bluuebunny/crossref_metadata_2025 huggingface dataset:
Simultaneous Quantification of Soil Water States, Water Fluxes, Greenhouse Gases and BVOC Exchange between soil and atmosphere during transient conditions
Authors: Diamantopoulos Efstathios , Nguyen Hai Anh , Leuther Frederic , Nölscher Anke
Published: March 2024

Biogenic volatile organic compounds (BVOCs) are a diverse group of chemicals emitted from living organisms. These compounds are involved in a variety of ecological processes, as well as the formation of aerosols and ozone, which can impact air quality and climate. Recent studies suggest that BVOCs can be released and taken up by soil through biotic and abiotic pathways in high amounts. In this work, we simultaneously quantified the BVOCs exchange between , soil water evaporation fluxes, and matric potential under transient conditions (drying-rewetting experiments). The experiment was conducted with 250 cm³ soil cores (n=4) packed with sieved soil (loamy sand, bulk density: 1.6g/cm³) taken from agricultural topsoil. Aluminum chambers (1L in volume) were attached to the top of the soil cylinders and gas with different BVOCs concentrations was applied at the inlet. At the outlet, the analysis of BVOCs mixing ratios and BVOCs emission was done with a Proton Transfer Reaction – Time of Flight – Mass Spectrometry (PTR-ToF-MS). In addition, a Greenhouse Gas Analyzer (GGA) was used for monitoring the fluxes of methane, carbon dioxide, and water vapor. The analysis of soil water retention curves was done with a Hydraulic Property Analyzer (HYPROP). The results showed a strong negative correlation between ambient mixing ratios and soil emission rates of water-soluble BVOCs when the soil was wet. As the soil moisture fell below a threshold of 0.18 m3m-3 volumetric water content, BVOCs emission negatively correlated to soil water content. The more frequently the soil was rewetted, the more BVOCs could be taken up by wet soil. In conclusion, the study suggests that the BVOCs mixing ratio in the ambient air was the dominant driving factor of the BVOCs emission rate in disturbed soil samples from agricultural land use. Lastly, soil water content affected BVOCs emission mainly when the soil was dry.
Challenges of Rotational Ground Motion Measurements in the Local Distance Range
Authors: Donner Stefanie , Lehr Johanna , Krüger Frank , Hoffmann Mathias , Hobiger Manuel , Heimann Sebastian
Published: March 2024

Since almost two decades, there is a fast and steady progress in understanding the rotational part of the seismic wavefield and exploring possible applications. These achievements are based on studies using simulated data, array-derived measurements, and direct measurements of large (M > 5), teleseismic earthquakes by ringlasers. Since only a couple of years, direct measurements of smaller (M < 3) earthquakes in the local distance range are also feasible. This was made possible due to new instrumentation developments such as portable rotation sensors.From experience with translational measurements, seismology has developed a relatively simple description of the seismic wavefield, as long as the observation is recorded in the source far-field, and site-effects at the point of observation can be neglected by choosing an appropriate frequency range for the analysis.Within the NonDC-BoVo project two portable rotational sensors have been installed in the Vogtland/West-Bohemia earthquake swarm region with the goal to incorporate the rotational waveform data into the inversion for seismic moment tensors. Both sensors are located in an epicentral distance of ~10 km to the center of the swarm activity. So far, we have recorded 197 events with ML ≥ 1 and 6 events with ML ≥ 2.5.Although we are positively surprised how well we can record rotational ground motion of earthquakes with even very small magnitudes, we encountered challenges in the details of the waveform recordings. At the sensor location in Landwüst (D) we recorded events down to ML ~ 0.5 with good signal-to-noise ratio in a frequency range of 5 to 25 Hz. At the second location in Skalna (CZ) the signal-to-noise ratio is worse and we recorded earthquakes only with ML ≥ 1.5. Relocating the sensor to Wernitzgrün (D), about 25 km to the North of Skalna, did not improve the quality of the waveform recordings. Technical issues with the sensor can be ruled out for both locations.Here, we want to present details of the challenges with the rotational ground motion data from these small and local earthquake recordings. First analyses hint to a much stronger effect of local site conditions onto rotational than translational ground motion data. In addition, with the above-mentioned setting, we have to consider the complexities of the near-field part of the wavefield as well. With our contribution we aim to add another aspect to the understanding of the rotational wavefield.
Towards hyperspectral exploration vectors in the Central European Kupferschiefer district
Authors: Kirsch Moritz , Thiele Samuel , Madriz Yuleika , Simões Filipa , Basoglu Atilla , Kim Yonghwi , Gloaguen Richard
Published: March 2024

Europe holds significant potential for crucial metals essential for renewable energy and digital advancements. However, there is a need for a deeper understanding of the European subsurface, coupled with a requirement to reduce the environmental impact of exploration activities. We employ hyperspectral scanning of legacy drill cores to develop innovative indicators of mineralization in the Central European Kupferschiefer district, home to Europe's largest copper and silver resources. Hyperspectral imaging, capturing spectral reflectance and emission across numerous spectral bands, allows for non-invasive, high-resolution mineral mapping of drill cores. Initial findings showcased the technique's ability to identify critical redox boundaries and alteration minerals, aiding ore deposit characterization. In the framework of two research projects, we scanned 2400 meters of drill core from 87 boreholes across the Spremberg–Graustein Kupferschiefer deposit in Germany. For data acquisition, we deployed a drill-core scanner with a full suite of hyperspectral sensors covering the visible and near-infrared (400 to 970 nm), shortwave (970 to 2500 nm), mid-wave (2700 to 5300 nm), and longwave infrared (7700 to 12300 nm) ranges. The collected data were processed through a novel, open-source software pipeline, which enables i) real-time correction, processing, and analysis, ii) efficient data management and storage, and iii) comprehensive visualization and integrative interpretation of the hyperspectral drill core data. We upscaled mineral abundances across all of the scanned drill cores using a supervised learning model trained on quantitative mineralogical data from select samples. Initial analyses, particularly the visual alignment of hyperspectral derivatives at the base of the Kupferschiefer marker horizon, indicate geographical patterns in dolomite content and correlations between carbonate, clay, and mica compositions and copper grade. The hyperspectral data will eventually be integrated with geological, geophysical, and geochemical constraints to create accurate 3D subsurface and 4D mineral system models, aimed at enhancing our understanding of geological processes and resource management strategies in similar geological settings worldwide. Acknowledgements: This research has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement nº 101058483 (VECTOR), and from the Geological Survey of Saxony (Sächsisches Landesamt für Umwelt, Landwirtschaft und Geologie, LfULG) under agreement nº 4-0912014LFULG01-88.
Advancing Earth Monitoring: China's hyperspectral Operational Satellite Constellation
Authors: Xiao Chenchao , Tang Hongzhao , Shang Kun
Published: March 2024

China's first hyperspectral operational satellite constellation, launched in 2023, has significantly enhanced comprehensive Earth observation capabilities by integrating extensive quantitative data from space and ground sources. The constellation comprises the GF5-02, GF5-01A and ZY1-02D and ZY1-02E satellites. Operating in a sun-synchronous orbit, these satellites constitute a medium-resolution Earth observation system. Each satellite, GF5-02, GF5-01A, ZY1-02D and ZY1-02E, is equipped with visible and near-infrared as well as hyperspectral imager, enabling them to perform wide swath observations and acquire intricate spectral data. Significantly, ZY1-02E has been additionally equipped with a thermal infrared camera, thereby broadening its detection scope. The satellite team, collaborating with specialists across various fields, conducted 32 business tests in areas like land resources, geology, mapping, and marine monitoring, adhering to standards for natural resources survey and monitoring. After a year of operation, the constellation has shown robust functionality, stability, and data quality, meeting requirements for diverse applications such as resource enforcement, geological surveys, ecological restoration, geospatial updates, coastal surveillance, and industrial capacity reduction. The success in quantitative application tests of hyperspectral and thermal infrared payloads demonstrates the satellite's potential in providing critical insights for global users in the hyperspectral domain.
EU engagement for sustainable water management in the Aral Sea basin
Authors: Assubayeva Aliya , Sehring Jenniver
Published: March 2024

Integrated Water Resources Management (IWRM) stands as a globally advocated approach heralded for its promise to orchestrate equitable and coordinated water allocation, usage, and governance. However, its implementation varies significantly across different river basins and countries. Transboundary water resources management in the Aral Sea basin presents a critical environmental and political challenge in the region, bringing concerns not only to basin countries, including Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan but also to external actors.  The European Union (EU) has emerged as a pivotal donor in developing sustainable water resource management since the early 1990s. The EU's involvement stems from recognizing water challenges as potential threats to regional security and stability and fosters diverse regional and bilateral water programs and projects. This study delved into the evolution of the EU policies concerning environment and water management in the Aral Sea basin, focusing on promoting IWRM, raising environmental awareness, and building capacities. Methodologically, the research employed semi-structured interviews conducted with national, regional, and international experts engaged in EU initiatives, along with a synthesis of academic publications, EU official documents, and recent reports. Research reveals the changes in EU water policy in Central Asia since the 2000s, including shifts in objectives, the scale of cooperation, and the interplay between EU policies and the perceptions, responses, and shaping by regional actors. The EU has successfully promoted certain norms of ‘good water governance,’ and Central Asian countries have, to a certain degree, adopted them in their policies and legal frameworks. However, The EU's reliance on soft tools and multi-stakeholder dialogues, limited financial commitments, coordination challenges, and local political constraints have constrained its impact on the ground. This situation has created a palpable sense of 'dialogue fatigue' among national stakeholders. The contextual disparities, divergent interests, and issues at stake between the EU and Central Asian countries pose significant obstacles to transferring EU experiences and practices. Central Asian actors' responses to EU water initiatives, amid the influence of the external and internal political environment, bear implications for sustainable water management. These implications are particularly pressing given the region's vulnerability to climate variability, the geopolitical landscape, and the countries' capacity to navigate multiple crises.
PYRAMID: A Platform for dynamic, hyper-resolution, near-real time flood risk assessment integrating repurposed and novel data sources
Authors: Green Amy , Lewis Elizabeth , Tong Xue , Wang Shidong , Smith Ben , Fowler Hayley
Published: March 2024

It is essential that we work towards better preparation for flooding, as the impacts and risks associated increase with a changing climate. Standard methods for flood risk assessment are typically static, based on flood depths corresponding to return levels. In contrast flood risk changes over time, with the time of day and weather conditions, driving the location and extent of potential debris (e.g. vehicles or trees may cause blockages in culverts) affecting the associated risks. To this end, we aim to provide a platform for dynamic flood risk assessment, to better inform decision making, allowing for improved flood preparation at a local level. With stakeholder collaboration at a local level, a web-platform demonstrator is presented, for the city of Newcastle upon Tyne (U.K.) and the wider catchment, providing interactive visualisations and dynamic flood risk maps.To achieve this, near real-time updates are incorporated as part of a fully integrated workflow of models, with traditional datasets combined with novel, hidden data. More realistic high-resolution data, citizen science data and novel data sources are combined, making use of data scraping and APIs to obtain additional sensor data. Using machine learning methods, more complex datasets are generated, using artificial intelligence algorithms and object detection to identify potential debris information from satellites, LIDAR point clouds and trash screen images. The model framework involves hyper-resolution hydrodynamic modelling (HIPIMS), with a hydrological catchment model (SHETRAN), working towards a digital twin.
Ensemble forecasts of marine flood maps assisted by probabilistic machine learning techniques: Application at Arcachon Lagoon (France)
Authors: Rohmer Jeremy , Membrado Eva , Lecacheux Sophie , Idier Deborah , Filippini Andrea , Pedreros Rodrigo , Dalphinet Alice , Paradis Denis , Ayache David
Published: March 2024

Recent advances in high performance computing have enabled numerical weather prediction systems to move from deterministic to probabilistic forecasting using Ensemble Prediction Systems (EPS). While EPS are increasingly used to predict river flows and induced floods in several countries, it is only emerging for marine flooding. Despite ongoing efforts to develop new generations of high performance hydrodynamic models accounting for complex processes, the main challenge still remains the computer power required to run multiple simulations with a chain of models of increasing resolutions (from a hundred meters for water level at the coast, to a few meters for coastal waves and marine flooding). To overcome this limitation, the machine-learning-based metamodelling approach has made great progresses in this field of application.Through a statistical analysis of pre-calculated training databases, metamodels can predict key flooding indicators (surge, discharge, water depth, etc.) at a given spatial locations of interest within reasonable time and computing resources while preserving the accuracy of full process models. Yet, some issues remain to push this approach toward operational applications: (1) the production of spatialized indicators with metamodels such as inland water depth maps, (2) the characterization of the cascading sources of uncertainties throughout the entire chain.To address these difficulties, we use a set of numerical simulation results of about 200 flood maps computed on the Arcachon Lagoon (Gironde, France) for a large variety of randomly-generated metoceanic forcing conditions (surge, tide, wave and wind). On this basis, a metamodeling procedure is developed by combining a non-linear dimension reduction method relying on deep-learning-based autoencoders, denoted AE (to represent the very high-dimensional spatialized output) and on Gaussian process (Gp) regression (to model the link between the metoceanic forcing conditions and the flood response). Cross validation and comparison to historical real cases (such as storms Xynthia and Klaus) show satisfying predictive capability. However, the concern is the model uncertainty that affects the different steps of the whole metamodeling procedure. To quantify it, we rely on a stochastic approach that combines conditional Gp simulations with AE random responses using Monte Carlo Dropout method. In order to discuss predictive uncertainty to support decision-making for real-time forecasts, we compare the impact of metamodelling uncertainty with that induced by the variability of metoceanic forcing conditions which are modelled on the basis of the Meteo-France ensemble named PEARP "Prévision d'Ensemble ARPege" for recent storm events, as well as for synthetic marine inundation events.
Climate change variability and its implications for rising GLOF risk in the Kinnaur district of Himachal Pradesh, India
Authors: Singh Divya , Joshi Varun
Published: March 2024

Recent studies on climate change in the fragile landscapes of the Indian Himalayan Region showed that they are highly sensitive to climatic variability. Glaciers, snow, and permafrost, all interact and respond to climate in distinct ways and there is continual concern about current and projected climate change implications. Floods, landslides, glacial lake outburst floods (GLOFs), and shifting precipitation patterns are all potential hazards in the Kinnaur district. These risks have the potential to disrupt the region's socioeconomic fabric and imperil human lives, infrastructure, agriculture, and ecosystems. The Kinnaur district of Himachal Pradesh, India, remains susceptible to the impending threat of GLOFs, as evidenced by its turbulent history marred by devastating flood disasters in 1997 and 2005. This study aims to examine temperature and rainfall variability to imply a notional link between climate change and the spatio-temporal dynamism of glacial lakes in the area. Therefore, using the Mann-Kendall (MK) test and the Sen's slope test trend analyses are performed for 30 years (1990 to 2020) using gridded rainfall and temperature data of the district corresponding to yearly scales. The trend results were then correlated with the spatial area percentage change in the glacial lakes present in the district. The pertinent knowledge on climate change-associated hazards will assist stakeholders and policymakers in boosting resilience to climate change and concealing the socioeconomic and environmental systems amidst the mountain GLOF hazard risks.
Extended Kalman filtering applied to high-rate GNSS-R sea level measurements
Authors: Pira Aurélien , Santamaría-Gómez Alvaro , Woppelmann Guy
Published: March 2024

Coastal water monitoring is of increasing importance for applications such as sea level monitoring and urban planning. Currently, traditional tide gauge by radar measurement remains the most widely used method, but it involves placing a sensor close to the water surface, which can lead to its destruction, particularly in hostile maritime environments.Sea level measurement by GNSS-R offers a promising alternative to traditional tide gauge methods by enabling continuous and global sea level measurements (e.g., Larson et al., 2013). It has the significant advantage of limiting the constraints linked to the installation of sensors physically close to the water surface, as a GNSS antenna can be placed away from the coast or on a high structure. Furthermore, this technique takes advantage of the high availability of existing GNSS installations around the globe, which would make it possible to considerably extend the scope of tide gauge measurements on a global scale.Most of the methods used in GNSS-R are based on the analysis of the signal/noise ratio (SNR). They generally use a spectral analysis based on a Lomb-Scargle periodogram and are effective for monitoring mean sea level at the centimeter level (e.g., Larson et al., 2013; Santamaría-Gómez and Watson, 2017; Peng et al., 2021). However, they require a relatively long portion of the SNR series to obtain a precise estimate of the oscillation frequency of the SNR signal. This has the effect of limiting the sampling rate of the measurement series and limits spectral methods to the observation of slow variations in sea level such as the tide. Other approaches use Kalman filtering and show that it is possible to achieve an accuracy of less than 5cm in near real time (e.g., Strandberg, Hobiger and Haas, 2019; Liu et al., 2023). Furthermore, these methods show that it is possible to considerably increase the data sampling rate and thus monitor rapid variations in sea level. This extends the scope of GNSS-R techniques to all applications requiring real-time sea level measurement.We present a novel approach for measuring sea level by analyzing SNR signals with Kalman filtering. This approach relies on the estimation of the oscillation frequency and amplitude of SNR signals using an extended Kalman filter. It has the advantage of providing sea level height estimates at a sampling rate as high as the SNR measurements. The major constraint linked to the method lies essentially in the estimation of the initial phase of the SNR signals, which particularly affects the fit of the SNR signals from setting satellites.GNSS-R measurements were carried out with a sampling frequency of 1 second and compared to those of a tide gauge colocated on the Aix Island ILDX site (France). By combining data from different existing GNSS systems (GPS, GLONASS, Galileo, BDS) and considering all available carriers, we estimate that it is possible to obtain an RMS error of less than 5cm on sites with high tidal ranges (± 6m).
Simulating ground temperatures in mountainous terrain with remote sensing observations and modeling
Authors: Scherler Dirk , Langer Moritz , Wulf Hendrik , Gök Deniz , Phillips Marcia
Published: March 2024

The warming of high mountain regions caused by climate change leads to decreasing snow cover and thawing permafrost, which has far-reaching effects on ecosystems and societies. In this study, we used historical observations of land surface temperature (LST) derived from Landsat satellite data in conjunction with 1-D thermal modeling to simulate the annual evolution of ground temperatures. Our model includes precipitation and the evolution of snow cover, which exerts important control on ground temperatures. We tested this approach in the European Alps, where snow depth observations from high-elevation sites in Switzerland allowed us to evaluate the performance of different precipitation data sets and a simple scheme for snow removal by avalanches. We assessed our model results by comparing them with existing temperature measurements at boreholes and with Landsat-derived snow cover frequencies. All our analysis is based on daily conditions, but averaged over multiple years, hence neglecting interannual variability. Preliminary results indicate generally good agreement between modelled and observed values at weather stations, depending on the used precipitation data set and the sensitivity of the simple snow avalanche scheme. Typical root-mean-square errors (RMSE) are (1) ~2.7 K for daily ground surface temperature, (2) ~50 cm for daily snow depth, and (3) ~25% for monthly snow cover frequency. Typical RMSE for borehole temperatures are ~2 K at depths >1 m, and somewhat higher, at ~4 K for shallow depths (
Exploring Seismoelectric Interface Responses at Poroelastic/Elastic Boundaries: numerical and experimental approaches
Authors: Bernardo Natael , Martins-Gomes Victor , Bordes Clarisse , Brito Daniel
Published: March 2024

Seismoelectric effects, arising from the interaction between seismic waves and electromagnetic fields, have attracted considerable scientific interest for their potential applications in subsurface characterization, geothermal exploration, and hydrocarbon prospecting. While most of previous research has predominantly focused on fluid/poroelastic and poroelastic/poroelastic interfaces, there has been a notable knowledge gap regarding the behavior of seismoelectric signals at poroelastic/elastic interfaces, a crucial aspect in many geological scenarios. This study addresses this gap by providing concrete evidence of interface responses within poroelastic/elastic transitions through experimental measurements of seismoelectric coseismic and interface responses. The experiments were conducted using a plastic container filled with Landes sand as the poroelastic medium, saturated  with NaCl. The container featured distinct interfaces with four different elastic media: glass, plastic, aluminium, and granite, as well as a poroelastic medium (Vosges sandstone) for comprehensive analysis.
The experiments were conducted separately for each interface, with specific focus on two different pore fluid conductivities (36 μS/cm and 100 μS/cm). Furthermore, numerical simulations enable a direct comparison between experimental data and theoretical predictions, leading to an excellent agreement between measured and simulated  data in particular regarding the amplitude and polarity of the seismoelectromagnetic signal generated at poroelastic/elastic interfaces. The present demonstration of the electromagnetic signature at poroelastic/elastic boundaries contribute to the overall understanding of seismoelectric phenomena, enhancing the toolkit available to geophysicists and improving the accuracy of subsurface assessments. 
Enhanced tropical cyclone inflow flood forecasts by using deep learning and spatial‑temporal information
Authors: Liu Li , Xu Yue-Ping , Gu Haiting
Published: March 2024

Reliable Tropical Cyclone (TC) precipitation and flood nowcasting play an important role in disaster prevention and mitigation. Especially for small-scale reservoirs, timely and accurate inflow forecasts are required to provide safe space for capturing high flows without having to resort to hazardous and damaging releases. Numerous studies have investigated the ability of deep learning in TC precipitation nowcasts. However, few of them focus on the skill of deep-learned TC precipitation forecasts in inflow flood forecasts. In this study, a novel framework is developed by introducing TC track information together with antecedent precipitation in the Convolution LSTM model (PTC-ConvLSTM). The ConvLSTM forecast precipitation is then input to an event-based Xinanjiang hydrological model for inflow flood forecasting, and the propagation of errors from TC track forecasts to inflow forecasts is further analyzed. The results show that TC track information enables a further 5% improvement compared to outputs from ConvLSTM with only precipitation information. PTC-ConvLSTM precipitation nowcasts present a probability of detection (POD) greater than 0.34 for a threshold of 5mm/h in a lead time of 6h. The nowcasts-driven flood forecasts have an NSE greater than 0 with a lead time of 5h at least. It is also indicated that the 100km error in TC track forecasts could generally result in a 10% degradation in precipitation forecasts and a further 8% deterioration in the driven flood forecasts. The effectiveness of our model indicates that the precipitation nowcasts from deep learning have strong applicability in disaster mitigation.
Current deficiencies and potential for improvement in the realisation of consistently combined Earth Orientation Parameter time series
Authors: Seitz Florian , Kehm Alexander , Bloßfeld Mathis , Duan Bingbing , Hugentobler Urs , Dill Robert
Published: March 2024

Accurate knowledge of the Earth’s orientation and rotation in space is essential for a broad variety of scientific and societal applications such as near-Earth and deep space navigation, global positioning and satellite orbit determination as well as monitoring geodynamics and climate change phenomena. Consequently, an essential basis for any of the above-mentioned applications is the accurate determination and prediction of Earth Orientation Parameters (EOP), which describe the instantaneous relation between reference frames fixed to the Earth and to inertial space at any epoch. High-precision EOP are determined by combining the observations of four different geodetic space techniques.Due to different standards for the processing of the observations – most notably the parameterisation of the EOP in the observation-type-specific processing softwares – current EOP combination approaches lack consistency. Such inconsistencies represent a major limiting factor of today’s accuracy of determined EOP as well as of short-term EOP predictions, which are an essential prerequisite for any application in (near-)real time.This study identifies current deficiencies that limit the consistency and achievable accuracy of combined EOP series. It provides recommendations on how to improve the parameterisation and processing standards of the technique-specific input, and it outlines strategies to achieve a more consistent and accurate EOP combination. The proposed processing strategies shall serve as a basis for improved EOP prediction algorithms in a later stage of the study.
Deformed archeological remains at Lilybaeum in Western Sicily (southern Italy) as possible ground signatures of coseismically-slipped fault in the area
Authors: Giovanni Barreca , Fabrizio Pepe , Attilio Sulli , Gabriele Morreale , Salvatore Gambino , Maurizio Gasparo Morticelli , Sabrina Grassi , Carmelo Monaco , Sebastiano Imposa
Published: March 2024

Archaeoseismic analysis performed in Western Sicily point to deformed archeological remains at Lilybaeum, a Punic coastal city founded in 397 B.C. at the Island’s westernmost edge. Starting from the direct observation of deformed ruins, an interdisciplinary work-strategy, which has included field-structural analysis, drone-shot high-resolution aerial photogrammetry, and geophysical prospecting, was employed to investigate whether the identified deformations may represent the ground effects of a previously unknown large earthquake in the area. Among the unearthed remains, some mosaics and a stone-paved monumental avenue show evidence of tectonic deformation being fractured, folded, and uplifted. Trend of folding and fracturing is consistent with the NNW-SSE oriented tectonic max stress axis to which western Sicily is currently undergoing. Displacement along a fracture deforming the Decumanus Maximus together with the finding of a domino-type directional collapse, enable us to interpret the observed deformation as the ground signature of a coseismic slip. Seismic rupture occurred along a previously unmapped deformation front that well fits in the seismotectonic context of Western Sicily. Measured offset, geophysical prospecting, and age-constraints all point to the possibility that a highly-energetic earthquake nucleated in the area following a coseismic rupture along a NE-SW trending back-verging reverse fault towards the end of the IV century A.D. Since seismic catalogs do not provide evidence of such a large earthquake, the latter might represent a missed event in the historical seismic record. This finding provides constraints to redefine the seismic hazard of Western Sicily, a region where recurrence-time intervals for large earthquakes are still unknown.
Numerical modelling of the Montenegro tsunami of 15 April 1979
Authors: Kapitanovic Vedran , Sepic Jadranka , Pasaric Miroslava , Heidarzadeh Mohammad
Published: March 2024

On April 15, 1979, the coastal region of Montenegro was shaken by a devastating earthquake (M = 6.8, Modified Mercalli Intensity = IX-X). Towns and villages were severely damaged, numerous cultural heritage sites were destroyed and around 150 people were killed. The hypocenter was in the sea near the coast between Bar and Ulcinj at a depth of 13 km. The earthquake triggered a tsunami, which was registered by several tide gauges. The strongest waves with an initial height of 45 cm were registered in nearby Bar, where oscillations lasted for more than 24 hours. Tsunami waves of up to 10 cm in height were also recorded on the opposite Adriatic coast, at the Bari (Italy) tide gauge. According to newspaper reports, the tsunami had a strong impact along the Montenegrin coast, with waves reaching a height of up to 3 metres and one person drowning. The numerical model COMCOT (Cornell Multi-grid Coupled Tsunami model) was used to simulate the tsunami. Since various parameters for the earthquake source fault parameters are given in the literature, with varying values for the location of the epicentre, the depth, the earthquake magnitude, and the properties of the nodal plane, we carried out a series of simulations by considering a reasonable range for each parameter. The simulations differed in the parameters of the earthquake source - as given in the literature, as well as in the length and width of the fault plane. The simulation that best reproduced the waves recorded at the tide gauges was selected as representative and was further analysed to determine maximum heights, currents, inundation areas and tsunami propagation in the Adriatic Sea.
Spatial and temporal exploration of lake-water humic DOM quality - from the Northern hemisphere
Authors: Brecke Gundersen Cathrine , Austnes Kar , de Wit Heleen A.
Published: March 2024

A widespread increase in the level of dissolved organic matter (DOM) in lakes has been documented across the northern hemisphere. Interestingly, a corresponding increase has not been seen in elements that are typically strongly linked to DOM (e.g., nitrogen, phosphorous, mercury, iron, and aluminium). This has been hypothesized to result from changes in the quality of the DOM.
Here, we explore the link between DOM quality and temporal change in selected water chemical parameters  (generalised additive model). The study sites cover 400 lakes across Norway, providing large gradients in climate, atmospheric deposition, land cover, and primary productivity. At two timepoints (years 1995 and 2019) the lakes were sampled and the water chemistry determined, while the quality of DOM was described in 2019 only. DOM qualitative parameters covered fluorescence parallel factor analysis (PARAFAC) model components, fluorescence indices (BIX, HIX), light absorption indices and slope ratios (e.g., sUVa, A250_364), and biodegradation rate constants derived from incubation experiments.  
Temporal changes in the lake-water chemistry covered declines in elemental ratios of nitrogen-to-carbon, iron-to-carbon, and non-labile aluminium-to-carbon. For iron and nitrogen, strong regional variations were observed (de Wit et al., 2023).
The three PARAFAC components explained 72% of the spatial variation in the 2019 dataset of selected catchment and water chemistry descriptors (partial least square regression analysis). The characteristics of the underlying fluorophores were identified to be 1) allochthonous humic matter of terrestrial origin, 2) autochthonous humic matter that had been microbially or photochemically altered, and 3) humic matter with larger size and more hydrophobic and aromatic character than component 1. This was found from matches with the OpenFluor database and further substantiated through strong correlations within the dataset.
Preliminary investigations show strong links between temporal change in the nitrogen-to-carbon ratio and component 1 as well as to the fluorescence humification index (HIX), the light absorption slope ratio (A250_364), and to the fraction of forest in the catchment. For iron-to-carbon, the temporal change can be linked to component 2 as well as to the light absorption index, sUVa. These findings can support the hypothesis of changing DOM quality.
The establishment and use of local coastal water boards is tested in Denmark to find bottom-up solutions for RBMP 2027
Authors: Windolf Jørgen , Piil Kristoffer , Jørgensen Torben B. , Andersen Hans E. , Dalgaard Tommy , Kronvang Brian
Published: March 2024

The Danish EPA has in the 3rd River Basin Management Plan (RBMP) under the Water Framework Directive set target nitrogen loads for each coastal water for how to reach the reduction needed from coastal catchments to be implemented in 2027. In this context four locally based pilotprojects have been initiated to engages stakeholders to find local solutions for the RBMP. One of these new pilots are focusing on the Hjarbæk estuary situated in Limfjorden being one of the coastal water bodies in Denmark that needs the highest reductions in nitrogen loadings to be achieved before 2027 (ca. 65 %). This new project involving a coastal water board with all main stakeholders in the region being represented was initiated in February 2023 and has delivered proposals for 2 scenarios by the end of 2023 that can assure that the Hjarbæk estuary reach the target of achieving good ecological conditions.Because of the high reductions in nitrogen loadings needed it is necessary to reduce all sources and both nitrogen and phosphorus to reach the goal. Focus in the RBMP has so far been to reduce the total nitrogen (TN) loadings. In the locally based scenarios phosphorus has gained greater focus. Our calculations show that every ton of phosphorus that is removed corresponds to removing 22 tons of nitrogen in Hjarbæk Fjord.  To be most cost-effective the effort will be carried out based on the principle of achieving the greatest possible effect per area unit. For that a detailed mapping of nitrogen (N) attenuation in the catchment have been conducted at a scale of ca. 15 km2 (ID15 sub-catchments) including mapping of both N-retention in groundwater and surface waters as well as N-delays in groundwater in Karst sub-catchments. The mapping shows huge differences in N-retention in both groundwater and surface waters within the ID15 sub-catchment (80 %).The local engagement of stakeholders representing all sectors in the catchment and estuary have worked together to set up two scenarios that includes: i) marine mitigation measures such as mussel farming and eelgrass planting; ii) reductions in point source loadings; iii) use of a new portfolio of N mitigation measures to be adopted at source (e.g. catch crops, early seeding, set a side, afforestation, etc.); iv) use of transport mitigation measures from field to surface water (several types of constructed wetlands, riparian buffers and restored wetlands); v) the possible use of different phosphorus mitigation strategies in the catchment (lowering bank erosional P-losses, buffer strips, afforestation, etc.).
Dynamics and controls of a tropical slow moving landslide measured by remote sensing: the study case of Grand Éboulis, Réunion Island. 
Authors: Hopquin Coline , Gayer Éric , Michon Laurent , Smittarello Delphine , Lucas Antoine
Published: March 2024

Landslides are efficient erosion processes that release large volumes of sediments in rivers, posing threats to nearby population when remobilised during large flood events. Thus, understanding the dynamics and controls of landslides and quantifying the volumes involved in subsequent sediment transfer are crucial for resilient development in mountainous settings.In this study, we use the very high standing island of Réunion (Indian Ocean) as a natural laboratory to investigate the interaction between landslides, sediment transfer and climatic forcing. This volcanic island, characterised by mountainous landscapes resulting from intense river incision and frequent landslides, shows physical erosion and chemical weathering rates exceeding most of active mountain belts (Gayer et al, 2019). Here, we focus on studying the Grand Éboulis landslide short-term (i.e bi-monthly) and mid-term (i.e multi-decennial) dynamics using SAR imagery and photogrammetry. First, we computed cumulative displacement maps and time series using the AMSTer software and Sentinel-1 StripMap images acquired every 12 days between 2017 and 2021. These time series reveal velocity fluctuations, including acceleration and/or deceleration episodes, correlated with extreme climatic events such as intense precipitation and drought episodes. Furthermore, from 2017 to 2021, Grand Éboulis exhibited a characteristic slow-moving landslide behaviour with a consistent eastward movement of up to 14 cm/year, coupled with continuous subsidence of up to 9 cm/year. The mid-term dynamics of Grand Éboulis, spanning from 1950 to 2011, was investigated using a series of nine Digital Surface Models (DSM). Each DSM was derived from historical aerial photographs obtained by the French National Institute of Geographic and Forest Information (IGN) and processed through the photogrammetric workflow of Lucas and Gayer (2022). Preliminary findings indicate numerous catastrophic failures in or near the steepest slopes of the landslide that experience the highest velocity gradients. The sediment volumes involved in such events range from a few tens of thousands to millions of cubic meters, predominantly released into the nearby river and transported away from the landslide.Our results suggest that the Grand Éboulis landslide is in an active mobilisation phase with a continuous slow displacement primarily influenced by extreme climatic events and with catastrophic failures that release large volumes of sediments in the nearby river.
Deciphering Fossilization Pathways: Sediment Composition Impacts Biofilm-Forming and Biomineralizing Microbial Communities in Early Stages of Leaf Taphonomy
Authors: Palmer Brianne , Karacic Sabina , Bierbaum Gabriel , Gee Carole
Published: March 2024

The formation of leaf compressions is dependent on the type of sediment in which the leaves are buried and on burial depth because greater burial depth leads to a more anoxic environment conducive to fossilization. Recent research has hypothesized that the presence of a microbial biofilm on leaf surfaces in the early stages of decay also enhances preservation. In decaying leaves, the biofilm community is likely influenced by the same factors: sediment type and burial depth. Here we investigate experimentally the microbial community composition of microbial biofilms formed on floating and buried leaves of living Ginkgo in four sediment types—montmorillonite clay, kaolin clay, quartz sand, and pond mud. Leaves were placed in aquariums with pond water under identical light conditions and room temperatures for three months. The leaves, sediments, and pond water were then evaluated with 16S and ITS sequencing to identify the bacterial and fungal communities. We found that the biofilms on the floating and buried leaves differed in their basic microbial community composition. The leaves buried in the kaolin clay showed the most distinctive microbial communities, while the montmorillonite clay buried leaves contained several genera noted for biomineralization. In general, the buried leaves had microbial communities that were more diverse than those on the floating leaves and richer in anaerobic microbes and biomineralizers. These results suggest that biofilms form best in very fine-grained sediments with low organic content, such as kaolin and montmorillonite clays, and under burial conditions fostering anaerobic environments and the incorporation of minerals that enhance biomineralization on leaf surfaces. Our results provide new insights into the role of microbial biofilms and microbe–sediment interactions in the early stages of leaf fossilization.
Estimating GRACE-FO orbit perturbations with numerical weather prediction models
Authors: Motlaghzadeh Sanam , Vasiuta Maksym , Bister Marja , Navarro Trastoy Angel , Tuppi Lauri , Mayer-gürr Torsten , Järvinen Heikki
Published: March 2024

Satellites in Earth orbit are exposed to Earth radiation, consisting of reflected solar and emitted thermal radiation, thereby exerting a radiation pressure force that causes acceleration and affects the orbits. Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission aiming to retrieve the Earth gravity potential is critically dependent on accounting for all non-gravitational forces, including the Earth radiation. Although weather-of-the-day; e.g., clouds and their properties, has a major role in Earth radiation pressure, only climatology has been used so far to represent this force. Using climatological data doesn’t account for orbit perturbations owing to weather-related transient changes in the Earth radiation pressure. We show here that the top-of-atmosphere radiation fluxes computed with a numerical weather prediction model explain most of the measured variations in the radial acceleration of the GRACE-FO satellite. Our physics-based modelling corrects a hitherto unexplained lack of power spectral density in the measured accelerations. For example, we can accurately model the accelerations associated with a tropical storm in Indian Ocean in December 2020, which would not be possible when using climatological data. Our results demonstrate that using a global numerical weather prediction model significantly improves the simulation of non-gravitational effects in the satellites’ orbit. This advancement will allow more precise gravity retrieval and its applications in Earth sciences. 
Investigating phenological variability of beech forests across Europe using satellite data 
Authors: Ferrara Carlotta , Bregaglio Simone Ugo Maria , Chianucci Francesco , Ricotta Carlo , Bajocco Sofia
Published: March 2024

Climate change has a major impact on the current environment, with vegetation phenology being the earliest indicator of these effects. Long-term phenological observations, such as those provided by satellite remote sensing, are fundamental for understanding spatio-temporal forest dynamics. Normalized Difference Vegetation Index (NDVI) data represent a well-known proxy for monitoring forest productivity and detecting seasonal variations. The objectives of this work are to identify phenological clusters of beech forests, and to quantify the role of geographic and physiographic variables in the phenological timing of each cluster.  The research focuses also on examining the influence of environmental variables on the mechanisms of phenological response to climate change. To this end, we used the EU-Forest dataset to derive the beech forest location across Europe. Then, for each location, NDVI data were extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua sensors, from 2003 to 2023, with spatial resolution of 250 m and temporal frequency of 8 days. To identify groups of different forest types with similar seasonal timing (i.e., pheno-clusters), we carried out K-means Cluster Analysis on the NDVI temporal profiles. Finally, we characterized each pheno-cluster based on latitude, elevation, temperature, and precipitation, to identify gradients and discriminant environmental conditions. Results showed that the obtained pheno-clusters follow a clear elevation gradient, with a high variability at local scale even within the same macroclimatic conditions. This study indicates that characterizing vegetation phenology can provide valuable information about how forests ecosystems respond to both environmental conditions and climate change.