The Baltic Sea is suffering from eutrophication caused by nutrient discharges from land to sea, and these loads might change in a changing climate. We show that the impact from climate change by mid-century is probably less than the direct impact of changing socioeconomic factors such as land use, agricultural practices, atmospheric deposition, and wastewater emissions. We compare results from dynamic modelling of nutrient loads to the Baltic Sea under projections of climate change and scenarios for shared socioeconomic pathways. Average nutrient loads are projected to increase by 8% and 14% for nitrogen and phosphorus, respectively, in response to climate change scenarios. In contrast, changes in the socioeconomic drivers can lead to a decrease of 13% and 6% or an increase of 11% and 9% in nitrogen and phosphorus loads, respectively, depending on the pathway. This indicates that policy decisions still play a major role in climate adaptation and in managing eutrophication in the Baltic Sea region.

This study analyzes the role of large river flow events in annual loads, for three constituents and for up to 32 years of daily data at multiple watersheds with different land-uses. Prior studies were mainly based on simple descriptive statistics, such as the percentage of nutrient loadings transported during several of the largest river flows, while this study uses log-regression and analysis of covariance (ANCOVA) to describe and quantify the relationships between large flow events and nutrient loadings. Regression relationships were developed to predict total annual loads based on loads exported by the largest events in a year for nitrate plus nitrite nitrogen (NO₃-N + NO₂-N, indicated as total oxidized nitrogen; TON), total phosphorus (TP), and suspended solids (SS) for eight watersheds in the Lake Erie and Ohio River basins. The median prediction errors for annual TON, TP, and SS loads from the top five load events for spatially aggregated watersheds were 13.2%, 18.6%, and 13.4%, respectively, which improve further on refining the spatial scales. ANCOVA suggests that the relationships between annual loads and large load events are regionally consistent. The findings outline the dominant role of large hydroclimatic events, and can help to improve the design of pollutant monitoring and agricultural conservation programs.

This study explores visualization-supported dialogues with water management and ecosystem stakeholders from four catchments in Sweden, Latvia, Germany and Poland. An interactive visualization tool was designed to present information regarding modelled effects of chosen future pathways including different measures that address ecosystem issues under present and future scenarios of land use and climate change, and estimated benefits and costs of the measures. This paper assesses if and how visualization-supported dialogues hinder or support key components of good governance of water and ecosystem management among expert stakeholders. We discuss challenges and opportunities related to the tool and dialogue design, and performance of dialogues. Results from a cross-case workshop indicate that the form and functionality of the tool contributes to participation, empowerment, accessibility and flexibility, while dialogue design is instrumental for encouraging trust and inclusion of local knowledge and competence.

It is increasingly important to know the water quality of a reservoir, given the prospect of an environment poor in water reserves, which are based on intense and short-lived precipitation events. In this work, vegetation indices (NDVI, EVI) and bio-physical parameters of the vegetation (LAI, FC), meteorological variables, and hydrological data are considered as possible drivers of the spatial and temporal variability of water quality (WQ) of the Banja reservoir (Albania). Sentinel-2 and Landsat 8/9 images are analyzed to derive WQ parameters and vegetation properties, while the HYPE model provides hydrological variables. Timeseries of the considered variables are examined using graphical and statistical methods and correlations among the variables are computed for a five-year period (2016–2022). The added-value of integrating earth observation derived data is demonstrated in the analysis of specific time periods or precipitation events. Significant positive correlations are found between water turbidity and hydrological parameters such as river discharge or runoff (0.55 and 0.40, respectively), while negative correlations are found between water turbidity and vegetation descriptors (−0.48 to −0.56). The possibility of having easy-to-use tools (e.g., web portal) for the analysis of multi-source data in an interactive way, facilitates the planning of hydroelectric plants management operations.

The Baltic Sea is suffering from eutrophication caused by nutrient discharges from land to sea. These freshwater inflows vary in magnitude from year to year as well as within each year due to e.g. natural variability, weather patterns, and seasonal human activities. Nutrient transport models are important tools for assessments of macro-nutrient fluxes (nitrogen, phosphorus) and for evaluating the connection between pollution sources and the assessed water body. While understanding of current status is important, impacts from changing climate and socio-economics on freshwater inflows to the Baltic Sea also need to be taken into account when planning management practices and mitigation measures.Continental to global scale catchment-based hydrological models have emerged in recent years as tools e.g. for flood forecasting, large-scale climate impact analyses, and estimation of time-dynamic water fluxes into sea basins. Here, we present results from the pan-European rainfall-runoff and nutrient transfer model E-HYPE, developed as a multi-purpose tool for large-scale hydrological analyses. We compared current freshwater inflows from land with those from dynamic modelling with E-HYPE under various climate and socioeconomic conditions. The socioeconomic conditions (land use, agricultural practices, population changes, dietary changes, atmospheric deposition, and wastewater technologies) were evaluated for 3 additional time horizons: 2050s using the Shared Socioeconomic Pathways, 1900s using historical data, and a reference period using a synthetic “no human impact” scenario. An ensemble of 4 climate models that preserves the range of projected changes in precipitation and temperature from a larger ensemble was selected for analysis of climate impacts in 2050s.  We show that while climate change affects nutrient loads to the Baltic Sea, these impacts can be overshadowed by the impacts of changing socioeconomic factors. Historical nitrogen loads were estimated as 43% and 33% of the current loads for the 1900s and the “no human impact” scenarios, respectively. Average nitrogen loads are projected to increase by 4-10% (8% on average) as a response to climate change by 2050s. Purely mitigation measures that did not address the magnitude of the nutrient sources reduced the total nitrogen load by <5%, with local efficiencies being reduced through retention processes. However, changes in the socioeconomic drivers led to significant changes in the future loads with the range of impacts spanning 30% of the current load depending on the socioeconomic pathway to be followed. This means that policy decisions have by far the largest impact when managing eutrophication in the Baltic Sea region.Bartosova, A., Capell, R., Olesen, J.E. et al. (2019). Future socioeconomic conditions may have a larger impact than climate change on nutrient loads to the Baltic Sea. Ambio 48, 1325–1336 doi:10.1007/s13280-019-01243-5