Fine-scale temporal characterization of trends in soil water dissolved organic carbon and potential drivers

Long-term monitoring of surface water quality has shown increasing concentrations of Dissolved Organic Carbon (DOC) across a large part of the Northern Hemisphere. Several drivers have been implicated including climate change, land management change, nitrogen and sulphur deposition and CO2 enrichment. Analysis of stream water data, supported by evidence from laboratory studies, indicates that an effect of declining sulphur deposition on catchment soil chemistry is likely to be the primary mechanism, but there are relatively few long term soil water chemistry records in the UK with which to investigate this, and other, hypotheses directly. In this paper, we assess temporal relationships between soil solution chemistry and parameters that have been argued to regulate DOC production and, using a unique set of co-located measurements of weather and bulk deposition and soil solution chemistry provided by the UK Environmental Change Network and the Intensive Forest Monitoring Level II Network . We used statistical non-linear trend analysis to investigate these relationships at 5 forested and 4 non-forested sites from 1993 to 2011. Most trends in soil solution DOC concentration were found to be non-linear. Significant increases in DOC occurred mostly prior to 2005. The magnitude and sign of the trends was associated qualitatively with changes in acid deposition, the presence/absence of a forest canopy, soil depth and soil properties. The strongest increases in DOC were seen in acidic forest soils and were most clearly linked to declining anthropogenic acid deposition, while DOC trends at some sites with westerly locations appeared to have been influenced by shorter-term hydrological variation. The results indicate that widespread DOC increases in surface waters observed elsewhere, are most likely dominated by enhanced mobilization of DOC in surficial organic horizons, rather than changes in the soil water chemistry of deeper horizons. While trends in DOC concentrations in surface horizons have flattened out in recent years, further increases may be expected as soil chemistry continues to adjust to declining inputs of acidity.

Assessment and improvement of biotransfer models to cow’s milk and beef used in exposure assessment tools for organic pollutants

The aim of this study was to assess and improve the accuracy of biotransfer models for the organic pollutants (PCBs, PCDD/Fs, PBDEs, PFCAs, and pesticides) into cow’s milk and beef used in human exposure assessment. Metabolic rate in cattle is known as a key parameter for this biotransfer, however few experimental data and no simulation methods are currently available. In this research, metabolic rate was estimated using existing QSAR biodegradation models of microorganisms (BioWIN) and fish (EPI-HL and IFS-HL). This simulated metabolic rate was then incorporated into the mechanistic cattle biotransfer models (RAIDAR, ACC-HUMAN, OMEGA, and CKow). The goodness of fit tests showed that RAIDAR, ACC-HUMAN, OMEGA model performances were significantly improved using either of the QSARs when comparing the new model outputs to observed data. The CKow model is the only one that separates the processes in the gut and liver. This model showed the lowest residual error of all the models tested when the BioWIN model was used to represent the ruminant metabolic process in the gut and the two fish QSARs were used to represent the metabolic process in the liver. Our testing included EUSES and CalTOX which are KOW-regression models that are widely used in regulatory assessment. New regressions based on the simulated rate of the two metabolic processes are also proposed as an alternative to KOW-regression models for a screening risk assessment. The modified CKow model is more physiologically realistic, but has equivalent usability to existing KOW-regression models for estimating cattle biotransfer of organic pollutants.

Modelling the bioaccumulation of persistent organic pollutants in agricultural food chains for regulatory exposure assessment

New models for estimating bioaccumulation of persistent organic pollutants in the agricultural food chain were developed using recent improvements to plant uptake and cattle transfer models. One model named AgriSim was based on K OW regressions of bioaccumulation in plants and cattle, while the other was a steady-state mechanistic model, AgriCom. The two developed models and European Union System for the Evaluation of Substances (EUSES), as a benchmark, were applied to four reported food chain (soil/air-grass-cow-milk) scenarios to evaluate the performance of each model simulation against the observed data. The four scenarios considered were as follows: (1) polluted soil and air, (2) polluted soil, (3) highly polluted soil surface and polluted subsurface and (4) polluted soil and air at different mountain elevations. AgriCom reproduced observed milk bioaccumulation well for all four scenarios, as did AgriSim for scenarios 1 and 2, but EUSES only did this for scenario 1. The main causes of the deviation for EUSES and AgriSim were the lack of the soil-air-plant pathway and the ambient air-plant pathway, respectively. Based on the results, it is recommended that soil-air-plant and ambient air-plant pathway should be calculated separately and the K OW regression of transfer factor to milk used in EUSES be avoided. AgriCom satisfied the recommendations that led to the low residual errors between the simulated and the observed bioaccumulation in agricultural food chain for the four scenarios considered. It is therefore recommended that this model should be incorporated into regulatory exposure assessment tools. The model uncertainty of the three models should be noted since the simulated concentration in milk from 5th to 95th percentile of the uncertainty analysis often varied over two orders of magnitude. Using a measured value of soil organic carbon content was effective to reduce this uncertainty by one order of magnitude.

Transit times – the link between hydrology and water quality at the catchment scale

In spite of trying to understand processes in the same spatial domain, the catchment hydrology and water quality scientific communities are relatively disconnected and so are their respective models. This is emphasized by an inadequate representation of transport processes, in both catchment-scale hydrological and water quality models. While many hydrological models at the catchment scale only account for pressure propagation and not for mass transfer, catchment scale water quality models are typically limited by overly simplistic representations of flow processes. With the objective of raising awareness for this issue and outlining potential ways forward we provide a non-technical overview of (1) the importance of hydrology-controlled transport through catchment systems as the link between hydrology and water quality; (2) the limitations of current generation catchment-scale hydrological and water quality models; (3) the concept of transit times as tools to quantify transport and (4) the benefits of transit time based formulations of solute transport for catchment-scale hydrological and water quality models. There is emerging evidence that an explicit formulation of transport processes, based on the concept of transit times has the potential to improve the understanding of the integrated system dynamics of catchments and to provide a stronger link between catchment-scale hydrological and water quality models.

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 1x1 km 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.

Riparian shading controls instream spring phytoplankton and benthic diatom growth

Dissolved oxygen (DO) concentrations showed a striking pattern in a multi-year study of the River Enborne, a small river in SE England. In each of three years (2010-2012), maximum DO concentrations were attained in mid-April, preceded by a period of steadily increasing diurnal amplitudes, followed by a steady reduction in both amplitude and concentration. Flow events during the reduction period reduce DO to low concentrations until the following spring. Evidence is presented that this pattern is mainly due to benthic algal growth which is eventually supressed by the growth of the riparian tree canopy. Nitrate and silicate concentrations are too high to inhibit the growth of either benthic algae or phytoplankton, but phosphate concentrations might have started to reduce growth if the tree canopy development had been delayed. This interpretation is supported by evidence from weekly flow cytometry measurements and analysis of the diurnal, seasonal and annual patterns of nutrient concentrations. As the tree canopy develops, the river switches from an autotrophic to a heterotrophic state. The results support the use of riparian shading to help control algal growth, and highlight the risks of reducing riparian shade.