Turkey Lakes Watershed,Ontario, Canada: 40 years of interdisciplinary whole-ecosystem research

The Turkey Lakes Watershed (TLW) study is a federal, interdepartmental study established in 1979 to investigate the effects of acid rain on terrestrial and aquatic ecosystems. The 10.5 km² watershed, located in the Eastern Temperate Mixed Forest on the Canadian Shield, has been the site of multidisciplinary studies on biogeochemical and ecological processes conducted across plot to catchment scales. The whole-ecosystem investigative approach was adopted from the outset and has allowed research to evolve from its original (and continuing) acidification focus to include investigations on the effects of climate change, forest harvesting and other forest ecosystem perturbations. The extensive scientific and support infrastructure allows for collection of a comprehensive data record essential for understanding long-term environmental trends. Data include atmospheric deposition, meteorology, stream hydrology and chemistry, soil, pore and ground water properties, understory and overstory vegetation, lake and outflow physical and chemical properties, and aquatic macroinvertebrate and fish community composition and abundance. These data have contributed to over 400 published research papers and graduate theses. The watershed has also figured prominently in many continent-wide comparisons advancing fundamental watershed theory. The knowledge gained at TLW has influenced pollutant emission and natural resource management policies provincially, nationally and internationally.     

Evaluating the reliability of time series analysis to estimate variable riparian travel times by numerical groundwater modelling

The transition zones between rivers and adjacent riparian aquifers are locations of high biogeochemical activities that contribute to a removal of potentially hazardous substances in the aquatic system. The potential of the removal processes depends highly on subsurface water travel times, which can be determined by using the propagation of electrical conductivity (EC) signal from the river into the riparian aquifer. Although this method has been applied and verified in many studies, we observe possible limitations for the usage of EC fluctuation analysis. Our findings are based on EC time series analyses during storm events and artificial hydropeaks induced by watermill operations. Travel times derived by cross‐correlation analysis were compared with travel times calculated based on backward particle tracking of a calibrated transient numerical groundwater flow model. The cross‐correlation method produced only reasonable travel times for the artificial hydropeaks. In contrast, cross‐correlation analysis of the EC data during natural storm events resulted in implausibly negative or unrealistically low travel times for the bulk of the data sets. We conclude that the reason for this behaviour is, first, the low EC contrast between river and groundwater in connection with a strong damping of the infiltrating river EC signal into the subsurface during storm events. Second, the existence of old and less‐mineralized riparian water between the river and the monitoring well resulted in bank‐storage‐driven EC breakthrough curves with earlier arrival times and the subsequent estimation of implausible riparian travel times.     

Ultrasonic prediction of crack density using machine learning:A numerical investigation

Cracks are accounted as the most destructive discontinuity in rock, soil, and concrete. Enhancing our knowledge from their properties such as crack distribution, density, and/or aspect ratio is crucial in geo-systems. The most well-known mechanical parameter for such an evaluation is wave velocity through which one can qualitatively or quantitatively characterize the porous media. In small scales, such information is obtained using the ultrasonic pulse velocity(UPV) technique as a non-destructive test. In large-scale geo-systems, however, it is inverted from seismic data. In this paper, we take advantage of the recent advancements in machine learning(ML) for analyzing wave signals and predict rock properties such as crack density(CD) – the number of cracks per unit volume. To this end, we designed numerical models with different CDs and, using the rotated staggered finite-difference grid(RSG) technique, simulated wave propagation. Two ML networks, namely Convolutional Neural Networks(CNN) and Long Short-Term Memory(LSTM), are then used to predict CD values. Results show that, by selecting an optimum value for wavelength to crack length ratio, the accuracy of predictions of test data can reach R2> 96% with mean square error(MSE) < 25e-4(normalized values). Overall, we found that:(i) performance of both CNN and LSTM is highly promising,(ii) accuracy of the transmitted signals is slightly higher than the reflected signals,(iii) accuracy of 2D signals is marginally higher than 1D signals,(iv)accuracy of horizontal and vertical component signals are comparable,(v) accuracy of coda signals is less when the whole signals are used. Our results, thus, reveal that the ML methods can provide rapid solutions and estimations for crack density, without the necessity of further modeling.     

Remote Sensing of Biologically Reworked Sediments: A Laboratory Experiment

The present study aims to test the application of remote sensing to address the impact of bioturbation on physical sediment properties. Therefore, a laboratory experiment was developed, using microcosms mimicking a marine intertidal water–sediment interface to test the influence of Corophium volutator densities on sediment properties. Three main variables (water content, clay content, and mean grain size) were measured in three treatments (no Corophium, 5,000 Corophium per square meter, and 20,000 Corophium per square meter) after 16 days of bioturbation. Results obtained with conventional—destructive—techniques showed a significant increase of water content and a significant, but small decrease of clay content in the presence of Corophium. The remote sensing technique detected the impact of Corophium on water content as an increase in absorption at 1,450 nm, but was not able to detect the animal impact on clay content. This study demonstrates that remote sensing data could be significantly modified by bioturbation activities and that remote sensing can be applied in the laboratory to address the impact of bioturbation on sediment properties. This possibly opens new perspectives for long-term experiments concerning the role of bioturbation on sedimentary processes.     

Hazard assessment and runout analysis for an unstable rock slope above an industrial site in the Riviera valley, Switzerland

This paper presents a detailed field investigation and hazard assessment for an unstable rock slope above an industrial site in the Riviera valley in the Canton of Ticino in southern Switzerland. An integrated framework was used to counter issues of geological complexity and uncertainty, linking geological mapping and numerical modeling to develop an understanding of the acting instability mechanism to 2-D and 3-D dynamic runout simulations to predict the travel path and reach in the event of a large volume rockslide. The results from the numerical stability analysis provided a means to constrain failure volume estimates, whereas a series of calibration simulations were used to constrain the input parameters required by the rheological model used for the runout analysis. Results from this assessment suggest that current protection measures in place may not be sufficient, helping local authorities to define hazard zones and aid further development plans for the region.     

Biochemical biomarkers in adult female perch (Perca fluviatilis) in a chronically polluted gradient in the Stockholm recipient (Sweden)

A battery of biochemical biomarkers and the SigmaPCB concentration in adult female perch (Perca fluviatilis) verified an aquatic pollution gradient with the city of Stockholm (Sweden) as a point source of anthropogenic substances. The investigation included both an upstream gradient, 46 km westwards through Lake M?laren, and a downstream gradient, 84 km eastwards through the Stockholm archipelago. Besides the main gradient from Stockholm, there were strong indications of pollution coming from the Baltic Sea. The results indicated a severe pollution situation in central Stockholm, with poor health status of the perch, characterised by increased specific EROD activity in the liver, increased liver EROD somatic index, decreased AChE activity in the muscle, increased amount of DNA adducts in the liver, and a high concentration of biliary 1-pyrenol. In addition, laboratory exposure to common EROD inducers elicited an abnormal response, suggestive of chronic intoxication.     

Marine cold-air outbreaks in the future: an assessment of IPCC AR4 model results for the Northern Hemisphere

For many locations around the globe some of the most severe weather is associated with outbreaks of cold air over relatively warm oceans, referred to here as marine cold-air outbreaks (MCAOs). Drawing on empirical evidence, an MCAO indicator is defined here as the difference between the skin potential temperature, which over open ocean is the sea surface potential temperature, and the potential temperature at 700 hPa. Rare MCAOs are defined as the 95th percentile of this indicator. Climate model data that have been provided as part of the Intergovernmental Panel on Climate Change (IPCC) Assessment Report Four (AR4) were used to assess the models’ projections for the twenty-first century and their ability to represent the observed climatology of MCAOs. The ensemble average of the models broadly captures the observed spatial distribution of the strength of MCAOs. However, there are some significant differences between the models and observations, which are mainly associated with simulated biases of the underlying sea ice, such as excessive sea-ice extent over the Barents Sea in most of the models. The future changes of the strength of MCAOs vary significantly across the Northern Hemisphere. The largest projected weakening of MCAOs is over the Labrador Sea. Over the Nordic seas the main region of strong MCAOs will move north and weaken slightly as it moves away from the warm tongue of the Gulf Stream in the Norwegian Sea. Over the Sea of Japan there is projected to be only a small weakening of MCAOs. The implications of the results for mesoscale weather systems that are associated with MCAOs, namely polar lows and arctic fronts, are discussed.     

A strike‐slip core complex from the Najd fault system,Arabian shield

Metamorphic core complexes are usually thought to be associated with regional crustal extension and crustal thinning, where deep crustal material is exhumed along gently dipping normal shear zones oblique to the regional extension direction. We present a new mechanism whereby metamorphic core complexes can be exhumed along crustal‐scale strike‐slip fault systems that accommodated crustal shortening. The Qazaz metamorphic dome in Saudi Arabia was exhumed along a gently dipping jog in a crustal‐scale vertical strike‐slip fault zone that caused more than 25 km of exhumation of lower crustal rocks by 30 km of lateral motion. Subsequently, the complex was transected by a branch of the strike‐slip fault zone, and the segments were separated by another 30 km of lateral motion. Strike‐slip core complexes like the Qazaz Dome may be common and may have an important local effect on crustal strength.     

The simulation of European heat waves from an ensemble of regional climate models within the EURO-CORDEX project

The ability of a large ensemble of regional climate models to accurately simulate heat waves at the regional scale of Europe was evaluated. Within the EURO-CORDEX project, several state-of-the art models, including non-hydrostatic meso-scale models, were run for an extended time period (20 years) at high resolution (12 km), over a large domain allowing for the first time the simultaneous representation of atmospheric phenomena over a large range of spatial scales. Eight models were run in this configuration, and thirteen models were run at a classical resolution of 50 km. The models were driven with the same boundary conditions, the ERA-Interim re-analysis, and except for one simulation, no observations were assimilated in the inner domain. Results, which are compared with daily temperature and precipitation observations (ECA&D and E-OBS data sets) show that, even forced by the same re-analysis, the ensemble exhibits a large spread. A preliminary analysis of the sources of spread, using in particular simulations of the same model with different parameterizations, shows that the simulation of hot temperature is primarily sensitive to the convection and the microphysics schemes, which affect incoming energy and the Bowen ratio. Further, most models exhibit an overestimation of summertime temperature extremes in Mediterranean regions and an underestimation over Scandinavia. Even after bias removal, the simulated heat wave events were found to be too persistent, but a higher resolution reduced this deficiency. The amplitude of events as well as the variability beyond the 90th percentile threshold were found to be too strong in almost all simulations and increasing resolution did not generally improve this deficiency. Resolution increase was also shown to induce large-scale 90th percentile warming or cooling for some models, with beneficial or detrimental effects on the overall biases. Even though full causality cannot be established on the basis of this evaluation work, the drivers of such regional differences were shown to be linked to changes in precipitation due to resolution changes, affecting the energy partitioning. Finally, the inter-annual sequence of hot summers over central/southern Europe was found to be fairly well simulated in most experiments despite an overestimation of the number of hot days and of the variability. The accurate simulation of inter-annual variability for a few models is independent of the model bias. This indicates that internal variability of high summer temperatures should not play a major role in controlling inter-annual variability. Despite some improvements, especially along coastlines, the analyses conducted here did not allow us to generally conclude that a higher resolution is clearly beneficial for a correct representation of heat waves by regional climate models. Even though local-scale feedbacks should be better represented at high resolution, combinations of parameterizations have to be improved or adapted accordingly.