Combining two filter paper‐based analytical methods to monitor temporal variations in the geochemical properties of fluvial suspended particulate matter

Cooper, Richard J.; Rawlins, Barry G.; Lézé, Bertrand; Krueger, Tobias; Hiscock, Kevin M.

doi:10.1002/hyp.9945

Cited by 19 publications

(21 citation statements)

References 59 publications

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“…Recently, studies have demonstrated the promise of spectral reflectance-based (visible and (near) infrared) fingerprinting methods as a quicker and less costly alternative for sediment source apportionment, with considerable potential to expand the temporal resolution of sediment fingerprinting analyses during high-flow events (e.g. Cooper et al, 2014aCooper et al, , 2014bEvrard et al, 2013;Martínez-Carreras et al, 2010;Poulenard et al, 2009;Tiecher et al, 2015).…”

Section: Methodological Challengesmentioning

confidence: 99%

Suspended sediment transport dynamics in rivers: Multi-scale drivers of temporal variation

Vercruysse

Grabowski

Rickson

2017

Earth-Science Reviews

325

181

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Suspended sediment is a natural part of river systems and plays an essential role in structuring the landscape, creating ecological habitats and transporting nutrients. It is also a common management problem, where alterations to sediment quantity and quality negatively impact ecological communities, increase flood hazard and shorten the lifespan of infrastructure. To address these challenges and develop appropriate sustainable management strategies, we need a thorough understanding of sediment sources, pathways and transport dynamics and the drivers that underlie spatial and temporal variability in suspended sediment transport in rivers. However, research to date has not sufficiently addressed the temporal complexity of sediment transport processes, which is limiting our ability to disentangle the hydro-meteorological, catchment, channel and anthropogenic drivers of suspended sediment transport in rivers. This review critically evaluates previously published work on suspended sediment dynamics to demonstrate how the interpretation of sediment sources and pathways is influenced by the temporal scale and methodology of the study. To do this, the review (i) summarizes the main drivers of temporal variation in suspended sediment transport in rivers; (ii) critically reviews the common empirical approaches used to analyze and quantify sediment sources and loads, and their capacity to account for temporal variations; (iii) applies these findings to recent case studies to illustrate how method and timescale affect the interpretation of suspended sediment transport dynamics; and finally (iv) synthesizes the findings of the review into a set of guidelines for a multi-timescale approach to sediment regime characterization. By recognizing a priori that study design and temporal scale have an impact on the interpretation of SS dynamics and employing methods that address these issues, future research will be better able to identify the drivers of suspended sediment transport in rivers, improve sediment transport modelling, and propose effective, sustainable solutions to sediment management problems.

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Section: Methodological Challengesmentioning

confidence: 99%

Suspended sediment transport dynamics in rivers: Multi-scale drivers of temporal variation

Vercruysse

Grabowski

Rickson

2017

Earth-Science Reviews

325

181

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“…From each source area, 30 soil/sediment samples were collected, wet sieved to <63 μm to extract the fine clay‐silt fraction, and transferred onto quartz fibre filter papers. These filter papers were then analysed by X‐ray fluorescence spectroscopy to determine the geochemistry (wt.%) following the method of Cooper, Rawlins, Lézé, Krueger, and Hiscock (), which had previously been successfully applied in this catchment. In total, concentrations of eight major elements (Al, Ca, Ce, Fe, K, Mg, Na, and Ti) were determined and selected as fingerprints for use in the mixing models.…”

Section: Methodsmentioning

confidence: 99%

An extended Bayesian sediment fingerprinting mixing model for the full Bayes treatment of geochemical uncertainties

Cooper

Krueger

2017

Hydrological Processes

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Recent advances in sediment fingerprinting research have seen Bayesian mixing models being increasingly employed as an effective method to coherently translate component uncertainties into source apportionment results. Here, we advance earlier work by presenting an extended Bayesian mixing model capable of providing a full Bayes treatment of geochemical uncertainties. The performance of the extended full Bayes model was assessed against the equivalent empirical Bayes model and traditional frequentist optimisation. The performance of models coded in different Bayesian software (‘JAGS’ and ‘Stan’) was also evaluated, alongside an assessment of model sensitivity to reduced source representativeness and non-conservative fingerprint behaviour. Results revealed comparable accuracy and precision for the full and empirical Bayes models across both synthetic and real sediment geochemistry datasets, demonstrating that the empirical treatment of source data here represents a close approximation of the full Bayes treatment. Contrasts in the performance of models coded in JAGS and Stan revealed that the choice of software employed can impact significantly upon source apportionment results. Bayesian models coded in Stan were the least sensitive to both reduced source representativeness and non-conservative fingerprint behaviour, indicating Stan as the preferred software for future Bayesian sediment fingerprinting studies. Whilst the frequentist optimisation generally yielded comparable accuracy to the Bayesian models, uncertainties around apportionment estimates were substantially greater and the frequentist model was less effective at dealing with non-conservative behaviour. Overall, the effective performance of the extended full Bayes mixing model coded in Stan represents a notable advancement in source apportionment modelling relative to previous approaches. Both the mixing model and the software comparisons presented here should provide useful guidelines for future sediment fingerprinting studies

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“…One litre grab samples were filtered through pre-weighed Millipore quartz fibre filter (QFF) papers with a particle retention rating of 99.3 % at 0.45 μm to extract SPM (Cooper et al 2014). Filters were then oven dried at 105°C for 2 h and reweighed to determine SPM concentration.…”

Section: Data Processingmentioning

confidence: 99%

Diel turbidity cycles in a headwater stream: evidence of nocturnal bioturbation?

2016

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Purpose A small number of recent studies have linked daily cycles in stream turbidity to nocturnal bioturbation by aquatic fauna, principally crayfish, and demonstrated this process can significantly impact upon water quality under baseflow conditions. Adding to this limited body of research, we use highresolution water quality monitoring data to investigate evidence of diel turbidity cycles in a lowland, headwater stream with a known signal crayfish (Pacifastacus leniusculus) population and explore a range of potential causal mechanisms. Materials and methods Automatic bankside monitoring stations measured turbidity and other water quality parameters at 30-min resolution at three locations on the River Blackwater, Norfolk, UK, during 2013. Specifically, we focused on two 20-day periods of baseflow conditions during January and April 2013 which displayed turbidity trends typical of winter and spring seasons, respectively. The turbidity time-series, which were smoothed with 6.5-h Savitzky-Golay filters to highlight diel trends, were correlated against temperature, stage, dissolved oxygen and pH to assess the importance of abiotic influences on turbidity. Turbidity was also calibrated against suspended particulate matter (SPM) over a wide range of values via linear regression.Results and discussion Pronounced diel turbidity cycles were found at two of the three sites under baseflow conditions during April. Spring night-time turbidity values consistently peaked between 21:00 and 04:00 with values increasing bỹ 10 nephelometric turbidity units (NTU) compared with the lowest recorded daytime values which occurred between 10:00 and 14:00. This translated into statistically significant increases in median midnight SPM concentration of up to 76 % compared with midday, with night-time (18:00-05:30) SPM loads also up to 30 % higher than that recorded during the daytime (06:00-17:30). Relating turbidity to other water quality parameters exhibiting diel cycles revealed there to be neither any correlation that might indicate a causal link nor any obvious mechanistic connections to explain the temporal turbidity trends. Diel turbidity cycles were less prominent at all sites during the winter. Conclusions Considering the seasonality and timing of elevated turbidity, visual observations of crayfish activity and an absence of mechanistic connections with other water quality parameters, the results presented here are consistent with the hypothesis that nocturnal bioturbation is responsible for generating diel turbidity cycles under baseflow conditions in headwater streams. However, further research in a variety of fluvial environments is required to better assess the spatial extent, importance and causal mechanisms of this phenomenon.

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Combining two filter paper‐based analytical methods to monitor temporal variations in the geochemical properties of fluvial suspended particulate matter

Cited by 19 publications

References 59 publications

Suspended sediment transport dynamics in rivers: Multi-scale drivers of temporal variation

Suspended sediment transport dynamics in rivers: Multi-scale drivers of temporal variation

An extended Bayesian sediment fingerprinting mixing model for the full Bayes treatment of geochemical uncertainties

Diel turbidity cycles in a headwater stream: evidence of nocturnal bioturbation?

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