture of container with stones before and after experiment. The small picture inserted shows a 180 mm stone sluiced during the experiment.

5.5.3 Offshore experience The gravel that was sluiced offshore proved to contain even larger stones than were tested in the onshore experiment. Some stones had one or two axes substantially longer than 150 mm. As the bottom openings were 170 by 170 mm a number of stones could not physically enter the SSS, and sluicing was seriously delayed. It was also observed that two or three stones entering at the same time could block the bottom openings. It was therefore decided to sluice the gravel directly into the open end of the flexible pipe. This was possible because the gravel was coarse, and the ROV (Remotely Operated Vehicle) was able to guide the pipe with such force that the pipe end never became sucked into the gravel. Although suction was more efficient without the saxophone suction head some single stones were large enough to block the 250 mm flexible pipe, indicating the difficult conditions under which the SSS had been used.

By accident, an attempt was made to sluice the original soft seabed deposits (silt and clay) into the open-ended flexible pipe. This proved to be impossible as the end of the pipe was drawn deep into the deposits which clogged the pipe. The SSS was not tested soft seabed deposits, but it is likely that it would have performed significantly better than the open-ended pipe.

Stones were removed through a 300 mm pipe in a similar operation in 1997. It was found that stones could block the pipe if they hit small, abrupt contractions. This happened in spite of the pipe ’s cross-section being larger than the inlet of the suction head. Thus the necessity of a smooth conduit all the way from the suction inlet to the outlet was proved, and is hereby strongly emphasised.

91 5. The saxophone Sediment Sluicer

5.6 Conclusions A technique that permits controlled suction of sediment and water into a pipe, the Saxophone Sediment Sluicer (SSS) has been developed. From the laboratory experiments it was found that the suction capacity of the SSS can be controlled by three factors: 1. The diameter of suction head relative to the diameter of the outlet pipe. 2. An opening in the suction head immediately before the connection to the outlet pipe, allowing inflow of “extra” water. 3. To a certain degree, the width of the bottom slots. By varying these factors the suction capacity can be adjusted to obtain optimum transport conditions in the outlet pipe.

The SSS sluices sediment from the surface of the sediment deposits and is therefore suitable for preserving reservoir capacity as well as for removal of old sediment deposits. From the laboratory and field experiments with the SSS, as well as from its use in the North Sea it can be concluded: 1. Sluicing of sediment from a reservoir is possible without interrupting the water supply. 2. The technique is simple in implementation and operation, and can be operated by local staff after a short period of training. The chance of maloperation causing severe problems such as clogging of the pipeline seems to be small. 3. The size of the sediments that can be sluiced is limited by the possibility of one single or a few stones blocking the bottom openings.. 4. Sluicing is economic with respect to investments and requires a minimum of water for the transport of sediment out of the reservoir. 5. The system can be operated without input of external energy if the head between the water surface and the outlet is sufficient. Sediment is released from a pipeline and can therefore be used for construction, irrigation, land reclamation or for regaining the natural sediment regime in the river.

92 6. Hydraulic sediment transport

6. HYDRAULIC SEDIMENT TRANSPORT

6.1 Introduction Hydraulic sediment transport in the present context refers to transport of sediment by using a fluid (which for all practical purposes is water) as a transporting medium. The sediment-water mixture is transported in a conduit which is either an open channel (free surface flow) or in a pipe (closed conduit). Of these two, sediment transport in pipes is by far the most widely used method. For this reason, sediment transport in pipes has been more widely studied than on sediment transport in open channels.

The removal of sediment from reservoirs using the Slotted pipe sediment Sluicer (SPSS) and the Saxophone Sediment Sluicer (SSS) has been described in Chapters 4 and 5 respectively. Both techniques require that the sediment-water mixture is removed through a pipe. This pipe may extend all the way through the reservoir ending downstream of the dam. Alternatively, the sediment-water mixture may be transferred to an open channel through which it is transported out of the reservoir. The open channel can, for example, be in a tunnel parallel to the reservoir. In both cases the basic idea is to use the existing head between the water surface and the outlet downstream of the dam as the driving force.

Factors that limit the rate of sediment transport in a conduit include the energy gradient, the size and shape of the conduit and the characteristics of the sediment. In hydraulic transport of sediment out of a reservoir the energy gradient will always be a limiting factor. Sediment properties are difficult to change, except for the possibility of retaining very coarse sediment before it enter the reservoir or in the upstream end of the reservoir. The challenge is thus to optimise the conduit so it can transport sufficient sediment, preferably with minimum use of water. Knowledge of sediment transport in conduits is therefore crucial to any sediment removal scheme based on the SPSS and the SSS.

6.2 Sediment transport in pipes

6.2.1 Introduction Hydraulic sediment transport in pipes (for short pipeline transport) is widely used. In the mining industry sediment-water mixtures can be pumped over long

93 6. Hydraulic sediment transport

distances as an alternative to truck, rail or conveyer belt transport. In hydraulic dredging the dredged material has to be transported to surface or to a disposal site through a pipe. Several equations and methods for the computation of hydraulic sediment transport in pipes have been developed. Many of these methods have been developed for the purpose of computing commercial pipeline transport. In principle, conventional pipeline transport and pipeline transport from reservoirs are equal. However, differences do exist that may influence the applicability of methods for computation of pipeline transport: 1. In conventional pipeline transport the sediment is often processed in mills, which allows control of the grain size distributions. In this way the grain size can be selected on the basis of an economical optimisation. In many cases the transported sediment has a different density from normal sand, such as coal or iron tailings. In removing sediment from reservoirs wide and changing grain-size distributions must be expected, whereas the density of natural sediment does not vary much. 2. In conventional pipeline transport the slurry is pumped and the energy gradient can thus be controlled. Often, a high concentration slurry is pumped with a high energy gradient through a pipeline with a small cross-section. This normally reduces both energy consumption and the investment costs for the pipeline. In removing sediment from reservoirs the energy head is fixed, and often small compared to the required length of the pipeline. With a fixed (low) energy gradient in the pipeline, the maximum rate of sediment transport is determined by the sediment properties and the cross-section and roughness of the conduit. In many cases a low concentration of sediment must be expected, compared to conventional pipeline transport.

6.2.2 Types of flow There are three main types of flow of sediment-water mixtures in pipes: 1. Homogeneous (or nonsettling) How occurs when there is a small vertical difference in sediment concentration, and the slurry can be treated by single­ phase models. However, no slurry is truly homogeneous because it consists of distinct phases, nor is there a sharp distinction between homogeneous and heterogeneous slurries (Shook and Roco, 1991). Wasp et al (1979) suggests that a slurry can be treated as homogeneous when the ratio of volumetric concentration of solids at 0.08 D from top to pipe centre is larger than 0.8. 2. Heterogeneous flow is affected by gravitational forces on the sediment particles and is therefore characterised by a pronounced solids concentration gradient across the vertical axis of the pipe. Heterogeneous flow is encountered in a wide variety of commercial applications ranging from

94 6. Hydraulic sediment transport

dredging to coal transportation (Wasp et al, 1978). Heterogeneous flow may be divided into truly heterogeneous flow and flow with saltation (Herbich, 1990). This is not pursued in the present study, as it does not affect the methods for computation of head loss that are studied. 3. At some mean velocity less than that required for heterogeneous flow some of the suspended particles begin to settle, and an identifiable bed surface will be formed, that is, flow with a stationary bed. In the transition between heterogeneous flow and stationary bed a sliding, compact bed layer may be observed. The velocity at which this transition takes place is named by Durand as the Limit Deposit Velocity, VL. Durand also notes that VL appears to correspond fairly accurately to the minimum head loss, and thus to the most favourable operating conditions from an economic point of view. The value of VL is thus of great practical interest. (Vanoni, 1975) Of these types of flow heterogeneous flow is of special interest, because it is the kind of flow most likely to exist in pipe transport of sediment out of a reservoir. VL is also studied because it often is the most favourable operating velocity,. Flow with a stationary bed is possible, at least at low concentrations, but is normally less stable and results in a higher head loss. At high concentrations the minimum head loss velocity (critical velocity, Vc) can be higher than VL. (Vanoni 1975, Eftekharzadeh 1987)

6.2.3 Methods for computation of limit deposit velocity A number of methods for determining VL have been proposed. Three of them have been selected for presentation on the basis of recommendations by Vanoni (1975) and Shook and Roco (1991). Durand ’s method is widely used and is recommended by Vanoni (1975). Wilson ’s nomogram, proposed originally for the highest value of VL at any concentration, is a useful and simple method for estimating the conditions where deposition becomes likely (Shook and Roco, 1991). Gillies’ Correlation is derived from pipes up to 0.5 m in diameter and aqueous slurries with dynamic viscosities between 5-10"4 and. 5-10"3 N-s-m"2. It can model slurries where the content of fines increases the viscosity of the carrier fluid. (Shook and Roco, 1991).

DURAND’S METHOD Vanoni (1975) recommends using two charts for VL. One chart (by Durand) is for uniform material and the other (by Durand and Condolios) for non-uniform material. However, no criterion to distinguish between uniform and non-uniform material is provided. VL can be expressed in terms of the factor FL:

95 6. Hydraulic sediment transport

VL=FLA/2gD(Ss-l) (6-1)

VL limit deposit velocity Fl dimensionless limit deposit velocity g acceleration due to gravity D diameter of pipe Ss relative density of solids; p s/p w p s density of solids p w density of water

Limit deposit velocity for uniform material; Durand

_2 Concentration q oy volume (Cv) ; as percentage

Grain size (mm)

limit deposit velocity for non-uniform material; Durand & Condolios

'? Concentration 3 by volume (Cv) I as percentage

Grain size (mm)

Figure 6-1 Charts for determining the factor FL in Equation 6-1. From Vanoni (1975)

WILSON’S NOMOGRAM The nomogram summarises important observations concerning the effects of pipe diameter and particle size. It shows a tendency for VL to decrease above particle sizes of 0.5 mm. Some observations have suggested that this decrease does not always occur. Because of neglected variables one should not expect predictions to be much better than ± 20%. (Shook and Roco, 1991)

To predict the velocity at which deposition forms in a pipe of diameter D, a line is drawn from the D-axis in Figure 6-2 through the appropriate particle diameter. The extrapolated line intersects the central vertical axis at the value of VL for

96 6. Hydraulic sediment transport

particles with a density ratio, Ss, of 2.65. For particles of other Ss values a line is drawn from the central axis through the appropriate Ss value to intersect the right- hand vertical axis.

0.10 :10 -1.0 0.11 0.12 0.13 0.14 0.15

1 0.25

t 0.30 .1 a 0.40 0.50

1.1 5.0 1.0 7.0 1.5 1.0 10

Figure 6-2: Wilson ’s nomogram for estimating deposition velocities. From Shook and Roco (1991)

GILLIES’ CORRELATION Gillies’ correlation (Shook and Roco, 1991) was obtained from data obtained using pipes up to 0.5 m in diameter and aqueous slurries with absolute viscosities between 0.5 and 5 • 10"3. VL for sediment-water mixtures is expressed in terms of the factor FL G:

(6 -2)

Fl g dimensionless limit deposit velocity using Gillies ’ correlation (Note that Fl_g corresponds to FL / 4l)

„ _ PsCf + Pw(1~Cr) (6-3) p f density of fluid and fines < 0.74 pm Cf mean in situ concentration of fines < 0.74 pm Cr mean in situ concentration

97 6. Hydraulic: sediment transport

The factor Fl,g is found from the expression:

(6.4)

CD drag coefficient for d50 p w viscosity of water

The viscosity of the “equivalent ” fluid vehicle is needed for computation of drag coefficient. D. G. Thomas ’s equation is a useful average of results from a number of experimental studies using deflocculated monosize spheres. (Shook and Roco, 1991) p r = 1 + 2.5CV +10.05Cvf2 + 0.00273 exp(16.6C vf) (6-5)

Pr relative viscosity, p f/p w p f viscosity of “equivalent ” liquid! vehicle Cv,f volumetric concentration of fine particles contributing to “equivalent liquid vehicle"

Drag coefficient should ideally be calculated from measured fall velocity. Fall velocity can alternatively be found in charts such as Figure 2.2 in Vanoni (1975). Drag coefficients can also be calculated from equations such as (Shook and Roco, 1991).

Co — ai (Ar)bl (6 -6 )

Table 6-1: Constants for computing Cp for sand; Equation 6-6 Range Ar < 24 576 -1 24 < Ar < 2760 80.9 -0.475 2760 < Ar< 46100 8.61 -0.193 46100 < Ar 1.09 0

Ar Archimedes number, CDRep 2 = ------=- 3llL

drag coefficient of particle,

S

98 6. Hydraulic sediment transport

Rep Reynolds particle number, ------Mx ws settling velocity of particle p L density of liquid p L viscosity of liquid

In this study Equation 6-6 has been used when calculating CD.

COMPARISON OF THE METHODS In order to compare the methods a hypothetical sediment-water mixture of 10 % concentration was studied. The spread of the grain size distribution, defined as dfio/dio, is 4.5. This determines the content of fines < 75 g when using Gillies’ correlation. Using Wilson ’s nomogram the factor FL varies with the pipe diameter. Two diameters, 100 and 250 mm, were therefore studied. Figure 6-3 shows predicted V L as a function of grain size.

- 8-x-:

—Gillies correlation —♦— Durand, uniform, 10% —* — Durand, non-uniform, 10% ..-x-.. Wilson, D =100mm - - - o- - - Wilson, D =250 mm

Average grain size, d5o- (mm)

Figure 6-3: Variation in VL as a function of grain size. A sediment concentration of 10 % by volume was studied.

COMPARISON WITH EXPERIMENTAL RESULTS From experiments with the Slotted Pipe Sediment Sluicer described in chapter 4 230 data sets containing velocity, concentration and kind of flow are available. The three kinds of flow are flow with stationary bed, flow with a sliding bed layer and heterogeneous flow. In these experiments, sand with average grain size of 0.6 mm was transported through a 44 mm pipe. Concentrations of up to 10 %

99 6. Hydraulic sediment transport

by volume were measured. The experimental results are plotted together with theoretical VL calculated from Durand ’s method and Gillies’ correlation, see Figure 6-4. It was not possible to compare with Wilson ’s nomogram because the smallest pipe diameter to be calculated using this method is 100 mm. From experiments described in section 6.3 110 data sets are available. In these experiments a sand with average grain size of 1.2 mm sand was transported in a 60 mm pipe, and concentrations of up to 3 % by volume were measured, the results are shown in Figure 6-5.

Velocity in pipe

Figure 6-4: Observed flow of 0.6 mm sand in a 44 mm pipe plotted together with VL calculated from Durand ’s method and from Gillies’ correlation.

0.030 Stat. bed 0.025 -- Transition Met flow - Dur. -non-uniform 0.020 -- ■ Gillies correlation 0.015 -- - Dur. -uniform

0.010

0.005

0.000

Velocity in pipe

Figure 6-5: Observed flow of 1.2 mm sand in a 60 mm pipe plotted together with VL calculated from Durand ’s method and from Gillies’ correlation.

100 6. Hydraulic sediment transport

DISCUSSION An interesting feature of the three methods is that the highest VL is predicted for sediments with d5o between approximately 0.3 and 0.6 mm. Wilson ’s nomogram predicts a substantial decrease in VL with increasing grain size. It noteworthy that Wilson ’s nomogram and Gillies’ correlation do not account for sediment concentration as opposed to Durand ’s method. Durand ’s method also accounts for the non-uniformity of grain size distribution, as there is a choice between two charts. Wilson ’s nomogram and Gillies’ correlation do not account for non ­ uniformity of grain size distribution, but Gillies’ correlation includes the effect of fine sediment < 74 g.

Gillies’ correlation seems to offer the best prediction of VL when compared with the experimental results. However, it should be noted that the experiments were performed in relatively small pipes and with medium to coarse sand which is not necessarily representative of a field situation.

An assessment of VL based on Durand ’s value of FL for uniform sediment will be the most conservative. (Equation 6-1 and Figure 6-1) When grain size is between approximately 0.1 and 0.3 mm Gillies’ correlation predicts VL close that of Durand ’s method for uniform sediment. Gillies’ correlation (Equations 6-2 - 6-6) may give a better estimate, and should be considered especially if the content of fine sediment < 74 p is high. A. D. Thomas however, suggests that a value of FL

= 0.3 (FLjg = 0.21) should be used as a lower bound for VL (Shook and Roco, 1991).

The best way to find the VL is to perform experiments with the actual sediment and use Equation 6-1 to scale up the results. A large pipe diameter will increase the reliability of the experimental results.

6.2.4 Methods for computing head loss Two methods for computing head loss for solid-water mixtures in pipes were considered. The Durand-Condolios equation is based on 310 tests (reported in 1952) with sediment sizes ranging from 0.2 - 25 mm, sediment concentrations ranging from 2% - 23% by volume and pipes ranging in size from 38-711 mm in diameter (Vanoni, 1975). The Two-layer model was developed by K.C. Wilson in the seventies (Shook and Roco, 1991). The two methods have been compared with results obtained from laboratory and field experiments.

101 6. Hydraulic sediment transport

THE DURAND-CONDOLIOS EQUATION One of the most frequently used equations for head loss of water-sediment mixtures in pipes is the Durand-Condolios equation (Shook and Roco, 1991).

0 = KY % (6-7)

Where dimensionless excess head loss

(6 -8)

and Durand-Condolios group of independent variables:

(6-9) gD(S, -1)

V velocity K constant in the Durand-Condolios equation, 81 i energy gradient of water (m /m) im energy gradient of slurry (m H;0 /m) Cv sediment concentration by volume (-)

The energy gradient of water can be found from the Darcy-Weisbach equation:

(6-10) 2gD

f Darcy-Weisbach friction factor

For normal sediment with a density of 2680 kg/m3 Equation 6-7 can be written as:

(6 -11)

Equation 6-11 is recommended by Vanoni (1975) for analysing heterogeneous flow because it seems to give the best agreement with observations.

Correlations based on T usually overestimate head loss as the pipe diameter increases. Any <$> - V correlation developed from small pipe measurements would therefore overestimate 0 for large pipes. (Shook and Roco, 1991) Furthermore,

102 6. Hydraulic sediment transport

correlations based on Y do not take into account the spread of grain size distribution, unless a modified value of CD is used, or the content of very small particles is treated separately.

MODERATELY BROAD SIZE DISTRIBUTIONS For moderately broad size distributions, the empirical weighing method of Equation 6-12 seems to be as good as any (Shook and Roco, 1991). The size distribution is regarded as being divided into a number of intervals. The zth interval contains the volume fraction of x, of particles, where Zx, = 1.0. Particles in the zth interval settle (at infinite dilution) in the carrier fluid with drag coefficient CDi The weighted mean drag coefficient for the mixture is computed as:

■=z (6 -12) 'Dm VCDi J

X, volume fraction of particles with CDi Cd , drag coefficient of fraction x; CDm average drag coefficient of sediment particles.

BROAD GRAIN SIZE DISTRIBUTIONS One method for including broad grain size distributions is to assume that particles smaller than a particular size contribute to the “equivalent liquid vehicle ”. According to Faddick these can be particles that settle with a drag coefficient larger than 24 (Shook and Roco, 1991). For heterogeneous particles, Y is estimated from an expression such as

Y = [gD(ss/SL^-l)Jf - 1E(xiVc^T)het (6-13) LZXi,het j

St.eq pL,eq/pw p L-eq density of water and fines contributing to equivalent liquid vehicle p w density of water CDi drag coefficient of fraction, calculated from p L,cq and p, L_eq gL,eq viscosity of the equivalent liquid vehicle (Equation 6-5)

THE TWO-LAYER MODEL A complete presentation of this method would be space-consuming, so only a brief introduction is provided here. A complete presentation is provided by Shook and Roco (1991). The slurry flowing in a pipe is visualised as forming two layers

103 6. Hydraulic sediment transport

separated by a hypothetical interface. Within each layer, variations in solids concentration and velocity are neglected when computing boundary stresses and stresses at the interface. The mixture in the upper layer, of volumetric solids concentration, Q, behaves essentially as a liquid as far as the wall shear stress is concerned. The lower layer is assumed to have a high total solids concentration, Qjm, which in this model is assumed to be 0.6. The increment, C2, (see Figure 6- 6) is assumed to consist of particles whose immersed weight is transmitted to the pipe wall by interparticle contact. Coulombic sliding friction is assumed to occur at the interface between the wall and the lower layer.

A: B:

Figure 6-6: A: Pipe cross-section, as idealised in the model. B: Concentration variation with elevation.

The volumetric flowrate of the mixture is:

A-V = Aj-V, +a 2-v 2 (6-14)

V velocity in pipe V, velocity in the upper layer V2 velocity in the lower layer A cross-section of pipe Ai cross-section of the upper layer a 2 cross-section of lower layer

The local slip velocity for particles relative to the fluid is neglected, so that the volumetric flowrate of solids is:

Cv •A-V = C1 -A-V + C2 -A2 -V2 (6-15)

Cv concentration by volume Ci concentration in upper layer C2 concentration in lower layer

104 6. Hydraulic sediment transport

Mean in situ concentration:

(6-16) A

Cr mean in situ volume fraction

Volumetric concentration of particles contributing to Coulombic friction:

(6-17)

Cc contact load concentration

The Two-layer model provides an equation for Cc and equations for interfacial stresses written in terms of momentum equations.

COMPARISON OF THE METHODS The three versions of the Durand-Condolios equation and the Two-layer model were compared with respect to variation of pipe diameter, D, and average grain size, d50. A synthetic grain size distribution characterised by d^/dio = 5 was chosen. The grain size distribution is shown in Figure 6-7.

100 an

0

I o o d o

Figure 6-7: Synthetic grain size distribution used to compare methods for prediction of head loss in sediment transport pipes.

First, a hypothetical sediment-water mixture with average grain size of 0.16 mm and a concentration of 15 % by volume was studied. The sediment-water mixture was assumed to be transported through smooth pipes with diameters ranging from 40 to 800 mm. The results are shown in Figure 6-8.

105 6. Hydraulic: sediment transport

12 —A— Eq 6-7 10 —D— Eq 6-12 —o—Eq 6-13 —■—Two layer model

2

0 0 0.2 0.4 0.6 0.8

Pipe diameter (m)

Figure 6-8: Dimensionless excess head loss for a sediment-water mixture with average grain size of 0.16 mm and a concentration of 15 % by volume transported through smooth pipes of various diameters. Velocities are computed from Gillies’ correlation.

Next, a sediment-water mixture being conveyed through a 250 mm smooth pipe with a concentration of 15 % by volume was studied. The average grain size was varied from 0.04 mm to 39 mm. The velocities used are partly predicted by Gillies’ correlation. A plot of the velocities is shown in Figure 6-9.

5

0.01 0.1 10 100

Median particle size (mm)

Figure 6-9: Velocities used when comparing methods for prediction of head loss in sediment transport pipes.

106 6. Hydraulic sediment transport

Eq 6-7 40 -- Eq 6-12 Eq 6-13 Two layer model

Median particle size dso (mm)

Figure 6-10: Dimensionless excess head loss for a sediment-water mixture of varying d50 being transported through a 250 mm pipe at a concentration of 15 % by volume. The velocities used are shown in Figure 6-9.

From Figure 6-8 and 6-10 several conclusions can be drawn: • When the Durand-Condolios equation is used on fine sediments it is found that a lower head loss is predicted using a drag coefficient based on the average grain size, than if a weighted drag coefficient is used. An even higher head loss is predicted if the “equivalent liquid vehicle ” approach is used. These differences become small when grain size is above 0.3 mm. • The Two-layer model predicts a much higher head loss for coarse particles than the three versions of the Durand-Condolios equation. The Durand- Condolios equation predicts no further increase in head loss when d50 exceeds 1-2 mm whereas the Two-layer model predicts increase with sizes up to 10 - 20 mm. • A major difference is found when different pipe diameters are compared. The Durand-Condolios equation predicts no change in dimensionless excess head loss as the diameter changes, except a very small change for the “equivalent liquid vehicle approach ”. The Two-layer model predicts a substantial decrease in dimensionless excess head loss as pipe diameter increases.

COMPARISON WITH EXPERIMENTAL RESULTS From experiments with the Slotted Pipe Sediment Sluicer described in Chapter 4 230 data sets containing velocity, concentration and kind of flow are available. In these experiments sand with average grain size of 0.6 mm was transported through a 44 mm pipe. Concentrations up to 10 % by volume were measured. The measured dimensionless excess head loss plotted together with dimensionless

107 6. Hydraulic sediment transport

♦ bed ■ sliding o heterog. ------Eg 6-7

Velocity (m/s)

Figure 6-11: Comparison of measured and predicted dimensionless excess head loss. The Durand-Condolios equation was applied to a 44 mm pipe carrying 0.6 mm sand.

Figure 6-12 shows measured dimensionless excess head loss and dimensionless excess head loss predicted by the Durand-Condolios equation and the Two-layer model. Dimensionless excess head loss is measured for concentrations between 4.5 and 5.5 % by volume.

Velocity (m/s)

Figure 6-12: Comparison of measured and predicted dimensionless excess head loss. The Durand-Condolios equation and the Two-layer model were applied to a 44 mm pipe carrying 0.6 mm sand at concentrations between 4.5 and 5.5 % by volume. From experiments described in section 6.3 110 data sets are available. In these experiments a sand with average grain size of 1.2 mm was transported in a 60

108 6. Hydraulic sediment transport

mm pipe. Concentrations up to 3 % by volume were measured. The measured dimensionless excess head loss plotted together with dimensionless excess head loss predicted from the Durand-Condolios equation (Equation 6-8) is shown in Figure 6-13. Figure 6-14 shows measured dimensionless excess head loss and dimensionless excess head loss predicted by the Durand-Condolios equation and the Two-layer model. Dimensionless excess head loss is measured for concentrations between 2.25 and 2.75 % by volume.

♦ bed B sliding o heterog. ------Eq 6-7 ------Eq 6-12

Velocity (m/s)

Figure 6-13: Comparison of measured and predicted dimensionless excess head loss. The Durand-Condolios equation was applied to a 60 mm pipe carrying 1.2 mm sand.

♦ bed B sliding o heterog. ------Two-layer model ° 100 ------Eq 6-7

S 10

Velocity (m/s)

Figure 6-14: Comparison of measured and predicted dimensionless excess head loss. The Durand-Condolios equation and the Two-layer model were applied to a 60 mm pipe carrying 1.2 mm sand at concentrations between 2.25 and 2.75 % by volume.

109 6. Hydraulic sediment transport

It can be seen from Figure 6-11 - Figure 6-14 that the head loss is underestimated by both the Durand-Condolios equation and the Two-layer model. The figures also show that the Two-layer model models head loss better than the Durand- Condolios equation for these particular cases. It is also noteworthy that flow with stationary bed is modelled almost as well as heterogeneous flow.

COMPARISON WITH FIELD EXPERIENCE Two pipelines for sediment transport have been studied. The 125 mm pipeline used for experiments in Jhimruk in Nepal is described in chapter 4. The other pipeline studied is a 3 km long 300 mm pipeline used for the transport of mining residue at the Titania mines in Tellnes near Egersund in southern Norway.

Table 6-2: Measured and computed head loss for two pipelines

JHIMRUK TITANIA Inner pipe diameter (m) 0.125 0.318 Average velocity (m/s) 1.8 3.95 Average grain size, d# (mm) 0.136 0.083 Concentration by volume; Cv 0.09 0.081 Density of sediment, kg/m3 2650 3100 Measured energy gradient for mixture; im (*) 0.030 0.039 Predicted energy gradient for clear water, i 0.019 0.033 Predicted energy gradient for mixture;; im Durand-Condolios eq; Cd based on d50 (6-7) 0.031 0.034 Durand-Condolios eq; weighted Co (6-12) 0.034 0.040 Durand-Condolios eq; “eq. liquid vehicle ” (6-13) 0.032 0.040 Two-layer model 0.030 0.035 *: It is estimated that the true energy gradient may deviate a ± 0.002 from the measured.

In the case of Jhimruk, the Two-layer model gives the best prediction. The Durand-Condolios equation using Cr> based on d50 (Equation 6-7) also gives a good prediction in this case. Equation 6-12 and 6-13 seem to predict a higher head loss than actual. In the case of Titania Equation 6-12 and 6-13 seem to give the best prediction of head loss, whereas the Two-layer model and Equation 6-7 underestimate head loss.

DISCUSSION It is seen that both the Durand-Condolios equation and the Two-layer model underestimate head loss when compared with the laboratory experiments. When compared with field measurements both over-prediction and under-prediction is

110 6. Hydraulic sediment transport

observed. The differences may be attributed to either grain size or pipe diameter. When CD is corrected for grain size distribution (Equations 6-12 and 6-13), a decrease in dimensionless excess head loss is predicted when d5o increases from 0.04 to 0.12 mm (see Figure 6-10). However, sediment water-mixtures with such fine sediments should be treated as homogeneous.

Sediment transport in inclined pipes has not been discussed here. In inclined pipes both VL and im will be lower than in horizontal pipes. At inclinations less than 5% this effect is limited to a few per cent of the total head loss, and thus marginal (Shook and Roco, 1991). Another, and more important, effect is that energy gradient, in terms of metres water per metre, will increase with increasing concentration if the energy gradient in terms of metre sediment-water mixture per metre is constant. This effect is discussed further in Section 6-3 and in Chapter 7.

6.3 Sediment transport in open channels

6.3.1 Introduction An alternative to hydraulic transport of sediment in a pipe is the use of an open channel. In an open channel transverse currents are likely to keep sediment in suspension at lower velocities and the hydraulic radius can be larger compared to a pipe of the same cross-section. There was therefore reason to believe that a specific flow of a sediment-water mixture could be transported with less head loss in an open channel than in a pipe. Industrial transport of solids in open channels has been reported by several authors (Kleiman 1976, Khun 1980). Faddick (1986) reports that the 140 km open channel at El Teniente in Chile is designed to carry ultimately 180,000 tonnes per day of copper tailings. This is a very large quantity, but if the tailings are transported at 20 % by volume and the velocity is 4 m/s it can be shown that the required cross-section of the flow is less than 1.0 m2.

6.3.2 Methods for computing sediment transport in open channels Since velocity in an open channel is not proportional to flow, prediction of velocity and head loss is more difficult compared with transport of solids in pipes. It was also found that less information is available on sediment transport in open channels than on pipeline transport.

Ill 6. Hydraulic sediment transport

The equation proposed by M. B. Lytle & A. J. Reed, (Lytle, 1984) is specific to coarse coal. The work of Ambrose (Reported by Lytle, 1984) was aimed at determining design parameters for elimination of deposition in storm sewers. Nnadi (reported by Shook and Roco, 1991) suggests a method for calculating the required slope for a given velocity in an open channel. The equation does not incorporate the effect of variation in grain size and sediment concentration. Novak and Nalluri (1975) presents equations for bed load and suspended concentration, but the highest concentration in their experiments was 0.24 % by volume. Their equation for suspended, concentration is similar to the equation by Graf and Acaroglu (Lytle, 1984). Shook and Roco (1991) suggests that a modified version of the Two-layer model can be used for open channel flow, but they provide no complete presentation. The following paragraphs present the equations of Faddick (1986), Graf and Acaroglu (presented by Lytle, 1984) and Smart (1984).

FADDICK Faddick (1986) suggests an approach based on Manning ’s formula, that provides the necessary slope for a rectangular channel with a width that is twice the depth. To avoid depth and velocity fluctuations the Fronde number must be larger than 1.25. Prandtl velocity distribution with Von Karmans constant, k, of 0.2. is used. The low value of k is attributed to the content of sediment (Vanoni, 1975) Further, velocity at distance above bed equal to 1/10 of depth is set at 35 times the maximum settling velocity in order to keep particles in suspension. The solution can be written as

100 (35 vj^ S - (6-18)

S slope (%) vr settling velocity of particles W =T/28.19p mCw T throughput, tonnes per hour p m unit weight of sediment-water mixture, kg-m"3 Cw concentration by weight, decimal fraction n Manning ’s n = 1/M

The slope and computed velocity become unreasonably high for coarse particles as the computed velocity in the open channel is proportional to the settling velocity of the largest sediment particles. Equation 6-18 is therefore limited to finer sediments, although no criterion is provided. The computed velocity and slope are not related to sediment concentration. The velocity computed is not

112 6. Hydraulic sediment transport

dependent on open channel size as with most VL-relationships for pipes. A modified version of this equation is provided by Shook and Roco (1991).

GRAF AND ACAROGLU Graf and Acaroglu plotted the results of 903 tests to derive the regression equation (Lytle, 1984):

O = 10.39¥"2'52 (6-19)

<$> transport parameter; CvVR / ((Ss-1 )d503 -g)0,5 V|/ shear intensity parameter; (Ss-l)-d50 / S R

Experiments with large coal particles indicate that these parameters are inadequate to model the transportation of coarse coal in open channel flow (Lytle, 1984). This equation predicts that the concentration will be inversely proportional to average grain size, d50, resulting in a very low rate of coarse sediment transport. Novak and Nalluri (1975) presents a different version of this equation:

SMART Smart shows that the Meyer - Peter Mueller equation seriously underestimates sediment transport capacity on slopes steeper than 3 %, mainly because of deficiencies in the form resistance factor (Smart, 1984). On the basis of experiments in a steep flume a new equation is suggested. The equation predicts transport capacity for alluvial material with mean size greater than 0.4 mm in slopes with gradients ranging from 0.04 to 20 %:

0 = 4 [((WW^- S°* C @^ (8-8=)] (6-20)

0 dimensionless sediment transport rate, qt/[g(Ss-l)d3]0,5 d$o grain diameter for which 90 % by weight of a sample is finer d30 grain diameter for which 30 % by weight of a sample is finer d mean grain diameter of sample S channel slope C flow resistance factor (conductivity), = V/(gHS)0,5 8 dimensionless bed shear stress HS/[(Ss-l)d] H flow depth 8 cr critical Shields parameter adjusted for slope 9 cr,o critical Shields parameter

113 6. Hydraulic sediment transport

It can be shown that Equation 6-20 is insensitive to mean grain size, d, when 6 » 0cr,o- Further, when 0 » 0cr>o, and provided the grain size and channel slope are constant the predicted unit bed load, qb , is proportional to the unit discharge. The result is that, provided slope and grain size are kept constant, the predicted sediment concentration is constant for different flow depths.

Rickenmann (1990) presents design procedures that are extensions of Smart’s equation, incorporating the effect of an increasing fluid density and viscosity on the bed load transport capacity of the flow. In the experiments a coarse, uniform gravel (d$o - 10 mm and d9 o/d 3o = 1.38) transported in clay suspensions was studied.

6.3.3 Experimental setup INTRODUCTION As open-channel transport can be an alternative to pipeline transport it is of great interest to compare the two directly. An experiment was therefore performed, in which a sediment-water mixture was first transported in a pipe and then transferred directly into an open channel whose slope could be adjusted.

EXPERIMENTAL APPARATUS To perform an experiment of this kind with the recourses available, proved to be challenging. A flow of sediment-water mixture in the pipe was needed where both gradient and the two dependent variables velocity and concentration could be controlled. This was achieved by a further development of the Slotted Pipe Sediment Sluicer. A uniform flow in the open channel had to be created at varying energy gradients and the velocity in the channel had to be measured.

A tank, 1.0 m wide, 1.2 m long and 1.5 m high was used for the experiments. One side of the tank was transparent so th at sediment suction could be observed. The water surface was 3.2 m above floor level. A Slotted Pipe Sediment Sluicer was used to feed sediment into the pipe. An adjustable water inlet downstream of the slots in the Slotted Pipe Sediment Sluicer was used to regulate the concentration. The sediment-water mixture flowed through a 10 m-long acrylic pipe with an internal diameter of 60 mm. After the pipe the sediment-water mixture was transferred to a 10 m-long open channel with adjustable slope gradient. The open channel was made of a 90 mm acrylic pipe. The inlet was shaped to obtain uniform open channel flow. The depth in the open channel was measured at three different points. The experimental setup is shown in Figure 6-15

114 6. Hydraulic sediment transport

Cross section B-B: Detail C:

Detail A:

Figure 6-15: Setup of the experiment. Flow of sediment-water mixture in a pipe was compared directly with open-channel flow in a tilting open channel. Sediment concentration can be adjusted by the inlet of extra water into the slotted pipe.

1: Tank with sediment 9: Adjustable contraction 2: Slotted Pipe Sediment Sluicer 10: Open channel flow in 90 mm pipe 3: Inlet of “extra” water 11: Adjustment of channel slope 4: Valve 12: Monitoring of channel slope 5: Electro-magnetic flowmeter 13: Separation of water and sediment 6: Pipe flow in 60 mm acrylic pipe 14: Contraction 7: Pressure measurement points 15: Air inlet 8: Monitoring of energy gradient 16: Measurement of flow depth

115 6. Hydraulic sediment transport

MEASUREMENTS Each experimental ran provided a 50 - 70 1 sample of sediment-water mixture, consisting of 10 part-samples collected over a period of several minutes. The sediment concentration was found by the “constant volume - weight difference method ”. The flow was found as the average of the 10 flowmeter readings made at each experimental ran. The cross-section of flow in the open channel was found by measuring the location of the water surface at three points in the open channel This was done by point gauges that could be adjusted until they barely touched the water surface. The velocities was computed from the flow, measured by an electromagnetic flowmeter, and cross section. The energy gradient in the pipe was measured by the “pressure tap method ”. The slope of the open channel could be observed on a scale, with an accuracy better than 1:1000. The pipe and the channel are made of acrylic plastic and are therefore transparent. The kind of flow (i.e. deposition, sliding bed or heterogeneous transport) could be observed. The “constant volume - weight difference method ”, “pressure tap method ” and a description of the electromagnetic flowmeter are described in Appendix B.

THE SEDIMENT The sediment used for the experiments was a natural sand of alluvial origin. Approximately two tonnes of sand were sieved to achieve a maximum grain size of 7 mm. The median grain size, d50 of the sand was 1.17 mm. The average shape factor for 18 particles ranging from 3.3 - 7.25 mm was 0.56. Shape factor is defined in appendix B. The sand was also washed so that very little fines were left. (The fines in this case are particles that do not settle out easily in the 2 m3 collecting tank.) Changes in sediment properties due to washing out of fines are therefore believed to be very small, although the sand was used several times.

Grain size (mm)

Figure 6-16: Grain-size distribution of sediment.

116 6. Hydraulic sediment transport

6.3.4 Experimental procedure

INITIAL EXPERIMENTS DETERMINING SEDIMENT TRANSPORT CAPACITY OF THE PIPE Preliminary experiments were performed to determine the maximum concentration that could be transported in the 60 mm pipe at a specific energy gradient. At each energy gradient the sediment suction capacity of the Slotted Pipe Sediment Sluicer was varied by use of the inlet for “extra" water downstream of the slots. By stepwise reductions in the inflow of “extra" water, the sediment suction capacity was increased. Each increase in the suction capacity gave a reduced velocity in the pipe.

0.030

im = 7.5 ° ° a

0.025 . ? m 6 m E 0.020 im = 6.0 % * * £ 0.015 I irn = 4.5 % "T* 5 * % & g 0.010 o Flow with stationary bed □ sliding bed 6 im = 3.0 % ------<■ a heterogeneous flow ♦ Repeated exp, stat bed 0.005 m ■ Repeated exp, slid, bed r im = 2.0 -----►* a Repeated exp, het. flow m From experiment 0.000 0.50 1.00 1.50 2.00 2.50 Velocity in pipeline, m/s

Figure 6-17: Velocity and concentration when the inlet of extra water is gradually varied. Coarse sand (d50 =1,2 mm) is transported in 60 mm pipe. Both results from the initial experiments and experiments comparing pipe flow with open channel flow are shown.

The corresponding velocities and concentrations were measured. The results of this experiment are shown in Figure 6-17. For energy gradients exceeding 6 % it was found that the maximum concentration was transported when the flow is in the transition zone between flow with stationary bed and heterogeneous flow (sliding bed). At energy gradients lower than 6 %, the highest concentrations were obtained when there was flow with stationary bed. However, this flow

117 6. Hydraulic sediment transport

situation is normally not desirable because stationary-bed flow is unstable. The velocity at transition between stationary-bed flow and heterogeneous flow was therefore regarded as the optimum velocity for all energy gradients.

MEASUREMENT OF OPEN CHANNEL SEDIMENT TRANSPORT CAPACITY Each experiment started with the open channel set at maximum slope, which was 7 %. The desired energy gradient in the pipe was achieved by using the adjustable contraction at the downstream end of the pipe. The velocity and concentration (which are inversely related) were adjusted by using the inlet of clear water at the downstream end of the slotted pipe. Values of flow and velocity in the pipe for the experiments are reproduced in Figure 6-17. Once the desired flow situation in the pipe was achieved, the depth at three points in the open channel and the sediment concentration was measured. Next, the channel slope was decreased to 6 % and the measurements were repeated. The procedure of stepwise reducing the channel slope was repeated until a stationary bed started to form. The channel slope was then increased 1/10 % at a time, until flow again was heterogeneous. The cha nnel slope was then the lowest possible setting at which the actual sediment-water mixture could be transported. Three situations were tested at four different energy gradients (3,4.5, 6 and 7.5 %): 1. Maximum suction capacity of the; Slotted Pipe Sediment Sluicer. (No inflow of extra water) This gives low velocity and flow with a stationary bed. 2. Minimum suction capacity of the Slotted Pipe Sediment Sluicer. (Maximum inflow of extra water) This gives high velocity and heterogeneous flow 3. Optimum suction capacity. (Achieved by adjusting the inflow of extra water) The gives flow with sliding bed, that is in the transition between flow with stationary bed and heterogeneous flow. This procedure was also repeated with the pipe tilt equal to the energy gradient in the pipe.

6.3.5 Comparison between limit deposit velocity in pipe and in open channel The limit deposit velocity for the open channel, VL,0c» is the velocity at which a stationary sediment deposit starts to form on the bottom. The experiments conducted seem to imply that deposition in a circular open channel occurs at a slightly lower velocity than in a horizontal pipe transporting the same sediment- water mixture. The average velocity in the open channel was 94 ± 2 % of the velocity in the pipe. When the pipe was at a tilt equal to the energy gradient in the pipe the average velocity in the open channel was 98 ± 4 % of the velocity in the pipe.

118 6. Hydraulic sediment transport

2.0 1 o o 1.6 B 1 B 1 1.2 < ! E 51

0.8 o Velocity in horisontal pipe a Velocity in inclined pipe 0.4 a Velocity in open channel 0.0 0.000 0.005 0.010 0.015 0.020 0.025

Concentration by volume, Cv

Figure 6-18: measured limit deposit velocity in the pipe and the open channel.

6.3.6 Comparison between head loss in pipe and in open channel The experimental setup allowed the flow of a sediment-water mixture to be studied in both a pipe and an open channel simultaneously. The results are shown in Table 6-3 and in Figure 6-19. The energy gradient in the pipe was adjusted to a fixed value. The sediment concentration was then adjusted to the highest possible value that was it possible to transport in the pipe with either sliding bed or heterogeneous flow. The mixture transported in the pipe was led directly into the open channel. The slope gradient of the open channel was reduced stepwise, until the minimum slope at which the mixture could be transported in the open channel was found. It was found that the slope needed in the open channel was only 58 - 63 % of the energy gradient in the horizontal pipe. Experiments in which the pipe inclination was equal to the energy gradient in the pipe were also performed. In this case, the minimum slope in the open channel was 67 - 70 % of the energy gradient in the pipe. The flow in the open channel was supercritical, as the Froude number, F, in the experiments varied between 1.9 and 4.7. Froude number is defined as (Chow, 1973).

F = (6-21) Vsy oc yoc hydraulic depth of open channel, Aoc / b^ Aqc cross-sectional area of flow in the open channel boc width of water surface in open channel

119 6. Hydraulic; sediment transport

Table 6-3: Results of experiments comparing energy gradients in horizontal and inclined pipe with energy gradients in a inclined open channel. For comparison the energy gradient is measured as metres sediment-water mixture per metre, S and imm respectively, w = im/(l+Cv(Ss-l)) Concentration Energy gradient by volume (metres mixture/metre) (Cv) pipe (imm) open channel (S) S/l^m(%) Horizontal 0.005 0.030 0.018 60 pipe 0.010 0.044 0.026 58 0.017 0.059 0.038 64 0.023 0.072 0.047 65 Average 62 Pipe inclination 0.006 0.030 0.021 70 equal to 0.011 0.045 0.030 67 energy grad. 0.020 0.061 0.041 67 Average 68

0.08 o

0.06

ii < » A ■ 1 11 0.04 ■ 0 ■ A I 1 ■ n 0.02 ■ o Horisontal pipe 0) a Pipe tilting equal to en. grad. E ■ Open channel 0.00 0 0.005 0.01 0.015 0.02 0.025 0.03

Concentration by volume, Cv

Figure 6-19: Results from experiment comparing flow of sediment mixture in horizontal pipe, tilting pipe and in inclined open channel.

Experiments in which the sediment-water mixture was transported in the pipe at velocities different from the VL were also performed. Figure 6-20 shows that the difference between open channel slope and energy gradient in the pipe increases as velocity in the pipe increases.

120 6. Hydraulic sediment transport

1.0 0 c Q. 0 'cl 0.9 73 — ' ► CO 0 _c ^ c O) c c 0.8 >, CO 0 » ♦ 73 0.7 5 « II O) = s. >v 0.6 ♦ «% o ° t ♦ 0E> o .5 c 0.5 <0 0 CL S 0.4 0.5 0.7 0.9 1.1 1.3

Dimensionless velocity in pipe, V/W

Figure 6-20: Relationship between difference in energy gradient (in pipe and open channel) and the velocity in the pipe.

6.3.7 Proposed method for computing open-channel sediment transport The experiments indicate similarities between open channel and pipeline sediment transport. As discussed in section 6.3.2, existing methods for computing sediment transport in open channels were found to differ from those for pipeline transport, especially with respect to the modelling of grain size effects. Considering the experimental results alternative methods for computation of limit deposit velocity and head loss are therefore suggested.

LIMIT DEPOSIT VELOCITY The experiments showed that a specific sediment-water mixture could not be transported in an open channel unless all sediment were moving. The experiment showed that once a stationary deposit started to form, it continued to increase in size. The limit deposit velocity in the open channel, VL>0C, was found as the velocity at which a stationary deposit started to form. A stationary bed building up in an open channel causes one of two effects: 1. If the free-surface flow is in a closed conduit, a full pipe flow with thick sediment deposits will occur and possibly block the conduit. 2. If the conduit is open sediment deposits will increase until the sediment- water mixture is spilling over the edges. It is therefore clear that the optimum transport condition with respect to energy gradient in an open channel is flow at a velocity equal to VLt0C.

121 6. Hydraulic sediment transport

It is suggested that Equation 6-1 can be modified for use in open channel by substituting D for Dh . with.

FL,oc = Vwc/V2-S-Dh-(S,-1) (6-^2)

Fl?oc dimensionless limit deposit velocity in open channel VL-0C limit deposit velocity in open channel. Dh hydraulic diameter of conduit == 4Rh Rh hydraulic radius of open channel, = A^/P P wetted perimeter

The factor FL oc was calculated from observed limit deposit velocities in the open channel. The measured values of FL in the horizontal and tilting pipe and the factor FL-oc for the open channel are shown in Figure 6-21.

1.4

1.2 o 8 o i£ 1.0 > L "O < 0 I H (Qc B 0.8 Q □ Ltd 0.6 O oho rizontal pipe 3CD I 0.4 atilting pipe - II 0.2 ElflUme

0.0 _ 0.000 0.00!) 0.010 0.015 0.020 0.025

Concentration by volume

Figure 6-21: Measured values of Fl / Fl,oc in 60 mm horizontal pipe, 60 mm tilting pipe and in 90 mm circular open channel. It is therefore suggested that limit deposit velocity in an open channel, Lj0C, can be found from Equation 6-22. The measured factor FL;0C for the open channel averaged 78 % of the measured factor FL for the horizontal pipe. (See Figure 6- 21) Fl can be found from Figure 6-1 or from Gillies’ correlation.

ENERGY GRADIENT IN OPEN CHANNEL It can be seen from Figure 6-19 that the measured energy gradient in the open channel is proportional to the measured head loss in the pipe. From Table 6-3 it can be seen that the energy gradient in the open channel (i.e. the slope) was 61 % of the energy gradient in the horizontal pipe. The energy gradient in the open

122 6. Hydraulic sediment transport

channel was 68 % of the energy gradient in the pipe with a tilt equal to the energy gradient.

Equation 6-7 is a common version of the correlation between dimensionless excess head loss and Durand ’s group of variables for pipes. A modified form of the equation is proposed for open channel flow:

(6-23)

S — s = —------(dimensionless excess head loss for open channel)

(modified Durand ’s group for open channel)

Sm energy gradient in open channel = S(l+Cv(Ss-l)) (m H20 per m) S0 channel slope at which velocity with clear water is equal to velocity at slope S with sediment-water mixture. S0 was found from clear water measurements in the open channel. Kqc constant of proportionality

Only flow velocities close to limit deposit velocity were studied. This is because the differences between im and i and between Sm and S0 were small at higher velocities, and thus 0 and <3>oc became sensitive to erroneous prediction of clear water head loss. For the same reason, only concentrations above 1.0 % by volume were studied.

The dimensionless excess head loss in the open channel, 0OC, was plotted against the modified Durand ’s group of variables, T,oc - Similarly, 0, for pipe flow, was plotted against Durand ’s group of variables VP. Values of and K were obtained using the least square method. The results are shown in Figure 6-22.

123 6. Hydraulic sediment transport

Measured 0 in pipe 138 Y' Measured in open channel

o

e c

i > _E o II e Durands group

Figure 6-22: Measured dimensionless excess head loss for pipe and open channel. From experiments with 60 mm pipe and 90 mm open channel. The best fits of K and Koc, obtained by the least square method, are also shown.

The values of K and Kq C found by the least square method. Figure 6-22 show that dimensionless excess head loss in the open channel, 0^, is measured to be 48% of dimensionless excess head loss in the pipe, 0. As a constant K = 81 is recommended for Equation 6-7, the equation the equation for open channel flow 0^=39-^-% (6-24) corresponds to the Durand-Condolios equation. (Equation 6-7) As shown in Figure 6-22, using K = 81 and = 39 will underestimate the head loss in the pipe and open channel studied in this experiment. However, as discussed in section 6.2.4, using K = 81 may tie more appropriate for larger size pipes. Consequently, = 39 is believed to be valid for larger size open channels.

DISCUSSION The alternative approach for computing sediment transport in an open channel described above is tentative, as it is based on a limited set of experimental results. Neither variations in grain size nor in the shape and size of the open channel were studied.

124 6. Hydraulic sediment transport

It is worth noticing that flow in an open channel is likely to depend on the shape of the cross section. In an open channel of circular cross section the shape may be represented by the dimensionless group P/D, where P is the wetted perimeter and D is the diameter of the conduit. The results shown in Figure 6-23 indicate that 5>oc is correlated to the P/D ratio.

♦ «% I O) "cc

best fit Half full pipe, P/D = pi/2

Wetted perimeter/ Diameter, P/D

Figure 6-23: Predicted values of Kq C plotted against the P/D ratio. All experiments where Cv > 0.01 is plotted.

COMPARISON BETWEEN EXISTING METHODS AND EQUATION 6-24 A 90 mm open channel and a flow situation similar to the experiment is modelled, using the same sediment (d50 =1.17 mm). A slightly higher flow than obtained in the experiments was selected, in order to obtain a semicircular cross- section of flow. A velocity of 1.65 m/s was used, which is slightly above the highest VLoc measured. The predictions by the Equation 6-24 were compared with the predictions obtained by the equations of Smart (1984), Graf (Lytle, 1984) and Faddick (1986). The results are presented in Table 6-4. Table 6-4: Comparison between methods for computation of open channel sediment transport. A 90 mm pipe flowing half full is studied. Predicted values are underlined. Flow Velocity Slope Concentration Method: (m3/s) (m/s) (-) (m3/m3) Equation 6-24 (K<,c = 66) 0.00525 1.65 0.047 0.025 Equation 6-24 (K<,c = 39) 0.00525 1.65 0.047 0.042 Equation 6-18 (Faddick) 0.00525 >M 3.20 - Equation 6-19 (Graf) 0.00525 1.65 0.047 0.009 Equation 6-20 (Smart) 0.00525 1.65 0.047 0.0% 2H

125 6. Hydraulic sediment transport

The sediment concentration predicted by Equation 6-24 using = 66 corresponds to the experimental results. However, a value of K<,c = 39 may be valid for larger open channels. In pipes, correlations based on ¥ usually underestimate concentration as the pipe diameter increases. (Shook and Roco, 1991). This phenomenon is also found in the laboratory and field experiments described in section 6.2.4

Equation 6-18 greatly overestimates velocity and slope, and is apparently not suitable for modelling of coarse sediment transport in open channels. It can also be seen that Equation 6-19 underestimates concentration, whereas Equation 6-20 overestimates concentration.

6.4 Conclusions Three methods for computation of limit deposit velocity in a pipe, VL were studied, and differences between them were found. Gillies’ correlation gave the best prediction when compared to experimental results. These experiments however, where performed with relatively small pipes and coarse sediment.

The Durand-Condolios equation, which predicts head loss, was found to be sensitive to selection of method for computation of drag coefficient, CD. Using methods that takes wide grain size distribution or content of fines into account may give better predictions when fine sediment is modelled. The Two-layer model was found to predict a higher head loss for coarse sediment and a lower head loss for large diameter pipes, than the Durand-Condolios equation.

An experiment showed that a sediment-water mixture can be transported in an open channel at a slope which is less than 2/3 of the energy gradient required in a full pipe. In removing sediment from a reservoir through a pipe or in an open channel the available energy gradient will be a limiting factor. The use of open channel sediment transport is therefore an option worthy of proper consideration.

Existing methods for the computation of sediment transport in open channels are found to predict the actual experimental conditions poorly. Equations 6-22 and 6- 24 for computing open-channels sediment transport are therefore proposed. Both equations are based on similarity between pipe and open channel flow. However, the experimental basis for these equations are limited, as one kind of sediment and one open channel were used in the experiments.

126 7. applications and economic aspects

7. APPLICATIONS AND ECONOMIC ASPECTS

7.1 Applications

7.1.1 Introduction This section describes the applications of the Slotted Pipe Sediment Sluicer (SPSS) and The Saxophone Sediment Sluicer (SSS), which were developed with the aim of removing sediment from reservoirs. Their applicability depends to a large degree on the sediment transporting capacity of the conduit through which the sediment is transported out of the reservoir.

As an alternative or supplement to removing sediment from reservoirs the sediment can be made to bypass the reservoir, resulting in additional storage because less sediment will enter the reservoir. A higher head may also be obtained, which is beneficial to hydraulic sediment transport.

The SPSS and the SSS may have applications in sand traps and desilting basins as well as in various dredging operations. The simplicity of the techniques makes them particularly suitable for sediment removal where monitoring is impossible. The removed sediment may also have uses. The sand and gravel fractions will normally be useful, e.g. for construction purposes. A technique for extraction of the coarse fraction from sediment transporting pipes is therefore proposed.

7.1.2 Sediment transport capacity of pipes and open channels The Durand-Condolios equation and the two-layer model have been used to calculate sediment transport capacities in pipes and a modified version of the Durand Condolios equation has been used to calculate transport capacities in open channels. (Hydraulic sediment transport is treated in chapter 6) To enable a true comparison between pipe and open channel sediment transport to be made, it is assumed that both have an inclination equal to the energy gradient measured as metres sediment-water mixture per metre, i^ and S respectively.

The energy gradient used for computation of the necessary pipe diameter, im, is computed as:

127 7. applications and economic aspects

im=imm(l + Cv(Ss-U) (7-1) im energy gradient in pipe (m H20 per m) imm energy gradient measured as m sediment-water mixture per m. Cv sediment concentration, by volume Ss density ratio of sediment, p s/p w

Similarly, the energy gradient used! for computing open channel transport capacity, Sm, is the energy gradient measured as metres sediment-water mixture per metre.

S„=S(l + Cv(S,-n) (7-2)

S open channel slope S0 chann el slope at which velocity with clear water is equal to velocity at slope S with sediment-water mixture. Cv sediment concentration by volume Ss relative density of sediments, p,/p w

It is important to note that the energy gradients im and Sm will depend on the energy gradient of water, the energy gradient of sediment, the sediment concentration and the sediment density. If sediment is sluiced at an elevation equal to the outlet of the conduit im and Sm will be equal to AH/Lr. AH is the difference between reservoir surface and the outlet of the conduit and Lr is the length of the conduit. If sediment is sluiced at a higher elevation, im and Sm will be higher than AH/Lr because of the additional weight of the sediment.

In the calculations it is also assumed that:

• dso of sediment is 0.12 mm • The pipe is smooth. • The open channel has a Manning ’s number M = 1/n = 100 • The open channel diameter, DK is the diameter of a pipe or a tunnel flowing half full, and therefore equal to the hydraulic diameter, Dh . • The density ratio of sediment is 2.65 • The dry density of sediment deposit is 1325 kg-m"3 • The velocity is equal to 1.2-VL,G, where VL G is the limit deposit velocity computed by Gillies’ correlation. The results are presented graphically in Figure 7-1 and in Figure 7-2. The energy gradients imm and S correspond to AH/Lr if the sediment is sluiced at an elevation equal to the water surface of the reserv oir.

128 7. applications and economic aspects

-----Two-layer model, Cv max = 50% -----Durand Condolios eq., Cv max = 50 % ... Tw o-layer model, Cv max = 20% • ■ • Durand Conddios eq., Cv max = 20 % -—Open channel Cv max = 50 % - - Open channel, Cv max = 20 %

0.025 0.035

Energy gradient imm and s (m sediment-water mixture per m)

Figure 7-1: Computed diameter of pipe and open channel when the energy gradient is varied. It is assumed that 3300 m3 of sediment deposits per hour are removed.

-----Two-layer model, Cv max = 50 % 2.8 • — — Durand Condolios eq., Cv max - 50 % . - - Tw o-layer model, Cv max - 20 % 2.4 • — • - Durand Condolios eq., Cv max = 20 % Open channel Cv max =50% - - Open channel, Cv max - 20 %

10000 100000

m3 sediment remold per hour

Figure 7-2: Necessary diameter of pipe and open channel diameter when the rate of sediment removal is varied. An energy gradient of 0.03 (m sediment-water mixture per m is computed.

From Figure 7-1 it is seen that the difference between pipe and open channel diameter becomes smaller as energy gradient is reduced. At an energy gradient of 0.0175 a smaller diameter is required for an open channel than for a pipe. The cross-section of flow is thus less than 50 %, because the open channel is in a pipe or a tunnel flowing half full. Figure 7-2 shows that the calculated transport

129 7. applications and economic aspects

capacity of a 1.5 m pipe is 64,000 m3 sediment deposits per hour at Cv = 0.5, and imm = 3 %. If Cv is limited to 0.2 a pipe diameter of 2.05 m is required. The open channel diameters at Cv = 0.5 and 0.2 are 1.9 and 2.7 m respectively. It is emphasised that these computations are made for very large pipe and open channel sizes, compared to the experimental basis on which these methods were derived. The modified version of the Durand-Condolios equation, used to compute open channel flow, is based on experiments with an open channel only 90 mm in diameter. These experiments are described in Chapter 6.

7.1.3 Removal from reservoirs Both of the techniques described in Chapters 4 and 5 are designed for removal of sediment already deposited in the reservoir. However, this may be sediment that is removed continuously as it enter the reservoir (reservoir maintenance) or it may be sediment that is trapped over a long time (reservoir recovery).

Figure 7-4: Removal of sediment from a reservoir with the SPSS

The SPSS can be suitable for reservoir maintenance, as it is put in place before the sediment is depositing. Once the thickness of the sediment deposit is sufficient the SPSS is operated and the sediment covering the pipe is removed. The procedure is repeated as often as necessary. In the case of recovery of reservoir volume the SSS will be more suitable, as it removes sediment from the

130 7. applications and economic aspects

surface of the sediment deposits. As explained later in this section, the SSS is less vulnerable to being blocked by large items in the sediment deposits which may be an important advantage.

OPERATIONAL CHALLENGES During operation in a reservoir there are likely to be operational problems that do not occur in a laboratory or field experiment. Inflow of very coarse sediment and organic debris which is likely to occur during floods may block the SPSS and SSS. The SPSS is fixed to the reservoir bed and can not be taken to the surface for maintenance. If it becomes blocked during a flood it is also likely to be covered with sediment. The SPSS is therefore more vulnerable than the SSS and it is recommended that it should be used where the deposition of both very coarse sediment and organic debris can be controlled. This can, for example be in lower parts of the reservoir, or special check-dams can be built to retain such material upstream of the reservoir. On the other hand, the SSS is operated from the surface. If it is blocked it can be brought to the surface and the material can be removed. It is important that the bottom slots on the SSS should be so small that any material passing through can be transported through the pipe as well. Experience of removing coarse stones from the seabed in the North Sea, described in chapter 5, clearly shows the importance of a smooth conduit all the way through the conduit.

Veiy fine sediment, like silt and clay, can be cohesive. In these cases it may be necessary to mobilise the sediment deposits before sluicing. This may be achieved by installing a water jet or a cutting head at the suction head inlet (Hotchkiss and Huang, 1995).

The SPSS and the SSS are designed to sluice sediment at an optimum concentration. However, any sediment removal system involving long conduits for transport of sediment may require in situ measurement of velocity and sediment concentration. Relevant methods have been outlined by Shook and Roco (1991).

Any pipe or open channel carrying sediment water mixtures will be subject to wear, on which the technical and economi c feasibility of a sediment removal project will depend. Jacobs and James (1984) tested different pipe materials in a 38 mm pipe carrying a 10 % concentration of medium emery (0.15 mm) at 4 ms"'. The annual wear rates recorded ranged from 0.13 mm (rubber) and 0.67 (High density polyethylene) to 1.57 mm (mild steel). Comprehensive reviews of the wear resistance of various pipe materials are provided by Jacobs and James (1984) and Murakami et al (1980)

131 7. applications and economic aspects

7.1.4 Sediment modelling The numerical model SSIIM has proved its capability to model erosion and deposition per size fraction in a reservoir (see Chapter 3). There are several applications of such a model, two of which is briefly mentioned here: 1. Modelling of the amount and location of sediment deposition can be done per size fraction, and prior to the development of the reservoir. 2. Reservoir drawdown strategies can be investigated, with the aim of reducing deposition of sediment upstream of the reservoir. Drawdown strategies, which allow sediment to be transported as far as possible into the reservoir (or eventually out of the reservoir), can also be studied. Thus a sediment removal system can be designed prior to the development of the reservoir, and operational strategies can be chosen which allows efficient operation of a such a system.

7.1.5 Sediment bypass

Figure 7-5: A sediment bypass system. Sediment is trapped in a trapping reservoir and sluiced with either a SPSS or a SSS and transported by free surface flow or pipe flow (e.g. in a tunnel) past the reservoir. An optional balancing reservoir downstream of the main reservoir will ensure that sediment is released into the river only when surplus water is passing the dam. 1: Upstream sediment retention 4: Trapped sediment 2: Main reservoir 5: (SPSS or SSS) 3: Optional balancing reservoir 6: Tunnel or pipe

132 7. applications and economic aspects

Ando et al (1994) describes a sediment bypass system where a tunnel is used to bypass a substantial portion of the sediment laden water during floods. This however requires a channel or a tunnel of substantial size. A sediment bypass system based on hydraulic transport in a pipe is described by Eftekharzadeh (1987), but this system is based on continuous withdrawal of sediment without deposition taking place. A sediment bypass system based on hydraulic transport in a pipe has never been constructed (Hotchkiss and Huang, 1995).

It is suggested that the sediment can be trapped upstream of the main reservoir, in a separate trapping reservoir. The SPSS or the SSS can be used to feed a pipe or an open channel through which the sediment can pass the dam. A bypass system based on the SPSS or SSS is schematically shown in Figure 7-5.

Bypassing sediment has the advantage that a higher head can be created than if sediment is removed from the main reservoir. Not only is the head of water higher, but the sediment is deposited at a higher elevation, thus adding energy to the sediment-water mixture.

From Figure 7-2 it can be seen that substantial sediment removal capacities can be obtained in large pipes and open channels. Tunnels up to 10 m or more can be drilled with a TBM (Tunnel Boring Machine) A relatively smooth, circular cross- section is obtained. The cost of lining an open channel in a TBM-drilled tunnel is likely be to low compared with the cost of a pipe of the same size, because the thickness of the lining can be varied. For example, a thicker lining can be used in the channel bottom where abrasion is likely to most severe.

7.1.6 Sand traps and desilting basins The removal of sediment from sand traps and desilting basins is a topic that does not belong within the main frame of this thesis. However, the SPSS could have some useful applications which are discussed briefly below.

Due to its simplicity the SPSS is well suited for pressurised sand traps. It is operated simply by opening a valve on the outside and no monitoring is necessary. Thus, sediment removal is possible without interrupting the water supply. The SPSS is installed at Jhimruk hydropower project in Nepal (see chapter 4), in a small sand trap located downstream in the headrace tunnel and immediately upstream of the pressure shaft. A similar application of the SPSS is planned for the Kimthi hydropower project in Nepal (under construction in 1997). In both cases the SPSS provides an extra sediment removal facility, as the main sediment removal facility is desilting basins near the intake.

133 7. applications and economic aspects

Trapped Slotted Pipe sediment Sediment Sluicer

To outlet

Figure 7-6: Use of the SPSS in a pressurised sand trap in a tunnel. The design is in principle equal to designs at Jhimruk and Kimthi Hydropower projects.

The SPSS equipped with a downstream water inlet can be used in a hopper, with a design very similar to the experimental set-up described in Chapter 6. The experimental results indicate that the design allows an effective control of the sluicing of sediment, as the concentration can easily be adjusted to match the transport capacity of the outlet pipe. It is thus possible to compensate for variations in energy gradient in the outlet pipe, and for variations in sediment properties. A desilting arrangement will normally consist of several hoppers. The hoppers can be emptied individually, which ensures that water consumption for flushing is kept at a minimum.

Figure 7-7: Use of the SPSS in hoppers. The suction capacity is controlled by an inlet of “extra” water downstream of the slots. 1: Inflow of water and sediment 5: Adjustable inlet of “extra” water 2: Hopper with sediment 6: Outlet pipes 3: SPSS 7: Water with less sediment 4: Inflow of water

134 7. applications and economic aspects

7.1.7 Extraction of coarse sediment from pipes Using the SPSS and SSS to remove sediment through pipelines is discussed in Chapters 4 and 5 and the sediment transport is discussed in chapter 6. One extension of this work could be the study of the exploitation of the removed sediment. In many places the availability of sand and gravel for construction are limited in supply (pers. comm. Lysne, 1993). River bed sediment in many parts of the world has a bimodal grain size distribution, as they lack coarse sand and fine gravel fractions. (Axelson 1967, Melone et al 1975, Tufte 1975 and Selmer Olsen 1976)

80 —Coarse sand, 0.6-2.0 mm 60--

10.00 100.00

Grain size d (mm)

Figure 7-8: Example of bimodal grain size distribution; river bed sediment in Andi Khola in Nepal. Modified from Tufte (1989).

When sediment is transported in a pipe the solids concentration gradient along the vertical axis varies according to the grain size. Fine sediment is evenly distributed, whereas coarse sediment is fond mainly in the lower part of the pipe. During the experiment with the SSS (described in chapter 5) the vertical concentration distributions were studied. 20 mm pipes were used to collect samples simultaneously at five elevations in the 125 mm pipe. Analysis showed a pronounced vertical solids concentration gradient for the coarser particles, as shown in Figure 7-9. The median grain size of the transported sediment, d50, was 0.13 mm, the concentration 2 % by volume and the velocity 2 - 2,1 m s'1.

135 7. applications and economic aspects

110- Grain size (mm) • 0 - 0.075 • - 0.075-0.15 - 0.15-0.3 — 0.3 - 0.6 D= 125 mm — 0.6-1.2

Concentration (% of fraction average)

Figure 7-9: Vertical distribution of different grain size fractions in a 125 mm pipe. The total concentration, Cv, was 0.023 and the velocity 2.05 m/s.

An experiment was performed to show that coarse sediment can be extracted from a pipe by a simple method. A schematic set-up of the experiment is shown in Figure 7-10. The upper pipe is carrying the sediment-water mixture sluiced by the SSS and the lower pipe draws clear water from the reservoir. The pressure difference between the pipes, on which the flow velocity in the connecting pipe depended, could be adjusted simply by adjusting the outlet level of the lower pipe. The grain size distributions of the sediment sluiced and of the sediment extracted through the lower pipe is shown in Figure 7-11.

[Mixed sediment — Finer sediment

Clear water" [Coarse sediment

Figure 7-10: Schematic of experimental apparatus used to extract coarse sediment from a sediment water mixture. The upper pipe is 125 mm in diameter and the connecting pipe and the lower pipe 50 mm.

136 7. applications and economic aspects

sedimentsluiced from reservoir da, = 0.13 mm

sediment ectracted from bottom of pipe da, = 0.32 mm

0.038 0.074 0.147 0.295 0.589 1.168

Grain size d (mm)

Figure 7-11: Grain size distribution of sediment sluiced from reservoir through a 125 mm pipe and of coarse sediment extracted through a 50 mm pipe.

The set-up of this experiment was simple in that only readily available material was used. There is therefore reason to believe that more efficient extraction of coarse sediment can be achieved than demonstrated in this experiment.

This experiment demonstrated that coarse sediment could be extracted from a pipe. Fine sediment may also have uses, such as soil improver. By tapping from the upper part of the (main) pipe extraction of fine sediment is likely to be achieved. However, this has not been tested experimentally.

7.1.8 Discussion Some applications of the SPSS and SSS have been described. Other applications for these techniques are also likely to exist. The SPSS may be used industrially, both for emptying tanks of solid deposits and for feeding pipes with solids at the appropriate concentration. The SSS may be suitable for hydraulic dredging when monitoring is impossible. Extraction of coarse sediment may not only be to produce construction material; in some cases it may be desired to transport sediment further downstream from the dam, for instance to where water is discharged from a power plant. Extracting coarse sediment in such a case will reduce the energy requirement for sediment transport, that is either the consumption of water or energy gradient in the conduit.

137 7. applications and economic aspects

7.2 Economic aspects

7.2.1 Introduction Many reservoirs are built to store water for hydropower. However, when a reservoir has other purposes in addition to hydropower it is often the hydropower part aspect that forms the financial basis for the project. Other purposes of a reservoir than hydropower may be: • domestic and industrial supply • irrigation • flood control • navigation • recreation Sediment that deposit in a reservoir has a number of negative effects besides loss of storage capacity. Increased flood levels may be caused by deposition of sediment in the upstream end of the reservoir. (Webby et al, 1996). Intake works in the reservoir can be affected before the reservoir has lost any significant storage capacity. Downstream of a reservoir, the sediment transport regime in the river may be significantly altered as a large proportion of the sediment, and all the coarse, is trapped in the reservoir. Scouring of the riverbed is likely, which can cause failure of riverbanks and lowered water levels. Changed conditions in the river are likely to affect ecology (ICOLD 1985). Beaches and deltas will also be affected by reduced sediment feeding.

Sediment that is released from a reservoir can also cause problems. The negative consequences are mainly associated with the release of reservoir sediment into the river. A reservoir will affect the water discharge, so that discharge is more evenly distributed. Water may also be lost permanently, either to consumption and irrigation, or to evaporation from the reservoir surface. Both will reduce the overall sediment transporting capacity of the river and cause sediment aggregation. The sediment may also be contaminated with negative impacts where and when it is released.

In any study of the economic impacts of removal of sediment for a specific case as many as possible of the factors mentioned above should be included. As this was a general study, several simplifications had to be made: 1. Only the economic impacts caused by the loss of storage capacity are considered. 2. The value of water is assumed to be related only to hydropower generation.

138 7. applications and economic aspects

3. It is assumed that all sediment is removed from the live storage of the reservoir. 4. The sediment is assumed to be removed trough a horizontal pipeline, which can be achieved for example by use of the SPSS or SSS. These techniques are described in Chapters 4 and 5 and in Section 7.1.3.

7.2.2 Calculation of sediment transport capacity in a pipeline LIMIT DEPOSIT VELOCITY The experiments described in chapter 6 showed that Gillies’ correlation offered a good prediction of limit deposit velocity, VL. Gillies’ correlation can be programmed on a worksheet which also makes it easier to use for this study. In a real situation a velocity is normally selected that is slightly above V L, because this reduces the possibility of blocking. A velocity equal to 1,2-VL was therefore used for the pipe flow.

HEAD LOSS In Chapter 6 it was found that both the Two-layer model and the Durand- Condolios equation can predict head loss in a pipe satisfactorily. The main difference between the two is that the Two-layer model is more sensitive to grain size than the Durand-Condolios equation. For this study, the Two-layer model was selected.

7.2.3 Features of the hypothetical reservoir studied A hypothetical reservoir was studied. The reservoir was given properties typical of reservoirs subject to a monsoon climate in the foothills of the Himalayas, such as for example in Nepal. It thus has wet and dry seasons with most of the rain falling in the months of July, August and September. The reservoir is operated so that the whole of its live storage is used for electricity production once every dry season. Essential to these calculations is that the electricity price is assumed to be higher in the dry season, due to scarcity of water. Table 7-1 provides data that are constant for all cases.

139 7. applications and economic aspects

Table 7-1 Reservoir properties common to all cases CATCHMENT: Catchment area: 473 km2 Erosion: 5,000 t-km"2-yr" 1 Runoff: 1,000 mm-yr" 1 Average discharge, Qm: 15 m3-s"1 Annual discharge, Qa: 473-106 m3 Annual sediment load, Qs>a: 2,365,000 t-yr 1 SEDIMENT: Dry density of sediment deposits: 1,333 kg-m'3 Density of sediment: 2,650 kg-m'3 STORAGE RESERVOIR: Reservoir volume: 100-106 m3 Head for sediment transport: 150 m Capacity inflow ratio (CIR): 0.21 Trap efficiency: 93% OTHER VALUES: Lifetime of removal system: 20 yr Lifetime of cleared reservoir volume: 45 yr Electricity price, wet season: 2 cents-kWh" 1

7.2.4 Calculation for a basic case VALUE OF RECOVERED RESERVOIR VOLUME The economics of sediment removal were computed step by step for a basic case and were based on values given in Tables 7-1 and 7-2. An overall efficiency of the powerplant of 0,85 is assumed. The amount of electricity produced from each m3 is: lm3 • 432m • 0.85 • 3600 s/h • 9.81 m/s = 1.0 kWh/m 3

Annual deposition of sediment is:

0.93-2,365,0001 1,640,000m3 1.33 t/m3

It is further assumed that 91.5 % of the incoming sediment, equivalent to 1.5 mill. m3 (2 mill tonnes) is removed from the live storage of the reservoir annually. The extra production obtained in each dry season because of the increased reservoir volume is:

140 7. applications and economic aspects

1,500,000m3 • 1.0 kWh/mi = 1.5 • 106kWh = \.5GWh

It is assumed that 50 % of the water stored for the dry season could have been used for electricity production in the wet season. It is further assumed that the electricity price is 4 cents/kWh in the dry season. The value of the extra production during the dry season is therefore:

1.5 • 106 kWh • (4 - (2 • 0.5))centsjkWh = $45,000

The net present value of the removal of the sediment can be calculated by multiplying the annual recurring benefit by the inverse annuity discount factor, dfA, which is given as:

r

If the volume is used for 45 years and the discount rate is 7 %, the inverse annuity discount factor dfA = 13.6 and the reservoir volume recovered annually has a present value equal to: $45,000 • 13.6 = $612,000

COST OF REMOVAL The amount of sediment removed annually is 2.0 million tonnes and d50 = 0.12 mm. The length of the pipeline through which the sediment is transported is assumed to be 5,000 metres. The head is 150 metres, and the available energy gradient in the pipeline is thus 3.0 %. Computations using the Two-layer model show that a 460 mm pipeline can transport 1,314 tonnes/hour at this gradient. Thus 1,522 hours are required to remove the sediment at a water discharge rate in the pipeline of 0.55 m3/s. The amount of water used annually to transport sediment out of the reservoir is:

0.551 m3/s • 3600 s/h - 1522h/year = 3.02-10* m3

(which is 0.6% of total annual discharge.) It is assumed that 50 % of the water used for transport of sediment would otherwise have been discharged past the reservoir during floods. The cost of using water for sediment transport is therefore calculated as: 3.019 -10* m3 • 2 cents/m 3 • 0.5 = $30,190

141 7. applications ;and economic aspects

It is further estimated that the sediment removal system has annual operation and maintenance costs of $300.000.

The cost of a removal system is difficult to assess correctly. A simple way of assessing the cost is therefore used. Steel pipe with wall thickness = 2.5 % of pipe diameter is assumed, and the price is taken as 5.5 times a steel price of $500/tonnes (World Bank, 1997). The cost of the other equipment is arbitrarily set at $500,000 which give a total cost of the removal system:

(5,000m * $370/m) + $500,000 = $2.350.000

The annual cost of the investments is found by dividing the investment by the inverse annuity discount factor, dfA (lifetime of removal system is set to 20 years):

$2,350,000/10.6 = $221,700

The total annual cost is composed of cost of water, operation and maintenance cost and annual investment costs:

$30,190 + $300,000+ $221,700 = $551.890

NET BENEFIT OF REMOVAL SYSTEM The net annual benefit from the removal system is:

$612,000 - $551890 = $60.110

The net present value is found by multiplying the annual benefit by the inverse annuity discount factor, dfA:

10.6 $60.110 = $637.000

The internal rate of return of the project is 7.7 %. The internal rate of return is the rate of return that gives a net present value equal to zero.

7.2.5 Sensitivity to variation of input data The sensitivity of the net present value of the sediment removal system to variations in different factors is considered. For each case only one set of data is changed while the others are kept constant at the values given in Tables 7-1 and 7-2.. The range of variation is also given in Table 7-2.

142 7. applications and economic aspects

Table 7-2: Values that can be varied. Values used for the basic case are given. Values in brackets are ranges of data in the sensitivity analysis. VARIABLE VALUES Length of pipeline 5,000 m (1,500- 10,000) dso of sediment: 0,12 mm (0,04 - 0,5) Head for power generation: 432 m (300 - 1000) Electricity price, dry season: 4 c/kWh (3 - 7) Discount rate: 7% (3-10) COST OF REMOVAL SYSTEM: (D = pipeline diameter) Pipeline: (D/460 mm)2'$370/m Other equipment: (D/460 mm)-$500,000 Operation and maintenance: (D/460 mm)-$300,000/yr.

10000 J- 8000 • - 6000 4000 ■ - Basic case

-2000 ■ ■ -4000 ■ ■ -6000 1500 3000 4500 6000 7500 9000 Length of pipeline (m)

Figure 7-12: The net present value of a sediment removal system is calculated assuming different lengths of the pipeline. A shorter pipeline will give a higher energy gradient, so that a smaller diameter pipeline is needed. The amount of water used is also reduced.

10000 y 8000- 6000 - • 4000 • ■ Basic case

35 o 2000 - - 0) o

-2000 - ■ -4000 - - -6000

Grain size, d50 (mm)

Figure 7-13: The net present value of a sediment removal system is calculated assuming different grain sizes, d50. The grain size influences flow resistance and thus the size of the pipeline as well as amount of water used for sluicing.

143 7. applications and economic aspects

10000 a> 8000 § S 6000 Basic case ■£ “ 4000 $ O 2000

-2000 -4000 -6000 300 475 650 825 1( Head available for energy production (m)

Figure 7-14: The net present value of a sediment removal system is calculated assuming different heads available for power generation.

10000 -p 8000 -- 6000 -- 4000 - Basic case

2000 --

-2000 -4000 -- -6000 )3 0.04 0.05 0.06 0. Electricity price in dry season ($/kWh)

Figure 7-15: The net present value of a sediment removal system is calculated assuming a different electricity prices in the dry season.

10000 8000 g 6000 M 4000 Basic case o 2000

-2000 -4000 -6000

Discount rate (%)

Figure 7-16: The net present value of a sediment removal system is calculated assuming varying discount rate. A low discount rate increases the value of costs and benefits obtained in the future.

144 7. applications and economic aspects

7.2.6 Discussion It is important to note that several simplifications were made to make this study feasible. In particular the costs associated with a sediment removal system were assessed on a very rough basis. The study is therefore intended to provide a survey of factors that influence the economics of sediment removal, rather than predicting exact values for specific cases.

CONDITIONS FOR SEDIMENT TRANSPORT IN A PIPELINE The length of the pipeline (i.e. the energy gradient) and the grain size determine both how much water is needed for transport of sediment and the investments in piping and other equipment. For long pipelines and/or for large sediment sizes a larger-diameter pipeline and thus a much more costly sediment removal system is necessary, as shown in Figure 7-12 and 7-12.

THE VALUE OF WATER STORED IN THE RESERVOIR The value of the storage volume varies linearly with the head available for energy production and the price for electricity in the dry season, and therefore has a major influence on the economics of power generation. The value of the water used in this study is based on using of the stored water once a year. In a real case the water can be used several times a year but it is also possible that there are years where the storage volume is not fully exploited. Figure 7-14 and 7-14 show how the net present value can depend on the electricity price and head for power generation, that is, the value of the water.

THE DISCOUNT RATE The discount rate can be seen to have a major influence on the economics of the system, as shown in Figure 7-16. The discount rate used for the basic case is equal to the Norwegian discount rate of 7 % set by the Norwegian Government in 1978. This is well above the real rate of interest in Norway from 1946 - 1992 which was 1.4 %. It is therefore argued that a discount rate of 7 % is too high (Myhre 1995). Discounting may also be criticised for environmental reasons, the most important of these being (Myhre 1995):

1. Depletion of natural resources. 2. Obstacle for environmental investments. 3. Welfare of future generations. 4. Environmental risk. 5. Irreversibility.

One example of where normal discounting is not used is planting of trees in Norway. In an ordinary economic assessment this is not profitable at all since the

145 7. applications and economic aspects

discounted value of the trees 60 - 80 years from now is practically zero. Hence, “normal ’’ economic considerations are; not sufficient for these applications.

NON-ECONOMICAL COSTS AND BENEFITS The non-economical costs or benefits from removing sediment from a reservoir have not been considered in this study. These costs and benefits are likely to add weight to the argument for removal of sediment from reservoirs, provided the consequences of sediment release are not significant.

FURTHER IMPROVEMENT OF CALCULATIONS Factors which could have affected the outcome of the calculations, but which have been ignored in this study, apart from the non-economical costs and benefits, are:

1. The time available for removal of sediment will affect both the size of the removal system, and the cost of operation 2. The size of the reservoir and the iimount of sediment removed annually will affect the economics. 3. It is assumed in the study that the sediment deposits in the live storage. In a new reservoir the percentage of sediment which deposits in the live storage is likely to be less than 100 %. However, as the dead storage is being filled, the portion will increase with time and eventually reach 100 %. 4. The benefits of avoiding rebuilding of intake works and other structures are not taken into account. 5. Annual sedimentation rates will always vary, and rates varying from 100,000 to over 4,000,000 tonnes/year have been reported for a reservoir (Ando et al, 1994). Uncertainty regarding sedimentation rates is likely to affect the economics. 6. The head available for sediment transport has not been studied. However, the outcome would be similar to what is found from the study of pipe length, as a reduced head gives a lower energy gradient, and thus a larger size pipe. 7. The influence of the selected method for computation of head loss and transport capacity was not studied in detail. For the basic case described, the Durand-Condolios equation predicts the pipe diameter almost similar to the Two-layer model. However, the Two-layer model must be expected to calculate a lower transport capacity than the Durand-Condolios equation when coarse sediment is studied. A more detailed study of sediment transport in pipes is provided in Chapter 6. 8. A comparison between pipeline and open-channel transport has not been made. As shown in Figures 7-1 and 7-2 open channel transport can be advantageous when the energy gradient is low, because a similar or even

146 7. applications and economic aspects

smaller diameter of pipe (or tunnel) flowing half full is needed. Open channel transport must in any case be expected to require less water, compared to pipeline transport.

SEDIMENT REMOVAL FROM SMALL RESERVOIRS Small reservoirs can be used to store water on a day-to-day basis. A discharge higher than that of the river can then be used for production of electricity during a limited period of the day. This can be of considerable value, as the demand for electricity is normally higher during the day.

Small reservoirs can sometimes be flushed by opening bottom gates and drawing down the water level. However, this loses water and interrupts the power supply. Often, only a portion of the reservoir is flushed so that much sediment remains in the reservoir. This is the case in Jhimruk (see Chapter 4) where sediment can only be removed from the river channel by flushing.

Removal of sediment from small (peaking) reservoirs can have a high value compared to larger reservoirs, because the increased reservoir volume obtained thus is used more often. A study of use of the SSS at Jhimruk Hydropower Plant in Nepal (see Chapter 5 and Jacobsen (1997)) showed that the investment in the SSS was $1000. Because of the low labour costs sediment deposits could be removed at a cost of 38 cents per m3, at a rate of removal similar to what was obtained during the field experiments. Assuming that the volume regained was available in the dry season, and that it was used for peak production 79 times, the additional cost of peak production was found to be 1 cent/kWh. It should be noted that this reservoir was far from ideal with respect to sediment removal, as the sediment deposits are shallow and head across the dam is low.

7.2.7 Conclusions It is concluded that the benefits from increased dry-season power production can justify removal of sediment from a medium-sized reservoir. However, of more importance is the finding that the economics of such an undertaking are highly dependent on a number of technical and economic conditions, some of which have been identified and studied. The removal of sediment from small reservoirs can be highly beneficial, because of the frequency with which the reservoir volume is used. Several additional benefits apart from the purely economical aspects are likely to be obtained, adding to the arguments for implementing a sediment removal system.

147

8. Conclusions and recommendations

8. CONCLUSIONS AND RECOMMENDATIONS

8.1 Conclusions The objectives of this study were to study the problem of reservoir sedimentation and to investigate methods of removing of sediment from reservoirs. As conclusions are provided in each chapter, only the main conclusions will be given here.

• Reservoir sedimentation in many regions seriously affects the development and operation of reservoirs. Medium-sized reservoirs in particular are affected, and in many places such reservoirs are not feasible unless sediment can be removed efficiently.

• Sediment erosion and deposition in a reservoir can be modelled numerically, which permits efficient planning and operation of a sediment removal system.

• Methods that permit controlled suction of sediment and water into a pipeline have been developed. Laboratory and field experiments as well as field experience show promising results, and these methods may therefore provide efficient means for removal of sediment from reservoirs.

• Existing methods are found to provide reasonably good predictions of necessary velocities and head loss in sediment transporting pipes.

• An experiment comparing pipe and open-channel sediment transport has shown that sediment can be transported more efficiently in an open channel. A method for computation of open-channel sediment transport, that was derived on the basis of this experiment, has been proposed.

• The economics of sediment removal from reservoirs are found to be highly dependent o a number of technical and economic conditions, some of which are identified and discussed.

149 8. Conclusions and recommendations

8.2 Recommendations for future work Given the extent and magnitude of reservoir sedimentation, it is clear that this study only can provide a small piece of knowledge. The topic that is studied is of such a kind that few answers are final. Therefore, there is room for more work not only within the scope this thesis, but also as an extension of it.

Knowledge of the phenomenon is crucial, because only then can it be addressed correctly and with sufficient means. Studies of existing reservoirs combined with much more detailed maps of CSR than the one shown in Figure 2-11 can be useful tools in the planning of reservoirs.

Numerical modelling of flow of water and sediment is probably in its very beginning. The rapid developments in computer technology combined with improved models make increased benefits from numerical modelling highly probable.

Two techniques for the removal of seiiiment have been developed, the SPSS and SSS. Much work remains, not least field trials, before the full benefit of these techniques can be obtained. There is clearly room for the development of new techniques for sediment control, as well as for other approaches to mitigate the problem, such as reservoir operation, off-stream storage of water and watershed management.

Hydraulic sediment transport in pipes and open channels has been studied, and this seems to provide an efficient method by which sediment can be removed from reservoirs. The complexity of the topic, and the special characteristics of hydraulic sediment transport out of reservoirs, ensures that challenges will never be a limiting factor for anyone working in this field. Hydraulic sediment transport in open channels in particular is a field in which much work remains to be done.

150 References

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Ando, Nobuo et al (1994) Sediment removal project at Miwa Dam. 18. ICOLD Congress, Durban 1994. Asthana, B. N. and Chaturverdi, M. C. (1996) Reservoir sedimentation - a case study. Int. Conference on Reservoir Sedimentation, Fort Collins, USA, Sept 9. - 13.1996. Axelson, Walter (1967) The Laitaure delta. University of Uppsala. Basson, G. R. and Rooseboom A. (1996) Sediment pass-through operations in reservoirs. Int. Conference on Reservoir Sedimentation, Fort Collins, USA, Sept 9. - 13. 1996. Basson, G. R. et al (1996) Mathematical Modelling of Reservoir Flushing, Int Conference on Reservoir Sedimentation, Fort Collins, USA, Sept 9. - 13. 1996. Borland, W.M. (1971) “Reservoir Sedimentation ” in River Mechanics: (H. Shen. Editor) Water Res. Publication, Fort Collins. Bruk, Stevan (1985) (Rapporteur) Methods of computing sedimentation in lakes and reservoirs. Chap. 4: Methods of preserving reservoir capacity. Contr. to the Int. Hydrological Programme, IHP - II Project (UNESCO - 1985). Bruk, Stevan (1996) Reservoir sedimentation and sustainable management of water resources - the international perspective. Int. Conference on Reservoir Sedimentation, Fort Collins, USA, Sept 9. - 13. 1996.

Brune, Gunnar M. (1953) Trap Efficiency of Reservoirs, Transactions of the American Geophysical Union Volume 34, Number 3, June 1953, pp.407-418. Bulgurlu, B (1977) A study of sediment transport in River Gaula. Doctoral Thesis, Division of Hydraulic and Sanitary Engineering, the University of Trondheim, the Norwegian Institute of Technology. Central Water Commission (1996) Experience in sedimentation of Indian reservoirs and current scenario. Int. Conference on Reservoir Sedimentation, Fort Collins, USA, Sept 9.- 13. 1996. Chen (1975) Design of Sediment Retention Curve, Urban Hydrology and Sediment Control Symposium, Lexington USA, 1975. Chen, C. L. (1996) Modelling sediment and phosphorus transport in Te Chi Reservoir watershed. Int. Conference on Reservoir Sedimentation, Fort Collins, USA, Sept 9.- 13. 1996.

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156 Appendix

157 158 > Annual 13 Annual sediment Measured CSR predicted id runoff, W transport CSR from map River Resevoir Country (m3/yr) (t/yr) (CIR=0.1) (CIR=0.1) Reference § Oued Agrioun Iril Emda Algeria 210.0E+6 3.3-E+6 8 0-10 Bruk (1985) & Nile Lake nasser Egypt 82.0-E+9 124.0-E+6 88 25-50 El-Moattassem and Shalaby (1996) Blue Nile Roseires Sudan 50.0E+9 93.0-E+6 71 50-100 Pemberton (1996) > Hanjiang Danjiankou China 39.4E+9 115.0E+6 45 10-25 Yang et at (1996)

Yellow River Sanmenxia China 41.0-E+9 1.4-E+9 4 0-10 Yuqian (1996) Appendix Yellow River Lijiaxia China 28.6E+9 95.4E+6 40 10-25 Jiao and Li (1990) r Hutuo Hushan China 5.9E+6 265.0E+3 3 0-10 Bruk (1985) A:

Yongding River Guanting China 1.4-E+9 62.1-E+6 3 0-10 Qishun et al (1996) Reservoir Panchet Hill Damodar India 5.4-E+9 8.8-E+6 81 50-100 Hasan (1996) I a Betwa Matatila India 6.0-E+9 15.8E+6 50 50-100 Asthana and Chaturverdi (1996)

Tungabadhra Tungabadhra India 11.5E+9 20.4E+6 74 25-50 Hasan (1996) I data Bhakra Sutlej India 24.9-E+9 46.8E+6 71 10-25 Hasan (1996) Mahanadi Hirakud India 35.2-E+9 74.2E+6 63 50-100 Misra and panda (1996) Veeranam India 75.0E+6 323.6E+3 31 >100 Moham and Arumugam (1996) Krishnagiri India 308.4-E+6 1.0E+6 39 50-100 Moham and Arumugam (1996) Kulekhani Kulekhani Nepal 137.4E+6 1.6E+6 12 10-25 Sthapit (1996) Indus Tarbela Pakistan 71.5E+9 397.4E+6 24 10-25 Fox and Tariq (1996) Da Jia River Te Chi R. Taiwan 1.2-E+9 1.5E+6 108 >100 Chen (1996) Bayindir Turkey 14.0E+6 140.0E+3 13 25-50 Gpgus and Yalcinkaya (1992) Yavlac Turkey 26.6E+6 314.8-E+3 11 25-50 G0gus and Yalcinkaya (1992) Annual Annual sediment Measured CSR predicted runoff, W transport CSR from map River Resevoir Country (m3/yr) (Vyr) (CIR=0.1) (CIR=0.1) Reference Karamanli Turkey 32.8E+6 296.8-E+3 15 25-50 G0gus and Yalcinkaya (1992) Buldan Turkey 36.0-E+6 1.2-E+6 4 25-50 Gpgus and Yalcinkaya (1992) Kesikkppru Turkey 72.0E+6 1.1 E+6 8 0-10 G0gus and Yalcinkaya (1992) Selevir Turkey 144.4E+6 1.4.E+6 14 25-50 G0gus and Yalcinkaya (1992) Appendix Cubuki Turkey 168.0E+6 421.5E+3 53 25-50 G0gus and Yalcinkaya (1992) Kemer Turkey 620.0E+6 7.7-E+6 11 25-50 G0gus and Yalcinkaya (1992)

Dcm; ilv0pru Turkey 1.3-E+9 19.1 Efu 9 25-50 U0gus and Yalcinkaya (1992) A:

Reservoir Seyhan Turkey 3.9-E+9 13.9 E+6 37 25-50 G0gus and Yalcinkaya (1992) Hirfanli Turkey 5.2E+9 130.4 E+6 5 0-10 G0gus and Yalcinkaya (1992)

Tedzen Turkm. Tedzen 700.0-E+6 10.8-E+6 9 10-25 Bruk(1985) data Mima Botonega Croatia 30.6-E+6 106.7-E+3 38 >100 Josip (1996) River Aire Av, 5 res. England 1.7 E+6 770.1-E+0 299 >100 White et al (1996) Lech Fargegensee Germany 1.8-E+9 349.9E+3 689 >100 Bechteler and Nujic (1996) Danube Iron gates Rom./Yug 174.113+9 32.0-E+6 721 >100 Focsa(1980) Colorado Lake mead USA 4.9E+9 155.0 E+6 4 0-10 Bruk (1985) Clutha L.Roxburgh N.Zealand 16.7E+9 2.5E+6 878 >100 Webby et al (1996) Appendix B: Measuring methods

APPENDIX B: MEASURING METHODS

Measurement of flow Volume-time method: The flow was measured by taking the time required to fill a 70 litre bucket with a measured volume of water or sediment-water mixture. The volume was measured by observing litre marks on a 701 bucket. The outlet pipe could easily be shifted from one side to another, thus pointing the nozzle into or outside of the bucket. In this way a sharp distinction could be made between when water was filled in the bucket and not. A stop-watch was used to take the time.

Electromagnetic flowmeter The flow was measured by using a 2” electromagnetic flowmeter, type Slurry- Magmaster. The flowmeter is based on Faraday’s law of induction. The fluid acts as a conductor moving in a magnetic field, creating a voltage. This flowmeter is designed to measure slurries with high solids content, and has a claimed accuracy of 0.15 %. The flow was determined as the average of the 10 flowmeter readings made at each experimental run.

Velocity Knowing the flow of water or sediment-water mixture, continuity gives the velocity in a pipe or an open channel where cross section of flow is known.

Measurement of energy gradient in pipe Pressure tap method Thin transparent plastic tubes were attached to pressure taps on the outlet pipe. The plastic tubes were connected to vertical transparent pipes mounted on a board with a centimetre-scale on which the pressure could be observed. As the velocity head is constant throughout the outlet pipe the energy gradient of the sand-water mixture, im, is calculated as:

(h A -Iib)

h A observed water level in tube connected to point A h B observed water level in tube connected to point B 1AB distance between points A and B on outlet pipe.

161 Appendix B: Measuring methods

The sediment Shape factor definition

Fs = a/Vbc a shortest axis b medium axis c longest axis

Measurement of sediment concentration Constant volume - weight difference method Sediment concentration was measured by using a specially made container with a volume of 10 litres, made of 10 mm acrylic plastic. The container lid had a small hole for aeration, so that all air could be evacuated and complete filling obtained. The 10 litre container filled with clear water was weighed. Next, the container was filled with all the sand from the (50-70 litre) sample and water and weighed again. A mechanical balance with a 10 gram accuracy was used. The sediment concentration by volume, Cv, is calculated as follows:

1 = (wB.S+W -W;B,W )' (?s-Yw) VSample

WB S+w weight of container with water and sand WBW weight of container with water volume of sample

Measurement of sediment concentration. All the sand from the sample is transferred to a 10 litre container that is completely filled with water and weighed. The 10 litre container is shown as a cross section.

162 Appendix C: Experimental results

APPENDIX C: EXPERIMENTAL RESULTS

Experiment with Slotted Pipe Sediment Sluicer. Diameter of outlet pipe = 44 mm

Slotted Energy pipe Slot width gradient Velocity Cons. diameter B in, V Cv Kind of Run no. Date (mm) (mm) m H20/m (m/s) (volume) flow 1.1 13/02/95 56 31 0.030 0.69 0.0078 bed 1.2 13/02/95 56 31 0.037 0.86 0.0094 bed 1.3 13/02/95 56 31 0.053 0.90 0.0168 bed 1.4 13/02/95 56 31 0.063 1.01 0.0219 bed 1.5 13/02/95 56 31 0.080 1.17 0.0279 bed 1.6 13/02/95 56 31 0.103 1.36 0.0391 het 1.7 13/02/95 56 31 0.120 1.38 0.0596 slid 1.8 14/02/95 56 31 0.133 1.49 0.0929 het 2.1 3/03/95 56 31 0.027 0.67 0.0056 bed 2.2 3/03/95 56 31 0.040 0.85 0.0103 bed 2.3 3/03/95 56 31 0.053 0.93 0.0147 bed 2.4 3/03/95 56 31 0.063 1.00 0.0234 bed 2.5 3/03/95 56 31 0.083 1.06 0.0303 bed 2.6 3/03/95 56 31 0.100 1.22 0.0432 het 2.7 3/03/95 56 31 0.117 1.28 0.0549 het 2.8 3/03/95 56 31 0.143 1.39 0.0823 het 3.1 27/02/95 56 31 0.030 0.67 0.0053 bed 3.2 27/02/95 56 31 0.045 0.76 0.0104 bed 3.3 27/02/95 56 31 0.060 0.89 0.0154 bed 3.4 27/02/95 56 31 0.070 0.99 0.0247 bed 3.5 27/02/95 56 31 0.085 1.12 0.0304 bed 3.6 27/02/95 56 31 0.100 1.25 0.0399 het 3.7 27/02/95 56 31 0.120 1.25 0.0538 het 3.8 27/02/95 56 31 0.140 1.30 0.0750 het 4.1 14/02/95 56 20 0.027 0.76 0.0052 bed 4.2 14/02/95 56 20 0.040 0.87 0.0059 bed 4.3 14/02/95 56 20 0.053 0.99 0.0142 bed 4.4 14/02/95 56 20 0.073 1.07 0.0183 bed 4.5 14/02/95 56 20 0.083 1.06 0.0290 bed 4.6 14/02/95 56 20 0.100 1.09 0.0368 bed 4.7 14/02/95 56 20 0.107 1.31 0.0537 het 4.8 14/02/95 56 20 0.140 1.57 0.0738 het 5.1 15/02/95 56 20 0.027 0.68 0.0064 bed 5.2 15/02/95 56 20 0.040 0.82 0.0105 bed 5.3 15/02/95 56 20 0.053 0.83 0.0139 bed 5.4 15/02/95 56 20 0.063 0.98 0.0237 bed 5.5 15/02/95 56 20 0.087 1.06 0.0310 bed

163 Appendix C: 1 Experimental results

5.6 15/02/95 56 20 0.103 1.21 0.0376 het Slotted Energy pipe Slot width gradient Velocity Cons. diameter B im V Cv Kind of Run no. Date (mm) (mm) m H20/m (m/s) (volume) flow 5.7 15/02/95 56 20 0.120 1.31 0.0498 het 5.8 15/02/95 56 20 0.143 1.60 0.0672 het 6.1 28/02/95 56 20 0.026 1.03 0.0041 bed 6.2 28/02/95 56 20 0.035 1.05 0.0053 bed 6.3 28/02/95 56 20 0.055 1.07 0.0144 bed 6.4 28/02/95 56 20 0.065 1.14 0.0223 bed 6.5 28/02/95 56 20 0.085 1.35 0.0281 bed 6.6 28/02/95 56 20 0.110 1.41 0.0377 het 6.7 28/02/95 56 20 0.120 1.59 0.0517 het 6.8 28/02/95 56 20 0.135 1.63 0.0720 het 7.1 17/02/95 56 15 0.027 0.68 0.0055 bed 7.2 17/02/95 56 15 0.037 0.90 0.0094 bed 7.3 17/02/95 56 15 0.053 0.92 0.0114 bed 7.4 17/02/95 56 15 0.063 0.98 0.0206 bed 7.5 17/02/95 56 15 0.077 1.09 0.0231 bed 7.6 17/02/95 56 15 0.090 1.27 0.0378 het 7.7 17/02/95 56 15 0.110 1.33 0.0506 het 7.8 17/02/95 56 15 0.133 1.43 0.0696 het 8.1 20/02/95 56 15 0.030 0.65 0.0023 bed 8.2 20/02/95 56 15 0.037 0.76 0.0099 bed 8.3 20/02/95 56 15 0.050 0.97 0.0158 bed 8.4 20/02/95 56 15 0.070 1.04 0.0213 bed 8.5 20/02/95 56 15 0.083 1.07 0.0256 bed 8.6 20/02/95 56 15 0.100 1.31 0.0394 het 8.7 20/02/95 56 15 0.110 1.36 0.0545 het 8.8 20/02/95 56 15 0.137 1.42 0.0675 het 9.1 1/03/95 56 15 0.030 0.74 0.0026 bed 9.2 1/03/95 56 15 0.035 0.97 0.0106 bed 9.3 1/03/95 56 15 0.055 0.99 0.0129 bed 9.4 1/03/95 56 15 0.070 1.16 0.0207 bed 9.5 1/03/95 56 15 0.085 1.31 0.0294 bed 9.6 1/03/95 56 15 0.095 1.31 0.0401 het 9.7 1/03/95 56 15 0.110 1.66 0.0492 het 9.8 1/03/95 56 15 0.135 2.04 0.0540 het 10.1 20/02/95 56 11 0.027 0.71 0.0020 bed 10.2 20/02/95 56 11 0.037 0.90 0.0072 bed 10.3 20/02/95 56 11 0.057 1.09 0.0134 bed 10.4 20/02/95 56 11 0.067 1.19 0.0181 bed 10.5 20/02/95 56 11 0.083 1.36 0.0256 slid 10.6 20/02/95 56 11 0.097 1.54 0.0345 het 10.7 20/02/95 56 11 0.103 1.64 0.0463 het 10.8 20/02/95 56 11 0.137 1.72 0.0707 het 11.1 21/02/95 56 11 0.027 0.68 0.0032 bed 11.2 21/02/95 56 11 0.040 0.94 0.0102 bed

164 Appendix C: Experimental results

11.3 21/02/95 56 11 0.053 1.13 0.0155 bed Slotted Energy pipe Slot width gradient Velocity Cons. diameter B V Cv Kind of Run no. Date (mm) (mm) m H20/m (m/s) (volume) flow 11.4 21/02/95 56 11 0.063 1.21 0.0181 bed 11.5 21/02/95 56 11 0.077 1.37 0.0283 slid 11.6 21/02/95 56 11 0.090 1.52 0.0378 het 11.7 21/02/95 56 11 0.110 1.67 0.0504 het 11.8 21/02/95 56 11 0.133 1.67 0.0724 het 12.1 1/03/95 56 11 0.035 0.82 0.0059 bed 12.2 1/03/95 56 11 0.040 1.03 0.0087 bed 12.3 1/03/95 56 11 0.055 1.10 0.0171 bed 12.4 1/03/95 56 11 0.065 1.19 0.0216 bed 12.5 1/03/95 56 11 0.080 1.25 0.0297 bed 12.6 1/03/95 56 11 0.095 1.45 0.0367 het 12.7 1/03/95 56 11 0.120 1.59 0.0497 het 12.8 1/03/95 56 11 0.135 1.83 0.0668 het 13.1 22/02/95 56 8 0.027 0.79 0.0061 bed 13.2 22/02/95 56 8 0.040 1.00 0.0087 bed 13.3 22/02/95 56 8 0.050 1.30 0.0132 bed 13.4 22/02/95 56 8 0.070 1.32 0.0175 bed 13.5 22/02/95 56 8 0.077 1.57 0.0258 bed 13.6 22/02/95 56 8 0.093 1.69 0.0320 het 13.7 22/02/95 56 8 0.107 1.81 0.0403 het 13.8 22/02/95 56 8 0.127 1.90 0.0586 het 14.1 22/02/95 56 8 0.030 0.86 0.0021 bed 14.2 22/02/95 56 8 0.043 1.07 0.0098 bed 14.3 22/02/95 56 8 0.057 1.17 0.0121 bed 14.4 22/02/95 56 8 0.063 1.38 0.0191 bed 14.5 22/02/95 56 8 0.077 1.68 0.0196 slid 14.6 22/02/95 56 8 0.090 1.70 0.0340 het 14.7 22/02/95 56 8 0.110 1.71 0.0450 het 14.8 23/02/95 56 8 0.123 1.97 0.0486 het 16.1 9/03/95 71 37 0.033 1.13 0.0044 het 16.2 9/03/95 71 37 0.047 1.36 0.0081 het 16.3 9/03/95 71 37 0.060 1.54 0.0151 het 16.4 9/03/95 71 37 0.073 168 0.0197 het 16.5 9/03/95 71 37 0.087 1.78 0.0260 het 16.6 9/03/95 71 37 0.100 1.91 0.0325 het 16.7 9/03/95 71 37 0.110 2.06 0.0389 het 16.8 9/03/95 71 37 0.130 2.25 0.0443 het 17.1 9/03/95 71 37 0.035 1.10 0.0044 het 17.2 9/03/95 71 37 0.045 1.32 0.0078 het 17.3 9/03/95 71 37 0.060 1.47 0.0145 het 17.4 9/03/95 71 37 0.075 1.65 0.0194 het 17.5 9/03/95 71 37 0.087 1.76 0.0239 het 17.6 9/03/95 71 37 0.098 1.90 0.0310 het 17.7 9/03/95 71 37 0.112 2.07 0.0383 het

165 Appendix C: Experimental results

17.8 9/03/95 71 37 0.132 2.28 0.0462 het Slotted Energy pipe Slot width gradient Velocity Cons. diameter B im V Cv Kind of Run no. Date (mm) (mm) m H20/m (m/s) (volume) flow 18.1 8/03/95 71 31 0.032 1.12 0.0015 het 18.2 8/03/95 71 31 0.045 1.33 0.0058 het 18.3 8/03/95 71 31 0.057 1.52 0.0115 het 18.4 8/03/95 71 31 0.068 1.68 0.0170 het 18.5 8/03/95 71 31 0.083 1.78 0.0217 het 18.6 8/03/95 71 31 0.097 1.97 0.0263 het 18.7 8/03/95 71 31 0.110 2.11 0.0302 het 18.8 8/03/95 71 31 0.130 2.30 0.0392 het 19.1 7/03/95 71 31 0.033 1.10 0.0030 het 19.2 7/03/95 71 31 0.043 1.24 0.0076 het 19.3 7/03/95 71 31 0.055 1.56 0.0112 het 19.4 7/03/95 71 31 0.067 1.65 0.0156 het 19.5 7/03/95 71 31 0.082 1.80 0.0223 het 19.6 7/03/95 71 31 0.100 1.95 0.0313 het 19.7 7/03/95 71 31 0.113 2.14 0.0363 het 19.8 7/03/95 71 31 0.127 2.27 0.0454 het 20.1 10/03/95 71 20 0.033 1.17 0.0017 het 20.2 10/03/95 71 20 0.045 1.35 0.0059 het 20.3 10/03/95 71 20 0.057 1.54 0.0097 het 20.4 10/03/95 71 20 0.073 1.69 0.0157 het 20.5 10/03/95 71 20 0.083 1.83 0.0186 het 20.6 10/03/95 71 20 0.097 2.02 0.0213 het 20.7 10/03/95 71 20 0.110 2.16 0.0261 het 20.8 10/03/95 71 20 0.127 2.30 0.0345 het 21.1 10/03/95 71 20 0.033 1.13 0.0009 het 21.2 10/03/95 71 20 0.047 1.32 0.0062 het 21.3 10/03/95 71 20 0.057 1.54 0.0124 het 21.4 10/03/95 71 20 0.072 1.71 0.0150 het 21.5 10/03/95 71 20 0.087 1.90 0.0202 het 21.6 10/03/95 71 20 0.097 2.05 0.0258 het 21.7 10/03/95 71 20 0.107 2.10 0.0312 het 21.8 10/03/95 71 20 0.123 2.29 0.0337 het 22.1 10/03/95 71 15 0.032 1.15 0.0031 het 22.2 10/03/95 71 15 0.045 1.40 0.0045 het 22.3 10/03/95 71 15 0.057 1.63 0.0062 het 22.4 10/03/95 71 15 0.073 1.74 0.0138 het 22.5 10/03/95 71 15 0.083 1.89 0.0173 het 226 10/03/95 71 15 0.097 2.00 0.0201 het 22.7 10/03/95 71 15 0.108 2.22 0.0212 het 22.8 10/03/95 71 15 0.127 2.37 0.0247 het 23.1 10/03/95 71 15 0.033 1.18 0.0012 het 23.2 10/03/95 71 15 0.047 1.39 0.0061 het 23.3 10/03/95 71 15 0.058 1.58 0.0080 het 23.4 10/03/95 71 15 0.068 1.75 0.0116 het

166 Appendix C: Experimental results

23.5 10/03/95 71 15 0.083 1.90 0.0160 het Slotted Energy pipe Slot width gradient Velocity Cons. diameter B im V Cv Kind of Run no. Date (mm) (mm) m H20/m (m/s) (volume) flow 23.6 10/03/95 71 15 0.097 2.02 0.0182 het 23.7 10/03/95 71 15 0.110 2.23 0.0204 het 23.8 10/03/95 71 15 0.122 2.39 0.0221 het 24.1 13/03/95 71 8 0.033 1.20 0.0004 het 24.2 13/03/95 71 8 0.047 1.43 0.0031 het 24.3 13/03/95 71 8 0.057 1.61 0.0045 het 24.4 13/03/95 71 8 0.072 1.78 0.0088 het 24.5 13/03/95 71 8 0.083 1.97 0.0084 het 24.6 13/03/95 71 8 0.097 2.13 0.0042 het 24.7 13/03/95 71 8 0.107 2.24 0.0144 het 24.8 13/03/95 71 8 0.122 2.40 0.0158 het 25.1 13/03/95 71 8 0.035 1.19 0.0005 het 25.2 13/03/95 71 8 0.047 1.40 0.0044 het 25.3 13/03/95 71 8 0.058 1.62 0.0049 het 25.4 13/03/95 71 8 0.070 1.76 0.0092 het 25.5 13/03/95 71 8 0.083 1.93 0.0123 het 25.6 13/03/95 71 8 0.095 2.14 0.0026 het 25.7 13/03/95 71 8 0.108 2.27 0.0102 het 25.8 13/03/95 71 8 0.123 2.39 0.0147 het 26.1 13/03/95 71 8 0.033 1.17 0.0025 het 26.2 13/03/95 71 8 0.047 1.42 0.0020 het 26.3 13/03/95 71 8 0.057 1.63 0.0062 het 26.4 13/03/95 71 8 0.070 1.80 0.0082 het 26.5 13/03/95 71 8 0.083 1.95 0.0100 het 26.6 13/03/95 71 8 0.097 2.13 0.0082 het 26.7 13/03/95 71 8 0.110 2.27 0.0130 het 26.8 13/03/95 71 8 0.115 2.44 0.0126 het 27.1 24/05/95 44 25 0.027 0.40 0.0053 bed 27.2 24/05/95 44 25 0.043 0.48 0.0145 bed 27.3 24/05/95 44 25 0.053 0.54 0.0176 bed 27.4 24/05/95 44 25 0.073 0.64 0.0294 bed 27.5 24/05/95 44 25 0.083 0.74 0.0370 bed 27.6 24/05/95 44 25 0.100 0.76 0.0490 bed 27.7 24/05/95 44 25 0.117 0.82 0.0575 bed 27.8 24/05/95 44 25 0.133 0.87 0.0619 bed 29.1 8/05/91 44 15 0.025 0.49 0.0093 bed 29.2 8/05/91 44 15 0.040 0.72 0.0089 bed 29.3 8/05/91 44 15 0.053 0.62 0.0213 bed 29.4 8/05/91 44 15 0.070 0.68 0.0206 bed 29.5 8/05/91 44 15 0.083 0.79 0.0352 bed 29.6 8/05/91 44 15 0.097 0.90 0.0442 bed 29.7 8/05/91 44 15 0.113 1.02 0.0595 bed 29.8 8/05/91 44 15 0.133 1.13 0.0680 bed 30.1 8/05/91 44 15 0.028 0.43 0.0050 bed

167 Appendix C: Experimental results

30.2 8/05/91 44 15 0.040 0.58 0.0137 bed Slotted Energy pipe Slot width gradient Velocity Cons. diameter B im V Cv Kind of Run no. Date (mm) (mm) m H20/m (m/s) (volume) flow 30.3 8/05/91 44 15 0.057 0.60 0.0196 bed 30.4 8/05/91 44 15 0.067 0.72 0.0261 bed 30.5 8/05/91 44 15 0.080 0.80 0.0341 bed 30.6 8/05/91 44 15 0.097 0.88 0.0426 bed 30.7 8/05/91 44 15 0.117 0.97 0.0636 bed 30.8 8/05/91 44 15 0.133 1.13 0.0710 bed 31.1 4/05/95 44 8 0.027 0.62 0.0048 bed 31.2 4/05/95 44 8 0.037 0.65 0.0108 bed 31.3 4/05/95 44 8 0.053 0.69 0.0164 bed 31.4 4/05/95 44 8 0.067 0.80 0.0283 bed 31.5 4/05/95 44 8 0.080 0.87 0.0314 bed 31.6 4/05/95 44 8 0.103 0.97 0.0479 bed 31.7 4/05/95 44 8 0.117 089 0.0678 bed 31.8 4/05/95 44 8 0.130 1.01 0.0730 bed 31.9 4/05/95 44 8 0.123 1.02 0.0680 bed

168 Appendix C: Experimental results

Experiment with Saxophone Sediment sluicer Outlet pipe diameter = 60 mm

extra Energy Pipe D Bottom water gradient, velocity Kind Vel. Run Saxoph. slot with (%of dso im V cv of dev, no. (mm) (mm) cr.sect) (mm) (mH,0/m) (m/s) (volume) flow s 1.1 60 20*80 * 25 1.2 0.028 1.06 0.0049 bed 1.2 60 20* 80* 25 1.2 0.039 1.29 0.0090 bed 1.3 60 20*80 * 25 1.2 0.048 1.43 0.0119 bed 2.1 60 40 75 1.2 0.045 1.67 0.0005 het 2.2 60 40 50 1.2 0.045 1.65 0.0014 het 2.4 60 40 37 1.2 0.045 1.51 0.0077 het 2.6 60 40 37 1.2 0.030 1.30 0.0031 het 2.7 60 40 37 1.2 0.057 1.60 0.0137 het 3.1 80 40 0 1.2 0.045 1.61 0.0051 het 4.1 70 40 29 1.2 0.045 1.66 0.0024 het 4.2 70 40 22 1.2 0.045 1.59 0.0054 het 4.3 70 40 15 1.2 0.047 1.55 0.0098 het 5.1 70 40 0 1.2 0.056 1.43 0.0118 bed 0.25 5.2 70 40 7 1.2 0.051 1.50 0.0104 het 0.11 5.3 70 40 4 1.2 0.051 1.39 0.0118 bed 0.34 5.4 70 40 7 1.2 0.049 1.44 0.0128 slid 0.19 5.5 70 40 7 1.2 0.050 1.43 0.0040 het 0.04 5.6 70 40 7 1.2 0.062 1.39 0.0215 bed 0.48 6.1 60 23 7 1.2 0.051 1.01 0.0160 bed 0.09 6.2 60 23 15 1.2 0.052 1.17 0.0155 bed 0.13 6.3 60 23 22 1.2 0.050 1.33 0.0126 bed 0.09 6.4 60 23 29 1.2 0.050 1.44 0.0134 slid 0.05 7.1 70 23 48 0.6 0.047 1.50 0.0078 bed 0.1 7.2 70 23 48 0.6 0.051 1.58 0.0089 bed 0.07 8.1 80 5 0 0.6 0.049 1.56 0.0098 slid 0.04 8.2 80 10 0 0.6 0.052 1.42 0.0115 het 0.08 8.3 80 10 25 0.6 0.049 1.59 0.0077 het 0.06 8.4 80 5 25 0.6 0.049 1.68 0.0062 het 0.06 8.5 80 20 25 0.6 0.049 1.61 0.0080 het 0.06 8.6 80 40 25 0.6 0.050 1.48 0.0094 bed 0.09 8.7 80 40 25 0.6 0.061 1.61 0.0152 bed 0.04 8.8 80 40 25 0.6 0.041 1.26 0.0088 bed 0.05 8.9 80 65 25 0.6 0.050 1.43 0.0089 bed 0.07

169 Appendix C: Experimental results

Experiment comparing (60 mm) pipe and (90 mm) open-channel sediment transport

Comparing flow in horisontal pipe at optimum conditions with flow in inclined flume. Pipe Flume Serial Cons. Velocity En. grad Flow Velocity gradient Flow 2.1 0.005 1.20 0.031 het 2.08 0.070 het 2.1 0.005 1.21 0.031 het 1.89 0.060 het 2.1 0.005 1.22 0.030 het 1.77 0.050 het 2.1 0.005 1.22 0.030 het 1.63 0.040 het 2.1 0.005 1.20 0.031 het 1.44 0.030 het 2.1 0.005 1.21 0.030 het 1.30 0.025 het 2.1 0.004 1.22 0.029 het 1.19 0.020 het 2.1 0.005 1.23 0.030 het 1.11 0.018 slid 2.1 - 1.21 0.030 het - 0.016 dep 2.1 - 1.22 0.030 het 1.08 0.017 dep 2.2 0.010 1.47 0.045 slid 2.13 0.070 het 2.2 0.010 1.47 0.045 slid 2.02 0.060 het 2.2 0.010 1.46 0.045 slid 1.89 0.050 het 2.2 0.010 1.47 0.045 slid 1.74 0.040 het 2.2 0.010 1.46 0.045 slid 1.50 0.030 het 2.2 - 1.45 0.045 slid 1.46 0.029 het 2.2 - 1.47 0.045 slid 1.39 0.028 slid 2.2 - 1.46 0.045 slid 1.37 0.027 slid 2.2 0.010 1.49 0.045 slid 1.36 0.026 dep 2.2 - 1.48 0.045 slid - 0.025 dep 2.3 0.018 1.63 0.060 slid 2.08 0.070 het 2.3 0.016 1.63 0.060 slid 1.94 0.060 het 2.3 0.017 1.64 0.060 slid 1.84 0.050 het 2.3 0.016 1.63 0.060 slid 1.65 0.040 het 2.3 0.017 1.64 0.061 slid 1.52 0.038 slid 2.3 - 1.64 0.060 slid 1.44 0.037 dep 2.3 - 1.64 0.060 slid - 0.036 dep 2.4 0.026 1.73 0.075 slid 2.01 0.070 het 2.4 0.025 1.76 0.074 slid 1.96 0.060 het 2.4 0.025 1.76 0.076 slid 1.68 0.050 het 2.4 0.024 1.75 0.074 slid 1.64 0.048 slid 2.4 - 1.74 0.075 slid - 0.046 dep 2.4 0.023 1.75 0.075 slid 1.61 0.047 slid

Comparing flow in horisontal pipe at equal velocity and varying gradient/concentration with flow ir inclined flume. Pipe Flume Serial Cons. Velocity En. grad Flow Velocity gradient Flow 3.1 0.006 1.47 0.040 het 2.07 0.070 het 3.1 0.007 1.45 0.040 het 1.96 0.060 het

170 Appendix C: Experimental results

Pipe Flume Serial Cons. Velocity En. grad Flow Velocity gradient Flow 3.1 0.006 1.46 0.040 het 1.84 0.050 het 3.1 0.006 1.46 0.040 het 1.73 0.040 het 3.1 0.006 1.47 0.040 het 1.52 0.030 het 3.1 0.006 1.46 0.040 het 1.24 0.020 slid 3.1 - 1.47 0.040 het - 0.019 bed 3.2 0.013 1.47 0.050 slid 2.05 0.070 het 3.2 0.012 1.47 0.050 slid 1.93 0.060 het 3.2 0.012 1.48 0.050 slid 1.77 0.050 het 3.2 0.013 1.47 0.050 slid 1.63 0.040 het 3.2 - 1.47 0.050 slid - 0.030 bed 3.2 0.013 1.47 0.050 slid 1.42 0.032 slid 3.2 0.013 1.46 0.050 slid 1.36 0.031 slid 3.3 0.017 1.46 0.060 bed 1.99 0.070 het 3.3 0.017 1.48 0.060 bed 1.90 0.060 het 3.3 0.017 1.47 0.060 bed 1.73 0.050 het 3.3 0.017 1.48 0.060 bed 1.59 0.040 het 3.3 - 1.47 0.060 bed 1.53 0.038 slid

3.3 - 0.00 0.060 bed - 0.037 bed

Comparing pipe flow in horisontal pipe with flow in inclined flume. 100% (4) and 0 % (5) extra water. Pipe Flume Serial Cons. Velocity En. grad Flow Velocity gradient Flow 4.1 0.004 1.31 0.030 het 2.02 0.070 het 4.1 0.004 1.28 0.030 het 1.81 0.050 het 4.1 0.003 1.27 0.030 het 1.48 0.030 het 4.1 - 0.00 0.030 het - 0.016 bed 4.1 0.003 1.29 0.030 het 1.15 0.017 slid 4.2 0.007 1.52 0.045 het 2.06 0.070 het 4.2 0.008 1.53 0.045 het 1.83 0.050 het 4.2 0.007 1.56 0.045 het 1.52 0.030 het 4.2 - 1.56 0.045 het - 0.021 bed 4.2 0.006 1.57 0.045 het 1.28 0.022 slid 4.3 0.011 1.82 0.060 het 2.14 0.070 het 4.3 0.011 1.81 0.060 het 1.87 0.050 het 4.3 - 0.00 0.060 het - 0.030 bed 4.3 0.011 1.80 0.060 het 1.54 0.031 slid 4.4 0.013 2.13 0.075 het 2.26 0.070 het 4.4 0.014 2.11 0.075 het 1.99 0.050 het 4.4 0.019 2.03 0.075 het 1.65 0.039 slid 4.4 - 2.03 0.075 het - 0.038 bed 5.1 0.006 0.88 0.030 bed 1.78 0.070 het 5.1 0.005 0.89 0.030 bed 1.61 0.050 het 5.1 0.005 0.89 0.030 bed 1.34 0.030 slid 5.1 - 0.00 0.030 bed - 0.029 bed 5.2 0.012 1.06 0.045 bed 1.89 0.070 het

171 Appendix C: Experimental results

Pipe Flume Serial Cons. Velocity En. grad Flow Velocity gradient Flow 5.2 0.010 1.04 0.045 bed 1.63 0.050 bet 5.2 0.011 1.04 0.046 bed 1.53 0.040 slid 5.2 - 0.00 0.046 bed - 0.039 bed 5.3 0.016 1.16 0.060 bed 1.88 0.070 het 5.3 0.017 1.22 0.060 bed 1.68 0.050 het 5.3 - 1.19 0.060 bed - 0.045 bed 5.3 0.017 1.18 0.060 bed 1.58 0.046 slid 5.4 0.022 1.34 0.075 bed 1.90 0.070 het 5.4 0.024 1.36 0.076 bed 1.72 0.057 slid 5.4 - - 0.075 bed - 0.055 bed

Comparing optimum flow in inclined pipe with flow in inclined flume. Pipe Flume Serial Cons. Velocity En. grad Flow Velocity gradient Flow 7.1 0.006 1.16 0.030 slid 1.92 0.070 het 7.1 0.005 1.15 0.030 slid 1.73 0.050 het 7.1 0.005 1.14 0.030 slid 1.40 0.030 het 7.1 - 1.16 0.030 slid - 0.020 bed 7.1 0.006 1.16 0.030 slid 1.18 0.021 slid 7.2 0.011 1.36 0.045 slid 1.92 0.070 het 7.2 0.011 1.41 0.045 slid 1.78 0.050 het 7.2 - 1.41 0.045 slid - 0.029 bed 7.2 0.012 1.40 0.045 slid 1.39 0.030 slid 7.3 0.021 1.58 0.060 slid 1.97 0.070 het 7.3 0.020 1.59 0.060 slid 1.68 0.050 het 7.3 - 1.59 0.060 slid - 0.040 bed 7.3 0.020 1.61 0.060 slid 1.49 0.041 slid

172 Appendix C: Experimental results

Experiments with clear water in 60 mm pipe and 90 mm open channel

PiPe 0 pen channel Run no. Velocity Gradient Cr.sect of P-wet Rh Velocity S (m/s) Om) flow (mm2) (mm) (mm) (m/s) (-) 2 1.28 0.030 1772 108.7 16.31 2.04 0.070 2 1.29 0.031 2027 115.0 17.63 1.80 0.050 2 1.30 0.031 2288 121.2 18.88 1.60 0.035 2 1.31 0.031 2821 133.4 21.16 1.31 0.020 2 1.76 0.053 2288 121.2 18.88 2.17 0.070 2 1.77 0.053 2465 125.3 19.67 2.03 0.050 2 1.78 0.053 2732 131.4 20.80 1.84 0.035 2 1.78 0.053 3361 145.4 23.12 1.50 0.020 3 0.41 0.005 1370 97.9 13.99 0.85 0.015 3 0.89 0.016 2394 123.7 19.36 1.05 0.015 3 1.19 0.028 2929 135.8 21.57 1.15 0.015 3 1.48 0.039 3352 145.2 23.09 1.25 0.015 3 1.81 0.055 3764 154.4 24.37 1.36 0.015 3 1.80 0.055 3199 141.8 22.56 1.59 0.025 3 1.63 0.046 2992 137.2 21.81 1.54 0.025 3 1.21 0.027 2465 125.3 19.67 1.39 0.025 3 0.85 0.016 1941 112.9 17.20 1.24 0.025 3 0.48 0.006 1338 97.0 13.80 1.01 0.025 3 0.50 0.006 1182 92.4 12.79 1.20 0.040 3 0.98 0.019 1772 108.7 16.31 1.56 0.040 3 1.14 0.025 1950 113.1 17.24 1.65 0.040 3 1.51 0.040 2412 124.1 19.44 1.77 0.040 3 1.79 0.054 2723 131.1 20.76 1.85 0.040 3 1.77 0.052 2403 123.9 19.40 2.08 0.060 3 1.56 0.042 2175 118.5 18.35 2.03 0.060 3 1.16 0.025 1755 108.2 16.22 1.87 0.060 3 0.92 0.017 1450 100.1 14.48 1.79 0.060 3 0.56 0.008 1053 88.4 11.91 1.51 0.060 3 0.57 0.008 2140 117.7 18.18 0.76 0.010 3 0.87 0.016 2696 130.5 20.65 0.91 0.010 3 1.25 0.028 3487 148.2 23.53 1.01 0.010 3 1.53 0.041 3985 159.5 24.99 1.08 0.010 3 1.78 0.049 3370 145.6 23.15 1.49 0.010 4 0.43 0.000 2288 121.2 18.88 0.53 0.004 4 0.58 0.000 2288 121.2 18.88 0.72 0.008 4 0.78 0.000 2288 121.2 18.88 0.96 0.014 4 0.90 0.000 2288 121.2 18.88 1.12 0.019 4 111 0.000 2288 121.2 18.88 1.37 0.028 4 1.27 0.000 2288 121.2 18.88 1.57 0.036 4 1.45 0.000 2288 121.2 18.88 1.80 0.049 4 1.59 0.000 2288 121.2 18.88 1.97 0.060 4 1.77 0.000 2288 121.2 18.88 2.19 0.070

173 Appendix C: Experimental results

Run no. Velocity Gradient Cr.sect of P-wet Rh Velocity S (m/s) (im) flow (mm") (mm) (mm) (m/s) (-) 5 1.88 0.000 3091 139.4 22.18 1.72 0.035 5 1.76 0.000 3091 139.4 22.18 1.61 0.031 5 1.66 0.000 3091 139.4 22.18 1.52 0.028 5 1.50 0.000 3091 139.4 22.18 1.37 0.024 5 1.35 0.000 3091 139.4 22.18 1.23 0.019 5 1.19 0.000 3091 139.4 22.18 1.09 0.015 5 1.02 0.000 3091 139.4 22.18 0.93 0.011 5 0.79 0.000 3091 139.4 22.18 0.72 0.006 6 0.97 0.018 2821 133.4 21.16 0.97 0.010 6 1.12 0.022 2821 133.4 21.16 1.12 0.016 6 1.33 0.030 2821 133.4 21.16 1.33 0.022 6 1.51 0.039 2821 133.4 21.16 1.51 0.028 6 1.75 0.049 2821 133.4 21.16 1.75 0.035 6 1.88 0.056 2821 133.4 21.16 1.88 0.043 6 2.01 0.063 2821 133.4 21.16 2.02 0.054 7 0.82 0.013 2553 127.3 20.06 0.91 0.010 7 0.98 0.018 2553 127.3 20.06 1.08 0.015 7 1.12 0.023 2553 127.3 20.06 1.25 0.019 7 1.28 0.028 2553 127.3 20.06 1.42 0.025 7 1.45 0.033 2553 127.3 20.06 1.61 0.030 7 1.57 0.041 2553 127.3 20.06 1.74 0.035 7 1.76 0.051 2553 127.3 20.06 1.95 0.047 7 1.68 0.040 2553 127.3 20.06 1.86 0.042 7 1.90 0.058 2553 127.3 20.06 2.10 0.053 8 1.05 0.020 3091 139.4 22.18 0.96 0.010 8 1.21 0.027 3091 139.4 22.18 1.10 0.014 8 1.34 0.030 3091 139.4 22.18 1.22 0.017 8 1.49 0.037 3091 139.4 22.18 1.36 0.020 8 1.61 0.041 3091 139.4 22.18 1.48 0.024 8 1.72 0.048 3091 139.4 22.18 1.57 0.026 8 1.77 0.051 3091 139.4 22.18 1.62 0.028 8 1.84 0.054 3091 139.4 22.18 1.68 0.030 8 1.95 0.060 3091 139.4 22.18 1.78 0.033

174 Appendix C: Experimental results

Clear-water headless in 44 mm pipe

Run no. Date Velocity (m/s) Gradient (i) 1.2 14/03/95 1.47 0.047 1.3 14/03/95 1.66 0.058 1.4 14/03/95 1.86 0.070 1.5 14/03/95 2.00 0.083 1.6 14/03/95 2.19 0.097 1.7 14/03/95 2.34 0.110 1.8 14/03/95 2.44 0.123 2.2 6/03/95 1.37 0.038 2.3 6/03/95 1.60 0.052 2.4 6/03/95 1.78 0.062 2.5 6/03/95 1.90 0.073 2.6 6/03/95 2.10 0.087 2.7 6/03/95 2.18 0.098 2.8 6/03/95 2.34 0.112 3.1 15/03/95 1.26 0.036 3.2 15/03/95 1.02 0.025 3.3 15/03/95 0.82 0.017 3.4 15/03/95 0.62 0.011 3.5 15/03/95 0.74 0.014 3.6 15/03/95 0.96 0.021 3.7 15/03/95 1.14 0.030 3.8 15/03/95 1.22 0.034 3.9 15/03/95 1.63 0.055

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