bluuebunny/crossref_metadata_2025 huggingface dataset:
Zooming into the transition between thrusting and strike-slip in an intra-continental compressional setting
Authors: Köhler Saskia , Koehn Daniel , Stollhofen Harald , Fazlikhani Hamed , Stephan Tobias , Duschl Florian
Published: February 2023

We investigated Mesozoic sequences of the Franconian Platform (SE Germany) according to their deformation history. Based on field observations we performed fault-slip and stylolite stress inversion. We could distinguish two stress cycles in an intraplate compressional setting starting with (i) normal faulting, (ii) thrusting and the development of folds and tectonic stylolites (iii) and strike-slip regimes. The first cycle is caused by the Europe-Iberia-Africa collision in the Cretaceous, while the second cycle is induced by the Cenozoic Alpine orogeny. We can zoom into the transition between the thrusting and strike-slip regime of the first cycle by the preservation of a stress field with none principal stress being in the vertical axis. The combination of field and microscopic observations shows a rather complex chronology of this relatively short time span with alternating sedimentary and tectonic stylolites.With our work we contribute to the understanding of stress development in intraplate compressional settings.
Microbial community dynamics and utilization of rhizodeposits and synthetic urine in grassland soils.
Authors: Koirala Manisha , Ding Yang , Banfield Callum , Dipplod Michaela
Published: February 2023

Microbial community dynamics and utilization of rhizodeposits and synthetic urine in grassland soils. Manisha Koirala 1, Yang Ding 2, Callum C. Banfield2, Michaela A. Dippold2 1 Biogeochemistry of Agroecosystems, University of Göttingen, 37077 Göttingen, Germany 2 Geo-Biosphere Interactions, University of Tübingen, 72076 Tübingen, Germany Soil microbes thrive in a wide range of nutrient inputs and cope with an imbalanced supply of resources by adjusting their utilization strategies. In grasslands, animal urine and root exudates are essential drivers of C and macronutrient inputs and thus microbial growth and community composition, but little is known about how urine and exudates affect microbial community dynamics and utilization. In a factorial design, synthetic cow urine was applied to a Vertic Cambisol densely rooted by Dactylis glomerata. One day, four days, and 14 days after synthetic cow urine application, root-affected and not-rooted bulk soils were harvested. CFE microbial biomass, phospholipid fatty acids (PLFAs), DNA, and enzymatic activities were quantified to characterize the microbiome and its metabolic response.Shoot biomass increased by 11%, 21%, and 36% at one, four, and 14 days after urine application compared to water application respectively. Root biomass increased by 4% and 9% after four and 14 days of water application, respectively, compared to urine application. In the root-affected soil, the activity of the enzyme acid phosphatase was 26%  higher 14 days after water application compared to that of urine. Conversely, the activity of the ß-glucosidase was 10% higher 14 days after cow urine application compared to water application in root-affected soil. Similarly, 14 days after urine application MBC in bulk soil was 84% higher compared to only water application. However, in the root-affected soils, MBC was 18% higher with water compared to urine application. The amount of DNA was also 0.5% higher 14 days after urine application compared to water application in the root-affected soils.This study examined and compared the metabolic response of microbial communities and microbial community dynamics due to synthetic urine and water in bulk and root-affected soil. By approaching the study of soils from chemical as well as biological perspectives, an overview of microbial adaptation and structure can be gained to maintain healthy soil in grassland ecosystems.Keywords: synthetic cow urine, grassland, soil microbial communities, root-affected soil, bulk soil, extracellular enzymes.   
Assessing the atmospheric correction algorithms for improving the retrieval data accuracy in the remote sensing technique
Authors: Diganta Mir Talas Mahammad , Uddin Md Galal , Olbert Agnieszka I.
Published: February 2023

For the purposes of cost-effective and rapid surface water quality monitoring, the utilization of the cutting-edge satellite remote sensing (RS) technique has increased over the years. Recently, several studies have revealed that the RS technique severely suffers from particles present in the atmosphere, especially from aerosol particles. This interference significantly influences the quality of the information extracted from remote sensing measurements and produces much more uncertainty in retrieving optically active water quality indicators (e.g., chlorophyll-a, coloured dissolved organic matter, total suspended matter) from optically complex water bodies. Therefore, it is required to minimize the uncertainty within the remotely sensed data by reducing the impact of atmospheric interference through the atmospheric correction (AC) process. Currently, a series of algorithms have been utilized in the literature for treating the AC in the RS technique, among which ACIX-Aqua, ACOLITE, BAC, C2RCC, FLAASH, iCOR, l2gen, LaSRC, POLYMER, GRS, Sen2Cor, and 6SV are widely used. Since the development of the AC algorithms, its applications have increased in handling of big data, like as remote sensing data. Recently, several studies have revealed that the existing algorithms have produced a considerable uncertainty in the retrieval data due to the architectural complexity of algorithms. Although, the application of cutting-edge machine learning and artificial intelligence techniques is increasing for atmospheric correction process. Therefore, the aim of the research is to develop an efficient algorithm utilizing the publicly available AC algorithms and incorporating machine learning and artificial intelligence approaches in order to reduce atmospheric interference from the RS data. The results of the research could be helpful for retrieving various optically active water quality indicators most efficiently in terms of reducing the uncertainty in monitoring water quality.
Keywords: surface water quality; remote sensing; atmospheric correction, artificial intelligence; optically active water quality indicators.
The evolution of a thrust belt within a continental indenter: investigating the internal deformation of the Dolomites Indenter, eastern Southern Alps, in a combined low-temperature thermochronology, field and analogue modelling study
Authors: Pomella Hannah , Klotz Thomas , Sieberer Anna-Katharina , Ortner Hugo , Wzietek Alexandra , Dunkl István , Willingshofer Ernst
Published: February 2023

The Dolomites Indenter represents the eastern front segment of the Neogene to ongoing N(W)-directed continental indentation of Adria into Europe. Concomitant shortening is accommodated within a south-vergent thrust belt, situated between the Periadriatic Fault system and the South-Alpine front. A combination of low temperature thermochronological analyses, focussed mapping and analogue modelling is used for unravelling the Neoalpine history of the crustal and lithospheric scale tectonic processes during indentation.In our analogue models, extensional platform-basin geometries, formed at passive continental margins, are subject to subsequent shortening and orogenesis. Parallel to oblique (10 to 20 degrees with respect to the basin axes) contraction has been applied leading to the inversion of the pre-orogenic basins. The experiments show that the simple presence of an inherited platform-basin configuration controls the overall style of compressional deformation, no matter of including frictional or viscous basal décollements, of varying the rheology of the basin fill, or of changing platform-basin thickness ratios. Orientations of thrust faults change laterally across inherited platform-basin transitions throughout all experiments. New fault slip data and shortening directions from fold axes along the western segment of the Belluno thrust of the Valsugana fault system support variations of thrust fault orientation and a lateral change in shortening direction (from SSW to SSE along strike) along one single fault. Based on our modelling results, we infer that this variability of shortening directions depends on inherited structures and do not necessarily reflect different deformation phases.Our low-temperature thermochronological dataset (zircon and apatite (U-Th)/He, and apatite fission track analyses) focuses on the Dolomites Indenter and spans from the Periadriatic Fault System (Pustertal-Gailtal fault) in the north to the footwall of the Bassano thrust in the south. The results argue against an only in-sequence fault activity within the dominantly WSW – ENE striking thrust belt but indicate a more complex fault system development, including backstepping fault activity. This is locally supported by field observations of fault cross-cutting relationships (e.g., at the Moschesin fault near Agordo). Remarkable that west of the Transalp Corridor Mesozoic apatite fission track ages are preserved within fault delimited areas while further to east all apatite fission track data show Cenozoic ages indicating younger exhumation in the eastern part of the study area.
Satellite data as a predictor for monitoring tree health and stress in reforestation projects
Authors: Van den Dool H. Gijs J. , Bidwai Deepali
Published: February 2023

In many parts of the world, reforestation is an ongoing activity, but due to the deforestation processes (e.g. the change in soil conditions, agricultural expansion, and infrastructure expansion such as urbanisation or road building), the success rate of replanting is far from sure; therefore, it is essential to:have a good idea of the pre-planting conditions at the location,
monitor the growth,
improve the growing conditions whenever possible, and
adapt the site selection criteria
In the proposed method, it is not possible to change the site selections of already planted locations, but it is possible to monitor the selected location and check under which conditions the trees are growing best. Several data sources are identified to predict plant health and stress, first to establish a baseline and, from this baseline, project into the future (short and mid-term). We compute the main vegetation index (NDVI) from the high-resolution image data provided by Planet (through the NICFI Basemaps for Tropical Forest Monitoring program). The historical NDVI values are obtained from the Sentinel 2 (and potentially LandSat) data at lower resolutions. Environmental conditions are added to the stress index by extracting the relevant meteorological parameters from the ERA5 database (temperature and precipitation) to compute the drought indices (e.g. KBDI/SPI/SPIE) and water availability (AWC) with the dominant soil type, supplemented with supporting indices from the satellite data (e.g. NDWI/SAVI/EVI-2).For reforestation projects, it is vital to monitor the impact of environmental parameters on plant health and stress, and to assist with the forest maintenance of the sites, we built time series models for temperature, precipitation, and various vegetation indices to create a baseline for site-specific growing conditions. Deep Learning (DL) models like semantic segmentation based on Convolutional Neural Network (CNN) can be built on top of it using transfer learning to extract the features from pre-trained models using large (global) datasets. The model can not only predict tree health but can also be used to predict growing conditions in the near future by flagging out potential dry periods before they happen.The high-resolution remote sensed products are available in the (sub)tropical zone [30N - 30S], while the lower resolution products and the ERA5 data have a global cover. The test sites in this study are example sites, but the developed method can be applied to any reforestation monitoring project. The result of the analysis is a near-term growth indicator, which can be used to adjust the growing conditions of the site, as well as assist with the site selection for new reforestation projects (based on the established baseline and predictions).The next step, after validation, is to create a dashboard where the user can select any location (within the data domain) and construct the baseline and prediction, based on available information.
Anthropogenic and natural CH4 and CO2 emissions observed by a combination of passive, active, and in situ airborne measurements during the CoMet 2.0 Arctic mission in Canada 2022
Authors: Krautwurst Sven , Borchardt Jakob , Huhs Oke , Gerilowski Konstantin , Fruck Christian , Galkowski Michal , Burrows John P. , Gerbig Christoph , Fix Andreas , Bösch Hartmut , Bovensmann Heinrich
Published: February 2023

Anthropogenic greenhouse gas (GHG) emissions remain the main concern for global climate change. To reduce and mitigate those emissions both anthropogenic and natural sources must be identified and quantified. However, high northern latitude wetland regions may also overlap with, e.g., fossil fuel extraction sites. Consequently, commonly used passive satellite sensors are often challenged to observe and disentangle those emissions due to challenging illumination conditions and their large ground scene size, respectively.To investigate anthropogenic and wetland GHG emissions, a team of scientists deployed a comprehensive suite of instruments aboard the German Research aircraft HALO (High Altitude and Long Range Research) during the CoMet 2.0 Arctic mission conducted in Canada in August and September 2022. During the campaign, passive airborne remote sensing measurements by MAMAP2D-Light (Methane airborne mapper 2D light) were combined with active airborne remote sensing measurements by CHARM-F (CH4 Airborne Remote Monitoring – Flugzeug) and in situ GHG concentration measurements, also including an extensive suite of meteorological parameters.Those column and in-situ concentration observations of CH4 and CO2 will be used to identify and quantify emissions over a wide range of source types and scales in Canada (and Europe). This comprises single point source emissions (e.g., power plants), small areal sources such as landfills (e.g, the Valdemingomez and Pinto landfills in Madrid) and opencast coal mines, and extensive oil and gas exploration sites, including oil sand areas, which might be embedded in natural wetland regions or river deltas. The imaging capabilities of the MAMAP2D-Light instrument enable precise localisation of emissions and therefore mitigation strategies in the case of, e.g., leakages. This work will summarize and present first results and emission estimates from the CoMet 2.0 Arctic mission with a focus on localised emitters observed by the airborne imaging instrument MAMAP2D-Light.
Distributions of tritium in the marine water and biota around Rokkasho Reprocessing Plant
Authors: Ohtsuki Satoru , Shirotani Yuhei , Takata Hyoe
Published: February 2023

For decommissioning of Fukushima Daiichi Nuclear Power Station (FDNPS), it is one of the biggest problems to treat the radioactive contaminated stagnant water in the building. It is difficult to remove H-3 from the contaminated water by only Advanced Liquid Processing System (ALPS) treatment. Thus, the Japanese Government announced to release the ALPS treated water containing H-3. To predict the alteration of the dose rate of the marine biota by the change of H-3 concentration in marine water after the release of ALPS water, it is necessary to understand the dynamics of H-3 in marine ecosystem. In this study, we studied the behavior of H-3 in the marine environment (water and biota) off Aomori and Iwate prefectures from FY2003 to FY2012, as the background data of the Pacific Ocean along the coast of the North East Japan. To clarify the dynamics of H-3 in marine biota, we compared H-3 and Cs-137. Excluding the period of the intermittent test operation of the Rokkasho Reprocessing Plant (FY2006-FY2008), the concentration of H-3 in seawater, tissue free water tritium (TFWT) and organically bound tritium (OBT) were 0.052-0.20 Bq/L with a mean of 0.12±0.031 Bq/L, 0.050-0.34 Bq/kg-wet with a mean of 1.1±0.039 Bq/kg-wet and 0.0070-0.099 Bq/kg-wet with a mean of 0.042±0.019 Bq/kg-wet, respectively. Before the FDNPS accident (FY2003-FY2010), Cs-137 concentration in seawater and marine biota were 0.00054-0.0027 Bq/L with a mean of 0.0016±0.00041 Bq/L and 0.022-1.8 Bq/kg-wet with a mean of 0.090±0.037 Bq/kg-wet, respectively. Concentration Ratio (CR), the ratio of the concentration of marine biota and seawater for TFWT, was to be 0.34-2.37 with a mean of 0.97±0.31 in all spices, meaning the concentration of marine biota was almost equal to seawater. For Cs-137, CR were 46-78 with a mean of 56±22. We compared CRs for TFWT of Gadus macrocephalus, Lophius litulon and Oncorhynchus keta with those of Cs-137. Comparing CR-TFWT and CR-Cs-137 for these three species, Spearman-R was <0.4 and p was >0.05, indicating that the dynamics of TFWT and Cs-137 in marine ecology is decoupled.
NH3 emissions derived from CRIS observations over Europe
Authors: Ding Jieying , van der A Ronald , Eskes Henk , Dammers Enrico , Shephard Mark
Published: February 2023

Over the past century ammonia (NH3) emissions have increased with human population growth and fertilizer usage. The abundant NH3 emissions lead to climate change, reduction in biodiversity and affect the human health. Up-to-date information of NH3emissions are essential to better understand the impact of NH3. In this study we adapted the existing DECSO (Daily Emissions Constrained by Satellite Observations) algorithm for use of NH3 observations from the Cross-track Infrared Sounder (CrIS) to estimate NH3 emissions. By considering the interaction between NH3 and NOx, we implemented DECSO to estimate NOx and NH3 emissions simultaneously on 20 km resolution over European domain. NH3 and NOx emissions over Europe are derived for 2020 on a daily basis from CrIS and TROPOMI (on Sentinel 5p). Due to the sparseness of daily satellite observations of NH3, monthly emissions of NH3 are constructed and analysed.  The comparison of these emissions with other existing emission inventories will be presented.
Representation of different flood types in rainfall-runoff modelling
Authors: Thiele Luisa-Bianca , Salehfard Golbarg , Spadari Germán Enrique , Haberlandt Uwe
Published: February 2023

Flood characteristics vary due to different processes causing the floods. Classifying flood events according to their causative processes can help to improve the estimation accuracy of flood probabilities. Hydrological models can be used for derived flood frequency analyses when the length of observed climate and runoff data is insufficient. This also allows the estimation of uncertainties due to variable catchment characteristics, climate conditions, and runoff regimes. The aim of this work is to investigate whether rainfall-runoff models are capable of reproducing different flood types. Observed flood events of the period 1980 - 2020 are classified according to the approaches of Fischer et al. (2019) and Tarasova et al. (2020). The conceptual rainfall-runoff model HBV-IWW is operated for 120 meso- and macroscale (30km² - 1500km²) catchments in Germany. Observed and simulated flood events are compared to assess the model performance separately for different flood types. In addition, the model performance is evaluated for the pre-event phase to determine whether the preconditions of the flood event are met.  The results indicate that the model reproduces certain flood types better than others. The model performance is in particular poor for snow dominated flood events both for the pre-event phase and during the flood event. The outcome of these investigations should help to find and improve the deficits of the hydrological modelling.
Automated mapping of grain size distributions from UAV imagery using the CNN-based GRAInet model
Authors: Lendzioch Theodora , Langhammer Jakub , Kootanoor Sheshadrivasan Veethahavya
Published: February 2023

The grain size distribution of gravel riverbed material is an essential parameter to estimate the sediment transportation, groundwater-river flow interaction, river ecosystem, and fluvial geomorphology. Conventional and present methods of obtaining grain size distribution analysis of more extensive areas are time-consuming and remain challenging in effectively modeling sediment load. On this account, this paper appraised the role of employing the end-to-end data-driven GRAINet approach, a convolutional neural network (CNN) application, to predict and map the grain size distribution at particular locations over an entire gravel bar based on georeferenced drone-based orthoimagery. We conducted multiple drone surveys after post-flood events in the Javoří Brook Šumava National Park (Šumava NP) in Czechia over a small unregulated montane stream with an exposed gravel bar and frequently changed fluvial dynamics. The GRAINet model performances between the predicted mean diameter (dm) and ground truth diameter dm (human performance) produce the result of different loss functions, i.e., the mean absolute errors (MAEs), the mean squared errors (MSEs), and the root-mean-square errors (RMSEs). Corresponding averages of MAEs varied between 3 cm to  4.8 cm with standard deviations (STDs) of 1.7 cm and 3.8 cm, respectively. The averages of MSE ranged between 13 cm to 14.5 cm with  STDs of 12.7 cm and 12.8 cm, and RMSE of 3.2 cm to  5.6 cm with STDs of 1.6 cm and 4.6 cm, respectively. With high to moderate accuracies and lower computational costs than other deep learning approaches, the tested ensemble model shows that the integration of UAV remote sensing and machine learning (ML) provides a promising tool to help make decisions using timely mapped high-resolution grain size maps without access to direct object counts or locations.   
Design Rainfall controls on Pluvial Flood Risk at different spatial and temporal scales – a U.S. case study
Authors: Nicotina Ludovico , Moges Edom , Sharifian Mohammad , Jankowfsky Sonja , Li Shuangcai , Hilberts Arno
Published: February 2023

As Catastrophe models tend to focus more on Fluvial Flood Risk, Pluvial Flood Risk can be sometimes underestimated or neglected. However, when high intensity and short duration events such as hurricanes Ida and Ian occur in urban and semi urban areas, failure to account for Pluvial Flood Risk is consequential. To this end, the importance of accurately estimating Pluvial Flood Risk has strengthened.In this study, we investigate the sensitivity of Pluvial Flood Risk to design rainfall characteristics. In particular, we explored the trade-off between flood extent and flood depths for different design rainfall durations, as well as the resulting economic losses at different spatial scales covering local, catchment and county levels. The study focuses on urban and semi-urban areas, where besides rainfall duration and intensity, drainage characteristics are expected to play a significant role in Pluvial Flood Risk.
Response of Mature Storms to Soil Moisture State in Global Hotspot Regions
Authors: Barton Emma , Klein Cornelia , Taylor Christopher , Marsham John , Parker Douglas
Published: February 2023

Mesoscale Convective Systems (MCSs) represent some of the most intense and destructive thunderstorms in the world. Understanding the physical processes that drive these storms and influence their characteristics is vital for hazard prediction and mitigation. A significant amount of research in the “natural laboratory” of West Africa has shown that soil moisture heterogeneity on different spatial scales can influence the location of convective initiation (10s of km) and the intensification of remotely triggered storms (100s of km).Previous studies have demonstrated that the control of soil moisture state on convective initiation identified in West Africa is also important elsewhere in the world whereas very little is known about the influence of surface conditions on travelling storms in other regions.In the current work we combine satellite observations and reanalysis data to characterise the impact of pre-storm soil moisture conditions on the atmospheric environment and characteristics of mature storms in seven MCS hotspot regions, West Africa, South Africa, South America, Great Plains, India, China and Australia. We observe a clear latitudinal dependence of the coupling signal with distinct differences between regions where convection is predominately driven by monsoonal or frontal dynamics. However our results suggest that in all regions, large-scale (100s of km) soil moisture gradients are having an impact on convection within mature MCSs through moderation of the climatological temperature gradient in the lower atmosphere, which influences factors that favour convection such as shear and convergence.
Water observations by the public- experiences from the CrowdWater project
Authors: van Meerveld Ilja , Schwarzenbach Franziska , Goebel Rieke , Scheller Mirjam , Blanco Ramirez Sara , Seibert Jan
Published: February 2023

Hydrology is a data limited science, especially spatially distributed observations are lacking. Citizen science observations can complement existing monitoring networks and provide useful data. Engaging the public in data collection can also increase people’s interest and awareness about water-related topics. In this PICO, we will present the CrowdWater project, in which citizen scientists share, with the help of a smartphone app, hydrological observations on stream water levels, the presence of water in temporary streams, soil moisture conditions, plastic pollution, and general information on water quality. We will highlight the type of data that are collected, our quality control procedures, and the value of the data for hydrological model calibration. We will also discuss the motivations of the citizen scientists to join the project and to continue to contribute to the project. Although the majority of our frequent contributors are adults, we try to engage the youth in the project by giving presentations in schools and at science fairs. Therefore, we will end the PICO presentation with some examples of our outreach work and lessons learned.
Comparison of Runoff characteristics in bare and vegetated headwater catchments, Northern Alps, Japan
Authors: Fujino Mayu , Sakakibara Koich , Tsujimura Maki , Suzuki Keisuke
Published: February 2023

We evaluated an effect of alpine vegetation on water storage and runoff characteristics in alpine zones. We sampled rainwater, snowmelt water and runoff water from bare and vegetated catchments in August and October 2019 in headwater catchment of Mt. Norikura, Japan. We compared the water chemistry of runoff water from bare catchments and vegetated catchments. The pH, electrical conductivity and total dissolved ion concentrations of runoff water from vegetated catchments were higher than those from bare catchments, suggesting a longer contact time between water and the regolith in the vegetated catchments. We also applied two-component hydrograph separation to calculate the contribution of precipitation and groundwater components to the runoff water. The contribution of groundwater component to runoff water ranged from 0.8% to 63.8% in the vegetated catchments, whereas that ranged from 0.3% to 14.6% in the bare catchments. Furthermore, the groundwater contribution was higher in the area with vegetation predominantly over the bare area in each catchment. This suggests that the runoff water has longer transit time in the vegetated areas than the bare areas. In the vegetated areas, the subsurface water should flow with longer transit time due to an existence of well-developed regolith with coarse-grained sediments as compared with that in bare areas. Thus, the alpine vegetated area has a higher water storage function than the bare area. Our results show that we need to consider the vegetation and regolith conditions and subsurface flow processes to the hydrological processes in mountainous areas, especially in alpine zones.
Exploring Coronal Structures in Metric-Decametric Radio Imaging
Authors: Kozarev Kamen , Zucca Pietro , Zhang Peijin , Stepanyuk Oleg , Nedal Mohamed
Published: February 2023

Large-scale solar coronal structures may have very different signatures in low-frequency metric-decametric interferometric images than their optical/EUV counterparts, or even at higher frequencies. Notable examples are coronal holes and streamers. This may be due to scattering effects of the thermal emission in the corona, or to unexpected mechanisms contributing to the overall emission at these frequencies, such as gyrosynchrotron emission. In this work, we explore the effects of frequency and emission mechanisms (thermal and gyrosynchrotron) on large-scale coronal structures, comparing data with synthetic observations based on global magnetohydrodynamic modeling and forward modeling. We analyze observations by the LOw Frequency ARray (LOFAR) and Murchison Widefield Array (MWA) radio telescopes in a frequency range between 20-250 MHz. We address the unanswered question of why coronal holes often appear bright in the lowest frequencies observable on the ground, and whether this changes with the observer’s viewpoint. We attempt to segment and classify large-scale coronal structures based on their multiwavelength appearance and emission mechanism.
P-TRAP – Reducing diffuse phosphorus input to surface waters
Authors: Behrends Thilo , Walter Sylvia
Published: February 2023

In 2019 the EU Marie Sklodowska-Curie Training Network P-TRAP has been launched and is now approaching its end. The project has been targeting the diffuse flux of phosphate (P) into surface waters, i.e. the problems of understanding and controlling environmental P fluxes. P-TRAP has been aiming to develop new methods and approaches to trap P in drained agricultural areas and in the sediments of eutrophic lakes. The P-TRAP technologies have in common that they rely on the naturally strong connection between the biogeochemical cycling of P and iron (Fe). Trapping of P involved the application of Fe-containing by-products from drinking water treatment. P-TRAP aspired the ideas of a circular economy and aimed at recovering the retained P in agricultural systems and to convert it into valuable products for agricultural applications. In order to direct and support the development of the technologies, process-orientated investigations on the behaviour of P during the transformation of Fe minerals have been conducted. The poster will highlight some results from the project and will present conclusions, which can be drawn based on the current achievements.
Contourites and paleo-gateways: An integrative ichnological and sedimentological approach
Authors: Rodriguez Tovar Francisco Javier , Hernandez Molina Francisco Javier , Miguez-Salas Olmo
Published: February 2023

Closing and opening of ocean paleo-gateways strongly influenced the tectono-stratigraphic and sedimentary evolution of basins, affecting global ocean circulation, climate, sedimentary processes, and living biota. Particularly, closing and opening of ocean paleo-gateways determine significant changes in ocean dynamic affecting deepwater circulation, and then deepsea sedimentary facies and benthic community. Changes in bottom-current dynamic and their effects (e.g., erosion, nondeposition and variable rate of deposition) can cause changes in substrate features that might exert a major effect on the benthic habitat. To improve knowledge of paleo-gateways, involved oceanographic processes, and variations in the depositional systems, detailed analysis of the Contourite Depositional Systems and associated sediments controlled by deep-water circulation processes reveals of major interest. In this context an integrative ichnological and sedimentological approach is proved as a useful strategy.This study focuses in the application of an integrative sedimentological (i.e., primary sedimentary structures, grain size analysis, microfacies, etc.) and ichnological approach to improve characterization of contourites and differentiation from other deep-sea facies associated to paleo-gateways. Examples from middle Miocene contourite deposits in Cyprus associated to the Indian Gateway, the late Miocene contourites Morocco related to the Rifian Corridor and from the Pliocene and Quaternary deposits in the Gulf of Cadiz related to the Strait of Gibraltar are presented. Changes in paleoenvironmental (ecological and depositional) conditions induced by gateways evolution, as hydrodynamic energy, rate of sedimentation, organic matter availability, affecting tracemaker community are interpreted based on integration of sedimentological and ichnological features.
Automatic landslide detection using Sentinel-1 and -2 images - a glacial case study
Authors: Ganerød Alexandra Jarna , Lindsay Erin , Fredin Ola , Myrvoll Tor-Andre , Nordal Steinar , Calovi Martina , Rød Jan Ketil
Published: February 2023

Although Norway is a country with rough terrain and a high frequency instable steep slopes, there is a scarcity of landslide data available. This limits the accuracy of thresholds for early warning systems, and hazard maps, both of which rely on historic event data. There is great potential to supplement existing ground-based observations with automated landslide detection, using satellite imagery and deep learning. In working towards an automated system for landslide detection in Norway, we investigated which imagery types and machine-learning models performed best for detecting landslides in a formerly glaciated landscape.We locally trained a deep learning model with the use of Keras, TensorFlow 2 and U-net architecture. As input data, we used multi temporal composites with Sentinel-1 and -2 image stacks of all available images from one month pre- and post-event. Processed bands included: dNDVI (difference in maximum normalised difference vegetation index) from Sentinel-2, and pre- and post-event Synthetic Aperture Radar (SAR) data (terrain-corrected, mean of multi-temporal ascending descending images, in VV polarisation) from Sentinel-1. Training and evaluation were performed with a well-verified landslide inventory of 120 manually mapped rainfall-triggered landslides from Jølster (30-July-2019), in Western Norway. We tested the model with four input data settings using different bands and various polarization for the pre- and post-event SAR data, including: 1) full version (all 13 bands) 2) dNDVI (Sentinel-2), preVV, postVV (Sentinel-1), 3) preVV, postVV (Sentinel-1), and 4) post-R, post-G, post-B, post-NIR, dNDVI (Sentinel-2). The results were compared to the results of a pixel-based conventional machine learning model (Classification and Regression Tree) using the same input data. The second input data setting provides the best results. The performance scores show precision results for all four input data settings between 80-85%, with Matthews corelation coefficient values from 51-89%. Moreover, the deep-learning model significantly outperforms the conventional machine learning model in the input data setting #3. We see that the patch-based classification method far out-performs the pixel-classification due to the ability to differentiate the landslide signal from random noise produced from speckle in undisturbed areas. In addition, this represents one of the first attempts to fuse SAR and optical data for landslide detection, and we show there is an advantage in doing so in this case. 
Observations and modelling of water balance components with the Noah-MP land surface model in a Mediterranean pine forest
Authors: Sofokleous Ioannis , Eliades Marinos , Djuma Hakan , Siakou Melpomeni , Bruggeman Adriana
Published: February 2023

The Noah-MP land surface model is a multi-parameterization model that simulates the components of the energy and water balances at the land surface and the interaction of these components with the atmosphere. Modifying and parameterizing the model equations with the use of field observations can improve model applications for the local area but also for areas with similar environmental conditions. Our objective is to improve the simulation of ET (evaporation, transpiration, interception) in Noah-MP, using soil moisture, sapflow and throughfall observations from a monitoring site in a pine forest near the 78-km2 Peristerona watershed in Cyprus. The model simulations and evaluation period cover the years 2014 - 2018. The Jarvis stomatal conductance model in Noah-MP was modified to account for nocturnal transpiration.  The use of the Jarvis model with the nocturnal transpiration resulted in a substantial increase in transpiration. The modified Noah-MP simulated ET to amount to 79% of the total precipitation, close to the observed fraction of 76%, compared to a fraction of 45% obtained with the baseline set-up of Noah-MP with the Ball-Berry stomatal conductance model. The improved Noah-MP can be combined with the WRF-Hydro model and other hydrological models to simulate the entire terrestrial hydrological cycle.This research has received financial support from the PRIMA (2018 Call) SWATCH Project, funded by the Republic of Cyprus through the Cyprus Research and Innovation Foundation. The PRIMA programme is supported by Horizon 2020, the European Union's Framework Program for Research and Innovation.
Climatology of boundary layer wind patterns from clear air radar echoes in Germany
Authors: Buschow Sebastian , Friederichs Petra
Published: February 2023

Long term observations of shallow convection in the atmospheric boundary layer are rare and difficult to obtain, making it hard to evaluate the capabilities of weather models to accurately represent such features. In this study, we demonstrate that clear air radar reflectivities from insects can be exploited to visualize the horizontal structure of convective cells and rolls over Germany. The patterns observed over a 7 year period are analyzed in terms of their spatial scale, orientation and anisotropy using a two-dimensional wavelet transform. Comparable characteristics can be computed from the near-surface windfields of the convection-permitting regional reanalysis COSMO-REA2. We show that, despite the proximity to the gray zone of turbulence, the reanalysis reproduces a surprisingly realistic diurnal cycle in the spatial patterns and may thus give hints on the wind structures during the unobserved part of the timeseries.
Biodegradation of commercial mulch films in Swiss agricultural soils: Results from combined laboratory, mesocosm and field incubations
Authors: Arn Silvan , Wille Flora , Cerri Mattia , Kägi Ralf , Bucheli Thomas , Widmer Franco , McNeill Kristopher , Sander Michael
Published: February 2023

Non-biodegradable polyethylene mulch films are widely used in agriculture to allow for an extended growing season and to increase crop yields. These mulch films are, however, difficult to completely recollect from the field after use, particularly when they are thin (< 25 µm). Residual mulch film pieces can accumulate in soils over time, thereby negatively impacting soil productivity and possibly turning agricultural soils into sources of plastics to surrounding environments. Mulch films certified as biodegradable in soils promise to be a solution to these problems. While such mulch films are already commercially available, a thorough assessment of the biodegradation dynamics of biodegradable mulch film products in soils in the field is lacking. So far, certification relies exclusively on laboratory soil incubations coupled to respirometric analysis of CO2 formed from the mulch films during biodegradation. Respirometric analyses are, however, very challenging to implement in field incubation studies. Past studies determining concentrations of biodegradable mulch films in field soils and attempts to follow their biodegradation dynamics in the field have relied on approximate quantification approaches, such as determining the decrease in surface area or gravimetric mass of film pieces recollected by hand. To advance a more robust and quantitative analytical approach for residual mulch film quantification in soils, we present a methodology to solvent extract and quantify the main synthetic polymeric components of commercial biodegradable mulch films, poly(butylene adipate-co-terephthalate) (PBAT) and polylactic acid (PLA), from soil. The methodology is based on exhaustive Soxhlet extraction using chloroform/methanol coupled to quantitative 1H-NMR of the extracted residual PBAT and PLA. We show full recovery of these polymers added to soils in spike-recovery experiments. Here, we use this approach to assess the biodegradation of two commercial biodegradable mulch films in three Swiss agricultural soils in a multiyear incubation study. These incubations are conducted at three experimental incubation scales: flasks in the laboratory, mesocosms in a greenhouse and the actual field. We statistically compare biodegradation rates and extents between three soils, two tested films across the three incubation scales, as well as differences in the relative rates of biodegradation between PBAT and PLA. Thereby, we assess the transferability of biodegradation results from laboratory incubations to field incubations. Our results highlight variations in biodegradation between soils and polyesters and indicate that laboratory soil incubations show faster biodegradation than measured in the same soil in the field.
Antarctic firn thickness variations from multi-mission satellite altimetry and firn modelling
Authors: Kappelsberger Maria T. , Horwath Martin , Buchta Eric , Willen Matthias O. , Schröder Ludwig , Veldhuijsen Sanne B.M. , Kuipers Munneke Peter , van den Broeke Michiel R.
Published: February 2023

On interannual to decadal timescales, surface mass balance (SMB) exerts an important control over variations in the overall mass balance of the Antarctic Ice Sheet (AIS). A proper characterization of this variability is required to determine statistically significant long-term trends in SMB in a robust manner. To do so, we quantify variations in SMB and firn thickness by combining results from multi-mission satellite altimetry and SMB/firn modelling at grid scale. The objective of this study is twofold: First, we characterise the errors in both the altimetry and firn model in a spatially and temporally highly-resolved way. Second, we introduce a new approach that sets the stage for inferring long-term trends in SMB and firn processes at grid scale by taking into account interannual firn thickness variations. We use observed altimetric elevation changes of the AIS from Schröder et al. (2019; doi: 10.5194/tc-13-427-2019) and Nilsson et al. (2022; doi: 10.5194/essd-14-3573-2022) and modelled elevation changes of the AIS from IMAU-FDM v1.2A over the period 05/1992 to 12/2017. We assume that the firn model is able to capture the timing of variations in SMB and firn processes, but not necessarily the amplitude of these variations. The location-dependent amplitude is adjusted to the altimetry observations. We detect highest absolute differences between modelled and observed amplitudes at lower elevations, near the AIS margins. In a relative sense, the largest mismatch in amplitude is found in the dry interior of the East AIS across wind glazed areas of e.g. megadune fields. About 37 % of the variance in altimetry is captured by the adjusted firn thickness variations while about 64 % cannot be explained and is still included in the residuals. These residuals contain both altimetry errors (time-variable penetration and scattering effects of radar signals, intermode and intermission offsets) and firn model errors, like real SMB and firn processes not captured by the model. We identify that the time series of altimetric residuals are highly correlated and conclude that we need to consider an appropriate noise model for determining long-term trends and their uncertainties.
Evolution of a submesoscale cyclone in the Balearic Sea
Authors: Poulain Pierre-Marie , Centurioni Luca , Ozgokmen Tamay , Rypina Irina , Mahadevan Amala , Middelton Leo , Johnston Shaun , D'Asaro Eric
Published: February 2023

A submesoscale cyclonic eddy, less than 10 km in diameter, was observed in the Balearic Sea from inception to dissipation for more than a month in winter 2022 The feature was heavily sampled by freely-drifting (Lagrangian) instruments to study its kinematics, spatial structure and temporal evolution.  The Lagrangian sensors included drifters, wirewalkers and profiling floats. Additional shipboard data (underway CTD, ADCP) and remote sensing images revealed that the eddy was formed by doming isopycnals, extending more than 200 m in depth, with dense salty water at the center. The near-surface chlorophyll concentration was maximum in the eddy center, as clearly seen in ocean color satellite images.The eddy formed in late February by pinching off from a larger cyclonic feature via the collapse of a sharp submesoscale ridge that connected it to a larger cyclone. Wavelet analysis of the drifter trajectories revealed that the submesoscale eddy had a maximum orbital speed of ~ 30 cm/s, at a radius of ~3 km. In its inner core, vorticity was as large as twice the local inertial frequency (Rossby number ~ 2). The surface drifters made looping tracks that were slightly elliptical. Tracked by the swarm of drifters until mid-March, the eddy remained surprisingly coherent as it moved to the South and then East with a drift speed between 2 and 5 cm/s. After a strong wind event, just a few drifters remained in the eddy until it weakened and dissipated in early April.These observations were a part of the CALYPSO program, an ONR Departmental Research Initiative that addresses the challenge of observing, understanding and predicting the three-dimensional pathways by which water from the surface ocean makes its way into the deeper ocean. Vertical transports by submesoscale fronts and eddies can play an important role in ocean and climate dynamics.
Enabling carbon farming: a robust, affordable and scalable approach leveraging remote and proximal sensing
Authors: Verweij Sven , van Doort Maarten , Fuijta Yuki , van der Voort Tessa , Ros Gerard
Published: February 2023

The main hurdle in instrumentalizing agricultural soils to sequester atmospheric carbon is a development of methods to measure soil carbon stocks on farm level which are robust, scalable and widely applicable. Specifically, it is necessary that socio-economic barriers related to cost, usability and accessibility are overcome. We present the Wageningen Soil Carbon Stock pRotocol (SoilCASTOR), a method for soil carbon stock assessment using satellite data, direct soil measurements via mobile soil sensors and machine learning which can help overcome these socio-economic hurdles. The method has a low cost per hectare and uses plug-and play tools (soil scanner), which lower the threshold users need to overcome. The method has been tested and applied for multiple farms in Europe and the United states on agricultural fields with variable crop rotations, soil types and management history. Results show that the estimates are precise, repeatable and that the approach is rapidly scalable. Carbon stocks in the top 30 cm range between 1.8-6.1 kg C/hectare and resolution is up to 10x 10 meters. The precision of farm C stocks is below 5% enabling detection of SOC changes desired for the 4 per 1000 initiative. The assessment can be done robustly with as few as 0.5 samples (or 2-3 minutes) per hectare over a range of scales, for farms varying from 20 to 200 hectares.These findings can enable the structural and widespread implementation of carbon farming. This approach has recently been awareded the Bayer Grants4Tech innovation prize.