bluuebunny/crossref_metadata_2025 huggingface dataset:
Identifying Mixing Components by Natural Tracers in the Lake Hévíz System
Authors: Bidar Kahnamuei Saeed , Hegedűs-Csondor Katalin , Baják Petra , Horváth Ákos , Szieberth Dénes , Czuppon György , Vargha Márta , Izsák Bálint , Erőss Anita
Published: March 2024

One of the largest natural thermal lakes in the world, Lake Hévíz is located in the southwestern part of the Transdanubian Range’s karst system (Hungary). It is fed by springs with different temperatures, which are located in a cave beneath the lake. The mixing of cold and hot waters generates the lake’s sulphuric therapeutic water, and it is responsible for the cave formation at the bottom, resulting in the lake's unique ecosystem. The presented research aimed at the comprehensive geochemical characterization of waters in the wider surroundings of the lake (lake water, springs, observation, drinking water, and thermal water wells). Investigating the geochemical characteristics of water took on a novel perspective through the innovative application of radionuclides as natural tracers. Within the framework of this investigation, we utilized uranium, radium, and radon isotopes to identify the mixing of fluids and infer the mixing end members in the Hévíz karst system. Alpha spectrometry was applied on selectively adsorbing Nucfilm discs as an inventive approach to measure uranium and radium isotopes. Moreover, stable isotopic ratios of hydrogen and oxygen (δ2H and δ18O) were determined to supplement the information on waters with different origins. Hydrochemical water analysis for measuring the concentration of major ions and trace elements was carried out using ICP-MS, ion chromatography, and UV-Vis spectrophotometry. The inferred fluid end members and their compositions are anticipated to provide insightful information on the hydrogeological functioning of the Lake Hévíz karst system, which is indispensable in sustainable water resource management and understanding climate change's impact.  Keywords: Thermal lake; Hydrogeochemical characteristics; Mixing fluids; Radionuclides; Stable isotopes; ICP-MS, Nucfilm, Alpha spectroscopy
Basin-scale hydrological response to leaky wooden dam installation
Authors: Wolstenholme Joshua , Skinner Christopher , Milan David , Thomas Robert , Parsons Daniel
Published: March 2024

Leaky wooden dams are commonly incorporated into rivers as part of restoration efforts to increase channel roughness and force geomorphic complexity, slowing the flow in the headwaters and aiming to desynchronise flows to reduce downstream flood risk. These structures are (dis)connectivity agents, working to decrease longitudinal connectivity whilst simultaneously increasing floodplain connectivity and encouraging water storage.Most numerical modelling of leaky wooden dams at the basin scale does not consider sediment transport at spatial resolutions fine enough to appropriately represent the dams as individual features. Due to the paucity of both spatially- and temporally-distributed sediment transport data, there is also a high level of uncertainty regarding the influence of leaky wooden dams on basin hydrology over time, yet it is important that we consider the geomorphological influence of these structures and how their evolution influences flood hazard, particularly given that extreme storms are becoming increasingly common.This study implements a heuristic behavioural approach within the landscape evolution model CAESAR-Lisflood to assess the broad influence of leaky wooden dams on a 32 km2 prototype catchment with a mixture of first, second and third order streams. A 20-year spatially-distributed modelled rainfall time series capable of representing convective storms (2020–2040 obtained from the 2018 UK Climate Projections) was used to drive the hydrology across a suite of simulations where leaky wooden dam location in the river network was systematically varied.Installing leaky wooden dams only on first order streams desynchronised flow and reduced downstream flood peaks by up to 50% whilst retaining the greatest volume of water in the catchment when compared to other stream order combinations. Conversely, installing leaky wooden dams on only third order streams increased peak discharge by over 10% for 22% of storm events owing to the presence of fewer structures and therefore reduced opportunity for desynchronisation of peak flows from the various sub-catchments. Most importantly we detail how storm sequencing, and the capacity of the active channel, plays an important role in exacerbating flood risk, with frequent, yet relatively minor, storms increasing peak discharge despite the presence of leaky wooden dams. As such where leaky dam interventions are installed plays a critical role in their efficacy in mitigating flood peaks and should be given more consideration by practitioners.
Multidecadal to multicentennial variability in Holocene transient simulations 
Authors: Braconnot Pascale , Marti Olivier
Published: March 2024

Transient Holocene climate simulations with state-of-the-art Earth system models offers new opportunities to investigate the relationship between multidecadal to multicentennial variability, the long-term climate trends, and interannual to decadal variability (Braconnot et al. GRL, 2019). However, multidecadal to multicentennial variability is still poorly known, both because it is difficult to properly extract from proxy records and because it is at the limit of what can actually be done with Earth System models. In addition, the different feedbacks from ocean or land-surface properties that can shape its characteristics are still poorly understood. Different climate models seem to provide different centennial variability patterns between the different ocean basins that reflect either the chaotic nature of the climate system or a poor representation of these variability scales. In this presentation, we will consider new mid-to-late Holocene simulations with the IPSL Earth System model, one of which includes interactive dynamical vegetation. We will first investigate the characteristics of multidecadal to multicentenial variability in these new simulations, with reference to recent publications comparing different transient Holocene simulations and addressing temperature variability scales, the thermohaline circulation, or Atlantic Ocean patterns leading to a reduction of the African monsoon interannual variability. We will also focus on key variability events that appear in the simulations and have a substantial impact on rapid changes in the African monsoon or on Northern Europe climate and land surface conditions (snow, soil moisture or vegetation). This opens the way to new research directions as part of the Paleoclimate Modeling Intercomparison Project.
High-velocity frictional behavior and microstructure evolution of quartz-bearing dolomite fault gouge
Authors: Huang Jianhua , Zhang Bo , Zou Junjie , He Honglin , Dang Jiaxiang , Zhang Jinjiang
Published: March 2024

        Abundant cherts (nodules and bands) were discontinuously hosted by dolostones of the Mesoproterozoic group Strata (∼1.5 Ga) in the Shanxi graben system, North China, where earthquakes are common. Measurements of the shear strength and stability of granular quartz reveal that quartz is a typical tectosilicate which exhibits high frictional strength and velocity-weakening properties. Conversely, dolomite is usually frictionally weak but velocity strengthening. The two minerals also behave differently during coseismic slip. Due to the high temperature generated by frictional heating, the thermal decomposition of dolomite usually results in calcite, periclase nanoparticles and carbon dioxide. However, quartz melts by friction at high temperatures. In order to investigate the role of quartz in dolomite fault rock during the process of coseismic slip, high velocity shear experiments were conducted on the quartz-bearing dolomite fault gouge taken from Yuguang Basin South Margin Fault (YBSMF), northeast of the Shanxi graben system. Also, we carried out high velocity experiments with the synthetic quartz-dolomite gouge with different mass ratio. For a slip velocity ≥ 0.1 m/s and normal stresses from 1.0 to 1.5 MPa, the friction values of the gouge decrease exponentially from a peak value of more than 0.5 to a steady-state value from 0.1 to 0.4. This high-velocity weakening feature was observed in the synthetic quartz-dolomite gouge as well as in the YBSMF gouge. With the increase of quartz content, the slip weakening distance (Dw) increases from 4.27 to 13.24 m, and the steady-state friction coefficient increases from 0.2 to 0.4 at 1.0 MPa normal stress and 1.0 m/s slip velocity. The textures of the gouge are characterized by grain comminution, R shear planes and localized deformation zone in the friction weakening stage. The slip surfaces are characterized by mirror-like smooth surface and nanoparticle aggregates. The theoretical calculation results show that the temperature inside the gauge layer did not exceed 300 °C during the experiments. However, the microstructures present that the dolomite experienced thermal decomposition, indicating that the temperature at the asperity exceeds 550 ℃. We suggest that thermal decomposition together with flash heating may lead to the slip-weakening behavior of quartz-bearing dolomite gauge, and the addition of quartz will increase of the strength of the dolomite gouge.
Deep Learning for Spatially Distributed Rainfall–Runoff Modeling
Authors: Gauch Martin , Kratzert Frederik , Dube Vusumuzi , Gilon Oren , Klotz Daniel , Metzger Asher , Nearing Grey , Ofori Florence , Shalev Guy , Shenzis Shlomo , Tekalign Tadele , Weitzner Dana , Zlydenko Oleg , Cohen Deborah
Published: March 2024

Deep learning approaches have emerged as the state of the art for rainfall–runoff modeling. Yet—until now—the best-performing models have typically been used with inputs that are averaged across possibly large catchment areas, modeling each (sub-)basin independently. This lumped modeling approach is in contrast to reality, where rivers form networks of connected subbasins. This discrepancy limits our ability to accurately and interpretably predict certain types of rivers. Here, we present recent work to build graph-based deep learning models that explicitly account for this network structure. These models promise to unlock improvements in both the quality and interpretability of predictions:Catchment size: Lumped models lack information about spatial heterogeneity, i.e., they do not know where inside a basin events (such as precipitation) occur. This makes it hard to model large basins, especially at high temporal resolution. Spatially distributed models can explicitly learn to account for travel times between subbasins inside a larger catchment, which also allows to analyze runoff generation separately from routing behavior.Data assimilation: In lumped models, it is hard to include (real-time) measurements from upstream river sections that could improve predictions at downstream locations. In a graph-based model of connected subbasins, any downstream prediction can benefit from upstream information that is propagated along the river network.Human intervention: It is unclear how to explicitly represent human water extraction, reservoirs, or dams in lumped models. Graph-based models provide more flexibility, as we can account for the spatial location of human interventions explicitly in the graph structure and learn to represent their influence on runoff.In this work, we compare different types of spatially distributed deep learning models with lumped deep learning models and traditional physics-based hydrologic modeling and routing approaches on >600 gauges of the LamaH dataset [1].[1] Klingler, C., Schulz, K., and Herrnegger, M.: LamaH-CE: LArge-SaMple DAta for Hydrology and Environmental Sciences for Central Europe, Earth Syst. Sci. Data, 13, 2021.
Global impacts of an extreme Solar Particle Event under different geomagnetic field strengths
Authors: Arsenovic Pavle , Rozanov Eugene , Usoskin Ilya , Turney Chris , Sukhodolov Timofei , McCracken Ken , Friedel Marina , Anet Julien , Simic Stana , Maliniemi Ville , Egorova Tatiana , Korte Monika , Rieder Harald , Cooper Alan , Peter Thomas
Published: March 2024

Solar particle events (SPEs) are short-lived bursts of high-energy particles from the solar atmosphere and are widely recognized as posing significant economic risks to modern society. Most SPEs are relatively weak and have minor impacts on the Earth’s environment but historic records contain much stronger SPEs which have the potential to alter atmospheric chemistry, impacting climate and biological life. The impacts of such strong SPEs would be far more severe when the Earth’s protective geomagnetic field weakened, such as during past geomagnetic excursions or reversals. Here we model the impacts of an extreme SPE under different geomagnetic field strengths, focusing on changes in atmospheric chemistry and surface radiation using the atmosphere-ocean-chemistry-climate model SOCOL3-MPIOM and the radiation transfer model LibRadtran. Under current geomagnetic conditions, an extreme SPE would increase NOx concentrations in the polar stratosphere and mesosphere, causing reductions in extratropical stratospheric ozone lasting for about a year. In contrast, with no geomagnetic field there would be a substantial increase in NOx throughout the entire atmosphere, resulting in severe stratospheric ozone depletion for several years. The resulting ground-level UV radiation would remain elevated for up to six years, leading to increases in UV index up to 20-25% and solar-induced DNA damage rates by 40-50%. The potential evolutionary impacts of past extreme SPEs remains an important question, while the risks they pose to human health in modern conditions continue to be underestimated.
Mid-Holocene environmental change in the Central Highlands of Madagascar: pre- and post-human settlement
Authors: Razafimanantsoa Andriantsilavo Hery Isandratana , Bond William , Gillson Lindsey
Published: March 2024

The climate in the tropic is favourable for forest development and the presence of open and mosaic ecosystems in this region lead to confusion and controversies. The Central Highlands of Madagascar is dominated by a matrix of grassland with forest patches, but whether these open ecosystems are ancient or anthropogenically derived is still scientifically debated. Understanding the landscape history including vegetation history and its drivers of change is therefore required to identify the nature and origin of the vegetation particularly prior to and after human settlement to inform appropriate conservation and management plans in the region. Here we provide a high-resolution environmental reconstruction of the last 6300 years from a sediment core collected at a lake called Dangovavy from the Central Highlands. Pollen and stable carbon isotopes were used to reconstruct vegetation history, while charcoal and coprophilous spores were used for fire frequency and herbivory activities, respectively. The data showed that open and mosaic ecosystems comprising forest patches of variable extent in a matrix of open montane grassland and ericoid shrubland occupied the area surrounding the lake from at least 6000 years ago, i.e. 4000 years before human settlement suggested around 2 cal. ka BP. Variations in forest extent and montane possibly C3–dominated grassland were recorded until 1 cal. ka BP., associated with fluctuations in fire, herbivory and rainfall. However, an expansion of the grassland ecosystem supported by C4 plant dominance, as shown in the stable carbon isotopes (δ13C) results, was recorded in the last millennium. This change was also associated with highly increasing fire frequency and herbivory activities most likely linked to human influence. Based on these findings, the natural presence of open and mosaic ecosystems in the Central Highlands of Madagascar should be considered, as well as their validity as conservation targets other than closed forests.
What can we learn from magnetic surveys at different scales? Geological insight from mineral to airborne surveys in the Bjerkreim-Sokndal Layer Intrusion, Norway
Authors: McEnroe Suzanne , Lee Madeline , Madriz Yuleika , Gloaguen Richard , Pastore Zeudia , Lelièvre Peter , Church Nathan
Published: March 2024

Multiple magnetic surveys, including fixed-wing, helicopter-borne, uncrewed aerial vehicle (UAV), and ground magnetics have been acquired over parts of the Bjerkreim-Sokndal layered intrusion (BKS) in Rogaland, Norway. The Proterozoic 230 km2 Bjerkreim-Sokndal layered complex intrudes into anorthosites and hosts recurrent megacyclic units (MCU) with varying cumulus and critical minerals. Some MCUs are associated with strong magnetic remanence, resulting in Koenignsberger ratios (Q ratio) over 5 and anomalies of 12 000 nT below background.  A comparative analysis of these surveys over the Bjerkreim Lobe provide insights into what features can be mapped at different scales. Here we focus on new geological details provided by UAV, ground, and mineral scale surveys.  A UAV can typically operate at a maximum altitude of 150 m above terrain to a minimum of tens- of centimeters in ideal conditions. Thus, UAV magnetic surveys are optimal for understanding the change of a magnetic anomaly with varying source-separation through multiple flight altitudes. Survey altitudes by UAVs overlap with the source-sensor separation of ground and low-altitude crewed flights, therefore allowing a comparative analysis.In 2023, the Norwegian University of Science and Technology and Helmholtz Institute Freiberg acquired coincident magnetic survey grids by UAV and ground magnetometer over key sites in the Bjerkreim lobe. Here we compare results of crewed-, uncrewed-, and ground-based data collected over the eastern margin of the Bjerkreim lobe and assess how these impact subsequent geologic interpretations. The petrophysical database for the survey area also contains > 1500 previously collected samples in combination with surface geometry information. This database in combination with the extensive lateral magnetic survey data at various sensor heights and other available complementary geophysics, including gravity, provide excellent parameters and constraints for forward modelling and inversions.In the Bjerkreim lobe two MCU have significant magnetic remanence where anomalies are several thousand nT below background due to natural remanent magnetizations that are typically > 15 A/m. Therefore, an additional focus is on understanding the nature of the magnetic mineralogy using high-resolution scanning magnetic microscopy. These large amplitude magnetic anomalies may also cause logistical challenges for both airborne- and ground magnetic surveying. UAVs employ onboard magnetometer for navigation and attitude corrections which can be impacted by these large magnetic gradients. Similarly, significant noise or sensor drop-outs when the sensor’s dead zone is aligned with these large, often steep, magnetic gradients.
Halokinetic-related Dolomitization in the Middle Eocene Carbonates, Saudi Arabia
Authors: Abdullahi Misbahu , Herlambang Adhipa , Koeshidayatullah Ardiansyah
Published: March 2024

Salt movement influenced the eastern part of the Arabian platform during the Eocene time. The halokinesis was not only important for creating hydrocarbon trap but also controlling dolomitization via thermal convection of fluid and provision of pressure gradient. Previous works on mid-Eocene dolomites of the Arabian platform proposed various models as the mechanisms for the genesis of the dolomite. However, most did not consider the impact of the halokinesis in building their predictive mechanisms. To contribute to this knowledge gap, integrated mineralogical, petrographic, chemical, and stable isotope analyses were employed on Mid-late Eocene samples taken from shallow cores. Core descriptions revealed two dolomite types: an upper light grey, coarse, indurated dolomite (Type I) and a bottom dark grey, more sucrosic but less indurated dolomite (Type II). Petrographic results showed pervasive, fabric non-selective and non-mimetic dolomites with dominant euhedral-subhedral (idiotopic-hypidiotopic mosaic) fabric in Type II dolomite and dominant subhedral in Type I. Geochemical analyses indicated that Type I dolomite is near-stoichiometric, well-ordered, and low in Sr, while Type II is non-stoichiometric, poorly ordered, and high in Sr content. Both dolomite types exhibit lower Fe (av.5238ppm) and Sr (av.823ppm) values compared to the associated limestones but comparable Mn (av.261ppm=dolomite and av.273ppm=limestone). Both the dolomites and the adjacent limestones have tight clusters of δ13C value ranges of between 0.89 and 1.83‰ but a slightly wider range of δ18O values of between -2.59 and 0.95‰ for the dolomites and -3.34 to +0.36‰ for the limestone. The dolomite isotopic and paleotemperature (av.32.8°C) values are comparable to the Eocene marine water values with very little variation. Thus, contrary to previous interpretations involving meteoric mixing or evaporation of the seawater, we propose that the dolomite originated from seawater, especially since there is an absence of evaporites throughout the core, but slightly modified by salt diapir-driven convection. The absence of deep burial features, co-enrichment of Sr and Fe-Mn elements, and low paleotemperatures of the studied dolomites suggest early dolomitization at near-surface and sub-oxic condition. Hence, our work provides a new understanding of dolomitization in shallow carbonate platforms that are underlain by deep-seated salt diapirs.
Improved geodetic datum realization based on simulation studies for co-located SLR-VLBI stations
Authors: Najder Joanna , Kehm Alexander , Bloßfeld Mathis , Sośnica Krzysztof , Glomsda Matthias
Published: March 2024

The International Terrestrial Reference System is realised in the form of multi-year reference frames such as the International Terrestrial Reference Frame (ITRF) or in the form of epoch reference frames relying on short observation time spans up to several weeks. The realisation is based on the combination of space-geodetic techniques, namely the global navigation satellite systems (GNSS), satellite laser ranging (SLR), very long baseline interferometry (VLBI) and Doppler orbitography and radiopositioning integrated by satellite (DORIS). In some ITRF and epoch reference frame solutions, SLR and VLBI are responsible for realising the datum parameters origin (only by SLR) and the scale, while the orientation of the network with respect to the Earth’s body is maintained by a mathematical constraint. The integration of the techniques is achieved by introduction of local ties (LTs) at co-located sites, i.e., by ground-based measurements of difference vectors between the technique-specific reference points. High accuracy of current LTs between techniques and the establishment of new co-location sites are necessary to provide (and further improve) a reliable realisation of the geodetic datum. Co-location sites with the SLR technique are of particular significance as this is the only technique that enables the realisation of a terrestrial reference frame origin with a high level of accuracy. As previous studies demonstrate, the performance of the observational networks has a significant impact on the accuracy and stability of the corresponding datum realisation, especially for epoch reference frames.This study aims to examine how improving the performance of the existing network of co-located SLR stations could affect the quality of determined datum parameters. The considered simulation scenarios study the performance of SLR stations co-located with the VLBI technique and improve the performance of those that do not meet the standards set by the International Laser Ranging Service (ILRS). Moreover, it is examined how significant the improvement of the datum parameters is in the case of extending the SLR network with stations located nearby existing VLBI telescopes (due to a ‘better’ datum transfer via a higher number of local ties).
The stratigraphic and orogenic response to the Middle Miocene Climatic Optimum in the southern Central Andes
Authors: George Sarah W.M. , Carrapa Barbara , DeCelles Peter G. , Jepson Gilby , Nadoya Hamida , Tabor Clay , Howlett Caden J. , Ronemus Chance B. , Clementz Mark T. , Schoenbohm Lindsay
Published: March 2024

Changes in precipitation can drive major shifts in stratigraphy and fold-thrust belt behavior. We investigate the stratigraphic and orogenic response to pronounced climatic warming during the Middle Miocene Climatic Optimum (ca. 17-14 Ma) in the southern Central Andes.  New and compiled stratigraphic and geochronologic data come from depocenters at ~25-35°S; these basins would have occupied both high and low elevation positions during the middle Miocene. Regionally ubiquitous eolianite deposition from ca. 22-17 Ma supports arid conditions on the eastern flank of the Central Andes preceding the Middle Miocene Climatic Optimum. Eolian facies are replaced by fluvial-lacustrine strata near the onset of the Middle Miocene Climatic Optimum over 1000 km along-strike. These results support a change from arid to more seasonal and humid conditions during the Middle Miocene Climatic Optimum. New climate models also support increased seasonality and moisture availability on the eastern flank of the Andes during the Middle Miocene Climatic Optimum, which we attribute to intensification of the South American Monsoon. We compare our results with published sequentially restored, regional cross-sections to explore linkages between the climatic shift and orogenic growth. A more seasonal climate should drive increased erosion, which in turn should drive the wedge into sub-critical state as predicted by critical taper theory.
Whistler-mode quasiperiodic emissions and magnetospheric line radiation: Fine inner structure
Authors: Němec František , Santolík Ondřej , Manninen Jyrki , Martinez-Calderon Claudia , Shiokawa Kazuo , Hospodarsky George B. , Kurth William S.
Published: March 2024

The intensity of magnetospheric whistler-mode waves at frequencies of a few kilohertz sometimes exhibits nearly periodic temporal or frequency modulation. Events exhibiting temporal modulation are typically referred to as quasiperiodic (QP) emissions, while those with frequency modulation are commonly known as magnetospheric line radiation (MLR). Although these events are rather routinely observed both by spacecraft and ground-based instruments, their exact formation mechanism is still not fully understood.We use high-resolution burst mode data, measured by the Van Allen Probes spacecraft in the equatorial region at larger radial distances, by the low-altitude DEMETER spacecraft, and by the Kannuslehto and PWING ground-based instruments, to demonstrate and investigate the fine inner structure of these events. We show that such a fine inner structure is often present for both QP and MLR events. Detailed wave propagation and timing analysis reveals that it corresponds to the wave bouncing between the hemispheres. We discuss the possible implications of these observations for understanding the event formation mechanisms.
Diversifying maize rotation with industrial crops can improve maize yield, soil nutrient stocks, and nitrate leaching losses depending on time since adoption and crop species
Authors: Zong Mingming , Manevski Kiril , Liang Zhi , Abalos Diego , Jabloun Mohamed , Lærke Poul Erik , Jørgensen Uffe
Published: March 2024

Maize (Zea mays L.) is a major crop worldwide, commonly used as monoculture and with high nitrate leaching losses. Diversified maize rotations can improve the environmental problems of maize monoculture without reducing yields and soil nutrients. Previous research focused on maize-legume or maize-cereal rotations, with limited exploration of rotations with industrial crops for biorefining. Furthermore, long-term field trials are rare, hindering our understanding of the crop performance and nutrient dynamics over time. In a four-year rotation system of maize, hemp (Cannabis sativa L.), beet (Beta vulgaris L.), and triticale (Triticosecale) established in 2012 on a sandy soil in Denmark, quadruplicated for maize to appear each year, we examined dry matter yield, yield stability, biomass nitrogen (N) and biomass N stability of maize in rotation compared to monoculture across two rotation cycles. We also quantified nitrate leaching, soil carbon (C) and N stocks in the root zone of 0-100 cm. Moreover, the period between the main crops was covered with “secondary crops”- winter rye (Secale cereale L.), winter rape (Brassica napus L.), grass/clover (Festuca rubra L. – Trifolium repens L.). The results showed that in the initial four years, the aboveground biomass yield of maize in rotation (15.5 Mg ha-1) was significantly lower (by 7%) than that in monoculture (16.6 Mg ha-1), but this difference disappeared in the following four years (17 and 16.5 Mg ha-1). The maize biomass N yield in rotation (194.5 kg ha-1) was similar to that in monoculture (196.6 kg ha-1) in the first cycle and was significantly higher (by 8%) in the second cycle (195.5 and 165.7 kg ha-1). Nitrate leaching showed interannual variability affected by double-cropping, being almost halved by the diverse rotation compared to the monoculture at the start of the rotation, but increasing at the onset of the second cycle when the preceding winter rape did not survive in the winter. Also, winter rye following maize reduced nitrate leaching, except when the preceding secondary crop was grass-clover or poorly thriving winter rape. During the whole period, the rotation system can increase both soil C and N stocks. This study shows that several of the benefits of diverse crop rotations in comparison to monoculture require several years to take place, and that the management of the secondary crops is particularly vital for reducing nitrateleaching.
Unveiling RISICO 2024: Enhancing Wildfire Forecasting through Cutting-Edge Updates
Authors: Perello Nicolò , Trucchia Andrea , Meschi Giorgio , D'Andrea Mirko , Degli Esposti Silvia , Fiorucci Paolo
Published: March 2024

The socio-economic changes over recent decades, marked by rural abandonment and fuel accumulation, coupled with the impact of climate change altering spatio-temporal weather patterns, have created conditions conducive to potential extreme wildfire events. Numerous wildfire management systems have thus faced significant challenges, leading to an additional push to develop or improve decision-support tools. Forest Fire Danger Rating models have been widely used by wildfire management systems in recent decades, aiding in daily operations planning and the production of fire bulletins.Since the year 2000, independent research programs conducted by the Liguria Region in Italy, and subsequently by the Italian Civil Protection, have led to the creation of the Forest Fire Danger Rating system known as RISICO. The system incorporates meteorological observations and forecasts from Limited Area Models, utilizing vegetation cover and topography as additional inputs to enhance its capabilities. The system is currently adopted at the national level in Italy by the Civil Protection system (Dipartimento della Protezione Civile), supporting the production of the national daily fire danger bulletin, and by several regional authorities.Over the past year, significant efforts have been made to upgrade the model. Specifically, a new fuel map based on fire susceptibility obtained through Machine Learning techniques has been proposed. This new approach allows for the structured integration of wildfire susceptibility information within the assessment of wildfire danger. Given the importance RISICO places on information about fuel classes, this approach allows a focus on fuel conditions that, when combined with specific meteorological conditions, can lead to extreme wildfire events. Furthermore, the Fine Fuel Moisture component of RISICO has been modified in its dynamics and calibrated using observed data from fuel sticks. This modification aims to better identify prolonged conditions of dry fuel that facilitate the ignition and spread of fires. Finally, the Rate of Spread model has been enhanced through the integration of the PROPAGATOR wildfire spread model's approach, with the goal of providing a more accurate description of the interaction between wind and topography.The updated model was subsequently validated using fires that occurred in Italy from 2007 to 2022 and compared with the model's performance before the modifications. The results demonstrate an improvement in the model's ability to identify situations particularly dangerous for fire ignition and spread. The updated model, therefore, enhances the prediction of wildfire danger, providing scientific support in the decision-making process and promoting effective wildfire management.
Investigating the Atmospheric Dispersion of Microplastic Particles - A Model Study
Authors: Faust Matthias , Schrödner Roland
Published: March 2024

Widespread contamination of several environmental compartments by micro and nano plastic particles has been documented globally, extending even to rural regions. The airborne transport of these particles is a recognised phenomenon; however, the intricacies of this atmospheric pathway remain poorly understood. In this study, we employ the COSMO-Itpas model system, enabling the simulation of Lagrangian transport for individual particles within the turbulent regime of the atmospheric boundary layer. This modelling technique facilitates the calculation of thousands of trajectories, providing valuable insights into the connectivity between potential sources of plastic particles such as roads, agricultural activities, and water bodies and the observation sites where particles may be detected. Our pilot study focuses on the atmospheric pathway of idealised microplastic particles in central Germany, aiming to discern potential sources and assess their significance. By utilising the COSMO-Itpas model system, we aim to better understand the atmospheric dispersion of microplastics.
Application of K-means classification for extraction of atmospheric synoptic conditions leading to the high-frequency sea level extremes of the Adriatic Sea
Authors: Ruić Krešimir , Šepić Jadranka , Vojković Marin
Published: March 2024

Sea-level extremes represent a great danger to coastal infrastructure and a daily threat to people living near the coast. These extremes are predicted to become more frequent in the coming years and decades, mostly due to mean sea-level rise. Knowledge of the underlying principles that drive these events is, thus, of greater importance than ever. Our analysis focuses on events of high-frequency sea-level extremes (extremes at periods shorter than 2 hours). Extreme events were extracted from sea level data series measured at six Adriatic Sea tide gauge records. Series lengths were from 16 to 17.5 years. The sea-level data series were split into a training set and a testing set. Splitting was done so that approximately 80% of the series were used for the training and remaining 20% for the testing. K-means classification was then used to associate extremes events of the training period with atmospheric synoptic conditions, represented with the synoptic variables downloaded from the ERA5 reanalysis. The atmospheric variables considered were the ones found by earlier research to be the most important when it comes to generation of intense high-frequency sea-level oscillations. These variables are: (i) temperature at 850 hPa, (ii) mean sea-level pressure and wind at 10 m and (iii) geopotential at 500 hPa. K-means classification was used to find prevailing clusters related to extremes at each of the six tide gauges. After that, the same synoptic variables were downloaded for each day of the testing period. To each tide gauges, and to each day of the testing period, a cluster, previously defined for the training period, was assigned. The idea was to check whether days of known extremes will be correctly clustered. The goodness of the approximations was determined by estimating the distance of the synoptic maps from the clusters. The results show that the testing period days with extremes have a smaller distance from the clusters than random days indicating that there is a potential for prediction of these events.
Lithium geochemical traceability: development of a multi-criteria approach using on-site and laboratory technologies for the implementation of a battery digital product passeport
Authors: Moradell-Casellas Alban , Desaulty Anne-Marie , Monfort-Climent Daniel , Perret Sebastien , Guerrot Catherine , Kloppmann Wolfram , Lafaurie Nicolas , Gilardi Nicolas , Delchini Sylvain , Maubec Nicolas , dezes Maria
Published: March 2024

Transition from fossil fuels to renewable energies is key to reduce human CO2 emissions, in order to cope global warming. As well as the need of technological progress, this raise the needs for metal resources. Some commodities are likely to experience very strong growth of their demand over the coming decades such as Lithium (Li), Aluminum (Al), Cobalt (Co), Nickel (Ni), Copper (Cu), and Rare Earth Elements (“REE”), due to their uses in “green” energy technologies.The EU-funded “MADITRACE” project aim for the development of traceability methods and certification systems for four critical raw material (CMR): lithium, graphite, cobalt and REEs, in order to integrate sustainable provenance of materials into a Digital Product Passport (DPP) for batteries and vehicles. In the particular case of lithium, a previous study has shown that the deposit type -‘Hard rock’ or Salar- origin of a lithium material can be tracked through the supply chain up to the battery using lithium isotopic analysis1. Nevertheless, some processes can affect this signature. In addition, these analyses requires high-cost instruments and are time-consuming. In order to verify in the future the provenance of a batch of raw material, traceability tools must be resilient to processes and mixing. They should also be more democratized and faster to set-up.In this regard, the project focuses on the development of the combination of rapid and easy-to-use on-site analysis for routine screening as well as laboratory verification in case of anomalies during the provenance verification of a lithium product. This relies on conventional geo-physico-chemical analysis such as mineralogy, major and trace element compositions, as well as isotopic analysis. The methods investigated includes hyperspectral spectroscopy, IR spectroscopy, LUXREM (XRF-XRD coupling, in development) as well as conventional X-Ray Fluorescence (XRF) and X-Ray Diffraction (XRD), Laser Induced Breakdown Spectroscopy (LIBS), (Laser Ablation) Inductively Coupled Plasma Mass Spectrometry ((LA)-QQQ-ICP-MS), (Laser Ablation)  Multi-Collector Inductively Coupled Plasma Mass Spectrometry ((LA)-MC-ICP-MS) and Thermal Ionization Mass Spectrometry (TIMS). Desaulty, A. M. et al. Tracing the origin of lithium in Li-ion batteries using lithium isotopes. Nat Commun 13, (2022).
 
PRIME: Probabilistic Regional Impacts from Model patterns and Emissions 
Authors: Mathison Camilla , Burke Eleanor , Munday Gregory , Kovacs Eszter , Huntingford Chris , Jones Chris , Smith Christopher , Wiltshire Andy , Steinert Norman , Gohar Laila , Varney Rebecca
Published: March 2024

We present PRIME, a framework for analysis of scenarios of regional impacts for user-prescribed future emissions. PRIME combines global mean temperature and CO2 concentrations from the emissions driven FaIR simple climate model, as used in the IPCC Sixth Assessment Report, with patterns of climate change from CMIP6 Earth System models to drive the JULES land model. This simulation system projects regional changes to the land surface and carbon cycle. We evaluate PRIME by running it with Shared Socioeconomic Pathways and illustrate its robustness by comparing these known scenarios with ESMs that have also been run for the same scenarios. PRIME correctly represents the climate response for these known scenarios, which gives us confidence that PRIME will be useful for rapidly providing probabilistic spatially resolved information for novel climate scenarios; substantially reducing the time between the scenarios being released and being used in impact assessments. Therefore PRIME fulfills an important need, providing the capability to include the most recent models, science and scenarios to run ensemble simulations on multi-centennial timescales and include analysis of many variables that are relevant and important for impact assessments.
A transition from arbuscular to ectomycorrhizal forests halts soil carbon sequestration during subtropical forest rewilding
Authors: Liu Ruiqiang , Zhou Xuhui
Published: March 2024

Abstract：Ecological succession and restoration rapidly promote multiple dimensions of ecosystem functions and mitigate global climate change. However, the factors governing the limited capacity of forests to sequester soil carbon (C) in old ecosystems are poorly understood. Ecological theory predicts that plants and microorganisms jointly evolve into a more mutualistic relationship to accelerate detritus decomposition and nutrient regeneration in old than young ecosystems, likely explaining the changes in C sinks across forest succession or rewilding. To test this hypothesis, we conducted a field experiment of root-mycorrhizal exclusion in successional subtropical forests to investigate plant-decomposer interactions and their effects on soil C sequestration. Our results showed that soil C accrual rate at the 0-10 cm soil layer was higher in early-successional arbuscular mycorrhizal (AM) forests with an average value of 1.26 mg g−1 yr−1 than that in the late-successional ectomycorrhizal (EcM) forests with nonsignificant change. A transition from early-successional AM to late-successional EcM forests increase fungal diversity, especially EcM fungi. In the late-successional forests, the presence of ectomycorrhizal hyphae promotes soil C decomposition and nutrient cycle by increasing soil nitrogen and phosphorus degrading enzyme activity as well as saprotrophic microbial richness. Across early- to late-successional forests, mycorrhizal priming effects on soil C decomposition explain a slow-down in the capacity of older forests to sequester soil C. Our findings suggest that a transition from AM to EcM forests supporting greater C decomposition can halt the capacity of forests to provide nature-based global climate change solutions.
Keywords: Belowground C allocation; Ectomycorrhizal richness; Enzyme activity; Mycorrhizae-saprotroph interaction; Nutrient competition
 
Investigating aquitard heterogeneity by inverse groundwater modelling of drinking water extraction sites
Authors: van Leer Martijn , Zaadnoordijk Willem Jan , Zech Alraune , Griffioen Jasper , Bierkens Marc
Published: March 2024

Aquitards are important hydrogeological features and their properties play an important role in e.g. water resources management, subsidence, aquifer thermal energy storage and contamination transport. The hydraulic conductivity of aquitards is typically parameterized by analytical interpretation of pumping tests or model calibration. However, these methods may not be very accurate for aquitards and usually do not account for spatial variability and uncertainty. Alternatively, core-scale measurements of hydraulic conductivity are used in geostatistical upscaling methods, for which their correlation lengths are needed. However, this information is extremely difficult to obtain. In this study we investigate whether readily available data from three drinking water extraction sites in The Netherlands can be used to obtain the geostatistical parameters of aquitard hydraulic conductivity needed for upscaling and to provide information about spatial variability of the hydraulic conductivity. We generated conditional random realizations from core scale data with varying correlation lengths and lithology distributions, upscaled these to model block scale and inserted these into a groundwater flow model that simulates the impacts of drinking water extraction and natural variability in precipitation and evapotranspiration over an extensive time period. We select the realizations that best fit observed groundwater heads to extract information about aquitard correlation lengths and lithology distributions and derive upscaled spatially varying aquitard conductivities.
Assessing the climate drivers leading to winter wheat yield shock in Europe
Authors: Stainoh Federico , Biess Bianca , Gudmundsson Lukas , Moemken Julia , Seneviratne Sonia I. , Pinto Joaquim G.
Published: March 2024

Ongoing global warming has major implications on the food security and the agricultural sector. Extreme weather such as precipitation extremes, heatwaves, frost and drought can cause severe reductions in crop production. Furthermore, these events can be strongly amplifyed when considered as compound events. In this study, we inquire into the temporally combination of climate extremes leading to substantial drops in winter wheat yield (in the following called “yield shock “) throughout different countries in Europe. Winter wheat is one of the most important crops in Europe in terms of production, and is also acknowledged a major crop globally. We use the Global Data of Agricultural Yield, a satellite-reported yield hybrid dataset of major crops. We categorise the yield as “yield shock” and “no yield shock” in order to reduce the uncertainty and to mainly focus on historical yield plunges. We consider and test different climate indicators (like the number of warm days or cumulative precipitation) that represent weather extreme events at a subseasonal scale. Moreover, we employ a Random Forest to capture any possible nonlinear relation. Our study illustrates the probability of winter wheat yield shock under the occurrence and co-occurrence of subseasonal weather extremes, and the nuances throughout countries with different climatic patterns.