bluuebunny/crossref_metadata_2025 huggingface dataset:
3D characterisation of the Yorkshire Wolds chalk aquifer, UK
Authors: Burrel Laura , Vernon Rowan , Ford Jon , Haslam Richard , Randles Tom , Burke Helen , Woods Mark , Lee Jonathan , Whitbread Katie
Published: February 2023

The Yorkshire Wolds Chalk aquifer, provides the main source of water supply in East Yorkshire and the city of Hull, which have a population over 900.000. Its structural configuration, including the effects of faulting, influence groundwater flow across the region. However, stratigraphic and structural characterisation is challenging due to limited bedrock being exposed at surface, with most of its extension covered by Quaternary glacial deposits and arable fields and pastures. While the coastal sections have been well characterised through the years, inland areas of the Yorkshire Wolds Chalk aquifer have not been systematically mapped since the late 19th century. The available maps do not reflect present-day stratigraphic divisions or current tectonic understanding, leading to an underestimation of the structural complexity of the aquifer.A multi-faceted approach to geological mapping is being undertaken in the region by the British Geological Survey, in collaboration with the Environment Agency and Yorkshire Water, integrating remote sensing, targeted field mapping, palaeontological analysis, 2D onshore seismic interpretation and borehole records. The objective of the project is to deliver an up-to-date geological map and structural model of the Chalk bedrock and Quaternary deposits which will impact on the groundwater resources management.The recent mapping campaigns have led to identifying and characterising numerous new faults in different structural trends, which were not present on previous maps. It has also led to a significant shifting of stratigraphic contacts and formation thicknesses, which have more lateral variability than previously thought. We present some of the most recent updates on the Yorkshire Wolds Chalk aquifer map, which highlight the importance of revising old cartography using modern tectonic and stratigraphic concepts and a multidisciplinary approach to field data collection and compilation. We are also interested in discussing with the hydrogeologist community how to better capture and represent structural complexity around fault zones, so it has an impact on hydrogeological modelling.
Revisiting the 2015 Mw=8.3 Illapel earthquake: Unveiling complex fault slip properties using Bayesian inversion.
Authors: Duputel Zacharie , Caballero Emmanuel , Twardzik Cédric , Rivera Luis , Klein Emilie , Jiang Junle , Liang Cunren , Zhu Lijun , Jolivet Romain , Fielding Eric , Simons Mark
Published: February 2023

The 2015 Mw=8.3 Illapel earthquake is one of the largest megathrust earthquakes that has been recorded along the Chilean subduction zone. Given its magnitude, different rupture scenarios have been obtained. Previous studies show different amounts of shallow slip with some results showing almost no slip at the trench and others showing significant slip at shallow depths, up to 14 meters. In this work, we revisit this event by assembling a comprehensive data set including continuous and survey GNSS measurements corrected for post-seismic and aftershock signals, ascending and descending InSAR images of the Sentinel-1A satellite, tsunami data along with high-rate GPS, and doubly integrated strong-motion waveforms. We follow a Bayesian approach using the AlTar algorithm, in which we aim to obtain the posterior PDF of the joint inversion problem. In addition, we explore a new approach to account for forward problem uncertainties using a second-order perturbation approach. Results show a rupture with two main slip regions, and with significant slip at shallow depth that correlates with outer-rise aftershocks. Furthermore, kinematic models indicate that the rupture is encircling two regions updip of the hypocenter that remain unbroken during the mainshock and its aftershocks. These encircling patterns have been previously suggested by back-projection results but have not been observed in finite-fault slip models. We propose that the encircled regions correspond to barriers that can potentially be related to secondary fracture zones in the Chilean subduction zone.
Strain sensitivity of seismic velocity variation induced by hydrological forcing of karst aquifers in the Apennines, Italy
Authors: Tarantino Stefania , Poli Piero , D'Agostino Nicola , Festa Gaetano , Vassallo Maurizio , Ventraffrida Gerardo , Zollo Aldo
Published: February 2023

Non-linear response of the elastic properties of the crust has been studied using the analysis of seismic velocity variations induced by various natural forcing agents (earthquakes, tides, volcanic processes, and others). Here we study 1) the variations of seismic velocities in response non-tectonic deformations associated to phases of groundwater recharge/discharge in large karstic aquifers in the Southern Apennines of Italy and discuss 2) the implications in terms of non-elastic behavior of the crust. Karst systems are complex aquifers common within the carbonate rocks of the Apennines. They store large amount of groundwater producing significant horizontal dilatational strains that modulate the secular, tectonic deformation (~3 mm/yr extension across the Apennines) and background seismicity (Silverii et al., 2019; D’Agostino et al., 2018) with seasonal and multi-seasonal signatures. The availability of accurate and temporally-long hydrological measurements (rainfall and karst spring discharge) in addition to dense seismic and geodetic networks provide the opportunity to assess the elastic response of the crust to strain forcing at various periods and the sensitivity of relative velocity variations to non-tectonic, hydrological strain variations. We performed velocity variation measurements on seismic noise autocorrelation signals recorded at seismic stations for different coda waves time lapse and compared them with strain measured by the GPS network. We observe that seismic velocities decrease during dilatation episodes (high hydraulic head) and increase during contraction (low hydraulic head). We find that the retrieved strain sensitivity of seismic velocity changes is of the order of ~103 and discuss such sensitivity with previous natural and laboratory results.
Boreal Summer Intraseasonal Oscillation extreme rainfall propagation modulated by Pacific sea surface temperatures
Authors: Strnad Felix , Schlör Jakob , Geen Ruth , Boers Niklas , Goswami Bedartha
Published: February 2023

Intraseasonal variability of extreme rainfall events (EREs) during the South Asian Summer Monsoon season is dominated by the Boreal Summer Intraseasonal Oscillation (BSISO). However, deviations from its canonical north-eastward propagation are poorly understood, posing challenges to the prediction of EREs and climate modeling. Here, we combine a climate network-based approach determining regions of synchronously occurring EREs witha clustering analysis of zonal and meridional BSISO propagation patterns which reveals three distinct modes: canonical north-eastward, eastward-blocked, and stationary propagation. We show that Pacific sea surface temperature background states determine the propagation mode. In particular, El Niño (La Niña)-like conditions favor the stationary (eastward-blocked) mode by modifying the zonal and meridional overturning circulation structures and the strength of the BSISO Kelvin wave component. The uncovered mechanism for BSISO diversity has implications for the predictability of large, spatially extensive EREs in South Asia and the development of early warning signals on a time horizon of 3-5 weeks.
Three-dimensional geological modelling of the western sector of the Po Plain (Italy) for seismic site response evaluation
Authors: Luzi Lucia , Grignaschi Alessia , Mascandola Claudia
Published: February 2023

It is widely recognized that a significant part of the variability of earthquake ground motion is related to local geological conditions, which can strongly modify the ground-motion amplitude, duration and frequency. This is commonly referred to as seismic response of a site. In the case of sedimentary basins, the characteristics of the soil deposits and the buried geometry of the basin can strongly influence the nature of the surface shaking, which may be amplified or reduced. Therefore, the knowledge of the 3D structure of the subsoil is crucial for seismic hazard studies and seismic risk management. 
To this end, 3D geological modeling allows the combination of multidisciplinary data in the shaping and visualization of the current knowledge of the subsoil and allows integration with new data or interpretations, as they become available (Calcagno, 2015). Moreover, 3D geological models represent the basis for physics-based numerical simulations, provided that a reliable scientific procedure is defined to convert the different types and levels of the available complex geological information (Klin et a., 2019).
The aim of this study is to create a 3D seismo-stratigraphic model of the central-western portion of the Po Plain, one of the deepest and widest sedimentary basins worldwide that can reach about 8 km in the Apennine foredeep (Pieri and Groppi, 1981). Although its topography is mostly flat, the buried geometry is quite complex, with north-verging thrust systems of the Apennines and south-verging thrust systems of the Alps. The 3D geological model was implemented through the integration of geological cross sections (Pieri and Groppi 1981, Casero 2004, Fantoni and Franciosi 2010, Maesano et al., 2015), deep drill holes (VIDEPI project) and geophysical surveys (sonic logs, microtremor single-station and array measurements; MASW and downhole surveys). We relied on the commercial GeoModeller software by Intrepid Geophysics for merging and interpolating the geological and geophysical data to create a 3D digital model, that is initially used to simulate 1D wave propagation and represents the basis for further improvements and 2D / 3D modelling.
Detection of chlorine, bromine and bromine chloride (BrCl) in volcanic emissions: Studies at Mt. Etna (Italy), 2022
Authors: Geil Bastien , Karbach Niklas , Bobrowski Nicole , Hoffmann Thorsten
Published: February 2023

Halogens in volcanic plumes are important for both volcanic and environmental research. For example, changes in the composition of the volcanic plume can be an indication of changes in the activity of the volcano. Volcanic emissions consist mainly of emitted H2O, CO2 and SO2 and are rapidly mixed with surrounding background atmosphere. Additionally, HF, HCl and HBr are also significant constituents of volcanic emissions.A particularly interesting element in this context is bromine because of its atmospheric relevance. Among others BrO forms in the volcanic plume and, like SO2, can be determined spectroscopically using remote sensing techniques, making it ideal for monitoring and surveillance of volcanoes. However, to interpret and use BrO concentrations, we need to fully understand the formation and evolution of BrO in volcanic plumes. Measuring all relevant halogen species can take us one step further in our understanding of the interaction between atmosphere and volcanic gas and particle emissions.Currently, several methods are used to detect the various halogen compounds. Remote sensing methods exist for only a few (in general BrO, OClO, HCl, HF). We use in-situ sampling methods such as diffusion separators, filter packs or aqueous alkaline traps to collect reactive and total halogen species, respectively.In this study, we will present results for Cl2, Br2 and BrCl in volcanic plumes using AV based in situ measurement with cis-Stilbene coated syringe filters for halogens and interhalogens (i.e., Cl2 ,Br2 and BrCl). The results are discussed considering the different degassing activities and halogen chemistry in volcanic plumes.
Improving Streamflow Prediction Using a Model Integration Approach
Authors: Kadu Akshay , Biswal Basudev
Published: February 2023

Accurate streamflow prediction is necessary both during wet and dry periods for efficient management of water resources. However, most hydrological models mainly focus on simulating high flows and perform poorly during low-flow or recession periods. Therefore, past studies have resorted to various calibration techniques to allow rainfall-runoff (R-R) models better capture recession flow dynamics. In the present study, we propose integrating two structurally different models and utilising their relative strengths to improve overall streamflow prediction. The proposed framework integrates a conceptual rainfall-runoff model (HBV) and a simple power-law regression (PLR) such that the former is utilised for high-flow prediction and the latter for low-flow prediction. We compared the performance of this integrated model framework (HBV-PLR) with the original HBV model using data from 108 basins in the United States. It was found that the 25th, 50th, and 75th percentiles of mean absolute error (MAE) for HBV, respectively, improved from (0.47, 0.62, and 0.77) to (0.38, 0.50, and 0.67) using the HBV-PLR integrated framework. Similarly, the median Nash-Sutcliffe Efficiency (NSE) during the recession improved from 0.65 to 0.74. Here, we also argue that forcing HBV model to simulate low-flow dynamics by calibrating it using an objective function biased towards lower values may not lead to a prediction as accurate as HBV-PLR. Therefore, a model integration approach is a better option than using a single model to improve streamflow prediction during different flow regimes.
SciKit-GStat Uncertainty: A software extension to cope with uncertain geostatistical estimates
Authors: Mälicke Mirko , Guadagnini Alberto , Zehe Erwin
Published: February 2023

We provide an extension of a well established geostatistical software to allow for effective and interactive assessment of environmental scenarios in a geostatistical context. The extension comprises a pre-built interface and a freely accessible demo application.The heat of the approach relies on replacing a sample variogram with its uncertainty bound. Doing so enables one to fully and consistently embed various sources of uncertainties stemming from available datasets and methodological approaches employed for their interpretation. Methodological approaches included in the software include capabilities leading to: i) a statistical estimation of uncertainty bounds from residual point-pair distributions; ii) a statistical robustness test for uncertainty bounds; and iii) a Monte Carlo simulation tool to propagate a variety of aleatory uncertainties. We illustrate the capabilities of our approach and software through the analysis of two different datasets. We focus on manual variogram estimation to comprehensively illustrate how insights on uncertainty can be used to reject candidate variogram models or model parameter sets.
Overestimated water-use efficiency responses to rising CO2 revealed by tree-ring 13C record
Authors: Gong Xiao Ying , Ma Wei Ting , Yu Yong Zhi , Wang Xuming
Published: February 2023

Water-use efficiency (WUE) is a key determinant of carbon and water fluxes at scales ranging from individual plants to continents and thus a key driver of hydro-climatic changes and carbon models. Multiple lines of evidence suggest that WUE of plants increases with atmospheric CO2, pointing to potential changes in physiological forcing of global carbon and hydrological cycles. Although the increase in forest WUE with atmospheric CO2 is widespread, declines in tree growth have been observed in different forests. These controversial results highlight the need to re-evaluate the historical trend of forest WUE.13C signatures (i.e., δ13C) of plant organic matter is a useful tool for estimating WUE at temporal scales ranging from days to centuries. This estimation relies on photosynthetic 13C discrimination models that have different assumptions about the components of isotope discrimination. Mesophyll conductance is a key uncertainty in estimated WUE owing to its influence on diffusion of CO2 to sites of carboxylation.We developed a 13C-based WUE model that takes into account the effect of mesophyll conductance and tested its performance with experimental data. We applied this model to 464 δ13C chronologies in tree-rings of 143 species spanning global biomes. Adjusted for mesophyll conductance, mean sensitivity of WUE to atmospheric CO2 (0.15 ppm ppm-1) was considerably smaller than those estimated from conventional modelling (0.23-0.30 ppm ppm-1). Our results showed a 10-ppm gain in WUE during the 20th century. Ratios of internal-to-atmospheric CO2 (ci/ca) in leaves maintained constant over time but differed among biomes and plant taxa. Our results also suggest that ratios of chloroplastic-to-atmospheric CO2 (cc/ca) are constrained over time, but this result is associated with the sensitivity of gs /gm ratio to CO2 which need further evaluation.Over the last century, a general increase in forest WUE across the globe has been confirmed. However, our study shows that forest WUE may have not increased as much as previously suggested and that projections of CO2 fertilization may need to be adjusted accordingly.
Improving sub-seasonal drought forecasting via machine learning to leverage climate data at different spatial scales
Authors: Bosso Francesco , Bertini Claudia , Giuliani Matteo , Solomatine Dimitri , van Andel Schalk Jan
Published: February 2023

Droughts are one of the most dangerous natural hazards that are affecting societies, with an economic impact amounting to over 9 billion euros per year in Europe. Drought events usually originate from a precipitation deficit, which can then cause water shortages, agricultural losses, and environmental degradation. Despite the numerous efforts and recent advances in predicting weather and extreme weather events, accurately forecasting rainfall remains a challenge, especially at sub-seasonal lead-times. In this case, the reference period is short enough for the atmosphere to retain a memory of its initial conditions, but also long enough for oceanic variability to affect atmospheric circulation. However, the relative contribution of climate teleconnections and local atmospheric conditions to the genesis of total precipitation at sub-seasonal scale remains unclear. In this work, we aim to address this gap by advancing the Climate State Intelligence (CSI) framework to examine the impact of both teleconnection patterns and local atmospheric conditions on monthly total precipitation. We then use the information gained to forecast total precipitation with a one-month lead time, and we test three different Machine Learning (ML) models: (i) Extreme Learning Machine (ELM); (ii) Fully Connected Neural Network; (iii) Convolutional Neural Network (CNN). We finally assess the skill of our ML-based precipitation forecasts in predicting the Standardized Precipitation Index (SPI), using the ECMWF Extended Range forecasts as a benchmark. Our framework is developed within the CLImate INTelligence (CLINT) project and applied in the Rhine Delta area, in the Netherlands. Initial findings indicate that combining global and local climate contexts into ML-based models significantly improves state-of-the-art drought forecast accuracy, thus representing a promising option to timely prompt anticipatory drought management measures.
Investigation and preliminary assessment of the Casamicciola landslide in the island of Ischia (Italy) on November 26, 2022
Authors: Romeo Saverio , Bonasera Mauro , Chiessi Vittorio , D'Angiò Danilo , Fraccica Alessandro , Olivetta Luca , Perrotti Michele , Roma Mauro , Trigila Alessandro , Vitale Valerio , Amanti Marco
Published: February 2023

Active volcanic environments, due to their rapid processes of growth and deformation, can be considered a typical setting for the formation of both subaerial and subaqueous gravitational instabilities. Occasionally, such conditions - coupled with heavy rainfalls or earthquakes - can trigger sudden and rapid mass movements such as mud-debris flows and/or debris avalanches, representing serious hazards for human settlements.The active volcanic island of Ischia is localized within the Gulf of Naples and its complex volcanism began prior to 350ka and continued, with centuries to millennia of quiescence, until the last eruption occurred in the historical period (AD 1302). 56ka a caldera-forming eruption occurred, followed by a resurgence process that has affected the caldera floor and generated a net uplift of about 900m since 33ka. Thus, the main morphostructural feature is the Mt. Epomeo resurgent block.From a geological point of view, the island is composed of volcanic rocks, epiclastic deposits, and terrigenous sediments, demonstrating an alternation of constructive and destructive phases. In this context, the continuous occurrence of landslides on the island, even causing death to humans, is historically documented. In the last decades, the risk has been greatly exacerbated by the high level of human exposure due to not properly planned urban development.On November 26, 2022, as a consequence of heavy rainfall, diffuse landslide events occurred along the island, the main of which affected a small catchment basin in the vicinity of an urban settlement within the Casamicciola Municipality. The area affected by the landslide events is located along the northern slope of Mt. Epomeo. On the summit, Mt. Epomeo is characterized by the strongly weathered Green Tuff Formation. The generated debris flow affected about 30 buildings causing 12 casualties, 5 injured, 230 people displaced, and severe damages to roads and properties. It should be pointed out that the maximum occurred rainfall - recorded by the local weather station - for durations from 1 to 24 hours are all higher than the corresponding maximum values recorded in the years 2007÷2021.The present work shows the first outcomes, in terms of landslide types, volumes, extent, etc., from a preliminary multidisciplinary investigation carried out immediately following the event by using desk research, on-field survey, geomorphological mapping, remote sensing, and numerical modeling.
Transferability of data-driven models to predict urban pluvial floodwater depth in Berlin, Germany.
Authors: Seleem Omar , Ayzel Georgy , Bronstert Axel , Heistermann Maik
Published: February 2023

Hydrodynamic models are considered the best representation of the physical process of runoff generation and concentration. However, they are computationally expensive. Data-driven models are raising as a potential alternative to surrogate them but the models’ transferability in space is still a major challenge. This study compared the performance of random forest (RF) and convolutional neural networks (CNN) based on the U-Net architecture for predicting urban pluvial floodwater depth, the models’ transferability in space and whether using transfer learning techniques could improve the models’ performance outside the training domains. The results showed that RF models were better for predictions among the training domains, though this may be due to overfitting. The CNN models had a better potential to generalize beyond the training domains and were able to benefit from transfer learning techniques to improve their performance outside the training domains than RF models.
Satellite-based continental-scale inventory of European wetland types at 10m spatial resolution
Authors: Kovács Gyula Mate , Oehmcke Stefan , Horion Stéphanie , Gominski Dimitri , Tong Xiaoye , Fensholt Rasmus
Published: February 2023

Wetlands provide invaluable services for ecosystems and society and are a crucial instrument in our fight against climate change. Although Earth Observation satellites offer cost-effective and accurate information about wetland status at the continental scale; to date, there is no universally accepted, standardized, and regularly updated inventory of European wetlands <100m resolution. Moreover, previous satellite-based global land cover products seldom account for wetland diversity, which often impairs their mapping performances. Here, we mapped major wetland types (i.e., peatland, marshland, and coastal wetlands) across Europe for 2018, based on high resolution (10m) optical and radar time series satellite data as well as field-collected land cover information (LUCAS) using an ensemble model combining traditional machine learning and deep learning approaches. Our results show with high accuracy (>85%) that a substantial extent of European peatlands was previously classified as grassland and other land cover types. In addition, our map highlights cultivated areas (e.g., river floodplains) that can be potentially rewetted. Such accurate and consistent mapping of different wetland types at a continental scale offers a baseline for future wetland monitoring and trend assessment, supports the detailed reporting of European carbon budgets, and lays down the foundation towards a global wetland inventory.
Reconstructing Holocene body size changes of Adriatic gobies using radiocarbon dating and sclerochronological analyses of modern and fossil otoliths
Authors: Leonhard Isabella , Agiadi Konstantina , Nawrot Rafal , Jarochowska Emilia , Zuschin Martin
Published: February 2023

Climate warming is expected to lead to a reduction in the body size of marine organisms, a trend already observed in commercial fishes, but the effects of temperature rise on size distribution in exploited populations are difficult to separate from the impact of overfishing and other anthropogenic stressors. We aim to test the hypothesis that fish body sizes, as well as growth rates changed during the late Holocene and Anthropocene in the northern Adriatic Sea due to environmental perturbations caused by climate warming. We perform sclerochronological analysis on modern otoliths from fish sampled alive, as well as radiocarbon-dated fossil otoliths of non-commercial, demersal gobies (Gobius niger Linnaeus, 1758) sampled from a sediment core taken off Piran (Slovenia) to quantify changes in body size and growth parameters throughout the Holocene. Otoliths are the aragonitic structures of the fish’ inner ear with species-specific morphology, and thanks to their incremental growth, they serve as unique environmental and life-history archive. Moreover, otolith size correlates with fish size. We use otoliths cut in half to perform both sclerochronology and radiocarbon dating, obtaining a high-resolution time series of changes in fish body size, growth dynamics and life history parameters. We employ backscatter electron (BSE) imaging and electron probe microanalysis (EPMA) to identify body sizes and growth dynamics, as well as to correlate their growth increments with climatic and other environmental parameters. The reconstructed changes in body size and growth rates of very common, non-commercial fish species over the last 7.000 years, can serve as an ecological baseline for evaluating the magnitude of ongoing temperature rise and future shifts in fish populations in response to global warming.
Investigating ventilation and saturation dynamics in the Arctic Ocean using noble gas tracer techniques
Authors: Arck Yannis , Gerke Lennart , Engelhardt Edith , Freundt Florian , Robertz Julian , Scott Stanley , Wachs David , Oberthaler Markus , Tanhua Toste , Aeschbach Werner
Published: February 2023

Timescales of ventilation of the Arctic Ocean are still only poorly known. The commonly used tracers for ocean ventilation studies like CFCs and SF6 are limited to young water masses that are either close to the surface or in highly ventilated deep waters. The radioisotope 39Ar with its half-life of 269 years covers time scales of 50 to 1000 years, perfectly suitable to investigate ventilation timescales of deep and intermediate water masses within the Arctic Ocean. The new measurement technique called Argon Trap Trace Analysis (ArTTA) only requires samples sizes of a few liters of ocean water, instead of the previous low-level counting method, which required about 1000 liters of water. The benefit for ocean studies is evident, much more samples can be taken during one cruise if ArTTA is applied. This enables a better resolution of the water column in great depths at the desired sampling location in the Arctic Ocean. Combined with the additional data of the CFC-12 and SF6 measurements, ventilation timescales of the complete water column from surface to bottom are obtained by constraining transit time distributions via this multi-tracer approach.Another focus of this study is the saturation of all gaseous transient tracers. It is determined by surface conditions as well as interior mixing processes. Measurements of stable noble gas isotopes (He, Ne, Ar, Kr, Xe) are used to determine possible saturation anomalies that arise during air bubble dissolution, rapid cooling and subduction, or ice formation and subsequent interior mixing of water masses. These saturation distortions for different boundary conditions are of key importance to correct the input function for gas tracers in the Arctic Ocean and hence to constrain the ventilation timescales. The uncertainty of the age distributions will be reduced, and ocean circulation models can be improved.This contribution presents first stable and radioactive noble gas results of the project Ventilation and Anthropogenic Carbon in the Arctic Ocean (VACAO), which is part of the Synoptic Arctic Survey carried out in summer 2021 on the Swedish icebreaker Oden.
The impact of copper and iron distribution on reactive oxygen species concentrations in the atmospheric multiphase system
Authors: Aregahegn Kifle , Ervens Barbara
Published: February 2023

Redox reactions transition metal ions (TMI), such as iron and copper, affect the concentrations of reactive oxygen species (ROS) in atmospheric cloud droplets and aqueous aerosol particles. Copper and iron have distinct emission sources resulting in only a small number fraction of cloud condensation nuclei and droplets that contain these metals. The fact that TMI reactions only occur in a small subset of particles and droplets is not taken into account in current multiphase chemistry models that are usually initialized with TMI concentrations derived from bulk sampling.Our previous model studies have shown that model predictions based on bulk iron concentrations may significantly underestimate total OH and HO2 budgets if iron is assumed in all cloud (Ervens, 2022; Khaled et al., 2022). We extend this approach to copper reactions and to reactions between copper and iron ions. We use a multiphase chemistry box model to investigate the importance of the number fraction of TMI-containing particles and droplets and show under which atmospheric conditions detailed information on this parameter is most important. The aim of our study is to identify the impacts of the copper and iron distributions in cloud droplets and aqueous aerosol particles on the total gas and aqueous budgets of OH, HO2, H2O2 and O3 in the multiphase system. Our model results give guidance for measurement needs to further constrain the ROS budgets in the atmosphere.
Modelling the combination of aquifer thermal energy storage with remediation of contaminated groundwater
Authors: Dörnbrack Maximilian , Chen Dr. Chaofan , Shao Dr. Haibing , Weiß Prof. Dr. Holger
Published: February 2023

In the scientific park of Leipzig an Aquifer Thermal Energy Storage (ATES) system is planned in combination with the remediation of groundwater contaminated with chlorinated volatile organic compounds.During the operation of the ATES system a two-well system is used. The cold groundwater is extracted from one well, and reinjected after heating up through the other well into the aquifer as storage. Later this pumping mode will be reversed and the heated-up groundwater will be extracted as a heating source.In the most of ATES system, hot water is injected into aquifers at temperature lower than 25°C, while the planned system will inject at temperature of up to 80°C. This leads to a more significant influence on the chemical composition of the groundwater than with lower temperature ATES systems. Additionally laboratory tests from a previous project also show a drastic change in the microbiological biome at 45 and 60°C.To facilitate the understanding of such impacts, a simplified 2D numerical model has been constructed, simulating both hydraulic and heat transport process in the aquifer. The model is currently being used as a planning tool to predict the propagation of the thermal plume, as well as designing the pumping rate of the circulation system. The model results already show a larger thermal-affected zone due to the high-temperature injection compared to low temperature ATES system.Future application of the model is to investigate the impact of thermal signal on the mobilization of the contaminants, and also its contribution to the natural attenuation through change in the microbiological biome and activity, which determines the degradation rate in most cases. The overall goal of the project is to develop a fully coupled THC model that will be used to simulate the thermal, hydraulic and chemical processes associated with the thermal usage of a contaminated aquifer in urban areas.
First radon dataset from the seismic area of north-eastern Sicily, Italy
Authors: Romano Davide , Magazù Salvatore , Sabatino Giuseppe , Di Bella Marcella , Italiano Francesco
Published: February 2023

North-eastern Sicily can be considered a radon-prone area due to the presence of a Variscan crystalline basement, that includes high-radionuclides content rocks such as low to high-grade metamorphites and felsic plutonic rocks. The area is also characterized by intense seismic activity: the Mw 7.1 seismic event that struck this area on 28th December 1908 is still the deadliest earthquake recorded in Europe, having caused more than 120,000 casualties. Despite the proven link between high radon concentrations and some geogenic and tectonic settings (e.g. seismogenic areas and volcanic and crystalline rock environments), no radiological data had been collected for north-eastern Sicily. In order to fill this gap, a series of radiological surveys were performed in a sector of this vulnerable area with the aim of determining the radon concentration in soil gases and groundwaters.Radon dissolved in groundwater was derived in the range of 1.6–57.5 Bq L-1, well below the limit of 100 Bq L-1 set by the Italian Legislation (D. Lgs. 28/2016). Concerning soil gases, radon and thoron levels range from <1 to 81 kBq m-3 and from 3 to 123 kBq m-3, respectively. All those values are quite similar to those recorded in the adjacent Region of Calabria by previous studies.Although the health risk due to ingestion and inhalation of groundwater can be neglected, the presence of several soil radon anomalies testifies a potentially harmful effect on the population. Radon index maps, built based on the measured radon concentration and the permeability of the soil, highlight that parts of the investigated area are characterized by an enhanced hazard. Those maps might have a useful role in preliminary screening activities related to the identification of the so-called Radon Priority Areas (EURATOM 59/2013 and Italian legislative decree 101/2020).Soil-radon anomalous values seem to have a tectonic origin and are presumably associated with the presence of fault segments probably representing the on-land continuation of a transtensional fault zone located in the southern Tyrrhenian Sea between the Aeolian Island and the northern margin of Sicily. In this context, the seismic and radiological hazards are strictly connected, further complicating the mitigation strategies against those geological processes. Since this study illustrates the first radiological data collected in this sector of the southern Apennines of Italy, a lot of work has to be done in the near future. The main goals are to extend radon investigation in other sectors of north-eastern Sicily as well as to perform a series of indoor radon measurements to determine if a clear correlation exists between high soil radon areas and high indoor radon levels.  
Deriving targeted intervention packages for ecosystem-based adaptation: A geospatial multi-criteria approach for building climate resilience in the Puna region, Peru.
Authors: Higuera Roa Oscar , Cotti Davide , Aste Natalia , Bustillos-Ardaya Alicia , Schneiderbauer Stefan , Tourino-Soto Ignacio , Roman-Dañobeytia Francisco , Walz Yvonne
Published: February 2023

Emergent dynamic climate risks challenge conventional approaches for climate adaptation and disaster risk reduction. This situation demands new ways of addressing climate risks with integrated solutions. However, little attention has been paid to exploring methodological approaches for combining adaptation measures to reduce climate risks. Still, selecting the appropriate and effective combination of adaptation measures is a challenging task. This research results in a geospatial multi-criteria approach for developing ecosystem-based adaptation packages to face climate change effects and applies this innovative methodology to a case study area in the Puna region in Peru. We started with an in-depth literature analysis combined with a participatory process with local experts to identify and select locally valid adaptation measures for the specific context of the case study area. Building upon that, we developed the overall multi-criteria approach consisting of a matrix-based procedure to evaluate the applicability of relevant adaptation measures and their feasibility of being combined in adaptation packages. We then integrated the multi-criteria analysis into a Geographic Information System using a spatial analysis model to map suitable intervention areas. Next to the methodological innovation, we applied this multi-criteria approach in the case study area to generate a place-based adaptation package for addressing the risk of reduced water provision, with its respective potential intervention sites differentiated by adaptation measure. This methodological approach is novel and considered an affordable support tool that helps practitioners design more robust and effective adaptative interventions. Furthermore, this methodological approach involves shifting the perspective from activities focused on "single adaptations" to "multi-solution" strategic interventions that address climate risks more comprehensively, recognizing the dynamics and complexities of the social-ecological systems. We encourage researchers and practitioners to transfer the methodological approach to other contexts and, with that, accelerate the efficient and targeted implementation of nature-based solutions for climate resilience.
Soils and Economy - Snapshots on Europe and Southern Africa
Authors: Meyer Uwe
Published: February 2023

Soils are often underestimated and overlooked in reviewing national economic structures. Soils and groundwater are the essential basics for food production. Beyond securing nourishment, quantity and quality of soils are pivotal factors in farming, forestry and further land use. The potential of soils governs the availability and variety of its products for national food security and trading. In most industrial European countries, farming has only a share of about 1% of the national gross domestic product but secures vital needs. In the Sub-Saharan region, the same share varies between 16% and 20%, largely depending on regional weather, water availabilty and soil quality. The largest threats are climate change and depletion of soils. Whereas European countries aim for steadily increasing sustainability, countries in Southern Africa are often struggling between short term profits, preservation of soils and necessary climate adaptions. The study sheds some light on the different roles of soils in European and Southern African economies, their inter-dependencies, the necessity to map quantities and qualities of soils for managemant measures and growing needs with a still fastly rising population in Southern-Africa. 
The growth of fault damage zones; field data and analogue modelling
Authors: Soliva Roger , Mayolle Sylvain , Dominguez Stéphane , Wibberley Christopher
Published: February 2023

The study of faults in the upper crust has generated interests in modelling their impact on fluid flow and the mechanical behavior of the earth's crust. Fault damage zones are important structures with multiple implications for resource management and earthquake studies. This work aims to characterize the distribution and growth of damage around faults, and to study its impact on the Displacement - Damage thickness (D-T) scaling law. Two complementary approaches of field analyses and analog modelling of normal faults are developed to answer this question. We presents new results of fault damage mapping, D-T scaling in carbonate rocks and the first analog modelling experiments of fault damage zones inspected in-plane. The results show a heterogeneous and asymmetric distribution of damage around faults, mainly influenced by fault interactions during their growth (segmentation, conjugate faults). A D-T law specific to wall damage is established and shows a normal correlation between D and T for less than c. 100 m of fault displacement, and also confirms the existence of a damage thickness threshold after c. 100 m of displacement. To explain this law, we propose a damage zone growth model controlled by the interaction and coalescence of fault segments. Analogue modelling shows a failure mode transition during fault growth, from a segmented dilatational-shear mode to a localized compactional-shear mode. They also demonstrate that initiation of segmentation, segment activity selection, interaction and coalescence processes control the development of fault damage zones and the D-T law. Furthermore, the thickness of the faulted brittle layer is a main controlling parameter of segmentation, strain localization and the fault damage thickness threshold observed.
Generating multi-temporal landslide inventories through a general deep transfer learning strategy using HR EO data
Authors: Bhuyan Kushanav , Tanyas Hakan , Nava Lorenzo , Puliero Silvia , Meena Sansar Raj , Floris Mario , Westen Cees van , Catani Filippo
Published: February 2023

Mapping landslides in space has gained a lot of attention over the past decade with good results. Current methods are primarily used to generate event inventories, but multi-temporal (MT) inventories are rare, even with manual landslide mapping. Here, we present an innovative deep learning strategy employing transfer learning. This allows our Attention Deep Supervision multi-scale U-Net model to be adapted to landslide detection tasks in new regions. This method also provides the flexibility to retrain a pretrained model to detect both rain and seismic landslides in new regions of interest. For mapping, archived Planet Lab remote sensing imagery from 2009 to 2021 at spatial resolutions of 3–5 m was used to systematically generate MT landslide inventories. Examining all cases, our approach provided an average F1 value of 0.8, indicating that it successfully identified the spatiotemporal occurrence of landslides. To examine the size distribution of mapped landslides, we compared the frequency distribution of predicted co-seismic landslides with manually mapped products from the literature. The results showed good agreement between the calculated exponents of the power law, with differences ranging from 0.04 to 0.21. Overall, this study demonstrated that the proposed algorithm can be applied to large areas to construct a polygon-based MT landslide inventory.
An assessment of satellite-derived supraglacial lake depth measurements on the Greenland ice sheet
Authors: Melling Laura , Leeson Amber , McMillan Mal , Maddalena Jennifer , Glen Emily , Sandberg Sørensen Louise , Winstrup Mai , Arildsen Rasmus
Published: February 2023

Supraglacial lakes (SGLs) form when meltwater collects in glacial surface depressions. On the Greenland ice sheet (GrIS), SGL position is controlled by bedrock topography, meaning SGLs form in approximately the same locations each melt season. SGLs provide surface water storage and mediate the transfer of surface water to the ice sheet bed. Drainage water from SGLs has been shown to infiltrate to the base of the ice sheet and lubricate the ice sheet-bedrock interface, causing transient increases in basal sliding at the glacier margin. SGL depth is used to calculate the volume of water contained within the basin and thus the likelihood of hydrofracture caused by increased pressure from overlying water. As overlying water pressure is a function of water depth, determining the accuracy of depth estimation techniques is of the utmost importance in obtaining reliable estimates of hydrofracture likelihood and in determining SGL drainage impacts on ice sheet velocity.Here, we present the results of an intercomparison of SGL depth measurements focused on the Watson River region of the GrIS. Previous studies have derived SGL depth by applying the Philpot (1989) radiative transfer equation to satellite-derived optical imagery. These results proved difficult to validate until recent advancements in remote sensing which allowed us to compare the radiative transfer-derived depths to laser altimetry measurements and high-resolution digital elevation modelling. Previous research has separately investigated the use of the Philpot (1989) radiative transfer equation, laser altimetry and digital elevation models, but none have intercompared all three.This research compares estimates of SGL depths in the Watson River region in southwest Greenland that have been derived using three satellite-based approaches; 1) by applying the radiative transfer equation proposed by Philpot (1989) to Sentinel-2 optical satellite imagery, 2) using ICESat-2 laser altimetry and 3) from ArcticDEM digital elevation models.Using the radiative transfer equation, we find the green band overestimates SGL depth and the red band underestimates SGL depth (with caveats) compared to ICESat-2 transects and digital elevation models. In summary, we achieve the first comprehensive intercomparison of these methods and provide insight into the strengths and potential limitations of each method, including levels of agreement between datasets, and associated uncertainties. This work helps to improve confidence in radiative transfer-derived estimates of SGL depth and volume and, consequently, quantitative estimates of meltwater storage on the surface of the GrIS. This research is associated with ESA’s Polar+ 4DGreenland study.