Intensive field monitoring of a reach of upland gravel-bed river illustrates the temporal and spatial variability of in-channel sedimentation. Over the six-year monitoring period, the mean bed level in the channel has risen by 0·17 m with a maximum bed level rise of 0·5 m noted at one location over a five month winter period. These rapid levels of aggradation have a profound impact on the number and duration of overbank flows with flood frequency increasing on average 2·6 times and overbank flow time increasing by 12·8 hours. This work raises the profile of coarse sediment transfer in the design and operation of river management, specifically engineering schemes. It emphasizes the need for the implementation of strategic monitoring programmes before engineering work occurs to identify zones where aggradation is likely to be problematic. Exploration of the sediment supply and transfer system can explain patterns of channel sedimentation. The complex spatial, seasonal and annual variability in sediment supply and transfer raise uncertainties into the system's response to potential changes in climate and land-use. Thus, there is a demand for schemes that monitor coarse sediment transfer and channel response. AGGRADATION IN A TEMPERATE, UPLAND, GRAVEL-BED RIVER 1187 Note: The table shows the 12 cross-sections which have experienced the highest rates of erosion and deposition since December 2002 alongside the slope and curvature rank for that location. Large slope rank values indicate the greatest increase in slope whilst small slope rank values correspond with reduction in slopes. Low curvature rank values indicate curved reaches whilst high values indicate straight reaches. For both the slope and curvature, values range from 1-34. Italic typeface values indicate higher importance.Figure 6. Seasonal width-averaged bed level change. Individual data points indicate seasonal change whilst the solid line is the cumulative bed level change over time. Vertical error bars in (a) represent the bed level change uncertainty.
Upland river systems constantly evolve in response to a wide range of complex and interlinked processes. These include internal factors such as the discharge, sediment supply and transfer, and the role of the channel boundary. All are influenced by external catchment-scale factors including climate and land use. Managing these systems to reduce flood risk, prevent bank erosion and preserve habitats is typically carried out without sufficient consideration of the complex interrelationships governing the fluvial system. This is partly due to a lack of broad-scale thinking and partly due to the intensive field-based data collection required to inform the processes. As such, decisions are often ill-informed, becoming unsuccessful or simply shifting the problems elsewhere in the system. Furthermore, the continually changing nature of rivers makes management more challenging as an implemented scheme is highly unlikely to remain effective in the long term. While upland catchment hydrology and the implications of climate and land-use change have received much attention in recent decades, in-channel interactions between sediment transfer and morphological change have been relatively neglected. These interactions are fundamental to flood risk, lateral channel adjustment, and habitat and ecology; thus, they require a more concentrated research effort. Central to this is a more holistic approach to catchment operations and a greater understanding of the links between the in-channel dynamics and broader catchment changes.
A sequence of major flood events in Britain over the last two decades has prompted questions about the influence of anthropogenic greenhouse gas emissions on flood risk. Such questions are difficult to answer definitively, as a range of other factors are involved, but modelling techniques allow an assessment of how much the chance of occurrence of an event could have been altered by emissions. Here the floods of winter 2013/2014 in Great Britain are assessed by combining ensembles of climate model data with a national‐scale hydrological model and, for one severely impacted river basin (the Thames), a detailed analysis of flood inundation and the increased number of residential properties placed at risk. One climate model ensemble represents the range of possible weather under the current climate, while 11 alternative ensembles represent the weather as it could have been had past emissions not occurred. The pooled ensemble results show that emissions are likely to have increased the chance of occurrence of these floods across much of the country, with a stronger influence on longer duration peaks (~10 days or more) than for shorter durations (consistent with observations). However, there is substantial variation in results between alternative ensembles, with some suggesting likely decreases in the chance of flood occurrence, at least in some regions of the country. The influence on flows and property flooding varies spatially, due to both spatial variation in the influence on precipitation and variation in physical properties that affect the transformation of precipitation to river flow and flood impacts, including flood defences. This complexity highlights the importance of using hydrological modelling to attribute hydrological impacts from meteorological changes. Changes in snow occurrence in a warming climate are also shown to be important, with effects varying spatially.
Abstract. In countries globally there is intense political interest in fostering effective university–business collaborations, but there has been scant attention devoted to exactly how an individual scientist's workload (i.e. specified tasks) and incentive structures (i.e. assessment criteria) may act as a key barrier to this. To investigate this an original, empirical dataset is derived from UK job specifications and promotion criteria, which distil universities' varied drivers into requirements upon academics. This work reveals the nature of the severe challenge posed by a heavily time-constrained culture; specifically, tension exists between opportunities presented by working with business and non-optional duties (e.g. administration and teaching). Thus, to justify the time to work with business, such work must inspire curiosity and facilitate future novel science in order to mitigate its conflict with the overriding imperative for academics to publish. It must also provide evidence of real-world changes (i.e. impact), and ideally other reportable outcomes (e.g. official status as a business' advisor), to feed back into the scientist's performance appraisals. Indicatively, amid 20–50 key duties, typical full-time scientists may be able to free up to 0.5 day per week for work with business. Thus specific, pragmatic actions, including short-term and time-efficient steps, are proposed in a “user guide” to help initiate and nurture a long-term collaboration between an early- to mid-career environmental scientist and a practitioner in the insurance sector. These actions are mapped back to a tailored typology of impact and a newly created representative set of appraisal criteria to explain how they may be effective, mutually beneficial and overcome barriers. Throughout, the focus is on environmental science, with illustrative detail provided through the example of natural hazard risk modelling in the insurance sector. However, a new conceptual model of academics' behaviour is developed, fusing perspectives from literature on academics' motivations and performance assessment, which we propose is internationally applicable and transferable between sectors. Sector-specific details (e.g. list of relevant impacts and user guide) may serve as templates for how people may act differently to work more effectively together.
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