Coastal and shoreline management increasingly needs to consider morphological change occurring at decadal to centennial timescales, especially that related to climate change and sea-level rise. This requires the development of morphological models operating at a mesoscale, defined by time and length scales of the order 101 to 102 years and 101 to 102 km. So-called ‘reduced complexity’ models that represent critical processes at scales not much smaller than the primary scale of interest, and are regulated by capturing the critical feedbacks that govern landform behaviour, are proving effective as a means of exploring emergent coastal behaviour at a landscape scale. Such models tend to be computationally efficient and are thus easily applied within a probabilistic framework. At the same time, reductionist models, built upon a more detailed description of hydrodynamic and sediment transport processes, are capable of application at increasingly broad spatial and temporal scales. More qualitative modelling approaches are also emerging that can guide the development and deployment of quantitative models, and these can be supplemented by varied data-driven modelling approaches that can achieve new explanatory insights from observational datasets. Such disparate approaches have hitherto been pursued largely in isolation by mutually exclusive modelling communities. Brought together, they have the potential to facilitate a step change in our ability to simulate the evolution of coastal morphology at scales that are most relevant to managing erosion and flood risk. Here, we advocate and outline a new integrated modelling framework that deploys coupled mesoscale reduced complexity models, reductionist coastal area models, data-driven approaches, and qualitative conceptual models. Integration of these heterogeneous approaches gives rise to model compositions that can potentially resolve decadal- to centennial-scale behaviour of diverse coupled open coast, estuary and inner shelf settings. This vision is illustrated through an idealised composition of models for a ~ 70 km stretch of the Suffolk coast, eastern England. A key advantage of model linking is that it allows a wide range of real-world situations to be simulated from a small set of model components. However, this process involves more than just the development of software that allows for flexible model coupling. The compatibility of radically different modelling assumptions remains to be carefully assessed and testing as well as evaluating uncertainties of models in composition are areas that require further attention

We use a new exploratory model that simulates the evolution of sandy coastlines over decadal to centennial timescales to examine the behavior of crenulate-shaped bays forced by differing directional wave climates. The model represents the coastline as a vector in a Cartesian reference frame, and the shoreface evolves relative to its local orientation, allowing simulation of coasts with high planform-curvature. Shoreline change is driven by gradients in alongshore transport following newly developed algorithms that facilitate dealing with high planform-curvature coastlines. We simulated the evolution of bays from a straight coast between two fixed headlands with no external sediment inputs to an equilibrium condition (zero net alongshore sediment flux) under an ensemble of directional wave climate conditions. We find that planform bay relief increases with obliquity of the mean wave direction, and decreases with the spread of wave directions. Varying bay size over 2 orders of magnitude (0.1–16 km), the model predicts bay shape to be independent of bay size. The time taken for modeled bays to attain equilibrium was found to scale with the square of the distance between headlands, so that, all else being equal, small bays are likely to respond to and recover from perturbations more rapidly (over just a few years) compared to large bays (hundreds of years). Empirical expressions predicting bay shape may be misleading if used to predict their behavior over planning timescales.

The dataset Future Flows Hydrology was developed as part of the project "Future Flows and Groundwater Levels'' to provide a consistent set of transient daily river flow and monthly groundwater level projections across England, Wales and Scotland to enable the investigation of the role of climate variability on river flow and groundwater levels nationally and how this may change in the future. Future Flows Hydrology is derived from Future Flows Climate, a national ensemble projection derived from the Hadley Centre's ensemble projection HadRM3-PPE to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications. Three hydrological models and one groundwater level model were used to derive Future Flows Hydrology, with 30 river sites simulated by two hydrological models to enable assessment of hydrological modelling uncertainty in studying the impact of climate change on the hydrology. Future Flows Hydrology contains an 11-member ensemble of transient projections from January 1951 to December 2098, each associated with a single realisation from a different variant of HadRM3 and a single hydrological model. Daily river flows are provided for 281 river catchments and monthly groundwater levels at 24 boreholes as .csv files containing all 11 ensemble members. When separate simulations are done with two hydrological models, two separate .csv files are provided. Because of potential biases in the climate–hydrology modelling chain, catchment fact sheets are associated with each ensemble. These contain information on the uncertainty associated with the hydrological modelling when driven using observed climate and Future Flows Climate for a period representative of the reference time slice 1961–1990 as described by key hydrological statistics. Graphs of projected changes for selected hydrological indicators are also provided for the 2050s time slice. Limitations associated with the dataset are provided, along with practical recommendation of use. Future Flows Hydrology is freely available for non-commercial use under certain licensing conditions. For each study site, catchment averages of daily precipitation and monthly potential evapotranspiration, used to drive the hydrological models, are made available, so that hydrological modelling uncertainty under climate change conditions can be explored further. doi:10.5285/f3723162-4fed-4d9d-92c6-dd17412fa37b

International audienceNear surface gas measurements are presented from a shallow (20 m depth) CO2 injection experiment at the CO2 Field Lab site in Svelvik, Norway, which was designed to test a variety of monitoring tools. Small areas of surface seepage of CO2 were detected during the experiment and these spread as the injection rate was increased. These features only accounted for a small fraction of the injected gas. Isotopic measurements revealed traces of injected CO2 at 50 cm depth nearer the injection point. The spatial extent of this is unknown but it is not likely to imply a significant amount of CO2 seepage. The locations of the gas escape were not as anticipated by prior modelling and highlight the difficulty of predicting where leakage may occur and, hence, where to deploy monitoring equipment. This unpredictability and the limited size of the seeps implies that monitoring will have to be flexible, preferably mobile and capable of detecting small features in large areas if successful leakage detection at surface is to be achieved. Low level seepage, such as that suggested isotopically here, could be significant for carbon auditing if it occurs over wide areas. This could be tested in areas of natural CO2 seepage