bluuebunny/crossref_metadata_2025 huggingface dataset:
Revealing and interpreting patterns from continuous seismic data with unsupervised learning
Authors: Seydoux Léonard , Steinmann René , Mouaoued Sarah , Esfahani Reza , Campillo Michel
Published: March 2024

Exploring large datasets of continuous seismic data is a challenging task. When targeting signals of interest with a good a priori knowledge on the signal's properties, it is possible to design a dedicated processing pipeline (earthquake detection, noise reduction, etc.). Many other sources can sign up in the data, with characteristics that differ from the targetted ones (changes in noise frequency, modulating signals, etc.). In this case, it is difficult to design a processing pipeline that will be robust to all the possible sources. In this work, we propose to use unsupervised learning to explore the data and reveal patterns in an interpretable way. We extract relevant features of continuous seismic data with a deep scattering network —a deep convolutional neural network with interpretable feature maps— and experiment various classical machine learning tools (clustering, dimensionality reduction, etc.) to reveal and interpret patterns in the data. We apply this method to various cases including to a decade of continuous data in the region of Guerrero, Mexico, and interpret the results in terms of seismicity and external datasets.
Quantized eddy accumulation with error diffusion: a new direct micrometeorological technique with minimal requirements
Authors: Emad Anas
Published: March 2024

Atmospheric fluxes near the surface are key metrics for understanding the interactions between the biosphere and the atmosphere. There is an increasing demand for highly accurate flux measurements for species where fast-response analytical techniques are not available. This includes, among others, stable isotopes, oxygen, ammonia, nitrogen compounds, and bio-aerosols.Here we introduce quantized eddy accumulation with error diffusion, a new easy-to-implement, high-accuracy eddy accumulation method that is compatible with slow-response analytical techniques. Similar to relaxed eddy accumulation, this method involves sampling air at a constant flow rate and directing it into one of two containers, depending on the vertical wind velocity. The flux is then calculated based on accumulated concentration averages over the flux averaging interval. However, unlike relaxed eddy accumulation, the new method is a direct method that does not require the empirical coefficient β. These developments were made possible by developing a new representation of conditional sampling at a constant flow rate as a quantization process of vertical wind velocity. Fluxes estimated with relaxed eddy accumulation were found to be biased due to sub-optimal quantization. To account for these errors, an error diffusion algorithm was developed, which made it possible to minimize the biases inherent in the quantization process, thereby allowing for accurate and direct flux estimates.Quantized eddy accumulation with error diffusion is shown to achieve direct flux measurements with errors smaller than 0.1% of the reference eddy covariance flux. Additionally, this method enables an increase in the concentration difference in accumulated samples between updrafts and downdrafts without compromising accuracy, making it especially suitable for detecting smaller fluxes. It also provides improved accumulation volume dynamics, flexible accumulation intervals, and is less prone to errors from non-zero vertical wind velocities.These new developments are especially useful for measuring small fluxes of elusive atmospheric constituents, particularly in the presence of measurement challenges such as instrument drift or frequency attenuation. A notable application is the accurate measurement of water stable isotopes, which enables the tracing of biological processes and the accurate partitioning of measured fluxes.
On the atmospheric response to idealized freshwater input around Antarctica
Authors: Xu Xiaoqi , Martin Torge , Beadling Rebecca
Published: March 2024

The enhanced mass loss from the Antarctic ice sheet (AIS) and ice shelves has recently gained greater attention. Most climate models lack an interactive ice sheet and meltwater runoff is prescribed instead. The implications of AIS meltwater are studied most often with a focus on ocean and sea ice. We show that the changing surface conditions trigger an atmospheric response as well with consequences extending into the stratosphere. The release of meltwater into the Southern Ocean has important impacts on the ocean temperature, stratification, currents, and sea ice properties. Remote atmosphere responses tied to a shift in the ITCZ were reported as well, such as changes in (sub-)tropical precipitation.However, patterns and magnitudes of the various responses remain uncertain due to varying ways of freshwater forcing input and model uncertainty. Thus, the Southern Ocean Freshwater Input from Antarctica (SOFIA) initiative has been formed to demonstrate the robustness and quantify the uncertainty of such responses. About a dozen modeling groups participate in running the same 100-year freshwater-release experiment (0.1 Sv distributed uniformly to the ocean surface along the Antarctic coast under preindustrial forcing) with a range of state-of-the-art climate models (Swart et al., 2023, GMD, accepted).Using the SOFIA multi-model ensemble, we study the atmospheric response to the additional freshwater. First results are based on an 8-member ensemble using GEOMAR’s Flexible Ocean and Climate Infrastructure (FOCI) model. Sea level pressure and surface air temperature over Antarctica and the Southern Ocean decline and westerly winds from 40°S to 60°S strengthen. Significant atmosphere cooling, with the maximum zonal-mean anomaly of up to 0.6oC near the surface, extends to 300 hPa. This is accompanied by a weak but significant warming in the lower stratosphere, which is likely associated with a slight lowering of the tropopause or enhanced wave propagation. The zonal winds strengthen on the southern flank of the westerlies belt with a maximum at 300 hPa, the level of the jet stream core. A corresponding intensification of the Ferrell cell is found as well. The circulation changes are caused by near-surface cooling and buoyancy reduction at polar latitudes, enhancing the meridional temperature and pressure gradients. These responses have strong seasonal patterns with strongest tropospheric imprints in austral winter and a stratosphere response in late winter/spring---despite the prescribed freshwater release being constant in time without seasonal cycle. We suggest that changing sea ice conditions play a key role in creating the seasonal response.These first results have been confirmed by a parallel study using the GFDL climate model. We will expand our analysis to the SOFIA multi-model ensemble to further prove the robustness and estimate model uncertainty, which we will present in this session.
Global ice-thickness inversion using a deep-learning-aided 3D ice-flow model with data assimilation
Authors: Cook Samuel , Jouvet Guillaume , Millan Romain , Rabatel Antoine , Maussion Fabien , Zekollari Harry , Dussaillant Inès
Published: March 2024

Mountain glaciers are a major source of sea-level rise and also represent an important freshwater resource in many mountainous regions. Thus, accurate estimations of their thickness and, therefore, the total ice volume are important both in predicting and mitigating the global and local effects of climate change. However, to date, only 2% of the world’s glaciers outside the ice sheets have any thickness observations, due to the logistical difficulties of obtaining such measurements, creating a large and policy-relevant scientific gap.The recent development of a global-scale ice-velocity dataset, however, provides an ideal opportunity to fill this gap and determine ice thickness across the 98% of glaciers for which no thickness data is available. This can be done by inverting an ice-dynamics model to solve for ice thickness. For accurate thickness results, this needs to be a higher-order model, but such a model is far too computationally cumbersome to apply on a global scale, and simpler, quicker methods usually based on the shallow ice approximation (SIA) are unsuitable, particularly where sliding dominates glacier motion. The only attempt that has been made to leverage the global velocity dataset to retrieve ice thickness has, though, used the SIA, simply because higher-order approaches are not computationally realistic at this scale. Consequently, most of the widely-used global glacier models have made no systematic attempt to invert global ice thickness, owing to these limitations. Allied to this is that, once an inversion is done, subsequent forward modelling is rarely physically consistent with the physics used in the inversion, leading to model inconsistencies that affect the accuracy of simulations.As a solution to these problems, we extend our recent work on the European Alps using a deep-learning-driven inversion model, the Instructed Glacier Model (IGM), that emulates the performance of state-of-the-art higher-order models at a thousandth of the computational cost. This model, by solving a multi-variable optimisation problem, can fully use and assimilate all available input datasets (surface velocity and topography, ice thickness, etc.) as components of its cost function to invert ice thickness. This approach also gives us the possibility of using consistent ice-flow physics for inversion and forward modelling, reducing the magnitude of the shock inherent in traditional modelling approaches. We present here the first results of glacier-ice-thickness inference at a global scale obtained by the inversion of a higher-order three-dimensional ice-flow model.
New Active Antarctic Subglacial Lakes using 10 years of CryoSat-2 Altimetry
Authors: Wilson Sally , Hogg Anna , Rigby Richard , Slater Thomas , Nias Isabel
Published: March 2024

Subglacial lakes beneath the Antarctic Ice Sheet were first identified using airborne radio-echo sounding (RES) surveys from the 1960s. In Antarctica, 20% of 675 currently identified subglacial lakes are “active,” exhibiting draining and filling behaviour as water flows through them. Clusters of active subglacial lakes often form in networks, connected by subglacial hydrological pathways which enable transfer of water between lakes themselves. Signals of this hydrological activity at the ice base can be detected in height changes at the ice sheet surface. Despite efforts to observe and understand this component of ice sheet mechanics, triggers of lake drainage events, in addition to drainage mechanisms and their variability are currently unresolved. An ongoing challenge lies in accurately identifying the location and extent of subglacial lakes.We present a new dataset of locations and boundaries for over 100 newly identified subglacial lakes in Antarctica. Using 10 years of CryoSat-2 swath-processed altimetry data, from 2011-2021, we identify localised regions of ice surface uplift and subsidence associated with subglacial lake filling and draining cycles. We use a new method to manually delineate subglacial lake maximum extent boundaries for individual filling and drainage periods. These results provide insights into new areas of subglacial hydrological activity in Antarctica and their evolution over time, which are vital to resolve in order to understand their impacts on Antarctic Ice Sheet stability.
Towards a continuous, multiyear, high resolution dataset of evaporation  over Europe and Africa
Authors: Baez-Villanueva Oscar Manuel , Koppa Akash , Bonte Olivier , Miralles Diego G.
Published: March 2024

High resolution accurate evaporation (E) estimates are crucial for large-scale agricultural, ecological, and hydrological applications. However, field observations are sparse, traditional satellite-based datasets based on thermal and optical imagery are unavailable during cloudy times, and most continuous global records are too coarse in terms of spatial resolution.  One of the latter, the Global Land Evaporation Amsterdam Model (GLEAM)¹ dataset, has been widely used in climate studies in recent years, but the realm of hydrological and agricultural applications was prohibited until recently due to its coarse spatial resolution². Ongoing developments have led to the development of high-resolution (1-km) E estimates over the Mediterranean region covering the period 2015–2021. The Mediterranean region, characterised by diverse hydroclimatic conditions and seasonal rainfall, experiences challenges related to droughts, floods, and landslides, making it an ideal testbed for GLEAM datasets at a high spatial resolution (GLEAM-HR).This work summarises current activities and future plans for GLEAM-HR. Our ongoing efforts include extending coverage from the Mediterranean to embrace the entire Meteosat disk (including Europe and Africa). This expansion involves incorporating modifications in the interception module³, addressing groundwater effects⁴, and using deep learning for transpirational stress estimation⁵. These advancements enhance the utility of GLEAM-HR for addressing water-related challenges, supporting sustainable water management practices, and contributing to evidence-based decision-making. ¹Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011.²Koppa, A., Rains, D., Hulsman, P., Poyatos, R., Miralles, D. G., 2022: A deep learning-based hybrid model of global terrestrial evaporation. Nature Communications, 13 (1), 1912.³Zhong, F., Jiang, S., van Dijk, A. I. J. M., Ren, L., Schellekens, J., and Miralles, D. G.: Revisiting large-scale interception patterns constrained by a synthesis of global experimental data, Hydrol. Earth Syst. Sci., 26, 5647–5667, https://doi.org/10.5194/hess-26-5647-2022, 2022.⁴Hulsman, P., Keune, J., Koppa, A., Schellekens, J., and Miralles, D. G: Incorporating plant access to groundwater in existing global, satellite-based evaporation estimates, Water Resources Research, https://doi.org/10.1029/2022WR033731, 2023.⁵Koppa, A., Rains, D., Hulsman, P., Poyatos, R., and Miralles, D. G.: A deep learning-based hybrid model of global terrestrial evaporation, Nat. Commun., 13, 1912, https://doi.org/10.1038/s41467-022-29543-7, 2022.
Assessing the Mitigation of Uranium and Heavy Toxic Elements with Physicochemical and Hydrogeochemical properties of groundwater in the Malwa Region of Punjab, India
Authors: Chauhan Neeraj , Krause Stefan , Singh Jaswant , Toor Amrit Pal , Srivastava Alok
Published: March 2024

The escalating levels of uranium in groundwater present a critical challenge to public health and environmental sustainability in the Malwa region of Punjab, India. This study addresses the dearth of understanding regarding uranium contamination by investigating its hydrogeochemical behavior in the hot, sub-tropical steppe, semi-arid Malwa region. Our research aims to unravel the controlling factors influencing uranium mobility and distribution in groundwater. Ion chromatography was employed for the comprehensive determination of cations (Na+, K+, Li+, Ba+) and anions (F-, Cl-, Br-, NO3-, SO42-, PO4-). Inductive-coupled plasma mass spectrometry was utilized for the quantification of heavy elements including strontium (Sr), cadmium (Cd), lead (Pb), uranium (U), aluminium (Al), chromium (Cr), manganese (Mn), iron (Fe), copper (Cu), cobalt (Co), zinc (Zn), arsenic (As), and selenium (Se) concentrations in groundwater samples. Results indicate alarming uranium levels ranging from 1.13 to 299.40 µg/L with mean of 54.03 µg/L. 73% to 92% of samples surpassing Bureau of Indian Standards (BIS) and World Health Organization (WHO) guidelines. Groundwater is primarily of Mg-HCO3 type which exhibited alkaline characteristics attributed to silicate weathering, ion exchange, and carbonate weathering in semi-arid conditions. Cluster analysis grouped uranium with nitrate, sodium and potassium, emphasizing their interconnected behavior. Spearman correlation analysis revealed a close association between uranium concentrations and various parameters including electrical conductivity, total dissolved solids (TDS), alkalinity, nitrate, sulfate, Na, and K. TDS, nitrate, and alkalinity exhibited high correlations with uranium which indicates that salt-induced competition among ions is the primary cause of uranium mobilization. This is evident in increased uranium levels with mixed water species (Mg-Cl, Na-HCO3). Furthermore, concerning levels of arsenic and selenium exceeding BIS and WHO limits underscore additional health concerns. This research underscores the urgent need for understanding and managing uranium contamination in the Malwa region. The broader implications for public health and environmental sustainability necessitate immediate attention and comprehensive remediation strategies.
Sudden disappearance of winter ice from Caldera Lake Öskjuvatn, Iceland
Authors: Olafsson Jon , Olafsdottir Solveig , Jónsdóttir Ingibjörg
Published: March 2024

The caldera Lake Öskjuvatn lies in the remote Dyngjufjöll Mountains in Iceland´s interior. The lake is at 1050 m elevation, it is 11 km2 and 217 m deep. The lake developed after an eruption in 1875. From 1921 to 1926 there were volcanic eruptions in and around the lake. The lake is cold but thermal activity at has been observed at 80 m depth which generally maintains a small opening in the winter ice. There are furthermore several warm marginal springs and seeps (Ólafsson 1980). In February 2012 remote sensing data unexpectedly revealed progressively disappearing ice cover which resulted in Lake Öskjuvatn being totally ice-free by late March. This normally occurs in late June.  We investigated the ice-free lake in early April 2012 and again when the lake was ice covered in April 2013.Using SeaBird Sea Cat CTD instrument and Niskin bottles for water sampling we acquired data to compare the state of the lake under ice-free and ice-covered conditions. From April 2012 to July 2014, we had a moored string of Star-Oddi recording temperature sensors from surface to 60 m depth at a location in the deepest part of the lake. We examined the lake water chemical composition for evidence of active volcanism. The differences in the temperature structure 2012 and 2013 yield signs of circulation and the moored temperature recorders illustrate seasonal variations.  With this data combined we seek to explain why the lake became ice free in 2012 but was mostly covered with 80 cm thick ice at the same time the following year.Ólafsson, J. (1980). "Temperature structure and water chemistry of the caldera Lake Öskjuvatn, Iceland." Limnology and Oceanography 25: 779-788.
Assessment of ensemble selection methods aligning decadal climate variability in a perfect-model framework
Authors: Cos Pep , Díaz Leandro B. , Doblas-Reyes Francisco , Marcos-Matamoros Raül , Donat Markus G.
Published: March 2024

Multi-model ensembles of climate simulations often fail to correctly represent the climate evolution of the next decades due to the dominance of internal variability uncertainty in the near-term future. With the objective to solve this issue, in recent years new constraining methods have been developed. These methods aim to select members from the ensemble of climate simulations that have their variability and forced response most in phase with an observational or climate prediction reference. Through an evaluation of the performance of the different methods (Befort et al. 2020, Mahmood et al. 2021, Mahmood et al. 2022) against observations, we find that applying them directly to the CMIP6 multi-model ensemble exhibits high sensitivity to variations in the different parameters that define the methods. This complicates the interpretability of the results. We will illustrate the results of a study where we simplify the complexity of the ensemble selection methods by applying them to a single-model large ensemble. We use a perfect-model approach where, in turns, one of the members plays the role of the constraining and evaluation reference. In this study there is only one climate system involved, the one of the climate model chosen, and the differences between models and biases against observations no longer influences the results of the selection methods. Therefore, through this idealized approach, the mechanisms of the different selection methods can be better isolated and studied. Furthermore, this study offers perspectives of the potential improvements that could be expected from these methods and opens the door to finding ways of optimizing the metrics and approaches used to constrain a climate projections ensemble. 
Relationships between the tectonic evolution of an orogen and the formation of polymetallic vein deposits 
Authors: Torvela Taija , Chapman Rob , Shaw James , Manuc Georgian , Savastano Lucia
Published: March 2024

The Caledonian-Appalachian Belt (CAB) hosts several economic and sub-economic polymetallic vein systems and is, therefore, an excellent natural laboratory to study the variations in the characteristics of ore deposit and the timing of their formation, within an orogenic belt. We present some of the preliminary outcomes of a large-scale study on the variability of the vein-hosted mineralisation within the CAB, covering c. 20 different polymetallic vein systems within the Grampian Terrane and its equivalents in Scotland, Northern Ireland, Ireland and Newfoundland.The multi-disciplinary study combines structural data, age determinations, vein textural mapping and paragenetic interpretation, gold geochemical characterisation, and stable isotope data to show that although the occurrences show many superficial structural and mineralogical similarities, there are significant differences between the structural styles, mineralogy and timing of the mineralisation in different areas (see [1] and [2] for the first publications coming from this work). At least three, possibly four, distinct mineralisation stages are identified between Ordovician and Early Devonian, each associated with a characteristic structural style that can be linked to the overall tectonic evolution of the Grampian Terrane. The tectonic evolution of the orogen in time and space therefore greatly influenced both the timing and the style of mineralisation.References:[1] Shaw J, Torvela T, Cooper M, Leslie G, Chapman R (2022). A progressive model for the Cavancaw Au-Ag-Pb vein deposit, Northern Ireland, and implications to the metallogeny and evolution of the Grampian Terrane. J. Struct. Geol. 161, https://doi.org/10.1016/j.jsg.2022.104637.[2] Chapman R., Torvela T, Savastano L (2023).  Insights into regional metallogeny from detailed compositional studies of alluvial gold: An example from the Loch Tay area, central Scotland. Minerals 13, doi.org/10.3390/min13020140.
Paleoclimatic and eco-environmental changes on the southeastern Chinese Loess Plateau since the last deglaciation: evidence from terrestrial mollusk records 
Authors: Jia Yana , Yan Hong , Dong Jibao , Dong Yajie , Kang Shugang
Published: March 2024

ABSTRACT Terrestrial mollusks in loess-paleosol sequences serve as natural biological archives that document the evolution of paleoclimate and paleoenvironment. In this study, terrestrial mollusk records from two loess-paleosol profiles on the southeastern Chinese Loess Plateau (CLP) were analyzed. Our results show that the cold-aridiphilous species decreased and the mollusk communities expanded gradually during the last deglaciation (~19.0-11.5 ka BP), which was accompanied with the shift from cold-dry to warm-humid climate. In the early-middle Holocene (~11.5-6.5 ka BP), mollusk communities were dominated by the thermo-humidiphilous and warmth-loving species, characterized with stable community composition, increased species richness and evenness. Thereafter, there was a noticeable decrease in species diversity and increase in the cold-aridiphilous species in the late Holocene (~6.5-0 ka BP), associated with a gradual shift towards cold-dry climate. Notably, the count of thermo-humidiphilous and warmth-loving species increased remarkably at ~16 ka BP, which is synchronously with significant increase in the Northern Hemisphere summer insolation. Interestingly, this change of terrestrial mollusks preceded the rise in magnetic susceptibility and decrease of mean grain size for ~6.5 ka, suggesting that the East Asian summer monsoon (EASM) precipitation intensification lagged the onset of deglacial warming on the southeastern CLP. Furthermore, this delay may be attributed to the negative feedback of North Atlantic meltwater, which caused a decline in the intensity of Atlantic Meridional Overturning Circulation (AMOC) and inhibited the rapid enhancement of EASM precipitation during the initial of last deglaciation. Altogether, this provides crucial geological background evidence for exploring the regional hydrothermal responses to global climate change.Key words: Terrestrial mollusk; Loess-paleosol; Species diversity; Paleoclimate; Deglacial warming
The IPOC catalog goes deep: preliminary results
Authors: Najafipour Nooshin , Puente Huerta Jorge Antonio , Sippl Christian , Kasravi Javad , Folesky Jonas , Schurr Bernd
Published: March 2024

Northern Chile is one of the most seismogenic regions on the planet, and has been monitored by a permanent network of seismic stations since 2007. We here present a first step towards a new, more complete seismicity catalog for this region, leveraging modern deep-learning based algorithms for phase picking and association.We first assessed the performance of EQTransformer, a deep learning based phase picker, in detecting and phase picking seismic data from the Northern Chile Subduction Zone by comparison with a large, meticulously handpicked dataset. We found that the "INSTANCE" model within SeisBench yielded the best performance for our study area. Through systematic threshold variations, we determined the optimal values using Precision-Recall curves (0.4 for event detection, 0.1 for P and S picks). Subsequently, we applied GaMMA, identified as the best performing phase associator in synthetic tests, coupled with NonLinLoc for initial event location. One of GaMMA's key operational criteria is the association threshold, where we required a minimum of five seismic phases to define an event, which yielded a high reliability in the phase association process. Moreover, we refined the catalog by automatically identifying and removing duplicate events. All associated events were consecutively relocated in a 1D and a 2D velocity model, using the VELEST and simul2000 algorithms. Events with disproportionally high RMS residuals as well as single picks with high residuals were removed in the process. In a final step, events were relocated with a double-difference approach.A first application of this combined approach for the year 2020 yielded 2,838,080 P and S picks in the picking stage, with a total of 83,194 events after association and relocation. This is a nearly tenfold increase in event numbers compared to the IPOC catalog of Sippl et al. (2023), which contains 8,716 events for the same time interval.In this contribution, we present results from a larger-scale application of our procedure to several years of IPOC data, and compare retrieved geometries as well as event numbers to the previously published IPOC catalog. Our findings demonstrate the potential of modern deep-learning algorithms in the creation of larger and more complete earthquake catalogs. Moving forward, our goal is to extend this preliminary catalog to span the entire 15 years of IPOC operation, facilitating in-depth analysis of regional processes.
Dynamics and patterns of water quality and stream metabolism in a low-land Mediterranean urban stream
Authors: Godinger Tal , Adar Zafrir , Arnon Shai
Published: March 2024

Water quality in streams provides fundamental information on ecosystem functioning and status. The use of sensors instead of grab sampling provides near-continuous information on the water quality, which reveals information on hydrological and biogeochemical processes that were unrecognized before. While information from sensors on water quality in temperate climates becomes ubiquitous, it is still rare in semi-arid and Mediterranean climate. The aim of this work was to quantify the dynamics and patterns of water quality and metabolism in a Mediterranean low-land urban stream. Sensors that measure oxygen, carbon dioxide, nitrate, cDOM, chlorophyll a, turbidity, electric conductivity, pH, water level, and light were deployed in July 2019 in the Yarkon Stream, an urban lowland stream in Israel. Preliminary results indicated that seasonal differences were observed under base-flow conditions for parameters that are indicative of biological processes. For example, the average concentrations of nitrate and oxygen were higher in the winter than in the summer. Differences between summer and winter to spring and autumn were less consistent. Seasons also affected the daily fluctuations of the biological-related parameters. For example, oxygen concentrations were roughly stable during the day in the winter but followed a clear peak in the afternoon during the summer. In addition, oxygen consumption was dominant all year long, leading to hypoxic conditions in the stream for most of the year. The driving mechanisms for the observed patterns will be discussed in the presentation, and further comparisons will be made to patterns in streams from temperate climates. It is expected that this work will provide new insights into the water quality dynamics and ecosystem status of Mediterranean streams, which can potentially improve water resources management and future restoration efforts.
Constraining internal variability in CMIP6 simulations to provide skillful near-term climate predictions
Authors: Mahmood Rashed , G. Donat Markus , Ortega Pablo , Doblas-Reyes Francisco
Published: March 2024

Adaptation to climate change requires accurate and reliable climate information on decadal and multi-decadal timescales. Such near-term climate information is obtained from future projection simulations, which are strongly affected by uncertainties related to, among other things, internal climate variability. Here we present an approach to constrain variability in future projection simulations of the coupled model intercomparison project phase 6 (CMIP6). The constraining approach involves phasing in the simulated with the observed climate state by evaluating the area-weighted spatial pattern correlations of sea surface temperature (SST) anomalies in individual members and observations. The constrained ensemble, based on the top ranked members in terms of pattern correlations with observed SST anomalies, shows significant added value over the unconstrained ensemble in predicting surface temperature 10 and also 20 years  after the synchronization with observations, thus extending the forecast range of the standard initialised predictions. We also find that while the prediction skill of the constrained ensemble for the first ten years is similar to the initialized decadal predictions, the added value against the unconstrained ensemble extends over more regions than the decadal predictions. In addition, the constraining approach can also be used to attribute predictability of regional and global climate variations to regional SST variability.
Temporal impact of treated wastewater irrigation on field hydraulic conductivity
Authors: Wang Lin , Cuypere Tim De , Pollet Sabien , Garré Sarah , Corneils Wim
Published: March 2024

Hydraulic properties of agricultural soils exhibit dynamic temporal variations influenced by field management practices, such as tillage and irrigation, as well as climatic factors, particularly changes in precipitation and temperature. With the emergence of using treated wastewater (TWW) in irrigation as a solution to alleviate increased pressure on available water resources, but characterized by elevated salt and solute concentrations, understanding its potential impact on soil hydraulic properties is crucial. In this study, we aimed to discern the influences of field management practices and irrigation water sources on the temporal variability of soil hydraulic conductivity.
Mini disk infiltrometers were employed to assess near-saturated hydraulic conductivity Kh and associated soil indicators (including soil’s electrical conductivity ECe, sodium adsorption ratio SAR, water repellency WR, bulk density BD, aggregate stability AS, and air permeability Ka) in the top 20 cm of a Retisol soil in Beitem (50°91′N, 3°12′E), Belgium. A comparative analysis was conducted to evaluate the effects of irrigation using treated wastewater (from households, from vegetable industry and from potato industry) and rainwater, relative to those under rainwater irrigation conditions. All treatments significantly affected ECe and SAR. Across four replicated plots per treatment, Kh was measured at distinct matric potentials on various dates, spanning a wet (2021) and a dry (2022) year, during a crop rotation of cauliflower (Brassica oleracea L.) and spinach (Spinacia oleracea L.). The plots were tilled with a rotary harrow till 30 cm depth to prepare the seedbeds.
Our findings highlighted tillage as the predominant factor influencing Kh . Irrespective of the irrigation type, Kh increased post-tillage and subsequently decreased throughout the growing season. Yearly weather differences also played a significant role, with the dry, warm year resulting in a higher average Kh at each matric potential. Surprisingly, there were no significant differences in Khbetween irrigation treatments over two crop cycles
Despite the elevation of soil salinity (ECe) and sodicity (SAR) with TWW irrigation, it did not detrimentally impact or other soil attributes (WR, BD, AS, and Ka) in this study. Our results underscore the importance of considering the interplay of tillage, weather conditions, the timing/frequency of irrigation/rain events, and matric potential when evaluating the effects of different irrigation sources on soil hydraulic properties.
Tracking organic matter pollution and bacteria using fluorescence-based approaches in a UK Chalk stream
Authors: Gunter Hannah , Khamis Kieran , Bradley Chris , Hannah David M. , Heppell Catherine M. , Kelly Tom , Nelson Rosie , Parry-Wilson Hannah , Stevens Rob
Published: March 2024

Fluorescence spectroscopy is a rapidly evolving method for determining freshwater organic pollution. Historically, measurement was confined to the laboratory with a coarse temporal resolution. The development of field-deployable sensors has enabled in-situ, multi-peak monitoring - although challenges remain regarding fluctuating environmental conditions (e.g. pH and turbidity) that can impact on fluorometer accuracy and interpretation. This study aimed to use fluorescence spectroscopy (including in-situ sensors) to detect and differentiate sources of organic matter pollution in a predominantly groundwater fed, sewage-impacted, chalk stream.High frequency monitoring (15 min resolution for 12 months) was undertaken at two sites on the River Chess, S. England. Two multi-parameter water quality sondes were installed above and below a Wastewater Treatment Works (WWTW) effluent outflow point in a mixed land use catchment (105 km2). Additional grab sampling was conducted during baseflow and stormflow for laboratory-based nutrient, spectrofluorimetric and bacterial analysis.All sites had low turbidity (
Determination of effective sapwood areas of Common oaks (Quercus robur) and analysis of uncertainties for estimation of the water balance component evapotranspiration in lowland floodplain forests
Authors: Tiedke Alexandra , Werisch Stefan
Published: March 2024

Water balance observations in forest stands are challenging. Sap flow measurements in trees are promising for a direct measurement of transpiration in individual trees. The estimation of stand level transpiration from individual sap flow measurements requires scaling to the individual scale, mainly by estimation of the associated sap wood area, and then to the stand level. All involved steps are associated with uncertainties. Thus, this study was set up to answer four main questions:1. Which uncertainties are involved in determining the stem-circumference-sapwood-area-relationship?
2. Do single-point measurements provide reliable sap flux density data or is the radial variability of the sapwood and thus the water transport too great?
3. Is it feasible to determine water balance components from sapflow measurements in quercus robur under the conditions of uncertainties and sources of error?
4. How do sap flow estimates of evapotranspiration compare to alternative methods, such as lysimeters, soil water profile observations or passive capillary wick samplers?
The study was carried out at a long term soil monitoring site in the floodplain area of the Parthe river in the lowlands of Leipzig, Germany, with Quercus robur as the site dominant tree species.A site-specific relationship between circumference and sap flow area for Quercus robur was established based on the colour change method (methyl-orange) and drill cores from 20 trees of varying circumference. The results show that the main uncertainties of estimating sapwood area come from deviation of the sapwood area from an optimal circular ring (± 31,2%) and the variability of the sapwood depths (± 9,2%). Furthermore, analysis of sap flow velocities at various depths in the trunk, shows that there is a radial heterogeneity of the axial water transport and thus a single-point measurement can lead to both a possible over- and underestimation of the sap flow under certain circumstances. When scaling the transpiration from tree to stand level, a comparative water balance equation was set up with the aid of infiltration meters in order to investigate the significance of the estimated transpiration.The investigated low land stand of Quercus robur shows a distinct, but uncertain, relationship between circumference and sapwood area, which is unique compared to relationships of other oak species. In conclusion the results of the study show that the transpiration using sap flow und sap wood measurements cannot be obtained with high sufficient precision due to uncertainties: (1) in the relationship between circumference and sapwood area, (2) in sap flux densities within individual trees and (3) sap flow measurements themselves. As a direct result it is shown, that scaling transpiration from individual trees to the stand level needs to consider the associated uncertainties and leads to comparable results with other estimates.
Holographic Particle Tracking Velocimetry: Resolving cloud droplet dynamics
Authors: Thiede Birte , Nordsiek Freja , Schlenczek Oliver , Bodenschatz Eberhard , Bagheri Gholamhossein
Published: March 2024

We present the newly developed holographic particle tracking velocimeter (HPTV) designed for use on the Max Planck CloudKite helikites. With airborne in-line holography we can retrieve information about cloud droplets in a large three-dimensional sample volume from a single image. We can resolve individual cloud particles, their cross-section and 3D position in space.
The low true airspeed of the CloudKite Helikite, combined with a high sample volume of 0.1 l per image and a high sampling rate in our latest holographic imaging system HPTV, allows a detailed view into each cloud section.
Most importantly, the low true airspeed allowed us to develop a holographic particle tracking instrument: The HPTV can capture up to 35 image pairs per second. The time between the images of each pair is short enough that we can track the particles from image to image. This allows us to measure not only the position and cross-sectional size, but also the speed of the cloud particles with just one image system.
With this instrument, we will therefore gain more insight into the spatial and temporal properties of cloud droplets on small scales and deepen our understanding of clustering, inhomogeneities and mixing processes in clouds.
HPTV can also be used to study the shape and orientation of non-spherical objects such as ice crystals in clouds, volcanic and forest fire ash, and the dispersion of microplastics in the atmosphere.
DSM products at continental scale: how to assess these? 
Authors: Poggio Laura , Rossiter David , Genova Giulio , Kempen Bas , Calisto Luis , Batjes Niels
Published: March 2024

Many Digital Soil Modelling (DSM) products have been generated for diverse regions, countries and continents.  While most of these products provide some accuracy metrics, a few also incorporate assessments of uncertainty. The current uncertainty estimates for DSM products often fail to represent  elements that are essential for evaluating the suitability of a map for a specific application.  For instance, different models can have very similar accuracy metrics but produce different soil-landscape patterns. It is important to be able to evaluate the accuracy of the patterns as well, current accuracy metrics do not do this. Additional metrics could be defined that are able to do this such the ‘area of applicability’, i.e. the area in covariate space where the model learns about relationships based on the training data) and the landscape heterogeneity both in the landscape itself and in covariate space.  
This study delves into the integration of the aforementioned elements into an assessment of DSM uncertainty at the continental scale. Europe was used as test area, incorporating input observations from EU-LUCAS datasets. A covariate space encompassing the soil forming factors as defined by the SCORPAN model served as a basis for fitting the necessary models for soil products.. We characterized the spatial heterogeneity of both the landscape and the covariate space by employing commonly employed landscape metrics. The findings offer practical insights on how to integrate these components to produce  more reliable products for stakeholders. 
Suitability Mapping for Subsurface Floodwater Storage Schemes
Authors: Augustin Lea , Baumann Thomas
Published: March 2024

Co-management strategies for floods and droughts offer a promising solution for dealing with two extremes that are increasingly close in time and space. Techniques originally developed for drought prevention, such as managed groundwater recharge (MAR), could use floods as a source of water (Flood-MAR) to simultaneously protect against flooding.The project Smart-SWS aims to develop this concept further by capturing the flood waves in a river and infiltrating them into aquifers nearby. Subsurface storage is created through geotechnical measures in the aquifer. This storage could secure the seasonal water supply while protecting downstream settlements from flooding.The main attributes of Smart-SWS sites mirror the overall objective: On the one hand, potential sites for such a system are located in areas that are regularly flooded and, at the same time, have problems with groundwater scarcity. In order to infiltrate large volumes of water into the aquifer and store this water for extended periods, the characteristics of the aquifer, the surface, and the water source must be taken into account to assess the suitability of these sites.In this work, we have identified suitable sites for such an underground flood storage system by applying a GIS-based multi-criteria decision analysis (MCDA). The workflow for the suitability mapping is based on publicly available data and implemented in Python. The results are shown for the administrative district of Swabia in Bavaria, Germany, where approximately 35% of the study area was identified as having varying degrees of suitability. The robustness of the MCDA is validated with a sensitivity analysis, and the results are checked against expert opinions based on field data.
Assessment of a global hydrological service by application-based metrics
Authors: Olsson Jonas , Du Yiheng , Isberg Kristina , Strömqvist Johan , Hundecha Yeshewatesfa
Published: March 2024

The calibration and validation of hydrological models often involve a suite of established statistical metrics, which may not always match the needs of local stakeholders, thereby constraining the evaluative scope, particularly in the context of global climate services. This study introduces an alternative, complementary evaluation approach by formulating two types of application-based evaluation metrics (Du et al., 2024), representing model performance in terms of (i) temporal matching of the extreme quantiles and (ii) reproduction of the maximized split-sample difference in flow signatures. The introduced metrics are compared to conventional statistical metrics, at seven case study areas across the world, with three model settings representing different datasets and calibrations, generated from the global hydrological model World-Wide HYPE (WWH; Arheimer et al., 2020). The different performances found using application-based and conventional metrics, respectively, reveal their ability to uncover the models' capability in various aspects. Ultimately, the comprehensive analysis of conventional and application-based metrics allows us to delineate two scenarios for model application: generally applicable models, and conditionally applicable models. For example, in some areas the WWH model, when applied with global dataset and local calibration, is well capable of producing predictions for the timing of extreme quantiles and the relative difference in flow signatures, even though it may not excel according to conventional evaluation metrics. Consequently, this model can be classified as conditionally applicable, suitable for areas where local data is scarce, yet providing reliable information that can aid decision-makers in developing strategies for water resources management.Arheimer, B., Pimentel, R., Isberg, K., Crochemore, L., Andersson, J.C.M., Hasan, A.,  Pineda, L. (2020). Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation. Hydrology and Earth System Sciences, 24, 535-559.Du, Y., Olsson, J., Isberg, K., Strömqvist, J., Hundecha., Y., Silva, B.C., Rafee, S.A.A., Fragoso Jr., C.R., Beldring, S., Hansen, A., Uvo, C.B., Sörensen, J. (2024). Application-based evaluation of multi-basin hydrological models. Journal of Hydrology, under revision.
Metallic Nanoparticles: Differential  impact on Fungal vs Bacterial Soil Communities 
Authors: Kavroulakis Nektarios , Tsiknia Myrto , Kissandraki Maria , Chrysikopoulos Constantinos , Malandrakis Anastasios
Published: March 2024

This study investigated the impact of metallic nanoparticles (NPs) containing copper, silver, copper oxide, and zinc oxide, recognized as potential pollutants, on the structural and compositional aspects of soil microbial communities in comparison to their bulk counterparts. The influence of these nanoparticles was examined at two distinct accumulation levels within the soil ecosystem.The potential effects of metallic nanoparticles in comparison to their bulk counterparts were evaluated in a pot experiment under controlled environmental conditions. High-throughput sequencing of PCR-amplified 16S rRNA and ITS2 marker genes was employed to analyze the impact of NPs and counterparts on bacterial and fungal rhizospheric communities using two dosage levels.Bioinformatic analysis of the obtained sequencing results revealed a distinct metal-dependent differentiation in bacterial and fungal soil community structures. Silver-containing treatments exhibited an enhanced ability to induce changes in both bacterial and fungal communities compared to other metals. Furthermore, treatment dose had a profound differentiation effect on the two microbial communities. The low dose notably influenced bacterial communities to a greater extent compared to the high dose, whereas fungal communities exhibited significant alterations under high-dose conditions rather than under low-dose conditions.This study was co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Rural Development Program (RDP/ΠΑΑ) 2014 – 2020, under the call "Cooperation for environmental projects, environmental practices and actions for climate change” (project code: Μ16SΥΝ2-00354) and by the European Union- Next Generation EU, Greece 2.0 National Recovery and Resilience plan (project code: TAEDR-0535675)