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The mitigation of diffuse sediment pollution requires reliable provenance information so that measures can be targeted. Sediment source fingerprinting represents one approach for supporting these needs, but recent methodological developments have resulted in an increasing complexity of data processing methods rendering the approach less accessible to non-specialists. A comprehensive new software programme (SIFT; SedIment Fingerprinting Tool) has therefore been developed which guides the user through critical data analysis decisions and automates all calculations. Multiple source group configurations and composite fingerprints are identified and tested using multiple methods of uncertainty analysis. This aims to explore the sediment provenance information provided by the tracers more comprehensively than a single model, and allows for model configurations with high uncertainties to be rejected. This paper provides an overview of its application to an agricultural catchment in the UK to determine if the approach used can provide a reduction in uncertainty and increase in precision. Five source group classifications were used; three formed using a k-means cluster analysis containing 2, 3 and 4 clusters, and two a-priori groups based upon catchment geology. Three different composite fingerprints were used for each classification and bi-plots, range tests, tracer variability ratios and virtual mixtures tested the reliability of each model configuration. Some model configurations performed poorly when apportioning the composition of virtual mixtures, and different model configurations could produce different sediment provenance results despite using composite fingerprints able to discriminate robustly between the source groups. Despite this uncertainty, dominant sediment sources were identified, and those in close proximity to each sediment sampling location were found to be of greatest importance. This new software, by integrating recent methodological developments in tracer data processing, guides users through key steps. Critically, by applying multiple model configurations and uncertainty assessment, it delivers more robust solutions for informing catchment management of the sediment problem than many previously used approaches. [ABSTRACT FROM AUTHOR]

The classification of sediment source groups is often the least thoroughly considered part of a sediment fingerprinting methodology; however, the use of inappropriate source groups can be the cause of significant uncertainty. In many catchments, source groups based on land use or geology are a poor fit for their geomorphological processes and the nature of the tracers used. Against this context, this study directly compared the average percentage difference in the standardised concentrations of all tracers between a sediment sample and each individual source sample, to map the similarity between the properties of sources and sediment in 3 study catchments. The environmental significance of individual tracers and their similarity between individual samples were also examined in order to identify functionally important source groups. In the River Nene, UK, the mean percentage differences between source and sediment tracer concentrations were primarily controlled by the presence of distinctive ironstone and urban sources, which had very dissimilar properties to the target sediment. However, a generally consistent trend of certain source samples having more similar properties to multiple target sediment samples than others was also found; a finding that could not be identified when using conventional source groups. In the Sywell reservoir catchment, UK, sediment originated from throughout its catchment, apart from in the case of damaged road verges, and there was little indication of any major change in sediment sources through recent time. In the Vuvu catchment, South Africa, there was a larger contribution from distal igneous sources during high-flow events. The trialled method, however, provided little advantage over the standard fingerprinting approach in this case, due to the existing good fit between catchment geomorphology, the tracers used, and the geological source groups. The method trialled herein can provide distinct advantages over the conventional fingerprinting approach and, although it should not replace it, provides a useful supplement by permitting an assessment of whether potential source groupings make best environmental sense and providing increased resolution of sediment provenance. [ABSTRACT FROM AUTHOR]

Mitigation of diffuse water pollution from agriculture is a key national environmental policy objective in England. With the recent introduction of the new agri-environment scheme, Countryside Stewardship, there is an increased emphasis on the macro-spatial targeting of on-farm mitigation measures to reduce pollutant pressures, and a concomitant need to forecast the technically feasible impacts of on-farm measures detailed in current policy and their associated costs and benefits. This paper reports the results of a modelling application to test these limits in the context of the associated costs and benefits for the reduction of diffuse water pollution from agriculture for each Water Framework Directive (WFD) water management catchment (WMC) and nationally. Four mitigation scenarios were modelled, including pollutant source control measures only (SC), mobilisation control measures only (MC), delivery control measures only (DC) and measures for source, mobilisation and delivery control (SMDC) combined. Projected impacts on nitrate, phosphorus and sediment export to water, ammonia, methane and nitrous oxide emissions to the atmosphere, together with the associated costs to the agricultural sector were estimated for each WFD WMC and nationally. Median WMC-scale reductions (with uncertainty ranges represented by 5th–95th percentiles) in current agricultural emissions, were predicted to be highest for the SMDC scenario; nitrate (18%, 11–23%), phosphorus (28%, 22–37%), sediment (25%, 18–43%), ammonia (26%, 17–32%), methane (13%, 7–18%) and nitrous oxide (18%, 16–20%). The median benefit-to-cost ratios (with uncertainty ranges represented by 5th–95th percentiles) were predicted to be in the following order; DC (0.15, 0.09–0.65), MC (0.19, 0.09–0.95), SMDC (0.31, 0.20–1.39) and SC (0.44, 0.19–2.48). Of the four scenarios simulated, the SC and SMDC suites of measures have the greatest potential to deliver reductions in BAU emissions from agriculture, and the best benefit:cost ratio. [ABSTRACT FROM AUTHOR]

The growing awareness of the environmental significance of fine-grained sediment fluxes through catchment systems continues to underscore the need for reliable information on the principal sources of this material. Source estimates are difficult to obtain using traditional monitoring techniques, but sediment source fingerprinting or tracing procedures, have emerged as a potentially valuable alternative. Despite the rapidly increasing numbers of studies reporting the use of sediment source fingerprinting, several key challenges and uncertainties continue to hamper consensus among the international scientific community on key components of the existing methodological procedures. Accordingly, this contribution reviews and presents recent developments for several key aspects of fingerprinting, namely: sediment source classification, catchment source and target sediment sampling, tracer selection, grain size issues, tracer conservatism, source apportionment modelling, and assessment of source predictions using artificial mixtures. Finally, a decision-tree representing the current state of knowledge is presented, to guide end-users in applying the fingerprinting approach. [ABSTRACT FROM AUTHOR]

A multi-pollutant modelling framework for England and Wales is described. This includes emissions of nitrate, phosphorus and sediment to water and ammonia, methane and nitrous oxide to air, and has been used to characterise baseline (no uptake of on-farm measures) and business-as-usual (BAU) annual pollutant losses, comparing these with the loss under a range of new policies aimed at increasing the uptake of relevant source control measures to 95% across England and Wales. Model outputs, including uncertainty ranges, evaluated using national water and air quality data layers have been summarised at both farm (Robust Farm Type) and water management catchment (WMC) scale. Nationally, across all farm types, the median annual reductions in pollutant losses under the new scenario, relative to BAU in 2010, were predicted to range between 9 and 16% for nitrate, 13–37% for phosphorus, 12–21% for sediment, 2–57% for methane and 10–17% for nitrous oxide. For ammonia, the range was −2–28%, indicating the potential for pollution swapping and an increase in ammonia emissions under scenarios designed to reduce nitrogen flux to waters. Increased uptake of pollution source control measures would result in a wide range of annual total (capital and operational) costs (per farm) for the major farm types, with median estimates ranging from £635 yr −1 (Less Favourable Areas (LFA) with grazing livestock) to £15,492 yr −1 (Cereals) in Nitrate Vulnerable Zone (NVZ) areas, compared with a range of £23 yr −1 to £13,484 yr −1 for the same respective farm types in non-NVZ areas. The estimated median annual load reductions for all WMCs relative to BAU, were predicted to be 16% for nitrate, 20% for phosphorus, 16% for sediment, 16% for ammonia, 15% for methane and 18% for nitrous oxide. These predictions suggest that almost perfect (95% uptake) implementation of source control measures will not deliver substantial improvements in pollutant emissions. [ABSTRACT FROM AUTHOR]

Mitigation of agricultural diffuse pollution poses a significant policy challenge across Europe and particularly in the UK. Existing combined regulatory and voluntary approaches applied in the UK continue to fail to deliver the necessary environmental outcomes for a variety of reasons including failure to achieve high adoption rates. It is therefore logical to identify specific on-farm mitigation measures towards which farmers express positive attitudes for higher future uptake rates. Accordingly, a farmer attitudinal survey was undertaken during phase one of the Demonstration Test Catchment programme in England to understand those measures towards which surveyed farmers are most receptive to increasing implementation in the future. A total of 29 on-farm measures were shortlisted by this baseline farm survey. This shortlist comprised many low cost or cost-neutral measures suggesting that costs continue to represent a principal selection criterion for many farmers. The 29 measures were mapped onto relevant major farm types and input, assuming 95% uptake, to a national scale multi-pollutant modelling framework to predict the technically feasible impact on annual agricultural emissions to water and air, relative to business as usual. Simulated median emission reductions, relative to current practise, for water management catchments across England and Wales, were estimated to be in the order sediment (20%) > ammonia (16%) > total phosphorus (15%) ≫ nitrate/methane (11%) > nitrous oxide (7%). The corresponding median annual total cost of the modelled scenario to farmers was £3 ha − 1 yr − 1 , with a corresponding range of -£84 ha − 1 yr − 1 (i.e. a net saving) to £33 ha − 1 yr − 1 . The results suggest that those mitigation measures which surveyed farmers are most inclined to implement in the future would improve the environmental performance of agriculture in England and Wales at minimum to low cost per hectare. [ABSTRACT FROM AUTHOR]

Although traditional sediment tracing approaches provide valuable information for characterising key generic sediment sources, Catchment Officers working as part of the Catchment Sensitive Farming initiative frequently require more detailed evidence to permit improved targeting of mitigation. Accordingly, a novel framework combining conventional sediment source fingerprinting and a dual signature tracking method has recently been used to improve sediment source information for the River Glaven (~115 km2) priority catchment in eastern England. Conventional geochemical tracing incorporating a number of recent refinements to the mass balance modelling, including the combined use of local and genetic algorithm optimisation, was used to provide information on the average median relative contributions (±95% confidence limits) of generic sediment sources in three sub-catchments, categorised as grassland (1 ± 1%-12 ± 1%) or arable (25 ± 1%-46 ± 1%) surface soils, damaged road verges (2 ± 1%-50 ± 1%) and channel banks/subsurface sources (20 ± 1%-50 ± 1%) and to provide a framework for the spatial extrapolation of tracking data. Particle tracking using fluorescent-magnetic grains was used to provide preliminary sub-catchment scale information on sediment loss from key components of the primary arable topsoil and channel bank generic sources, characterised, respectively, as wheelings (18 ± 1%-33 ± 1%) or inter-wheelings (7 ± 1%-13 ± 1%) and poached (19 ± 1%-47 ± 1%) or fluvially eroded (1 ± 1%-3 ± 1%) channel margins. The insertion of high-strength magnets in watercourses ensured that the tracking component of the novel framework links sediment loss from labelled areas to river channels as opposed to providing information to edge-of-field only. Uncertainty and prior information on source contributions are explicitly recognised by the framework. This study represents the first in the UK to link wheeling sediment losses to river channels. The findings underpin the importance of compacted areas used for trafficking as sources of, and conduits for, sediment delivery in the lowland agricultural landscape of the UK. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Increasing recognition of the deleterious environmental effects of excessive fine sediment delivery to watercourses means that reliable sediment source assessment represents a fundamental component of catchment planning targeting the protection of freshwater resources and their ecological integrity. Sediment tracing or fingerprinting approaches have been increasingly used to provide catchment scale sediment source information, but there is a need to continue refining existing procedures especially with respect to uncertainty analysis during mass balance modelling. Consequently, an updated Monte Carlo numerical modelling framework was devised and tested, incorporating both conventional and robust statistics coupled with random and Latin Hypercube Sampling (LHS) together with local and genetic algorithm (GA) optimisation. A sediment sourcing study undertaken in the River Axe catchment, southwest England, suggested that the use of robust statistics and LHS with GA optimisation generated the best performance with respect to predicting measured bed sediment geochemistry in six out of eight model applications. On this basis, the catchment-wide average median sediment source contributions were predicted to be 38 ± 1% (pasture topsoils), 3 ± 1% (cultivated topsoils), 37 ± 1% (damaged road verges) and 22 ± 1% (channel banks/subsurface sources). Using modelling frameworks which provide users with flexibility to compare local and global optimisation during uncertainty analysis is recommended for future sediment tracing studies. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: Catchment erosion, soil losses and resulting sediment pressures continue to represent cause for concern with respect to the ecological vitality and amenity value of riverine systems, including those in the agricultural catchments of southern England. Given that the sources of fine-grained sediment are typically diffuse in nature, it is essential to adopt a catchment-wide perspective to corresponding management strategies and sediment source tracing procedures have proved useful in assisting such planning. There remains, however, scope for further refining sediment sourcing procedures and on that basis, a recent study in the upper River Kennet (~214km2) catchment in southern England, provided an opportunity for designing and testing a refined statistical procedure for sediment source discrimination with composite fingerprints using Genetic Algorithm (GA)-driven Discriminant Function Analysis, the Kruskal–Wallis H-test and Principal Components Analysis. The revised statistical verification of composite signatures was combined with numerical mass balance modelling using recent refinements including a range of tracer weightings and both local and GA optimisation. Comparison of the local and global optimisation increased confidence in the outputs of local optimisation and the goodness-of-fit for the predicted source contributions using the optimum composite signatures selected from the revised statistical testing ranged from 0.914 to 0.965. Overall relative frequency-weighted average median source type contributions were estimated to be 4% (agricultural topsoils; predicted deviate median inputs 1–19%), 55% (unmetalled farm track surfaces; predicted deviate median inputs 9–91%), 6% (damaged road verges; predicted deviate median inputs 4–42%), 31% (channel banks/subsurface sources; predicted deviate median inputs 5–41%) and 4% (urban street dust; predicted deviate median inputs 0–20%). The study provides further evidence of the importance of eroding farm tacks as a catchment scale sediment source and confirms the utility of tracing for assembling information on sediment inputs from both the agricultural and urban sectors. [Copyright &y& Elsevier]

Abstract: Sediment fingerprinting techniques provide a means of assembling valuable reliable information on the principal sources of sediment problems at catchment scale. However, there is a need to refine existing approaches to take account of a variety of sources of uncertainty and to incorporate prior information. To address this need, a modified mass balance model incorporating a Monte Carlo approach for representing the uncertainty surrounding source and sediment sampling, as well as weightings to take account of the within-source variability and discriminatory power of individual tracer properties and prior information on bank erosion, was used to apportion recent sediment sources in sub-catchments of the Somerset Levels, south west UK. Sensitivity tests confirmed that the precision of source apportionment was improved by incorporating the weightings and prior information into the mixing model. Estimates of the overall mean contributions from individual source types, bounded by 95% confidence limits, were assessed to be 42±2% (pasture topsoils), 22±2% (cultivated topsoils), 22±1% (channel banks/subsurface sources), 12±2% (damaged road verges) and 2±1% (STWs). Respective estimates of net sediment delivery to watercourses, provided by integrating the source ascription results with estimated sediment yield ranges and sub-catchment or land use areas, ranged between 33–829kgha−1 yr−1, 30–1995kgha−1 yr−1, 2–315kgha−1 yr−1, 0–217kgha−1 yr−1, and 0–28kgha−1 yr−1. Sediment fingerprinting should always include uncertainty analysis but on the understanding that the latter will be conditional on the assumptions used. [Copyright &y& Elsevier]

Despite increasing concerns about the negative effects that increased loads of fine-grained sediment are having on freshwaters, the need is clear for a rapid and cost-effective methodology that gives precise estimates of deposited sediment across all river types and that are relevant to morphological and ecological impact. To date few attempts have been made to assess the precision of techniques used to assemble data on fine sediment storage in river channels. Accordingly, we present an investigation into the sources of uncertainty associated with estimates of deposited fine-grained sediment in rivers using a sediment resuspension technique, an approach that provides an instantaneous measure of deposited fine sediment (surface and subsurface) in terms of quantity and quality. We investigated how variation associated with river type, spatial patchiness within rivers, sampling, and individual operators influenced estimates of deposited fine sediment using this approach and compared the precision with that of visual estimates of river bed composition — a commonly applied technique in rapid river surveys. We have used this information to develop an effective methodology for producing reach-scale estimates with known confidence intervals. By using a spatially-focussed sampling strategy that captured areas of visually high and low deposition of fine-grained sediment, the dominant aspects of small-scale spatial variability were controlled and a more precise instantaneous estimate of deposited fine sediment derived. The majority of the remaining within-site variance was attributable to spatial and sampling variability at the smallest (patch) scale. The method performed as well as visual estimates of percentage of the river bed comprising fines in its ability to discriminate between rivers but, unlike visual estimates, was not affected by operator bias. Confidence intervals for reach-scale measures of deposited fine-grained sediment were derived for the technique, and these can be applied elsewhere. [ABSTRACT FROM AUTHOR]