bluuebunny/crossref_metadata_2025 huggingface dataset:
Aerial Laser Scanning for Forest Change Assessment: An Evaluation Framework for Forest Change Map Products
Authors: Capobianco Samuele , Piccardo Matteo , Migliavacca Mirco , Cescatti Alessandro
Published: March 2024

Accurate mapping of forest cover changes is essential for monitoring the health of the vegetation, evaluating the forests' capacity to store the carbon dioxide absorbed from the atmosphere, and comply with international sustainable forest management goals. In the literature, the Global Forest Change product proposed by Hansen and estimated at a 30 meters spatial resolution from Landsat optical data is a widely used dataset for detecting forest loss. Another widely used approach involves studying how a Land Use/Land Cover (LULC) product changes over time. In this regard, the partnership between Google and the World Resources Institute (WRI) has led to the development of the Dynamic World dataset which provides LULC information at a high spatial resolution of 10 meters and a daily temporal frequency, estimated from Sentinel 2 optical data. These change maps are essential for researchers worldwide monitoring dynamic shifts in forest landscapes. Among various Earth observation (EO) technologies, Light Detection and Ranging (LiDAR) scanning stands out for its potential in obtaining detailed information on forest structures over large geographical areas with high spatial resolution and accuracy. Airborne LiDAR scanning data can be used to measure the height of trees above the ground topography producing Canopy Height Models (CHMs). This work proposes a robust procedure for CHM computation at the desired spatial resolution using the LiDAR point cloud detected by Aerial Laser Scanning (ALS) in the area of interest. The differences between CHMs at different observation times define tree cover change maps with high accuracy in the specified area. The study employs publicly available ALS data covering Estonia to calculate CHMs with a spatial resolution of 5 meters. Utilizing these data, we compute high-definition tree cover change maps in the temporal window between 2018 and 2021 providing an accurate quantification of forest loss. The resulting tree cover change maps play a crucial role in evaluating widely used forest change maps such as Global Forest Change and Dynamic World derivatives. Through the establishment of a robust evaluation framework, including the comparison of common metrics (e.g. commission and omission error) with existing forest change maps, the study contributes significantly to the reliability analysis of forest change map products. The research addresses challenges in quantifying regional forest changes and offers valuable insights for researchers and policymakers engaged in sustainable forest management.
Long-term soil warming causes acceleration of soil nitrogen losses in a temperate forest studied by 15N isotope fractionation
Authors: Wanek Wolfgang , Bachmann Michaela , Tian Ye , Kwatcho Kengdo Steve , Heinzle Jakob , Inselsbacher Erich , Borken Werner , Schindlbacher Andreas
Published: March 2024

Climate warming was shown to strongly affect the biogeochemical cycles in global forests, reducing soil carbon storage and accelerating soil nitrogen (N) and phosphorus cycling. In a long-term soil warming experiment in a temperate old-growth forest in Achenkirch, Austria, we recently showed faster root turnover and growth, decreases in microbial biomass, carbon use efficiency and soil carbon storage, increases in ecosystem phosphorus limitation, and varied responses of the soil N cycle in warmed plots (+4 ° C above ambient for 14 years). In this study we therefore employed natural stable isotope techniques to better understand ecosystem-level responses of the N cycle in Achenkirch, studying the abundance of 15N and 14N (expressed as δ15N values) in a wide range of soil nitrogen pools (bulk soil N, root N, microbial biomass N, extractable organic N, ammonium, nitrate) and employed isotope fractionation models to explain the patterns found dependent on soil warming. Specific N cycle processes such as mineralization, nitrification and denitrification cause substantial isotope fractionation (against the heavy stable isotope 15N), leading to 15N enrichment of the residual substrates and 15N depletion of the cumulative products, depending on the fraction on substrates consumed and the isotope fractionation factor of that process. Other processes such as diffusion, (de)sorption and depolymerization exert negligible isotope fractionation. We found a significant warming effect on the isotopic signatures of root N and the soil ammoniumpool, i.e. a 15N enrichment in these pools. 15N enrichment of tree fine roots, considered to be isotopic integrators of the plant available N pool, suggest increased soil N cycling and greater soil N losses in warmed plots causing a 15N enrichment of the soil inorganic N pool (ammonium and nitrate). The increased 15N enrichment in ammonium of warmed soils highlights an increased activity of nitrifiers, with greater fractions of ammonium oxidized to nitrate causing the observed 15N enrichment of ammonium. However, soil nitrate did not show the expected 15N depletion imparted by nitrifiers but matched or even exceeded δ15N values of soil ammonium. Isotope fractionation calculations indicated that >50% of the soil nitrate produced was lost, particularly through denitrification promoting gaseous N losses in the form of NO, N2O and/or N2 and less through nitrate leaching. Natural 15N abundance studies thereby hold great potential for evaluating the status quo of the complex N cycle in terrestrial ecosystems and to monitor in situ responses to climate change with minimal invasion and improved time integration.
Adaptive mesh joint inversion using seismic body and surface wave data: Method and Application
Authors: Liu Ying , Fang Hongjian , Yao Huajian , Zhang Haijiang
Published: March 2024

Seismic tomography using body or surface wave data is a powerful tool to explore the structure of Earth’s interior structure. In recent decades, joint inversion of seismic body and surface wave data has been widely employed to investigate seismic velocities of the Earth’s lithosphere and asthenosphere. Benefited from the complementary sensitivities of different datasets, seismic velocities determined by joint inversion generally exhibit higher resolution and accuracy. Regular mesh (cell or grid) is commonly used in seismic tomography. As data distribution is uneven in most cases, regularization techniques are implemented in regular mesh seismic tomography method to stabilize ill-posed problems. Despite the selection of appropriate regularization parameters, it is also challenging to achieve multiscale resolution in regular mesh joint inversion method. In this study, we developed a joint inversion method using adaptive irregular mesh according to the real data distribution based on Poisson-Voronoi cells. Synthetic tests show that the newly developed method can better resolve multi-scale structures without regularizations. We applied this method to a dataset with seismic arrays in different scales. The newly determined multiscale velocity model reveals distinct features particularly in areas with dense data distribution.
Impact of ice nuclei on deep convection in Saudi Arabia's Southwest mountains
Authors: Gunturu Udaya Bhaskar , Aldhaif Abdulmunam , Abandeh Khalid
Published: March 2024

Within the Southwest mountainous region of Saudi Arabia, orographic convection, fueled by the substantial elevation rise, generates copious rainfall. However, due to the high cloud bases in this complex terrain, precipitation formation predominantly depends on a cascade of intricate mixed-phase processes. Consequently, ice nucleation, and the subsequent chain reactions it triggers, play a pivotal role in shaping the region's precipitation regime. This study leverages a state-of-the-art three-dimensional cloud-resolving model to simulate representative deep convective events. By meticulously examining the model's response to varying ice nuclei concentrations, we aim to shed light on the mechanistic pathways leading to mixed-phase processes and their critical role in governing precipitation formation. By systematically manipulating ice nuclei concentrations within the simulations, we will comprehensively assess the sensitivity of these mixed-phase processes to changes in nucleation availability. Our analysis will delve into the evolution and interplay of cloud microphysical processes under different ice nuclei concentrations, presenting and discussing the simulation results in detail.
 
The effect of ice damage on future Antarctic projections
Authors: Blasco Javier , Li Yanjun , Coulon Violaine , Pattyn Frank
Published: March 2024

The Antarctic Ice Sheet (AIS) is the largest ice sheet and hence the potentially largest contributor to future sea-level rise. However, the AIS represents also the largest source of uncertainty regarding future projections. One of the main sources for this uncertainty are the floating ice shelves. While these ice shelves do not directly contribute to sea-level rise, they play a major role in the dynamics of the AIS. By transmitting resistive stress to the grounding line, they are capable of slowing down inland ice. If ice shelves disintegrate, this buttressing effect disappears, promoting the flow of inland ice into the ocean. Thus, the assessment of ice shelf stability in future scenarios becomes crucial for accurate predictions.One key element which is often overlooked is the formation of ice fractures. Satellite images display increased crevasse formation on Antarctic ice shelves and grounded ice near the grounding line over the past decade. These fractures, referred to as damage, impact the ice flow by reducing its viscosity. Reduced viscosity enhances ice flow, leading to higher strain rates which further promotes more damage formation. However, despite its known effect, its application has been only done on idealized domains so far.Here we will assess the damage sensitivity of a three-dimensional ice-sheet-shelf model in a simplified, symmetric case (MISMIP+ domain) and a complex real-world scenario such as the Amundsen-Sea Embayment (ASE). For this we will test three different damage formulations from literature which account for explicit crevasse formation. In addition, we will also test a new regularization approximation in our viscosity formulation. This approximation ensures that if no damage is applied, then the effective yield strength of our model cannot exceed the failure strength of ice.Our findings reveal that incorporating damage or viscosity regularization into future projections of the ASE results in higher sea-level contribution and faster grounding-line migration. This underscores the critical need to enhance our understanding of damage and its implications for future sea-level rise, since current projections do not account for this process.
Non-destructive moisture monitoring of historical load-bearing structures with Thermography, Ultrasound and Ground Penetrating Radar
Authors: Esel Yunus , Schulte-Kortnack Detlef , Erkul Ercan , Meier Thomas
Published: March 2024

Restoration or maintenance of historical monuments and buildings require profound knowledge of the history of the structure and its internal properties. This task requires interdisciplinary efforts that minimize destructive approaches.Particularly moisture intrusions often pose significant threats for historic buildings. Thus, knowledge of the mechanisms of moisture ingress is of crucial importance for the realization of a sustainable and resource-saving restoration.  A usual way to get information about the inner conditions of the examined object is by removing material selectively by core drillings. The drillings are supplemented by a visual assessment and evaluation of the changes near the surface. However, this method is limited not only in the scale of the investigated area but also with respect to the depth of the investigated structure. Therefore, methods are needed allowing non-destructive and ideally rapid assessment of larger parts of the structure. An integrative approach is essential, not only to remedy acute damage, but also to take preventive measures and ensure the long-term preservation of historic buildings. The aim of this contribution is to demonstrate the feasibility of non-destructive geophysical measurements techniques for moisture detection during the renovation process, including Infrared Thermography (IR), Ultrasound (US) and Ground-Penetrating-Radar (GPR).  The focus is on adapting measurement principles from the field of geophysics to transfer them into practicable measurement and evaluation methods for historic buildings and detection of moisture.          We report on results obtained by geophysical investigations of objects in Northern Germany. Results show that it is possible to identify moisture and classify the non-visible internal properties of both brick masonry and timber structures non-destructively.  The combination of Ultrasound, GPR and Thermography allow to quantify and monitor material properties during restoration by repeated measurements. 
Extended seasonal forecast of Antarctic Sea Ice using ANTSIC-UNet
Authors: Yang Ziying , Liu Jiping , Grand Graversen Rune
Published: March 2024

Antarctic sea-ice variability affects the ocean and atmosphere both locally through thermodynamic processes and beyond the Antarctic regions remotely through dynamic processes, which may all change due to global warming. In this study, we develop the ANTSIC-UNet, a deep-learning model trained on physically enriched climate variables, to predict the extended seasonal Antarctic sea ice concentration of up to 6 months in advance. We assess the predictive skill of ANTSIC-UNet as regards linear trend prediction and anomaly persistence prediction in the Pan- and regional Antarctic areas using comparative analyses with two baseline models. Our results exhibit superior performance of ANTSIC-UNet for the extended seasonal Antarctic forecast. The predictive skill of ANTSIC-UNet is notably season-dependent, showing distinct variations across regions. Optimal prediction accuracy is found in winter, while diminished skill found during the summer can be largely attributed to the ice-edge error. High predictive skills are found in the Weddell Sea throughout the year, which suggests that regional Antarctic sea-ice predictions beyond 6 months are possible. We further quantify variable importance through a post-hoc interpretation method which indicates that ANTSIC-UNet has learned the relationships between SIC and other climate variables and the method therefore provides information on the physics of the model. At short lead times, on timescales of up to two months, ANTSIC-UNet predictions exhibit heightened sensitivity to sea surface temperature, radiation conditions and vertical atmospheric circulation conditions in addition to the sea-ice itself. At longer lead times, predictions are dependent on stratospheric circulation patterns at 7-8 months lead in addition to sea-ice. Furthermore, we discuss the potential of implementing physical constraints to enhance sea-ice-edge predictability.
REFLOW: An Open-Source Workflow for Renewable Energy Potentials
Authors: Pelser Tristan , Hoffmann Maximilian , Weinand Jann Michael , Kuckertz Patrick , Stolten Detlef
Published: March 2024

The evaluation of renewable energy potentials is growing in importance across multiple sectors, including in energy planning, industry, research, and policymaking. Despite the abundance of research into regional-scale wind and solar potentials, the lack of reproducibility and transparent workflows consistently challenges validity. Typically, various steps in renewable energy potential assessments are conducted separately, often employing various software tools. For example, data processing may be conducted in a python environment, whereas land eligibility analysis utilizes Geographic Information System (GIS) software, and wind or solar simulations rely on specialized power simulation software. This fragmentation, as well as a general trend of not making data and code openly available, impedes efficiency, and hampers scientific reproducibility and transparency. Our research introduces a novel, Python-based open-source workflow to address this issue, which employs a pipeline management module (Luigi) for handling tasks and dependencies, and Docker to facilitate deployment. The Renewable Energy workFLOW (REFLOW) encompasses the entire process of potential assessments, from data acquisition to result validation, including critical steps like land eligibility assessment, explicit turbine placement, and wind or solar simulation. The workflow’s modular nature allows for integration of various software modules and methodologies, enhancing its adaptability to various scenarios. REFLOW can be executed in multiple operating systems and requires no significant programming knowledge. We demonstrate REFLOW’s capabilities for a wind power potential assessment of the North Sea region, conducting ocean eligibility exclusions, explicit turbine placings, and a simulation of wind power generation for a period of ten years, using data from the ERA-5 reanalysis and Global Wind Atlas. The entire workflow is fully reproducible, including all data acquisition and processing steps. Thus, REFLOW constitutes a significant step towards versatile yet reproducible renewable potential analyses.
Modeling interactions of water fluxes with species and structural diversity in temperate forests
Authors: Bohn Friedrich J. , Attinger Sabine , Demir Gökben , Kihm Charlotte , Hildebrandt Anke
Published: March 2024

The ecosystem functions of temperate forests are expected to be severely affected by future climate change, in particular by hydro-meteorological extremes (heavy precipitation, droughts and heat waves), which will increase in frequency, duration, extent and magnitude. Previous studies have shown that both structural and tree species diversity can act as a buffer against the effects of climate extremes.
To better understand the influence of structural and tree species diversity, we use two models to analyse the influence of species and structural diversity on hydrological dynamics during recent drought events. The well-equipped experimental plots are located in central Germany and represent typical forests of the region. One of the models is the individual forest gap model FORMIND. Using a newly developed technique, it allowed us to analyse local heterogeneous patterns of carbon and water cycling, runoff and water stress and their relationship to structural and species diversity on a 2-metre scale. The second model is mHM, a mesoscale hydrological model with a parameterisation of the catchment area in which the field plots are located. We also used a coupled version of these two models for the analysis.
Our analyses show that only about half of the modelled water dynamics are driven by meteorological conditions and the LAI. The other half is driven about equally by functional and structural diversity. This new two-model and interdisciplinary workflow allows us to consider various soil-plant-atmosphere interactions in drought disturbed ecohydrological systems.
Trends in Antarctic Ice Speed 2014-2023 From Big Data Processing of Satellite Observations
Authors: Slater Ross A. W. , Hogg Anna E. , Dutrieux Pierre , Davison Benjamin J. , Rigby Richard
Published: March 2024

The speed at which the Antarctic Ice Sheet (AIS) flows from the continental interior to the ocean is a key indicator of its stability, and satellite-derived ice velocity measurements play a major role in our assessment of changes in ice dynamics. The Sentinel-1 constellation of synthetic aperture radar (SAR) satellites, part of the European Commission’s Copernicus program, has acquired repeat images of the AIS margins at a combination of 6 and 12-day intervals since 2014, leading to a dramatic improvement in the spatio-temporal resolution and coverage of key velocity measurements at the edge of the AIS.Such modern Earth observation satellites provide ever increasing volumes of data which can be used to study changes over time; however, this growing archive poses two key issues when performing timeseries analysis at continental scale. Firstly, generation of dense, pixelwise time series from thousands of successive observations, each stored in separate files corresponding to observation date, can require extremely large numbers of file reads, limiting computation speeds and increasing the memory required for data handling. Secondly, with ever increasing volumes of data, analysis must be able to scale effectively and easily handle out-of-core computation where datasets are larger than the available memory.In this study, we present results from an analysis pipeline built on the Xarray and Dask python packages, and deployed on a HPC service, which allows both large scale interactive analysis in Jupyter notebooks as well as traditional batch processing. We first use an ice velocity processing chain to generate Antarctic-wide mosaics of ice speed on a 100 m grid for each combination of 6 and 12-day Sentinel-1 repeat observation dates, using the GAMMA Remote Sensing software to derive ice displacements from offset tracking of the SAR image pairs. The resulting stack of 2-dimensional mosaics is then restructured into a 3-dimensional data cube with dimensions x, y, time to facilitate time series analysis, overcoming the issue of excessive file reads and memory requirements by storing chunks of time series data together using the Zarr storage format.Using this pipeline we investigate trends in ice speed across the AIS, performing time series outlier removal on 11 billion time series and subsequently calculating linear rates of change across both grounded and floating ice during the study period. We present the resulting map of ice speed trends and highlight time series of notable individual outlet glaciers and ice shelves.
Modelling marine heatwaves impact on shallow and upper mesophotic tropical coral reefs 
Authors: Colombi Nicolas , Kropf Chahan M. , Burger Friedrich A. , Bresch David N. , Frölicher Thomas L.
Published: March 2024

Coral reefs ecosystems, often compared to rain forests for their high biodiversity, are threatened by coral bleaching. Coral bleaching occurs when the symbiotic relationship between dinoflagellates and corals breaks under environmental stresses, notably high ocean temperatures. Thermal stress on coral reefs predominantly occurs during marine heatwaves, which can take place synchronously at the surface and subsurface, or asynchronously in either one of the two levels. Subsurface marine heatwaves tend to last longer with potentially higher cumulative intensities compared to their surface counterpart. However, to the best of our knowledge, no global coral bleaching model takes into account the variability between the thermal stress measured at the surface and the one experienced by coral reefs at their specific depth. Here we show that developing a marine heatwave impact model for shallow and upper mesophotic coral reefs, increased coral bleaching modelling accuracy by 4.7 ± 1.3% compared to a model using surface marine heatwaves. To define marine heatwaves at coral reef depth, we used trilinear interpolation using the GLORYS12 reanalysis temperature product. Our model provides coral bleaching values at times and locations where no record was taken, providing a global reconstructed dataset of coral bleaching with daily resolution from January 1st 1993 to December 31st 2020 in 9944 locations. Furthermore, our model indicates that since 1993 over 40% of coral reefs bleached. We anticipate this study to be a starting point for more accurate coral bleaching modelling. Observing that upper mesophotic coral reefs (30-50m) might be more threatened than shallow coral reefs, provides additional evidence to reshape our perception of upper mesophotic coral reefs as potential refugees from climate change.
Evaluating the simulation of extreme events with the land surface model CLM5.0 over Europe for 2018-2022: comparison with in situ and remotely sensed data
Authors: Bose Arpita , Poppe Terán Christian , Naz Bibi , Sivaprasad Visakh , Kollet Stefan , Hendricks Franssen Harrie-Jan
Published: March 2024

Climate change is expected to amplify the frequency and intensity of extreme events in the future. Recently there was a series of summers with heat waves and droughts over central Europe from 2018 to 2022, but also severe flooding in 2021. These events had substantial effects on agriculture, water resources, and human lives. To monitor and assess the impacts of extreme events, in situ and remote sensing data for soil moisture, evapotranspiration and carbon fluxes are important. In this study we evaluate simulation results by the Community Land Model (CLM, version 5.0) over the EUROCORDEX domain for past extreme events between 2018 and 2022 and analyze to which degree the model is able to reproduce low soil moisture levels, and changes in evapotranspiration, leaf area index and carbon fluxes in the areas most affected by the extreme event, on the basis of a comparison with in situ (e.g., ICOS) and remotely sensed (e.g., SMAP, MODIS) data. Additionally, we will compare CLM5.0 results to other land surface models, such as ERA5-Land, GLDAS, GLEAM. Our model setup over EUROCORDEX is driven by atmospheric forcings from the ERA5 reanalysis. The soil texture information is obtained from FAO at 10 km resolution and the land use data is from LULC from NCAR mapped to plant/crop functional types. It was found that CLM5.0 overestimates soil moisture and exhibits a wet bias compared to SMAP during heat waves. In addition, the comparison of measured evapotranspiration with CLM5.0 shows that drought stress response is underestimated by the model. A systematic underestimation or overestimation of the impact of past extreme events on the land surface would point to model limitations which is important to resolve to gain confidence in the simulation of future extreme events under conditions of climate change.
Stochastic temporal downscaling in Northeast Italy using convection-permitting climate models: from hourly to sub-hourly timescales
Authors: Caruso Maria Francesca , Dallan Eleonora , Fosser Giorgia , Borga Marco , Marani Marco
Published: March 2024

The statistical properties of rainfall at short durations are pivotal for many hydrological applications. Commonly available rainfall records nor km-scale model, i.e. Convection-Permitting Models (CPMs), do not provide rainfall data at the sub-hourly scales needed for many applications, such as hydrological modelling in small or urban catchments or landslide or debris-flow models. Motivated by the above considerations, in this application a statistical downscaling technique is proposed for inferring the rainfall correlation structure at sub-hourly scale by using hourly statistics from CPM simulations. The proposed approach is based on the theory of stochastic processes, which establishes statistical relationships between coarse-scale predictors and fine-scale predictands. To validate the temporally downscaled results against observations, here we use, as a benchmark, high-resolution rainfall records from a dense network of rain gauges in northeastern Italy considering aggregation timescales ranging from 5 minutes to 24 hours. We then explore how the downscaling method developed here, coupled with the Complete Stochastic Modelling Solution (CoSMoS; Papalexiou, 2018) framework, may be used to generate sub-hourly rainfall sequences that reproduce the observed short- and long-timescale variability. Applied to statistics for each month in a year, to reproduce seasonality, the proposed downscaling method appropriately reproduces the observed correlation structure at desired fine-scale resolution. Consequently, the rainfall generator used here, by exploiting the downscaled information from CPM runs, allows to generate rainfall records at the desired scale that may be used for evaluating risk and risk change scenarios, for example associated with debris flows.
Data-driven short-term forecast of suspended inorganic matter as seen by ocean colour remote sensing.
Authors: Vient Jean-Marie , Jourdin Frédéric , Fablet Ronan , Delacourt Christophe
Published: March 2024

Short-term forecasting (several days in advance) of underwater visibility range is needed for marine and maritime operations involving divers or optical sensors, as well as for recreational activities such as scuba diving (e.g. Chang et al 2013). Underwater visibility mainly depends on water turbidity, which is caused by small suspended particles of organic and mineral origin (Preisendorfer 1986). Modelling the fate of these particles can be complex, encouraging the development of machine learning methods based on satellite data and hydrodynamic simulations (e.g. Jourdin et al 2020). In the field of forecasting visibility, deep learning methods are emerging (Prypeshniuk 2023). Here, in continuation of Vient et al (2022) on the interpolation purpose, this work deals with forecasting subsurface mineral turbidity levels over the French continental shelf of the Bay of Biscay using the deep learning method entitled 4DVarNet (Fablet et al 2021) applied to ocean colour satellite data, with additional data such as bathymetry (ocean depths) and time series of main forcing statistical parameters like wave significant heights and tidal coefficients. Using satellite data alone, results show that 2-day forecasts are accurate enough. When adding bathymetry and forcing parameters in the process, forecasts can go up to 6 days in advance.ReferencesChang, G., Jones, C., and Twardowski, M. (2013), Prediction of optical variability in dynamic nearshore environments, Methods in Oceanography, 7, 63-78, https://doi.org/10.1016/j.mio.2013.12.002Fablet, R., Chapron, B., Drumetz, L., Mémin, E., Pannekoucke, O., and Rousseau, F. (2021), Learning variational data assimilation models and solvers, Journal of Advances in Modeling Earth Systems, 13, e2021MS002572, https://doi.org/10.1029/2021MS002572Jourdin, F., Renosh, P.R., Charantonis, A.A., Guillou, N., Thiria, S., Badran, F. and Garlan, T. (2021), An Observing System Simulation Experiment (OSSE) in Deriving Suspended Sediment Concentrations in the Ocean From MTG/FCI Satellite Sensor, IEEE Transactions on Geoscience and Remote Sensing, 59(7), 5423-5433, https://doi.org/10.1109/TGRS.2020.3011742Preisendorfer, R. W. (1986), Secchi disk science: Visual optics of natural waters, Limnology and Oceanography, 31(5), 909-926, https://doi.org/10.4319/lo.1986.31.5.0909Prypeshniuk, V. (2023), Ocean surface visibility prediction, Master thesis, Ukrainian Catholic University, Faculty of Applied Sciences, Department of Computer Sciences, Lviv, Ukraine, 39 pp, https://er.ucu.edu.ua/handle/1/3948?locale-attribute=enVient, J.-M., Fablet, R.;, Jourdin, F. and Delacourt, C. (2022), End-to-End Neural Interpolation of Satellite-Derived Sea Surface Suspended Sediment Concentrations, Remote Sens., 14(16), 4024, https://doi.org/10.3390/rs14164024
Riparian monitoring using SAR image-based water body detection technique
Authors: Cho Shinhyeon , Cho Seongkeun , Kim Yeji , Kim HyunOk , Choi Minha
Published: March 2024

Sandbars on the riparian are ecologically important as they provide and protect habitats for organisms and act as natural septic tanks to filter and purify pollutants. In recent years, the role of sandbars in water pollution in rivers has been highlighted, and monitoring of the riparian is required. Sandbars are common in the lower reaches of deltas and at downstream of rivers, especially where the river is wide, and the flow velocity is relatively slow so that remote sensing can be used effectively. Synthetic Aperture Radar (SAR) imagery is an effective tool for spatial monitoring of the riparian because it provides high resolution and can detect regardless of weather conditions. In recent years, research has been conducted to use SAR imagery with AI to improve accuracy of detecting both riparian and sandbars. In this study, we utilized Sentinel-1 SAR (VV, VH polarized backscatter coefficient imagery), Sentinel-2 optical imagery Normalized Difference Water Index (NDWI), and Normalized Difference Vegetation Index (NDVI) data to identify changes of riparian and sandbars using AI-based clustering techniques. The confusion matrix is performed to validate the performance of deep learning techniques and waterbody detection. Technological advances in remote sensing will improve the data resolution of SAR and optical imagery, allowing detailed features to be observed. In further study is expected to improve the monitoring and management of sandbars on the riparian as monitoring technology advances.Keywords: Riparian, sandbars, Water body detection, Sentinel-1, Sentinel-2, Deep learningAcknowledgementThis work was supported by the “Development of Application Technologies and Supporting System for Microsatellite Constellation”project through the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2021M1A3A4A11032019). This research was supported by the BK21 FOUR (Fostering Outstanding Universities for Research) funded by the Ministry of Education (MOE, Korea) and National Research Foundation of Korea (NRF). This work is financially supported by Korea Ministry of Land, Infrastructure and Transport (MOLIT) as 「Innovative Talent Education Program for Smart City」
Towards efficient methods for estimating spatio-temporal wind energy yields in mountainous regions
Authors: Helbig Nora , Hammer Florian , Bischoff Reinhard , Lehning Michael , Barber Sarah
Published: March 2024

Complex mountain winds provide a largely unknown wind energy potential. Mountainous terrain influences air flow by e.g., wind flow sheltering, ridge acceleration, channelling, deflections, blocking and recirculation. Its impact on the energy production of wind turbines has not yet been thoroughly quantified, but various studies show that it could be significant. To accurately assess the wind energy potential in mountainous terrain, spatio-temporal wind fields capturing local wind-topography interactions are required. Ground measurements can retrieve spatio-temporal wind fields, but even with a dense weather station network, atmospheric models are still needed to capture the full spatial variability. However, it is challenging to generate the necessary fine-scale wind fields over long timescales and large regions computationally efficiently. Wind farm planning in mountainous regions is therefore much more challenging and uncertain than in flat areas.Here, we present our concept that addresses this challenge by evaluating and enhancing various state-of-the art computationally efficient downscaling methods (statistical and dynamical). These methods generate highly resolved spatio-temporal wind fields, considering dominant local wind-topography interactions. Using these fields, we can derive time-resolved wind energy yield potential. The evaluation involves assessing the methods across fine spatial scales (e.g., dekameter scale), large spatial extents (up to tens of kilometers), high temporal resolution (e.g., hourly scale), and long timescales (several years) in real Swiss mountain settings using wind field and energy production measurements. Our overall goal is to provide wind modelers and energy planners with recommendations for efficient methods for obtaining highly resolved spatio-temporal wind fields, enabling accurate energy yield estimations in mountainous terrain.
Basement inherited structures and their control on overburden sediments deformation: A study in the Eastern High Atlas and its northern foreland basins, Morocco
Authors: Es-sabbar Ismail , Amrouch Khalid , Soulaimani Abderrahmane
Published: March 2024

Inherited structures are widely recognized as one of the major factors that govern rift systems localizations, acting as weakening zones and influencing the subsequent inversion style during compression events, as well as controlling the deformation of overburden sediments. The High Atlas intermountain belt in Morocco, interpreted as evolution controlled by Paleozoic inherited structures, comprises Mesozoic and Cenozoic sediments overlying a Paleozoic and Precambrian basement. Exploring these structures is crucial for understanding the evolution of the belts and for assessing seismic hazards. Surface studies are often insufficient to unveil the complete image of the subsurface structural setting, as illustrated by the Mw 7 Al Haouz earthquake, which is interpreted as being linked to a blind fault (William et al., 2023; Cheloni et al., 2024). In this context, geophysical studies are indispensable to bridge this gap. Here, we present a 3D model depicting the morphology of the metasedimentary basement in the Eastern High Atlas and its northern foreland basins. This model is constrained through the inversion of gravity and aeromagnetic data, supported by seismic sections, borehole, and field data. Preliminary findings from fieldwork denote a series of large NE-SW to E-W structures, predominantly comprising reverse and thrust faults that have governed the deformation of Mesozoic-Cenozoic sediments. The depth of both outcropping and non-outcropping structures, along with their tectonic implications during the Alpine inversion, will be derived through the analysis of geophysical data.
Keywords: Inherited structures, High Atlas, basement, 3D model, inversion, geophysical data.
Comparing the strontium isotope signatures of human urinary stones, drinking waters and environmental matrices: A first case study from Italy
Authors: Francesco Izzo , Alessio Langella , Valeria Di Renzo , Massimo D'Antonio , Piergiorgio Tranfa , David Widory , Luigi Salzano , Chiara Germinario , Celestino Grifa , Ettore Varricchio , Mariano Mercurio
Published: March 2024

Urolithiasis is a rather common pathology among the adult population and the biominerals it produces, i.e., urinary stones, may represent a potential proxy to characterize the environmental matrices that surrounded patients before being diagnosed. The objective of the present investigation (recently published in Izzo et al., 2024) was to use 87Sr/86Sr, a peculiar geochemical tracer routinely used for interpreting geological processes, to correlate the characteristics of patients’ urolith and their lifestyle habits, trying to identify correlations with direct or indirect contacts with their geological and environmental surroundings (water, soil, rock, etc.). Analyzed samples consisted of 21 kidney and bladder stones that were collected at the Department of Urology of the San Pio Hospital (Benevento, Italy) from patients living in Campania Region admitted between 2018 and 2020. Investigation was also extended to a vital food for humans such as water. Local tap waters and bottle waters (38 samples) from totally different Italian areas were here analyzed in order to highlight if and how different geological and hydrogeological settings could influence their Sr isotope ratio characterizing the connections existing between humans and their surrounding environment.The 87Sr/86Sr ratios of uroliths ranged from 0.70761 for an uricite sample to 0.70997 for a weddellite one and seem to be partly discriminated based on the mineralogy. The comparison with the isotope characteristics of Italian drinking waters shows a general overlap in 87Sr/86Sr with the biominerals. However, on a smaller geographic area (Campania Region), we observe small 87Sr/86Sr differences between the biominerals and local waters. This may be explained by external Sr inputs for example from agriculture practices, inhaled aerosols (i.e., particulate matter), animal manure and sewage, non-regional foods. Nevertheless, biominerals of patients that stated to drink and eat local water/wines and foods every day exhibited a narrower 87Sr/86Sr range roughly matching the typical isotope ratios of local geological materials and waters, as well as those of archaeological biominerals from the same area. This preliminary study evidences how the strontium isotope ratio of urinary stones records that of the patient's surrounding environmental matrices, although further investigations will be necessary to confirm this hypothesis. Izzo F., Di Renzo V., Langella A., D’Antonio M., Tranfa P., Widory D., Salzano L., Germinario C., Grifa C., Varricchio E., Mercurio M. (2024) Investigating strontium isotope linkage between biominerals (uroliths), drinking water and environmental matrices. Environmental Pollution, https://doi.org/10.1016/j.envpol.2024.123316  
Flood control capacity of a large reservoir under moderate and extreme flood conditions
Authors: Chakraborty Pratik , De Kock Sophie , Archambeau Pierre , Pirotton Michel , Erpicum Sébastien , Dewals Benjamin
Published: March 2024

Dams, prevalent globally as major hydraulic structures, play essential roles in water supply, hydroelectric power, and flood management. However, they are known to significantly transform hydrological regimes by, among others, regulating flood and base flow dynamics. This, in turn, necessitates a meticulous understanding of the nature of these alterations.Focused on the Eupen dam in Belgium, this study examines its storage dynamics in relation to moderate and extreme flood events. The study analyses time-series of inflow and outflow discharges at the dam for the period from 1995 to 2023. The inclusion of the July 2021 extreme event provides valuable insights into the dam’s performance (or lack thereof) during such mega-events. Notable aspects of the methodology include adjustments for an ungauged sub-basin, the use of a Savitsky-Golay filter to refine (field-)data quality without compromising peak details and a fundamental mass-balance approach to compute outflow data from the inflow time-series.The examination of 18 flood events during this period reveals significant findings: the dam's ability to reduce peak discharge by 8.6 to 91%, delay peak discharge by up to 68 hours, decrease flood volume by 2 to 94%, and reduce the rising rate by 1.09 to 11.16 times. Distinctly, the study also reveals a strong correlation between the damping ratio of the flood wave and the ratio of the volumes of the incoming flood to that available in the reservoir (at the start of an event). The outcomes of the flood frequency analysis are also presented and interpreted in detail.The present study features a marked shift from existing dam-effects research, wherein the analysis is often focused on mean annual flow characteristics or aggregated data across numerous dams. It highlights the rewards of such a singular case study, in terms of being able to scrutinise individual flood events. This, in turn, provides the scope to understand more complex underlying conditions that prompt a dam's effects on streamflow characteristics. Finally, this research evidences the benefits provided by dam reservoirs on flood wave damping, but also their limits in doing so.
Parameter Estimation of Oxygen Transfer at Hydraulic Structures 
Authors: Tiwari Ashwini , Hari Prasad Kotnoor , Ojha Chandra Shekhar Prasad
Published: March 2024

Dissolved oxygen is an indicator of water quality, and a minimum of 4 ppm is required for the survival of aquatic life. The oxygen is transferred when water flows over the hydraulic structure by entraining air into the bulk of the flow. The entrained air breaks into small bubbles, increasing the surface area for oxygen transfer. The oxygenation of water removes organic matter, dissolved gases, volatile liquids, offensive taste, and odor, improving the quality of the water flowing in the rivers and streams. The oxygen transfer efficiency depends upon the liquid film coefficient and specific interface area. In this study, parameters, namely liquid film coefficient and specific interface area, are estimated from dissolved oxygen concentration data. The dissolved oxygen concentration data is generated using a liquid film coefficient of 500 m/s, a specific interface area of 0.00035 m2/m3, and dissolved oxygen saturation concentration at 250C. The Parameters are estimated through numerical inversion in which the numerical model representing oxygen transfer over hydraulic structure was optimized using genetic algorithm. The seed value used for optimization is taken as 0.6. The results show that it is not possible to estimate both the liquid film coefficient and specific interface area together from dissolved oxygen concentration data only, and at least one parameter should be known. This finding is supported by the presence of local minima in the liquid film coefficient-specific area parametric space.
Common, non-cubic garnet in metamorphic rocks: the state of the art
Authors: Cesare Bernardo , Mugnaioli Enrico , Tacchetto Tommaso , Lorenzon Sofia , Biagioni Cristian , Nestola Fabrizio , Campomenosi Nicola , Della Ventura Giancarlo
Published: March 2024

Since the first report on the tetragonal structure of common (OH- and andradite-free) garnet in metamorphic rocks (Cesare et al., 2019) , many new occurrences have been discovered.Non-cubic anhydrous garnets are widespread in low-temperature metamorphic terranes worldwide, including the world-renowned blueschists from the Franciscan Complex (USA), Syros (Greece) and Aosta Valley (Italy), and the phyllites from the iconic Barrow garnet zone of Scotland.These garnets share compositional features such as grossular >20% and pyrope
The Gauss and Matuyama recorded in drift sediments from the North Atlantic: preliminary study from IODP Expedition 395C.
Authors: Di Chiara Anita , Satolli Sara , Friedman Sarah , Dwyer Deepa , Karatsolis Boris Th. , Pearson Paul N. , Dunkley Jones Tom , Suzuki Takuma , Briais Anne , Parnell Turner Ross E. , LeVay Leah J. ,   Expedition 395 Science Team
Published: March 2024

Drift sediments are characterized by a rapid accumulation rate (≥10 cm/kyr), which can provide high-resolution records of the geomagnetic field behavior. Previous ocean drilling in the North Atlantic (e.g., ODP Leg 162 and IODP Exp 306) discovered magnetic instabilities of short duration, such as the Iceland Basin Excursion (188 ka). These records have contributed to our understanding of Earth’s magnetic field variations in the geological past and the foundation of the Geomagnetic Instability Time Scale (GITS) in the Quaternary (0-2.58 Ma).Between 2020 and 2023, IODP Expeditions 384, 395C, and 395 drilled six sites: five along a transect on the eastern side of the modern Mid-Atlantic Ridge (between 20-30°W at a latitude of ~60°N) and one on the western side, off the coast of Greenland. The expedition aims to investigate the formation of V-shaped ridges and V-shaped troughs in the Reykjanes Ridge and the evolution of deepwater currents.Shipboard paleomagnetic and microfossil data provided a preliminary age model for all sites, extending the regional record to 11 Ma.During the Expeditions(s), archive half sections were subjected to alternating field stepwise demagnetization cleaning of natural remanent magnetization. Shipboard paleomagnetic data were processed to remove edge effect, core disturbance, and are integrated with data from discrete samples. All directional data were interpreted, isolating the primary magnetization through the principal component analysis. The discrete samples confirm all polarity changes recognized in the shipboard inclination data. Here, we present the preliminary results from two of the sites drilled during the Expeditions 395C, U1555 (~2.7 Ma) and U1563 (~5.2 Ma), where most of the magnetic events (including excursions and reversals) reported in the Geomagnetic Instability Time Scale of the Quaternary are recognized. These high-resolution records provide the potential to extend the GITS further in the past, expanding the potential of using magnetic instabilities as a dating tool and help to refine our understanding of how the Earth’s magnetic field changed in the past.