Search Results (2,209)

Precise characterization of the thermospheric neutral wind is essential for comprehending the dynamic interactions within the ionosphere-thermosphere system, as evidenced by the development of models like HWM and the need for localized data. However, numerical models often suffer from biases due to uncertainties in external forcing and the scarcity of direct wind observations. This study examines the influence of incorporating actual neutral wind profiles from the Michelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) on the Ionospheric Connection Explorer (ICON) satellite into the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIE-GCM) via an ensemble-based data assimilation framework. To address the challenges of assimilating real observational data, a robust background check Quality Control (QC) scheme with dynamic thresholds based on ensemble spread was implemented. The assimilation performance was evaluated by comparing the analysis results against independent, unassimilated observations and a free-running model Control Run. The findings demonstrate a substantial improvement in the precision of the thermospheric wind field. This enhancement is reflected in a 45–50% reduction in Root Mean Square Error (RMSE) for both zonal and meridional components. For zonal winds, the system demonstrated effective bias removal and sustained forecast skill, indicating a strong model memory of the large-scale mean flow. In contrast, while the assimilation exceptionally corrected the meridional circulation by refining the spatial structures and reshaping cross-equatorial flows, the forecast skill for this component dissipated rapidly. This characteristic of “short memory” underscores the highly dynamic nature of thermospheric winds and emphasizes the need for high-frequency assimilation cycles. The system required a spin-up period of approximately 8 h to achieve statistical stability. These findings demonstrate that the assimilation of data from ICON/MIGHTI satellites not only diminishes numerical inaccuracies but also improves the representation of instantaneous thermospheric wind distributions. Providing a high-fidelity dataset is crucial for advancing the modeling and understanding of the complex interactions within the Earth’s ionosphere-thermosphere system. Full article

Recurrent flooding poses a persistent and growing threat to West African watersheds facing rapid urbanization and climate change. Despite advances in machine learning and geospatial datasets, urban planning and flood prevention often rely on limited datasets and traditional analysis. This study addresses this research gap in the Bonoumin-Palmeraie watershed (Abidjan, Côte d’Ivoire) by developing an integrated approach leveraging remote sensing, Geographic Information Systems (GIS), and the Random Forest algorithm to assess and map flood susceptibility. Twelve conditioning factors related to topography, hydrology, land use, and climate were derived from Sentinel-1, ALOS PALSAR, and multi-source earth observation datasets. Historical flood extents were mapped in Google Earth Engine to train the Random Forest model in a Google Colab environment. The model demonstrated high discriminatory power, yielding an Area Under the Curve of 0.94 and Overall Accuracy of 0.83. Drainage density, rainfall, and altitude were identified as the primary explanatory drivers. The resulting flood susceptibility map indicates that 39% of the watershed exhibits medium to very high susceptibility, with critical hotspots in the neighborhoods of Palmeraie, Attoban, Akouedo, Djorogobité, and Riviera-Sogefiha. While limited by the exclusion of certain anthropogenic variables and ground truth constraints, the study provides a reproducible, data-driven framework for flood risk assessment in tropical urban environments. These findings offer essential scientific support for urban planners and decision-makers to enhance territorial planning and sustainable flood management in Abidjan. Full article

An extended operational space kinematics and dynamics formulation is presented for the control of redundant non-serial compound robotic manipulators. A broad spectrum of high-load-capacity non-serial manipulators used in earth moving, material handling, and construction applications is addressed. Departing from conventional approaches that rely on Jacobian pseudoinverses and local null-space projections, a globally valid, differential-geometry-based, multi-valued inverse kinematic mapping is defined at the configuration level, with the explicit self-motion parameterization of manipulator redundancy. The formulation yields coupled second-order ordinary differential equations of manipulator dynamics on the product space of task variables and self-motion coordinates. This enables the direct integration of system dynamics with control strategies, such as model predictive control or feedback design, while maintaining task constraint compliance. The methods presented are validated through the simulation and control of a non-serial compound material loader manipulator with multiple degrees of redundancy, demonstrating advantages in generality, numerical accuracy, and trajectory smoothness. Full article

Parabolic cylindrical antennas are characterized by their structural simplicity, high radiation efficiency, and low manufacturing costs. Consequently, they are widely used in Earth observation and serve as a viable option for spaceborne Synthetic Aperture Radar (SAR) systems. However, structural errors in the phased array feed and the parabolic cylindrical reflector are inevitable during manufacturing, assembly, and operation. These errors significantly degrade the accuracy of antenna pattern models. To address this issue, this paper proposes a comprehensive radiation pattern model that accounts for structural errors in both the linear feed and the reflector. This approach enables precise pattern prediction and efficient in-orbit calibration. Specifically, the reflected far-field pattern is first calculated using the field superposition principle and the Physical Optics (PO) method. Specifically, the combined phase effects resulting from feed and reflector structural errors are superimposed to establish a direct integration pattern model for the parabolic cylindrical antenna. Given the high computational complexity of the direct integration model, a simplified model based on Fresnel approximation is proposed. This approach significantly reduces integration complexity while preserving the quadratic phase characteristics of the main lobe, thereby substantially improving computational efficiency. Simulation results verify that the simplified model maintains high accuracy in both normalized amplitude and phase. Furthermore, a partitioned calibration method is proposed to compensate for the absolute gain deviation inherent in the simplified model. By integrating weighting relationships derived from sensitivity analysis of individual errors, an empirical parameter is defined to quantify the correlation between total structural errors, antenna performance, and the prediction accuracy of the simplified model. The results indicate that reflector structural errors are the dominant factor affecting the overall performance of the antenna. In contrast, the prediction accuracy of the simplified model is found to be more sensitive to feed structural errors. The simplified model exhibits tolerance to structural errors far exceeding the wavelength, enabling it to effectively replace the direct integration model. This work provides new theoretical foundations and technical methods for tolerance design, performance assurance, in-orbit testing, and calibration of parabolic cylindrical antennas. Full article

Recently, unmanned aerial vehicles (UAVs) based on electric propulsion systems are being increasingly adopted in various fields, including industrial and military applications. Outer-rotor surface-mounted permanent magnet synchronous motors (SPMSMs) are predominantly applied in UAV propulsion systems. However, these motors are vulnerable to the price fluctuations of rare-earth materials and supply chain instability. In addition, the magnets in these motors are prone to detachment at high rotational speeds, and demagnetization under high-temperature conditions may reduce output performance. To address these limitations, research is being actively conducted on non-permanent magnet motors, among which, wound-rotor synchronous motors (WRSMs) offer the advantage of controllable field excitation at high speeds. Furthermore, WRSMs can use both magnetic and reluctance torques, thereby increasing power density relative to other non-permanent magnet motors. However, the adoption of an additional field winding increases copper loss, thus reducing motor efficiency. This study investigates the application of the toroidal winding structure, which is already widely applied in permanent magnet and brushless direct current machines, to WRSMs. The performance of these motors is compared with that of motors using conventional tooth-coil windings. The toroidal windings are circumferentially distributed along both the inner and outer stator yoke paths, effectively reducing the end-turn length relative to that of conventional tooth-coil windings. Two WRSMs, one with tooth-coil and another with toroidal windings, are designed using identical specifications to compare performances via finite element analysis. The armature copper loss in the proposed model decreased by approximately 28% because the toroidal winding structure reduced the end-turn length. As a result, the efficiency increased by about 1.9% due to the reductions in copper, core, and eddy current losses. Full article

Mixed-phase clouds, in which liquid droplets and ice crystals coexist at temperatures between $-38{}^{\circ }$C and $0{}^{\circ }$C, play a critical role in Earth’s radiation budget. Here, we assess the ability of climate and storm-resolving models to represent mixed-phase cloud properties and their hemispheric contrasts as inferred from satellite observations. We compare observations from the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) with one global climate model, the Community Atmosphere Model version 6, Oslo configuration (CAM6-Oslo), and three storm-resolving models: the ICOsahedral Non-hydrostatic model (ICON), the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM), and the Goddard Earth Observing System model (GEOS). Our results show that all models reproduce the geographic distribution of mixed-phase clouds but differ significantly in detail. CAM6-Oslo yields the closest agreement in hemispheric contrasts of supercooled liquid fraction and its relationship with the liquid effective radius. Our results highlight the role of aerosol–cloud interactions and microphysics schemes in determining model performance and demonstrate that storm-resolving models still do not overcome the challenge of representing mixed-phase clouds at global scales. Full article

The farmland protection compensation system plays a pivotal role in addressing the dual global crises of food insecurity and ecological degradation, as well as in overcoming persistent challenges in China’s agricultural governance. By internalizing the opportunity costs borne by stakeholders fulfilling statutory obligations for farmland protection, this mechanism offers effective incentives for their active engagement, thereby establishing a societal-level interest-balancing framework conducive to sustainable land management. Existing research in China has mainly concentrated on empirical analyses of implementation models, regional disparities, and policy effectiveness evaluations of farmland protection compensation schemes. Nevertheless, systematic exploration of the normative construction and improvement pathways of the compensation rules themselves remains relatively underdeveloped. Based on the practical requirements and institutional constraints of China’s current farmland protection compensation regime, this study adopts an integrated approach that combines comparative legal analysis, textual review of regulatory documents, and empirical research to critically examine feasible paths for institutional improvement. The research findings emphasize that the optimization of China’s farmland protection compensation rules should be guided by three core principles: market orientation, ecological sustainability, and precision-based targeting. Specifically, the establishment of scientifically sound methods for calculating compensation amounts is crucial for reconciling the interests of conservation actors with inter-regional development disparities. Meanwhile, the compensation mechanism should be strategically utilized to strengthen positive incentives for ecosystem conservation. Ultimately, such institutional improvement aims to ensure the sustainable utilization of farmland resources while safeguarding global food security and maintaining the Earth’s ecological balance. Full article

Problem Statement: Two global trends, including aging populations and the acceleration of global warming, are increasing the risk of heat-related illness, challenging the health of populations, and the sustainability of healthcare systems. Global warming refers to the increase in the Earth’s average surface temperature, generally attributed to the greenhouse effect, which is occurring at three times the rate of the pre-industrial era. The global population of older adults, defined here as individuals aged 60 and over, is expected to reach over 2 billion by mid-century. This population is particularly vulnerable to heat-related illness, specifically disruption of thermoregulation from excessive exposure to environmental heat due to metabolic and cognitive changes associated with aging. Objectives: This review examines heat-related illness and its impact on older adults within a socio-ecological framework, considering both drivers and mitigation strategies related to global warming, the built environment, social determinants of health, healthcare system responses, and the individual. The authors were motivated to create a conceptual model within this framework drawing on their lived experiences as healthcare providers interacting with older adults in a large urban area of the southwestern US, known for its extreme heat and extensive heat island effects. Based on this framework, the authors suggest actionable strategies supported by the literature to reduce the risks of morbidity and mortality. Methods: The literature search utilized a wide lens to identify evidence supporting various aspects of the hypothesized framework. In this sense, this review differs from systematic and scoping reviews, which seek a complete synthesis of the available literature or a mapping of the evidence. The first author conducted the literature search and synthesis, while the second and third authors reviewed and added publications to the initial search and conceptualized the socio-ecological framework. Discussion: This study is unique in its focus on a global trend that threatens the well-being of a growing population. The population health focus underscores social determinants of health and limitations of existing healthcare systems to guide healthcare providers in reducing older adults’ vulnerability to heat-related illness. This includes patient education regarding age-related declines in extreme heat tolerance, safe and unsafe physical activity habits, the impact of prescription drugs on heat tolerance, and, importantly, identifying the symptoms of heatstroke, which is a medical emergency. Additional strategies for improving survivability and quality of life for this vulnerable population include improved emergency response systems, better social support, and closer attention to evidence-based treatment for heat-related health conditions. Full article

Kazakhstan, located in Central Asia, is experiencing faster warming than the global trend, making it an important region regarding the study of how climate change is affecting climatic zones. This research aims to identify projected shifts in Köppen–Geiger climate zones under high-emission Shared Socioeconomic Pathway (SSP) 5-8.5 climate scenarios. The Köppen–Geiger climate classification system is a practical tool that effectively captures climate types based on just two variables: temperature and precipitation. Monthly temperature and precipitation data from Climatic Research Unit (CRU,) ERA5-Land, and Coupled Model Intercomparison Project Phase 6 (CMIP6) ensembles from 1951 to 2100 were used to generate climatic zone maps. CMIP6 models were evaluated against meteorological station data and ERA5-Land, with bias metrics used to identify the best-performing models for temperature and precipitation in Kazakhstan. Based on these results, two inter-model datasets were developed and used to generate Köppen–Geiger climate maps for high-emission scenarios for the 2061–2100 time period. This research resulted in two key outcomes. First, to facilitate this analysis, a Google Earth Engine (GEE) application was developed as an open accessible tool for dynamic visualization of Köppen–Geiger climate maps. Second, projected maps based on CMIP6 SSP5-8.5 scenario projections indicate that southern Kazakhstan may shift to BSh (Hot Semi-Arid) and Csa (Mediterranean) climates, and the southwest region of the country is projected to shift to a BWh (Hot Desert) climate. These projected Köppen–Geiger climate maps contributed to climate adaptation efforts by identifying regions at risk of desertification and aridification. This study provides a comprehensive analysis of climate zone transformations in Kazakhstan and offers a practical scalable geovisualization tool for monitoring climate change impacts. This allows users easy access to climate-related information and insights into data processing procedures. Full article

The identification of non-circular critical slip surfaces in slopes using metaheuristic algorithms remains a frontier challenge in geotechnical engineering. Such approaches are particularly effective for assessing the stability of heterogeneous slopes, including earth dams. This study introduces ODACO, a comprehensive program developed to determine the optimum cross-section of earth dams with berms. The program employs the Max–Min Ant System (MMAS), one of the most robust variants of the ant colony optimization algorithm. For each candidate cross-section, the critical slip surface is first identified using MMAS. Among the stability-compliant alternatives, the configuration with the most efficient shell geometry is then selected. The optimization process is conducted automatically across all loading conditions, incorporating slope stability criteria and operational constraints. To ensure that the optimized cross-section satisfies seismic performance requirements, an artificial neural network (ANN) model is applied to rapidly and reliably predict seismic responses. These ANN-based predictions provide an efficient alternative to computationally intensive dynamic analyses. The proposed framework highlights the potential of optimization-driven approaches to replace conventional trial-and-error design methods, enabling more economical, reliable, and practical earth dam configurations. Full article

Water resource monitoring can provide beneficial information supporting water management; however, present operational systems are small and provide only a subset of the information needed. Primary advancements consist of the clear explanation of water redistribution and water use from groundwater and river schemes, achieving better spatial detail and increased precision as evaluated against hydrometric observation. In such cases, Earth Observation (EO) satellite systems are persistently creating extensive data, which is now essential for applications in different fields. With readily available open-source satellite imagery, aerial remote sensing is progressively becoming a quick and efficient tool for monitoring land and water resource development actions, demonstrating time and cost savings. At present, the deep learning (DL) model will be beneficial for monitoring water resources and EO utilizing remote sensing. In this paper, a Deep Neural Network-Based Object Detection for Water Resource Monitoring and Earth Observation (DNNOD-WRMEO) model is introduced. The main intention is to develop an effective monitoring and analysis framework for water resources and Earth surface observations using aerial remote sensing images. Initially, the Wiener filter (WF) model was used for image pre-processing. For object detection, the Yolov12 method was used for identifying, locating, and classifying objects within an image, followed by the DNNOD-WRMEO methodology, which implements the ResNet-CapsNet model for the backbone feature extraction method. Finally, the temporal convolutional network (TCN) model was implemented for the classification of water resources. The comparison analysis of the DNNOD-WRMEO methodology exhibited a superior accuracy value of 98.61% compared with existing models under the AIWR dataset. Full article

In recent years, the rapid development of commercial satellite projects, such as low-Earth orbit (LEO) communication and remote sensing constellations, has driven the satellite industry toward low-cost, rapid development, and large-scale deployment. Commercial off-the-shelf (COTS) components have been widely adopted across various commercial satellite platforms due to their advantages of low cost, high performance, and plug-and-play availability. However, the space environment is complex and hostile. COTS components were not originally designed for such conditions, and they often lack systematically flight-verified protective frameworks, making their reliability issues a core bottleneck limiting their extensive application in critical missions. This paper focuses on COTS solid-state drives (SSDs) onboard the Jilin-1 KF satellite and presents a full-lifecycle reliability practice covering component selection, system design, on-orbit operation, and failure feedback. The core contribution lies in proposing a full-lifecycle methodology that integrates proactive design—including multi-module redundancy architecture and targeted environmental stress screening—with on-orbit data monitoring and failure cause analysis. Through fault tree analysis, on-orbit data mining, and statistical analysis, it was found that SSD failures show a significant correlation with high-energy particle radiation in the South Atlantic Anomaly region. Building on this key spatial correlation, the on-orbit failure mode was successfully reproduced via proton irradiation experiments, confirming the mechanism of radiation-induced SSD damage and providing a basis for subsequent model development and management decisions. The study demonstrates that although individual COTS SSDs exhibit a certain failure rate, reasonable design, protection, and testing can enhance the on-orbit survivability of storage systems using COTS components. More broadly, by providing a validated closed-loop paradigm—encompassing design, flight verification and feedback, and iterative improvement—we enable the reliable use of COTS components in future cost-sensitive, high-performance satellite missions, adopting system-level solutions to balance cost and reliability without being confined to expensive radiation-hardened products. Full article

The Weishan rare earth element (REE) deposit, located in western Shandong, North China Block, is a typical carbonatite REE deposit and constitutes the third largest light REE resource in China. Its mineralization is closely related to the multi-stage evolution of a carbonatite magma–hydrothermal system. However, the mechanisms governing REE enrichment, migration, and precipitation remain insufficiently constrained from a mineralogical perspective, which hampers the understanding of the ore-forming processes and the establishment of predictive exploration models. Apatite is a pervasively developed REE phase in the Weishan deposit which occurs in multiple generations, and thus represents an ideal recorder of the magmatic–hydrothermal evolution. In this study, different generations of apatite hosted in carbonatite orebodies from the Weishan deposit were investigated using cathodoluminescence (CL), electron probe microanalysis (EPMA), and in situ LA-ICP-MS trace element analysis. Three types of apatite were identified. In paragenetic sequence, Ap-1 occurs as polycrystalline aggregates coexisting with calcite, is enriched in Na, Sr, and LREEs, and shows high (La/Yb)_N ratios, suggesting crystallization from an evolved carbonatite magma. Ap-2 and Ap-3 display typical replacement textures: both contain abundant dissolution pits and dissolution channels within the grains, which are filled by secondary minerals such as monazite and ancylite, and thus exhibit characteristic features of fluid-mediated dissolution–reprecipitation during the hydrothermal stage. Ap-2 is commonly associated with barite and strontianite, whereas Ap-3 is associated with pyrite and monazite and is characterized by relatively sharp grain boundaries with adjacent minerals. From Ap-1 to Ap-3, total REE contents decrease systematically, whereas Na, Sr, and P contents increase. All three apatite types lack Eu anomalies but display positive Ce anomalies. Discrimination diagrams involving LREE-Sr/Y and log(Ce)-log(Eu/Y) indicate that apatite in the Weishan REE deposit formed during the magmatic to hydrothermal evolution of a carbonatite, and that the dissolution of early magmatic apatite, followed by element remobilization and mineral reprecipitation, effectively records the progressive evolution of the ore-forming fluid. Full article

Aerospace power systems, including satellites in low earth orbit (LEO) and geostationary earth orbit (GEO), face stringent thermal constraints to minimize size, weight, and power (SWaP). Gallium nitride (GaN) devices offer superior radiation hardness—critical for the harsh space environment—and MHz-level switching capabilities. This high-frequency operation minimizes passive components, particularly magnetics, thereby reducing the overall volume. However, above 10 MHz, magnetic cores become impractical due to material limitations. To address these issues, this article proposes a design methodology for a GaN-based quasi-square-wave (QSW) buck converter integrated with a PCB air-core inductor. First, the impact of the switching frequency and dead time on the zero-voltage switching (ZVS) condition is elaborated. Then, a power loss model accounting for various loss mechanisms is presented. To overcome high GaN body diode reverse conduction loss, an auxiliary diode is employed. Based on the model, a design procedure is developed to optimize the inductor for 10 MHz operation while maximizing efficiency. To validate the design, a 28 V/12 V, 18 W prototype was built and tested. Experimental results demonstrate a peak efficiency of 86.5% at 10 MHz. The auxiliary diode improves efficiency by 4%, verifying reverse conduction loss mitigation. Thermal analysis confirms a full-load case temperature of 62.2 °C, providing a 47.8 °C safety margin compliant with aerospace derating standards. These findings validate the solution for high-frequency, space-constrained aerospace applications. Full article

The six platinum group elements (PGE) are among the rarest elements in the upper continental crust of the earth. Higher values of PGE have been detected in the upper mantle and in chondrite meteorites. The PGE are siderophile and chalcophile elements and are divided into the following: (1) the Ir subgroup (IPGE) = Os, Ir, and Ru and (2) the Pd subgroup (PPGE) = Rh, Pt, and Pd. The IPGE are more refractory and less chalcophile than the PPGE. High concentrations of PGE led, in rare cases, to the formation of mineral deposits. The PGE are carried in discrete phases, the platinum group minerals (PGM), and are included as trace elements into the structure of base metal sulphides (BM), such as pentlandite, chalcopyrite, pyrite, and pyrrhotite. Similarly to PGE, the PGM are also divided into two main groups, i.e., IPGM composed of Os, Ir, and Ru and PPGM containing Rh, Pt, and Pd. The PGM occur both in mafic and ultramafic rocks and are mainly hosted in stratiform reefs, sulphide-rich lenses, and placer deposits. Presently, there are only 169 valid PGM that represent about 2.7% of all 6176 minerals discovered so far. However, 496 PGM are listed among the valid species that have not yet been officially accepted, while a further 641 are considered as invalid or discredited species. The main reason for the incomplete characterization of PGM resides in their mode of occurrence, i.e., as grains in composite aggregates of a few microns in size, which makes it difficult to determine their crystallography. Among the PGM officially accepted by the IMA, only 13 (8%) were discovered before 1958, the year when the IMA was established. The highest number of PGM was discovered between 1970 and 1979, and 99 PGM have been accepted from 1980 until now. Of the 169 PGM accepted by the IMA, 44% are named in honour of a person, typically a scientist or geologist, and 31% are named after their discovery localities. The nomenclature of 25% of the PGM is based on their chemical composition and/or their physical properties. PGM have been discovered in 25 countries throughout the world, with 64 from Russia, 17 from Canada and South Africa (each), 15 from China, 12 from the USA, 8 from Brazil, 6 from Japan, 5 from Congo, 3 from Finland and Germany (each), 2 from the Dominican Republic, Greenland, Malaysia, and Papua New Guinea each, and only 1 from Argentine, Australia, Bulgaria, Colombia, Czech Republic, England, Ethiopia, Guyana, Mexico, Serbia, and Tanzania each. Most PGM phases contain Pd (82 phases, 48% of all accepted PGM), followed, in decreasing order of abundances, by those of Pt 35 phases (21%), Rh 23 phases (14%), Ir 18 phases (11%), Ru 7 phases (4%), and Os 4 phases (2%). The six PGE forming the PGM are bonded to other elements such as Fe, Ni, Cu, S, As, Te, Bi, Sb, Se, Sn, Hg, Ag, Zn, Si, Pb, Ge, In, Mo, and O. Thirty-two percent of the 169 valid PGM crystallize in the cubic system, 17% are orthorhombic, 16% hexagonal, 14% tetragonal, 11% trigonal, 3% monoclinic, and only 1% triclinic. Some PGM are members of a solid-solution series, which may be complete or contain a miscibility gap, providing information concerning the chemical and physical environment in which the mineral was formed. The refractory IPGM precipitate principally in primitive, high-temperature, mantle-hosted rocks such as podiform and layered chromitites. Being more chalcophile, PPGE are preferentially collected and concentrated in an immiscible sulphide liquid, and, under appropriate conditions, the PPGM can precipitate in a thermal range of about 900–300 °C in the presence of fluids and a progressive increase of oxygen fugacity (fO₂). Thus, a great number of Pt and Pd minerals have been described in Ni-Cu sulphide deposits. Two main genetic models have been proposed for the formation of PGM nuggets: (1) Detrital PGM represent magmatic grains that were mechanically liberated from their primary source by weathering and erosion with or without minor alteration processes, and (2) PGM reprecipitated in the supergene environment through a complex process that comprises solubility, the leaching of PGE from the primary PGM, and variation in Eh-pH and microbial activity. These two models do not exclude each other, and alluvial deposits may contain contributions from both processes. Full article