bluuebunny/crossref_metadata_2025 huggingface dataset:
Nitrogen fixation in the shallow waters off a coastal wetland with outcropping peat
Authors: Klett Angelina , Liskow Iris , Voss Maren
Published: March 2024

Biological nitrogen (N) fixation is the microbial transformation of atmospheric N2 to ammonia, which is carried out by various groups of microorganisms and in all environments. The organisms, called diazotrophs, do not rely on bioavailable combined N such as nitrate or ammonium, which are often limiting ecosystem productivity. On the other hand, their activity provides nutrients to the otherwise N-limited ocean. In the central Baltic Sea high nitrogen fixation occurs each summer in surface waters introducing up to 792 000 t N per year, but was also identified in the deep and anoxic waters. In coastal waters the heterotrophic and autotrophic N2 fixation is not well studied and even less is known about the annual cycle and its regulation by the environment. Since coastal environments are considered to act as a filter for nutrients and organic matter, knowledge on an additional N source through N2 fixation is of great importance.Here, we present N2 fixation rates for bulk water and sediment slurries (upper 5 cm), incubated for 24 hours in the dark and during a daily light cycle. We selected three stations near a peatland with outcropping peat layers and sandy sediments. Monthly sampling over the course of one year was done together with in-situ measurements of temperature, salinity, pH, nutrient concentrations and dissolved organic substances. Incubations were spiked with 15N2 gas and incubated in the lab. The fixation rates ranged from our detection limit up to 285 nmol N L-1 d-1 in water and 2 nmol N gdw-1 d-1 in sediments with a mean fixation rate of 11.2 nmol N L-1 d-1 and 0.1 nmol N gdw-1 d-1 for water and sediment, respectively. We could not find significant difference between stations and overall, the rates were much lower than in the surface waters of the central Baltic Sea. Though the rates in the water observed in June 2022 agree well with the rates of a cyanobacterial bloom in late summer (4.3 – 7.8 µmol N m-3 h-1). The rates for the water as for the sediment showed significant positive correlation (Spearman, sig. level 0.05) with variables affected by the seasonal change as temperature, daylength, pH and oxygen saturation. during winter and spring, the rates in the water were low to non-detectable and highest in summer. Also, in the sediment the lowest rates were found during winter and highest rates in spring. In general, the light cycle treatment showed higher rates than the dark incubation, with the exception of spring where the dark incubated sediments had higher rates than the ones in a daily light cycle. The outcropping peat layer seemed to induce some variability in N2 fixation rates, reflecting the heterogeneity of substrate which was sometimes covered with sand layers of different thickness.Even though the rates in this study are comparably low for both water and sediment, a seasonal pattern became visible. Sediments and shallow waters clearly deserve more attention to better understand the process and the potential role as food and nitrogen source.
A landscape evolution model of how uplift has shaped drainage patterns in Central Europe
Authors: Rau Maximilian , Schwanghart Wolfgang , Krautblatter Michael
Published: March 2024

The large-scale reorganization of drainage patterns is one of the most enigmatic events in the landscape history of Central Europe. In particular, the rivers Main and Neckar show a reversal of the flow direction from southeast to northwest. Historically, this has been interpreted as a consequence of the subsidence of the Upper Rhine Graben (URG) and the subsequent lowering of the base level. However, the high uplift rates along the shoulders of the URG, which suggest an increased southeastward tilt, raise questions. This prompts the investigation of alternative uplift patterns contributing to the observed river reversals.This study uses a new version of the landscape evolution model TTLEM and river analyses with TopoToolbox to investigate the potential role of large-scale lithospheric folding resulting from the collision of the Alps. Our research challenges the conventional narrative by examining whether such folding could be a driving force behind the enigmatic flow reversals in the Main and Neckar rivers.During the transition from the Cretaceous to the Paleocene, a dome-shaped exhumation event in Europe led to the establishment of a radial river network originating in higher regions. Some rivers still have their original flow directions, such as the Wörnitz and the Brenz, or the Neckar, which now flows in the opposite direction. In southern Germany, a network of rivers flowed in a southward or southeastward direction. The Eocene marked the beginning of the formation of the URG, accompanied by a marked uplift of the Graben shoulders and a tilting of southern Germany to the east-southeast. During this period, the flow directions of the rivers remained constant, and the sinking URG initially failed to extend its drainage basin beyond the graben shoulders.The pivotal moment in the redirection of the rivers has been evident since the Miocene when lithospheric folding occurs parallel to the Alpine front. This previously unnoticed event highlights a crucial link between the collision of the Alps and the redirection of the Main and Neckar rivers. Our findings shed light on the complex interplay of tectonic forces, landscape evolution, and river dynamics, challenging existing paradigms and contributing to a deeper understanding of the geomorphic history of Central Europe.
A multi-ecosystem service assessment for urban climate adaptation in Singapore 
Authors: Ramsay Emma , Tan Leanne , Wang Yuan , Hamel Perrine
Published: March 2024

Nature-based solutions are an important tool to adapt to climate change in cities. Green spaces including nature reserves, parks and green streetscapes are essential to mitigate urban heat and also provide important recreation opportunities that benefit peoples physical and mental health. Effectively planning climate resilient and liveable cites thus requires quantitative, spatially explicit information about these ecosystem services. Such data are especially important in dense cities where vacant land is limited and trade-offs must be made to prioritise certain services. Here we present a multi-ecosystem service assessment for Singapore using the urban InVest models to evaluate urban cooling and urban nature access. We generate future greening scenarios based on policy targets to plant one million trees and increase the land area of parks by 50% by 2030 and compare ecosystem service provision for each scenario when either cooling or nature access is maximised in the spatial configuration of scenarios. We compare the benefits and trade-offs achieved by each scenario and explore the potential to quantify these through health indicators. Finally, we discuss how multi-ecosystem service assessment cans be integrated into urban planning and the implications for cities in an uncertain climate future.
Observation of temporal and spatial variability of deep near-inertial waves in the western Arctic Ocean
Authors: Jeon Chanhyung , Boury Samuel , Cho Kyoung-Ho , Lee Eun-Joo , Park Jae-Hun , Peacock Thomas
Published: March 2024

Near‐inertial waves are waves propagating in the interior of the ocean. Created by surface storms, they have the potential to influence the ocean environment by inducing vertical mixing. Compared to other oceans, the Arctic Ocean has low near-inertial wave activity, but might be changing. It is a challenge, however, to predict near-inertial wave activity in the Arctic Ocean due to its intricate vertical salinity and temperature stratification. Our in-situ campaign has obtained the first direct deep current measurements revealing notable temporal and spatial variability of deep near-inertial waves in the western Arctic Ocean. These observations are an important step towards a clearer depiction of the evolving energy budget, and concomitant mixing, associated with potentially high impact near-inertial wave activity in an increasingly ice-free Arctic Ocean.
The impact of Hurricane Fiona on sandy beaches and foredunes in Prince Edward Island National Park: Implications for management.
Authors: Delgado-Fernandez Irene , Davidson-Arnott Robin , Ollerhead Jeff , George Elizabeth , Houser Chris , Bauer Bernard , Hesp Patrick , Walker Ian , van Proosdij Danika
Published: March 2024

This study investigates the impact of Hurricane Fiona on sandy beaches and foredunes within Prince Edward Island National Park (PEINP). Fiona was the strongest storm to strike the island in nearly a century, with significant wave heights reaching 8 metres. Its impact on sandy beach-dune systems provides an opportunity to gauge the effectiveness of current PEINP's management policies and practices, and to consider potential changes that enhance the role of foredunes and beaches as natural defences against future storms and rise in relative sea level.Survey data and ground/UAV photography were used to compare various locations before (October 2021 to July 2022) and after (October 2022 and May 2023) the storm. High dunes experienced stoss slope erosion without significant changes in the height or position of the foredune crest, offering protection to landward areas. Low dunes were substantially eroded, leading to overwash in certain areas, and dunes located on bedrock and till were completely eroded, exposing the underlying surface. Hurricane Fiona's impact highlights the need of reinforcing current management strategies in PEINP that aim at safeguarding the natural biotic and abiotic components of beach-dune systems, and securing the accommodation space needed for their natural inland migration with rising sea level.
Advancing Seismic Event Detection: Integrating Machine Learning with Waveform-Stacking Techniques
Authors: Isken Marius Paul , Dahm Torsten , Heimann Sebastian , Münchmeyer Jannes , Cesca Simone , Niemz Peter
Published: March 2024

In the realm of seismic and microseismic event detection and localization, our research marks a significant step forward by integrating machine learning with advanced waveform-stacking techniques for detecting, locating and characterising seismic events. This integration is crucial for unravelling the complex spatio-temporal patterns of seismicity sequences. Our study addresses the challenges posed by noise-dominant microseismic events, which are typically overlooked by conventional detection methods.Building upon the foundational work on migration and stacking, we have developed an automated, data-driven method utilising a neural network trained in seismic phase arrival identification. This approach, underpinned by stacking and migration techniques, is enhanced by the incorporation of a spatial octree to precisely and efficiently localise seismic sources. These enhancement gives insights into complex seismic sequences, such as volcanic swarms and regional tectonic sequences.The software framework facilitates extensive feature extraction, such as local and moment magnitudes, enabling the study of seismic events across various scales and tectonic settings. This is exemplified in our validation studies using data from the Eifel region, Germany, and the Reykjanes Peninsula, Iceland. These regions, known for their diverse seismic activities including tectonic earthquakes and fluid-induced swarm activity, provide a rich dataset for testing our method's efficacy in different geological contexts.Our research contributes to the session's overarching goal of understanding the physical processes behind complex seismic sequences. By enhancing detection and localization capabilities, we aim to offer new perspectives and tools for the geophysical community to investigate the triggering mechanisms of these sequences with unprecedented resolution.
Understanding drought risks for European ecosystems through conceptual risk models
Authors: Sabino Siemons Anne-Sophie , Cotti Davide , Wens Marthe , de Moel Hans , Rossi Lauro , Walz Yvonne , Hagenlocher Michael
Published: March 2024

Ecosystems in Europe are increasingly faced with more frequent and more intense drought events. The impacts of droughts do not only undermine ecosystem health and the provision of ecosystem services, but can lead to the deterioration of the system’s long-term resilience to droughts. In order to effectively assess, reduce, and manage the risks posed by droughts on ecosystems, it is first necessary to gain a thorough understanding of how droughts affect a particular ecosystem, what the underlying risk drivers and root causes are, and how these interact to produce that risk. Addressing this need, we have developed conceptual models of drought risks for two highly-relevant European ecosystem types, forest and freshwater ecosystems. The conceptual models were developed and visualized using the impact chain methodology, building on extensive literature review and expert consultations, and validated in a series of expert workshops. Following this process, the risks of decreased primary production, forest die-off, and soil degradation and desertification were identified for forest ecosystems, and the risk of disruption of environmental flow for freshwater ecosystems.The resulting impact chains provide insights into how different climatic, ecological, and societal risk drivers interact to produce drought risks for ecosystems, with some drivers being specific to a certain risk (e.g. forest composition), and others shared across them (e.g. societal water demand and abstractions). While some of these drivers relate to purely ecological features (e.g. plant physiology or soil conditions), many relate to how ecosystems are managed, and to the influence of other sectors/systems upon them (e.g. hydropower, river transportation or intensive agriculture and their adverse effects on freshwater ecosystems). Moreover, the impact chains also highlight some of the root causes (e.g. increased demand for energy, farmers' lack of awareness about agriculture's impacts on freshwater ecosystems, or incentives to enhance navigability) behind these drivers, indicating potential entry points for risk reduction and adaptation. The visualization in impact chains is useful to enhance the understanding and at the same time break down the complexity of the risks for these systems, which can support data-driven risk assessment, as well as the identification of entry points for risk management and adaptation. While in this work the risks posed by droughts for forests and freshwater ecosystems were assessed on European level, the impact chain approach presented here can be used at different scales and transferred to different ecosystems at risk from droughts. Moreover, it can be used to identify common risk drivers between ecosystems that could be addressed jointly, contributing to a more systemic drought risk management. 
Drought induces changes to redox chemistry and C exports from boreal riparian soils
Authors: Škerlep Martin , Reidy Melissa , Laudon Hjalmar , Sponseller Ryan
Published: March 2024

Extreme summer droughts can drastically lower water tables and lead to oxygenation of normally anoxic soils in boreal ecosystems. In organic rich riparian soils, this creates a dynamic redox environment, driving changes in soil organic matter stability and the export of redox sensitive elements (e.g., C, N, S, Fe, etc.) to surface waters.  We hypothesized that the destabilization of redox cycles and the activation of oxidative soil enzymes during drought periods can lead to prolonged periods of altered soil biogeochemical processes that drive element export from terrestrial to surface water systems upon rewetting. Here we simulated a soil core drying-rewetting event, to ask how riparian soil solution biogeochemistry changes during two months post drought. To three drought treatments (dry, semi-dry, wet), we also added a root exudate treatment (exudates or no exudates) to simulate the effects of riparian vegetation on microbial organic matter decomposition. We found that following drought, dissolved organic carbon (DOC) concentrations initially decreased, due to the increased acidity caused by the oxidation of reduced S to SO42-. As other preferred electron acceptors (O2, NO32-, Fe3+) were gradually reduced, reduction of SO42- lead to increases in DOC concentrations, which after 2 weeks surpassed concentrations in the control (wet) treatment, and continued increasing until the end of the experiment. Once SO42- was depleted and CO2 became the preferred electron acceptor, methane (CH4) in solution also increased to concentrations higher than those in control treatments. Peroxidase activity was increased post drought and remained elevated throughout the experiment, suggesting that microbial organic matter breakdown was enhanced, and could explain why DOC concentrations in drying treatments eventually surpassed those in wet controls. While the root exudate treatments produced mixed results, an increase of labile C supply appeared to increase extracellular enzymatic activity and serve as an alternative electron acceptor, thereby suppressing methanogenesis. Our results show that drought drastically changes the biogeochemistry of boreal riparian soils and that upon rewetting this can eventually lead to increased lateral exports of both organic and inorganic C. Changes in C biogeochemistry are seemingly caused by shifts in redox chemistry and by changes in microbial decomposition of soil organic matter induced by the oxygenation of riparian soils. Since this has implications for surface water chemistry, further study is needed on the length of drought effects to establish the duration of this influence of stream and riparian biogeochemistry.
Development of a high spatial resolution legacy soil profile database for the Southern Great Hungarian Plain
Authors: Kocsis Mihály , Hernádi Hilda , Makó András , Szabó Brigitta , Kassai Piroska , Szatmári Gábor , Laborczi Annamária , Takács Katalin , Balog Kitti , Mészáros János , Benő András , Bakacsi Zsófia , Pásztor László
Published: March 2024

A high spatial resolution soil database is under development in Hungary consisting of legacy soil observation data originating from different soil surveys. The soil data collected for the presented  pilot area situated in the Southern Great Hungarian Plain will be the part of the Profile-level Database of Hungarian Large-Scale Soil Mapping (Hungarian acronym: NATASA). Presently, the NATASA soil database contains data from about 15,000 soil profiles in the sample area. The data from the soil profile records consist of two major parts: field descriptions and results of laboratory investigations. Soil profile locations are being processed using specifically elaborated GIS tools. Digitized profile records are being revised according to the national soil system and expert-based criteria, and the content of the database is being developed according to a uniform nomenclature. Essentially, the NATASA database will form the basis for the production of target soil hydrophysical property maps using environmental auxiliary variables and proper inference methods in standardized DSM approaches providing predictions for specific soil depths.The results obtained will not only become tangible in the form of different target maps, but will also provide very valuable information on the extent of the vulnerability of the Hungarian Southern Great Plain production areas to inland water and drought caused by weather extremes under the influence of climate change. This could help in the development of a regional drought and water deficit management system, in the establishment of a basis for irrigation investments or in the further development of the methodology of the current inland water vulnerability map. A more detailed knowledge of the hydrophysical properties of soils with spatial data could help to develop natural water retention measures.Acknowledgement: The work was carried out within the framework of the Széchenyi Plan Plus program with the support of the RRF 2.3.1 21 2022 00008 project and the Sustainable Development and Technologies National Programme of the Hungarian Academy of Sciences (FFT NP FTA).
Modelling the geometry of abandoned coal mines for inter-seasonal heat and cold underground storage
Authors: N'depo Yanick , Dupont Nicolas , Martin Thierry , Kaufmann Olivier
Published: March 2024

Wallonia (southern Belgium) experienced intense coal mining in the 19th and 20th centuries. The depths of these abandoned coal mines range from the ground surface to more than 1000 m. These abandoned mines are now being studied as potential reservoirs for inter-seasonal geothermal storage operations as part of the operation of 5th generation heating networks. In the scope of feasibility studies, a major challenge is to reconstruct the geometry of former structures and works, a preliminary but essential step in modelling flows and heat transport underground.As these mines have long since closed and are no longer accessible, this work is based solely on archive documents such as mining maps from the former collieries and cross-sections held by the mining administration. The information available in these documents is invaluable. However, this information, some of which dates back more than a century, is sometimes difficult to interpret and cannot be considered exhaustive. Moreover, it is not homogeneous and the accuracy of the topographical information varies depending on the source and the time period.In order to reconstruct a coherent model of the mine workings, galleries and shafts, a geological model constrained by information from archive documents is constructed. Next, the elevation of the boundaries of the mine workings and galleries in layers is adjusted on the layers derived from the geological model in order to preserve the topological links between objects. Finally, a discretised model representing the zones of increased permeability around the workings and galleries is extracted. To carry out all these operations and the associated quality controls, a workflow based on developments in Python and relying on open source libraries has been developed and tested.
Interpolating proxy observations to high-resolution XRF data
Authors: Blaser Patrick , Lippold Jörg , Bruggmann Sylvie , Bollen Michael , Crosta Xavier , Jaccard Samuel
Published: March 2024

Proxy observations are the fundament for many insights in geosciences, such as the reconstruction of past environmental conditions from sediment cores. However, the labor-intensive nature of producing proxy data often renders high-resolution records prohibitively expensive. In contrast, state-of-the-art XRF analyses offer an efficient means of generating high-quality and very high-resolution elemental concentration data. Although these data initially provide only qualitative information about the bulk sample composition, their high-resolution renders them invaluable as a foundation for subsequent studies.Here we explore the potential utility of high-resolution XRF data as a foundation for interpolating more scarce sedimentological, geochemical, and environmental analyses to the same high-resolution. We base the investigation on a long sediment core obtained from the Crozet Plateau in the Indian sector of the Southern Ocean, where changes in surface productivity, dust influx, and delivery of detritus from the nearby island dominate the sedimentological and geochemical signals.We test different statistical methods for sediment classification and the interpolation of proxy data and discuss their reliability and limitations. For instance, application of a random forest model for the interpolation of carbonate and opal concentration conspicuously reveals the presence of distinct detrital layers. These layers are not readily discernible in the original XRF data or the sparse original opal and carbonate measurements.We propose these straight-forward statistical methods have potential to be used on many other sediment records for which high-quality and high-resolution XRF data and certain proxy observations are available. Such an approach can streamline the interpretation of XRF data and enhance the investigation of specific environmental proxy observations at a high-resolution.
Irrigation Estimation from Soil Water Balance and the Water Cloud Model by leveraging Sentinel-1 and Sentinel-2 observations
Authors: Natali Martina , Modanesi Sara , De Santis Domenico , Brocca Luca , Mantovani Fabio , Maino Andrea , De Lannoy Gabrielle , Massari Christian
Published: March 2024

Irrigation plays a pivotal role in the hydrological cycle, representing about 70% of freshwater withdrawals. However, its representation in Earth System models is characterized by significant uncertainties in terms of amount, timing and spatial distribution. Earth Observation data offer a viable way to reduce this uncertainty thanks to their ability to sense the soil and vegetation in its real condition with few-days revisit timing and high spatial resolution (~ 10 m), e.g. with the new Sentinel missions. 

In this contribution, we use remote sensing observations from the Sentinel-1 and Sentinel-2 satellite missions to constrain a simple Soil Water Balance (SWB) model coupled with the semi-empirical Water Cloud Model (WCM) and obtain irrigation estimates via an inverse modelling solution. The WCM, which is a model simulating backscatter observations (σ0) from soil moisture and a vegetation descriptor, is forced by vegetation indexes from Sentinel-2 data and soil moisture simulated by the SWB that includes a sprinkler irrigation scheme. The model outputs are then matched with Sentinel-1 observations to obtain irrigation estimates.

The model is tested over an irrigated field of the Po River valley, one of the most intensively European irrigated areas. Results show that the model can capture the irrigation signal with relatively good accuracy. It also provides an estimate of soil moisture in the field.  Nonetheless the revisit time of the satellite platforms and the simplicity of backscatter model, especially in the representation of the vegetation component, constitute two main limitations of the model. This model is a viable tool that can be easily applied in the context of precision agriculture to optimize irrigation practices and conserve water resources even when in-situ soil moisture and irrigation measurements are not available.
Steering agricultural interventions towards sustained irrigation adoption by farmers
Authors: Pande Saket , Adla Soham , Šaponjić Anja , Tyagi Ashray , Nagi Anukool , Pastore Prashant
Published: March 2024

Agriculture, the largest global freshwater consumer, necessitates water-saving techniques like efficient irrigation. However, the adoption of such technologies is influenced by complex contextual and sociopsychological factors. This study used the sociopsychological RANAS framework to examine the factors impacting irrigation adoption in Maharashtra (India). Logistic regression modeling was conducted with data from cross-sectional surveys in 2019 and 2022, with interim interventions promoting risk-awareness and irrigation technology training. Effects of the interventions on the psychological variables in 2022 were corrected using instrumental variable regression. While micro-irrigation adoption rose from 36.9% to 62.8% (as anticipated), overall irrigation counterproductively decreased from 81.8% to 70.5%. Results indicated that wealth and risk-aversion remained relevant, while self-perceived ability and attitude towards irrigation became non-significant to irrigation adoption. Based on these unintended consequences of the intervention, this study highlights the necessity to also transform attitudes, and promote psychological ownership and trust for sustained irrigation technology adoption behavior.
Comprehensive Investigation of Microplastics size distribution in Marine Environment: Detection, Quantification, and Optical Analysis Using Static Light Scattering (SLS)
Authors: Sandhani Chavapati Gouse , Shanmugam Palanisamy , Sannasiraj Sannasi Annamalaisamy
Published: March 2024

Microplastics are detected in the environment, particularly in oceanic waters, and have adverse effects on marine ecosystems, biota, climate dynamics, and human health, primarily through the induction of marine pollution. The microplastics are introduced into marine ecosystems either as primary particles through direct discharge or as secondary particles resulting from the weathering of macroplastics. For this, a new laboratory optical-based measurement technique using the static light scattering (SLS) instrument was proposed for the detection and quantification of the microplastics size distribution and to mitigate marine pollution. The SLS instrument relies on the Lorenz-Mie scattering and Fraunhofer diffraction theories and a single monochromatic laser beam is passed through the sample and measures the light scattered intensity in all the scattering angles and with one or many detectors. SLS analysis yields information about microplastic samples, including the volume fraction of each size class bin and the cumulative log-normal distribution of particles. The volume fraction calculation will give the microplastics mean diameter (Dµ) and standard deviation (σ). The microplastics considered in the present study, include polyethylene (PE), polypropylene (PP), polystyrene (PS), and polyvinyl chloride (PVC). The mean size and standard deviation for PE samples are 3 µm and 2 µm and similarly, the mean size and standard deviation for PP are 3.5 µm and 2 µm. In the case of PS samples, the mean size and standard deviation are 3.5 µm and 2 µm, whereas PVC samples demonstrate a mean size and standard deviation of 3 µm and 2 µm. The findings of the SLS data show the Dµ and σ values are in the range of 3-3.5 µm and 2 µm, respectively, for all the microplastic types. The results of the present study will be helpful for a comprehensive understanding of microplastic behavior, facilitating the development of targeted methodologies for detection using hyperspectral remote sensing data in marine environment.
Modelling of the Hunga Tonga eruption for testing the GPU port of ICON
Authors: Kornblueh Luis ,   Port ICON to Lumi
Published: March 2024

Porting weather and climate models such as ICON to GPU-based computer production systems requires serious testing of the code adapted to theadditional hardware and its software stack. The high resolution of storm resolving models poses problems for porting ICON and very short simulations facilitate this task.The 2022 eruption of the Hunga Tonga–Hunga Haʻapai submarine volcano had a very strong water vapour signal, which is modelled by adjusting the model initial conditions to include a cylindrical water vapour plume: a very simple setup to implement, but one that reflects the strong signal in the model results. This plume is visible in the model for years. For the test case we focus on the first time steps. These support the detection of technical errors in the porting of the model code in very short simulations at the final model resolution of 5 km.We present the scientific use case, the model configuration and some results from test simulations on Lumi.
Optimizing of alternative water resources reutilization on extreme sandy soil
Authors: Nxumalo Gift , Kiss Nikolett Éva , Fehér Zsolt Zoltán , Magyar Tamás , Bódi Erika Budayné , Szabó Andrea , Pásztor Dávid , Tamás János , Nagy Attila
Published: March 2024

All agricultural areas in the European Union, as one of the largest water-using sectors, are under increased threat from the growing frequency of extreme water-holding events due to climate change. These focus on alternative water resource management, spectral data integration and soil moisture modelling. Furthermore, the irrigated area in Hungary covers 2% of agricultural land, mostly with outdated irrigation technology. This research will evaluate farm-level water resource management and irrigation technology developments and research results based on the results of the Hungarian test area.The study area was conducted on a 85 ha maize field on sandy soil, located in a nitrate-sensitive area (based on European guidelines) and owned by the private company. The case study site situated at the alluvial cone plain is covered mainly with quicksand which is not optimal for maize production from a water management point of view. Irrigation is implemented by a GPS controlled, VRI technology controlled, reversible linear irrigation system with zone and nozzle irrigation control. However there is limited available water resources at the site, therefore alternative water sources utilization system was set up for irrigation to adapt to climate change and reduce fertilizers. The basis of the alternative water resources are excess water, treated wastewater, biogas fermentation sludge which is collected in a water reservoir with 114000 m3 capacity.In this research the role of these alternative water resources were evaluated in the hydrological system and in the water cycle. A wide variety of remote sensing platforms were used in this research, as satellites, drones, and laboratory instruments. These remote sensing (pigment and plant phenology) data formed the basis of time series studies. The results can contribute to a spatially and temporally optimal stress monitoring of plants and their water supply at the same time. Beside better irrigation management due to the used irrigation techniques as up to 30-50% of the required water can be replaced by using alternative water resources.This research was financed by project no. TKP2021-NKTA-32, which has been implemented with the support provided from the National Research, Development and Innovation Fund of Hungary, financed under the TKP2021-NKTA funding scheme. This research was supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences. 
Encroachment analysis of the invasive tree species Ailanthus altissima in Sicily (Italy) through an ecohydrological cellular automata model 
Authors: Alongi Francesco , Badalamenti Emilio , Capodici Fulvio , De Caro Dario , Ciraolo Giuseppe , La Mantia Tommaso , Pumo Dario , Noto Leonardo Valerio
Published: March 2024

Plant species diversity is fundamental for the stability and resilience of ecosystems, and the well-being of the entire planet. Healthy and diverse ecosystems also contribute to air and water pollution removal, climate regulation and flood prevention. In the last century, plant biodiversity has been facing severe threats, such as habitat destruction and fragmentation due to increasing urbanization, deforestation, agricultural expansion, wildfires, and pollution. In addition, changes in climate pose significant threats to plants biodiversity conservation and native species preservation. All these natural and anthropic disturbance factors are profoundly modifying the competitive dynamics among plant species, often favouring the establishment and spread of some invasive plants, and exacerbating the biodiversity loss of native ecosystems.A well-known invasive alien species is Ailanthus altissima, a tree native to East Asia and introduced to various regions around the world, including North America and Europe. It is characterized by rapid growth, high reproductive capacity, and ability to thrive in a wide range of environmental conditions, where it can significantly modify ecosystems by altering soil characteristics, releasing allelopathic chemicals that may inhibit the growth of other plants, and forming dense thickets that reduce the space available and development chance of native vegetation. Ailanthus has been recognized as the most widespread and invasive alien tree species in Sicily (Italy), with a capillary presence over the entire regional territory, where it poses a serious threat to the biodiversity of the local Mediterranean ecosystems.Ecohydrological models can simulate vegetation dynamics and predict Ailanthus encroachment mechanisms also in presence of disturbance effects and under climate change. In this work, the CATGraSS, an ecohydrological Cellular Automata model (Zhou et al., 2013), has been used for simulating spatio-temporal dynamics of Ailanthus altissima in a specific site of “Vallone di Piano della Corte” Nature Reserve, in the Erei mountains in central Sicily (Italy). The study area has a surface of approximately 1 km2 and it is characterized by a relevant nucleus of Ailanthus that has been growing rapidly in recent years. The study aims to reconstruct Ailanthus altissima spatio-temporal evolution in the study area over the last century. The model has been calibrated using the current Ailanthus distribution maps, obtained by classifying high-quality satellite images, collected by PlanetScope constellation, exploiting modern remote sensing techniques, together with field surveys.
A human-in-the-loop approach to monitor blue carbon ecosystems at scale with Copernicus Sentinel-2 imagery
Authors: Krüger Gyde , Huber Silvia , Nielsen Lisbeth T. , Daniel Paul , Malathounis Charalampos , Hansen Lars B.
Published: March 2024

A human-in-the-loop approach to monitor blue carbon ecosystems at scale with Copernicus Sentinel-2 imageryBlue carbon ecosystems, such as seagrass meadows, mangroves or coral reefs play an essential role for food provision, erosion control, disaster resilience, biodiversity and as habitats, and in addition they serve as important natural sinks for carbon. With increasing climate pressures and human impacts related to eutrophication, overfishing and habitat fragmentation, the coverage and health of these coastal habitats have declined globally. To address this, it requires first and foremost an accurate quantification of the distribution and quality of these ecosystems. This poses challenges from multiple angles (i.e., lack of manpower, fiscal limitations, etc.). By exploiting the full capacity of Copernicus Sentinel-2 imagery and AI technology, we have developed a cloud-based interactive platform, MCSAV – short for Mangrove, Coral and Submerged Aquatic Vegetation (Figure 1) – to map and improve the planning, management and monitoring of blue carbon ecosystems worldwide. The platform is designed with a focus on making coastal mapping as easy as possible for users with greater local knowledge of blue carbon ecosystems but without expert knowledge in satellite image processing or machine learning. The entire mapping process, from the selection of suitable satellite imagery to the final classification, can be executed in just a few clicks with the platform. The backbone of the classification model that is integrated into the backend of the platform, is a pretrained convolutional neural network (DeepResUNet). A Human-in-the-Loop component allows fine-tuning of the pre-trained classification model with additional training data.Our approach has already been applied to high latitude regions with success [1] and is currently applied to Semporna in Sabah, Malaysia, as part of the United Nations Development Programme’s (UNDP) third cohort of Ocean Innovations on marine protected areas, area-based management, and blue economy.We will give an introduction into the project, present the methods implemented in our interactive mapping approach, and demonstrate the coastal mapping tool. We will conclude with some lessons learnt and an outlook.Figure 1 MCSAV interface showing Copernicus Sentinel-2 image of 13 March 2023 after pre-processing module has been run (top) and an example habitat classification (preliminary) and deepwater areas for Mapul region (bottom). References[1]          S. Huber et al., “Novel approach to large-scale monitoring of submerged aquatic vegetation: A nationwide example from Sweden,” Integr Environ Assess Manag, vol. 18, no. 4, pp. 909–920, 2022, doi: https://doi.org/10.1002/ieam.4493. 
Differential Cooling Efficacy of Fine-Grained Urban Green Spaces Across Diverse Functional Zones: A Case Study in the Beijing Metropolitan Area, China
Authors: Zeng Yue , Guo Jianhua , Zhu Xiao Xiang
Published: March 2024

The urban heat island effect is a well-documented phenomenon in cities, particularly in metropolitan areas, with recognized environmental consequences. Mitigating this effect through urban green space planting strategies has been widely acknowledged. However, the extent of the spatial heterogeneity of the cooling effect across different urban functional zones remains insufficiently explored at a fine scale of urban green space.In this study, we employed a robust semi-supervised deep learning method to precisely segment urban green spaces from high-resolution remote sensing images and developed a 0.5 m fine-scale urban green space product tailored for the Beijing metropolitan area. Leveraging the fine-grained urban green space segmentation results, we modeled cooling efficiency through a nonlinear relationship, quantified as the temperature reduction for a 1% urban green space cover increase. We also conducted a comprehensive assessment of differential cooling efficacy, considering both reference temperature and urban green space cover levels, across diverse urban functional zones at the scale of 300 m × 300 m urban grids.The results revealed substantial disparities in cooling efficiency among different urban functional zones and different levels of urban green space coverage in Beijing. To be specific, with a 1% increase in urban green space, the commercial zone, residential zone, industrial zone, transportation zone, and public zone can achieve a cooling effect with a mean of 0.095 ± 0.075°C, 0.075 ±0.065°C, 0.075±0.065°C, 0.070±0.060°C and 0.055±0.045°C respectively. By uncovering spatial variations and heterogeneity in cooling effects, our study underscores the critical need for customized strategies in urban green space planning based on functional zone characteristics and offers valuable insights into urban planning and sustainable development practices.
Subsurface characterization using downhole passive Distributed Acoustic Sensing data in the Groningen gas field
Authors: Zhou Wen , Stork Anna , van Elk Jan , David Ari , Paulssen Hanneke , Muntendam-Bos Annemarie
Published: March 2024

This study presents passive downhole Distributed Acoustic Sensing (DAS) measurements conducted in the Groningen gas field, Netherlands, for subsurface and induced seismicity monitoring. The optical fiber installation, completed in Sept 2015, was partially cemented behind the inner casing along a deviated well (~3800 m), extending into the sandstone reservoir at temperatures ranging from 100-110 degrees Celsius. In Nov 2022, we interrogated the optical fiber utilizing a 10 m gauge length and 1 m sampling spacing.Within this setup, most DAS traces exhibit the lowest self-noise floor in the frequency range of 0.1 to 30 Hz. Noteworthy is the absence of visible differences between cemented and uncemented sections. Strong ambient seismic noise is observed in the near-surface unconsolidated sediment at approximately 800 m depth. Noise cross-correlation (CC) analysis is performed for DAS channels and DAS seismometer pairs. Surface wave signals in the 0.1 to 1 Hz range are identified in DAS-seismometer CCs, displaying amplitude and polarization changes with depth, following Surface wave theory.Induced seismicity is also recorded, with wavefields of events exhibiting clear amplitude variations along the fiber, strongly correlating with sonic logging. Our findings suggest that downhole DAS has the potential to characterize the subsurface with high resolution.
Dynamics of Persistent Low-Frequency Radio Pulsations During the November 04, 2015 CME
Authors: Kozarev Kamen
Published: March 2024

Detailed interferometric radio observations of solar activity allow us to constrain the dynamics of high-energy electron beams accelerated in flares and coronal mass ejections (CME). We have studied in detail the small-scale solar radio bursts, which accompanied one of the three homologous solar eruptions that originated from the western solar limb on November 04, 2015. We have used interferometric observations from the Murchison Widefield Array to image the multi-frequency emission in several radio channels between 80 and 300 MHz with 1-second resolution and 20 arcsec-pixels. The event began with a strong type II radio burst, and was followed by a separation of the emission into stationary and moving sources, the latter clearly related to the propagating CME structure. The observations show simultaneous multi-frequency flickering of intensity along a persistent off-limb structure related to the CME-driven shock wave, connecting the stationary and moving sources. This flickering emission persisted for more than 30 minutes. We present an analysis of its dynamics, its relation to the CME flux rope, the expected magnetic configurations, and electron beam properties. These observations provide valuable information about the evolution and kinematics of the CME in its early stages. 
Friction at the grain-scale: the role of inter-particle friction in granular media and its influence on grain-scale bed behaviour
Authors: Moss Jack , Glovnea Romeo
Published: March 2024

Granular media has near omnipresence in nature and is the second most processed substance in industry, after water. It is well accepted that it exhibits a wide spectrum of macro-scale behaviour which is ultimately determined by the grain-scale interactions of its constituent particles [1][2][3]; but there is still much to be discovered about those grain-scale interactions themselves. Away from the free surface of an agitated granular bed, the dominant grain-scale interactions are relative sliding and rolling between neighbouring particles [4], and it is this sliding and rolling which is the subject of this research.In these experimental lab-based tests, ‘dry’ and ‘wet’ ideal granular beds are harmonically compressed via a moving side-wall and their responses captured via high-speed imaging. The granular media itself is a quasi-2D bed of polydisperse discs consisting of an even mixture of five different disc diameters ranging from 11mm to 36mm. The cyclic compressions are specifically designed to impose a jamming effect within the granular beds, before subsequent relaxation and deformation.Use of the photo-elastic technique provides a window through which the grain-scale behaviour of the beds can be examined, as networks of inter-particle contact forces, known as force chains, become visible. Disc rotation is measured by tracking lines drawn onto each disc, providing useful insight into the sliding and rolling inter-particle interactions at the grain-scale. First, the behaviour of a ‘dry’ granular bed is examined, and then a thin layer of glycerol is spread onto the edges of each individual disc in order for the behaviour of an equivalent ‘wet’ granular bed – or at least, a bed with reduced inter-particle friction – to be examined. The behaviour of these beds are then compared to one another, and the results used to discuss how changes to friction at the grain scale affects the behaviour of granular bodies.  [1] Singh, S., Murthy, T.G.: Evolution of structure of cohesive granular ensembles in compression. International Journal of Solids and Structures 238(1), 111359 (2022)[2] Jiang, M., Yu, H., Harris, D.: A novel discrete model for granular material incorporating rolling resistance. Computers and Geotechnics 32(5), 340–357 (2005)[3] Oda, M., Konishi, J., Nemat-Nasser, S.: Experimental micromechanical evaluation of strength of granular materials: effects of particle rolling. Mechanics of Materials 1(4), 269–283 (1982)[4] Moss, J., Glovnea, R.: Behavioural responses to horizontal vibrations of quasi-2D ideal granular beds: an experimental approach. Granular Matter 25(4), 63 (2023).