bluuebunny/crossref_metadata_2025 huggingface dataset:
From intraplate weakening to plate boundary: New diagnostics to quantify rheological controls on deformation localization in a simple extension set-up at lithospheric scale
Authors: Van Broeck Etienne , Thoraval Catherine , Garel Fanny , Arcay Diane , Davies Rhodri
Published: March 2024

Initiation of new plate boundary can be related to a spatio-temporal evolution of an intraplate vast diffuse deformation towards a narrow highly deforming boundary. It can also occur by reactivation of an inherited weak zone. In all cases, breaking a plate requires a weakening of the lithospheric cold mantle, whose rheological parameterisation often features a « yield strength » formulation that is not clearly related to actual deformation mechanisms. On the other hand, the bulk effective viscosity for mantle rocks, either cold lithospheric mantle or the hotter asthenosphere underneath, have multiple dependencies, that may co-evolve in geodynamic settings, e.g. temperature and strain rate increase during asthenosphere upwelling associated with plate extension. In dynamic models, the (output) pattern of deformation localization cannot be directly predicted from the (input) flow laws governing material weakening, e.g. viscosity decrease when strain-rate or temperature increase. We currently lack diagnostics to quantify which rheological dependency weakens lithosphere through time.Using finite-element Fluidity code, we designed 2-D upper-mantle thermomechanical models of plate extension. Simulations were run for various background strain rates (associated to various horizontal velocity profiles imposed along vertical sides) and for various rheological parameterizations featuring Newtonian diffusion creep, non-Newtonian low/high temperature dislocation creep, and/or yield stress. We propose diagnostics to quantify, through space and time, the weakening efficiency associated to thermomechanical parameters (here either strain-rate, or temperature) . The weakening efficiency is defined as the temporal variation of viscosity relative to only strain rate (or only temperature), normalized to the total viscosity variation. It is used to characterize the chronological sequence and feedbacks leading to deformation localization, and compare them for different rheological parameterizations. From these diagnostics, we discuss which deformation mechanisms are activated during plate extension and thinning, and the characteristic time-scale of successful or failed localization for various rheologies. We compare especially simulations featuring an ad hoc yield strength parameterization vs. low-temperature dislocation creep.
Human drivers of flood losses in Europe since 195
Authors: Paprotny Dominik , Tilloy Aloïs , Vousdoukas Michalis I. , Kreibich Heidi , Feyen Luc , Morales Nápoles Oswaldo , Mengel Matthias
Published: March 2024

Human drivers significantly influence flood occurrence and impacts  through multiple avenues. In this work, we explore how human drivers contributed to flood risk in 42 European countries between 1950 and 2020, with particular focus on 1504 historical floods that caused significant socioeconomic impacts. Our modelling chain covers both riverine and coastal floods and is able to reconstruct past extreme events including the influence of (1) human impact on catchment hydrology through changing land use, water demand and reservoir capacity, (2) increase in exposure related to land use change, demographic and economic growth, and evolving structure of the economy, and (3) changes in flood preparedness, exhibited by flood protection levels (primarily from structural defences) and flood vulnerability (relative loss at given intensity of hazard). The results indicate that although construction of large reservoirs (the number of which increased six-fold in the study area since 1950) has locally led to a pronounced decline in riverine flood risk, human alterations to catchments overall increased the flood risk in Europe due to land-use change, particularly through strong increase in soil sealing caused by urbanization. An even stronger relative effect on the increase in flood impacts is caused by exposure growth, consisting of population growth, particularly in cities, a rapid increase in gross domestic product per capita, and further compounded by growth in capital-to-income ratio. Exposure growth is more pronounced for coastal floods compared to riverine floods. On the other hand, historical flood impact data analysed in this study show evidence of improving preparedness over time. Flood defences currently protect against higher return periods of floods than before, particularly for coastal floods, though they are mostly much lower than assumed in previous pan-European studies. A decline in flood vulnerability (relative losses) over time is also observed, partially compensating for negative human influences on flood risk.
Multisource fusion for high-accuracy land cover mapping: A 10m resolution strategy in China's hill and gully regions 
Authors: Chen Le
Published: March 2024

Highly accurate land cover (LC) information with fine spatial resolution serves as the cornerstone for reliable environmental insights, strategic land management, and ecological conservation. Yet, existing public LC products with 1-30m resolution exhibit considerable inconsistencies, particularly within complex terrains and fragmented habitats such as hill and gully regions, leading to uncertainties in various applications. In this context, our study innovatively targeted China's hilly and gully regions to develop an enhanced 10m resolution LC map for 2020, termed CLC-HG. The methodological advancement lied in fusing multiple LC products through accuracy evaluation, spatial consistency verification, object-oriented classification, and random forest classification. The research involved: (1) Strategic zoning of hilly and gully regions into five areas, selecting one or two representative validation regions within each; (2) Leveraging high-resolution imagery and 20000 field verification points to derive a 1m resolution land use dataset for validation regions, named GFLUCC, with 1m resolution and 95% accuracy; (3) Comprehensive validation of seven land use products spatial consistency and accuracy based on GFLUCC; (4) Filtering of layers based on spatial consistency, retaining regions with high and medium consistency; (5) Utilizing object-oriented classification and random forest classification, a higher-accuracy LC dataset was generated to replace the layers that were removed in the spatial consistency process; (6) Successful creation of CLC-HG, mirroring the accurate land use patterns of 2020. Our findings elucidated: (i) The superiority of WorldCover 10m in LC classification, contrasting with other products' regional inaccuracies; (ii) The influences of terrain complexity and human activity on accuracy, highlighting the precision in uniform areas versus the inaccuracy in complex regions; (iii) Substantial variations in spatial consistency across different terrains, with LP showing the weakest consistency; (iv) CLC-HG's remarkable performanced in identifying diverse LC types, boasting 85% overall accuracy; (v) Notable progress in classification accuracy with CLC-HG, uncovering the nuanced influences of land category complexity on consistency and human interventions on accuracy. This study breaks new ground by integrating multidimensional data and methodologies, contributing valuable insights for classification enhancements and more adept land resource management. The pioneering CLC-HGproduct holds significant potential to reduce uncertainties in global environmental change studies, ecosystem evaluations, and hazard assessments, marking an important step forward in remote sensing applications.
Food security in a changing climate - how can Earth observation and machine learning help? 
Authors: Bueechi Emanuel , Fischer Milan , Crocetti Laura , Trnka Miroslav , Grlj Ales , Zappa Luca , Dorigo Wouter
Published: March 2024

Climate change is threatening food security. To ensure food security, we do not only have to safeguard agricultural production - crop yields also need to be optimally distributed. For that, decision-makers need reliable crop forecasts so that they can plan which regions are likely to experience crop yield losses and which regions will produce a surplus. Earth observation and machine learning are key tools to calculate such forecasts. However, extreme crop yield losses, for example caused by severe droughts, are often underestimated. To test this, we developed a machine learning-based crop yield anomaly forecasting system for the Pannonian Basin and examined its performance, with a focus on drought years. We trained the model (XGBoost) with crop yield data from 43 regions in southeastern Europe and predictors describing soil moisture, vegetation, and meteorological conditions. Maize and winter wheat yield anomalies were forecasted with different lead times (zero to three months) before the harvesting season. Our results show that the crop yield forecasts are significantly more reliable from 2 months before the harvest than before in both, drought and non-drought years. The models have their clear strength in forecasting interannual variabilities but struggle to forecast differences between regions within individual years. This is related to spatial autocorrelations and a lower spatial than temporal variability of crop yields. In years of severe droughts, the wheat yield losses remain underestimated, but the maize forecasts are fairly accurate. The feature importance analysis shows that in general wheat yield anomalies are controlled by temperature and maize by water availability during the last two months before harvest. In severe drought years, soil moisture is the most important predictor for the maize model and the seasonal temperature forecast becomes key for wheat forecasts two months before harvest. 
An Operational Global Probability-of-Fire (PoF) Forecast : Can we predict extreme events?
Authors: McNorton Joe , Di Giuseppe Francesca
Published: March 2024

Wildfires have widespread effects on local ecosystems, communities, air quality, and global atmospheric conditions. Accurate wildfire forecasts can be used by local communities and agencies to manage and respond to wildfires effectively. As such, it is essential these predictions are not only accurate but are accessible in real-time and provide sufficient advanced notice to ensure successful actions can be taken. Existing systems typically use fire danger indices to predict landscape flammability, based on meteorological forecasts alone, often using little or no direct information on land surface or vegetation state. Here, we use a vegetation characteristic model, weather forecasts and a data-driven machine learning approach to construct a global daily ~9 km resolution Probability of Fire (PoF) model operating at multiple lead times. The PoF model outperforms existing indices, providing accurate forecasts of fire activity up to 10 days in advance, and in some cases up to 30 days and has been deployed operationally at the European Centre for Medium-Range Weather Forecasts (ECMWF). The model can also be used to investigate historical shifts in regional fire patterns. Furthermore, the underlying data driven approach allows PoF to be used for fire attribution, isolating key variables for specific fire events or for looking at the relationships between variables and fire occurrence. The 2023 Canadian wildfire season is used as a test case to assess model performance at predicting extreme wildfire events.
Exploring the effect of different VLBI Networks on EOPs estimation.
Authors: del Nido Herranz Lucía D. , Belda Santiago , Karbon Maria , Azcue Esther , Puente Víctor , Ferrándiz José M.
Published: March 2024

One of the key determinants influencing the accuracy and reliability of Earth Orientation Parameters (EOP) is the network Very Long Baseline Interferometry (VLBI) geometry. VLBI is a high-precision radio astronomy technique that involves multiple radio telescopes spread across the globe, working together as a network. The geometric configuration of these telescopes plays a crucial role in the quality of the data collected and, consequently, the accuracy of EOP measurements. The distribution and arrangement of the VLBI network antennas impact the triangulation process used to determine the positions of celestial radio sources, contributing to the calculation of Earth's rotation parameters. An optimal VLBI geometry ensures a well-constrained and robust observational setup, leading to more precise EOP results crucial for many scientific applications.In this study, we analyze the impact of using different VLBI networks on the EOP estimation. Due to its nature the Continuous VLBI Campaigns (CONT) give a good basis to investigate these effects. For this purpose, we artificially create different networks with distinct configurations (e.g. removing VLBI antennas located in the northern hemisphere and vice versa, taking out the longest north-south baselines or the east-west baselines…). This sensitivity analysis will contribute to the refinement of the EOP and will help to fulfill the stringent GGOS targets (i.e. a frame with accuracy at epoch of 1 mm or better and a stability of 0.1 mm/y).Acknowledgment. This research was supported partially by Spanish Projects PID2020-119383GB-I00 funded by Ministerio de Ciencia e Innovación (MCIN/AEI/10.13039/501100011033); PROMETEO/2021/030 and SEJIGENT/2021/001, funded by Generalitat Valenciana; and the European Union—NextGenerationEU (ZAMBRANO 21-04).
Cover crop´s carbon inputs to soils via aboveground and root biomass as affected by species, mixtures and sowing date
Authors: Reinelt Laura , Maack Nicole Christin , Heinemann Henrike , Don Axel
Published: March 2024

An increased use and optimised management of cover crops is a promising way to promote soil organic carbon accrual in agricultural soils. However, data is lacking on aboveground and especially root biomass of important cover crop species depending on the length of their cultivation window and on climatic conditions. We sampled aboveground and root biomass in a German field trial covering twelve common cover crop species and eight commercially available seed mixtures in 2021, a year with a rather wet summer, and 2022, a year with a rather dry summer. Each species and mixture were sown at three different dates and were sampled in early November, after having grown for 8 to 14 weeks.Root and shoot biomass differed significantly between species, years and sowing dates. Oil radish, Phacelia, Bristle oat and Italian rye-grass had the highest root biomass. Cover crop mixtures did not have significantly higher aboveground or root biomass than single species. Aboveground biomass was 60% lower in 2022 compared to 2021 and root biomass on average 52% lower. Biomass generally decreased substantially with later sowing dates, by up to 80%. In 2021, the root to shoot ratio decreased by on average 41% from the earliest to the latest sowing date.Based on the results of our study, management recommendations can be given regarding the selection and management of cover crop species for soil carbon accrual. Our data is also useful for more accurate mechanistic modelling of the soil carbon dynamics under different agricultural management scenarios. We conclude that there is a large optimisation potential for cover crop cultivation in Europa that could reveal a significant soil carbon sequestration potential.
Assessment and evaluation of the utility of hydrokinetic technologies in low head streams
Authors: El Mir Mohamad Anas , Valyrakis Manousos
Published: March 2024

Large dams exploiting hydropower have been marvels of engineering practice, but over the decades their accrued environmental effects, such as sediment budget balances (due to upstream aggregation and downstream erosion) and water quality and fish biota degradation, were visible. Moreover, large centralised hydropower systems present the challenge of grid connectivity, as it can be challenging to connect large electricity grids to remote and inaccessible rural areas, not only due to costs but also due to the loss of energy due to high distances. Scotland having many small rural communities and thousands of small low-head streams, is a prime example for efficiently demonstrating tackling the above crucial challenges of small scale decentralised power generation, with alternative schemes such as micro-hydropower and hydro-kinetic systems. These flexible to install and operate systems, can help prevent grid connectivity problems and electricity loss. They can be installed in several locations due to their small assembly and easy construction process compared to large hydropower plants. They can also be installed at wastewater plants to exploit outlet flows. In this study several criteria were analysed to assess the new technologies based on data collected from various suppliers. The criteria covered several aspects of the technologies: health and safety, design, environmental constraints, employability, and financial viability. The selection process started to classify the viability of the technologies according to the score they achieved. The technologies are assessed, and optimal use sometimes based on the location and real world application, are offered.
Quantification of climate-induced changes in groundwater levels using fuzzy rule-based modelling
Authors: Iffland Ronja , Haberlandt Uwe
Published: March 2024

"Quantification of climate-induced changes in groundwater levels using fuzzy rule-based modelling"Ronja Iffland and Uwe HaberlandtInstitute of Hydrology and Water Resources Management, Leibniz University of Hanover, Germany (iffland@iww.uni-hannover.de)The impact of climate change on hydrological processes, such as increased flooding and prolonged droughts, also affects groundwater recharge and therefore groundwater levels. To make reliable statements about possible changes in groundwater level dynamics prediction models are needed. In this study, fuzzy rule-based models are used to analyse and quantify the effects of changing climate conditions on groundwater levels.Focussing on 114 groundwater wells in Lower Saxony, Germany, the study aims to explain groundwater dynamics using assumed relationships between climatic indices and groundwater levels. Starting from linear methods, we used fuzzy logic to capture the non-linearities in groundwater level systems. While fuzzy logic models have mostly been considered in combination with neural networks in groundwater level prediction, our approach utilises the transparency of fuzzy rule-based modelling to maintain model interpretability. To improve the forecast accuracy, we introduced moving averages and time lags to account for the persistent influence of meteorological indices. As reference we calculated multiple linear regression models. The performance of both fuzzy rule-based models and linear regression models are evaluated using split validation. To predict future changes in groundwater levels, we applied both models to climate model data based on the RCP8.5 scenario. It is expected that the non-linear fuzzy rule-based models outperform the linear regression models.
Modelling the feasibility of using disused mines for heat extraction and storage
Authors: van Hunen Jeroen , Mouli-Castillo Julien , Sweeney Alexandra , Tu jiada , Wang Yuxiao , Adams Charlotte
Published: March 2024

The subsurface offers significant opportunities for geothermal heat extraction and storage. Disused, flooded coal mines, in particular, are capable of providing a major low-enthalpy, renewable and long-term heat resource if carefully managed. To establish a mine water geothermal system requires significant capital investment and a large amount of time. Therefore, a solid investigation of the feasibility of a mine as heat source or storage medium is essential.We have developed a modelling tool, GEMSToolbox, to investigate the feasibility of abandoned mines for long-term heat extraction and/or storage. This tool allows for a computationally fast and a low-cost study into the viability of mine water heating for given mine workings. We combine numerical and analytical methods with digitised legacy mine plan data to estimate the variations in the abstraction water temperature over the lifetime of a project. We couple the heat transfer approximation method originally proposed by Rodriguez and Diaz (2009) to that of flow in a pipe network as described by Todini and Pilati (1987), and refine the original heat transfer approximation by accounting for a flow regime specific heat transfer coefficient between the rock mass and the water, as prescribed by Loredo et al. (2017). A novel weighting function is also developed to account for the interference between adjacent mine galleries. This tool has been successfully applied to a range of mine system in the North East of England, and the results of this study are used to draw widely applicable conclusions on the feasibility of mine workings for heat extraction or storage more generally.References:Loredo C, Banks D, Roqueñí N. Evaluation of analytical models for heat transfer in mine tunnels. Geothermics 2017; 69; 153-164.
Rodriguez R and Díaz M. Analysis of the utilization of mine galleries as geothermal heat exchangers by means a semi-empirical prediction method. Renewable Energy 2009; 34(7), 1716-1725.
Todini E and Pilati S. A gradient method for the analysis of pipe networks. Computer app. In water supply 1987; 1-20, v1.
Reduction of systematic differences of LSASAF shortwave solar radiation fluxes using neural networks
Authors: Savli Matic , Mlakar Peter
Published: March 2024

To improve the process of solar energy production, we can utilize the downward
shortwave flux (DSSF) measurement, which constitutes a part of the satellite
derived total and diffuse downward surface shortwave flux (MDSSFTD) product.
MDSSFTD is issued by the Satellite Application Facility on Land Surface Analysis (LSA SAF).
However, its direct application in this area is inhibited by potential systematic
errors in the DSSF product. Therefore, this has to be addressed before the DSSF can be used downstream.
To this end, we implemented a neural network-based post-processing procedure
that uses previous temporal DSSF observations and additional predictors, such
as cloudiness and time of day, to generate a corrected DSSF value. The ground
truth for this regression task are the in-situ measurements across a variety of
locations in Slovenia. Additionally, the neural network produces DSSF estimates
in terms of quantiles, providing an uncertainty estimate of the corrected prediction itself.
We verified our new method on the aforementioned region over a period offour years. We found that our neural network approach successfully reduces
the presence of systematic differences present in the DSSF. Additionally, the
neural network method outperforms a baseline look-up-table approach in termsof multiple criteria, such as mean absolute error, bias, and error variability.
Integrating UAS-based lidar data in eddy covariance flux footprint modelling
Authors: Lehmann Jan Rudolf Karl , Arulmozhi Nambi Visweshwar , Giese Laura , Meyer Hanna , Gharun Mana
Published: March 2024

Peatlands, covering 3% of the global land area, store twice the carbon of all the world's forests combined, acting as crucial carbon sinks. However, under varying environmental conditions induced by global warming and land cover changes, they can transition into carbon sources. Monitoring gas exchanges in peatland ecosystems involves employing the eddy covariance method, often interpreted using flux footprint models. This study focuses on the application of the FFP model, specifically addressing the influence of spatially varying roughness parameters.Utilizing Unoccupied Aerial Vehicle (UAS)-based high-resolution LIDAR data, we incorporated spatially varying roughness values into the FFP model, comparing the results with traditional scalar roughness length values. Our findings reveal that spatially varying roughness introduces spatial heterogeneity, resulting in more irregular and smaller footprints. The inclusion of spatially varying roughness based on the surface reduced the area contribution to fluxes by 40%, emphasizing the significance of accounting for this spatial variability.Moreover, we investigated the impact of surface and terrain conditions on footprint modeling in a peatland previously subjected to extraction. Our analysis indicates that variations in terrain (both natural and extraction-induced) reduced the footprint contours by 18% compared to the original FFP model footprints. This underscores the importance of considering terrain changes in footprint modeling, especially in peatlands with a history of extraction activities.In conclusion, this research enhances our understanding of (1) the impacts of spatially varying roughness on modeled footprints and (2) the influences of surface and terrain on footprint size in peatland ecosystems. These insights contribute to improved modeling accuracy and aid in effective carbon management strategies for peatland conservation.
Investigating the groundwater contribution to the lakes and streams by environmental tracers in the catchment area of Lake Velence (Hungary) 
Authors: Pénzes Viktória , Erőss Anita , Hegedűs-Csondor Katalin , Baják Petra , Horváth Ákos , Czuppon György
Published: March 2024

Lake Velence is a shallow soda lake, the third largest natural lake in Hungary. The lake’s water level has been decreasing and the water quality has been declining in recent years. The shallow depth of the lake makes it more susceptible to droughts and evaporation. Climate change in Hungary will likely cause these phenomena to be more common in the future. In the lake’s water budget, only the surface water components and precipitation are considered. Revisiting the water management in the area is necessary for the local ecosystem and tourism industry. We intend to aid the efforts of the authorities and locals to stop the deterioration of the lake with exploring the surface water-groundwater interactions in the area using natural tracers. Groundwater may buffer the effects of climate change, which highlights the importance of the study. 

Groundwater mapping in the area proved that the lake is at the discharge point of local groundwater flow systems. In this previous study, similar uranium activity concentrations were also measured in the lake water and in groundwater samples collected by the lake indicating a close interaction between the lake and the groundwater.  

To further investigate this question, water samples were collected from different water sources in the catchment area of Lake Velence: from the lake, inflow streams, an artificial reservoir, and groundwater wells. The samples were analysed for stable isotopes δ2H and δ18O. Furthermore, 234U, 238U, 226Ra ,228Ra and 222Rn activity were measured by an innovative technique: alpha spectrometry applied on selectively adsorbing Nucfilm discs. Both the stable and the radioisotopes function as environmental tracers in this study to collect thorough evidence about the contribution of groundwater in the water budget of Lake Velence and in the inflowing streams. This will contribute to the sustainable water management of the whole catchment area of the Lake Velence by highlighting the role of groundwater.  

The research was supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences and the research was funded by the National Multidisciplinary Laboratory for Climate Change, RRF-2.3.1-21-2022-00014 project. 
Soil water retention function variability based on soil structure and moisture dynamics at field conditions affected by compaction in an Andosol
Authors: Bravo-Peña Sebastián , van Schaik Loes , van Dam Jos
Published: March 2024

The variability of soil hydraulic properties across different spatial and temporal scales leads to heterogeneous sub-surface water flows, affecting the accuracy of predicting soil water distribution and solute transport. Since soils such as Andosols can describe extreme physical behaviours and water rarely is in hydraulic equilibrium in the porous media, it is still challenging to derive hydraulic functions that realistically represent the influence of soil structure dynamics under different land uses, as well as to predict the occurrence of non-uniform flows at field conditions. This work aimed to describe the spatiotemporal variability of unimodal and dual-porosity (bi-modal) soil water retention (SWR) functions using high-resolution field observations in structured soil affected by compaction. We focused on the influence of water-filled pores volumes at wet and dry conditions, wetting/drying cycles, and soil structure dynamics using three depths (10, 20, and 60 cm). The land use was a diverse grassland sown in September 2019, including three compaction levels (0.65, 0.75, and 0.85 g cm-3, named Control, T1, and T2, respectively) in an Andosol of Southern Chile. A two-year 10-min-resolution dataset (June 2020 to June 2022) of soil moisture content (48 sensors) and matric potential (18 sensors) collected by 6 monitoring stations was analysed by i) separating wet and dry periods dynamics based on soil moisture states, ii) determining wetting and drying cycles using time derivatives of soil moisture content, and iii) fitting and comparing the parameters of unimodal and dual-porosity formulations of the Mualen-van Genuchten numerical solution. Separating soil moisture observations in wet and dry conditions, as well as in wetting and drying cycles, resulted in different SWR curves starting from contrasting water-filled pores volumes. This dynamic-based hydrological parameterisation resulted in a range of high goodness of fit (mean R2 of 0.89 ± 0.07 and 0.94 ± 0.06 for unimodal and dual-porosity van Genuchten models) while deriving SWR functions. However, the dual-porosity formulation better represented complex curvatures in SWR curves towards the soil surface in wet conditions, which would increase our capacity to describe near-saturation macropore dynamics at high resolution. Thus field observations allowed the representation of expected spatial variability between soil depths due to different physical properties and compaction influence. While at the same time, high-resolution time series were used to describe significant different SWR curves for wet and dry conditions when soil structure is affected by compaction, mainly influencing α and n parameters in unimodal formulations, and n1, α2, and n2 in dual-porosity formulations.
An Early Warming Over the Southern Ocean During the Last Deglaciation
Authors: Zheng Peisong , Osman Matthew , Bauska Thomas
Published: March 2024

The last deglaciation, spanning approximately 23 to 6 thousand years before present (ky BP), represents the most recent period in which Earth’s climate underwent large-scale reorganizations comparable (albeit not strictly analogous) to those projected under future climate changes. However, the precise sequence of events – in particular, the timing and spatial manifestation of the initial warming – remains uncertain. Here we present a new method using Gaussian Mixture Model clustering to objectively decompose a model and proxy-based climate reconstruction (LGMR; Osman et al., 2021) into four patterns of temperature change across the last deglaciation. Broadly speaking, the patterns allow us to delineate the impact of retreating Northern Hemisphere ice sheets, the rise in greenhouse gases, and the influence of the bipolar seesaw. Crucially, our analysis reveals that the high latitudes of the Southern Hemisphere exhibited the earliest signs of warming onset around 21 kyr BP, coincident with a retreat of sea ice across the Southern Ocean. A similar pattern is observed when decomposing a solely model-based climate reconstruction (TraCE-21k; He et al., 2013).  Using a combination of both highly-simplified energy balance-type models and fully-coupled climate models forced with insolation alone, we show that the early warming and sea ice retreat was likely linked to an initial rise in high latitude summertime energy that is dominated by enhanced obliquity-driven forcing. Our findings collectively suggest that insolation dynamics in the Southern Hemisphere were a critical trigger of the Last Deglacial onset and, further, may represent one of the key prerequisites for glacial terminations during the late Pleistocene.
Primary Devonian paleomagnetic results from the Qinling orogenic belt and its implication for the evolution of the Proto-Tethys Ocean
Authors: Xu Huiru , Liang Yuan , Lai Yiming , Li Guomin
Published: March 2024

The Qinling Orogenic Belt (QOB) is one of the most important orogens in Eastern Asia formed by the collision between the North China Block (NCB) and the South China Block (SCB). The evolution history of the QOB is essential to the assembly processes of the major blocks in China and the evolution history of the Proto-Tethys Ocean (Shangdan Ocean). Paleomagnetism can quantitatively restore the paleo-position of blocks, which is key to studying the related tectonic evolution. Hindered by the complex tectonic process, few paleomagnetic results have been reported from the QOB. Here we reported a primary paleomagnetic study from the northern QOB by conducting both rock magnetic and paleomagnetic experiments on the early Devonian Lajimiao pluton (~413Ma) in the North Qinling belt (NQB), to constrain its paleo-position and the evolution of the QOB during the early Paleozoic period.253 cores from 28 sites were drilled by portable gasoline drills, and oriented by a magnetic compass and also a sun compass if possible. Rock magnetic experiments indicate that the main magnetic mineral in most of the samples is mainly magnetite in a pseudo-single domain or multi-domain state. Both thermal demagnetization and alternating-field demagnetization were applied to obtain the characteristic remanent magnetization. The Fisher-mean direction of the low-temperature/coercivity component is roughly consistent with the present geomagnetic field (PGF), suggesting that it is probably a viscous remanent magnetization caused by the PGF. The high-temperature/coercivity component yielded a Fisher-mean direction Ds/ Is = 355.8°/19.1° in stratigraphic coordinates, corresponding to a paleomagnetic pole of 65.8°N/299.9°E (A95=2.4°). It is the first Devonian paleomagnetic pole among the scarce paleomagnetic results from the QOB. This pole indicates that the NQB may have been located at a low latitude at the early Devonian, probably in proximity to both the North China and South China blocks. However, the difference between the coeval paleomagnetic poles from the three blocks (NQB, NCB, SCB) may hint the assembly process of the several major blocks is not simple and direct. Anyway, the newly obtained paleomagnetic pole from the NQB would be able to refine our understanding of the tectonic evolution of the QOB and the Proto-Tethys Ocean.
Active deformation in Tunisia from GNSS measurements
Authors: Kristou Hamza , Masson Frédéric , Bahrouni Néjib , Meghraoui Mustapha , Ulrich Patrice
Published: March 2024

Tunisia lies at the centre of the East-West trending convergence zone between the Nubian and Eurasian plates, at the eastern end of the large tectonic structures of the Atlas and Tell mountains and to the west of the Pelagian block and Sicily. As a result, its complex tectonics along the plate boundary show N-S to NW-SE oblique convergence expressed by E-W- to WNW-ESE-trending right-lateral strike-slip faults associated with E-W- to NE-SW-trending thrust faults that affect the Neogene and Quaternary units of the Tell and Sahara Atlas of Tunisia.Although this region is generally characterized by moderate seismicity, it is known for its historical and instrumental seismic activity that has resulted in human and materiel losses, such as in Utique 408 AD, Kairouan 859 AD, Tozer 1997 and recently in March 2018 an earthquake felt between Tunis and Bizerte and in April 2023 an earthquake felt in Metlaoui, both earthquakes registered (Mw 5).A partnership between the National Office of Mines ONM-Tunisia and ITES-Strasbourg is being set up to develop spatial geodesy work using GNSS measurements to characterize and quantify the active deformation of Tunisia alongside previous tectonic and seismotectonic works.A network of already existing 21 GNSS stations spread over the Tunisian territory is managed by OTC (Office of topography and cadaster) so in the framework of this project 6 days/year of records from 2012 to 2019 has been purchased.To improve the resolution of the acquired data and fill the gaps between the OTC stations, a national network consisting of 24 mobile stations is set up and three campaigns of 3 days of records in 2019, 2021 and 2023 have already been carried out.Between 2022 and 2023, five more permanent stations have been installed to provide a continuous flow of data.Two target areas, Gafsa and Kairouan have been chosen to install regional networks consisting of 16 sites each around active faults. Three campaigns in 2021, 2022 and 2023 have been carried out and one more is planned in 2024 to detect the deformation in those areas.All these data allowed the calculation of a precise velocity field of Tunisia based on GPS trends and the establishment of the strain rate distribution across continental Tunisia. These new data will be analyzed in the light of existing knowledge, in particular the recent seismotectonic and paleoseismological work carried out as part of our project.
Assessing soil erosion in a small agricultural catchment in Austria using OSL-dating, modelling, 137Cs and field measurements: a critical comparison
Authors: Pöppl Ronald , Renschler Chris , Abatti Bruno , Asimus Nadine , Kraushaar Sabine , Strauss Peter , Fuchs Markus
Published: March 2024

Soil erosion causes severe on- and off-site effects, such as reductions in soil depth, eutrophication of water bodies, loss of organic matter, and clogging and smothering of riverine habitats. Attempts to assess water-induced soil erosion by water include modelling, measuring/monitoring, the use of tracers, and dating. All of these approaches have shown to have shortcomings (Parsons, 2019). The main objective of this research is to assess soil erosion in a small agricultural catchment (HOAL, Lower Austria) using modelling, OSL-dating, 137Cs and field measurements and to compare the gained results in the light of the shortcomings of each method. The study has been conducted in a small catchment (ca. 66 ha), located in the Northern foothills of the Eastern Alps in Austria (i.e. an area intensively agriculturally used since the Middle Ages). The catchment elevation ranges from 268 to 323 m a.s.l. and has a mean slope angle of 8 %. The lithology mainly consists of Tertiary marly to sandy deposits which are superimposed by Quaternary sediments (e.g. loess). The climate in this region is characterized as humid. The results of this study reveal significant – partly even dramatic - differences in soil erosion rates as derived from the different assessment methods. Details as well as a critical method comparison will be provided at the EGU General Assembly 2024.References:Parsons, A. J. (2019). How reliable are our methods for estimating soil erosion by water? Science of the Total Environment, 676, 215-221.
Continuous monitoring of the isotopic composition of methane in Cluj-Napoca.
Authors: van Es Jacoline , van der Veen Carina , Menoud Malika , Baciu Calin , Hmoudah Mustafa , Henne Stephan , Rockmann Thomas
Published: March 2024

Methane (CH4) plays a crucial role in the Earths’ radiative balance, since itis a potent greenhouse gas with a shorter lifetime compared to CO2. Mitigatingmethane emissions could help mitigate climate change in a short time frame.This requires a solid understanding of the emissions on the location, strength andthe type of the source. Isotopic analysis can help with the source partitioningsince different sources emit CH4 with slight but significant differences in theisotopic composition.Utrecht University developed an isotope ratio mass spectrometer (IRMS)system capable of measuring δ13C and δD of CH4 at high precision with ap-proximately hourly time resolution for both isotope signatures. Under the Hori-zon Europe project PARIS (Process Attribution of Regional Emissions) we ex-panded the coverage of high time resolution isotope measurements in Europe bydeployment of this system in Cluj-Napoca. The goal is to investigate the typicalsource mix of methane in this region and investigate whether the observationsagree with emission inventories. This data is combined with a mobile surveysto investigate suspected sources.The work performed on the continuous data-series indicate that the nighttime accumulation has an important role in the mixing ratio and the signaturesof both the δD and δ13C. Furthermore it suggest that the enhancements can beexplained by a combination of leakages from the gas network, combined withmicrobial sources. Wind directions indicates that the city centre has significantcontributions to these emissions.
Electrical conductivity estimation from a new fractal model for porous media under reactive processes
Authors: Soldi Mariangeles , Rembert Flore , Guarracino Luis , Jougnot Damien
Published: March 2024

Near-surface geo-electrical methods monitoring the electrical conductivity have gained particular interest for environmental studies. Their sensitivity to key properties of storage and transport in porous media and their non-destructive nature make these methods a significant asset for studying the subsurface. Nevertheless, their quantitative interpretation depends on the efficiency of the used petrophysical relationship to link the physical properties, obtained from the electrical measurements, with the hydrological properties and state variables of interest. Therefore, the electrical conductivity of a porous medium is related to several geological parameters such as mineral matrix, porosity, permeability, and degree of water saturation. All of these parameters are controlled by the pore structure which plays a key role in the distribution of the conductive fluid. During reactive processes, the pore structure is significantly affected which translates into surface and volume variations. This evolution of the pore space leads to changes in the macroscopic hydraulic properties and, therefore, the electrical conductivity. In this study, we present an analytical fractal model to describe the electrical conductivity evolution during reactive processes. Under the assumption that the pore system is represented by a bundle of tortuous capillaries with constrictivity, we account for the reactive processes in the model by considering the geometrical variations in the pore structure (i.e., the increase and decrease of the pores aperture). The derivation of the electrical conductivity is based on upscaling procedures and a fractal law which describes the size distribution of pores. Considering the electrical charges dragged by the water in one capillary, we upscale the electrical property and obtain closed-mathematical expressions to calculate the electrical conductivity of the medium. This can be achieved thanks to the independence from scales of fractal media. For partially saturated conditions of the medium, the model’s expressions can estimate the electrical conductivity as a function of hydraulic properties. The performance of the model has been tested with published data from different soil and rock textures, under reactive fluid flow or partial saturation conditions. The comparison shows that the model can satisfactorily reproduce the behavior of the data. The fractal distribution is consistent with mico-CT results and the dissolution rate is within the same order of magnitude of the value obtained from experimental results. From a geometrical approach and within a fractal framework, we included the effect of reactive processes in the estimates of the medium electrical conductivity which opens up new possibilities to characterize media from geoelectrical techniques.
Skilful prediction of mid-term sea surface temperature using 3D self-attention-based neural network
Authors: Wang Longhao , Zhang Yongqiang , Zhang Xuanze
Published: March 2024

Sea surface temperature (SST) is a critical parameter in the global ocean-atmospheric system, exerting a substantial impact on climate change and extreme weather events like droughts and floods. The precise forecasting of future SSTs is thus vital for identifying such weather anomalies. Here we present a novel three-dimensional (3D) neural network model based on self-attention mechanisms and Swin-Transformer for mid-term SST predictions. This model, integrating both climatic and temporal features, employs self-attention to proficiently capture the temporal dynamics and global patterns in SST. This approach significantly enhances the model's capability to detect and analyze spatiotemporal changes, offering a more nuanced understanding of SST variations. Trained on 59 years of global monthly ERA5-Land reanalysis data, our model demonstrates strong deterministic forecast capabilities in the test period. It employs a convolution strategy and global attention mechanism, resulting in faster and more accurate training compared to traditional methods, such as Convolutional Neural Network with Long short-term memory (CNN-LSTM). The effectiveness of this SST prediction model highlights its potential for extensive multidimensional modelling applications in geosciences.
Seismic Imaging of Submarine Volcanoes and Volcanic Ridges at the Southeastern Azores Plateau
Authors: Friedrich Annalena , Hübscher Christian , Preine Jonas , Beier Christoph , Hildenbrand Anthony , Nomikou Paraskevi , Terinha Pedro
Published: March 2024

There is an ongoing debate about the water depths to which explosive submarine volcanism is possible. In this study, we present high-resolution reflection seismic data from cone-shaped intraplate volcanoes on the southeastern Azores Plateau that indicate explosive submarine volcanism at water depths greater than 2 km. In addition, the data illustrate the early stages of volcanic ridge evolution at similar water depths, which were mainly formed by fissure eruptions. The volcanic cones are ca. 4 km wide and 500 m high above the ocean floor. They are characterised by stratified flanks that are onlapped by sub-horizontal, hummocky high-amplitude reflections. We interpret the layered flanks as evidence of rather unconsolidated volcanic deposits from submarine explosive eruptions, where the magma emerging from the seafloor was fragmented by expanding volatiles. Guided by diffraction imaging, we interpret the high-amplitude reflections as the top of lava flows from effusive eruptions, that postdated the explosive eruptions. Distinct upward-bent reflections beneath the volcanic cones are interpreted to be velocity pull-ups caused by the presence of dense, high p-wave velocity material in the central part of the volcanic cones. We apply depth-stretching to correct for these artefacts and to access the true geometry of the volcanic cones and the underlying features. Upward concave reflections within the basaltic basement might represent funnel shaped conduits or diatremes. The seismic signature of a volcanic ridge between two of the volcanic cones suggests that stacked effusive eruptions dominated its evolution. Both the cones and ridges superimpose hemipelagic sediments, which in turn overlie the basaltic basement. Hence, the evolution of the volcanic features postdated the main magmatic evolution of the western part of the eastern Azores Plateau that started in the middle Miocene. Generally, our study sheds new light on the complex volcanic evolution of the southeastern Azores Plateau and highlights the potential of seismic imaging as a tool for submarine volcanology.