Global uncertainty analysis of suspended sediment monitoring using turbidimeter in a small mountainous river catchment
Research highlights
► Uncertainties of suspended sediment concentrations and yields are highly site- and time-dependent. ► They significantly vary with the hydro-sedimentary conditions. ► At the Galabre River station, the uncertainty of the mean suspended sediment concentration during a flood is on average 20%. ► Sediment yield uncertainty is on average 30%. ► The automatic pumping procedure, the discharge measurement and the turbidity fluctuations are the greatest uncertainty components.
Introduction
Improving knowledge on suspended sediment yields, dynamics and water quality is one of today’s major environmental challenges addressed to scientists and hydropower managers (Owens et al., 2005). These advances will continue in the future as the acquisition of reliable and long-term suspended sediment concentration (SCC) time series are generalised to many hydrometric stations. In mountainous catchments, major fractions of the annual suspended sediment yields (SSY) are transported over a very short time period generally corresponding to several floods (e.g. Meybeck et al., 2003, Mano et al., 2009). Therefore high-frequency SSC monitoring is required for reliable SSC and SSY estimates. Nevertheless, a reliable and easy method to obtain a direct, continuous SSC measurement is not currently available. Although great progress is expected with, for instance, the backscatter acoustic method (Wren et al., 2000, Gray and Gartner, 2009), their application is still limited to large rivers and canals. However, problems remain in mountainous catchments where river channels generally show significant and rapid erosion–transport–sedimentation processes, with very high specific sediment yields (suspended as well as bed-load transport). Moreover, measuring suspended sediment dynamics in this restrictive context remains of prime importance, all the more so because these river basins determine the fine sediment delivery to the whole downstream lowland river system (Milliman and Syvitski, 1992, Hicks et al., 2000, Lenzi et al., 2003, Mathys et al., 2003, Meybeck et al., 2003, Mano et al., 2009, Navratil et al., 2010) and they govern reservoir siltation dynamics, water resources and aquatic habitat qualities (Wood and Armitage, 1997, House and Warwick, 1999, Rees et al., 1999, Valero-Garcés et al., 1999, Packman and Mackay, 2003, Owens et al., 2005).
Using only SSC samples with a predefined sampling frequency most often leads to large errors in suspended sediment flux (SSF) estimates (e.g., Thomas and Lewis, 1993, Thomas and Lewis, 1995, Lewis, 1996, Phillips et al., 1999, Coynel et al., 2004, Moatar et al., 2006). Therefore, given the problems of direct high-frequency SSC estimates, turbidity measurement is currently used as a surrogate measurement (Lenzi et al., 2003, Brasington and Richards, 2000, Mathys et al., 2003, Orwin and Smart, 2004, Stott and Mount, 2007, Mano et al., 2009, López-Tarazón et al., 2009). This method is based on the quasi-continuous measurement of turbidity, the sensor being calibrated with suspended sediment collected during many flood events. It remains the easiest and most widely used method for suspended sediment monitoring with high-frequency acquisition (Wren et al., 2000, Downing, 2006, Némery et al., 2010). However, this method shows many limitations and uncertainties within river applications and particularly in mountainous catchments exhibiting a very high SSC and complex spatio-temporal SSY variability.
The present paper aims (1) to analyse the major uncertainty components (referred to as UCs) associated with the turbidity approach for suspended sediment monitoring in a highly erodible mountainous catchment; (2) to assess the propagated uncertainty on SSC and SSY with Monte Carlo simulations; and (3) to classify the UCs according to their relative effect on the final results. This work will provide a practical methodological framework that can be applied to other hydrometric stations using similar monitoring techniques.
This study was based on a 2-year data set (October 2007–December 2009) collected in a small mountainous river basin, the Galabre River in Southern French Pre-Alps. Nine major uncertainty components (UC1–UC9) associated with turbidity measurement were identified and are summarised in Table 1: the choice of a turbidimeter (UC1) and its calibration (UC8); the temporal (UC2, UC3) and spatial (UC4) field sampling strategies; the technical field problems (UC5); the field (UC6) and laboratory (UC7) water sample sampling and procedures; and finally, the discharge estimation (UC9). UC2, UC4 and UC9 were considered in this study in comparison to the literature studies and on-site characteristics. Others (UC1, UC3, UC5–UC8) for which literature data were insufficient or not transposable to this context were quantified with specific analyses.
Uncertainty propagation applied to long-term time series is quite difficult to perform since the UCs may be correlated with each other; so analytical computations remain very complex. Therefore, Monte Carlo simulations were undertaken to evaluate the combined effect of UCs and to estimate the propagation of uncertainties (Fig. 1; Coleman and Steele, 1999, Joint Committee for Guides in Metrology, 2008a, Joint Committee for Guides in Metrology, 2008b, Lacour et al., 2009).
Section snippets
Study area
The Galabre River (lat.: 44°10′27″N, long.: 06°12′59″E) is a small tributary of the Bléone River in the Rhône River catchment, France (drainage area, 35 km2; Fig. 2). Its Mediterranean and mountainous climate (with frost in winter and high-intensity rainfall in summer) and its geology result in a badlands topography, gully development and substantial transfer of sediment. Highly erodible areas cover about 2% of the river basin. Mean annual temperature ranges between 12 and 13 °C at 400 m ASL
Choice of a suitable turbidimeter (UC1)
Sensor fouling is frequent in rivers, so the choice of the turbidimeter must take into account the auto-cleaning procedure adapted to each site’s characteristics (e.g. fouling by algae, calcification, macro-invertebrate, sediment accumulation) to avoid any lack of data or temporal trend (Wren et al., 2000, Lewis and Eads, 2008). Currently available turbidimeters are mainly limited by their range of measurement. Consequently, the choice of a suitable turbidimeter is mainly governed by the range
Choice of a suitable turbidimeter (UC1)
We first verified that our material was well suited to the study site. The turbidity uncertainty (provided by the manufacturer) was low given that it was less than 4% for the entire range of turbidity. The sensor had never been saturated during the 2007–2009 study period; the maximum turbidity observed was 58 g l−1 SiO2 and the maximum SSC was 130 g l−1 (Fig. 4a). No signal trend was observed. Finally, we found that 95% of the total SSY was transported with SSC > 1 g l−1 (Fig. 4b). As a result, the low
Conclusions
Suspended sediment monitoring cumulates many uncertainties from field monitoring to the SSC and SSY computation procedure. Assessing uncertainties is therefore required because it would help distinguish the spatio-temporal variability of SSY attributed to natural (e.g. rainfall, erodibility, relief) or anthropogenic factors (e.g. land use change) from the variability attributed to monitoring uncertainties. Furthermore, the quantification of these uncertainties is of prime importance to a
Acknowledgments
This study was funded by the French ANR-STREAMS project (ANR Blanc 06-1_139157). The authors are grateful to Fred Malinur, Lucas Muller, Vincent Thiabault, Jean-Marie Miscioscia, and Michel Ricard for the field campaigns and laboratory analysis and technical assistance, Linda Northrup (English Solution) for editing the manuscript, and two anonymous reviewers who helped improve the earlier versions of this manuscript.
References (57)
- et al.
Sampling frequency and accuracy of SPM flux estimates in two contrasted drainage basins
Science of the Total Environment
(2004) Twenty-five years with OBS sensors: the good, the bad, and the ugly
Continental Shelf Research
(2006)- et al.
Drivers of erosion and suspended sediment transport in three headwater catchments of the Mexican Central Highlands
Geomorphology
(2010) Determining annual suspended sediment and sediment-associated trace element and nutrient fluxes
The Science of the Total Environment
(2008)- et al.
Assessment of annual pollutant loads in combined sewers from continuous turbidity measurements: sensitivity to calibration data
Water Research
(2009) - et al.
Suspended sediment load during floods in a small stream of the Dolomites (Northeastern, Italy)
Catena
(2000) - et al.
Suspended sediment transport in a highly erodible catchment: The River Isábena (Southern Pyrenees)
Geomorphology
(2009) - et al.
The use of sediment colour measured by diffuse reflectance spectrometry to determine sediment sources: application to the Attert River catchment (Luxembourg)
Journal of Hydrology
(2010) - et al.
Erosion quantification in the small marly experimental catchments of Draix (Alpes de Haute Provence, France). Calibration of the ETC rainfall–runoff–erosion model
Catena
(2003) - et al.
Global variability of daily total suspended solids and their fluxes
Global Planetary Changes
(2003)
The influence of contrasting suspended particulate matter transport regimes on the bias and precision of flux estimates
Science of the Total Environment
Sediment-borne contaminants in rivers discharging into the Humber estuary, UK
Marine Pollution Bulletin
The sediment concentration–turbidity relation: its value in monitoring at Ranger Uranium Mine, Northern Territory, Australia
Catena
Alpine proglacial suspended sediment dynamics in warm and cool ablation seasons: implications for global warming
Journal of Hydrology
An evaluation of flow-stratified sampling for estimating suspended sediment loads
Journal of Hydrology
Sediment sources and siltation in mountain reservoirs: a case study from the central Spanish Pyrenees
Geomorphology
Uncertainty in river discharge observations: a quantitative analysis
Hydrology and Earth System Sciences Discussions
Turbidity and suspended sediment dynamics in small catchments in the Nepal Middle Hills
Hydrological Processes
Measuring solids concentration in stormwater runoff: comparison of analytical methods
Environmental Science and Technology
Experimentation and Uncertainty Analysis for Engineers
The impact of particle size controls on stream turbidity measurements; some implications for suspended sediment yield estimation
Estimation of suspended sediment concentration and yield using linear models, random forests and quantile regression forests
Hydrological Processes
Increase in surface runoff in the central mountains of Mexico: lessons from the past and predictive scenario for the next century
Hydrology and Earth System Science
Technological advances in suspended-sediment surrogate monitoring
Water Resources Research
Erosion thresholds and suspended sediment yields, Waipaoa River Basin, New Zealand
Water Resources Research
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