Flood events caused by high rainfall can have profound biogeochemical impacts on riverine systems but also on the receiving coastal waters. The winter flood in Germany in December 2023/January 2024 affected the Elbe and Weser River systems. We obtained unique data during the peak of the flood and compared these with the monthly means from previous years (2018-2023). Hydrographic parameters and nutrients were determined by standard methods. Low salinity values were observed in the Elbe estuary and the adjacent German Bight (part of North Sea). At Helgoland the lowest average salinity was observed in January 2024 with 31.3 ± 0.5 compared to an average salinity of 32.7 ± 0.7 for the years 2016 to 2023. Nutrient loads (nitrate, phosphate) in the rivers showed a six- to 11-fold increase in the Elbe and Weser rivers compared to years without flood events. Enhanced concentrations of nitrate and silicate were found in the German Bight in January. Nutrients were diluted with North Sea waters, indicating a conservative behavior of nutrients in winter. Atypical prevailing meteorological conditions in January 2024, with predominantly easterly winds, potentially affect the dispersal of the river plume and the nutrients in the North Sea. In March 2024 the chlorophyll-a concentration strongly increased to 2.9 ± 1.8 µmol/L and was twice as high compared to only 1.5 ± 0.7 µmol/L observed in previous years. The observed intensified spring bloom in March in the German Bight near the island of Helgoland indicates the impacts of the flood-derived nutrient inputs three months after the flood event, as the timing of light and nutrient availability was optimal. It is assumed that seasonality and magnitude of flooding in the Elbe estuary and adjacent coastal region will change in future due to climate warming. Thus, the timing of light and nutrient availability will also change, with unconstrained impacts on primary producers and higher trophic levels.

Extreme physical-oceanographic events, such as marine heatwaves, fluvial floods, droughts and storm surges, have major impacts on local communities, economic sectors and ecosystems, and their frequency, intensity and duration increase due to climate change. There is a lack of understanding of the systemic drivers of extreme events as well as of their interconnected impacts on estuarine and coastal ecosystems. This knowledge is essential for assessing future impacts on ecosystem services and the local communities that depend on them, and to inform robust risk assessments and develop comprehensive risk management and adaptation strategies including early warning systems. Considering this, the German Alliance for Marine Research (DAM)-funded programme “ElbeXtreme” focuses on an integrated approach utilizing stakeholder engagement, data mining, experimental and field observations to develop novel observational and modelling approaches for assessing and monitoring risks in the Elbe estuary. The programme will deliver new insights into risks and impacts of extreme events in the estuarine system of the Elbe and the adjacent region of the North Sea (German Bight) to build a systemic risk understanding and support adaptation planning for local communities and ecosystems. Here we outline the rationale of the ElbeXtreme project and its planned activities, with the aim of stimulating national and international collaboration in tackling the urgent issue of marine and coastal risks.

Global warming affects the Earth system in complex ways, often preventing a functional understanding of the underlying processes. Disentangling these processes between abiotic drivers and single species or entire communities is, however, essential for an in-depth understanding of the impacts of climate change on the ecosystem. Using a high-resolution time series on heat waves and cold spells in an Arctic fjord system, we demonstrate that AI-supported digital data processing, which is based on state-of-the-art observatory technology, has the potential to provide new insights into the effects of abiotic factors on biotic communities, which would not be possible with traditional expedition-based sampling methods. Furthermore, our study shows that short-term, event-driven anomalies in key ocean variables not only alter a system's hydrography but also have the potential to impact the entire community across the trophic chain from benthos and zooplankton to fish. We found a significant positive correlation between hydrographic temperature anomalies and biota abundance, with high biota abundances linked to 'Atlantic' phases with frequent heat waves and low biota abundances correlated with 'Arctic' phases dominated by cold spells. The study also revealed that hydrographic anomalies can not only influence overall biota abundance in an area but also trigger complex shifts in species composition. This leads to fluctuating interannual abundance peaks in specific biotic groups, such as jellyfish, fish, or chaetognaths, depending on trigger factors that are not yet fully understood.

Transformation and degradation of dissolved organic matter (DOM) are of considerable magnitude in large rivers but studies investigating a river system from source to sea are scarce. DOM composition changes from headwaters to tide-impacted river stretches due to natural processes, but is also influenced by anthropogenic impacts on river morphology and water quality. We tested the hypotheses that (1) aromatic, oxygen-rich, and large molecules of terrestrial DOM in upstream regions are transformed to more saturated, nitrogen-rich, and smaller molecules towards the tidal and coastal parts, and (2) chlorophyll a concentration and salinity are important explanatory variables of DOM transformation. We tracked the longitudinal dynamics of DOM composition and relevant drivers along the Elbe River in Central Europe from the Czech headwater region via the lowland freshwater section and the tidal region to the coastal waters of the North Sea applying a Lagrangian sampling approach. Chlorophyll a concentration and oxygen saturation increased longitudinally in the river but showed a distinct minimum in the estuary upstream of the salinity gradient whereas dissolved nutrients were depleted by algae in the freshwater part and were released at algal die-off in the estuary. DOM was dominated by aromatic, oxygen-rich components of terrestrial origin in the upstream region. However, the imprint of this terrestrial signal constantly decreased with increasing river stretch while the proportion of organic nitrogen increased towards the estuary and coastal regions. Analyses of DOM transformations along the river-estuary-ocean gradient revealed that decarboxylation was the most frequent transformation and that phytoplankton and salinity were major explanatory variables of DOM quality. Overall, our unique data set demonstrated a distinct sequence of DOM transformation along the land-ocean gradient highlighting the large activity of riverine and estuarine systems in terms of organic carbon dynamics.

Global warming affects the Earth system in complex ways, often preventing a functional understanding of the underlying processes. Disentangling these processes between abiotic drivers and single species or entire communities is, however, essential for an in-depth understanding of climate change impacts on the ecosystem. Using a high-resolution time series on heatwaves and cold spells in an Arctic fjord system, we show that for analysing the effects of environmental stressors on biota, AI supported digital data processing based on state-of-the-art observatory technology can provide insights in habitat-community interactions which are not possible with classic expedition-based sampling methods. Furthermore, our study shows that short-term event-based anomalies in key ocean variables may have an even stronger impact on a communities structure than long-term climate change trends.

Quantification of the diffusive methane fluxes between the coastal ocean and atmosphere is important to constrain the atmospheric methane budget. The determination of the fluxes in coastal waters is characterized by a high level of uncertainty. To improve the accuracy of the estimation of coastal methane fluxes, high temporal and spatial sampling frequencies of dissolved methane in seawater are required, as well as the quantification of atmospheric methane concentrations, wind speed and wind direction above the ocean. In most cases, these atmospheric data are obtained from land-based atmospheric and meteorological monitoring stations in the vicinity of the coastal ocean methane observations. In this study, we measured wind speed, wind direction and atmospheric methane directly on board three research vessels in the southern North Sea and compared the local and remote atmospheric and meteorological measurements on the quality of the flux data. In addition, we assessed the source of the atmospheric methane measured in the study area in the German Bight using air mass back-trajectory assessments. The choice of the wind speed data source had a strong impact on the flux calculations. Fluxes based on wind data from nearby weather stations amounted to only 58 ± 34 % of values based on in situ data. Using in situ data, we calculated an average diffusive methane sea-to-air flux of 221 ± 351 µmol m−2 d−1 (n = 941) and 159 ± 444 µmol m−2 d−1 (n = 3028) for our study area in September 2019 and 2020, respectively. The area-weighted diffusive flux for the entire area of Helgoland Bay (3.78 × 109 m2) was 836 ± 97 and 600 ± 111 kmol d−1 for September 2019 and 2020, respectively. Using the median value of the diffusive fluxes for these extrapolations resulted in much lower values compared to area-weighted extrapolations or mean-based extrapolations. In general, at high wind speeds, the surface water turbulence is enhanced, and the diffusive flux increases. However, this enhanced methane input is quickly diluted within the air mass. Hence, a significant correlation between the methane flux and the atmospheric concentration was observed only at wind speeds < 5 m s−1. The atmospheric methane concentration was mainly influenced by the wind direction, i.e., the origin of the transported air mass. Air masses coming from industrial regions resulted in elevated atmospheric methane concentrations, while air masses coming from the North Sea transported reduced methane levels. With our detailed study on the spatial distribution of methane fluxes we were able to provide a detailed and more realistic estimation of coastal methane fluxes.

&lt;p&gt;Coastal hazards such as erosion, flooding and pollution are major problems globally, exacerbated by increasing frequency and severity of hydro-meteorological extremes amidst inadequate technology and adaptive capacity. The Ghanaian coast is an example of a region impacted by such problems. Factors hampering the management and improvement of these issues include the lack of data, insufficient communication structures between stakeholders and missing pathways to informed decisions with sustained impact.&lt;/p&gt;&lt;p&gt;In this context, the MANCOGA project stands out by employing a co-design approach to develop a robust and participatory Nature-based Solution (NbS) to coastal hazards. The co-design pilot phase has drawn the focus onto steps for restoring wetlands, mangroves in particular, to provide sustainable livelihoods by protecting and reinvigorating coastal systems and environmental health.&lt;/p&gt;&lt;p&gt;In the implementation phase, MANCOGA will evaluate mangrove ecosystem services for their potential as NbS to a number of pressing local issues. A Digital Twin will use What-If scenarios to predict the role of mangroves as NbS for flood mitigation and erosion prevention. Being a dominant Blue Carbon ecosystem, mangroves will also contribute to climate change adaptation strategies as well as provide socio-economic value (e.g., through carbon credits). The wider effects on water quality, through the reduction of eutrophication, is critical for local economics, including fisheries. We employ aerial photography and remote sensing to identify possible nature-based solution areas.&lt;/p&gt;&lt;p&gt;The comprehensive community involvement of stakeholders from all societal and administrative levels facilitates frameworks to understand and evaluate effectiveness of NbS applications. The relationships and collaborative approach developed during the co-design phase will guarantee continued involvement of stakeholders. MANCOGA will provide a digital toolbox of intuitive, interactive tools to analyze and disseminate archived and new observational data, which will enable ecosystem service quantification before and after the application of NbS, and lead to knowledge-based decision-making.&lt;/p&gt;&lt;p&gt;We envision MANCOGA as the start of sustained collaboration, knowledge transfer and capacity building. Therefore, we warmly invite researchers and stakeholders, from Africa and elsewhere, to connect to MANCOGA and share experiences and efforts.&lt;/p&gt;

Nutrient and carbon dynamics within the river-estuary-coastal water systems are key processes in understanding the flux of matter from the terrestrial environment to the ocean. Here, we analysed those dynamics by following a sampling approach based on the travel time of water and an advanced calculation of nutrient fluxes in the tidal part. We started with a nearly Lagrangian sampling of the river (River Elbe, Germany; 580 km within 8 days). After a subsequent investigation of the estuary, we followed the plume of the river by raster sampling the German Bight (North Sea) using three ships simultaneously. In the river, we detected intensive longitudinal growth of phytoplankton connected with high oxygen saturation and pH values and an undersaturation of CO2, whereas concentrations of dissolved nutrients declined. In the estuary, the Elbe shifted from an autotrophic to a heterotrophic system: Phytoplankton died off upstream of the salinity gradient, causing minima in oxygen saturation and pH, supersaturation of CO2, and a release of nutrients. In the shelf region, phytoplankton and nutrient concentrations were low, oxygen was close to saturation, and pH was within a typical marine range. Over all sections, oxygen saturation was positively related to pH and negatively to pCO2. Corresponding to the significant particulated nutrient flux via phytoplankton, flux rates of dissolved nutrients from river into estuary were low and determined by depleted concentrations. In contrast, fluxes from the estuary to the coastal waters were higher and the pattern was determined by tidal current. Overall, the approach is appropriate to better understand land-ocean fluxes, particularly to illuminate the importance of these fluxes under different seasonal and hydrological conditions, including flood and drought events.

In 2018, Europe experienced an unprecedented heatwave and drought, especially in central and northern Europe, which caused decreased terrestrial production and affected ecosystem health. In this study, the effects of this event on the marine environment are investigate, with a focus on the biogeochemical response in the German Bight of the North Sea. Using time series data from FerryBoxes, research cruises, monitoring programs and remote sensing we compare conditions in 2018 to climatological values. We find that (1) the heatwave caused rapid warming of surface waters, (2) the drought reduced river discharge and nutrient loads to the coast, and (3) these combined effects altered coastal biogeochemistry and productivity. During 2018, both water discharge and nutrient loads from rivers discharging into the German Bight were below the seasonally variable 10th percentile from March onward. Throughout the study domain, water temperature was near or below that threshold in March 2018, but higher than in other years during May 2018, representing not only a heat wave, but also the fastest spring warming on record. This extreme warming period saw concurrent high peaks in chlorophyll a, dissolved oxygen and pH, consistent with the development of a strong spring bloom. It appears that productivity was above 75th percentile of the 21-year record in most of the nearshore region, while offshore it was widely below the 25th percentile in 2018. The drought-related low discharge limited nutrient supply from the rivers, but likely increased water residence time nearshore, where a surge in primary production with efficient nutrient utilization during the spring depleted nutrients available for transport offshore. There, the heatwave-related rapid warming of surface water resulted in the establishment of a stable thermal water column stratification, hindering vertical nutrient supply to the surface layer during the summer.

The estimations of the diffusive methane flux from the water phase into the atmosphere in coastal waters is relevant for a better estimate of the atmospheric greenhouse-gas budget. Unfortunately, so far, the numerical determination of the fluxes has a high level of uncertainty in coastal waters.To improve the estimation of coastal methane fluxes, not only a high temporal and spatial sampling resolution of the dissolved methane in the water are required. Besides, also the atmospheric methane concentration and the wind speed and wind direction above the surface is important. In most cases, these atmospheric data are obtained from near-by atmospheric and meteorologic monitoring stations. In this study, we measured wind speed, direction and atmospheric methane local directly on board of three research vessel cruising in the southern North Sea within the MOSES project and compared the effects of local versus remote measurements of these data on the flux data. In addition, using the wind direction and speed, we try to assess the origin of the atmospheric methane measured in the study area. Using these “improved” data sets, we discuss if local measurements of auxiliary data provide better insights in the determining factors of the methane flux, and thus also improve the regional aquatic methane budget.

Estuaries regulate carbon cycling along the land-ocean continuum and thus influence carbon export to the ocean, and global carbon budgets. The Elbe Estuary in Germany has been altered by large anthropogenic perturbations, such as widespread heavy metal pollution, minimally treated wastewater before the 1980s, establishment of wastewater treatment plants after the 1990s, and an overall nutrient and pollutant load reduction in the last three decades. Based on an extensive evaluation of key ecosystem variables, and an analysis of the available inorganic and organic carbon records, this study has identified three ecosystem states in recent history: the polluted (1985-1990), transitional (1991-1996), and recovery (1997-2018) states. The polluted state was characterized by very high dissolved inorganic carbon (DIC) and ammonium concentrations, toxic heavy metal levels, dissolved oxygen undersaturation, and low pH. During the transitional state, heavy metal pollution decreased by > 50%, and primary production re-established in spring to summer, with weak seasonality in DIC. Since 1997, during the recovery state, DIC seasonality was driven by primary production, and DIC significantly increased by > 23 & mu;mol L-1 yr(-1) in the mid to lower estuary, indicating that, along with the improvement in water quality the ecosystem state is still changing. Large anthropogenic perturbations can therefore alter estuarine ecosystems (on the order of decades), as well as induce large and complex biogeochemical shifts and significant changes to carbon cycling.

&lt;p&gt;Fluvial extreme events, such as floods and droughts, have an impact beyond the river bed. The change in river discharge and concentration of nutrients and pollutants in freshwater also affects coastal waters, esp. their biogeochemistry. Examining these impacts has been traditionally difficult, as one needs to first detect the river plume in the seawater and then infer its spatio-temporal extent. The River Plume Workflow was developed to support researchers with these tasks and enable them to identify regions of interest, as well as provide tools to conduct a preliminary analysis of the riverine extreme events&amp;#8217; impacts on the coastal waters.&lt;/p&gt; &lt;p&gt;The Riverplume Workflow is an open source software tool to detect and examine freshwater signals as anomalies in marine observational data. Data from a FerryBox, an autonomous measuring device installed on a commercial ferry, provide regular coverage of the German Bight, the region for which we developed this toolbox. Combined with drift model computations, it is possible to detect anomalies in the observational data and to comprehend their propagation and origin.&lt;/p&gt; &lt;p&gt;The Riverplume Workflow uses the Data Analytics Software Framework (DASF) that was developed as part of the Digital Earth project. Through its modular structure, DASF supports collaborative and distributed data analysis. The Riverplume Workflow&amp;#8217;s main feature is an interactive map with various data visualization options that allows users to examine the data closely and either manually select a presumed anomaly for analysis or use an automatic anomaly detection algorithm based on Gaussian regression. The Workflow offers a statistical analysis feature to compare the composition of the selected data to the surrounding measurements. Simulated trajectories of particles starting on the FerryBox transect at the time of the original observation and modelled backwards and forwards in time help verify the origin of the river plume and allow users to follow the anomaly across their area of interest. In addition, the workflow offers the functionality to assemble satellite-based chlorophyll observations along model trajectories as a time series. They allow scientists to understand processes inside the river plume and to determine the timescales on which these developments happen.&lt;/p&gt; &lt;p&gt;The FerryBox data used in the Riverplume Workflow are pre-processed automatically and updated daily. Synoptic drift model data is provided for all Elbe extreme events since 2013. We plan to automatize the provision of model data as well.&lt;/p&gt; &lt;p&gt;We currently use the Riverplume Workflow to monitor the impacts of Elbe extreme events in the German Bight, though we plan to adapt it to other regions or types of anomalies. The Workflows&amp;#8217; code and all components are available under open source licenses and registered under the DOI https://doi.org/10.5880/GFZ.1.4.2022.006.&lt;/p&gt;

AbstractData-driven science has turned into a fourth fundamental paradigm of performing research. Earth System Science, following a holistic approach in unraveling the complex network of processes and interactions shaping system Earth, particularly profits from embracing data-driven approaches next to observation and modeling. At the end, increasing digitalization of Earth sciences will lead to cultural transformation towards a Digital Earth Culture.

AbstractArtificial intelligence and machine learning (ML) methods are increasingly applied in Earth system research, for improving data analysis, and model performance, and eventually system understanding. In the Digital Earth project, several ML approaches have been tested and applied, and are discussed in this chapter. These include data analysis using supervised learning and classification for detection of river levees and underwater ammunition; process estimation of methane emissions and for environmental health; point-to-space extrapolation of varying observed quantities; anomaly and event detection in spatial and temporal geoscientific datasets. We present the approaches and results, and finally, we provide some conclusions on the broad applications of these computational data exploration methods and approaches.

AbstractThe Digital Earth project aimed for the integration of data science and Earth science. Here, we reflect on the main lessons learned that include the need for interdisciplinary collaboration, thinking out of the box, the concept of ‘thinking in workflows’ and models for the sustainable implementation of scientific software, data infrastructure and policies.

AbstractDigital Earth is a project funded by the German Helmholtz Association with all centers of the research field Earth and Environment involved. The main goal of the Digital Earth project is to develop and bundle data science methods in extendable and maintainable scientific workflows that enable natural scientists in collaboration with data scientists to achieve a deeper understanding of the Earth system. This has been achieved by developing solutions for data analysis and exploration with visual and computational approaches with data obtained in a SMART monitoring approach and modeling studies, accompanied by a continuous evaluation of the collaboration processes. In this chapter, the history, setup, and focus of the Digital Earth project are described.

The inventory and variability of oceanic dissolved inorganic carbon (DIC) is driven by the interplay of physical, chemical, and biological processes. Quantifying the spatiotemporal variability of these drivers is crucial for a mechanistic understanding of the ocean carbon sink and its future trajectory. Here, we use the Estimating the Circulation and Climate of the Ocean‐Darwin ocean biogeochemistry state estimate to generate a global‐ocean, data‐constrained DIC budget and investigate how spatial and seasonal‐to‐interannual variability in three‐dimensional circulation, air‐sea CO2 flux, and biological processes have modulated the ocean sink for 1995–2018. Our results demonstrate substantial compensation between budget terms, resulting in distinct upper‐ocean carbon regimes. For example, boundary current regions have strong contributions from vertical diffusion while equatorial regions exhibit compensation between upwelling and biological processes. When integrated across the full ocean depth, the 24‐year DIC mass increase of 64 Pg C (2.7 Pg C year−1) primarily tracks the anthropogenic CO2 growth rate, with biological processes providing a small contribution of 2% (1.4 Pg C). In the upper 100 m, which stores roughly 13% (8.1 Pg C) of the global increase, we find that circulation provides the largest DIC gain (6.3 Pg C year−1) and biological processes are the largest loss (8.6 Pg C year−1). Interannual variability is dominated by vertical advection in equatorial regions, with the 1997–1998 El Niño‐Southern Oscillation causing the largest year‐to‐year change in upper‐ocean DIC (2.1 Pg C). Our results provide a novel, data‐constrained framework for an improved mechanistic understanding of natural and anthropogenic perturbations to the ocean sink.

Climate projections show high temperature extremes, meteorological droughts and heavy precipitation events are set to increase across Europe (Barros et al., 2014), where the decadel average has already increaed, with temperature in 2002-2011 already 1.3°C±0.1°C above the 1850-1899 mean (Barros et al., 2014). The observed seasonal precipitation pattern presents drier summers and wetter winters across Europe, also mirrored in river flow changes. Across small river catchments in Europe from 1962 to 2004, winter period showed positive trends whereas summers were characterized by negative trends in river flow (Stahl et al., 2010). Such changes can alter the residence time of an estuary. Estuaries are biogeochemical hotspots, and critical zones for carbon cycling, and changes in the hydrological balance, still largely not well characterized, may influence processes within the water column. The present study will assess the potential impacts of droughts on the carbonate system in the Elbe estuary. One of the largest in central Europe, the Elbe River catchment spreads over approximately 150,000 km2 in four countries. Between 2014 and 2018, regions of Northern Germany have been under drought conditions during certain months (UFZ, 2018), reducing discharge in the Elbe River. From 2014, annual Elbe river discharge has been relatively low, where 2018 exhibited the lowest annual mean river discharge of 441 m3 s-1 since 1992. Model projections show the annual river discharge for the Elbe river is likely to remain low at 410 m2 s-1 in 2046-2055 compared to >550 m2 s-1 in 1960-1990 (Krysanova et al., 2005). Analysis of the long-term FGG Elbe (Flussgebietsgemeinschaft Elbe) records of dissolved inorganic carbon (DIC) in the mid to lower Elbe estuary show that over spring and summer months DIC values have increased with time (1997-2018). In this period, DIC increased from the freshwater to the mesohaline region, followed by a decrease to the polyhaline zone. This is opposing to previous DIC patterns in the early 1980s, where DIC decreased towards the mid-estuary after which increased to the outer estuary. An increase in DIC in the mid-estuarine region coincided with increased turbidity and extended residence time, and during the productive months with higher organic matter from upstream regions. This could suggest that more time for heterotrophic activity and availability of labile organic matter, acts to enrich DIC within the water column in the turbid regions, thus changing carbon cycling within the estuary. Further analysis will focus on the changes in river discharge and inorganic carbon during the past two decades, thus inclusive of low discharge and drought conditions.