Gerald Dörflinger

Assessing the ecological quality of inland waters is key to managing resources and guiding sustainable agriculture practices. In EU member states, the monitoring of surface waters is based on the Water Framework Directive (WFD; 2000/60/EC), which links the ecological status with anthropogenic pressures. For this, the framework introduced the biological quality elements (BQEs) that are used to establish ecological status. Among BQEs, a key element for assessing nutrient enrichment reflecting eutrophication is phytoplankton, for which several multi-metric indicators have been proposed and used for different types of lake and river water bodies. Among the metrics included in phytoplankton indicators, biomass, cyanobacterial contribution to total phytoplankton and composition are routinely integrated. However, classical phytoplankton measurements are based on the microscopic identification of several morphologically dubious taxa, cryptic and rare species, especially in the pico- and nanoplankton. Thus, eDNA high-throughput sequencing is emerging as a cost-effective, massively parallel approach to resolve morphology-based bottlenecks on phytoplankton water quality indicators. Aiming to propose and develop a multi-metric eDNA-based water quality indicator, we applied a staggered strategy using SSU rRNA gene metabarcoding of planktonic communities across lakes of different typologies in Greece and Cyprus. First, the mirroring of metabarcoding normalized abundance data, presented as relative number of reads per taxon, with conventional estimates of phytoplankton abundance and biomass was attempted. We found that correcting for unicellular eukaryotic rRNA gene copy number based on taxon-specific biovolume data provided reliable coupling of biomass-based metrics and read numbers. Then, assessment metrics were selected to reflect eutrophication conditions in the eDNA-based indicator through ecological modelling tools, including multiple linear regression models and random forest predictors. Among the tested metrics, the most fitted were the relative number of cyanobacterial reads, the dominance of bloom forming taxa, and the ratio of harmful:non-harmful groups or taxa. Using eDNA tools will further lead to the development of emerging indicators of additional quality elements, such as bacterioplankton, zooplankton, and functional diversity. Bacterial groups, albeit not included in the WFD legislation, can play key roles in nitrogen, phosphorus, and organic carbon cycling, with metabolic pathways that process many of the pollutants associated with eutrophication. Zooplankton species are the link between primary producers and higher trophic levels, containing taxa that are directly linked to eutrophication. In addition, by integrating shotgun metagenomics to resolve the underlying gene content, the functional genetic capacities of planktonic communities can be associated with environmental stressors reflecting the overall water quality. By associating phytoplankton metacommunity dynamics (composition, functional traits, and indicator taxa metrics), to hydro-ecological connectivity gradients, eDNA can provide a scalable tool for assessing ecosystem health, resilience, and the impacts of fragmentation or homogenization.

The robustness of hydrological models used in projections of future fresh water resources is compromised due to non-stationary climate conditions. This study aims to (i) develop a method for selecting a skillful hydrological model parameterization under changing climate conditions and (ii) apply a calibrated hydrological model to assess streamflow projections for 38 mountain watersheds in the eastern Mediterranean island of Cyprus over the next decades (2030–2060). A matrix-based approach was developed to evaluate six objective functions by eight performance measures. Using the GR4J hydrological model, evaluation matrices were computed for multiple 5-year simulation runs covering 1980–2015. The matrices covered 14 model calibrations and 182 validations in total, as well as 4 sets of validations under different climate change conditions, for each watershed. Based on the matrix method, the Nash-Sutcliffe Efficiency with square-root transformed streamflow resulted in the best performance for streamflow simulations in Mediterranean watersheds experiencing drying trends. This method is transferable and can be applied in different climate regions to identify the most suitable objective function and model parameterization for hydrologic climate impact assessments. Eighteen Regional Climate Models (RCMs) were bias-corrected, downscaled to 1 km and used to simulate streamflow with GR4J for 1980–2010. Nine RCMs underestimated the fraction of wet period precipitation (60–73 % instead of 82 % of annual precipitation), causing streamflow biases up to 40 %. The remaining nine RCMs selected for the study simulated the seasonal precipitation cycle accurately. The median of future projections showed a 6 % reduction in precipitation and a 17 % reduction in streamflow. In the worst case, reductions could reach 16 % and 39 %, respectively. Notably, during the driest years, streamflow reductions could reach 70 % relative to the driest years in the past. Our findings suggest that terrestrial water resources in the eastern Mediterranean may significantly deteriorate in the coming decades.

The robustness of hydrological models used in projections of future fresh water resources is compromised due to non-stationary climate conditions. This study aims to (i) develop a method for selecting a skillful hydrological model parameterization under changing climate conditions and (ii) apply a calibrated hydrological model to assess streamflow projections for 38 mountain watersheds in the eastern Mediterranean island of Cyprus over the next decades (2030–2060). A matrix-based approach was developed to evaluate six objective functions by eight performance measures. Using the GR4J hydrological model, evaluation matrices were computed for multiple 5-year simulation runs covering 1980–2015. The matrices covered 14 model calibrations and 182 validations in total, as well as 4 sets of validations under different climate change conditions, for each watershed. Based on the matrix method, the Nash-Sutcliffe Efficiency with square-root transformed streamflow resulted in the best performance for streamflow simulations in Mediterranean watersheds experiencing drying trends. This method is transferable and can be applied in different climate regions to identify the most suitable objective function and model parameterization for hydrologic climate impact assessments. Eighteen Regional Climate Models (RCMs) were bias-corrected, downscaled to 1 km and used to simulate streamflow with GR4J for 1980–2010. Nine RCMs underestimated the fraction of wet period precipitation (60–73 % instead of 82 % of annual precipitation), causing streamflow biases up to 40 %. The remaining nine RCMs selected for the study simulated the seasonal precipitation cycle accurately. The median of future projections showed a 6 % reduction in precipitation and a 17 % reduction in streamflow. In the worst case, reductions could reach 16 % and 39 %, respectively. Notably, during the driest years, streamflow reductions could reach 70 % relative to the driest years in the past. Our findings suggest that terrestrial water resources in the eastern Mediterranean may significantly deteriorate in the coming decades.

The robustness of hydrological models used in projections of future fresh water resources is compromised due to non-stationary climate conditions. This study aims to (i) develop a method for selecting a skillful hydrological model parameterization under changing climate conditions and (ii) apply a calibrated hydrological model to assess streamflow projections for 38 mountain watersheds in the eastern Mediterranean island of Cyprus over the next decades (2030–2060). A matrix-based approach was developed to evaluate six objective functions by eight performance measures. Using the GR4J hydrological model, evaluation matrices were computed for multiple 5-year simulation runs covering 1980–2015. The matrices covered 14 model calibrations and 182 validations in total, as well as 4 sets of validations under different climate change conditions, for each watershed. Based on the matrix method, the Nash-Sutcliffe Efficiency with square-root transformed streamflow resulted in the best performance for streamflow simulations in Mediterranean watersheds experiencing drying trends. This method is transferable and can be applied in different climate regions to identify the most suitable objective function and model parameterization for hydrologic climate impact assessments. Eighteen Regional Climate Models (RCMs) were bias-corrected, downscaled to 1 km and used to simulate streamflow with GR4J for 1980–2010. Nine RCMs underestimated the fraction of wet period precipitation (60–73 % instead of 82 % of annual precipitation), causing streamflow biases up to 40 %. The remaining nine RCMs selected for the study simulated the seasonal precipitation cycle accurately. The median of future projections showed a 6 % reduction in precipitation and a 17 % reduction in streamflow. In the worst case, reductions could reach 16 % and 39 %, respectively. Notably, during the driest years, streamflow reductions could reach 70 % relative to the driest years in the past. Our findings suggest that terrestrial water resources in the eastern Mediterranean may significantly deteriorate in the coming decades.

The robustness of hydrological models used in projections of future fresh water resources is compromised due to non-stationary climate conditions. This study aims to (i) develop a method for selecting a skillful hydrological model parameterization under changing climate conditions and (ii) apply a calibrated hydrological model to assess streamflow projections for 38 mountain watersheds in the eastern Mediterranean island of Cyprus over the next decades (2030–2060). A matrix-based approach was developed to evaluate six objective functions by eight performance measures. Using the GR4J hydrological model, evaluation matrices were computed for multiple 5-year simulation runs covering 1980–2015. The matrices covered 14 model calibrations and 182 validations in total, as well as 4 sets of validations under different climate change conditions, for each watershed. Based on the matrix method, the Nash-Sutcliffe Efficiency with square-root transformed streamflow resulted in the best performance for streamflow simulations in Mediterranean watersheds experiencing drying trends. This method is transferable and can be applied in different climate regions to identify the most suitable objective function and model parameterization for hydrologic climate impact assessments. Eighteen Regional Climate Models (RCMs) were bias-corrected, downscaled to 1 km and used to simulate streamflow with GR4J for 1980–2010. Nine RCMs underestimated the fraction of wet period precipitation (60–73 % instead of 82 % of annual precipitation), causing streamflow biases up to 40 %. The remaining nine RCMs selected for the study simulated the seasonal precipitation cycle accurately. The median of future projections showed a 6 % reduction in precipitation and a 17 % reduction in streamflow. In the worst case, reductions could reach 16 % and 39 %, respectively. Notably, during the driest years, streamflow reductions could reach 70 % relative to the driest years in the past. Our findings suggest that terrestrial water resources in the eastern Mediterranean may significantly deteriorate in the coming decades.

The robustness of hydrological models used in projections of future fresh water resources is compromised due to non-stationary climate conditions. This study aims to (i) develop a method for selecting a skillful hydrological model parameterization under changing climate conditions and (ii) apply a calibrated hydrological model to assess streamflow projections for 38 mountain watersheds in the eastern Mediterranean island of Cyprus over the next decades (2030–2060). A matrix-based approach was developed to evaluate six objective functions by eight performance measures. Using the GR4J hydrological model, evaluation matrices were computed for multiple 5-year simulation runs covering 1980–2015. The matrices covered 14 model calibrations and 182 validations in total, as well as 4 sets of validations under different climate change conditions, for each watershed. Based on the matrix method, the Nash-Sutcliffe Efficiency with square-root transformed streamflow resulted in the best performance for streamflow simulations in Mediterranean watersheds experiencing drying trends. This method is transferable and can be applied in different climate regions to identify the most suitable objective function and model parameterization for hydrologic climate impact assessments. Eighteen Regional Climate Models (RCMs) were bias-corrected, downscaled to 1 km and used to simulate streamflow with GR4J for 1980–2010. Nine RCMs underestimated the fraction of wet period precipitation (60–73 % instead of 82 % of annual precipitation), causing streamflow biases up to 40 %. The remaining nine RCMs selected for the study simulated the seasonal precipitation cycle accurately. The median of future projections showed a 6 % reduction in precipitation and a 17 % reduction in streamflow. In the worst case, reductions could reach 16 % and 39 %, respectively. Notably, during the driest years, streamflow reductions could reach 70 % relative to the driest years in the past. Our findings suggest that terrestrial water resources in the eastern Mediterranean may significantly deteriorate in the coming decades.

Land use composition, water level fluctuations (WLFs), and biogeographical factors are recognized as key drivers of phytoplankton dynamics in reservoir ecosystems. This two-year study presents the first assessment of the combined effects of catchment land use, WLFs, and geographical distance on phytoplankton biomass and community composition across twelve Mediterranean reservoirs in Cyprus, which serve primarily for drinking water supply and irrigation. The results show that higher phytoplankton biomass was recorded in reservoirs whose catchments had >30% coverage by developed land (urban and agricultural), suggesting that increased anthropogenic pressures may lead to nutrient enrichment and elevated productivity. However, despite elevated biomass, no consistent spatial patterns were observed in phytoplankton community composition. The geographical distance between reservoirs had only a minor effect on species distribution, implying that other factors—such as water residence time or hydrological variability—play a more prominent role in shaping community structure. Phytoplankton biomass maxima were most often recorded during periods of elevated water levels and were typically dominated by Chlorophyta, Dinoflagellata, Bacillariophyta, and Charophyta. The pronounced temporal variability in species composition across all reservoirs points to a highly dynamic system, where environmental fluctuations strongly influence community assembly. This study provides the first comprehensive data on phytoplankton in Cyprus reservoirs, highlighting the importance of land use and hydrological regulation for water quality management in similar settings. Importantly, this baseline dataset can support the implementation of the Water Framework Directive (WFD) by contributing to the definition of ecological status classes, establishing reference conditions, and guiding future monitoring and assessment efforts. Expanding such datasets through coordinated, basin-wide monitoring initiatives is essential to improve our understanding of phytoplankton dynamics and their role in ecosystem functioning under the pressures of climate change and intensified land use in this Mediterranean “hot spot”.

The robustness of hydrological models used in projections of future fresh water resources is compromised due to non-stationary climate conditions. This study aims to (i) develop a method for selecting a skillful hydrological model parameterization under changing climate conditions and (ii) apply a calibrated hydrological model to assess streamflow projections for 38 mountain watersheds in the eastern Mediterranean island of Cyprus over the next decades (2030–2060). A matrix-based approach was developed to evaluate six objective functions by eight performance measures. Using the GR4J hydrological model, evaluation matrices were computed for multiple 5-year simulation runs covering 1980–2015. The matrices covered 14 model calibrations and 182 validations in total, as well as 4 sets of validations under different climate change conditions, for each watershed. Based on the matrix method, the Nash-Sutcliffe Efficiency with square-root transformed streamflow resulted in the best performance for streamflow simulations in Mediterranean watersheds experiencing drying trends. This method is transferable and can be applied in different climate regions to identify the most suitable objective function and model parameterization for hydrologic climate impact assessments. Eighteen Regional Climate Models (RCMs) were bias-corrected, downscaled to 1 km and used to simulate streamflow with GR4J for 1980–2010. Nine RCMs underestimated the fraction of wet period precipitation (60–73 % instead of 82 % of annual precipitation), causing streamflow biases up to 40 %. The remaining nine RCMs selected for the study simulated the seasonal precipitation cycle accurately. The median of future projections showed a 6 % reduction in precipitation and a 17 % reduction in streamflow. In the worst case, reductions could reach 16 % and 39 %, respectively. Notably, during the driest years, streamflow reductions could reach 70 % relative to the driest years in the past. Our findings suggest that terrestrial water resources in the eastern Mediterranean may significantly deteriorate in the coming decades.

Freshwater macroinvertebrates are a diverse group and play key ecological roles, including accelerating nutrient cycling, filtering water, controlling primary producers, and providing food for predators. Their differences in tolerances and short generation times manifest in rapid community responses to change. Macroinvertebrate community composition is an indicator of water quality. In Europe, efforts to improve water quality following environmental legislation, primarily starting in the 1980s, may have driven a recovery of macroinvertebrate communities. Towards understanding temporal and spatial variation of these organisms, we compiled the TREAM dataset (Time seRies of European freshwAter Macroinvertebrates), consisting of macroinvertebrate community time series from 1,816 river and stream sites (mean length of 19.2 years and 14.9 sampling years) of 22 European countries sampled between 1968 and 2020. In total, the data include >93 million sampled individuals of 2,648 taxa from 959 genera and 212 families. These data can be used to test questions ranging from identifying drivers of the population dynamics of specific taxa to assessing the success of legislative and management restoration efforts.