Contrasting controls on the phosphorus concentration of suspended particulate matter under baseflow and storm event conditions in agricultural headwater streams.

Whilst the processes involved in the cycling of dissolved phosphorus (P) in rivers have been extensively studied, less is known about the mechanisms controlling particulate P concentrations during small and large flows. This deficiency is addressed through an analysis of large numbers of suspended particulate matter (SPM) samples collected under baseflow (n=222) and storm event (n=721) conditions over a 23-month period across three agricultural headwater catchments of the River Wensum, UK. Relationships between clay mineral and metal oxyhydroxide associated elements were assessed and multiple linear regression models for the prediction of SPM P concentration under baseflow and storm event conditions were formulated. These models, which explained 71-96% of the variation in SPM P concentration, revealed a pronounced shift in P association from iron (Fe) dominated during baseflow conditions to particulate organic carbon (POC) dominated during storm events. It is hypothesised this pronounced transition in P control mechanism, which is consistent across the three study catchments, is driven by changes in SPM source area under differing hydrological conditions. In particular, changes in SPM Fe-P ratios between small and large flows suggest there are three distinct sources of SPM Fe; surface soils, subsurface sediments and streambed iron sulphide. Further examination of weekly baseflow data also revealed seasonality in the Fe-P and aluminium oxalate-dithionate (Alox-Aldi) ratios of SPM, indicating temporal variability in sediment P sorption capacity. The results presented here significantly enhance our understanding of SPM P associations with soil derived organic and inorganic fractions under different flow regimes and has implications for the mitigation of P originating from different sources in agricultural catchments.

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.

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. KEY POINTS: An OFAT sensitivity analysis of sediment fingerprinting mixing models is conductedBayesian models display high sensitivity to error assumptions and structural choicesSource apportionment results differ between Bayesian and frequentist approaches.

Sedimentary transport and fate of polycyclic aromatic hydrocarbons (PAH) from managed burning of moorland vegetation on a blanket peat, South Yorkshire, UK.

This study reports the concentrations of 18 polycyclic aromatic hydrocarbons (PAH) from managed burning of moorland vegetation and compares them to PAH in catchment vegetation, underlying peats, head water suspended sediment (HSS), stream water and reservoir sediment cores. Total PAH ranged from 203 to 11,112 µg/kg in the blanket peats, 101-290 µg/kg in the fresh moorland vegetation, 4186 µg/kg at the burnt site, 17,439 µg/kg in the HSS, 56 ng/L in the stream water and 987 to 7346 µg/kg in the reservoir sediments. No total or individual PAH concentrations exceeded the published sediment quality guidelines. The perylene content of selected moorland vegetation (sphagnum, heather and bilberry) ranged from 10 to 18% as compared to only 2% for the sediment hosted PAH. A comparison of whole and <250 µm fractions from the burnt surface layer revealed a near threefold increase in PAH concentration in the fine fraction and a change in the PAH distribution such that naphthalene>>phenanthrene>2-methylnaphthalene. Elevated total PAH contents were observed close to the blanket peat sediment surface (0-10 cm) and then declined at greater depths. The high PAH content of the HSS was attributed to the high sorption capacity of the organic-rich particles (TOC 25.8% (wt/wt)). The distribution of individual PAH in reservoir cores and HSS was consistent and the results of the principal component analysis and isomeric ratios suggest mainly pyrolytic inputs, from either vegetation burning and coal combustion. A comparison of the reservoir core PAH profiles shows that the source(s) have remained largely unchanged since the reservoir construction in 1929A.D. reflecting consistent moorland management practices.

Disaggregation of legacy soil data using area to point kriging for mapping soil organic carbon at the regional scale.

Legacy data in the form of soil maps, which often have typical property measurements associated with each polygon, can be an important source of information for digital soil mapping (DSM). Methods of disaggregating such information and using it for quantitative estimation of soil properties by methods such as regression kriging (RK) are needed. Several disaggregation processes have been investigated; preferred methods include those which include consideration of scorpan factors and those which are mass preserving (pycnophylactic) making transitions between different scales of investigation more theoretically sound. Area to point kriging (AtoP kriging) is pycnophylactic and here we investigate its merits for disaggregating legacy data from soil polygon maps. Area to point regression kriging (AtoP RK) which incorporates ancillary data into the disaggre-gation process was also applied. The AtoP kriging and AtoP RK approaches do not involve collection of new soil measurements and are compared with disaggregation by simple rasterization. Of the disaggregation methods investigated, AtoP RK gave the most accurate predictions of soil organic carbon (SOC) concentrations (smaller mean absolute errors (MAEs) of cross-validation) for disaggregation of soil polygon data across the whole of Northern Ireland. Legacy soil polygon data disaggregated by AtoP kriging and simple rasterization were used in a RK framework for estimating soil organic carbon (SOC) concentrations across the whole of Northern Ireland, using soil sample data from the Tellus survey of Northern Ireland and with other covariates (altitude and airborne radiometric potassium). This allowed direct comparison with previous analysis of the Tellus survey data. Incorporating the legacy data, whether from simple rasterization of the polygons or AtoP kriging, substantially reduced the MAEs of RK compared with previous analyses of the Tellus data. However, using legacy data disaggregated by AtoP kriging in RK resulted in a greater reduction in MAEs. A jack-knife procedure was also performed to determine a suitable number of additional soil samples that would need to be collected for RK of SOC for the whole of Northern Ireland depending on the availability of ancillary data. We recommend i) if only legacy soil polygon map data are available, they should be disaggregated using AtoP kriging, ii) if ancillary data are also available legacy data should be disaggregated using AtoP RK and iii) if new soil measurements are available in addition to ancillary and legacy soil map data, the legacy soil map data should be first disaggregated using AtoP kriging and these data used along with ancillary data as the fixed effects for RK of the new soil measurements.

Controls on catchment-scale patterns of phosphorus in soil, streambed sediment, and stream water.

Many models of phosphorus (P) transfer at the catchment scale rely on input from generic databases including, amongst others, soil and land use maps. Spatially detailed geochemical data sets have the potential to improve the accuracy of the input parameters of catchment-scale nutrient transfer models. Furthermore, they enable the assessment of the utility of available, generic spatial data sets for the modeling and prediction of soil nutrient status and nutrient transfer at the catchment scale. This study aims to quantify the unique and joint contribution of soil and sediment properties, land cover, and point-source emissions to the spatial variation of P concentrations in soil, streambed sediments, and stream water at the scale of a medium-sized catchment. Soil parent material and soil chemical properties were identified as major factors controlling the catchment-scale spatial variation in soil total P and Olsen P concentrations. Soil type and land cover as derived from the generic spatial database explain 33.7% of the variation in soil total P concentrations and 17.4% of the variation in Olsen P concentrations. Streambed P concentrations are principally related to the major element concentrations in streambed sediment and P delivery from the hillslopes due to sediment erosion. During base flow conditions, the total phosphorus (<0.45 microm) concentrations in stream water are mainly controlled by the concentrations of P and the major elements in the streambed sediment.

Potential and pitfalls in establishing the provenance of Earth-related samples in forensic investigations.

Earth scientists are often asked to establish or constrain the likely provenance of very small quantities of earth-related material as part of a forensic investigation. We tested the independent and collective interpretations of four experts with differing analytical skills in the prediction of sample provenance for three samples from different environmental settings. The methods used were X-ray diffraction, scanning electron microscopy, the assessment of pollen assemblages, and structural characterization of organic matter at the molecular level. Independent interpretations were less accurate than those where multiple techniques were combined. Collective interpretation was very effective in the assessment of provenance for two of the three sites where the mineralogy and plant communities were distinctive. At the other site, although the mineralogical analysis correctly identified the Triassic mudstone soil parent material, Carboniferous spores from domestic coal were initially interpreted as deriving directly from bedrock. Such an interpretation could be a common pitfall owing to anthropogenic redistribution of material such as coal.