Heather Carter

Freshwater DOM quantity and quality from a two-component model of UV absorbance

We present a model that considers UV-absorbing dissolved organic matter (DOM) to consist of two components (A and B), each with a distinct and constant spectrum. Component A absorbs UV light strongly, and is therefore presumed to possess aromatic chromophores and hydrophobic character, whereas B absorbs weakly and can be assumed hydrophilic. We parameterised the model with dissolved organic carbon concentrations [DOC] and corresponding UV spectra for c. 1700 filtered surface water samples from North America and the United Kingdom, by optimising extinction coefficients for A and B, together with a small constant concentration of non-absorbing DOM (0.80 mg DOCL⁻¹). Good unbiased predictions of [DOC] from absorbance data at 270 and 350 nm were obtained (r² = 0.98), the sum of squared residuals in [DOC] being reduced by 66% compared to a regression model fitted to absorbance at 270 nm alone. The parameterised model can use measured optical absorbance values at any pair of suitable wavelengths to calculate both [DOC] and the relative amounts of A and B in a water sample, i.e. measures of quantity and quality. Blind prediction of [DOC] was satisfactory for 9 of 11 independent data sets (181 of 213 individual samples).

Aluminium speciation in streams and lakes of the UK Acid Waters Monitoring Network, modelled with WHAM

The Windermere Humic Aqueous Model (WHAM) incorporating Humic Ion-Binding Model VI was applied to analytical data from the United Kingdom Acid Waters Monitoring Network, collected for 22 streams and lakes over the period 1988-2007, to calculate the chemical speciation of monomeric aluminium (Al(mon)) in 3087 water samples. Model outputs were compared with analytical measurements of labile and non-labile Al(mon) concentrations, the former being equated with inorganic forms of Al(mon) and the latter with organically-complexed metal. Raw analytical data were used, and also data produced by applying a correction for the possible dissociation of organically-complexed Al(mon), and therefore its underestimation, during passage through the analytical cation-exchange column. Model calibration was performed by finding the conversion factor, F(FADOC), between the concentration of isolated fulvic acid, with default ion-binding properties, required by the model, and the measured concentration of dissolved organic carbon, [DOC]. For both uncorrected and corrected data, the value of F(FADOC) for streams was greater than for lakes, indicating greater binding activity towards aluminium. Model fits were better using uncorrected analytical data, but the values of F(FADOC) obtained from corrected data agreed more closely with previous estimates. The model provided reasonably good explanations of differences in aluminium speciation between sampling sites, and of temporal variations at individual sites. With total monomeric concentration as input, WHAM calculations might substitute for analytical speciation measurements, or aid analytical quality control. Calculated Al(3+) activities, a(Al3+), showed a pH-dependence similar to that previously found for other surface waters, and the modelling exercise identified differences between waters of up to two orders of magnitude in the value of a(Al3+) at a given pH. The model gives the net charge of dissolved organic matter, which is calculated to have risen significantly at 15 of the AWMN sites, due to increases in pH and decreases in aluminium concentration.

Spatial patterns and environmental constraints on ecosystem services at a catchment scale.

Improved understanding and prediction of the fundamental environmental controls on ecosystem service supply across the landscape will help to inform decisions made by policy makers and land-water managers. To evaluate this issue for a local catchment case study, we explored metrics and spatial patterns of service supply for water quality regulation, agriculture production, carbon storage, and biodiversity for the Macronutrient Conwy catchment. Methods included using ecosystem models such as LUCI and JULES, integration of national scale field survey datasets, earth observation products and plant trait databases, to produce finely resolved maps of species richness and primary production. Analyses were done with both 1×1km gridded and subcatchment data. A common single gradient characterised catchment scale ecosystem services supply with agricultural production and carbon storage at opposing ends of the gradient as reported for a national-scale assessment. Species diversity was positively related to production due to the below national average productivity levels in the Conwy combined with the unimodal relationship between biodiversity and productivity at the national scale. In contrast to the national scale assessment, a strong reduction in water quality as production increased was observed in these low productive systems. Various soil variables were tested for their predictive power of ecosystem service supply. Soil carbon, nitrogen, their ratio and soil pH all had double the power of rainfall and altitude, each explaining around 45% of variation but soil pH is proposed as a potential metric for ecosystem service supply potential as it is a simple and practical metric which can be carried out in the field with crowd-sourcing technologies now available. The study emphasises the importance of considering multiple ecosystem services together due to the complexity of covariation at local and national scales, and the benefits of exploiting a wide range of metrics for each service to enhance data robustness.

Determining E. coli burden on pasture in a headwater catchment: Combined field and modelling approach

Empirical monitoring studies of catchment-scale Escherichia coli burden to land from agriculture are scarce. This is not surprising given the complexity associated with the temporal and spatial heterogeneity in the excretion of livestock faecal deposits and variability in microbial content of faeces. However, such information is needed to appreciate better how land management and landscape features impact on water quality draining agricultural landscapes. The aim of this study was to develop and test a field-based protocol for determining the burden of E. coli in a small headwater catchment in the UK. Predictions of E. coli burden using an empirical model based on previous best estimates of excretion and shedding rates were also evaluated against observed data. The results indicated that an empirical model utilising key parameters was able to satisfactorily predict E. coli burden on pasture most of the time, with 89% of observed values falling within the minimum and maximum range of predicted values. In particular, the overall temporal pattern of E. coli burden on pasture is captured by the model. The observed and predicted values recorded a disagreement of >1 order of magnitude on only one of the nine sampling dates throughout an annual period. While a first approximation of E. coli burden to land, this field-based protocol represents one of the first comprehensive approaches for providing a real estimate of a dynamic microbial reservoir at the headwater catchment scale and highlights the utility of a simple dynamic empirical model for a more economical prediction of catchment-scale E. coli burden.

The contribution of algae to freshwater dissolved organic matter: implications for UV spectroscopic analysis

Abstract Dissolved organic matter (DOM) is an important constituent of freshwater that participates in a number of key ecological and biogeochemical processes but can be problematic during water treatment. Thus, the demand for rapid and reliable monitoring is growing, and spectroscopic methods are potentially useful. A model with 3 components—2 that absorb in the ultraviolet (UV) range and are present at variable concentrations and a third that does not absorb light and is present at a low constant concentration—was previously found to yield reliable predictions of dissolved organic carbon concentration [DOC]. The model underestimated [DOC] in shallow eutrophic lakes in the Yangtze Basin, China, however, raising the possibility that DOM derived from algae might be poorly estimated, an idea supported by new data reported here for eutrophic British lakes. We estimated the extinction coefficients in the UV range of algae-derived DOM from published data on algal cultures and from new data from outdoor mesocosm experiments in which high concentrations of DOC were generated under conditions comparable to those in eutrophic freshwaters. The results demonstrate the weak UV absorbance of DOM from algae compared to DOM from terrestrial sources. A modified model, in which the third component represents algae-derived DOM present at variable concentrations, allowed contributions of such DOM to be estimated by combining the spectroscopic data with [DOC] measured by laboratory combustion. Estimated concentrations of algae-derived DOC in 77 surface freshwater samples ranged from 0 to 8.6 mg L−1, and the fraction of algae-derived DOM ranged from 0% to 100%.