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Temperature and dissolved oxygen concentration are critical factors affecting the exchange of solutes between sediment and water; both factors will be affected by warming of lakes and thereby influence water quality. Temperature and oxygen responses of single solute fluxes are well known, however not much is known about interaction of temperature and oxygen in regulating the balance of different fluxes in the benthic environment. We analyzed benthic flux (mobilization and immobilization) data of various solutes (DOC, CH4, NO3--N, NH4+-N, SRP, SO4-, Fe, Mn, and O2) collected from laboratory incubations of 142 sediment cores from 5 different reservoirs incubated under varying in-situ temperature and oxygen conditions. Oxygen was the primary driver of benthic fluxes while temperature and total organic content were secondary. Temperature effects on benthic fluxes were stronger under anoxic conditions which imply that warming will substantially increase the benthic fluxes if the sediment surface becomes anoxic. The varying temperature response of processes underlying the studied fluxes will result in a shift of their relative importance in the benthic environment especially in shallow lakes that are more vulnerable to warming. For example more anoxic conditions will shift the equilibrium between net sulfate reduction and methane release towards the latter. We also predict that physical effects of warming leading to hypolimnetic oxygen depletion i.e. stronger stratification and longer hypolimnetic confinement will increase the benthic mobilization of phosphorus, dissolved organic carbon, and methane into water and immobilization of sulfate by the sediments even in deep lakes.

Despite high potential benefits, the development of seasonal forecasting tools in the water sector has been slower than in other sectors. Here we assess the skill of seasonal forecasting tools for lakes and reservoirs set up at four sites in Australia and Europe. These tools consist of coupled hydrological catchment and lake models forced with seasonal meteorological forecast ensembles to provide probabilistic predictions of seasonal anomalies in water discharge, temperature and ice-off. Successful implementation requires a rigorous assessment of the tools' predictive skill and an apportionment of the predictability between legacy effects and input forcing data. To this end, models were forced with two meteorological datasets from the European Centre for Medium-Range Weather Forecasts (ECMWF), the seasonal forecasting system, SEAS5, with 3-month lead times and the ERA5 reanalysis. Historical skill was assessed by comparing both model outputs, i.e. seasonal lake hindcasts (forced with SEAS5), and pseudo-observations (forced with ERA5). The skill of the seasonal lake hindcasts was generally low although higher than the reference hindcasts, i.e. pseudo-observations, at some sites for certain combinations of season and variable. The SEAS5 meteorological predictions showed less skill than the lake hindcasts. In fact, skilful lake hindcasts identified for selected seasons and variables were not always synchronous with skilful SEAS5 meteorological hindcasts, raising questions on the source of the predictability. A set of sensitivity analyses showed that most of the forecasting skill originates from legacy effects, although during winter and spring in Norway some skill was coming from SEAS5 over the 3-month target season. When SEAS5 hindcasts were skilful, additional predictive skill originates from the interaction between legacy and SEAS5 skill. We conclude that lake forecasts forced with an ensemble of boundary conditions resampled from historical meteorology are currentl

The occurrence of pharmaceuticals in influent wastewater samples (IWW) is a recurrent issue. The monitoring of their presence is not only valuable from an environmental point of view, but also as a tool to analyze patterns of human use by the so-called wastewater-based epidemiology. The development of an analytical method based on solid-phase extraction followed by liquid chromatography coupled to tandem mass spectrometry to monitor the occurrence of a group of seventeen pharmaceuticals including the most representative for various therapeutic families in IWW samples is described in this work. The samples were collected during a monitoring week in six wastewater treatment plants located in different cities and towns across Spain. The developed method provides acceptable figures of merit with apparent recoveries in IWW ranging from 42% to 139%, and low matrix effect (in general lower than ± 30%), and method quantification limits (MQL) between 1 ng/L and 24 ng/L for all compounds, except atenolol (58 ng/L). All the studied pharmaceuticals were found in all samples with concentrations ranging from < MQL to 10,393 ng/L, being the highest concentrations for tramadol. The population normalized daily loads revealed that the use of pharmaceuticals follows, in general, a similar pattern in all cities monitored.

Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5∘ × 0.5∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project

Advance warning of seasonal conditions has the potential to assist water management in planning and risk mitigation, with large potential social, economic, and ecological benefits. In this study, we explore the value of seasonal forecasting for decision-making at five case study sites located in extratropical regions. The forecasting tools used integrate seasonal climate model forecasts with freshwater impact models of catchment hydrology, lake conditions (temperature, water level, chemistry, and ecology), and fish migration timing and were co-developed together with water managers. To explore the decision-making value of forecasts, we carried out a qualitative assessment of (1) how useful forecasts would have been for a problematic past season and (2) the relevance of any windows of opportunity (seasons and variables where forecasts are thought to perform well) for management. Overall, water managers were optimistic about the potential for improved decision-making and identified actions that could be taken based on forecasts. However, there was often a mismatch between those variables that could best be predicted and those which would be most useful for management. Reductions in forecast uncertainty and a need to develop practical, hands-on experience were identified as key requirements before forecasts would be used in operational decision-making. Seasonal climate forecasts provided little added value to freshwater forecasts in these extratropical study sites, and we discuss the conditions under which seasonal climate forecasts with only limited skill are most likely to be worth incorporating into freshwater forecasting workflows.

Headspace analysis of CO2 frequently has been used to quantify the concentration of CO2 in fresh water. According to basic chemical theory, not considering chemical equilibration of the carbonate system in the sample vials will result in a systematic error. By analysing the potential error for different types of water and experimental conditions, we show that the error incurred by headspace analysis of CO2 is less than 5 % for typical samples from boreal systems which have low alkalinity (< 900 µmol L−1), with pH < 7.5, and high pCO2 (> 1000 µatm). However, the simple headspace calculation can lead to high error (up to −300 %) or even impossibly negative values in highly undersaturated samples equilibrated with ambient air, unless the shift in carbonate equilibrium is explicitly considered. The precision of the method can be improved by lowering the headspace ratio and/or the equilibration temperature. We provide a convenient and direct method implemented in an R script or a JMP add-in to correct CO2 headspace results using separately measured alkalinity.

One of the most important physical characteristics driving lifecycle events in lakes is stratification. Already subtle variations in the timing of stratification onset and break-up (phenology) are known to have major ecological effects, mainly by determining the availability of light, nutrients, carbon and oxygen to organisms. Despite its ecological importance, historic and future global changes in stratification phenology are unknown. Here, we used a lake-climate model ensemble and long-term observational data, to investigate changes in lake stratification phenology across the Northern Hemisphere from 1901 to 2099. Under the high-greenhouse-gas-emission scenario, stratification will begin 22.0 ± 7.0 days earlier and end 11.3 ± 4.7 days later by the end of this century. It is very likely that this 33.3 ± 11.7 day prolongation in stratification will accelerate lake deoxygenation with subsequent effects on nutrient mineralization and phosphorus release from lake sediments. Further misalignment of lifecycle events, with possible irreversible changes for lake ecosystems, is also likely.

Reservoir drawdown areas—where sediment is exposed to the atmosphere due to water-level fluctuations—are hotspots for carbon dioxide (CO2) emissions. However, the global extent of drawdown areas is unknown, precluding an accurate assessment of the carbon budget of reservoirs. Here we show, on the basis of satellite observations of 6,794 reservoirs between 1985 and 2015, that 15% of the global reservoir area was dry. Exposure of drawdown areas was most pronounced in reservoirs close to the tropics and shows a complex dependence on climatic (precipitation, temperature) and anthropogenic (water use) drivers. We re-assessed the global carbon emissions from reservoirs by apportioning CO2 and methane emissions to water surfaces and drawdown areas using published areal emission rates. The new estimate assigns 26.2 (15–40) (95% confidence interval) TgCO2-C yr−1 to drawdown areas, and increases current global CO2 emissions from reservoirs by 53% (60.3 (43.2–79.5) TgCO2-C yr−1). Taking into account drawdown areas, the ratio between carbon emissions and carbon burial in sediments is 2.02 (1.04–4.26). This suggests that reservoirs emit more carbon than they bury, challenging the current understanding that reservoirs are net carbon sinks. Thus, consideration of drawdown areas overturns our conception of the role of reservoirs in the carbon cycle.

Seasonal climate forecasts produce probabilistic predictions of meteorological variables for subsequent months. This provides a potential resource to predict the influence of seasonal climate anomalies on surface water balance in catchments and hydro-thermodynamics in related water bodies (e.g., lakes or reservoirs). Obtaining seasonal forecasts for impact variables (e.g., discharge and water temperature) requires a link between seasonal climate forecasts and impact models simulating hydrology and lake hydrodynamics and thermal regimes. However, this link remains challenging for stakeholders and the water scientific community, mainly due to the probabilistic nature of these predictions. In this paper, we introduce a feasible, robust, and open-source workflow integrating seasonal climate forecasts with hydrologic and lake models to generate seasonal forecasts of discharge and water temperature profiles. The workflow has been designed to be applicable to any catchment and associated lake or reservoir, and is optimized in this study for four catchment-lake systems to help in their proactive management. We assessed the performance of the resulting seasonal forecasts of discharge and water temperature by comparing them with hydrologic and lake (pseudo)observations (reanalysis). Precisely, we analysed the historical performance using a data sample of past forecasts and reanalysis to obtain information about the skill (performance or quality) of the seasonal forecast system to predict particular events. We used the current seasonal climate forecast system (SEAS5) and reanalysis (ERA5) of the European Centre for Medium Range Weather Forecasts (ECMWF). We found that due to the limited predictability at seasonal time-scales over the locations of the four case studies (Europe and South of Australia), seasonal forecasts exhibited none to low performance (skill) for the atmospheric variables considered. Nevertheless, seasonal forecasts for discharge present some skill in all but

Despite substantial advances in quantifying greenhouse gas (GHG) emissions from dry inland waters, existing estimates mainly consist of carbon dioxide (CO2) emissions. However, methane (CH4) may also be relevant due to its higher Global Warming Potential (GWP). We report CH4 emissions from dry inland water sediments to i) provide a cross-continental estimate of such emissions for different types of aquatic systems (i.e., lakes, ponds, reservoirs, and streams) and climate zones (i.e., tropical, continental, and temperate); and ii) determine the environmental factors that control these emissions. CH4 emissions from dry inland waters were consistently higher than emissions observed in adjacent uphill soils, across climate zones and in all aquatic systems except for streams. However, the CH4 contribution (normalized to CO2 equivalents; CO2-eq) to the total GHG emissions of dry inland waters was similar for all types of aquatic systems and varied from 10 to 21%. Although we discuss multiple controlling factors, dry inland water CH4 emissions were most strongly related to sediment organic matter content and moisture. Summing CO2 and CH4 emissions revealed a cross-continental average emission of 9.6 ± 17.4 g CO2-eq m−2 d−1 from dry inland waters. We argue that increasing droughts likely expand the worldwide surface area of atmosphere-exposed aquatic sediments, thereby increasing global dry inland water CH4 emissions. Hence, CH4 cannot be ignored if we want to fully understand the carbon (C) cycle of dry sediments.

Heat uptake is a key variable for understanding the Earth system response to greenhouse gas forcing. Despite the importance of this heat budget, heat uptake by inland waters has so far not been quantified. Here we use a unique combination of global‐scale lake models, global hydrological models and Earth system models to quantify global heat uptake by natural lakes, reservoirs, and rivers. The total net heat uptake by inland waters amounts to 2.6 ± 3.2 ×1020 J over the period 1900–2020, corresponding to 3.6% of the energy stored on land. The overall uptake is dominated by natural lakes (111.7%), followed by reservoir warming (2.3%). Rivers contribute negatively (‐14%) due to a decreasing water volume. The thermal energy of water stored in artificial reservoirs exceeds inland water heat uptake by a factor ∼10.4. This first quantification underlines that the heat uptake by inland waters is relatively small, but non‐negligible.

[EN] Many inland waters exhibit complete or partial desiccation, or have vanished due to global change, exposing sediments to the atmosphere. Yet, data on carbon dioxide (CO2) emissions from these sediments are too scarce to upscale emissions for global estimates or to understand their fundamental drivers. Here, we present the results of a global survey covering 196 dry inland waters across diverse ecosystem types and climate zones. We show that their CO2 emissions share fundamental drivers and constitute a substantial fraction of the carbon cycled by inland waters. CO2 emissions were consistent across ecosystem types and climate zones, with local characteristics explaining much of the variability. Accounting for such emissions increases global estimates of carbon emissions from inland waters by 6% (~0.12 Pg C y−1). Our results indicate that emissions from dry inland waters represent a significant and likely increasing component of the inland waters carbon cycle.

Human consumption of pharmaceuticals leads to high concentrations of pharmaceuticals in wastewater, which is usually not or insufficiently collected and treated before release into freshwater ecosystems. There, pharmaceuticals may pose a threat to aquatic biota. Unfortunately, occurrence data of pharmaceuticals in freshwaters at the global scale is scarce and unevenly distributed, thus preventing the identification of hotspots, the prediction of the impact of Global Change (particularly streamflow and population changes) on their occurrence, and the design of appropriate mitigation actions. Here, we use diclofenac (DCL) as a typical pharmaceutical contaminant, and a global model of DCL chemical fate based on wastewater sanitation, population density and hydrology to estimate current concentrations in the river network, the impact of future changes in runoff and population, and potential mitigation actions in line with the Sustainable Development Goals. Our model is calibrated against measurements available in the literature. We estimate that 2.74 ± 0.63% of global river network length has DCL concentrations exceeding the proposed EU Watch list limit (100 ng L-1). Furthermore, many rivers downstream from highly populated areas show values beyond 1000 ng L-1, particularly those associated to megacities in Asia lacking sufficient wastewater treatment. This situation will worsen with Global Change, as streamflow changes and human population growth will increase the proportion of the river network above 100 ng L-1 up to 3.10 ± 0.72%. Given this background, we assessed feasible source and end-of-pipe mitigation actions, including per capita consumption reduction through eco-directed sustainable prescribing (EDSP), the implementation of the United Nations Sustainable Development Goal (SDG) 6 of halving the proportion of population without access to safely managed sanitation services, and improvement of wastewater treatment plants up to the Swiss standards. Among the consid

Many inland waters exhibit complete or partial desiccation, or have vanished due to global change, exposing sediments to the atmosphere. Yet, data on carbon dioxide (CO2) emissions from these sediments are too scarce to upscale emissions for global estimates or to understand their fundamental drivers. Here, we present the results of a global survey covering 196 dry inland waters across diverse ecosystem types and climate zones. We show that their CO2 emissions share fundamental drivers and constitute a substantial fraction of the carbon cycled by inland waters. CO2 emissions were consistent across ecosystem types and climate zones, with local characteristics explaining much of the variability. Accounting for such emissions increases global estimates of carbon emissions from inland waters by 6% (~0.12 Pg C y−1). Our results indicate that emissions from dry inland waters represent a significant and likely increasing component of the inland waters carbon cycle.