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Lake Tanganyika, the deepest and most voluminous lake in Africa, has warmed over the last century in response to climate change. Separate analyses of surface warming rates estimated from in situ instruments, satellites, and a paleolimnological temperature proxy (TEX86) disagree, leaving uncertainty about the thermal sensitivity of Lake Tanganyika to climate change. Here, we use a comprehensive database of in situ temperature data from the top 100 meters of the water column that span the lake's seasonal range and lateral extent to demonstrate that long-term temperature trends in Lake Tanganyika depend strongly on depth, season, and latitude. The observed spatiotemporal variation in surface warming rates accounts for small differences between warming rate estimates from in situ instruments and satellite data. However, after accounting for spatiotemporal variation in temperature and warming rates, the TEX86 paleolimnological proxy yields lower surface temperatures (1.46 °C lower on average) and faster warming rates (by a factor of three) than in situ measurements. Based on the ecology of Thaumarchaeota (the microbes whose biomolecules are involved with generating the TEX86 proxy), we offer a reinterpretation of the TEX86 data from Lake Tanganyika as the temperature of the low-oxygen zone, rather than of the lake surface temperature as has been suggested previously. Our analyses provide a thorough accounting of spatiotemporal variation in warming rates, offering strong evidence that thermal and ecological shifts observed in this massive tropical lake over the last century are robust and in step with global climate change.

Background Rivers and lakes are used for multiple purposes such as for drinking water (DW) production, recreation, and as recipients of wastewater from various sources. The deterioration of surface water quality with wastewater is well-known, but less is known about the bacterial community dynamics in the affected surface waters. Understanding the bacterial community characteristics —from the source of contamination, through the watershed to the DW production process—may help safeguard human health and the environment. Results The spatial and seasonal dynamics of bacterial communities, their predicted functions, and potential health-related bacterial (PHRB) reads within the Kokemäenjoki River watershed in southwest Finland were analyzed with the 16S rRNA-gene amplicon sequencing method. Water samples were collected from various sampling points of the watershed, from its major pollution sources (sewage influent and effluent, industrial effluent, mine runoff) and different stages of the DW treatment process (pre-treatment, groundwater observation well, DW production well) by using the river water as raw water with an artificial groundwater recharge (AGR). The beta-diversity analysis revealed that bacterial communities were highly varied among sample groups (R = 0.92, p  <  0.001, ANOSIM). The species richness and evenness indices were highest in surface water (Chao1; 920 ± 10) among sample groups and gradually decreased during the DW treatment process (DW production well; Chao1: 320 ± 20). Although the phylum Proteobacteria was omnipresent, its relative abundance was higher in sewage and industrial effluents (66–80%) than in surface water (55%). Phyla Firmicutes and Fusobacteria were only detected in sewage samples. Actinobacteria was more abundant in the surface water (≥13%) than in other groups (≤3%). Acidobacteria was more abundant in the DW treatment process (≥13%) than in others (≤2%). In total, the share of PHRB reads was higher in sewage and surface water than in the DW treatment samples. The seasonal effect in bacterial communities was observed only on surface water samples, with the lowest diversity during summer. Conclusions The low bacterial diversity and absence of PHRB read in the DW samples indicate AGR can produce biologically stable and microbiologically safe drinking water. Furthermore, the significantly different bacterial communities at the pollution sources compared to surface water and DW samples highlight the importance of effective wastewater treatment for protecting the environment and human health.

Sensor networks are increasingly being implemented for environmental monitoring and agriculture to provide spatially accurate and continuous environmental information and (near) real-time applications. These networks provide a large amount of data which poses challenges for ensuring data quality and extracting relevant information. In the present paper we describe a river basin scale wireless sensor network for agriculture and water monitoring. The network, called SoilWeather, is unique and the first of this type in Finland. The performance of the network is assessed from the user and maintainer perspectives, concentrating on data quality, network maintenance and applications. The results showed that the SoilWeather network has been functioning in a relatively reliable way, but also that the maintenance and data quality assurance by automatic algorithms and calibration samples requires a lot of effort, especially in continuous water monitoring over large areas. We see great benefits on sensor networks enabling continuous, real-time monitoring, while data quality control and maintenance efforts highlight the need for tight collaboration between sensor and sensor network owners to decrease costs and increase the quality of the sensor data in large scale applications.

Open data and models are becoming increasingly available, but there are not yet good methods and platforms to turn those into systematic evidence-based decision support. Unicorn will produce such an enviro­­nment based on existing theoretical and practical knowledge about decision support and models. This con­sortium possesses the necessary models, data, and skills to set up an environment and demonstrate its func­tionality and usefulness with several case studies related to the environmental issues, human health, and economy. The Unicorn environment will be built in a generic and systematic way so that it could even be­come an international standard for evidence-based decision support. Developing a technical environment or standard is not enough. Using the Unicorn environment is a large cul­­tural change for both researchers and decision makers, as the current decision support practices do not re­flect the principles of openness, criticism, or reuse. Therefore, this cultural change must be promoted by train­ing to use the environment, by informing the society about its possibilities, and solving a number of practi­cal and technical problems related to current practices in research institutes, ministries, and municipalities. We acknowledge these problems and offer solutions to them with an extensive interaction plan.

In deep ice-covered lakes with temperatures below 4 °C the heat flux from the bottom sediment results in a horizontal density gradient and a consequent flow along the bottom slope. Measurements in Lake Pääjärvi, Finland, show a stable temperature field where a heat gain through the bottom and a heat loss through the ice nearly balance each other. The circulation is thermal with low velocities (less than 1.5 cm s–1). We used the 3D hydrodynamic Princeton Ocean Model as a tool to simulate the water circulation and the temperature distribution under the ice. The model forcing was based on field temperature measurements. The model simulations suggest that in midwinter the velocity field of the upper water layers is anticyclonic while that of deep layers is cyclonic. Comparison with current measurements at one site showed good agreement between the modelled and observed results. On the basis of the modelled results it is possible to better understand the distributions of some micro-organisms and the accumulation of oxygen depleted waters in the deepest part of the lake.

Freshwater lakes are important in carbon cycling, especially in the boreal zone where many lakes are supersaturated with the greenhouse gas carbon dioxide (CO2) and emit it to the atmosphere, thus ventilating carbon originally fixed by the terrestrial system. The exchange of CO2 between water and the atmosphere is commonly estimated using simple wind-based parameterizations or models of gas transfer velocity (k). More complex surface renewal models, however, have been shown to yield more correct estimates of k in comparison with direct CO2 flux measurements. We incorporated four gas exchange models with different complexity into a vertical process-based physico-biochemical lake model, MyLake C, and assessed the performance and applicability of the alternative lake model versions to simulate air–water CO2 fluxes over a small boreal lake. None of the incorporated gas exchange models significantly outperformed the other models in the simulations in comparison to the measured near-surface CO2 concentrations or respective air–water CO2 fluxes calculated directly with the gas exchange models using measurement data as input. The use of more complex gas exchange models in the simulation, on the contrary, led to difficulties in obtaining a sufficient gain of CO2 in the water column and thus resulted in lower CO2 fluxes and water column CO2 concentrations compared to the respective measurement-based values. The inclusion of sophisticated and more correct models for air–water CO2 exchange in process-based lake models is crucial in efforts to properly assess lacustrine carbon budgets through model simulations in both single lakes and on a larger scale. However, finding higher estimates for both the internal and external sources of inorganic carbon in boreal lakes is important if improved knowledge of the magnitude of CO2 evasion from lakes is included in future studies on lake carbon budgets.

Freshwater lakes are important in carbon cycling, especially in the boreal zone where many lakes are supersaturated with the greenhouse gas carbon dioxide (CO.sub.2) and emit it to the atmosphere, thus ventilating carbon originally fixed by the terrestrial system. The exchange of CO.sub.2 between water and the atmosphere is commonly estimated using simple wind-based parameterizations or models of gas transfer velocity (k). More complex surface renewal models, however, have been shown to yield more correct estimates of k in comparison with direct CO.sub.2 flux measurements. We incorporated four gas exchange models with different complexity into a vertical process-based physico-biochemical lake model, MyLake C, and assessed the performance and applicability of the alternative lake model versions to simulate air-water CO.sub.2 fluxes over a small boreal lake. None of the incorporated gas exchange models significantly outperformed the other models in the simulations in comparison to the measured near-surface CO.sub.2 concentrations or respective air-water CO.sub.2 fluxes calculated directly with the gas exchange models using measurement data as input. The use of more complex gas exchange models in the simulation, on the contrary, led to difficulties in obtaining a sufficient gain of CO.sub.2 in the water column and thus resulted in lower CO.sub.2 fluxes and water column CO.sub.2 concentrations compared to the respective measurement-based values. The inclusion of sophisticated and more correct models for air-water CO.sub.2 exchange in process-based lake models is crucial in efforts to properly assess lacustrine carbon budgets through model simulations in both single lakes and on a larger scale. However, finding higher estimates for both the internal and external sources of inorganic carbon in boreal lakes is important if improved knowledge of the magnitude of CO.sub.2 evasion from lakes is included in future studies on lake carbon budgets.

Compared with sporadic conventional water sampling, continuous water-quality monitoring with optical sensors has improved our understanding of freshwater dynamics. The basic principle in photometric measurements is the incident light at a given wavelength that is either reflected, scattered, or transmitted in the body of water. Here, we discuss the transmittance measurements. The amount of transmittance is inversely proportional to the concentration of the substance measured. However, the transmittance is subject to interference, because it can be affected by factors other than the substance targeted in the water. In this study, interference with the UV/Vis sensor nitrate plus nitrite measurements caused by organic carbon was evaluated. Total or dissolved organic carbon as well as nitrate plus nitrite concentrations were measured in various boreal waters with two UV/Vis sensors (5-mm and 35-mm pathlengths), using conventional laboratory analysis results as references. Organic carbon increased the sensor nitrate plus nitrite results, not only in waters with high organic carbon concentrations, but also at the lower concentrations (< 10 mg C L −1 ) typical of boreal stream, river, and lake waters. Our results demonstrated that local calibration with multiple linear regression, including both nitrate plus nitrite and dissolved organic carbon, can correct the error caused by organic carbon. However, high-frequency optical sensors continue to be excellent tools for environmental monitoring when they are properly calibrated for the local water matrix.

Anthropogenic chemicals in surface water and groundwater cause concern especially when the water is used in drinking water production. Due to their continuous release or spill-over at waste water treatment plants, active pharmaceutical ingredients (APIs) are constantly present in aquatic environment and despite their low concentrations, APIs can still cause effects on the organisms. In the present study, Chemcatcher passive sampling was applied in surface water, surface water intake site, and groundwater observation wells to estimate whether the selected APIs are able to end up in drinking water supply through an artificial groundwater recharge system. The API concentrations measured in conventional wastewater, surface water, and groundwater grab samples were assessed with the results obtained with passive samplers. Out of the 25 APIs studied with passive sampling, four were observed in groundwater and 21 in surface water. This suggests that many anthropogenic APIs released to waste water proceed downstream and can be detectable in groundwater recharge. Chemcatcher passive samplers have previously been used in monitoring several harmful chemicals in surface and wastewaters, but the path of chemicals to groundwater has not been studied. This study provides novel information on the suitability of the Chemcatcher passive samplers for detecting APIs in groundwater wells.

Freshwater lakes are important in carbon cycling, especially in the boreal zone where many lakes are supersaturated with the greenhouse gas carbon dioxide (CO2) and emit it to the atmosphere, thus ventilating carbon originally fixed by the terrestrial system. The exchange of CO2 between water and the atmosphere is commonly estimated using simple wind-based parameterizations or models of gas transfer velocity (k). More complex surface renewal models, however, have been shown to yield more correct estimates of k in comparison with direct CO2 flux measurements. We incorporated four gas exchange models with different complexity into a vertical process-based physico-biochemical lake model, MyLake C, and assessed the performance and applicability of the alternative lake model versions to simulate air–water CO2 fluxes over a small boreal lake. None of the incorporated gas exchange models significantly outperformed the other models in the simulations in comparison to the measured near-surface CO2 concentrations or respective air–water CO2 fluxes calculated directly with the gas exchange models using measurement data as input. The use of more complex gas exchange models in the simulation, on the contrary, led to difficulties in obtaining a sufficient gain of CO2 in the water column and thus resulted in lower CO2 fluxes and water column CO2 concentrations compared to the respective measurement-based values. The inclusion of sophisticated and more correct models for air–water CO2 exchange in process-based lake models is crucial in efforts to properly assess lacustrine carbon budgets through model simulations in both single lakes and on a larger scale. However, finding higher estimates for both the internal and external sources of inorganic carbon in boreal lakes is important if improved knowledge of the magnitude of CO2 evasion from lakes is included in future studies on lake carbon budgets.