Glaciers playa vital role in providing water resources for drinking, agriculture, and hydro-electricity in many mountainous regions. As global warming progresses, accurately reconstructing long-term glacier mass changes and comprehending their intricate dynamic relationships with environmental variables are imperative for sustaining livelihoods in these regions. This paper presents the use of eXplainable Machine Learning (XML) models with GRACE and GRACE-FO data to reconstruct long-term monthly glacier mass changes in the Upper Yukon Watershed (UYW), Canada. We utilized the H2O-AutoML regression tools to identify the best performing Machine Learning (ML) model for filling missing data and predicting glacier mass changes from hydroclimatic data. The most accurate predictive model in this study, the Gradient Boosting Machine, coupled with explanatory methods based on SHapley Additive eXplanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) analyses, led to automated XML models. The XML unveiled and ranked key predictors of glacier mass changes in the UYW, indicating a decrease since 2014. Analysis showed decreases in snow water equivalent, soil moisture storage, and albedo, along with increases in rainfall flux and air temperature were the main drivers of glacier mass loss. A probabilistic analysis hinging on these drivers suggested that the influence of the key hydrological features is more critical than the key meteorological features. Examination of climatic oscillations showed that high positive anomalies in sea surface temperature are correlated with rapid depletion in glacier mass and soil moisture, as identified by XML. Integrating H2OAutoML with SHAP and LIME not only achieved high prediction accuracy but also enhanced the explainability of the underlying hydroclimatic processes of glacier mass change reconstruction from GRACE and GRACE-FO data in the UYW. This automated XML framework is applicable globally, contingent upon sufficient high-quality data for model training and validation.

Wave propagation in an ocean site is an essential research topic in various scientific fields, such as offshore geotechnical engineering, ocean seismology, and underwater acoustics. Previous studies have considered the seabed soil as elastic or poroelastic, ignoring the viscoelastic characteristics of its solid skeleton. Based on the fractional-derivative viscoelastic theory and the modified Biot theory, considering the flow-independent viscosity related to solid skeleton, this paper proposes a generalized viscoelastic wave equation for a fluid-saturated porous medium. The equation has a flexible mathematical form to describe soil rheological properties more accurately through fractional order. On this basis, the total wave field equation of an ocean site, modeled as the fluid-poroviscoelastic-solid media, is established. Then an analytical solution for wave propagation in an ocean site subjected to obliquely incident P and SV waves is obtained, and its degeneration and extension are studied. The proposed method is comprehensively validated through experiment, analytical, and numerical methods. Finally, a parameter analysis is performed to investigate the effects of water depth, seabed properties (including viscoelastic parameters, fractional order and permeability), and incident angle on the seismic response of a poroviscoelastic seabed.

Liquefaction and shear sliding (i.e., slides) are common failure modes of cohesionless seafloor under ocean waves. However, existing research has rarely focused on shear-sliding failure, especially when considering wave- induced residual pore water pressure. Additionally, the relationship between shear-sliding failure and liquefaction is not well understood. In this study, a slice method is developed to assess the shear-sliding failure in cohesionless seafloor under non-linear waves, incorporating the effect of both oscillatory and residual seabed responses. The applicability of various liquefaction criteria is discussed, based on the interrelation between the shear-sliding and liquefaction zones. The results indicate that the seabed soil is more prone to shear-sliding failure than liquefaction under wave-induced pore water pressure. When only oscillatory pore water pressure is considered, the liquefaction criteria, assuming the initial vertical effective stress vanishes due to the excess pore water pressure, better identify the liquefaction zone, which is enveloped by and overlaps with the shear- sliding zone at a factor of safety of zero. In cases where both oscillatory and residual pore pressure coexist, the unified liquefaction criterion, which also assumes onset of liquefaction at zero vertical effective stress, provides more reliable predictions of the liquefaction zone. As residual pore pressure accumulates, the difference between shear sliding and liquefaction depths becomes more pronounced. A sensitivity analysis of shear-sliding depth with varying soil parameters indicates that relative density exerts the most significant influence, followed by the effective internal friction angle, while the shear modulus has the least effect. The effect of variations in soil parameters on shear-sliding depth diminishes to some extent with prolonged wave action.

Estimating the landscape and soil freeze-thaw (FT) dynamics in the Northern Hemisphere (NH) is crucial for understanding permafrost response to global warming and changes in regional and global carbon budgets. A new framework for surface FT-cycle retrievals using L-band microwave radiometry based on a deep convolutional autoencoder neural network is presented. This framework defines the landscape FT-cycle retrieval as a time-series anomaly detection problem, considering the frozen states as normal and the thawed states as anomalies. The autoencoder retrieves the FT-cycle probabilistically through supervised reconstruction of the brightness temperature (TB) time series using a contrastive loss function that minimizes (maximizes) the reconstruction error for the peak winter (summer). Using the data provided by the Soil Moisture Active Passive (SMAP) satellite, it is demonstrated that the framework learns to isolate the landscape FT states over different land surface types with varying complexities related to the radiometric characteristics of snow cover, lake-ice phenology, and vegetation canopy. The consistency of the retrievals is assessed over Alaska using in situ observations, demonstrating an 11% improvement in accuracy and reduced uncertainties compared to traditional methods that rely on thresholding the normalized polarization ratio (NPR).

Coral soil in large quantities of islands has been used for the construction of islands with the development of global marine construction projects. At present, the research on the macro and micromechanical behavior of coral soil during loading is insufficient, which is related to the development of marine engineering. Using the self-developed high-pressure geotechnical CT-triaxial apparatus, the consolidated drained triaxial tests were conducted on coral gravel under confining pressures ranging from 200 to 800 kPa, all the while employing realtime CT scanning to monitor the sample's deformation. The deformation, particle breakage, and porosity of coral gravel could be directly observed by CT images and its post-processing. The results show that the stress-strain relationship of the samples is strain hardening. Notably, particle breakage during consolidation predominantly manifests as corner breakoff, whereas shearing processes primarily induce splitting. The relative breakage Br is not only approximately linear with the average coordination number C-N of particles, but also with the logarithm of average particle size d, porosity n, and local strain s. Observing the evolution of the sample during loading, the increase of confining pressures leads to the decrease of the sample porosity, resulting in a diminishment in pore dimensions, a densification of particle packing, and the increase of contacts between particles. Consequently, this induces particle breakage and continuous volumetric contraction, thus the stress-strain relationship is hardening. The reciprocal influence between macroscopic and microscopic mechanics manifests in coral gravel. The experimental findings could provide valuable insights for marine engineering construction.

The soil moisture active passive (SMAP) satellite mission distributes a product of CO2 flux estimates (SPL4CMDL) derived from a terrestrial carbon flux model, in which SMAP brightness temperatures are assimilated to update soil moisture (SM) and constrain the carbon cyclemodeling. While the SPL4CMDL product has demonstrated promising performance across the continental USA and Australia, a detailed assessment over the arctic and subarctic zones (ASZ) is still missing. In this study, SPL4CMDL net ecosystem exchange (NEE), gross primary production (GPP), and ecosystem respiration (R-E) are evaluated against measurements from 37 eddy covariance towers deployed over the ASZ, spanning from 2015 to 2022. The assessment indicates that the NEE unbiased root-mean-square error falls within the targeted accuracy of 1.6 gC.m(-2).d(-1), as defined for the SPL4CMDL product. However, modeled GPP and R-E are overestimated at the beginning of the growing season over evergreen needleleaf forests and shrublands, while being underestimated over grasslands. Discrepancies are also found in the annual net CO2 budgets. SM appears to have a minimal influence on the GPP and R-E modeling, suggesting that ASZ vegetation is rarely subjected to hydric stress, which contradicts some recent studies. These results highlight the need for further carbon cycle process understanding and model refinements to improve the SPL4CMDL CO2 flux estimatesover the ASZ.

Copper, a malleable and ductile transition metal, possesses two stable isotopes. These copper isotopic composition data have recently found diverse applications in various fields and disciplines. In geology, copper isotopes serve as tracers that aid in investigating ore formation processes and the mechanisms of copper deposits Likewise, it has emerged as a valuable tracer in polluted environments. In plant biology, copper acts as an essential micronutrient crucial for photosynthesis, respiration, and growth. Copper isotopes contribute to understanding how plants uptake and dispense copper from the soil within their tissues. Similarly, in animals, copper serves as an essential trace element, playing a vital role in growth, white blood cell function, and enzyme activity. In humans, copper acts as an antioxidant, neutralising harmful free radicals within the body. It also helps in maintaining the nervous and immune system. Furthermore, copper isotopes find medical applications, particularly in cancer diagnostics, neurodegenerative diseases, and targeted radiotherapy. However, excessive copper can have detrimental effects in humans such as it can cause liver damage, nausea, and abdominal pain, whilst in plants it can affect the growth of plants, photosynthesis, and membrane permeability. This review emphasises the significance of copper and its isotopes in geology, the environment, and human health.

The SCATSAT-1 (Scatterometer Satellite) was launched by ISRO (Indian Space Research Organisation) on September 26, 2016 from the Satish Dhawan Space Centre, Sriharikota, India. With nearly five years of its journey, the Ku-band (13.5 GHz) based SCATSAT-1 made a profound impact on many scientific domains such as ocean-atmosphere dynamics, soil moisture and vegetation dynamics, climate change, hydrology and polar sea-ice and snowmelt studies. As a successor of the Oceansat-2 Scatterometer (OSCAT), the SCATSAT-1 supports the long-term analysis in climate studies, crop yield prediction, and forecasting analysis. In addition, the SCATSAT-1 provides the four different levels of data products at an enhanced resolution to improve the scope of the scatterometer in different applications. Recently the SCATSAT-1 has been explored in many emerging applications apart from oceanography e.g., crop growth, snow cover analysis, jute crop detection and river level estimation with advanced algorithms i.e., machine learning-based classification, information fusion, and super-resolution mapping. Therefore, it is desired to summarise all operational SCATSAT-1 products, applications, and their emerging trends at the global level in the various scientific domains. This paper has summarized the progress made by SCATSAT-1 in different scientific domains since its launch. A meta-analysis has also been conducted in this paper (using the SCOPUS database) to analyse the current research status of SCATSAT-1 in terms of study area targets. This study highlights the features, challenges, and future directions for the scatterometer improvements.

Calcareous sand is a favored unbound granular fill-in island project where complicated stresses are often applied. Traffic and ocean loadings are frequent in praxis, but poorly understood about the normalization of the pore pressure for both. This paper deals with an experimental simulation study on the pore pressure of calcareous sand subjected to ocean waves, traffic, and cyclic loading. Particular attention is devoted to the effect of the initial shear stress and the dynamic stress ratio (CSR). Results showed that, owing to the features of traffic loading and initial shear stress, the soil skeleton can still withstand partial external loading when reaching the failure criterion, hence the pore pressure at failure(ruf) is much smaller than liquefaction. In terms of the influence mechanism, unlike the initial shear stress, the increase in CSR accelerates the destruction of the soil skeleton, reducing the ruf, but having less effect on the critical pore pressure. Expressions for the number of cycles at failure (Nf) and ruf were obtained and the exponential model was simplified by changing N/Nf to epsilon 1/0.05 to reflect the characteristics of traffic loading. To normalize the pore pressure under different loadings, each stress component on Nf and ruf has been analyzed and the noteworthy finding is that torque has a very minor impact on the soil skeleton. Based on this finding, a new normalization method was proposed in which Nf needs to combine all loads including torque, while ruf only needs to consider axial forces. Hence, a pore pressure equation under three different loadings was established, taking into account the role of CSR and the initial shear stress.

Charge distribution measurements are required to understand the spatiotemporal distribution of the number concentrations of submicron atmospheric particles that affect radiative forcing and particle deposition in human airways. The number concentrations of non -charged and charged particles within the 0.3-0.5 pm diameter (D) range were measured at Keio University in Yokohama, Japan, from June 2022 to January 2023 by combining a parallel -pate particle separator and optical particle counters to investigate critical parameters controlling the charging state of submicron atmospheric particles. The measurement uncertainties in the average charge number per particle (pave) and the standard deviation (1 sigma), derived from the charge distribution of the submicron particles, were within 15%. The monthly median values of 1 sigma increased in summer and decreased in winter and correlated with the water vapor amount and wind speed. The 1 sigma values in summer and winter, derived from the seasonally averaged charge distributions of particles, were close to those from the theoretically calculated charge distribution of particles within 0.387-0.5 pm D range and with D = 0.3 pm, respectively, suggesting that the observed particle charge distributions approached the stationary charge distribution for the effective D. In summer, the frequent transport of water molecules and ions from the Pacific Ocean causes efficient collisions between multiple ions and submicron particles with a larger effective D, which may expand the charge distribution of particles. The polarity ratio, the concentration of positively charged particles relative to that of negatively charged particles, was almost unity, indicating the well-balanced charge polarity of the submicron atmospheric particles. The polarity ratio and pave changed significantly during lightning events, indicating that the atmospheric particle charge balance broke. Our findings show that the charge distribution of submicron atmospheric particles can be partly controlled by meteorological parameters (e.g., absolute humidity) and the microphysical properties of the particles.