S. M. Reaney

Representation of landscape hydrological connectivity using a topographically driven surface flow index

[1] This paper assesses the extent to which a topographically defined description of the spatial arrangement of catchment wetness can be used to represent landscape hydrological connectivity in temperate river catchments. A physically based distributed hydrological model is used to characterize the space-time patterns of surface overland flow connection to the drainage network. These characterizations are compared with a static descriptor of the spatial structure of topographically controlled local wetness, called here the Network Index. Theoretically, if topography is the primary control upon hydrological response, the level of catchment wetness required to maintain connectivity along a flow path should be greater for flow paths that have a lower value of the topographically controlled local wetness. We find that our static descriptor can be used to generalize a significant proportion of the time-averaged spatial variability in connectivity, in terms of both the propensity to and duration of connection. Although the extent to which this finding holds will vary with the extent of topographic control of hydrological response, in catchments with relatively shallow soils and impervious geology our index could improve significantly the estimation of the transfer of sediment and dissolved materials to the drainage network and so assist with both diffuse pollution and climate change impact studies. The work also provides a second reason for the concept that there are Critical Source Areas in river catchments: these arise from the extent to which that material can be delivered to the drainage network, as well as the generation of risky material itself.

Changing climate and nutrient transfers: Evidence from high temporal resolution concentration-flow dynamics in headwater catchments

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 (~10km(2)) 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 controllable risk factors, such as soil nutrient status, soil condition and crop cover.

Dominant mechanisms for the delivery of fine sediment and phosphorus to fluvial networks draining grassland dominated headwater catchments

Recent advances in monitoring technology have enabled high frequency, in-situ measurements of total phosphorus and total reactive phosphorus to be undertaken with high precision, whilst turbidity can provide an excellent surrogate for suspended sediment. Despite these measurements being fundamental to understanding the mechanisms and flow paths that deliver these constituents to river networks, there is a paucity of such data for headwater agricultural catchments. The aim of this paper is to deduce the dominant mechanisms for the delivery of fine sediment and phosphorus to an upland river network in the UK through characterisation of the temporal variability of hydrological fluxes, and associated soluble and particulate concentrations for the period spanning March 2012-February 2013. An assessment of the factors producing constituent hysteresis is undertaken following factor analysis (FA) on a suite of measured environmental variables representing the fluvial and wider catchment conditions prior to, and during catchment-wide hydrological events. Analysis indicates that suspended sediment is delivered to the fluvial system predominantly via rapidly responding pathways driven by event hydrology. However, evidence of complex, figure-of-eight hysteresis is observed following periods of hydrological quiescence, highlighting the importance of preparatory processes. Sediment delivery via a slow moving, probably sub-surface pathway does occur, albeit infrequently and during low magnitude events at the catchment outlet. Phosphorus is revealed to have a distinct hysteretic response to that of suspended sediment, with sub-surface pathways dominating. However, high magnitude events were observed to exhibit threshold-like behaviour, whereby activation and connection of usually disconnected depositional zones to the fluvial networks results in the movement of vast phosphorus fluxes. Multiple pathways are observed for particulate and soluble constituents, highlighting the challenges faced in mitigating the delivery of contaminant fluxes to headwater river systems.

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.

A Monte Carlo approach to the inverse problem of diffuse pollution risk in agricultural catchments

The hydrological and biogeochemical processes that operate in catchments influence the ecological quality of freshwater systems through delivery of fine sediment, nutrients and organic matter. Most models that seek to characterise the delivery of diffuse pollutants from land to water are reductionist. The multitude of processes that are parameterised in such models to ensure generic applicability make them complex and difficult to test on available data. Here, we outline an alternative--data-driven--inverse approach. We apply SCIMAP, a parsimonious risk based model that has an explicit treatment of hydrological connectivity. We take a bayesian approach to the inverse problem of determining the risk that must be assigned to different land uses in a catchment in order to explain the spatial patterns of measured in-stream nutrient concentrations. We apply the model to identify the key sources of nitrogen (N) and phosphorus (P) diffuse pollution risk in eleven UK catchments covering a range of landscapes. The model results show that: 1) some land use generates a consistently high or low risk of diffuse nutrient pollution; but 2) the risks associated with different land uses vary both between catchments and between nutrients; and 3) that the dominant sources of P and N risk in the catchment are often a function of the spatial configuration of land uses. Taken on a case-by-case basis, this type of inverse approach may be used to help prioritise the focus of interventions to reduce diffuse pollution risk for freshwater ecosystems.

The role of tributary relative timing and sequencing in controlling large floods

Hydrograph convolution is a product of tributary inputs from across the watershed. The time-space distribution of precipitation, the biophysical processes that control the conversion of precipitation to runoff and channel flow conveyance processes, are heterogeneous and different areas respond to rainfall in different ways. We take a subwatershed approach to this and account for tributary flow magnitude, relative timing, and sequencing. We hypothesize that as the scale of the watershed increases so we may start to see systematic differences in subwatershed hydrological response. We test this hypothesis for a large flood (T > 100 years) in a large watershed in northern England. We undertake a sensitivity analysis of the effects of changing subwatershed hydrological response using a hydraulic model. Delaying upstream tributary peak flow timing to make them asynchronous from downstream subwatersheds reduced flood magnitude. However, significant hydrograph adjustment in any one subwatershed was needed for meaningful reductions in stage downstream, although smaller adjustments in multiple tributaries resulted in comparable impacts. For larger hydrograph adjustments, the effect of changing the timing of two tributaries together was lower than the effect of changing each one separately. For smaller adjustments synergy between two subwatersheds meant the effect of changing them together could be greater than the sum of the parts. Thus, this work shows that while the effects of modifying biophysical catchment properties diminishes with scale due to dilution effects, their impact on relative timing of tributaries may, if applied in the right locations, be an important element of flood management.

A geospatial framework to support integrated biogeochemical modelling in the United Kingdom

Anthropogenic impacts on the aquatic environment, especially in the context of nutrients, provide a major challenge for water resource management. The heterogeneous nature of policy relevant management units (e.g. catchments), in terms of environmental controls on nutrient source and transport, leads to the need for holistic management. However, current strategies are limited by current understanding and knowledge that is transferable between spatial scales and landscape typologies. This study presents a spatially-explicit framework to support the modelling of nutrients from land to water, encompassing environmental and spatial complexities. The framework recognises nine homogeneous landscape units, distinct in terms of sensitivity of nutrient losses to waterbodies. The functionality of the framework is demonstrated by supporting an exemplar nutrient model, applied within the Environmental Virtual Observatory pilot (EVOp) cloud cyber-infrastructure. We demonstrate scope for the use of the framework as a management decision support tool and for further development of integrated biogeochemical modelling. High resolution geospatial biogeochemical framework for modelling nutrient flux.Nitrogen and phosphorus modeled across many spatial scales in the United Kingdom.Upscales from grid to river catchment, regional and national scale.Knowledge transfer from data-rich research catchments to data-poor areas.Many other biogeochemical models can be fit to the framework.

Predicting diffuse microbial pollution risk across catchments: The performance of SCIMAP and recommendations for future development

Microbial pollution of surface waters in agricultural catchments can be a consequence of poor farm management practices, such as excessive stocking of livestock on vulnerable land or inappropriate handling of manures and slurries. Catchment interventions such as fencing of watercourses, streamside buffer strips and constructed wetlands have the potential to reduce faecal pollution of watercourses. However these interventions are expensive and occupy valuable productive land. There is, therefore, a requirement for tools to assist in the spatial targeting of such interventions to areas where they will have the biggest impact on water quality improvements whist occupying the minimal amount of productive land. SCIMAP is a risk-based model that has been developed for this purpose but with a focus on diffuse sediment and nutrient pollution. In this study we investigated the performance of SCIMAP in predicting microbial pollution of watercourses and assessed modelled outputs of E. coli, a common faecal indicator organism (FIO), against observed water quality information. SCIMAP was applied to two river catchments in the UK. SCIMAP uses land cover risk weightings, which are routed through the landscape based on hydrological connectivity to generate catchment scale maps of relative in-stream pollution risk. Assessment of the models performance and derivation of optimum land cover risk weightings was achieved using a Monte-Carlo sampling approach. Performance of the SCIMAP framework for informing on FIO risk was variable with better performance in the Yealm catchment (rs=0.88; p<0.01) than the Wyre (rs=-0.36; p>0.05). Across both catchments much uncertainty was associated with the application of optimum risk weightings attributed to different land use classes. Overall, SCIMAP showed potential as a useful tool in the spatial targeting of FIO diffuse pollution management strategies; however, improvements are required to transition the existing SCIMAP framework to a robust FIO risk-mapping tool.

A catchment-scale model to predict spatial and temporal burden of E. coli on pasture from grazing livestock

Effective management of diffuse microbial water pollution from agriculture requires a fundamental understanding of how spatial patterns of microbial pollutants, e.g. E. coli, vary over time at the landscape scale. The aim of this study was to apply the Visualising Pathogen &Environmental Risk (ViPER) model, developed to predict E. coli burden on agricultural land, in a spatially distributed manner to two contrasting catchments in order to map and understand changes in E. coli burden contributed to land from grazing livestock. The model was applied to the River Ayr and Lunan Water catchments, with significant correlations observed between area of improved grassland and the maximum total E. coli per 1km2 grid cell (Ayr: r=0.57; p<0.001, Lunan: r=0.32; p<0.001). There was a significant difference in the predicted maximum E. coli burden between seasons in both catchments, with summer and autumn predicted to accrue higher E. coli contributions relative to spring and winter (P<0.001), driven largely by livestock presence. The ViPER model thus describes, at the landscape scale, spatial nuances in the vulnerability of E. coli loading to land as driven by stocking density and livestock grazing regimes. Resulting risk maps therefore provide the underpinning evidence to inform spatially-targeted decision-making with respect to managing sources of E. coli in agricultural environments.

Heads in the cloud

A professor and several PhD students at MIT examine the challenges and opportunities in human computation.