Bedload is the sediment component that moves downstream by rolling or saltation. In rivers and streams where hydraulic conditions are generally unsteady (Lisle et al., 2000) and spatial substratum grain size variability is high (Dollar, 2002), transport rate is highly variable in space and time (Gomez, 1991; Batalla, 1997; Ferguson, 2003; Vericat & Batalla, 2007). Bedload discharge also depends on the supply of sediments within the catchment and lateral and longitudinal connectivity of the river (Dietrich et al., 1989; Hooke, 2003; Fryirs et al., 2007). The transport of substratum can be expressed as volumetric change in sediment budgets, transport rate at a point, cross-sectional discharge or distance travelled by individual particles. Techniques for measuring bedload transport are ideally non-intrusive, flexible and representative for different types of transport (Ergenzinger & de Jong, 2003). To date most stream ecologists have only been interested in qualitative measures of bed stability. At the single particle-scale, qualitative assessment might be sufficient, but for whole reaches bedload transport occurs on a continuous graduation. For stream ecologists, quantitative measures of bedload transport can act as a superior indicator for the level of bed stability, particularly if only partial mobilisation of the bed occurs.
Tracer particles. Tracers are well suited for the stochastic and spatially variable nature of bedload transport because they reflect the movement of individual particles of known characteristics (Wilcock, 1997). Marked or tagged natural particles and artificial tracers are used to assess step length of movement (e.g. Habersack, 2001), proportion of the bed surface entrained (e.g. Laronne & Duncan, 1992), transport behaviour (e.g. Gottesfeld & Tunnicliffe, 2003) and transport rate (e.g. Ergenzinger & Conrady, 1982), or as an indicator of bed stability (e.g. Death & Winterbourn, 1994). Further they could facilitate the measurement of recolonisation periods of individual particles.
Stones coated with ordinary paint or fluorescent dye placed on the riverbed are often employed by ecologists and hydrologists (Death & Winterbourn, 1994; Townsend, Scarsbrook & Doledec, 1997; Ferguson & Wathen, 1998; Death, 2002; Ergenzinger & de Jong, 2003; Death & Zimmermann, 2005), but they have the disadvantage of a low recovery rate because of burial (Table 4). To overcome this, metal bars (Laronne et al., 1992; Schmidt & Ergenzinger, 1992) or magnets (Hassan, Church & Schick, 1991; Laronne & Duncan, 1992; Bunte, 1996; Ferguson & Wathen, 1998) can be inserted into the particles and they are detected using a metal detector or a magnetometer respectively. Magnetic tracers usually have a larger detection range (McEwan, Habersack & Heald, 2001) than metal tracers. An easier but less durable alternative to the insertion of metal is the wrapping of stones with aluminium foil (Sear et al., 2003). The transport rate and transport behaviour of particles marked with magnets or stones containing magnetic minerals can be monitored with a bar equipped with electromagnetic coils across the stream (Ergenzinger, 1985; Carling et al., 1998; Froehlich, 2003) or with a longitudinal line of ‘Bed Movement Detectors’ (Gottesfeld & Tunnicliffe, 2003). The overpassing of a magnetic particle induces an electric signal which is stored with high temporal resolution. The calculation of bedload discharge is possible using dispersion models (Sear et al., 2000b).
Table 4. Methods for reach-scale tracking of tracer particles
|Method||Constraints||Detection depth||Recovery rate (%)||Relation to biological data and comments|
|Tracking of initially unembedded particles|
|Painted tracer (visual)||Armour layer, burial||Surface||15–60||Negative with periphyton biomass (Death & Zimmermann, 2005), negative linear with invertebrate species number and species richness (Death & Winterbourn, 1995; Death, 2002; Death & Zimmermann, 2005), quadratic with invertebrate taxon number (Townsend et al., 1997)|
|Metal tracer (passive)||Armour layer, particle size||0.5–1 m||50–90|| |
|Stones wrapped in aluminium foil(passive)||Armour layer||0.25 m|| || |
|Magnetic tracer (passive)||Armour layer, particle size||0.5–1 m, usually higher than with metal tracer||50–90|| |
|Transmitters (active)||Armour layer, particle size, battery, low conductivity||Shallow water||Up to 100||Life span: a few weeks to 10 months (size from 0.01 to 0.08 m respectively)|
|Radioactive tracer (passive)||Armour layer, environmental issues|| ||c. 5|| |
|Different lithology (visual)||Armour, burial||Surface||5–30|| |
|Artificial tracer (visual/passive)||Armour layer, representativeness of substratum||Variable||c. 35|| |
|DUMPLING (active)||Size (0.3 m), weight (37 kg)|| ||100|| |
|Tracking of initially embedded particles|
|Chiselled stones (visual)||Particle choice||Low||Low|| |
|Dyed quick concrete mix (visual)||Particle choice||Surface|| ||Distribution of invertebrates (Barquin & Death, 2006)|
Radioactive tracers (e.g. 137Cs) are an alternative to tags because they do not change density or centre of gravity (e.g. Bartnik, Madeyski & Michalik, 1992). However, they are no longer widely applied because of environmental issues (Ergenzinger & de Jong, 2003). The employment of tracers of differing lithology from the natural substratum (Mosley, 1978; Kondolf & Matthews, 1986) provides an effective and easy measure for event-based distribution of transport length, although recovery rate is low.
For the in situ marking of substratum particles Downes et al. (1998) and Matthaei, Peacock & Townsend (1999a) used chisels and drills with long drill bit extensions, but relocation is difficult and embeddedness may be disturbed during the marking process. Thus this method is more suitable for the qualitative measurement of entrainment. Barquin & Death (2006) used dyed quick curing concrete mix to mark embedded stones.
Artificial stones provide an alternative to natural particles and also provide the opportunity to examine the influence of shape on transport length (Schmidt & Ergenzinger, 1992). The use of cast aluminium forms avoids the insertion of metal bars in pebbles (Sear et al., 2003). The collection of complex information about particle transport is also possible with artificial boulders like the DUMPLING (Ergenzinger & de Jong, 2003), although its size and weight restricts its application to bouldery streams.
The measurement of bedload transport with tracers provides comparable results to direct measures but requires less effort and avoids large-scale intervention in the stream bed. For low transport rates, tracers are likely to be more accurate (Wilcock, 1997). However, the dominating influence of bed structure and channel morphology on the distribution of tracer stones and the weak relationship with stream power (Kondolf & Matthews, 1986; Hassan, Church & Ashworth, 1992) suggests that short-term studies with tracers are not sufficient to compute rates of bedload transport. In contrast, shorter-term studies are more suitable for investigating the movement of surface particles because the transport rate of tracer particles decreases because of vertical mixing (burial) and storage in less active zones of the system (e.g. floodplain and bars) (Ferguson et al., 2002). If particles have to be removed from the stream for marking, bed structures and imbrication are destroyed and tracer particles placed on the bed surface may not represent the size characteristics of the substratum (Downes et al., 1998; Biggs et al., 1999). Longer-term studies can account for this, but they do not provide information about the frequency and magnitude of single disturbance events. The subjective choice and the shape of particles, as well as their number, may bias the results of tracer experiments (Schmidt & Gintz, 1995; Duncan et al., 1999; Warburton & Demir, 2000; Ferguson & Hoey, 2002).
Nevertheless, a stability index derived from tracer experiments showed a strong negative relationship with invertebrate diversity and periphyton biomass (Death & Winterbourn, 1995; Death, 2002; Death & Zimmermann, 2005; Table 4). In situ marked stones were also used to identify stable stones that can serve as refugia during floods (Matthaei et al., 2000). They relate the shear forces to the local substratum and consequently provide a better estimate of bed stability than unembedded tracers (Downes et al., 1998; Matthaei et al., 1999a). In combination with a non-invasive detection technique, in situ marked particles may be highly appropriate for ecological studies. Along with the objectives of a study, selection of an optimal tracer technique should consider representation of the substratum, tracer recoverability, longevity, durability, possibility of explicit identification of particles as well as labour and cost efficiency (Sear et al., 2000b).
Bedload transport sampler and traps. The rate of bedload transport can be assessed with samplers and traps at various scales (Table 5). The most common handheld bedload transport samplers are of the pressure-difference type (Helley-Smith-, Vyzkum Ustav Vodohospodarsky (VUV)- and Arnhem sampler) with orifices up to 0.05 m2 (Leopold, 1992; Hoey, Cudden & Shvidchenko, 2001; Hardardottir & Snorrason, 2003). Their sampling efficiency usually varies between 30% and 70%, but can be up to 100% (Helley-Smith sampler) (Gomez, 1991). A common constraint of these samplers is that the opening area needs calibration for hydraulic and substratum conditions (Gomez, 1991) but, much more critically, the sampling scheme should be sufficient to account for the cross-sectional substratum variability of the reach and the temporal variability in bedload transport (Ergenzinger & de Jong, 2003). This requires adjustment of the sampling period and may result in large sampling efforts in wide rivers. Therefore, predictions of bedload transport based on sampler measurements are often not very accurate (uncertainty of ± 50%) (Wilcock, 2001). In conditions encountered in mountain streams (e.g. local high flow velocities and high surface roughness) bedload transport samplers are less applicable (Mizuyama, Fujita & Nonaka, 2003). Here portable net traps fixed to platforms on the stream bed may be used, delivering similar results to pit traps (Wilcock, 2001; Bunte & Abt, 2003; Bunte et al., 2004). Bedload samplers are not frequently employed by stream ecologists perhaps because of the mentioned constraints and inaccuracy. However, for small-scale, event-based studies they constitute a potentially valid option for direct measurement of bedload transport rate.
Table 5. Methods for the assessment of bedload transport
|Method||Scale||Constraints||Interference with substratum||Accuracy/relation to biological data|
|Pressure-difference sampler||Patch, short-term||Orifice area (up to 0.05 m2), upscaling to stream width||Low||Sampling efficiency usually 30–70%, can reach up to 100%, small volume|
|Birkbeck slot sampler||Patch/reach||Slot width, upscaling to stream width||High for installation||Continuous during smaller floods|
|Sediment trap||Cross-section, continuous|| ||High for installation||Sampling efficiency up to 100%|
|Acoustic sensors||Patch/reach||Calibration||Low – high for installation||Comparable accuracy as bedload traps (Downing et al., 2003)|
|ADCP||Patch/reach||Sandy substratum, high suspended load||None|| |
|Electronic momentum sensor||Patch||Calibration||Low||Measures a combination of particle size and speed (Richardson et al., 2003)|
|Piezoelectric sensors||Reach, long-term||Calibration||Low (installation)||Limited accuracy for single events (Rickenmann & McArdell, 2007)|
|Bedload transport formulae||Reach||Calibration site specific||Low (measurement of parameters)||Inaccurate for general application|
Slot traps of various dimensions, inserted into the river bed, are used in many parts of the world (Salehi, Lagace & Pesant, 1997; Martin-Vide et al., 1999; Hassan & Church, 2001; Sear et al., 2003; Bond, 2004). They range from small sized pit traps, without continuous measurement, to Birkbeck samplers and large, stream-wide constructions for continuous monitoring. The latter is achieved with the employment of a weighing device (pressure cushion or load cell) below the sampling box or outside the channel (vortex tube, pump or conveyor belt) (Gomez, 1991; Sear et al., 2000a; Ergenzinger & de Jong, 2003; Sear, 2003). Load cell systems are more reliable than pressure cushion devices because they are less susceptible to damage (e.g. puncture of pressure pillows; Lewis, 1991). Smaller pit traps may fill rapidly during large events but are generally more accurate than handheld bedload transport samplers (Wilcock, 2001). Sampling efficiency for pit traps is up to 100%, decreasing with increasing fill (Laronne et al., 2003). In particular at base flow, bedload transport traps may also sample suspended sediments (Batalla, 1997). The installation and maintenance of a bedload trap is expensive and involves a serious disturbance of the stream bed and biota. For this reason, bedload traps have not been used for investigations of benthic biota but for long-term projects they offer a useful tool for the assessment of ecologically relevant bedload discharge. As an alternative, monitoring of sediment volume accumulated in natural traps (basins), reservoirs or retention and diversion devices provides an opportunity to assess bedload transport rate, but calibration to exclude suspended sediments is difficult (Gomez, 1991).
Acoustic sensors. Acoustic sensors can be used to assess bedload transport intensity and the onset and cessation of movement (Ergenzinger & de Jong, 2003). In addition, estimates of transport rate using acoustic energy and estimates of transported particle size using the emitted frequency can be obtained (Bogen & Moen, 2003; Downing et al., 2003; Froehlich, 2003; Mizuyama et al., 2003). Hydrophones must be calibrated against actual bedload samples at each site. The sensor consists of a plate fixed horizontally on the bed (Bogen & Moen, 2003), a vertical pressure plate (Downing et al., 2003) or horizontal steel pipes across the stream bed (Froehlich, 2003; Mizuyama et al., 2003). Calibration limits the application at numerous sites, but the accuracy can be similar to a bedload trap. Acoustic Doppler current profiling (ADCP) allows the combined measurement of multi dimensional flow and velocity of bedload and suspended load (Rennie & Millar, 2004). Limitations of this technique include problems with the differentiation between near-bed suspension, bedload and fine grained bottom sediments as well as varying sensitivity to different particle sizes (Kostaschuk et al., 2005).
Bedload transport formulae. Bedload transport formulae (e.g. Schoklitsch-type eqn (5)) are generally based on four principal approaches: shear stress, stream discharge, stream power and a stochastic function for sediment transport (Gomez & Church, 1989).
In this example, bedload discharge qb depends on excess water discharge and a sediment coefficient X′. Most bedload transport formulae originate from physical principles but their precision has been improved by the use of empirical datasets from flumes and streams. The formulae are consistent in that they employ in most instances the same hydraulic parameters (energy gradient, flow velocity, depth and discharge) which are in part intercorrelated (Gomez & Church, 1989; Martin & Church, 2000). Most formulae are well suited and parameterised for the dataset of their development, but fail when applied to other conditions (Knighton, 2008). They are based on limited basic assumptions which vary between streams and even within streams (e.g. selective entrainment). Characteristics like armouring, exposure to flow, equal mobility, variable sediment supply and pulsing cannot be fully accounted for, although some approaches try to incorporate these points (Parker, 1990; Duan & Scott, 2007; Thompson & Croke, 2008). Furthermore, the spatial variability within a stream is ignored because of the one-dimensional nature of the formulae (Hoey et al., 2001; Ferguson, 2003; Martin & Ham, 2005). The result of comparative studies with bedload samplers/traps (Gomez & Church, 1989; Batalla, 1997; Martin-Vide et al., 1999; Habersack & Laronne, 2002; Barry, 2004) and morphologic budgeting (Martin & Ham, 2005) show clearly that bedload transport formulae perform inconsistently (but see Bartnik et al., 1992). Thus, bedload transport formulae need to be carefully selected according to the conditions for which they were developed, for instance turbulent and shallow mountain streams require other types of models than gravel-bed rivers (Biggs et al., 2001; Mizuyama et al., 2003; Ancey et al., 2008). Additionally, empirical parameters and the entrainment threshold have to be determined to suit a new dataset, which is a difficult task (Wilcock, 2001; Habersack & Laronne, 2002). Thus the application of direct measurements of bedload transport is preferable to the use of bedload transport formulae (Gomez, 1991; Laronne et al., 1992).