High frequency un-mixing of soil samples using a submerged spectrophotometer in a laboratory setting—implications for sediment fingerprinting

Purpose This study tests the feasibility of using a submersible spectrophotometer as a novel method to trace and apportion suspended sediment sources in situ and at high temporal frequency. Methods Laboratory experiments were designed to identify how absorbance at different wavelengths can be used to un-mix artificial mixtures of soil samples (i.e. sediment sources). The experiment consists of a tank containing 40 L of water, to which the soil samples and soil mixtures of known proportions were added in suspension. Absorbance measurements made using the submersible spectrophotometer were used to elucidate: (i) the effects of concentrations on absorbance, (ii) the relationship between absorbance and particle size and (iii) the linear additivity of absorbance as a prerequisite for un-mixing. Results The observed relationships between soil sample concentrations and absorbance in the ultraviolet visible (UV–VIS) wavelength range (200–730 nm) indicated that differences in absorbance patterns are caused by soil-specific properties and particle size. Absorbance was found to be linearly additive and could be used to predict the known soil sample proportions in mixtures using the MixSIAR Bayesian tracer mixing model. Model results indicate that dominant contributions to mixtures containing two and three soil samples could be predicted well, whilst accuracy for four-soil sample mixtures was lower (with respective mean absolute errors of 15.4%, 12.9% and 17.0%). Conclusion The results demonstrate the potential for using in situ submersible spectrophotometer sensors to trace suspended sediment sources at high temporal frequency

Use of a submersible spectrophotometer probe to fingerprint spatial suspended sediment sources at catchment scale

Sediment fingerprinting is used to identify catchment sediment sources. Traditionally, it has been based on the collection and analysis of potential soil sources and target sediment. Differences between soil source properties (i.e., fingerprints) are then used to discriminate between sources, allowing the quantification of the relative source contributions to the target sediment. The traditional approach generally requires substantial resources for sampling and fingerprint analysis, when using conventional laboratory procedures. In pursuit of reducing the resources required, several new fingerprints have been tested and applied. However, despite the lower resource demands for analysis, most recently proposed fingerprints still require resource intensive sampling and laboratory analysis. Against this background, this study describes the use of UV-VIS absorbance spectra for sediment fingerprinting, which can be directly measured by submersible spectrophotometers on water samples in a rapid and non-destructive manner. To test the use of absorbance to estimate spatial source contributions to the target suspended sediment (SS), water samples were collected from a series of confluences during three sampling campaigns in which a confluence-based approach to source fingerprinting was undertaken. Water samples were measured in the laboratory and, after compensation for absorbance influenced by dissolved components and SS concentration, absorbance readings were used in combination with the MixSIAR Bayesian mixing model to quantify spatial source contributions. The contributions were compared with the sediment budget, to evaluate the potential use of absorbance for sediment fingerprinting at catchment scale. Overall deviations between the spatial source contributions using source fingerprinting and sediment budgeting were 18 % for all confluences (n = 11), for all events (n = 3). However, some confluences showed much higher deviations (up to 52 %), indicating the need for careful evaluation of the results using the spectrophotometer probe. Overall, this study shows the potential of using absorbance, directly obtained from grab water samples, for sediment fingerprinting in natural environments

The uncertainties associated with sediment fingerprinting suspended and recently deposited fluvial sediment in the Nene river basin

The use of tracers within a sediment fingerprinting framework has become a commonly used technique for investigating the sources of fine sediment. However, uncertainties associated with tracer behaviour have been cited as major potential limitations to sediment fingerprinting methodologies. This paper aims to determine the differences between fingerprinting results derived using different groups of tracer properties and to determine the role of organic matter content, particle size, and within-source variability in tracer concentrations on the observed differences. A mean difference of 24.1% between the predicted contributions of sediment originating from channel banks was found when using different tracer groups. Mean differences between tracer group predictions were lower, at between 8% and 11%, when fingerprinting contributions from urban street dusts. Organic matter content and / or particle size showed little indication that they caused differences between tracer group predictions. The within-source variability in tracer concentrations and small contrasts between the tracer concentrations of different source groups were identified as probable causes of inherent uncertainty in the fingerprinting predictions. We determined that the ratio of the percentage difference between median tracer concentrations in the source groups and the average within-source tracer concentration coefficient of variation could indicate the likely uncertainty in model predictions prior to tracer use

The Evaluation of a Chemical Fingerprinting Technique for Identifying the Sources of In-stream Sediments

Sediment is often listed as one of the main contributors to the impairment of surface waters throughout the United States. Sediment source identification is difficult in watersheds with complex combinations of land-uses and non-point sources because of the complexities involved in correlating water quality data, which are relatively easy to collect, to the source of a degrading component. The elemental properties of a particular soil on the landscape may be viewed as a “fingerprint”. A comparison of the elemental fingerprints of potential sources and in-stream sediment may be used to establish sediment source. The objectives of this investigation were to characterize the elemental content of suspended stream sediment and potential sources of sediment in an impaired watershed, Pond Creek watershed in east Tennessee (HUC: TN06010201013), and to use multivariate statistical techniques to identify and quantify sediment sources in the watershed. Potential sediment source samples were collected throughout the watershed and suspended sediment samples at two locations. Subsamples of the \u3c53\u3eμm material and suspended sediment were subjected to total dissolution, HNO3-extraction, and Mehlich 3-extraction. Descriptive statistics suggested that each dataset contained considerable heterogeneity. The source samples were grouped according to land management and position in the landscape. The results of a Kruskal-Wallis rank test and discriminant function analysis indicated that for all three datasets the elemental variability of the samples was not sufficient to differentiate the source and sediment samples and characterize the suspended sediment sources using the initial group definitions. When using all available elemental data from each dataset the groups defined by cluster analysis and canonical discriminant analysis did not match the contents of the initially defined groups. The composition of the clusters varied from one dataset to another, making it difficult to draw conclusions concerning the cluster contents, or to identify sources of suspended sediment. The lack of elemental content variability for differentiating the source and sediment samples and characterizing the suspended sediment sources is likely an artifact of the watershed sampling procedure that was employed, which was directed towards sampling sources likely to be contributing to the suspended sediment load in Pond Creek

Apportioning sources of organic matter in streambed sediments: An integrated molecular and compound-specific stable isotope approach

We present a novel application for quantitatively apportioning sources of organic matter in streambed sediments via a coupled molecular and compound-specific isotope analysis (CSIA) of long-chain leaf wax n-alkane biomarkers using a Bayesian mixing model. Leaf wax extracts of 13 plant species were collected from across two environments (aquatic and terrestrial) and four plant functional types (trees, herbaceous perennials, and C3 and C4 graminoids) from the agricultural River Wensum catchment, UK. Seven isotopic (δ13C27, δ13C29, δ13C31, δ13C27–31, δ2H27, δ2H29, and δ2H27–29) and two n-alkane ratio (average chain length (ACL), carbon preference index (CPI)) fingerprints were derived, which successfully differentiated 93% of individual plant specimens by plant functional type. The δ2H values were the strongest discriminators of plants originating from different functional groups, with trees (δ2H27–29 = − 208‰ to − 164‰) and C3 graminoids (δ2H27–29 = − 259‰ to − 221‰) providing the largest contrasts. The δ13C values provided strong discrimination between C3 (δ13C27–31 = − 37.5‰ to − 33.8‰) and C4 (δ13C27–31 = − 23.5‰ to − 23.1‰) plants, but neither δ13C nor δ2H values could uniquely differentiate aquatic and terrestrial species, emphasizing a stronger plant physiological/biochemical rather than environmental control over isotopic differences. ACL and CPI complemented isotopic discrimination, with significantly longer chain lengths recorded for trees and terrestrial plants compared with herbaceous perennials and aquatic species, respectively. Application of a comprehensive Bayesian mixing model for 18 streambed sediments collected between September 2013 and March 2014 revealed considerable temporal variability in the apportionment of organic matter sources. Median organic matter contributions ranged from 22% to 52% for trees, 29% to 50% for herbaceous perennials, 17% to 34% for C3 graminoids and 3% to 7% for C4 graminoids. The results presented here clearly demonstrate the effectiveness of an integrated molecular and stable isotope analysis for quantitatively apportioning, with uncertainty, plant-specific organic matter contributions to streambed sediments via a Bayesian mixing model approach

Fingerprinting and tracing the sources of soils and sediments: Earth and ocean science, geoarchaeological, forensic, and human health applications

publisher: Elsevier articletitle: Fingerprinting and tracing the sources of soils and sediments: Earth and ocean science, geoarchaeological, forensic, and human health applications journaltitle: Earth-Science Reviews articlelink: http://dx.doi.org/10.1016/j.earscirev.2016.08.012 content_type: article copyright: © 2016 Elsevier B.V. All rights reserved

Fingerprinting sediment contribution from alpine soils to mountain reservoirs

6 Pags.- 1 Tabl.- 1 Fig.Soil in alpine environments plays a key role in the development of ecosystem services and information is required on processes that lead to soil erosion to maintain and preserve this important resource. In common with other mountain alpine environments, the Benasque catchment is characterized by temperatures below freezing that can last from November to April, intense rainfall events, and rugged topography which makes assessment of erosion challenging. Indirect approaches to soil erosion assessment offer opportunity to evaluate soil erosion in such areas. In this study sediment fingerprinting procedures were used to evaluate soil sources in the area of the Posets- Maladeta National Park (Central Spanish Pyrenees). Sediment contributions of potential sediment sources defined by soil type (Kastanozems/Phaeozems; Fluvisols and Cambisols) were assessed by different characterizations of sources and identified Fluvisols, which dominate the riparian zone, as the main sediment source at the time of sampling indicating the importance of connectivity and also potential differences in the source dynamic of material in storage versus that transported efficiently from the system during high flows. The approach enabled us to better understand soil erosion processes in the Benasque alpine catchment wherein identified areas that, due to high connectivity, contribute more to sediment deposits.This research was funded by the project CGL2011-25486.Peer reviewe

High-temporal resolution fluvial sediment source fingerprinting with uncertainty: a Bayesian approach

This contribution addresses two developing areas of sediment fingerprinting research. Specifically, how to improve the temporal resolution of source apportionment estimates whilst minimizing analytical costs and, secondly, how to consistently quantify all perceived uncertainties associated with the sediment mixing model procedure. This first matter is tackled by using direct X-ray fluorescence spectroscopy (XRFS) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analyses of suspended particulate matter (SPM) covered filter papers in conjunction with automatic water samplers. This method enables SPM geochemistry to be quickly, accurately, inexpensively and non-destructively monitored at high-temporal resolution throughout the progression of numerous precipitation events. We then employed a Bayesian mixing model procedure to provide full characterization of spatial geochemical variability, instrument precision and residual error to yield a realistic and coherent assessment of the uncertainties associated with source apportionment estimates. Applying these methods to SPM data from the River Wensum catchment, UK, we have been able to apportion, with uncertainty, sediment contributions from eroding arable topsoils, damaged road verges and combined subsurface channel bank and agricultural field drain sources at 60- and 120-minute resolution for the duration of five precipitation events. The results presented here demonstrate how combining Bayesian mixing models with the direct spectroscopic analysis of SPM-covered filter papers can produce high-temporal resolution source apportionment estimates that can assist with the appropriate targeting of sediment pollution mitigation measures at a catchment level

Sensitivity of fluvial sediment source apportionment to mixing model assumptions: A Bayesian model comparison

Mixing models have become increasingly common tools for apportioning fluvial sediment load to various sediment sources across catchments using a wide variety of Bayesian and frequentist modeling approaches. In this study, we demonstrate how different model setups can impact upon resulting source apportionment estimates in a Bayesian framework via a one-factor-at-a-time (OFAT) sensitivity analysis. We formulate 13 versions of a mixing model, each with different error assumptions and model structural choices, and apply them to sediment geochemistry data from the River Blackwater, Norfolk, UK, to apportion suspended particulate matter (SPM) contributions from three sources (arable topsoils, road verges, and subsurface material) under base flow conditions between August 2012 and August 2013. Whilst all 13 models estimate subsurface sources to be the largest contributor of SPM (median ∼76%), comparison of apportionment estimates reveal varying degrees of sensitivity to changing priors, inclusion of covariance terms, incorporation of time-variant distributions, and methods of proportion characterization. We also demonstrate differences in apportionment results between a full and an empirical Bayesian setup, and between a Bayesian and a frequentist optimization approach. This OFAT sensitivity analysis reveals that mixing model structural choices and error assumptions can significantly impact upon sediment source apportionment results, with estimated median contributions in this study varying by up to 21% between model versions. Users of mixing models are therefore strongly advised to carefully consider and justify their choice of model structure prior to conducting sediment source apportionment investigations