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River discharge and nutrient measurements are subject to aleatory and epistemic uncertainties. In this study, we present a novel method for estimating these uncertainties in colocated discharge and phosphorus (P) measurements. The “voting point”‐based method constrains the derived stage‐discharge rating curve both on the fit to available gaugings and to the catchment water balance. This helps reduce the uncertainty beyond the range of available gaugings and during out of bank situations. In the example presented here, for the top 5% of flows, uncertainties are shown to be 139% using a traditional power law fit, compared with 40% when using our updated “voting point” method. Furthermore, the method is extended to in situ and lab analysed nutrient concentration data pairings, with lower uncertainties (81%) shown for high concentrations (top 5%) than when a traditional regression is applied (102%). Overall, for both discharge and nutrient data, the method presented goes some way to accounting for epistemic uncertainties associated with nonstationary physical characteristics of the monitoring site.

There is a need to model and predict the transfer of phosphorus (P) from land to water, but this is challenging because of the large number of complex physical and biogeochemical processes involved. This study presents, for the first time, a ‘limits of acceptability’ approach of the Generalized Likelihood Uncertainty Estimation (GLUE) framework to the Soil and Water Assessment Tool (SWAT), in an application to a water quality problem in the Newby Beck Catchment (12.5km2), Cumbria, United Kingdom (UK). Using high frequency outlet data (discharge and P), individual evaluation criteria (limits of acceptability) were assigned to observed discharge and P loads for all evaluation time steps, identifying where the model was performing well/poorly and to infer which processes required improvement in the model structure. Initial limits of acceptability were required to be relaxed by a substantial amount (by factors of between 5.3 and 6.72 on a normalized scale depending on the evaluation criteria used) in order to gain a set of behavioral simulations (1001 and 1016, respectively out of 5,000,000). Of the 39 model parameters tested, the representation of subsurface processes and associated parameters, were consistently shown as critical to the model not meeting the evaluation criteria, irrespective of the chosen evaluation metric. It is therefore concluded that SWAT is not an appropriate model to guide P management in this catchment. This approach highlights the importance of high frequency monitoring data for setting robust model evaluation criteria. It also raises the question as to whether it is possible to have sufficient input data available to drive such models so that we can have confidence in their predictions and their ability to inform catchment management strategies to tackle the problem of diffuse pollution from agriculture.

There is a need to model and predict the transfer of phosphorus (P) from land to water, but this is challenging because of the large number of complex physical and biogeochemical processes involved. This study presents, for the first time, a ‘limits of acceptability’ approach of the Generalized Likelihood Uncertainty Estimation (GLUE) framework to the Soil and Water Assessment Tool (SWAT), in an application to a water quality problem in the Newby Beck Catchment (12.5km2), Cumbria, United Kingdom (UK). Using high frequency outlet data (discharge and P), individual evaluation criteria (limits of acceptability) were assigned to observed discharge and P loads for all evaluation time steps, identifying where the model was performing well/poorly and to infer which processes required improvement in the model structure. Initial limits of acceptability were required to be relaxed by a substantial amount (by factors of between 5.3 and 6.72 on a normalized scale depending on the evaluation criteria used) in order to gain a set of behavioral simulations (1001 and 1016, respectively out of 5,000,000). Of the 39 model parameters tested, the representation of subsurface processes and associated parameters, were consistently shown as critical to the model not meeting the evaluation criteria, irrespective of the chosen evaluation metric. It is therefore concluded that SWAT is not an appropriate model to guide P management in this catchment. This approach highlights the importance of high frequency monitoring data for setting robust model evaluation criteria. It also raises the question as to whether it is possible to have sufficient input data available to drive such models so that we can have confidence in their predictions and their ability to inform catchment management strategies to tackle the problem of diffuse pollution from agriculture.

Phosphorus (P) losses from land to water will be impacted by climate change and land management for food production, with detrimental impacts on aquatic ecosystems. Here we use a unique combination of methods to evaluate the impact of projected climate change on future P transfers, and to assess what scale of agricultural change would be needed to mitigate these transfers. We combine novel high frequency P flux data from three representative catchments across the UK, a new high spatial resolution climate model, uncertainty estimates from an ensemble of future climate simulations, two P transfer models of contrasting complexity and a simplified representation of the potential intensification of agriculture based on expert elicitation from land managers. We show that the effect of climate change on average winter P loads (predicted increase up to 30% by 2050s) will be limited only by large scale agricultural changes (e.g. 20-80% reduction in P inputs).

Excess nutrients in surface waters, such as phosphorus (P) from agriculture, result in poor water quality, with adverse effects on ecological health and costs for remediation. However, understanding and prediction of P transfers in catchments have been limited by inadequate data and over-parameterised models with high uncertainty. We show that, with high temporal resolution data, we are able to identify simple dynamic models that capture the P load dynamics in three contrasting agricultural catchments in the UK. 10 For a flashy catchment, a linear, second-order (two pathways) model for discharge gave high simulation efficiencies for short-term storm sequences and was useful in highlighting uncertainties in out-of-bank flows. A model with nonlinear rainfall input was appropriate for predicting seasonal 15 or annual cumulative P loads where antecedent conditions affected the catchment response. For second-order models, the time constant for the fast pathway varied between 2 and 15 h for all three catchments and for both discharge and P, confirming that high temporal resolution data are necessary 20 to capture the dynamic responses in small catchments (10–50 km2/. The models led to a better understanding of the dominant nutrient transfer modes, which will be helpful in determining phosphorus transfers following changes in precipitation patterns in the future.

Climate projections for the future indicate that the United Kingdom will experience hotter, drier summers and warmer, wetter winters, bringing longer dry periods followed by rewetting. This will result in changes in phosphorus (P) mobilization patterns that will influence the transfer of P from land to water. We tested the hypothesis that changes in the future patterns of drying–rewetting will affect the amount of soluble reactive phosphorus (SRP) solubilized from soil. Estimations of dry period characteristics (duration and temperature) under current and predicted climate were determined using data from the UK Climate Projections (UKCP09) Weather Generator tool. Three soils (sieved <2 mm), collected from two regions of the United Kingdom with different soils and farm systems, were dried at 25°C for periods of 0, 2, 4, 5, 6, 8, 10, 15, 20, 25, 30, 60, and 90 d, then subsequently rewetted (50 mL over 2 h). The solubilized leachate was collected and analyzed for SRP. In the 2050s, warm period temperature extremes >25°C are predicted in some places and dry periods of 30 to 90 d extremes are predicted. Combining the frequency of projected dry periods with the SRP concentration in leachate suggests that this may result overall in increased mobilization of P; however, critical breakpoints of 6.9 to 14.5 d dry occur wherein up to 28% more SRP can be solubilized following a rapid rewetting event. The precise cause of this increase could not be identified and warrants further investigation as the process is not currently included in P transfer models.

We hypothesise that climate change, together with intensive agricultural systems, will increase the transfer of pollutants from land to water and impact on stream health. This study builds, for the first time, an integrated assessment of nutrient transfers, bringing together a) high-frequency data from the outlets of two surface water-dominated, headwater (~ 10 km²) agricultural catchments, b) event-by-event analysis of nutrient transfers, c) concentration duration curves for comparison with EU Water Framework Directive water quality targets, d) event analysis of location-specific, sub-daily rainfall projections (UKCP, 2009), and e) a linear model relating storm rainfall to phosphorus load. These components, in combination, bring innovation and new insight into the estimation of future phosphorus transfers, which was not available from individual components. The data demonstrated two features of particular concern for climate change impacts. Firstly, the bulk of the suspended sediment and total phosphorus (TP) load (greater than 90% and 80% respectively) was transferred during the highest discharge events. The linear model of rainfall-driven TP transfers estimated that, with the projected increase in winter rainfall (+ 8% to + 17% in the catchments by 2050s), annual event loads might increase by around 9% on average, if agricultural practices remain unchanged. Secondly, events following dry periods of several weeks, particularly in summer, were responsible for high concentrations of phosphorus, but relatively low loads. The high concentrations, associated with low flow, could become more frequent or last longer in the future, with a corresponding increase in the length of time that threshold concentrations (e.g. for water quality status) are exceeded. The results suggest that in order to build resilience in stream health and help mitigate potential increases in diffuse agricultural water pollution due to climate change, land management practices should target contro

Using a global atmospheric chemistry model, we have quantified for the first time, intercontinental transboundary contributions to crop ozone exposure and subsequent yield reductions in the Northern Hemisphere. We apply four metrics (AOT40, M7, M12, W126) to assess the impacts of 100% reductions in anthropogenic NOx emissions from North (N) America, South East (SE) Asia and Europe on global and regional exposure of 6 major agricultural crop types to surface ozone, and resultant crop production losses during the year 2000 growing season. Using these metrics, model calculations show that for wheat, rice, cotton and potato, 100 % reductions in SE Asian anthropogenic NOx emissions tend to produce the greatest global reduction in crop production losses (42.3–95.2%), and a 100 % reduction to N~American anthropogenic NOx emissions results in the greatest global impact on crop production losses for maize and soybean (59.2–85.9%). A 100% reduction in N~American anthropogenic NOx emissions produces the largest transboundary impact, resulting in European production loss reductions of between 14.2% and 63.2%. European NOx emissions tend to produce a smaller transboundary impact, due to inefficiency of transport from the European domain. The threshold nature of the AOT40 ozone-exposure metric results in strong dependence of non-local emissions impacts on the local ozone concentration distribution. Our calculations of absolute crop production change under emission reduction scenarios differ between the metrics used, however we find the relative importance of each region's transboundary impact remains robust between metrics. Our results demonstrate that local air quality and emission control strategies have the potential to partly alleviate ozone-induced crop yield loss in continents downstream, in addition to effectively mitigating local ozone-induced production losses.