In bloom

Much of the phosphorus which ends up in stream sediment, either through soil erosion or via field drains, is transported attached to particles. The quantity and chemical form of phosphorus in the stream sediment largely controls its concentration in stream water. The phosphorus in the sediments is associated with particular components such as organic matter, iron-bearing minerals and clay minerals

Comment on : 'multi-element signatures of stream sediments and sources under moderate to low flow conditions' by M.I. Stutter, S.J. Langan, D.G. Lumsdon, L.M. Clark

In a recent paper on ‘Multi-element signatures of stream sediments and sources under moderate to low flow conditions’, Stutter et al., 2009 M.I. Stutter, S.J. Langan, D.G. Lumsdon and L.M. Clark, Multi-element signatures of stream sediments and sources under moderate to low flow conditions, Appl. Geochem. 24 (2009), pp. 800–809. Article | PDF (392 K) | View Record in Scopus | Cited By in Scopus (2)Stutter et al. (2009) presented results of a simple sediment source tracing method based on major and trace elements for a small agricultural catchment in NE Scotland. The authors reported statistically significant, larger concentrations of four trace elements (Ce, Nd, Th and Y) in bank subsoils (n = 5) and stream bed sediments (n = 3) compared to topsoils from both pasture (n = 5) and arable (n = 5) land. They used these differences to aid discrimination between topsoil and subsoil (stream bank erosion) contributions to bed sediment. These elements may be more depleted in topsoil compared to subsoil because the former have been subject to more intense weathering over a longer period. If these naturally occurring trace elements could be used to understand the relative proportions of topsoil and subsoil contributions to headwater bed sediments this approach might be applied more widely to elucidate transport pathways for the transfer of agricultural contaminants such as particulate phosphorus to streams (Walling et al., 2008). This approach warrants further investigation across a range of catchments at different scales with contrasting land use and bedrock types. This can be undertaken using data from regional-scale geochemical surveys (Johnson et al., 2005) which include analyses of both stream bed sediments and subsoil samples. Previous studies have shown that much of lowland central England is at risk of topsoil transfer to watercourses via land drains (Chapman et al., 2003). A geochemical survey across part of central England covering 15 400 km2 was recently undertaken and these data are well-suited to testing whether three of the four trace elements identified by Stutter et al. (2009) might be used to discriminate between topsoil and subsoil in sediments more widely. Specifically, if the concentrations of these elements are significantly smaller in stream bed sediments than in the subsoil, this may be due to mixing with topsoils which have lower concentrations of these elements. Below the regional-scale survey, the methods the author used to compare the geochemical data in subsoil and bed sediments described, and the findings and their implications discussed

Using air photos to parameterise landscape predictors of channel wetted width at baseflow

Evasion of carbon dioxide from the surface of freshwater channels accounts for a substantial proportion of its flux from the terrestrial biosphere to the atmosphere; accurate estimates of channel wetted width (WW) are required to improve predictions of this flux. We investigated which landscape and climate-related data were statistically significant predictors of WW at baseflow across a large region (2200 km2) of north Wales and western England (UK) where habitat surveys suggest the majority of channels are in a near natural state. We used 25 cm pixel resolution air photos to measure channel WW at baseflow, and quantified the magnitude of the errors in these measurements. We used flow information from local gauging stations to ensure that channels were at or close to baseflow for the days on which the air photos were captured. The root mean squared difference between the fieldbased and air photo measurements of WW (n=28 sites) was small (0.14 m) in comparison to the median channel WW (3.07 m), and there was very little bias between the two sets of measurements (0.026 m). We created a set of points along those sections of channels which were visible in air photos and used a digital terrain model to create the drainage catchments for the points and computed their catchment area (CA).We removed points with CA <1 km2 and selected a random subset from the remaining points (n=472). We measured channel WW at these points from air photos and computed landscape and climate-related data for each of their catchments (mean slope, mean annual rainfall, land cover type, elevation) and also mean BFIHOST, a quantitative index relating to hydrological source of flow. We also computed the local slope at each of the selected points on the channel. As these data were not independent random variables, we used the linear mixed model framework with WW as the predictand and included the various landscape and climate-related data (including CA0:5) as fixed effects. We included a spatial covariance function using residual maximum likelihood which computes unbiased estimates of the predictors and accounts for clustering in the sample data. There was no evidence for retaining the spatial covariance function and so we computed a linear model by ordinary least squares and selected predictors using a stepwise procedure.With the exception of land cover, all the predictors were statistically significant and accounted for 76% of the variance of channelWW. When CA0:5 alone was used as a predictor it captured 54% of the variance. The vast majority of this difference was due to inclusion of an interaction between CA and hydrological source of flow (BFIHOST). As catchment area increases, those channels with larger mean catchment BFIHOST values (greater baseflow) have narrower channel WW by comparison to those with smaller mean BFIHOST for the same CA

Assessing geostatistical methods for presenting urban soil geochemical data from Coventry

The current shortest distance between sample points in urban soil surveys of the BGS GSUE (Geochemical Surveys in Urban Environments) project is around 350 metres. Geostatistical analysis using soil geochemical data from the survey of Stoke-on-Trent had shown that much of the variation occurs at shorter sampling intervals (less than 350 metres). This means that the uncertainties associated with estimating values at unsampled locations (using kriging) are likely to be relatively large. A project was designed to address three specific, and related, questions. First, what is the nature of the short-scale variability of major and trace elements in urban environments? Second, would recently published, robust geostatistical methods be more appropriate for producing interpolated maps of urban soil geochemistry in which there may be two processes operating; a background process and a quasi-point contaminant process? Third, is the current sampling resolution (adopted in urban surveys) appropriate? To address the first question we undertook a ‘nested’ survey at selected nodes within the urban area of Coventry where a standard GSUE survey had recently been undertaken. These samples were analysed for the same suite of major and trace elements as the standard survey, and also for their particle-size distribution (proportions of sand, silt and clay). In the case of the typical contaminant type elements (Pb, Sn, Sb, Cd, Ni, Cu and Zn) a large proportion (22-75%) of the variation occurred at spatial scales of 30 metres or less, compared to a range of major and trace elements and particle size classes. Without further chemical analysis, it is not possible to determine whether this variation is due to anthropogenic impacts (pollution) or natural variation. However, many of these elements are common environmental pollutants suggesting that their greater short-scale variability may result from human activities. The information on variability at short spatial scales collected in the nested survey enabled us to plot variograms for a range of elements in which almost all the spatial variation was captured. Robust geostatistical methods may be more appropriate when dealing with datasets in which there are a considerable number of outlying values. An assessment of conventional and robust geostatistical estimators was undertaken based on five elements with significantly skewed distributions (Cd, As, Pb, Zn and Ni). Based on the results of a cross-validation exercise, the conventional geostatistical estimator (that due to Matheron) was found to be optimal for estimating Cd, As, Pb and Ni. However, in the case of the data for Zn, in which there were a considerable number of outlying values, a robust estimator (Cressie-Hawkins) performed best. If optimal interpolation methods are to be used in mapping urban soil geochemistry, it is recommended that when a large number of outliers are present in a dataset, a comparison of robust and classical estimators is undertaken. In the case of Zn, another statistical technique was used to identify 29 spatial outliers - samples which appear to be the outcome of a quasi-point process. Interpolated maps were generated both with and without the spatial outliers to determine the scale of their impact on the background process. In the case of the latter, there was a significant difference in the distribution in the region of the highest values. In addition, a number of the ‘bullseye’ patterns which were associated with spatial outliers have been removed. This is a useful technique for separating the background process from the effects of a quasi-point process. However, it is computationally demanding and time-consuming. It remains to be seen whether a customer from a local authority would be prepared to pay for this level of skilled analysis in the preparation of contour maps. To determine whether robust geostatistcal methods should be applied to other urban data, there is a need to determine the skewness coefficients and the number of outliers in datasets from the other urban centres. This will provide a better understanding of whether the Coventry data is typical of the other centres for which data are available. Geostatistcal analysis of urban geochemical data to date has indicated that the current sampling resolution adopted in urban surveys does capture a varying proportion of the spatially correlated variation for most of the contaminant type elements. On the basis of the work presented here we would not advocate changing the current (4 samples per square kilometre) sampling resolution. However, when producing a continuous surface map, it is essential first to undertake exploratory data analysis and construct variograms of the data to assess the degree of autocorrelation prior to kriging. If little or no autocorrelation is present, it is preferable to present the data as proportional symbols because there is little or nothing to be gained from interpolation. When a continuous surface map has been produced it should be accompanied by a description of the method used to create it, and a statement that the contour intervals represent estimates, not true values. The nested survey also identified Cd (cadmium) contamination at the site of a series of allotments. Comparison with recently published soil guideline values suggests that it may represent a potentially significant risk to human health. This issue is currently being raised with the City Council. To increase the utility of the soil geochemical data collected in the urban environment, we recommend that it would be beneficial to focus on perhaps two or three key sites in an urban area where human exposure to contamination may be significant, such as allotments, children’s nurseries or groundwater protection zones. These sites could be selected in conjunction with the City/Local Council on the basis of land use information which may indicate the likely presence of historical contamination

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

High-temporal Resolution Sediment Fingerprinting in the River Wensum Demonstration Test Catchment, UK: A Bayesian Approach

A high-temporal resolution fluvial sediment source apportionment model, set within an empirical Bayesian framework, is presented for the River Wensum Demonstration Test Catchment (DTC), UK. Direct X-ray fluorescence (XRF) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analysis of sediment covered filter papers were used in conjunction with ISCO automatic water samplers to monitor suspended particulate matter (SPM) geochemistry at high-temporal resolution throughout the progression of five heavy precipitation events during 2012-2013. Exploiting the spatial and temporal variation in four potential sediment source areas and SPM geochemistry respectively, we are able to apportion sediment contributions from eroding stream channel banks, arable topsoils, damaged road verges and agricultural field drains at 60-120 minute resolution. For all monitored precipitation episodes, pre- and post-event conditions are dominated by elevated SPM calcium concentrations that indicate major sediment inputs from carbonate-rich subsurface sources. Conversely, precipitation events coincide with an increase in concentrations of clay-associated elements and a consequent increase in predicted contributions from surface sources. Employing a Gibbs sampling Markov Chain Monte-Carlo mixing model procedure has enabled full characterisation of both spatial geochemical variability and instrument precision to quantify uncertainty around posterior distributions. All model source apportionment estimates correspond favourably with understanding of the regional geology, analysis of hysteresis behaviour, and visual observations of catchment processes. The results presented here demonstrate how to directly analyse SPM trapped on filter papers by spectroscopy to yield the high-temporal resolution source apportionment estimates required by catchment managers to help mitigate the deleterious effects of land-to-river sediment transfer

Intermittent Small Baseline Subset (ISBAS) monitoring of land covers unfavourable for conventional C-band InSAR: proof-of-concept for peatland environments in North Wales, UK

This paper provides a proof-of-concept for the use of the new Intermittent Small Baseline Subset (ISBAS) approach to study ground elevation changes in areas of peat and organic soils in north Wales, which are generally, unfavourable for conventional C-band interferometric applications. A stack of 53 ERS-1/2 C-band SAR scenes acquired between 1993 and 2000 in descending mode was processed with both the standard low-pass SBAS method and ISBAS. The latter revealed exceptional improvements in the coverage of ground motion solutions with respect to the standard approach. The number of identified coherent and intermittently coherent pixels increased by a factor of 26 with respect to the SBAS solution, and extended the coverage of results across unfavourable land covers, particularly for coniferous woodland, bog, acid grassland and heather. The greatest increase was achieved over coniferous woodland, which showed ISBAS/SBAS pixel density ratios above 300. Despite the intermittent nature of the ISBAS solutions, ISBAS provided velocity standard errors generally below 1-1.5 mm/yr, thus preserving good quality of the estimated ground motion rates

Identify the opportunities provided by developments in earth observation and remote sensing for national scale monitoring of soil quality

Defra wish to establish to what extent national-scale soil monitoring (both state and change) of a series of soil indicators might be undertaken by the application of remote sensing methods. Current soil monitoring activities rely on the field-based collection and laboratory analysis of soil samples from across the landscape according to different sampling designs. The use of remote sensing offers the potential to encompass a larger proportion of the landscape, but the signal detected by the remote sensor has to be converted into a meaningful soil measurement which may have considerable uncertainty associated with it. The eleven soil indicators which were considered in this report are pH, organic carbon, bulk density, phosphorus (Olsen P), nitrogen (total N), magnesium (extractable), potassium (extractable), copper (aqua regia extractable), cadmium (aqua regia extractable), zinc (aqua regia extractable) and nickel (aqua regia extractable). However, we also comment on the potential use of remote sensing for monitoring of soil depth and (in particular) peat depth, plus soil erosion and compaction. In assessing the potential of remote sensing methods for soil monitoring of state and change, we addressed the following questions: 1. When will these be ready for use and what level of further development is required? 2. Could remote sensing of any of these indicators replace and/or complement traditional field based national scale soil monitoring? 3. Can meaningful measures of change be derived? 4. How could remote soil monitoring of individual indicators be incorporated into national scale soil monitoring schemes? To address these questions, we undertook a comprehensive literature and internet search and also wrote to a range of international experts in remote sensing. It is important to note that the monitoring of the status of soil indicators, and the monitoring of their change, are two quite different challenges; they are different variables and their variability is likely to differ. There are particular challenges to the application of remote sensing of soil in northern temperate regions (such as England and Wales), including the presence of year-round vegetation cover which means that soil spectral reflectance cannot be captured by airborne or satellite observations, and long-periods of cloud cover which limits the application of satellite-based spectroscopy. We summarise the potential for each of the indicators, grouped where appropriate. Unless otherwise stated, the remote sensing methods would need to be combined with ground-based sampling and analysis to make a contribution to detection of state or change in soil indicators. Soil metals (copper (Cu), cadmium (Cd), zinc (Zn), nickel (Ni)): there is no technical basis for applying current remote sensing approaches to monitor either state or change of these indicators and there are no published studies which have shown how this might be achieved. Soil nutrients: the most promising remote sensing technique to improve estimates of the status of extractable potassium (K) is the collection and application of airborne radiometric survey (detection of gamma radiation by low-flying aircraft) but this should be investigated further. This is unlikely to assist in monitoring change. Based on published literature, it may be possible to enhance mapping the state of extractable magnesium (Mg), but not to monitor change, using hyperspectral (satellite or airborne) remote sensing in cultivated areas. This needs to be investigated further. There are no current remote sensing methods for detecting state or change of Olsen (extractable) phosphorus (P). Organic carbon and total nitrogen: Based on published literature, it may be possible to enhance mapping the state of organic carbon and total nitrogen (but not to monitor change), using hyperspectral (satellite or airborne) remote sensing in cultivated areas only. In applying this approach the satellite data are applied using a statistical model which is trained using ground-based sampling and analysis of soil

Combining Two Filter Paper-Based Analytical Methods to Monitor Temporal Variations in Fluvial Suspended Solid Properties

Many of the commonly used analytical techniques for assessing the properties of fluvial suspended solids are neither cost-effective nor time-efficient, making them prohibitive to long-term high-resolution monitoring.We propose a novel methodology utilising two types of spectroscopy which, when combined with automatic water samplers, can generate accurate, high-temporal resolution sediment property data, inexpensively and non-destructively, directly from sediment covered filter papers. A dual X-ray fluorescence spectroscopy (XRFS) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) approach is developed to estimate concentrations for a range of elements (Al, Ca, Ce, Fe, K, Mg, Mn, Na, P, Si, Ti) and compounds (organic carbon, Aldithionate, Aloxalate, Fedithionate, and Feoxalate) within sediments trapped on quartz fibre filters at masses as low as 3 mg. Calibration models with small prediction errors are produced for a total of 16 elements and compounds for which the geochemical signal is demonstrated to be time stable enabling samples to be stored for several weeks prior to analysis. Spectral pre-processing methods are shown to enhance the reproducibility of results for some compounds, whilst corrections for sediment mass retention are derived, and the importance of filter paper selection and homogeneous sample preparation in minimising spectral interference are emphasized. The results presented here demonstrate the potential for a combined XRFS and DRIFTS analysis of sediment covered filter papers to be utilized under a range of in-stream hydrological conditions where there is an environmental requirement for high-resolution monitoring of suspended solid properties

Three-dimensional soil organic matter distribution, accessibility and microbial respiration in macroaggregates using osmium staining and synchrotron X-ray computed tomography

The spatial distribution and accessibility of organic matter (OM) to soil microbes in aggregates – determined by the fine-scale, 3-D distribution of OM, pores and mineral phases – may be an important control on the magnitude of soil heterotrophic respiration (SHR). Attempts to model SHR on fine scales requires data on the transition probabilities between adjacent pore space and soil OM, a measure of microbial accessibility to the latter. We used a combination of osmium staining and synchrotron X-ray computed tomography (CT) to determine the 3-D (voxel) distribution of these three phases (scale 6.6 μm) throughout nine aggregates taken from a single soil core (range of organic carbon (OC) concentrations: 4.2–7.7 %). Prior to the synchrotron analyses we had measured the magnitude of SHR for each aggregate over 24 h under controlled conditions (moisture content and temperature). We test the hypothesis that larger magnitudes of SHR will be observed in aggregates with (i) shorter length scales of OM variation (more aerobic microsites) and (ii) larger transition probabilities between OM and pore voxels. After scaling to their OC concentrations, there was a 6-fold variation in the magnitude of SHR for the nine aggregates. The distribution of pore diameters and tortuosity index values for pore branches was similar for each of the nine aggregates. The Pearson correlation between aggregate surface area (normalized by aggregate volume) and normalized headspace C gas concentration was both positive and reasonably large (r D0.44), suggesting that the former may be a factor that influences SHR. The overall transition probabilities between OM and pore voxels were between 0.07 and 0.17, smaller than those used in previous simulation studies. We computed the length scales over which OM, pore and mineral phases vary within each aggregate using 3-D indicator variograms. The median range of models fitted to variograms of OM varied between 38 and 175 μm and was generally larger than the other two phases within each aggregate, but in general variogram models had ranges <250 μm. There was no evidence to support the hypotheses concerning scales of variation in OM and magnitude of SHR; the linear correlation was 0.01. There was weak evidence to suggest a statistical relationship between voxel-based OM–pore transition probabilities and the magnitudes of aggregate SHR (r D0.12).We discuss how our analyses could be extended and suggest improvements to the approach we used