TerraMosaic Daily Digest: Feb 1, 2026
Daily Summary
This digest synthesizes 62 selected papers and focuses on seismic source-to-ground response pathways, landslide process mechanics and slope evolution, infrastructure-focused hazard performance. Top-ranked studies examine landslide susceptibility mapping, earthquake-triggered slope response and liquefaction, and cryosphere-driven slope and infrastructure instability.
Across the full set, evidence converges on mechanism-constrained analysis with operational relevance, especially for coastal and submarine hydro-geomechanics and flood generation, routing, and hydroclimatic forcing. The strongest contributions pair interpretable process evidence with monitoring or forecasting workflows that support warning design and risk prioritization.
Key Trends
- Seismic hazard research links source behavior to ground response: Recurring topics connect rupture or loading conditions with geotechnical performance and consequence assessment.
- Landslide studies increasingly resolve process chains: Contributions connect triggering conditions, slope deformation, and mobility outcomes, improving the basis for warning thresholds and scenario testing.
- Infrastructure-facing outputs are increasingly decision-ready: Asset performance is evaluated with uncertainty-aware frameworks to support mitigation and maintenance prioritization.
- Coastal and submarine hazards are treated as coupled systems: Wave, mass-transport, and shoreline processes are analyzed together with engineering implications.
- Flood analyses are becoming event-specific and process-based: Papers emphasize precipitation structure, antecedent wetness, and catchment controls rather than static hazard descriptors.
Selected Papers
This digest features 62 selected papers from 565 RSS items analyzed (out of 2244 raw RSS items scanned) across multiple journals. Each paper has been evaluated for its relevance to landslide and broader geohazard research and includes links to the original publications.
1. A comparative study among ensemble and independent statistical models: a high-accuracy and conservative framework for landslide susceptibility mapping in east sikkim himalaya
Core Problem: Developing a precise and conservative Landslide Susceptibility Map (LSM) in the Sikkim Himalaya, and evaluating whether high model accuracy necessarily corresponds with conservative predictions.
Key Innovation: Developed a high-accuracy and conservative LSM for East Sikkim by comparing individual (EBF, FR) and ensemble statistical methods, demonstrating that an ensemble can increase accuracy and highlighting the critical need to evaluate LSM conservativeness alongside accuracy for reliable recommendations.
2. Catena matters: Enhancing landslide prediction with soil profile characteristics and explainable AI
Core Problem: Most machine-learning-based landslide susceptibility models primarily rely on topographic variables, neglecting the critical role of depth-dependent soil profile characteristics, leading to reduced accuracy and overestimation.
Key Innovation: Integrated soil geotechnical and hydrological properties at multiple depths into a Random Forest model with SHAP-based XAI, significantly improving landslide prediction accuracy and interpretability, and highlighting the importance of soil profile characteristics.
3. CFD-DEM simulation of sand liquefaction with non-spherical particles and inherent anisotropic effects
Core Problem: Conventional methods for evaluating sand liquefaction struggle to precisely control granular deposition anisotropy and accurately characterize fluid-non-spherical particle interactions, while CFD-DEM methods face computational efficiency challenges for large-scale simulations.
Key Innovation: An improved CFD-DEM coupling framework incorporating a non-spherical particle model and optimized parameter matching, which efficiently and accurately simulates sand liquefaction, revealing that deposition angle significantly controls liquefaction resistance and providing micro-mechanistic insights for seismic liquefaction risk assessment.
4. Progressive modification of quartz sand under freeze-thaw weathering: Identification of critical particle size
Core Problem: The micro-mechanisms governing grain size and morphology evolution of sandy soils under freeze-thaw cycles, and their implications for geohazards, are insufficiently understood.
Key Innovation: Systematically elucidated the progressive 'coarsening-to-fining' shift and morphological evolution of quartz sand under freeze-thaw, identifying a critical particle size (0.01–0.05 mm) and providing a microstructural basis for improving predictive models of freeze-thaw related geohazards.
5. Effect of ageing on the seismic risk of RC wall–frame buildings under sequential earthquakes and consequences for insurance premiums
Core Problem: The seismic risk of RC wall-frame buildings with deficient structural wall plan density, particularly under combined ageing-induced deterioration and repeated seismic excitation, is not adequately evaluated for risk management and insurance.
Key Innovation: Developed a performance-based framework using nonlinear response-history analyses to quantify the combined influence of corrosion deterioration and sequential ground motions on seismic fragility, vulnerability, and financial risk, providing a novel approach to determine insurance parameters.
6. Wildfire risk assessment of nuclear power plant off-site power systems using human-activity–informed localized inputs: A case study of the Kori nuclear power plant
Core Problem: Conventional wildfire risk assessments for nuclear power plant off-site power systems often rely on generalized input data, leading to imprecise estimations and hindering effective safety policy development.
Key Innovation: Proposed a methodology for wildfire risk assessment using human-activity-informed localized input data (e.g., local wildfire frequency, site accessibility), demonstrating that this approach can substantially change (e.g., decrease by 95%) the estimated annual probability of loss of the off-site power system, enhancing reliability.
7. Cosmogenic 10Be dating of a relict flowslide in the Sudetes (SW Poland) – The first dated pre-Holocene landslide in the region and validation of previous soil investigations
Core Problem: Lack of cosmogenic dates for landslides in the Sudetes region, and a need to validate previous landslide age constraints based on soil distribution and characteristics.
Key Innovation: Provided the first cosmogenic 10Be surface exposure dates for a relict flowslide in the Sudetes (mean ages of 58.5 ± 5.7 ka and 47.0 ± 2.2 ka), confirming two phases of pre-Holocene displacement, validating previous soil investigations, and suggesting that surface roughness can be a proxy for landslide age.
8. Prediction of rock mass energy evolution during deep tunnel construction using static temporal fusion transformer and numerical surrogate model
Core Problem: Rapid and effective prediction of the energy evolution of surrounding rock during TBM tunneling is critical for forecasting potential hazards like rockburst, but current methods often fail to predict specific information like location and time.
Key Innovation: A numerical surrogate model based on a static Temporal Fusion Transformer (TFT) framework, trained with a mixed data and physical loss function, to achieve fast and accurate time series prediction of rock mass energy dissipation rate, providing an early-warning basis for rockbursts in deep tunnels.
9. Failure mechanism of tunnels subjected to stick-slip behavior of reverse fault using centrifuge model tests
Core Problem: Lack of effective simulation of fault stick-slip in large-scale model experiments and insufficient understanding of tunnel failure mechanisms under such conditions.
Key Innovation: Developed a centrifuge-based fault simulator to achieve stick-slip behavior, revealing a three-section tunnel failure mechanism within a trishear deformation zone induced by reverse fault stick-slip, validated by numerical simulations.
10. New Analytical Model for Forecasting Turbidity Current Run‐Up Heights: Implications for Risk Assessment of Seafloor Infrastructure on Submarine Slopes
Core Problem: Existing 2D predictive models for turbidity current run-up heights on submarine slopes significantly underestimate actual run-up, posing risks to seafloor infrastructure.
Key Innovation: A new analytical model for forecasting turbidity current run-up heights that addresses the underestimation of existing models, identifying a critical slope gradient and providing implications for risk assessment of seafloor infrastructure.
11. Investigating the 2021 cross-border flooding in Washington, USA, and British Columbia, Canada and associated influencing factors using multi-type remote sensing
Core Problem: Understanding the 2021 cross-border flooding event in Washington, USA, and British Columbia, Canada, caused by intense atmospheric rivers, and identifying associated influencing factors.
Key Innovation: Investigated the 2021 flooding event and its influencing factors using multi-type remote sensing. (Details are limited due to truncated abstract, but the core contribution is the investigation of a specific flood event using remote sensing.)
12. Analysis of seismic wave scattering characteristics for nearshore site slope terrain with SBFEM
Core Problem: Accurately modeling the seismic response of complex nearshore sites with slope terrain, considering seawater-seabed coupling and local topographic features, to enhance seismic hazard assessment.
Key Innovation: Proposed a time-domain analysis method using SBFEM for nearshore site seismic response, integrating quadtree mesh, open boundaries, and regional reduction to efficiently model seawater-nearshore site systems and investigate influence mechanisms of site characteristics and incident waves.
13. Distributionally robust fairness-based last-mile relief network optimization with casualty uncertainty
Core Problem: The suddenness and uncertainty of casualties in natural disasters necessitate a fair and robust network design for last-mile medical supply distribution and injured evacuation to minimize post-disaster impact.
Key Innovation: Established a distributionally robust chance-constrained model for medical supplies allocation in last-mile relief networks, minimizing worst-case CVaR of supply shortages under scenario-wise casualty uncertainty, demonstrating stronger robustness than traditional models.
14. Instability analysis of circumferential and radial yielding structures in high in-situ stress soft rock tunnels based on polyurethane foam
Core Problem: Traditional rigid support structures are often incapable of accommodating substantial, continuous deformation of surrounding soft rock in high in-situ stress tunnels, leading to structural failure.
Key Innovation: Investigates instability mechanisms of circumferential and radial yielding structures in soft rock tunnels using polyurethane foam, combining experiments, numerical simulations, and physical models, providing guidelines for optimal support selection based on strength-to-stress ratio.
15. Responses and failure characteristics of rock containing a circular hole under multi-path coupled true triaxial loading and unloading
Core Problem: Comprehensively understanding the influence of hole orientation and stress path on the mechanical response and failure characteristics of rock subjected to excavation-induced disturbances.
Key Innovation: Conducts multi-path coupled true triaxial loading and unloading tests on rock specimens with circular holes, revealing that hole orientation significantly affects rock stability and failure modes, and detailing the progressive failure stages under various stress paths.
16. A New Surface Rupture of the 1556 Huaxian M ∼ 8.5 Earthquake Revealed by Rock Surface Luminescence Dating of a Bedrock Fault Scarp and Colluvial Wedges
Core Problem: Accurately constraining coseismic displacement and reconstructing the activity history of the fault responsible for the 1556 Huaxian earthquake.
Key Innovation: Revealing a new surface rupture of the 1556 Huaxian earthquake by incorporating colluvial wedge components and using rock surface luminescence dating of a bedrock fault scarp and colluvial wedges.
17. Time Poverty and Disaster Readiness: How Routine Constraints Shape Hurricane Preparation
Core Problem: The impact of time poverty on hurricane preparation, especially during back-to-back disasters, is under-researched, leading to insufficient preparation and increased safety risks for certain groups.
Key Innovation: Conducted an in-depth investigation using geographically targeted surveys to identify five routine time-poverty profiles, revealing that time-poor caregivers and busy professionals experience greater time stress and complete fewer preparations, highlighting the need for targeted interventions.
18. Comparative assessment of AI-based and classical DSAS approaches in multi-temporal shoreline prediction: A case study of Ras El-Bar coast, Egypt
Core Problem: Traditional shoreline forecasting methods (e.g., DSAS-LRR) fail to capture the highly distinctive non-linear shoreline dynamics and abrupt anthropogenic regime shifts induced by engineering structures along anthropogenically modified coasts.
Key Innovation: This study comparatively assessed DSAS-LRR against AI recurrent neural networks (LSTM, NARX) for multi-decadal shoreline prediction, demonstrating that the intervention-aware NARX model achieved the highest predictive accuracy and spatial consistency (average RMSE 6–14 m), successfully capturing complex temporal responses to human interventions and providing a transferable framework for coastal management.
19. A review of ice accretion, detection, and mitigation methods for the gondola infrastructure application
Core Problem: Lack of a comprehensive reference about ice accretion, ice detection, and mitigation solutions for safe operations of gondola infrastructure, despite its economic and environmental advantages.
Key Innovation: Provides a state-of-the-art scientific literature review on ice accretion, detection, and mitigation methods for gondola infrastructure, identifying scientific and technological knowledge gaps, and mapping suitable techniques to critical gondola components.
20. Blade icing characteristics and dynamic response analysis of floating offshore wind turbine in cold marine environments
Core Problem: Floating offshore wind turbines (FOWTs) operating in cold marine environments must confront atmospheric icing, but there is a need to study blade icing characteristics in operation and the dynamic response of FOWT after icing.
Key Innovation: Simulates blade icing under various operating conditions for FOWTs using CFD and OpenFAST, revealing that operating regions significantly impact ice accretion, leading to power generation loss and potential structural overload due to reduced pitch angle under imbalanced icing.
21. Experimental and numerical study on icing characteristics of integrated wind turbines under operating conditions
Core Problem: The freezing phenomenon of wind turbine blades seriously affects the stability and structural safety of wind turbines, requiring better understanding of icing characteristics under operating conditions.
Key Innovation: Conducts finite element simulation and integrated wind tunnel icing experiments to determine the distribution law of icing positions on wind turbine blades, quantify the effects of liquid water content and temperature on icing rate, thickness, and shape, and validate icing simulation methods for rotating blades.
22. Nonstationary agricultural drought risk under compound meteorological drought and hot conditions
Core Problem: The limitation of existing approaches that assume stationarity in assessing agricultural drought risk, despite the nonstationary and time-varying dependencies among agricultural drought, meteorological drought, and heat extremes under global warming.
Key Innovation: Development of a novel nonstationary vine copula conditional probability model (NVCCP) to quantify nonstationary conditional probability of agricultural drought under compound dry-hot conditions, demonstrating its effectiveness in capturing complex relationships and revealing temporal variability in agricultural drought risks.
23. Coupling of Navier–Stokes and Boussinesq equations based on SPH and finite difference algorithms for wave propagation to breaking
Core Problem: Effectively simulating complex wave phenomena, including propagation, transformation, and breaking, especially when interacting with coastal structures, requires robust numerical models.
Key Innovation: Develops a two-way coupled model combining a Boussinesq model (finite difference) and an SPH model (Navier-Stokes) with a novel two-way open boundary algorithm and multi-time-step strategy to simulate wave propagation and wave-structure interactions, ensuring continuous free-surface evolution and stable fluid pressure.
24. Geospatial mapping of heatwaves and drought: Exploring their link to vegetation, soil moisture, and groundwater in the thirsty Barind Tract, Bangladesh
Core Problem: Understanding the spatiotemporal scrutiny of droughts and heatwaves and their relationship with vegetation, soil moisture, and groundwater levels in the high Barind Tract, Bangladesh.
Key Innovation: Employed a novel methodology combining SPI and LST for geospatial mapping of heatwaves and droughts, revealing a significant increase in their frequency and severity, a robust association between SPI and Groundwater table (GWT) depth, and highlighting the vulnerability of groundwater-based agriculture to extreme events.
25. Interpretation of integrated geophysical data for catchment identification in Western Türkiye (Soma, Manisa)
Core Problem: Identifying geological structures that control groundwater occurrence and flow for sustainable water resources, particularly in catchments, requires comprehensive subsurface hydrological understanding.
Key Innovation: Conducted an integrated geophysical investigation (ERT, DCIP, SP, SRT) in a catchment in Western Türkiye, successfully delineating the catchment, revealing interaction between faults and water discharge points, and identifying a buried fault as the youngest structural element, providing crucial insights for groundwater protection.
26. Research on transmission line icing classification and recognition algorithm based on BiTex-ResNet34
Core Problem: Complex transmission line icing scenarios with limited samples, high similarity between icing types, and a lack of non-contact methods for identifying icing types.
Key Innovation: Proposes BiTex-ResNet34, a dual-branch deep learning algorithm that extracts both raw and texture features of icing images and uses a Second-order Feature Fusion Module to accurately classify rime, hard rime, and soft rime on transmission lines.
27. Vertical and shear stresses at the base of a building on a deformable foundation excited by an incident P-wave pulse: Linear and nonlinear soil
Core Problem: Traditional methods for seismic analysis of structures often assume vertical seismic wave arrival and underestimate base shear and normal forces, especially with nonvertically incident P-waves and nonlinear soil.
Key Innovation: Developed a 2D continuum model to show that nonvertical P-wave incidence and soil nonlinearity lead to significant normal and shear stresses at building base corners, which are underestimated by traditional design methods, highlighting the need for revised computations.
28. Seismic functionality analysis of water distribution network affected by pipeline failure correlations
Core Problem: Existing studies on seismic functionality of WDN with pipeline failure correlations rely on connectivity models, failing to depict energy dissipation and water losses, and often assume independent pipeline failures.
Key Innovation: Proposed a framework for seismic functionality assessment of WDN using hydraulic simulation, accounting for spatial correlated ground motion and pipeline failure correlations, demonstrating that correlated failures lead to higher functionality than independent assumptions.
29. On the Role of Sea Surface Temperature in the 16 April 2024 Rainstorm Over the United Arab Emirates
Core Problem: Understanding the contributing factors, specifically the role of sea surface temperature, in the record-breaking 16 April 2024 rainstorm over the United Arab Emirates.
Key Innovation: Demonstrating through sensitivity experiments that anomalously warm sea surface temperatures in the Arabian Sea and nearby gulfs significantly contributed to the extreme rainfall event.
30. Three-dimensional longitudinal dynamic response of large diameter pipe piles considering the soil plug effect
Core Problem: Previous models for pipe pile dynamic response overestimate the soil plug effect, particularly for large-diameter piles, leading to inaccuracies in interpreting pile integrity.
Key Innovation: Proposed a modified additional mass model for three-dimensional longitudinal dynamic response of large-diameter pipe piles, accounting for partial soil plug contribution, and derived semi-analytical solutions to evaluate factors influencing pile integrity.
31. Flexural behavior of circular PHC piles strengthened with steel sleeve grouting
Core Problem: High-pile wharves are prone to damage in complex marine environments, necessitating effective repair and strengthening technologies for PHC piles.
Key Innovation: Investigated the flexural performance of circular PHC piles strengthened with steel sleeve grouting (CPSG) through tests and ABAQUS FEM, deriving a formula for ultimate flexural bearing capacity and providing guidance for engineering applications.
32. Experimental and Modeling Investigation on Effect of Structure and Composition on Laser-Induced Electro-Response of Shales
Core Problem: Developing new methods to characterize shale electrical properties and understanding the mechanism of composition and structure on laser-induced electro-response (LIER), as existing LIER mathematical models have shortcomings.
Key Innovation: Established a LIER model combining contributions from anisotropy in composition and structure, and through experimental investigation, demonstrated how LIER varies with sample preparation pressure, content of quartz/kerogen, and anisotropic bedding textures, confirming the model's validity for describing actual shale electrical characteristics.
33. Graph neural network-based identification of vulnerable regions in spatial complex networks via virtual node model
Core Problem: Existing regional identification models for vulnerable regions in spatial complex networks struggle to accurately describe network damage and integrate geographic information with topology, leading to poor precision.
Key Innovation: Introduced a virtual node model to capture network damage more effectively and proposed SNDM-VN, a graph neural network-based deep learning framework, which accurately identifies vulnerable regions in real-world networks by integrating topological and spatial features.
34. Monitoring snow cover dynamics at 30-m resolution in higher latitude regions using Harmonized Landsat Sentinel-2
Core Problem: Wide-area monitoring of snow cover dynamics (SCD) at high spatial resolution (10–30 m) has been limited by computational constraints and infrequent cloud-free observations, despite its importance for hydrology, climate, soil temperature, and permafrost.
Key Innovation: A new method was developed to map wide-area HSR SCD (snow start/end date, length, periods, status) by leveraging Harmonized Landsat Sentinel-2 (HLS) v2.0 (30-m resolution, 2–3-day revisit). The method, built around STACs and Python tools, demonstrated strong performance, particularly for snow end date, and provides publicly available products for Canada.
35. From climate-driven to dam-regulated: Impacts of dams on riparian vegetation in a mountainous river system
Core Problem: The ecological consequences of dams on riparian ecosystems and their spatial heterogeneity in mountainous environments remain poorly quantified, particularly regarding the disentanglement of dam operations vs. climatic variability.
Key Innovation: Analyzed long-term NDVI time series with climatic and hydrological datasets (2000-2019) in China's Lower Jinsha River Basin, quantitatively disentangling the relative contributions of dam operations (73.7% of NDVI variance) and climatic variability, demonstrating a shift from climate-driven to dam-regulated NDVI dynamics with strong spatial heterogeneity and implications for riparian vegetation management.
36. Plant–microbe interactions underpin contrasting enzymatic responses to flooding intensity variation in the cascade reservoir riparian areas
Core Problem: The non-uniform effect of periodic anoxia (induced by flooding) on soil organic carbon (SOC) preservation in riparian zones, with some areas retaining SOC (S-type) and others experiencing accelerated loss (Non-S-type), and the underlying plant-microbe interactions are not fully understood.
Key Innovation: Distinguished S-type and Non-S-type riparian areas based on SOC dynamics under flooding, revealing contrasting enzymatic responses and microbial resilience mechanisms. Non-S-type areas, exposed to high flooding intensity, showed higher phenol oxidase activity, microbial diversity, and structural stability, highlighting distinct microbial adaptations to hydrological extremes.
37. Towards intelligent shield position control: A novel offline reinforcement learning framework with SCA-MOPCEO integration
Core Problem: Untimely position control in shield tunneling, requiring intelligent decision-making for cylinder push thrust.
Key Innovation: Proposes a novel offline reinforcement learning framework integrating a State Classification and Assignment (SCA) method and a Model-based Offline Policy Conservative Exploration Optimization (MOPCEO) model to enable intelligent decision-making for shield tunneling position control, enhancing automation and intelligence.
38. New cutting tool wear testing method for evaluating the influence of foam additive on plowing effect during shield TBM tunnelling in dense sandy gravel ground
Core Problem: Unclear influence mechanisms of foam additives on the plowing effect, which mitigates ripper tooth wear during shield TBM tunneling in dense sandy gravel ground.
Key Innovation: Develops the WHU-SAT test apparatus and proposes a plowing coefficient to quantify the plowing effect, analyzing the variations in plowing coefficient, ripper tooth wear, and cutterhead torque with foam additive parameters, and revealing influence mechanisms based on particle contact analysis for optimizing TBM tunneling.
39. Evaluating a data space inversion surrogate model for predictive uncertainty quantification in a coupled SWAT + gwflow model
Core Problem: Traditional environmental model calibration for uncertainty quantification is computationally intensive and challenged by non-linear relationships between observations and parameters.
Key Innovation: A Data Space Inversion (DSI) surrogate model applied to a coupled SWAT+gwflow model, which efficiently quantifies predictive uncertainty for streamflow and groundwater head by conditioning predictions on measurements without updating physical parameters.
40. Analytical solutions for coupled unsaturated-saturated flow model in riparian zones: applicability and limitations
Core Problem: The Richards equation for unsaturated flow is highly nonlinear, making numerical solutions computationally expensive, and the applicability of simpler analytical solutions in coupled unsaturated-saturated systems is not systematically evaluated.
Key Innovation: Development of analytical solutions for a coupled unsaturated-saturated flow model in riparian zones using a linearized Richards equation, demonstrating high accuracy for river stage fluctuations but reduced applicability for high infiltration intensity or thick unsaturated zones.
41. Experimental study on seismic performance of GBC composite columns
Core Problem: Need to expand the application of raw bamboo in engineering and understand the seismic performance of novel composite columns (GBC) to improve structural resilience.
Key Innovation: Proposed and experimentally validated a novel GBC composite column, demonstrating its excellent plastic deformation capacity and ductility under seismic loading, and established a calculation method for its compression-flexure bearing capacity.
42. Direct displacement- and probabilistic residual displacement-based design method for RC double-column bridges with additional self-centering energy dissipation dampers
Core Problem: Achieving a balance between self-centering ability and energy dissipation in RC structures with SCEDs, and accounting for the discreteness of residual lateral drift ratio in seismic design.
Key Innovation: Developed a direct displacement- and probabilistic residual displacement-based design (DDRDBD) method for RC double-column bridges with SCEDs, enabling accurate targeting of maximum and residual displacements and balancing self-centering and energy dissipation capacities.
43. How Can FengYun—3G Satellite Precipitation Radar and Microwave Imager Unveil Multi—Phase Hydrometeors?
Core Problem: Developing methods to unveil multi-phase hydrometeors using satellite precipitation radar and microwave imager observations.
Key Innovation: Utilizing observations from FengYun-3G satellite precipitation radar and microwave imager to derive multi-phase hydrometeors, with an algorithm based on ARMS and incorporating graupel and other parameters.
44. Iterative fine-grained decoupling graph neural network for offshore wind turbine remaining useful life prediction
Core Problem: Existing GNN-based remaining useful life (RUL) prediction methods for multi-sensor equipment neglect the distinct feature requirements for RUL prediction and sensor spatial dependency modeling, leading to suboptimal task-level feature optimization.
Key Innovation: An iterative fine-grained decoupling graph neural network (IFGDGNN) with adaptive graph pooling is proposed for multi-sensor equipment RUL prediction, featuring a node feature iterative decoupling module and a decoupled features-based graph update module, successfully applied to offshore wind turbines.
45. A hybrid fault diagnosis framework for rudder propellers: Physics-guided learning from data and simulation
Core Problem: Intelligent fault diagnosis for rudder propellers is challenging due to their large size and complex installation, which limit the acquisition of fault data through physical experiments.
Key Innovation: A hybrid fault diagnosis framework is proposed, driven by both measured data and simulation models, integrating a high-fidelity multibody dynamics model, a dual-branch generative adversarial network (GAN) for signal adaptation, and a physics-informed neural network (PINN) for fault classification, achieving high accuracy.
46. Groundwater quality assessment for drinking by weighted WQIs: a guide based on comprehensive review analysis
Core Problem: The deterioration of groundwater quality (GWQ) is a major global issue, and there's a need for effective methods to assess GWQ, particularly regarding the impact of weight assignment in Water Quality Indices (WQIs).
Key Innovation: Provided a comprehensive review and evaluation of seven weighted-WQI techniques for groundwater quality assessment for drinking (GWQAD), discussing their frameworks, formulations, applications, advantages, and drawbacks, and suggesting comparative analysis to identify suitable WQI methods.
47. Effect of Stemming Material on Stemming Length-Burden Correlation in Cut Blasting
Core Problem: Irrational correlation between stemming length and burden in cut blasting leads to poor rock fragmentation and adverse consequences like stemming structure ejection.
Key Innovation: Designed model experiments to analyze the effect of stemming material (clay, water+clay, sand+clay) and length-burden correlation on cut blasting effectiveness, identifying optimal parameters (e.g., stemming length equals burden for clay) and providing recommendations based on stemming characteristic impedance to improve blasting performance.
48. Satellite Remote Sensing for Estimating Reservoir Physical Characteristics: A Global Review of Existing Methodologies for Operational Monitoring
Core Problem: Lack of a recent synthesis comparing remote sensing methods for estimating reservoir surface area, water level, and volume, and identifying operational gaps for water resource management.
Key Innovation: Provided a comprehensive global review (2000-2025) of satellite remote sensing methodologies for reservoir physical characteristics, identifying reliable techniques, operational gaps (e.g., small reservoirs, turbid waters, revisit times), and guiding future research for automated, high-resolution monitoring.
49. The methodology for upscaling surface albedo with consideration of surface heterogeneity
Core Problem: Current machine learning upscaling methods for land surface parameters often neglect surface heterogeneity, leading to significant prediction errors, and large-scale field data for validation is difficult to obtain.
Key Innovation: Proposed a novel land surface upscaling model that incorporates surface heterogeneity using a hybrid coefficient of variation (CV) index and a random forest (RF) model, achieving high accuracy (R2 of 0.93, RMSE of 0.026) for albedo upscaling and demonstrating improved performance in heterogeneous regions.
50. New insight into mechanical evolution and micro-mechanisms of early-age frozen engineered cementitious composites
Core Problem: Early-age frozen damage poses significant challenges to concrete durability and structural integrity in cold-region construction, with incompletely understood long-term mechanical properties of early-age frozen sulphoaluminate cement-engineered cementitious composites (SAC-ECC).
Key Innovation: Conducts comprehensive mechanical tests, single-fiber pullout tests, micromechanical modeling, and microstructural analyses to reveal that pre-curing times and frozen temperatures have complex, contrasting effects on SAC-ECC strength and ductility, providing insights for cold-region construction.
51. Comparative analysis of different machine learning models for prediction of compressive strength of early-age frozen concrete
Core Problem: Critical need for accurate prediction of compressive strength of early-age frozen concrete (EFC) to establish science-based mixture design criteria and ensure long-term structural performance in aggressive cold environments.
Key Innovation: Compares seven machine learning models for predicting EFC compressive strength, identifying GBDT and XGBoost as superior performers, and uses SHAP to reveal the most significant influencing variables (water-to-binder ratio, air-entraining agent), providing guidance for cold-region concrete design.
52. Temporal psychological and physiological responses to 120-hour isolation in an underground rescue chamber: A preliminary study
Core Problem: Lack of understanding of temporal psychological and physiological responses to prolonged isolation (beyond 48 hours) in underground rescue chambers, and the moderating effects of individual characteristics.
Key Innovation: A 120-hour simulated experiment investigating how exposure duration interacts with individual characteristics to influence psychological and physiological responses in a confined underground rescue chamber, providing empirical evidence for rescue chamber design and personnel training.
53. Impacts of storm events on watershed phosphorus critical source area identification based on SWAT model
Core Problem: The understudied variation of phosphorus (P) critical source areas (CSAs) under different storm events, despite P loss being predominantly event-driven and contributing to freshwater eutrophication.
Key Innovation: Investigation of the impacts of storm events on P CSAs identification using the SWAT model integrated with the cumulative pollution load curve method, revealing that storm-event-based analysis identifies more CSAs and potential risk areas, and that increasing storm levels significantly raise the number and contribution of CSAs.
54. Application of a coupled mechanistic and data-driven model for water level prediction considering the temporal and spatial effects of runoff evolution in cascade hydropower stations
Core Problem: Accurate water level prediction in cascade hydropower systems remains challenging due to complex runoff evolution and dynamic regulation.
Key Innovation: A coupled HD–WB–BP model integrating hydrodynamic, water balance, and neural network models with dynamic weighting via PSO, significantly improving short-term water level prediction accuracy and efficiency.
55. Factors affecting the preservation of the isotopic fingerprint of glacial meltwater in mountain groundwater systems
Core Problem: The factors affecting the preservation of the isotopic fingerprint of alpine glacier meltwater in mountain groundwater systems, including the influence of slope aspect and distance from the glacier, are not rigorously investigated.
Key Innovation: Using multiple environmental tracers (3H, 36Cl/Cl, 87Sr/86Sr) and an englacial mixing model (EMM) to demonstrate hydrostratigraphic controls on meltwater preservation in GNP and aspect-dependent preservation in MH, revealing the complex mixture of sources and the increasing influence of snowmelt in some systems.
56. Imputation of continuous missing values in water quality data using a temporal embedding-based self-attention variational autoencoder
Core Problem: Missing values in water quality data (WQD) due to various failures undermine the reliability of conventional imputation methods and hinder continuous environmental monitoring.
Key Innovation: A Temporal Embedding-based Self-Attention t-distributed Variational Autoencoder (TE-SAVAE-St) model that robustly and accurately imputes continuous missing values in WQD by incorporating a Student’s-t prior for outliers, temporal embeddings for chronological patterns, and multi-head self-attention for long-term dependencies, outperforming baseline methods.
57. Physical model study on dynamic behavior of PET geostrip-reinforced back-to-back MSE walls under bilateral cyclic loading
Core Problem: Lack of clarity on the dynamic behavior of geostrip-reinforced back-to-back MSE walls under bilateral cyclic loading, especially concerning high-speed railway loads.
Key Innovation: Physical model tests clarified the dynamic response characteristics (earth pressure, stress, tensile load, settlements, facing displacement) of BB-PET-MSE walls, identifying the influence of cyclic-load level, reinforcement spacing, spatial position, and wall height, and offering design guidance.
58. Numerical investigation of electrokinetic geosynthetics-assisted vacuum preloading combined with electroosmosis for consolidation and remediation of dredged sediments
Core Problem: Lack of a coupled model for dredged sediments improvement under VPE, hindering optimization of simultaneous consolidation and remediation.
Key Innovation: Established a coupled numerical model integrating electrical, hydraulic, mechanical, and chemical fields for VPE, enabling accurate prediction of dredged sediment consolidation and remediation performance and guiding optimization of treatment parameters.
59. Can a Single Sounding Predict the Weather? An AI Downscaling Framework for Local‐Circulation‐Dominated Flow Over Taiwan's Complex Topography
Core Problem: Accurately predicting local-circulation-dominated weather over complex topography using limited atmospheric sounding data.
Key Innovation: An AI downscaling framework that learns from upstream soundings and diurnal heating to predict local weather patterns over Taiwan's complex topography.
60. Identification of Key Factors Driving Dissolved Oxygen in Riparian Aquifers Through Deep Learning‐Assisted Global Sensitivity Analysis
Core Problem: Identifying key factors driving dissolved oxygen (DO) dynamics in riparian aquifers.
Key Innovation: Use of deep learning surrogates for efficient sensitivity analysis, revealing distinct controls on DO from river infiltration and groundwater flow.
61. Paying resilience forward
Core Problem: Not detailed in abstract, but likely discusses strategies or concepts for building future resilience.
Key Innovation: Not detailed in abstract, but implies a new approach or perspective on fostering resilience.
62. Fossil energy minimum viable scale
Core Problem: The potential for unseen infrastructural threats to safety and decarbonization as fossil energy systems are phased out.
Key Innovation: Highlighting potential safety and decarbonization risks associated with the minimum viable scale of fossil energy infrastructure during its phase-out.