S.G. Anthony

Ensemble modelling of nutrient loads and nutrient load partitioning in 17 European catchments

An ensemble of nutrient models was applied in 17 European catchments to analyse the variation that appears after simulation of net nutrient loads and partitioning of nutrient loads at catchment scale. Eight models for N and five models for P were applied in three core catchments covering European-wide gradients in climate, topography, soil types and land use (Vansjø-Hobøl (Norway), Ouse (Yorkshire, UK) and Enza (Italy)). Moreover, each of the models was applied in 3-14 other EUROHARP catchments in order to inter-compare the outcome of the nutrient load partitioning at a wider European scale. The results of the nutrient load partitioning show a variation in the computed average annual nitrogen and phosphorus loss from agricultural land within the 17 catchments between 19.1-34.6 kg N ha(-1) and 0.12-1.67 kg P ha(-1). All the applied nutrient models show that the catchment specific variation (range and standard deviation) in the model results is lowest when simulating the net nutrient load and becomes increasingly higher for simulation of the gross nutrient loss from agricultural land and highest for the simulations of the gross nutrient loss from other diffuse sources in the core catchments. The average coefficient of variation for the model simulations of gross P loss from agricultural land is nearly twice as high (67%) as for the model simulations of gross N loss from agricultural land (40%). The variation involved in model simulations of net nutrient load and gross nutrient losses in European catchments was due to regional factors and the presence or absence of large lakes within the catchment.

Description of nine nutrient loss models: capabilities and suitability based on their characteristics

In EUROHARP, an EC Framework V project, which started in 2002 with 21 partners in 17 countries across Europe, a detailed intercomparison of contemporary catchment-scale modelling approaches was undertaken to characterise the relative importance of point and diffuse pollution of nutrients in surface freshwater systems. The study focused on the scientific evaluation of different modelling approaches, which were validated on three core catchments (the Ouse, UK; the Vansjo-Hobøl, Norway; and the Enza, Italy), and the application of each tool to three additional, randomly chosen catchments across Europe. The tools involved differ profoundly in their complexity, level of process representation and data requirements. The tools include simple loading models, statistical, conceptual and empirical model approaches, and physics-based (mechanistic) models. The results of a scientific intercomparison of the characteristics of these different model approaches are described. This includes an analysis of potential strengths and weaknesses of the nutrient models.

MIRSED towards an MIR approach to modelling hillslope soil erosion at the national scale.

This paper reports a new methodology for assessing regional and national patterns of hillslope scale soil erosion rates in the UK using a MIR (minimum information requirement) version of WEPP (Water Erosion Prediction Project) known as MIRSED. WEPP is parameterised using a national coverage, environmental database containing topographic, soil, land management and climate variables for all hillslopes within each grid cell to be modelled. The MIRSED matrix summarises the behaviour of WEPP in a multi-dimensional parameter space, allowing results to be queried using a subset of key, spatially variable parameters to produce an averaged hillslope soil erosion response from each 1 km2 grid cell. The approach is demonstrated for the Great Ouse catchment, Cambridgeshire, UK and highlights highest hillslope erosion rates of 2.2 t ha−1 year−1 associated with steepest slopes, erodible soils and management practices that leave the soil exposed for critical times of the year. A mean soil erosion rate of 0.4 t ha−1 year−1 is predicted from hillslopes across the catchment which compares well with observed data collated at different scales, using contrasting measurement techniques.

Modelling the cost-effectiveness of mitigation methods for multiple pollutants at farm scale

Reductions in agricultural pollution are essential for meeting nationally and internationally agreed policy targets for losses to both air and water. Numerous studies quantify the impact of relevant mitigation methods by field experimentation or computer modelling. The majority of these studies have addressed individual methods and frequently also individual pollutants. This paper presents a conceptual model for the synthesis of the evidence base to calculate the impact of multiple methods addressing multiple pollutants in order to identify least cost solutions for multiple policy objectives. The model is implemented as a farm scale decision support tool that quantifies baseline pollutant losses for identifiable sources, areas and pathways and incorporates a genetic algorithm based multi-objective procedure for determining optimal suites of mitigation methods. The tool is generic as baseline losses can be replaced with measured data and the default library of mitigation methods can be edited and expanded. The tool is demonstrated through application to two contrasting farm systems, using survey data on agricultural practices typical of England and Wales. These examples show how the tool could be used to help target the adoption of mitigation options for the control of diffuse pollution from agriculture. The feedback from workshops where Farmscoper was demonstrated is included to highlight the potential role of Farmscoper as part of the farm advisory process.

Predicting microbial water quality with models : over-arching questions for managing risk in agricultural catchments.

The application of models to predict concentrations of faecal indicator organisms (FIOs) in environmental systems plays an important role for guiding decision-making associated with the management of microbial water quality. In recent years there has been an increasing demand by policy-makers for models to help inform FIO dynamics in order to prioritise efforts for environmental and human-health protection. However, given the limited evidence-base on which FIO models are built relative to other agricultural pollutants (e.g. nutrients) it is imperative that the end-user expectations of FIO models are appropriately managed. In response, this commentary highlights four over-arching questions associated with: (i) model purpose; (ii) modelling approach; (iii) data availability; and (iv) model application, that must be considered as part of good practice prior to the deployment of any modelling approach to predict FIO behaviour in catchment systems. A series of short and longer-term research priorities are proposed in response to these questions in order to promote better model deployment in the field of catchment microbial dynamics.

Predicting potential change in agricultural sediment inputs to rivers across England and Wales by 2015

Recent work has evaluated the gap between current and compliant suspended sediment losses due to farming across England and Wales and the potential for change by 2015. The study adopted the guideline annual average sediment threshold of 25 mg L–1 cited by the European Union Freshwater Fish Directive. Compliance testing required national scale sediment source apportionment to assess the current contributions of diffuse agricultural and urban sector losses, channel bank erosion and point source discharges to the total suspended sediment loads delivered to all rivers. Results suggested that the agricultural sector dominates present day (year 2000) sediment inputs to rivers (1929 kt = 76%) compared with eroding channel banks (394 kt = 15%), diffuse urban sources (147 kt = 6%) and point source discharges (76 kt = 3%). Projected change in farming by 2015, represented by the Business As Usual forecast of structural developments and predicted uptake of sediment mitigation methods, suggested a 9% reduction in sediment losses from the agricultural sector across England and Wales. Further mitigation of diffuse agricultural sediment transfers to watercourses will therefore be necessary to ensure ‘good ecological status’ in some catchments. A similar modelling framework could be applied in other countries.

A Model for Sclerotinia sclerotiorum Infection and Disease Development in Lettuce, Based on the Effects of Temperature, Relative Humidity and Ascospore Density

The plant pathogen Sclerotinia sclerotiorum can cause serious losses on lettuce crops worldwide and as for most other susceptible crops, control relies on the application of fungicides, which target airborne ascospores. However, the efficacy of this approach depends on accurate timing of these sprays, which could be improved by an understanding of the environmental conditions that are conducive to infection. A mathematical model for S. sclerotiorum infection and disease development on lettuce is presented here for the first time, based on quantifying the effects of temperature, relative humidity (RH) and ascospore density in multiple controlled environment experiments. It was observed that disease can develop on lettuce plants inoculated with dry ascospores in the absence of apparent leaf wetness (required for spore germination). To explain this, the model conceptualises an infection court area containing microsites (in leaf axils and close to the stem base) where conditions are conducive to infection, the size of which is modified by ambient RH. The model indicated that minimum, maximum and optimum temperatures for ascospore germination were 0.0, 29.9 and 21.7°C respectively and that maximum rates of disease development occurred at spore densities >87 spores cm−2. Disease development was much more rapid at 80–100% RH at 20°C, compared to 50–70% RH and resulted in a greater proportion of lettuce plants infected. Disease development was also more rapid at 15–27°C compared to 5–10°C (85% RH). The model was validated by a further series of independent controlled environment experiments where both RH and temperature were varied and generally simulated the pattern of disease development well. The implications of the results in terms of Sclerotinia disease forecasting are discussed.

Review and analysis of global agricultural N2O emissions relevant to the UK

As part of a UK government funded research project to update the UK N2O inventory methodology, a systematic review of published nitrous oxide (N2O) emission factors was carried out of non-UK research, for future comparison and synthesis with the UK measurement based evidence base. The aim of the study is to assess how the UK IPCC default emission factor for N2O emissions derived from synthetic or organic fertiliser inputs (EF1) compares to international values reported in published literature. The availability of data for comparing and/or refining the UK IPCC default value and the possibility of analysing sufficient auxiliary data to propose a Tier 2 EF1 reporting strategy is evaluated. The review demonstrated a lack of consistency in reporting error bounds for fertiliser-derived EFs and N2O flux data with 8% and 44% of publications reporting EF and N2O flux error bounds respectively. There was also poor description of environmental (climate and soil) and experimental design auxiliary data. This is likely to be due to differences in study objectives, however potential improvements to soil parameter reporting are proposed. The review demonstrates that emission factors for agricultural-derived N2O emissions ranged -0.34% to 37% showing high variation compared to the UK Tier 1 IPCC EF1 default values of 1.25% (IPCC 1996) and 1% (IPPC 2006). However, the majority (83%) of EFs reported for UK-relevant soils fell within the UK IPCC EF1 uncertainty range of 0.03% to 3%. Residual maximum likelihood (REML) analysis of the data collated in the review showed that the type and rate of fertiliser N applied and soil type were significant factors influencing EFs reported. Country of emission, the length of the measurement period, the number of splits, the crop type, pH and SOC did not have a significant impact on N2O emissions. A subset of publications where sufficient data was reported for meta-analysis to be conducted was identified. Meta-analysis of effect sizes of 41 treatments demonstrated that the application of fertiliser has a significant effect on N2O emissions in comparison to control plots and that emission factors were significantly different to zero. However no significant relationships between the quantity of fertiliser applied and the effect size of the amount of N2O emitted from fertilised plots compared to control plots were found. Annual addition of fertiliser of 35 to 557 kg N/ha gave a mean increase in emissions of 2.02 ± 0.28 g N2O/ha/day compared to control treatments (p<0.01). Emission factors were significantly different from zero, with a mean emission factor estimated directly from the meta analysis of 0.17 ± 0.02%. This is lower than the IPCC 2006 Tier 1 EF1 value of 1% but falling within the uncertainty bound for the IPCC 2006 Tier 1 EF1 (0.03% to 3%). As only a small number of papers were viable for meta analysis to be conducted due to lack of reporting of the key controlling factors, the estimates of EF in this paper cannot include the true variability under conditions similar to the UK. Review-derived EFs of 0.34% to 37% and mean EF from meta-analysis of 0.17 ± 0.02% highlight variability in reporting EFs depending on the method applied and sample size. A protocol of systematic reporting of N2O emissions and key auxiliary parameters in publications across disciplines is proposed. If adopted this would strengthen the community to inform IPCC Tier 2 reporting development and reduce the uncertainty surrounding reported UK N2O emissions.

A field scale model of soil drainage and nitrate leaching for application in nitrate vulnerable zones

We present a new conceptual model of nitrate leaching from structured soils at the field scale that is readily parameterised from nationally available soil datasets. The model explicitly captures the effects of incomplete equilibration between mobile and immobile waters, and lateral flow in the presence of tile drainage. The derivation of parameters and model validation are illustrated by the application of the model to experimental data sets from intensively monitored soil drainage systems at the ADAS Gleadthorpe, Boxworth, Brimstone and Rosemaund field experimentation sites in the UK. Results of the validation show that the model is capable of simulating the drain flow hydrographs observed on structured soils and also capturing the variations in over-winter leaching occurring on both unstructured and structured soils (respective r^2 of 0.58 and 0.49). The model also captures some of the daily variations in nitrate concentrations characteristic of structured soils.

A model‐based assessment of non‐compliance of phosphorus standards for lakes in England and Wales

Abstract High phosphorus concentrations causing eutrophication will prevent many lakes in England and Wales from reaching good ecological status by 2015 according to the EC Water Framework Directive (WFD). The aim of this study was to estimate the percentage of lakes in England and Wales that are likely to fail recently agreed WFD phosphorus standards. As measured lake phosphorus concentrations are only available for a small number of lakes a model‐based approach was adopted. This involved estimating phosphorus loads from a wide range of sources including agricultural loads, sewage effluents, septic tanks, diffuse urban sources, atmospheric deposition, groundwater and bank erosion. Lake phosphorus concentrations were predicted using the Vollenweider model, and the model framework was satisfactorily tested against available observed lake concentration data. Applying the model to all lakes in England and Wales greater than 1 ha, it was estimated that under current conditions, roughly two thirds of the lakes would fail good ecological status with respect to phosphorus. According to our estimates, agricultural phosphorus loads represent the dominant source for the majority of catchments, but diffuse urban runoff also is important in many lakes and sewage effluents are the most frequent dominant source for lake catchments greater than 100 km2. Required reductions of phosphorus loads to increase the number of lakes achieving good ecological status and potential delays because of internal loading and biological resistances are briefly discussed.