The ECOSUPPORT-project aims to help policy makers by supplying state-of-the-art research on the state of the Baltic Sea under different scenarios of nutrient supply, pressure from fisheries and impact of climate change. In order to make the research results accessible, a new form of scientific communication has been tested. Presentation of research data and physical, chemical and biogeochemical processes on land and in the sea were made using a special visualization platform, Uniview, which was projected onto a cupola-shaped screen inside an inflatable, enclosed dome. The visualization has been tested on different audiences including policy makers, politicians, researchers and university students. Overall, the response has been overwhelmingly positive with the audience expressing the view that the used visualization technique enhanced their understanding and receptiveness. This view was shared with the scientific presenters.

To reduce eutrophication of the Baltic Sea, all nine surrounding countries have agreed upon reduction targets in the HELCOM Baltic Sea Action Plan (BSAP). Yet, monitoring sites and model concepts for decision support are few. To provide one more tool for analysis of water and nutrient fluxes in the Baltic Sea basin, the HYPE model has been applied to the region (called Balt-HYPE). It was used here for experimenting with land-based remedial measures and future climate projections to quantify the impacts of these on water and nutrient loads to the sea. The results suggest that there is a possibility to reach the BSAP nutrient reduction targets by 2100, and that climate change may both aggravate and help in some aspects. Uncertainties in the model results are large, mainly due to the spread of the climate model projections, but also due to the hydrological model.

Water resource management is often based on numerical models, and large-scale models are sometimes used for international strategic agreements. Sometimes the modelled area entails several political entities and river basins. To avoid methodological bias in results, methods and databases should be homogenous across political and geophysical boundaries, but this may involve fewer details and more assumptions. This paper quantifies the uncertainty when the same model code is applied using two different input datasets; a more detailed one for the country of Sweden (S-HYPE) and a more general one for the entire Baltic Sea basin (Balt-HYPE). Results from the two model applications were compared for the Swedish landmass and for two specific Swedish river basins. The results show that both model applications may be useful in providing spatial information of water and nutrients at various scales. For water discharge, most relative errors are <10% for S-HYPE and <25% for Balt-HYPE. Both applications reproduced the most mean concentration for nitrogen within 25% of the observed mean values, but phosphorus showed a larger scatter. Differences in model set-up were reflected in the simulation of both spatial and temporal dynamics. The most sensitive data were precipitation/temperature, agriculture and model parameter values.

Open data make it possible to set up multi-basin models for large domains across environmental, climate and administrative boundaries. This study presents new methods for evaluating a number of aspects of multi-basin model performance, while exploring the performance of the E-HYPE_v2.1 model for several evaluation criteria in 181 independent river gauges across the European continent. Embedded model assumptions on dominant flow generating mechanisms are analysed by correlating physiographical characteristics to the flow regime. The results indicate that the model captures the spatial variability of flow and is therefore suitable for predictions in ungauged basins. The model shows good performance of long-term means and seasonality, while short-term daily variability is less well represented, especially for Mediterranean and mountainous areas. Major identified shortcomings refer to the resolution of precipitation patterns, aquifer exchanges, water extractions and regulation. This will guide the work with the next model version for which improvements in input data, processes and calibration have been identified to potentially contribute most to improved model performance. [GRAPHICS]

Overwash, the flow of water and sediment over the crest of a beach, contributes to flooding and the deposition of sand landward of the beach crest. Washover, the sand deposited by overwash, contributes to the sediment budget and migration of barrier islands. The ability to predict the occurrence, location, and thickness of overwash deposits is important for coastal residents, coastal town planners, environmental planners, and engineers alike. In this study, a numerical model that simulates the sediment transport and one-dimensional barrier profile change caused by overwash was developed. The magnitude of overwash and the morphology of washovers are dependent on the overwash regime. New formulae are developed to estimate the sediment transport rate over the beach crest for both run-up overwash, using ballistics theory, and inundation overwash, treating flow over the crest as weir flow. Two-dimensional flow is described on the back barrier by considering the continuity of a block of water at steady state, taking into account lateral spreading, friction, and infiltration. The model is tested against 26 different beach profile sets from several different locations, and several different storms, exhibiting a variety of initial morphologies. The model is capable of reproducing varying overwash morphology responses including dune crest erosion, dune destruction, barrier rollback, the thinning of a washover deposit on the backbarrier, and overwash over a multiple dune system.

Underpinning all hydrological simulations is an estimate of the catchment area upstream of a point of interest. Locally, the delineation of a catchment and estimation of its area is usually done using fine scale maps and local knowledge, but for large-scale hydrological modelling, particularly continental and global scale modelling, this level of detailed data analysis is not practical. For large-scale hydrological modelling, remotely sensed and hydrologically conditioned river routing networks, such as HYDROlk and HydroSHEDS, are often used. This study evaluates the accuracy of the accumulated upstream area in each gridpoint given by the networks. This is useful for evaluating the ability of these data sets to delineate catchments of varying scale for use in hydrological models. It is shown that the higher resolution HydroSHEDS data set gives better results than the HYDROlk data set and that accuracy decreases with decreasing basin scale. In ungauged basins, or where other local catchment area data are not available, the validation made in this study can be used to indicate the likelihood of correctly delineating catchments of different scales using these river routing networks.

This study reports on new projections of discharge to the Baltic Sea given possible realisations of future climate and uncertainties regarding these projections. A high-resolution, pan-Baltic application of the Hydrological Predictions for the Environment (HYPE) model was used to make transient simulations of discharge to the Baltic Sea for a mini-ensemble of climate projections representing two high emissions scenarios. The biases in precipitation and temperature adherent to climate models were adjusted using a Distribution Based Scaling (DBS) approach. As well as the climate projection uncertainty, this study considers uncertainties in the bias-correction and hydrological modelling. While the results indicate that the cumulative discharge to the Baltic Sea for 2071 to 2100, as compared to 1971 to 2000, is likely to increase, the uncertainties quantified from the hydrological model and the bias-correction method show that even with a state-of-the-art methodology, the combined uncertainties from the climate model, bias-correction and impact model make it difficult to draw conclusions about the magnitude of change. It is therefore urged that as well as climate model and scenario uncertainty, the uncertainties in the bias-correction methodology and the impact model are also taken into account when conducting climate change impact studies.

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist. As numerical weather prediction models continue to improve, operational centers are increasingly using their meteorological output to drive hydrological models, creating hydrometeorological systems capable of forecasting river flow and flood events at much longer lead times than has previously been possible. Furthermore, developments in, for example, modelling capabilities, data, and resources in recent years have made it possible to produce global scale flood forecasting systems. In this paper, the current state of operational large-scale flood forecasting is discussed, including probabilistic forecasting of floods using ensemble prediction systems. Six state-of-the-art operational large-scale flood forecasting systems are reviewed, describing similarities and differences in their approaches to forecasting floods at the global and continental scale. Operational systems currently have the capability to produce coarse-scale discharge forecasts in the medium-range and disseminate forecasts and, in some cases, early warning products in real time across the globe, in support of national forecasting capabilities. With improvements in seasonal weather forecasting, future advances may include more seamless hydrological forecasting at the global scale alongside a move towards multi-model forecasts and grand ensemble techniques, responding to the requirement of developing multi-hazard early warning systems for disaster risk reduction. (C) 2016 The Authors. WIREs Water published by Wiley Periodicals, Inc.

During severe storms high waves and water levels may greatly impact the sub-aerial portion of the beach inducing significant morphological change at elevations that the waves can not reach under normal conditions. Morphological formations such as dunes and barrier islands may suffer from direct wave impact and erode. Overwash occurs if the wave run-up and/or the mean water level are sufficiently high allowing for water and sediment to pass over the beach crest, which in turn causes flooding and deposition of sediment shoreward of the crest. An analytical model of sub-aerial beach response to storms was developed based on impact theory, including overwash, and the evolution of schematised dunes was investigated. Furthermore, the analytical model was applied to the case of schematised barrier islands exposed to extensive overwash. After validation using field data, the analytical model was employed at two coastal sites, namely Ocean City on the United States east coast and the Ebro Delta on the Spanish Mediterranean coast, in order to calculate quantities for assessing the storm impact on beaches, such as eroded volume, overwash volume, beach crest reduction, and contour-line retreat. These quantities were subsequently analysed to derive empirical probability distribution functions to be utilised in different types of risk assessment concerning flooding and erosion in coastal areas.

Multi-model ensemble simulations for the marine biogeochemistry and food web of the Baltic Sea were performed for the period 1850-2098, and projected changes in the future climate were compared with the past climate environment. For the past period 1850-2006, atmospheric, hydrological and nutrient forcings were reconstructed, based on historical measurements. For the future period 1961-2098, scenario simulations were driven by regionalized global general circulation model (GCM) data and forced by various future greenhouse gas emission and air-and riverborne nutrient load scenarios (ranging from a pessimistic 'business-as-usual' to the most optimistic case). To estimate uncertainties, different models for the various parts of the Earth system were applied. Assuming the IPCC greenhouse gas emission scenarios A1B or A2, we found that water temperatures at the end of this century may be higher and salinities and oxygen concentrations may be lower than ever measured since 1850. There is also a tendency of increased eutrophication in the future, depending on the nutrient load scenario. Although cod biomass is mainly controlled by fishing mortality, climate change together with eutrophication may result in a biomass decline during the latter part of this century, even when combined with lower fishing pressure. Despite considerable shortcomings of state-of-the-art models, this study suggests that the future Baltic Sea ecosystem may unprecedentedly change compared to the past 150 yr. As stakeholders today pay only little attention to adaptation and mitigation strategies, more information is needed to raise public awareness of the possible impacts of climate change on marine ecosystems.

We present a multi-model ensemble study for the Baltic Sea, and investigate the combined impact of changing climate, external nutrient supply, and fisheries on the marine ecosystem. The applied regional climate system model contains state-of-the-art component models for the atmosphere, sea ice, ocean, land surface, terrestrial and marine biogeochemistry, and marine food-web. Time-dependent scenario simulations for the period 1960-2100 are performed and uncertainties of future projections are estimated. In addition, reconstructions since 1850 are carried out to evaluate the models sensitivity to external stressors on long time scales. Information from scenario simulations are used to support decision-makers and stakeholders and to raise awareness of climate change, environmental problems, and possible abatement strategies among the general public using geovisualization. It is concluded that the study results are relevant for the Baltic Sea Action Plan of the Helsinki Commission.

A dynamic water quality model, HYPE, was applied to a large, data-sparse region to study whether reliable information on water quantity and water quality could be obtained for both gauged and ungauged waterbodies. The model (called S-HYPE) was set up for all of Sweden (similar to 450 000 km(2)), divided into sub-basins with an average area of 28 km(2). Readily available national databases were used for physiographic data, emissions and agricultural practices, fixed values for representative years were used. Daily precipitation and temperature were used as the dynamic forcing of the model. Model evaluation was based on data from several hundred monitoring sites, of which approximately 90% had not been used in calibration on a daily scale. Results were evaluated using the Nash-Sutcliffe efficiency (NSE), correlation and relative errors: 92% of the spatial variation was explained for specific water discharge, and 88% and 59% for total nitrogen and total phosphorus concentrations, respectively. Day-to-day variations were modelled with satisfactory results for water discharge and the seasonal variation of nitrogen concentrations was also generally well captured. In 20 large, unregulated rivers the median NSE for water discharge was 0.84, and the corresponding number for 76 partly-regulated river basins was 0.52. In small basins, the NSE was typically above 0.6. These major achievements relative to previous similar experiments were ascribed to the step-wise calibration process using representative gauged basins and the use of amodelling concept, whereby coefficients are linked to physiographic variables rather than to specific sites.

This study demonstrates a climate information service for pan-European water use sectors that are vulnerable to climate change induced hydrological changes, including risk and safety (disaster preparedness), agriculture, energy (hydropower and cooling water use for thermoelectric power) and environment (water quality). To study the climate change impacts we used two different hydrological models forced with an ensemble of bias-corrected general circulation model (GCM) output for both the lowest (2.6) and highest (8.5) representative concentration pathways (RCP). Selected indicators of water related vulnerability for each sector were then calculated from the hydrological model results. Our results show a distinct north-south divide in terms of climate change impacts; in the south the water availability will reduce while in the north water availability will increase. Across different climate models precipitation and streamflow increase in northern Europe and decrease in southern Europe, but the latitude at which this change occurs varies depending on the GCM. Hydrological extremes are increasing over large parts of Europe. The agricultural sector will be affected by reduced water availability (in the south) and increased drought. Both streamflow and soil moistures droughts are projected to increase in most parts of Europe except in northern Scandinavia and the Alps. The energy sector will be affected by lower hydropower potential in most European countries and reduced cooling water availability due to higher water temperatures and reduced summer river flows. Our results show that in particular in the Mediterranean the pressures are high because of increasing drought which will have large impacts on both the agriculture and energy sectors. In France and Italy this is combined with increased flood hazards. Our results show important impacts of climate change on European water use sectors indicating a clear need for adaptation. (C) 2015 Published by Elsevier B.V.