bluuebunny/crossref_metadata_2025 huggingface dataset:
The science of our Sun’s astrosphere: in-situ ions from the Voyagers and remotely sensed ENAs from Cassini
Authors: Dialynas Konstantinos , Krimigis Stamatios , Decker Robert , Hill Matthew , Nikoukar Romina
Published: March 2024

The path-breaking observations of the two Voyager spacecraft over the past two decades, have revolutionized our understanding of interplanetary space within our solar bubble. The crossings of the Voyagers (V1, V2) of the Termination Shock (TS) led to the discovery of the previously unknown reservoir of ions and electrons that constitute the heliosheath, whereas the combination of in-situ particle and fields measurements from V1 and V2 with remote images of ~5.2 to 55 keV ENAs from Cassini/INCA at 10 AU, revealed a number of previously unanticipated heliospheric structures such as the “Belt”, a region of enhanced particle pressure inside the heliosheath. The V1 and V2 crossings of the heliopause (HP) pinpointed the extent of the upwind heliosphere’s expansion into the VLISM and its rough symmetry. We will provide a brief discussion for the contribution of the >28 keV Voyager 1 & 2/LECP observations that established “ground truth” to the ENA images from Cassini/INCA towards addressing longstanding, fundamental questions for the heliosphere’s interaction with the Very Local Interstellar Medium (VLISM), such as the shape and properties of the ion spectra inside the heliosheath, the acceleration of low energy ions and Anomalous Cosmic Rays (ACR) in the heliosheath, the pressure balance and plasma beta in the heliosheath that dictate the magnitude of the magnetic field upstream at the heliopause, the thickness of the heliosheath, the effects of the solar cycle through the outward propagating solar wind that result in an “breathing” (inflating and deflating) heliosphere, together with the implications of these measurements towards addressing the global shape of the heliosphere. The crossings of V1 and V2 from the HP revealed that the primary driver of the interaction of the heliosphere with the VLISM is the pressure of the interstellar (IS) magnetic field, whereas this interaction is more complex than previously thought: The V1 crossing of the HP was associated with the discovery of a flow stagnation region, possibly due to flux tube interchange instability. Further, V1 showed the existence of a radial inflow of low energy ions within the HS for ~9 AU before the HP, and a small radial outflow over a spatial scale of at least 33 AU past the HP, that corresponds to an ion population leaking from the HS into interstellar space. The use of these observations drive the requirements for the particle and fields measurements for a possible future Interstellar Probe mission.
Magma ascent in active Australian intraplate basaltic volcanic provinces
Authors: Handley Heather , Cas Ray , England Thomas , Hellebrand Eric
Published: March 2024

Australia hosts at least two active continental basaltic volcanic fields with Holocene eruption ages yet very little is understood about magma ascent and mantle to surface ascent pathways and timescales. In this study we use textural and chemical information stored within minerals from two of the youngest volcanic eruptions in northeast and southeast Australia to investigate magmatic plumbing systems and magma ascent in Australia’s intra-plate volcanic fields. Volcanic rock samples from the three main eruptive phases at Mt Schank volcano in the Newer Volcanics Province, South Australia, reveal textural and mineralogical differences throughout the evolution of the eruption that correspond to variations in eruption style and the availability of external water. Crustal xenoliths (e.g., quartz and limestone) are abundant in the middle, maar-forming phase of the eruption. The lack of mantle-derived xenoliths and xenocrysts throughout the eruption, olivine compositions and sector and oscillatory zoned, euhedral clinopyroxene suggest a more stalled ascent pathway of magma compared to the mantle xenolith-bearing volcanoes in parts of the Victorian sector of the province. Skeletal olivine crystals and dendritic clinopyroxene microlites indicate moderate degrees of undercooling at Mt Schank during magma ascent. In northeast Queensland, interaction of magma with mantle xenolith’s are used to determine magma ascent dynamics. Disequilibrium and quench textures and chemical zoning patterns in olivine, clinopyroxene, orthopyroxene and spinel on xenolith margins and within host glass reveal a detailed and complex history of magma ascent.
Slowdown of the rise in the optimum temperature of photosynthetic productivity under future global warming
Authors: Xu Chongyang , Liu Hongyan , Yakir Dan , Liang Boyi , Zhu Xinrong , Feng Siwen , Grünzweig José
Published: March 2024

The optimum air temperature for photosynthetic ecosystem productivity (Topt) determines the annual maximum of terrestrial carbon uptake. Previous studies have quantified Topt and explored its acclimation in response to climatic warming. However, there remains uncertainty regarding the extent to which Topt has changed globally in recent decades and how it might evolve in the future. Our analysis, using both satellite- and ground-based datasets, reveals a slight increase in Topt over the past two decades (+0.14°C, 2000-2019), contrasting with a significant 0.46°C rise in maximum global growing-season temperature (Tmax). The lack of change in Topt was attributed to an insignificant trend of Tmax in cold areas and to drought inhibiting thermal acclimation of photosynthesis in temperate and arid regions. If global surface temperatures exceeded pre-industrial levels by 2°C, the mean Tmax over the globe was predicted to increase slightly more than Topt (1.5 vs. 1.2°C), with the gap widening under a 4°C temperature increase (4.1 vs. 3.4°C). In the +4°C scenario, soil drought dominated the widespread decline in photosynthetic acclimation across tropical and temperate vegetation, slowing the rate of Topt increase at the end of the century (+0.04°C, 2080-2099). Conversely, increasing atmospheric CO2 concentrations failed to have significant effects on Topt and its acclimation. These findings imply that the absorption of atmospheric CO2 by terrestrial vegetation, and subsequent carbon sequestration, may be further hampered by the limited acclimation capacity of Topt to rising global temperatures.
Diffusive smoothing of isotopic signals in ice cores: the grain-scale signature of excess diffusion as a testable prediction
Authors: Ng Felix S. L.
Published: March 2024

Diffusion limits the survival of climate signals on ice-core isotope records. Diffusive smoothing acts not only on annual signals near the surface, but also on millennial signals in deep ice where they shorten to decimetres or centimetres. Short-circuiting of the slow diffusion in crystal grains by fast diffusion along liquid veins can explain the accelerated or “excess” diffusion found on some isotope records. But direct experimental evidence is lacking whether the short-circuiting mechanism really operates as theorised; current theories of it also neglect diffusion along grain boundaries. The pattern of isotope concentrations across crystal grains caused by short-circuiting provides a testable prediction of the mechanism. Here, we extend the theory for grain boundaries and calculate the pattern for different assumptions of grain-boundary diffusivity and thickness, and different temperature, vein and grain sizes, and vein-water flow velocity. Two isotopic patterns prevail in ice of millimetre grain sizes: (i) an axisymmetric pattern with isotopic excursions centred on triple junctions in the case of thin, low-diffusivity grain boundaries; (ii) a three-spoke pattern of excursions around triple junctions in the case of thick, highly-diffusive grain boundaries. Because these signatures have excursions potentially reaching several per mil and as thick as 10–25% of the mean grain radius, they should be detectable by LA-ICP-MS mapping on ice affected by excess diffusion. We further examine how the predicted patterns vary with depth (through a wavelength of the bulk isotopic signal) to formulate the procedure of testing for the occurrence of short-circuiting, such as applicable to ice-core samples from the EPICA Dome C and Beyond EPICA Oldest Ice projects. Because our model accounts for grain boundaries and veins, it also characterises the bulk-ice isotopic diffusivity more comprehensively than past studies.
Impacts of land use change and interannual climate variability on biomass burning emissions, air quality and public health in Amazon
Authors: Ng Tsin Hung Leo , Tai Amos P. K. , Sitch Stephen , Aragao Luiz , Zhai Shixian
Published: March 2024

Biomass burning in Amazon Basin has a significant impact on regional climate and deteriorates regional air quality, which poses a threat to human and ecosystem health. The fire-induced pollution worsens during dry season (Jul to Nov) and shows a strong seasonal variation. Past research has demonstrated that the occurrence of wildfires in Amazon is not only influenced by deforestation, but also interannual climate variability, particularly droughts. Here we estimate the impacts of deforestation and droughts on fire emissions and regional air quality between 2010 to 2015 by using Global Fire Emission Database Version 4 (GFED v4) to drive a global 3-D atmospheric chemical transport model GEOS-Chem High Performance (GCHP) and further examine the effect of PM2.5 and O3 on premature mortality across the region. By comparing the “fire-on” and “fire-off” scenarios, we find that biomass burning alone in normal years (2011 and 2013) contributes 5.7 μg m-3 (47.6% of the total concentration) PM2.5, 0.08 ppm (46.3%) CO, 0.03 ppb (85.0%) NOx, and 9.5 ppb (41.2%) O3; and these numbers during drought years (2010, 2012, 2014 and 2015) increase to 19.6 μg m-3 (74.7%) for PM2.5, 0.20 ppm (67.0%) for CO, 0.19 ppb (97.4%) for NOx, and 15.6 ppb (52.0%) for O3. We find that these pollutants from wildfires mainly concentrate in the south-eastern Amazon and then transport southward, thus strongly impacting public health in the downwind regions. We estimate that premature mortality due to long-term exposure to particulate matter and ozone by applying the simulated concentration to the concentration-response functions from the European Environment Agency. We find that ~8,500 and ~10,400 deaths per year are attributable to PM2.5 and O3 exposure for 2010-2015 respectively. During drought years, we discover there are 2.8% and 3.4% more deaths than normal years for PM2.5 and O3 exposure. Our study shows the significance of biomass burning emissions in shaping the air quality in the Amazon region, and highlights the impact of drought events on enhancing biomass emissions, worsening regional air quality and causing public health issues. Therefore, it is important to address the underlying causes of biomass burning in the Amazon, such as deforestation and land use change, and droughts, to protect the region's ecosystems and mitigate the impacts of climate change.
The impact of the re-emission of road dust by vehicles passages on particulate matter concentrations – a case study with EMEP MSC-W
Authors: Walkowicz Aleksandra , Jeleniewicz Grzegorz , Kryza Maciej , Sattari Anahita , Strużewska Joanna , Werner Małgorzata
Published: March 2024

In most European countries road transport is the main contributor to airborne particulate matter (PM, PM2.5 and PM10) concentrations. PM from traffic is classified by the method of emission into three groups: 1) an exhaust or tail-pipe component, 2) a non-exhaust component due to the abrasion of tires and brakes and of the road surface, and 3) a non-exhaust component related to the re-emission of road dust by vehicles passages (resuspension). Considering the reduction of the exhaust emissions related to the strict regulations on the cars as well as coming stricter World Health Organisation (WHO) recommendations for PM10 and PM2.5 concentrations the role of non-exhaust emission is enhancing. Therefore the aim of this study is to estimate the impact of the re-emission of road dust on PM2.5 and PM10 concentrations.We used the EMEP MSC-W chemical transport model to calculate air pollution concentrations. The model was run two times for southern Poland for the year 2019. For the first run we had no changes to the emission inventories, which were provided from two databases (no resuspension included):1) the EMEP[gr1]  emissions data at 0.1o x 0.1o spatial resolution for Europe, and 2) emissions from the National Centre for Emissions Management, Institute of Environmental Protection - National Research Institute for Poland (0.005o x 0.005o). For the second run, PM emissions from the resuspension was added to the road transport sector. Road resuspension emissions were estimated using the VEIN model. We analysed the results in terms on annual mean and daily PM concentrations and exceedances of  EU limit and WHO recommended values. Acknowledgement: The study was supported by the LIFE Remy [No: LIFE20 PRE/IT/000004 ], LIFE-MAPPINGAIR/PL [No: LIFE17 GIE/PL/000631] and the Polish National Science Centre project [No: UMO-2021/43/B/ST10/01189].
Testing Hybrid-3DEnVar in the convective scale NWP model AROME-Austria
Authors: Jyoti Kaushambi , Weissmann Martin , Griewank Philipp , Meier Florian
Published: March 2024

We test a Hybrid 3-Dimensional Ensemble Variational (Hybrid-3DEnVar) Data Assimilation (DA) method in the limited-area NWP model AROME over Austria at 2.5km horizontal resolution, with a flow-dependent error covariance matrix sampled from a 50-member ensemble.
Rapidly evolving highly non-linear convective-scale processes and the unique orography of the Austrian Alps intensify the complexities of estimating model error correlations. While the climatological error covariance matrix can not well represent the non-linear error growth of convective-scale weather, these errors can be incorporated into the assimilation using the ensemble-based error covariance matrix. We explore 11 weighted combinations of climatological and sampled covariance matrices, ranging from a purely climatological (weight of 0) to a purely ensemble-based (weight of 1) B-matrix, with incremental weight adjustments to the ensemble by 10 percent increments. The pure climatological configuration (3-dimensional variational data assimilation, 3DVar) is the operational DA scheme of GeoSphere Austria and serves as a comparative benchmark for our experiments. Multiple distinct summertime convective weather scenarios with a special focus on local convection were tested, while cold and warm fronts also influenced some of these cases. Aircraft wind and temperature observations are split into assimilated and non-assimilated parts so that the latter serves as validation for the analysis.The resulting analysis from the Hybrid-3DEnVar configuration outperforms the operational 3DVAR of GeoSphere Austria, indicating a substantial leap forward in forecast accuracy of convective scale weather within Austria’s complex terrain. However, the optimal weight to the ensemble-based covariances for the optimal analysis strongly depends on the weather phenomenon investigated.Keywords: AROME-Austria, Hybrid-3DEnVar, a 50-member ensemble, convective scale, and non-linear error growth. 

 

 
Efficient and systematic evaluation of the global hydrological model WaterGAP against multiple types of observation data 
Authors: Rabanizada Ezatullah , Müller Schmied Hannes , Döll Petra
Published: March 2024

Global hydrological models (GHMs) play a crucial role in understanding Earth's water resources. To evaluate the strengths and limitations of these models, and how their performance changes with parameter modification or calibration, model outputs are compared against observational data. Traditionally, hydrological models have been evaluated against in-situ streamflow observations. However, this can lead to incomplete assessments of models because models might simulate streamflow well while failing in other aspects, such as overall terrestrial water storage anomaly (TWSA) or the dynamics of specific storage compartments. Nowadays, geodetic and remote sensing data (time series) have become available and are suitable for model evaluation in addition to streamflow. This study takes a comprehensive look at the GHM WaterGAP2.2e by extending the evaluation beyond streamflow observations by integrating different GRAC TWSA products, snow cover fraction, and the dynamics of lake and reservoir surface areas, and the corresponding storage anomalies. The multi-variable evaluation approach is particularly valuable in identifying areas where the model might need improvement. As an example, by comparing the model against GRACE TWSA and streamflow observation, we can test the effect of increasing water storage capacity in soils or decreasing the groundwater discharge coefficient. These parameters govern the flow from groundwater to surface water bodies, offering viable options to address, for example, underestimation or overestimation of the temporal variability of GRACE TWSA when using models like WaterGAP. Evaluating the snow cover fraction model output against observed data improves the model’s ability to simulate snowpack dynamics, a crucial element for estimating seasonal water supply in areas that depend on snowfall. Furthermore, comparing the model output with observed surface areas and storage anomalies of lakes and artificial reservoirs helps to improve, for example, the estimation of surface water use and the simulation of reservoir management. Ultimately, the multi-variable evaluation approach could pave the way for creating models better suited to address the complex questions in global water research.
Distinguishing natural and planted riparian forests by the Natural Numerical Network and the graph-Laplacian
Authors: Ožvat Aneta Alexandra , Mikula Karol , Kollár Michal , Šibíková Mária , Šibík Jozef
Published: March 2024

Our study focuses on identifying and classifying Natura 2000 habitats using Sentinel-2 multispectral data. The Natural Numerical Network is a deep learning algorithm for the classification of complex structures such as plant communities. It is based on the optical information from Sentinel-2 satellite bands and the basic statistical characteristics calculated from that information. Using the Natural Numerical Network, desired areas are classified, and relevancy maps are created. The relevancy map tells us about the relevancy of the classification of the segmented area into the chosen habitat. Our research is putting emphasis on the riparian forests along the Danube River. We construct the mean graph-Laplacian and show its application in distinguishing the natural riparian forests of the Natura 2000 system with high biodiversity from the planted monodominant forests with a similar species composition. The basic idea is that the natural forests are represented by much higher variability of the optical data from satellites than the planted ones. Using the relevancy maps calculated by the Natural Numerical Network, we find the potential Natura 2000 habitat-riparian forest areas, and the mean graph-Laplacian eliminates the planted forests from the relevancy maps by assigning the low or zero values to the areas with low optical data variability.
  PM2.5 concentration forecast using Hybrid models over Urban cities in India
Authors: k k Vyshnavi , Verma Shubha , Vaibhav Vibhu
Published: March 2024

Air pollution poses a substantial risk to both public health and the environment. Accurate forecasting of air quality is crucial in mitigating its detrimental impacts. The existing forecast method of air quality in India is computationally intensive and is not economical; hence, we utilize Advanced Machine and Deep Learning Models to forecast air quality. The objective of this research is to develop a novel hybrid model integrating Long Short-Term Memory (LSTM), Extreme Gradient Boosting (XGBoost), and Multi-Layer Perceptron (MLP) models to forecast concentrations over Kanpur. The study involved comprehensive data collection (Secondary air quality and meteorological data from the Central Pollution Control Board), analysis, and experimentation with multiple models. Root mean square error (RMSE) and coefficient of determination (R2 score) are used for model validation. MLP-XGBoost-LSTM hybrid model works well with a decreased RMSE (12.6 μg/m3 ) and increased R2 score (0.96) compared to individual models (XGBoost- 37 μg/m3, MLP-39 μg/m3, and LSTM-41 μg/m3).  The significance of the research lies in its potential to provide highly accurate forecasts, even with limited computational resources. These findings have significant implications for environmental policy, public health in heavily polluted regions, and the broader utilization of machine learning in environmental science.
Dynamic Evolution of the Northern Carnarvon Basin: An Integrated Kinematic Approach
Authors: Makuluni Patrick , Hauser Juerg , Clark Stuart
Published: March 2024

The geological histories of passive margin basins are dominated by tectonically induced vertical and lateral motions that control sediment transport and the development and distribution of resource systems within the basins. However, the upward (uplift and exhumation), downward (burial and subsidence) and lateral (extension, rifting and potential inversion) motions are rarely analysed together. Exploration models built from basin evolution models that include only the vertical dimension may contain larger uncertainties than those that combine lateral and vertical motions. Based on a case study, our research suggests that the combination of analyses can improve the accuracy of basin evolution models and help optimise exploration models. Here, we present a case study for the basin evolution model for the Northern Carnarvon Basin that incorporates data from such a combined vertical and lateral motion analysis. Backstripping and decompaction techniques were used to analyse subsidence in more than 200 wells to build the basin’s subsidence and sediment evolution maps. These maps were then used to analyse lateral motions associated with the intraplate rift development in the region. In parallel, we analysed exhumation using compaction and vitrinite reflectance analysis techniques on porosity, sonic logs and paleotemperature data from 210 wells. Our combined analyses revealed seven critical periods of basin development from the Triassic to the present. The Triassic Period was dominated by thermal subsidence and sedimentation within the south-western parts. High subsidence (~ 90 m/Ma) and sedimentation were dominant in the Early and Mid-Jurassic, coinciding with the intraplate rifting of up to ~8 mm/yr, which produced the major sub-basins in the southern and southeastern parts of the basin. This was followed by Callovian exhumation that removed up to 1500 m of sediments from the western part of the basin. The Cretaceous was dominated by rifting and breakup-related subsidence, truncated by exhumation episodes that removed up to 1000 m of sediment thickness in the southeastern parts of the basin. In the Cenozoic, the basin experienced subduction-related tilting that exhumed the southern part while the northeastern parts subsided. Our study has shown that integrating the vertical and lateral motions presents a more accurate and complete basin evolution model with the potential for improving the optimisation of basin exploration.
Flood impacts and adaption for transportation
Authors: Wang Weiping
Published: March 2024

The adverse effect of climate change continues to expand, and the risks of flooding are increasing. The transport system is crucial for daily life and threatened heavily by floods. Despite advances in emergency management for transportation, we still lack an integrated framework to examine the impact of transport system under floods. In this study, we propose an integrated approach to quantitatively assess how floods impact the functioning of a highway system. The framework has three parts: (1) a simulation model to represent traffic, heterogeneous user demand, and route choice in a transportation network; (2) a flood simulator using future runoff scenarios generated from global climate models and the CaMa-Flood model; and (3) an impact analyzer, which superimposes the simulated floods on the traffic simulation system, and quantifies the flood impact on a transportation system. This framework is illustrated with different cases studies including the Chinese highway network, urban transportation networks in 40 cities in China and road traffic system in the Guangdong-Hong Kong-Macao Greater Bay Area. Because of climate change, adaptation strategies are critical for mitigating future flood damage. Our approach provides a quantitative assessment tool to evaluate the effectiveness of adaptation measures. The results show that for different global climate models, the associated flood damage to a transportation system is not linearly correlated with the forcing levels, or with future years and floods in different years have variable impacts on regional connectivity. These results have critical implications for transport sector policies and can be used to guide highway design and infrastructure protection. The approach can be extended to analyze other networks with spatial vulnerability, and it is an effective quantitative tool for reducing systemic disaster risk.
Is drought protection possible without compromising flood protection? Estimating the maximum dual-use benefit of flood reservoirs in Southwest Germany
Authors: Ho Sarah , Kipp Chantal , Goeppert Hans , Hoefer Johannes , Seidel Frank , Ehret Uwe
Published: March 2024

As climate change drives intensification and increased frequency of hydrological extremes, the need to balance drought resilience and flood protection becomes critical for proper water resources management. Recent extreme droughts in the last decade in Germany have caused significant damages to ecosystems and human society, prompting renewed interest in sustainable water resources management. At the same time, protection from floods such as the catastrophic 2021 event in the Ahr Valley remain heavy in the public conscience. In the state of Baden-Württemberg in Southwestern Germany alone, over 600 small (< 1 million m3) to medium-sized (1-10 million m3) reservoirs are currently operated for flood protection. In this study, we investigate optimal reservoir operating (storage and release) rules in a dual flood-drought protection scheme for selected modeled flood reservoirs in Baden-Württemberg. Daily target releases for drought protection are proposed based on modeled inflows from the calibrated hydrological model LARSIM. In a first step, the reservoir operation is optimized in a scenario of perfect knowledge of the future by using  meteorological observations as artificial weather forecasts in LARSM. The results of different operating rules are then evaluated based on their adherence to the target releases and flood protection performance. Rulesets that result in worsened flood protection relative to the current (flood-only) operation were eliminated as potential operation schemes. Based on provisional results, we will present and discuss the maximum potential benefit of adapting and retrofitting existing flood reservoirs for drought water storage.
Understanding near-surface hydrogeological processes around Lake Velence (Hungary) – using mesh graph neural networks on multidimensional remote sensing data
Authors: Rapai Tibor , Baják Petra , Lukács András , Székely Balázs , Erőss Anita
Published: March 2024

Lake Velence is a shallow soda lake in Hungary whose water budget is mainly driven by precipitation and evaporation. The lake has shown a deteriorating tendency recently, including extremely low lake levels and poor water quality, which indicates its vulnerability against changing climatic conditions. At the same time several water usage conflicts appeared in the catchment area. Until recently, the groundwater component in the lake's water budget and the hydrogeological processes in the catchment area have not been taken into consideration. Recent hydrogeological studies, however, show groundwater discharge into the lake.  Thus, further investigating this question is of high importance, hence groundwater could reduce climatic vulnerability.Our ongoing work aims at developing a model-based evaluation technique, utilizing all map-based geophysical information and time series of different satellite data products, having sufficient spatial resolution and providing information about parameters strongly connected to subsurface processes, showing up on the surface. The basic DEM raster layer is imported from Copernicus GLO-30 dataset, having vertical precision
From infiltration to steady-state flow in partially saturated media – bridging solute transport between millimeter-decimeter and minute-day scales
Authors: Kalisman Doron , Dror Ishai , Berkowitz Brian
Published: March 2024

This study experimentally demonstrates the impact of water and solute influx magnitude, and its resulting local distribution, on transport at timescales longer than the influx duration, through a disparate velocity field of a partially saturated domain. In a sand-filled cell, steady-state flow is maintained with a constant horizontal hydraulic head, while the upper part of the cell is partially saturated. The horizontal velocity varies by orders of magnitude from the surface to the saturated zone. An influx of water with a dissolved tracer is applied at the middle of the upper boundary surface, over several minutes, forming a plume that reaches a depth of a few centimeters. This influx disturbs the flow field locally, but after it is terminated, the return to steady-state flow is of the order of magnitude of the influx timescale. Eventually, the solute flows to the saturated zone and out of the cell through a path on the scale of decimeters, over a time scale of days. Employing ICP-MS as a sensitive measurement tool to detect highly diluted concentrations of solute enables tracking of a small influx volume that does not significantly perturb the flow field. This maintains a separation between the distinct spatial-temporal scales of the short-term local infiltration and the long-term system-scale transport. Applying varying influx magnitudes sets the solute plume across different velocity profiles and thus dictates the downstream plume distribution. A low influx relative to the hydraulic conductivity of the partially saturated sand allows solutes to infiltrate farther down compared to a higher influx, so that the plume reaches higher flow velocities but also spans a wider velocity variability. A higher influx relative to the hydraulic conductivity leads to a local increase in saturation, but a shallower depth of infiltration compared to the lower influx, and the system accordingly exhibits a more uniform plume located at a lower velocity region. In downstream solute concentration measurements, these influx variations result in a faster but more smeared breakthrough for the lower influx compared to a slower and more uniform breakthrough for the higher influx, corresponding to their initial distribution after infiltration.
Comparative Study on Topography Prediction Using Gravity Anomalies and Gravity Gradient Anomalies
Authors: Tian Yuwei , Xu Huan , Yu Jinhai
Published: March 2024

Direct bathymetry is a primary data source for creating high-precision seafloor topography but cannot easily achieve high-resolution global coverage. Therefore, using gravity data for seafloor topography prediction is an alternative method. Current algorithms, reliant on the measurement of ship soundings and geophysical parameters, still have room for improvement in accuracy and coverage. In this study, we establish observation equations based on vertical gravity anomalies (VG, also called gravity anomalies) and vertical gravity gradient (VGG) anomalies generated by a rectangular prism and develop a new analytical algorithm for predicting topography. We validate its effectiveness through numerical simulations and actual applications. We determine the source of the errors, the mid–high frequency error caused by the boundary area is reduced by regularization, whereas the low-frequency error caused by the far area is reduced by the error equation algorithm. In the shallow areas with a maximum depth of 2 kilometers and deep-sea areas with a maximum depth of 5 kilometers, the root mean square errors (RMS) for VGG anomalies prediction are 93.8 m and 233.8 m, respectively, while for VG anomalies prediction they are 101.2 m and 239.4 m. We also find that VGG anomalies are more sensitive to topography fluctuations, but VG anomalies have a stronger linear correlation with topography. Additionally, we propose a cubic spline interpolation algorithm to effectively fuse the prediction results and ship soundings, improving topographic prediction accuracy in shallow and deep-sea areas by up to 53.2% and 39.67%, respectively.
Advanced soil moisture forecasting using Cosmic Ray Neutron Sensor and Artificial Intelligence (AI)
Authors: Khan Sanaraiz Ullah , Said Ahmed Hami , Mbaye Modou , Toloza Arsenio
Published: March 2024

By the year 2050, the global population is projected to reach 9 billion, intensifying the demand for food production and posing substantial challenges to water resources. In this context, the monitoring and prediction of soil moisture play a pivotal role in adopting precision irrigation and effectively managing agricultural water.
Cosmic Ray Neutron Sensors (CRNS), a nuclear technology designed for estimating soil moisture content across extensive areas (up to 40 hectares, contingent on sensor sensitivity and location), have demonstrated potential in supporting agricultural water management, hydrology research, and land surface modeling and could serve this purpose admirably.
Using a ten-year dataset of soil moisture records from CRNS in conjunction with weather data, we applied a variety of machine learning and artificial intelligence algorithms, such as support vector machines (SVM), extreme gradient descent boost (XGB), long-short term memory (LSTM), recurrent neural networks (RNN) to forecast soil moisture accurately.
Preliminary findings exhibit a promising correlation between the predicted and measured soil moisture. Notably one of the algorithms, the XGB  excelled, achieving a coefficient of determination (R2) of 0.67 a root mean square error (RMSE) of 4%, and a mean absolute error (MAE) of 2.7% within 48-hour prediction window in the general scenario.
These initial outcomes are encouraging, highlighting the potential fusion of cosmic-ray neutron sensors with artificial intelligence paving the way for a new agriculture era focused on precision irrigation. However, further analysis and validation are required to verify the robustness of this model.
Susceptibility of the Iberian Peninsula to extreme precipitation and aridity: a high-resolution analysis for 1950–2022
Authors: Claro André , Fonseca André , Fraga Helder , Santos João
Published: March 2024

This study consisted of the assessment of the Iberian Peninsula’s (IP) susceptibility to precipitation extreme events (PEE) and aridity across a long historical period of 1950–2022 and a shorter period of 1981–2022, based on the calculation of eight extreme precipitation and two aridity indices. Furthermore, two recently developed extreme precipitation susceptibility indices were also applied, namely a composite index and a principal component analysis-based index. ERA5-Land reanalysis data were used for those calculations, previously bias-corrected with the Iberia01 observational dataset as a baseline in their overlapping period of 1971–2015, following a quantile-mapping approach. A trend analysis performed for the two periods reveals an annual and seasonal drying trend over southwestern, central, and northeastern regions, as well as a wetting trend over the southeast annually. Regarding the PEE contribution to total precipitation (which is higher over eastern IP, and around 24% to 28%), it is increasing in several coastal regions during winter, and in north-central regions during summer and annually. High to very high susceptibility areas, which correspond to approximately 50% of the IP, are located on the mountains’ Atlantic-facing (western IP mountains) or Mediterranean-facing (eastern IP mountains) side, while the inner IP plateaus reveal low to moderate susceptibility. Our results agree with previous studies and show with high detail the susceptibility to PEEs and the recent past trends of all IP regions, which is a novelty comparatively to those studies. This highly detailed information can be used, e.g., to improve the assessment and mitigation of urban flood risks, mitigate water scarcity in the agro-food industry, or prevent crop destruction during extreme precipitation events.
What we can learn from aerosol size distribution measurements over the spring Arctic pack ice
Authors: Asplund Julia , Haberstock Lea , Matthew Jessica , Mattson Fredrik , Nilsson Lovisa , Swietlicki Erik , Willis Megan , Zang Cort , Zieger Paul
Published: March 2024

Aerosol- cloud interactions remain among the most uncertain key parameters in the fast-changing Arctic climate system, in large part due to a lack of observational data from this hardly accessible region. The spring-summer transition is a particularly under sampled time period, due to harsh ice conditions. Here, we present five weeks of aerosol size distribution measurements over the spring Arctic pack ice, including more than 30 hours of in-cloud data, obtained during the ARTofMELT 2023 expedition. A setup of three inlets, including a whole-air, an interstitial, and a counterflow virtual impactor inlet, were used to cover the full aerosol population as well as both the activated and interstitial aerosol when in cloud. We will show an overview of the collected observations and the link between the size distribution properties and parallel measured aerosol parameters such as chemical tracers, as well as an air mass source analysis. Fog events were recorded during a range of aerosol conditions, allowing us to study the activated fraction when concentrations span from under 20 particles per cc, to over 150. The dataset also features several distinct regimes where different processes such as blowing snow, new particle formation, and secondary ice production dominate or influence the aerosol population, and we will demonstrate how the regimes are characterized by the dominant mode of the size distribution.
Different tracers result in different storage and transport parameters in transient storage models 
Authors: Glaser Clarissa , Klaus Julian
Published: March 2024

Predicting in-stream transport and transient storage processes is crucial for determining biogeochemical turnover and protecting stream ecosystems. One common way to study these processes consists in analysing slug injections of artificial tracers into the stream. The explanatory power of processes inferred from these experiments depends on the quality and completeness of the recorded tracer signal, i.e., the breakthrough curve (BTC). The stream settings strongly influence the explanatory power of the BTC. For instance, an increase in transient storage zones can result in a more pronounced tailing of the BTC. It is well-known that different tracers such as sodium chloride or dye tracers exhibit different detection limits. However, limited guidance exists if and how the choice of the selected tracer or the stream settings biases the conclusion drawn from tracer experiments. To address this research gap, we carried out numerical experiments generating BTCs from slug injections through 10,000 randomly selected parameter combinations mimicking stream conditions. We employed these randomly selected parameter combinations from a predefined range for the dispersion parameter, flow velocity, cross-sectional area, and with and without consideration of transient storage exchange processes. The BTCs were truncated based on the detection limits for sodium chloride and the dye tracer uranine. We calculated transport metrics such as the temporal moments of BTCs and the transient storage index (TSI) to identify differences between the BTCs truncated based on the detection limits of both tracers. We found that the different tracers resulted in clearly different transport metrics. Specifically, the BTCs of the dye tracer exhibited higher TSI values compared to those resulting from BTCs derived from the salt tracer. The absolute and relative differences between the transport metrics of both tracers increased with higher values for the transient storage parameters, particularly for higher flow velocity and a higher dispersion coefficients representative for small streams. Our results revealed that analyzing BTCs from small streams is clearly biased when relying on sodium chloride in the experiments. These finding raise caution considering the importance of the choice of tracer, and we recommend the use of dye tracers over salt tracers for small streams where a high impact of transient storage processes is expected.
Using JULES to Model the Congo Peatlands
Authors: Cook Peter Anthony , Betts Richard , Chadburn Sarah , Burke Eleanor
Published: March 2024

The Cuvette Centrale swamp forest around the Congo has the most extensive peatland complex in the tropics, but due to its remoteness the extent and depth of the peat was only recently determined.  The international project CongoPeat has researchers from the UK, the Republic of the Congo and the Democratic Republic of the Congo, working alongside the local people in studying the peatlands to determine how they formed and the possible threats since it is vital that the peat is preserved.  While the peatlands are at least 20,000 years old the peat is thin compared to other tropical peatlands of similar age.  The JULES land surface model has been driven by a reconstruction of the past annual rainfall and meteorological data from a HadCM3 paleo global model to simulate the development of the peatlands.  The model results closely match measurements from the CongoPeat fieldwork and support the hypothesis that a long period of reduced rainfall a few thousand years ago lead to a large loss of peat.  This confirms that a consistently high water table is needed to keep decomposition of the peat to a minimum and hence preserve the peatlands.  Though JULES was unable to recreate the measured Carbon age profile, whereas simpler peat models did, this is only due to its low vertical resolution.  The JULES run was then continued with future climate projections from four global climate models to simulate how the peatlands are likely to change up to 2100.  In each projection there are lower water tables and increased decomposition of peat, but large losses only occur when rainfall is reduced or when drainage is introduced to represent disruption of the peatlands, both of which further lower the water tables.  This is in-spite of increased CO2 concentration affecting the vegetation by increasing the productivity and litterfall while reducing the amount of transpiration.
Kinematics of active deformation and possible segmentation of seismic slip along the foothills of the Western Kunlun (China).
Authors: Simoes Martine , Guilbaud Christelle , Van der Woerd Jérôme , Baby Guillaume , Barrier Laurie , Li Haibing , Pan Jiawei
Published: March 2024

The Tibetan Plateau stands as a prominent topographic feature at the Earth’s surface, characterized by intense seismic activity, in particular along the mountain ranges that form its bounding edges. To the northwest, the Western Kunlun Range has received increasing attention since the 2015 Mw 6.4 Pishan earthquake but its kinematics of deformation remain to be properly documented. Here, we analyse the terrace record of active deformation along the Karakash River, where it crosses the Hotan anticline. We date terraces using in-situ produced cosmogenic isotopes, and show that terrace incision and uplift are spatially correlated with blind duplex ramps beneath the anticline. From there, we quantify the overall slip rate of the duplex to be 1.2-2.8 mm/yr over the last ~250 kyr. Our data are not able to resolve the detailed kinematics on each blind ramp and we cannot exclude that several of them are active at places along the anticline. By comparison to the data available west of our study area, we propose that the blind structures all along the foothills of the Western Kunlun range have an overall slip rate of ~2 mm/yr. However, the way this slip rate is to be partitioned on one or several blind ramps is expected to vary along strike, generating a certain structural and kinematic segmentation of active deformation, and from there possibly explaining the moderate recorded seismicity in this region. Because this slip is transmitted upward and forward onto the Mazar Tagh wide and geometrically simple frontal thrust sheet, we question the possibility of large – but rare – earthquakes rupturing this structure. From there, we propose the idea of a bimodal seismicity in the region, as a mirror of the structural segmentation of active faults.
Based on hydroinformatics and machine learning: Evolutionary characteristics of water quality in the Yangtze River Basin over the past two decades
Authors: Wu Jiang , He Ling-Yan , Zeng Hui
Published: March 2024

The Yangtze River Basin, as the largest in China, assumes pivotal significance in comprehending its evolutionary characteristics through the examination of long-term hydroinformatics analyses. The rapid advancement of machine learning has significantly facilitated the elucidation of patterns in the evolution of water quality within the basin. This investigation relies on water quality data from 55 monitoring stations in the Yangtze River Basin, covering the period from 2004 to 2022. To address missing data, seasonal supplementation was undertaken using Kalman Smoothing and State Space Models algorithms. Subsequently, the Random Forest framework was applied to analyze the temporal evolution and spatial distribution characteristics of water quality parameters. Employing the Gower dissimilarity method, clustering analysis was conducted on mixed-type water quality data, resulting in the identification of distinct clusters, constructing water quality index models under different clusters. The findings indicate an overall enhancement in water quality within the Yangtze River Basin, with winter showcasing superior water quality and the main stem exhibiting significantly higher water quality than its tributaries. Notably significant total phosphorus pollution was observed throughout all seasons, particularly concentrated in the confluence area of the Minjiang and the main stem of the Yangtze. The comprehensive clustering results unveil the existence of three distinct water quality states in the Yangtze River Basin, further subdivided into four periods: 2004-2007, 2008-2014, 2015-2017, and 2018-2022, elucidating the evolving characteristics of water quality in the basin. The entire subset regression model underscores ammonia nitrogen and total phosphorus as common water quality parameters across various seasons and key tributaries, emphasizing the pollution characteristics of water quality in the Yangtze River Basin. This research furnishes essential data and scientific evidence, enriching our understanding and contributing to the efficient management and protection of the aquatic ecosystem in the Yangtze River Basin.