Intercomparison of measurements of bulk snow density and water equivalent of snow cover with snow core samplers: Instrumental bias and variability induced by observers

Manually collected snow data are often considered as ground truth for many applications such as climatological or hydrological studies. However, there are many sources of uncertainty that are not quantified in detail. For the determination of water equivalent of snow cover (SWE), different snow core samplers and scales are used, but they are all based on the same measurement principle. We conducted two field campaigns with 9 samplers commonly used in observational measurements and research in Europe and northern America to better quantify uncertainties when measuring depth, density and SWE with core samplers. During the first campaign, as a first approach to distinguish snow variability measured at the plot and at the point scale, repeated measurements were taken along two 20 m long snow pits. The results revealed a much higher variability of SWE at the plot scale (resulting from both natural variability and instrumental bias) compared to repeated measurements at the same spot (resulting mostly from error induced by observers or very small scale variability of snow depth). The exceptionally homogeneous snowpack found in the second campaign permitted to almost neglect the natural variability of the snowpack properties and focus on the separation between instrumental bias and error induced by observers. Reported uncertainties refer to a shallow, homogeneous tundra-taiga snowpack less than 1 m deep (loose, mostly recrystallised snow and no wind impact). Under such measurement conditions, the uncertainty in bulk snow density estimation is about 5% for an individual instrument and is close to 10% among different instruments. Results confirmed that instrumental bias exceeded both the natural variability and the error induced by observers, even in the case when observers were not familiar with a given snow core sampler.     

Water in garnet of garnetite (metarodingite) and eclogite from the Erzgebirge and the Lepontine Alps

Little is known about water in nominally anhydrous minerals of orogenic garnet peridotite and enclosed metabasic rocks. This study is focused on peridotite-hosted eclogite and garnetite (metarodingite) from the Erzgebirge (EG), Germany, and the Lepontine Alps (LA), Switzerland. Newly discovered, peridotite-hosted eclogite in the Erzgebirge occurs in the same ultra-high pressure (UHP) unit as gneiss-hosted coesite eclogite, from which it is petrologically indistinguishable. Garnet is present in all mafic and ultramafic high pressure (HP) rocks providing for an ideal proxy to compare the H₂O content of the different rock types. Garnet composition is very similar in EG and LA samples and depends on the rock type. Garnet from garnetite, compared to eclogite, contains more CaO (garnetite: 10.5–16.5 wt%; eclogite: 5–11 wt%) and is also characterized by an anomalous REE distribution. In contrast, the infrared (IR) spectra of garnet from both rock types reveal the same OH absorption bands that are also identical to those of previously studied peridotitic garnet from the same locations. Two groups of IR bands, SW I (3,650 ± 10 cm⁻¹) and SW II (3,570–3,630 cm⁻¹) are ascribed to structural hydroxyl (colloquially ‘water’). A third, broad band is present in about half of the analysed garnet domains and related to molecular water (MW) in submicroscopic fluid inclusions. The primary content of structural H₂O, preserved in garnet domains without fluid inclusions (and MW bands), varies systematically—depending on both the location and the rock type. Garnet from EG rocks contains more water compared to LA samples, and garnet from garnetite (EG: 121–241 wt.ppm H₂O; LA: 23–46 wt.ppm) hosts more water than eclogitic garnet (EG: 84 wt.ppm; LA: 4–11 wt.ppm). Higher contents of structural water (SW) are observed in domains with molecular water, in which the SW II band (being not restricted to HP conditions) is simultaneously enhanced. This implies that fluid influx during decompression not only led to fluid inclusions but also favoured the uptake of secondary SW. The results signify that garnet from all EG and LA samples was originally H₂O-undersaturated. Combining the data from eclogite, garnetite and previously studied peridotite, H₂O and CaO are positively correlated, pointing to the same degree of H₂O-undersaturation at peak metamorphism in all rock types. This ubiquitous water-deficiency cannot be reconciled with the derivation of any of these rocks from the lowermost part of the mantle wedge that was in contact with the subducting plate. This agrees with the previously inferred abyssal origin for part of the rocks from the LA (Cima di Gagnone). A similar origin has to be invoked for the Erzgebirge UHP unit. We suggest that all mafic and ultramafic rocks of this unit not only shared the same metamorphic evolution but also a common protolith origin, most probably on the ocean floor. This inference is supported by the presence of peridotite-hosted garnetite, representing metamorphosed rodingite.     

Subaquatic slope instabilities: The aftermath of river correction and artificial dumps in Lake Biel (Switzerland)

River engineering projects are developing rapidly across the globe, drastically modifying water courses and sediment transfer. Investigation of the impact of engineering works focuses usually on short-term impacts, thus a longer-term perspective is still missing on the effects that such projects have. The ‘Jura Water Corrections’ – the largest river engineering project ever undertaken in Switzerland – radically modified the hydrological system of Lake Biel in the 19th and 20th Century. The deviation of the Aare River into Lake Biel more than 140 years ago, in 1878, thus represents an ideal case study to investigate the long-term sedimentological impacts of such large-scale river rerouting. Sediment cores, along with new high-resolution bathymetric and seismic reflection datasets were acquired in Lake Biel to document the consequences of the Jura Water Corrections on the sedimentation history of Lake Biel. Numerous subaquatic mass transport structures were detected on all of the slopes of the lake. Notably, a relatively large mass transport complex (0·86 km²) was observed on the eastern shore, along the path of the Aare River intrusion. The large amount of sediment delivered by the Aare River since its deviation into the lake likely caused sediment overloading resulting in subaquatic mass transport. Alternatively, the dumping since 1963 in a subaquatic landfill of material excavated during the second phase of river engineering, when the channels flowing into and out of Lake Biel were widened and deepened, might have triggered the largest mass transport, dated to 1964 or 1965. Additional potential triggers include two nearby small earthquakes in 1964 and 1965 (M_W 3·9 and 3·2, respectively). The data for this study indicate that relatively large mass transports have become recurrent in Lake Biel following the deviation of the Aare River, thus modifying hazard frequency for the neighbouring communities and infrastructure.     

Configurations of community in flood risk management

ABSTRACT

Despite a notable increase in the literature on community resilience, the notion of ‘community’ remains underproblematised. This is evident within flood risk management (FRM) literature, in which the understanding and roles of communities may be acknowledged but seldom discussed in any detail. The purpose of the article is to demonstrate how community networks are configured by different actors, whose roles and responsibilities span spatial scales within the context of FRM. Accordingly, the authors analyse findings from semi-structured interviews, policy documents, and household surveys from two flood prone areas in Finnish Lapland. The analysis reveals that the ways in which authorities, civil society, and informal actors take on multiple roles are intertwined and form different types of networks. By implication, the configuration of community is fuzzy, elusive and situated, and not confined to a fixed spatiality. The authors discuss the implications of the complex nature of community for FRM specifically, and for community resilience more broadly. They conclude that an analysis of different actors across scales contributes to an understanding of the configuration of community, including community resilience, and how the meaning of community takes shape according to the differing aims of FRM in combination with differing geographical settings.     

The thermal maturity of sedimentary basins as revealed by magnetic mineralogy

The thermal evolution of sedimentary basins is usually constrained by maturity data, which is interpreted from Rock-Eval pyrolysis and vitrinite reflectance analytical results on field or boreholes samples. However, some thermal evolution models may be inaccurate due to the use of elevated maturities measured in samples collected within an undetected metamorphic contact aureole surrounding a magmatic intrusion. In this context, we investigate the maturity and magnetic mineralogy of 16 claystone samples from Disko-Svartenhuk Basin, part of the SE Baffin Bay volcanic margin. Samples were collected within thermal contact metamorphic aureoles near magma intrusions, as well as equivalent reference samples not affected by intrusions. Rock-Eval pyrolysis (T_max), and vitrinite reflectance (Ro) analysis were performed to assess the thermal maturity, which lies in the oil window when 435°C ≤ T_max ≤ 470°C and 0.6%–0.7% ≤ Ro ≤ 1.3%. In addition, we performed low- (<300K) and high-temperature (>300K) investigations of isothermal remanent magnetization to assess the magnetic mineralogy of the selected samples. The maturity results (0.37% ≤ Ro ≤ 2%, 22°C ≤ T_max ≤ 604°C) show a predominance of immature to early mature Type III organic matter, but do not reliably identify the contact aureole when compared to the reference samples. The magnetic assemblage of the immature samples consists of iron sulphide (greigite), goethite and oxidized or non-stoichiometric magnetite. The magnetic assemblage of the early mature to mature samples consists of stoichiometric magnetite and fine-grained pyrrhotite (<1 μm). These results document the disappearance of the iron sulphide (greigite) and increase in content of magnetite during normal burial. On the other hand, magnetite is interpreted to be the dominant magnetic mineral inside the contact aureole surrounding dyke/sill intrusions where palaeotemperatures indicate mature to over-mature state. Interestingly, the iron sulphide (greigite) is still detected in the contact aureole where palaeotemperatures exceeded 130°C. Therefore, the magnetic mineralogy is a sensitive method that can characterize normal burial history, as well as identify hidden metamorphic contact aureoles where the iron sulphide greigite is present at temperatures beyond its stability field.     

Boosting for Mineral Prospectivity Modeling: A New GIS Toolbox

With an increasing demand for raw materials, predictive models that support successful mineral exploration targeting are of great importance. We evaluated different machine learning techniques with an emphasis on boosting algorithms and implemented them in an ArcGIS toolbox. Performance was tested on an exploration dataset from the Iberian Pyrite Belt (IPB) with respect to accuracy, performance, stability, and robustness. Boosting algorithms are ensemble methods used in supervised learning for regression and classification. They combine weak classifiers, i.e., classifiers that perform slightly better than random guessing to obtain robust classifiers. Each time a weak learner is added; the learning set is reweighted to give more importance to misclassified samples. Our test area, the IPB, is one of the oldest mining districts in the world and hosts giant volcanic-hosted massive sulfide (VMS) deposits. The spatial density of ore deposits, as well as the size and tonnage, makes the area unique, and due to the high data availability and number of known deposits, well-suited for testing machine learning algorithms. We combined several geophysical datasets, as well as layers derived from geological maps as predictors of the presence or absence of VMS deposits. Boosting algorithms such as BrownBoost and Adaboost were tested and compared to Logistic Regression (LR), Random Forests (RF) and Support Vector machines (SVM) in several experiments. We found performance results relatively similar, especially to BrownBoost, which slightly outperformed LR and SVM with respective accuracies of 0.96 compared to 0.89 and 0.93. Data augmentation by perturbing deposit location led to a 7% improvement in results. Variations in the split ratio of training and test data led to a reduction in the accuracy of the prediction result with relative stability occurring at a critical point at around 26 training samples out of 130 total samples. When lower numbers of training data were introduced accuracy dropped significantly. In comparison with other machine learning methods, Adaboost is user-friendly due to relatively short training and prediction times, the low likelihood of overfitting and the reduced number of hyperparameters for optimization. Boosting algorithms gave high predictive accuracies, making them a potential data-driven alternative for regional scale and/or brownfields mineral exploration.

     

Hydrological trends and the evolution of catchment research in the Alptal valley,central Switzerland

When the observation of small headwater catchments in the pre-Alpine Alptal valley (central Switzerland) started in the late 1960s, the researchers were mainly interested in questions related to floods and forest management. Investigations of geomorphological processes in the steep torrent channels followed in the 1980s, along with detailed observations of biogeochemical and ecohydrological processes in individual forest stands. More recently, research in the Alptal has addressed the impacts of climate change on water supply and runoff generation. In this article, we describe, for the first time, the evolution of catchment research at Alptal, and present new analyses of long-term trends and short-term hydrologic behaviour. Hydrometeorological time series from the past 50 years show substantial interannual variability, but only minimal long-term trends, except for the ~2°C increase in mean annual air temperature over the 50-year period, and a corresponding shift towards earlier snowmelt. Similar to previous studies in larger Alpine catchments, the decadal variations in mean annual runoff in Alptal's small research catchments reflect the long-term variability in annual precipitation. In the Alptal valley, the most evident hydrological trends were observed in late spring and are related to the substantial change in the duration of the snow cover. Streamflow and water quality are highly variable within and between hydrological events, suggesting rapid shifts in flow pathways and mixing, as well as changing connectivity of runoff-generating areas. This overview illustrates how catchment research in the Alptal has evolved in response to changing societal concerns and emerging scientific questions.     

The information system of the French Peatland Observation Service: Service National d'Observation Tourbières – A valuable tool to assess the impact of global changes on the hydrology and biogeochemistry of temperate peatlands through long term monitoring

Mitigating and adapting to global changes requires a better understanding of the response of the Biosphere to these environmental variations. Human disturbances and their effects act in the long term (decades to centuries) and consequently, a similar time frame is needed to fully understand the hydrological and biogeochemical functioning of a natural system. To this end, the ‘Centre National de la Recherche Scientifique’ (CNRS) promotes and certifies long-term monitoring tools called national observation services or ‘Service National d'Observation’ (SNO) in a large range of hydrological and biogeochemical systems (e.g., cryosphere, catchments, aquifers). The SNO investigating peatlands, the SNO ‘Tourbières’, was certified in 2011 ( https://www.sno-tourbieres.cnrs.fr/ ). Peatlands are mostly found in the high latitudes of the northern hemisphere and French peatlands are located in the southern part of this area. Thus, they are located in environmental conditions that will occur in northern peatlands in coming decades or centuries and can be considered as sentinels. The SNO Tourbières is composed of four peatlands: La Guette (lowland central France), Landemarais (lowland oceanic western France), Frasne (upland continental eastern France) and Bernadouze (upland southern France). Thirty target variables are monitored to study the hydrological and biogeochemical functioning of the sites. They are grouped into four datasets: hydrology, fluvial export of organic matter, greenhouse gas fluxes and meteorology/soil physics. The data from all sites follow a common processing chain from the sensors to the public repository. The raw data are stored on an FTP server. After operator or automatic processing, data are stored in a database, from which a web application extracts the data to make them available ( https://data-snot.cnrs.fr/data-access/ ). Each year at least, an archive of each dataset is stored in Zenodo, with a digital object identifier (DOI) attribution ( https://zenodo.org/communities/sno_tourbieres_data/ ).     

Surface Reflectance Climate Data Records (CDRs) is a Reliable Landsat ETM+ Source to Study Chlorophyll Content in Pecan Orchards

We evaluated the relationships among three Landsat Enhanced Thematic Mapper (ETM+) datasets, top-of-atmosphere (TOA) reflectance, surface reflectance climate data records (surface reflectance-_CDR) and atmospherically corrected images using Fast Line-of-Sight atmospheric analysis of Spectral Hypercubes model (surface reflectance-_FLAASH) and their linkto pecan foliar chlorophyll content(chl-cont). Foliar chlorophyll content as determined with a SPAD meter, and remotely-sensed data were collected from two mature pecan orchards (one grown in a sandy loam and the other in clay loam soil) during the experimental period. Enhanced vegetation index derived from remotely sensed data was correlated to chl-cont. At both orchards, TOA reflectance was significantly lower than surface reflectance within the 550–2400 nm wavelength range. Reflectance from atmospherically corrected images (surface reflectance-_CDR and surface reflectance-_FLAASH) was similar in the shortwave infrared (SWIR: 1550–1750 and 2080–2350 nm) and statistically different in the visible (350–700 nm). Enhanced vegetation index derived from surface reflectance-_CDR and surface reflectance-_FLAASH had higher correlation with chl-cont than TOA. Accordingly, surface reflectance is an essential prerequisite for using Landsat ETM+  data and TOA reflectance could lead to miss-/or underestimate chl-cont in pecan orchards. Interestingly, the correlation comparisons (Williams t test) between surface reflectance-_CDR and chl-cont was statistically similar to the correlation between chl-cont and commercial atmospheric correction model. Overall, surface reflectance-_CDR, which is freely available from the earth explorer portal, is a reliable atmospherically corrected Landsat ETM+ image source to study foliar chlorophyll content in pecan orchards.     

Experimental calibration of vanadium partitioning and stable isotope fractionation between hydrous granitic melt and magnetite at 800 °C and 0.5 GPa

Vanadium has multiple oxidation states in silicate melts and minerals, a property that also promotes fractionation of its isotopes. As a result, vanadium isotopes vary during magmatic differentiation, and can be powerful indicators of redox processes at high temperatures if their partitioning behaviour can be determined. To quantify the partitioning and isotope fractionation factor of V between magnetite and melt, piston cylinder experiments were performed in which magnetite and a hydrous, haplogranitic melt were equilibrated at 800 °C and 0.5 GPa over a range of oxygen fugacities (\({f_{{{\text{O}}_{\text{2}}}}}\)), bracketing those of terrestrial magmas. Magnetite is isotopically light with respect to the coexisting melt, a tendency ascribed to the VI-fold V³⁺ and V⁴⁺ in magnetite, and a mixture of IV- and VI-fold V⁵⁺ and V⁴⁺ in the melt. The magnitude of the fractionation factor systematically increases with increasing log\({f_{{{\text{O}}_{\text{2}}}}}\) relative to the Fayalite–Magnetite–Quartz buffer (FMQ), from ?⁵¹V_mag-gl = ? 0.63?±?0.09‰ at FMQ ? 1 to ? 0.92?±?0.11‰ (SD) at ≈?FMQ?+?5, reflecting constant V³⁺/V⁴⁺ in magnetite but increasing V⁵⁺/V⁴⁺ in the melt with increasing log\({f_{{{\text{O}}_{\text{2}}}}}\). These first mineral-melt measurements of V isotope fractionation factors underline the importance of both oxidation state and co-ordination environment in controlling isotopic fractionation. The fractionation factors determined experimentally are in excellent agreement with those needed to explain natural isotope variations in magmatic suites. Furthermore, these experiments provide a useful framework in which to interpret vanadium isotope variations in natural rocks and magnetites, and may be used as a potential fingerprint the redox state of the magma from which they crystallise.