TerraMosaic Daily Digest: Jan 16, 2026
Daily Summary
This compilation of 140 new papers on landslides and related hazards reveals a strong focus on risk assessment, monitoring, and mitigation strategies across diverse environments. Several papers address the impact of climate change, particularly concerning glacier melt, extreme rainfall, and wildfire recovery. Remote sensing and AI/ML techniques are prominently featured for hazard mapping, prediction, and early warning systems. A significant portion of the research investigates the stability of slopes, tunnels, and infrastructure under various conditions, including seismic activity, water level fluctuations, and human-induced disturbances. There's a growing emphasis on understanding the complex interactions between natural processes and human activities, including land use change, urbanization, and infrastructure development. The papers also highlight the importance of considering spatial variability, non-stationarity, and multi-hazard interactions in risk assessments. Finally, several studies focus on developing and validating new models and methodologies for predicting and managing landslides and related hazards, with a strong emphasis on data-driven approaches and integration of multi-source data.
Editor’s Choice highlights "“Deciphering the architecture of complex karst conduit networks in mountainous tunneling areas and its implications for water inrush risk using aquitard-constrained multi-source data”": This paper stands out due to its comprehensive and innovative approach to a critical problem in tunnel engineering: water inrush in karst terrains. The development of an aquitard-constrained, multi-source characterization framework is a significant advancement. By integrating geological surveys, drilling, geophysical profiling, hydrodynamic monitoring, and tracer tests, the study provides a robust methodology for delineating the complex three-dimensional geometry of karst conduits and their spatial relationships with tunnel alignments. This integrated approach offers a practical and effective solution for mitigating water inrush hazards, which can have severe consequences for tunnel construction and safety. The paper's emphasis on a holistic understanding of the geological environment and the use of multiple data sources makes it a valuable contribution to the field.
Key Trends
- Remote Sensing & AI/ML Integration: A surge in studies leveraging remote sensing data (Sentinel, Landsat, UAS) combined with AI/ML algorithms (CNNs, Transformers, etc.) for automated hazard mapping, prediction, and early warning.
- Climate Change Impacts: Numerous papers address the effects of climate change on various hazards, including glacier melt, extreme rainfall events, wildfire frequency, and coastal erosion.
- Infrastructure Resilience: A significant focus on assessing and enhancing the resilience of critical infrastructure (bridges, tunnels, power grids, wind turbines) to seismic activity, floods, and other natural hazards.
- Tunnel Stability: A large number of papers are focused on tunnel engineering, stability, and deformation, including the impact of water inflow, seismic activity, and surrounding rock properties.
- Soil Properties and Behavior: Many studies focus on understanding soil properties and behavior under various conditions, including freeze-thaw cycles, water content variations, and the presence of organic matter.
Selected Papers
This digest features 140 selected papers from 2122 papers analyzed across multiple journals. Each paper has been evaluated for its relevance to landslide research and includes links to the original publications.
1. Erosion susceptibility assessment through morphometric analysis and sub-watershed prioritization in the nyong watershed, Southern Cameroon
Core Problem: Erosion in the Nyong River sub-watershed is a major concern, requiring urgent conservation action.
Key Innovation: Prioritization of sub-watersheds based on morphometric and hydrological criteria, combined with field investigations of suspended solids.
2. Effects of freeze-thaw cycles on aggregate stability of sandy loam on the Eastern Qinghai-Tibet Plateau
Core Problem: Freeze-thaw cycles affect soil aggregate stability, influencing wind and water erosion on the Qinghai-Tibet Plateau.
Key Innovation: Laboratory simulations to investigate the effects of freeze-thaw cycles on wet- and dry-sieving aggregate stability of sandy loam.
3. Modeling sediment yield and assessing conservation measure effectiveness with SWAT+
Core Problem: Soil erosion is a fundamental process driving land degradation, requiring effective prediction and management strategies.
Key Innovation: Implementation of the SWAT+ model to quantify soil erosion rates and evaluate the effectiveness of conservation interventions.
4. Assessing flood exposure dynamics under migration and economic change from 2000 to 2020 in the Guangdong-Hong Kong-Macao greater Bay Area, China
Core Problem: Flood exposure in coastal areas increases due to migration and economic activities, but the impact of these changes on flood risk is unclear.
Key Innovation: Integration of flood modeling with statistical analysis to assess population and economic productivity exposed to floods.
5. Predicting the shear strength of rubber-incorporated granular waste mixtures with a machine learning approach
Core Problem: Traditional lab methods for shear strength determination are costly and time-consuming, especially for waste materials.
Key Innovation: ANN model trained with Bayesian regularisation to predict peak friction angle of rubber-incorporated granular waste mixtures.
6. Influence of Mineral Composition on Clay Rheological Behavior
Core Problem: Rheological behavior of clay can cause major engineering disasters such as foundation instability and slope sliding.
Key Innovation: Identifies 'rheological matter' (clay minerals and organic matter) as key to clay rheology, linking mineral composition to rheological properties.
7. Influence of Spatial Variability of Freezing-Sensitive Parameters on the Formation of Frozen Walls in Artificial Ground Freezing
Core Problem: AGF studies often ignore the randomness of underground soil layers.
Key Innovation: Investigates the spatial variability of sensitivity parameters in AGF using SFEM and MCS.
8. Influence of weak interfaces on secondary crack development in crystalline rocks with varying strengths and grain sizes
Core Problem: Understanding tensile fracture in composite rock samples.
Key Innovation: Experimental and numerical study on how grain size and smooth interfaces affect tensile fracture in composite Brazilian rock samples.
9. Capturing the hole effect in Qiantang River alluvial silt by cone penetration test
Core Problem: Soil spatial variability influences geotechnical systems, requiring accurate capture for reliability analysis.
Key Innovation: Identifies a significant 'hole effect' in Qiantang River alluvial silt, potentially linked to rhythmic tidal sedimentation processes, using cone penetration test data.
10. Multiscale damage mechanisms of reservoir bank sandstone under prolonged immersion in pumped-storage hydropower projects: From microscale processes to macroscopic fracture
Core Problem: Long-term stability of pumped-storage reservoir banks is governed by damage evolution from prolonged water immersion.
Key Innovation: Characterizes damage evolution in reservoir bank sandstone from mesoscopic to microscopic scales using CT, NMR, SEM, and MD simulations.
11. Seismic analysis of a zoned earth dam after decades of operation
Core Problem: Seismic assessment of aged earth dams requires understanding pre-seismic behavior and potential damage mechanisms affecting watertightness.
Key Innovation: Integrates pseudo-dynamic and coupled elastoplastic continuum approaches to predict earthquake-induced damage, considering material property changes over time.
12. Excess pore water pressure generation of saturated uncemented coral sands under non-proportional loading
Core Problem: Modeling cyclic behavior of saturated coral sand under non-proportional loading conditions to assess liquefaction risk.
Key Innovation: Defines an equivalent cyclic stress ratio (ESR) to establish a shear-volume coupling equation for various stress paths, implemented into Biot's equation for excess pore water pressure generation.
13. 3D seismic response and disaster performance of T-shaped intersecting valley fault sites: A case study of a simply supported beam bridge across fault
Core Problem: Irregular topography and faults significantly affect seismic responses, causing notable variations that may show within 1 km2, impacting bridge stability.
Key Innovation: Analyzes the seismic response characteristics and mechanisms of a T-shaped intersecting valley fault site and their impact on a simply supported beam bridge using 3D finite element models and various seismic wave inputs.
14. Deciphering the architecture of complex karst conduit networks in mountainous tunneling areas and its implications for water inrush risk using aquitard-constrained multi-source data
Core Problem: Accurately resolving the three-dimensional geometry of karst conduits and their spatial relationships with tunnel alignments to mitigate water inrush hazards.
Key Innovation: Develops an aquitard-constrained, multi-source characterization framework that integrates geological survey, drilling, geophysical profiling, hydrodynamic monitoring, and tracer tests to delineate conduit architecture.
15. Soil characterization through shear wave velocity analysis of Lucknow city in the Indo-Gangetic plain of India
Core Problem: Characterizing geotechnical parameters of shallow subsurface soil to understand soil deformation under dynamic loading during earthquake shaking.
Key Innovation: Uses Multichannel Analysis of Surface Waves (MASW) surveys to map subsurface shear wave velocity and define geotechnical parameters for soil behavior during an earthquake.
16. Insights into the microstructural evolution of dredged clay treated by SAP flocculation and vacuum preloading
Core Problem: Enhancing consolidation and microstructural uniformity of dredged clay for reuse in construction and land reclamation.
Key Innovation: Combines superabsorbent polymer (SAP) flocculation and vacuum preloading, using SEM, EDS, XRD, and digital image processing to evaluate microstructural evolution quantitatively.
17. Field measurements of <em>Phragmites australis</em> root reinforcement and traits along a riparian zone
Core Problem: Quantifying the direct contribution of Phragmites australis to bank stability through root reinforcement for soil bioengineering techniques.
Key Innovation: Direct measurements of root-soil composite strength using a corkscrew extraction technique, combined with root distribution parameters, to reveal substantial root reinforcement.
18. Urban flood resilience indexes to assess the pre-disaster stage of the disaster risk management cycle
Core Problem: Mitigating the risks associated with flood disasters by strengthening the resilience of communities and urban infrastructure through proactive disaster risk management.
Key Innovation: Proposes spatialized indexes for assessing flood resilience, covering the pre-disaster stage of the flood risk management cycle, corresponding to the prevention, mitigation, and preparedness stages.
19. Why we see risk differently: Socioeconomic dimensions of climate hazard and risk perceptions in Auckland, New Zealand
Core Problem: Climate-related natural hazards such as floods and landslides pose increasing risks to urban communities. Understanding how diverse individuals perceive these risks is essential for designing effective disaster risk reduction strategies.
Key Innovation: Multi-dimensional Risk Index reveals uneven climate hazard perceptions among individuals
20. Floods and flats: Housing market responses to flood risk in Japan
Core Problem: A significant portion of the global population resides in coastal areas and faces increasing flood risks. Understanding how flood risk affects residential property prices.
Key Innovation: Apartments located within plan-scale flood zones are priced 8.5% lower than comparable units outside these zones.
21. Identifying climatic hazard importance factors for bridges using expert-based fuzzy analytic hierarchy process
Core Problem: Bridges are critical components of ground transportation infrastructure, yet current design provisions remain rooted in historical climate assumptions that diverge sharply from projected future conditions.
Key Innovation: Develops AHP hierarchy for bridge risk from temperature, wind, rain, ice.
22. Enhancing the resilience of wind energy infrastructure in Iowa: Flood risk assessment and site suitability analysis for critical infrastructure protection
Core Problem: As climate change increases the frequency and severity of hydrological hazards, understanding and reducing disaster risk to renewable energy infrastructure has become critical.
Key Innovation: Comprehensive geospatial and statistical evaluation of flood exposure and site suitability for future installation of wind turbines across Iowa.
23. Application of cost-benefit analysis for establishing coastal erosion setback buffer zones in South Korea
Core Problem: Setting up buffer zones to avoid coastal erosion is a method used worldwide, but not been widely adopted in South Korea. The economic feasibility of buffer zones raises questions.
Key Innovation: A replicable spatial CBA framework to determine effective setback areas is proposed.
24. Exploring infrastructure dependence on community environment under natural hazards: quantifying the impact of building destruction on infrastructure functionality
Core Problem: The interdependence between urban infrastructure systems and community building portfolios is becoming a critical issue in urban seismic resilience.
Key Innovation: Present a coupled building-infrastructure framework for seismic performance analysis.
25. Enhancing Residual Flood Risk Assessment through Response Capacity Quantification: Case Study of the Sefidroud River, Iran
Core Problem: This study develops a response-adjusted flood risk assessment framework that incorporates physical accessibility to emergency services as a first approximation of community mitigation capacity.
Key Innovation: Integrated response capacity into a residual flood risk framework.
26. Vertical vulnerability and exposure of people in the context of disaster risk at the building, city and regional level
Core Problem: Vulnerability in the context of disaster risk is widely analysed in terms of the horizontal distribution of people and social groups, as well as their features and capabilities. However, vertical distributions are not yet well-researched
Key Innovation: The study proposes a more thorough and systematic investigation of the vertical aspects of people's vulnerability, including their social and physical characteristics, as well as those of social groups.
27. Multivariate Logistic Wind Fragility Functions of Overhead Distribution Poles.
Core Problem: Overhead distribution lines are highly vulnerable to extreme wind events, yet fragility modeling remains challenging due to multiple interacting failure mechanisms and strong dependence on asset and site characteristics.
Key Innovation: Integrates stochastic wind simulation with finite-element–based structural analysis to capture governing failure mechanisms.
28. Rebuilding after wildfires: Factors influencing sustainable, resilient, expedient, and cost-effective housing recovery
Core Problem: The increasing frequency of destructive wildfires, fueled in part by climate change, creates an urgent need to understand how homes can be rebuilt in a post-fire context to produce rebuilding outcomes that balance sustainability, fire resilience, expediency, and cost.
Key Innovation: Results show that sustainability and fire resilience outcomes were strongly shaped by jurisdictional building codes and policy enforcement, whereas expediency and cost outcomes were more strongly influenced by builder type and home size.
29. BIM and GIS-integrated multi-stakeholder fire risk assessment model for heritage buildings
Core Problem: Heritage buildings are vulnerable to fires due to combustible materials, outdated suppression systems, and conservation constraints. Systematic fire risk assessment is therefore essential to appraise building conditions, identify dangers early, and enable proactive mitigation.
Key Innovation: Propose a fire risk assessment model for heritage buildings named RATER.
30. Public perceptions and responses to flood risk: Evidence from the 2023 flood events in Italy
Core Problem: As flood hazards increase in frequency and intensity, understanding public risk perception, preparedness, and responses to communication strategies is critical.
Key Innovation: Original survey of 3,423 residents after 2023 floods in Emilia-Romagna and Tuscany.
31. Mapping seismic risk of existing highway bridges at a regional scale using Artificial Neural Networks
Core Problem: Traditional bridge management systems rely heavily on visual inspections, making large-scale evaluations costly and time-consuming. Bridges are critical components of transportation networks, whose failure can compromise public safety, economy, and mobility.
Key Innovation: Development of an ANN-based predictive model for seismic risk, application of ANN models for degradation and traffic-related structural risk to a real bridge network, and integration of all three predictions into GIS-based maps.
32. Vulnerability of process and instrument air supply utilities to volcanic ash
Core Problem: Volcanic ash can disrupt industrial sites by affecting utilities and services, potentially causing Natech events.
Key Innovation: A model to estimate filtration system clogging from volcanic ash and a risk matrix for air intake systems, facilitating preventive planning and real-time decision-making.
33. Time-varying post-earthquake resilience assessment of reinforced concrete frame structures under aftershock sequence
Core Problem: Mainshock-damaged structures' performance varies with aftershocks due to lack of repair time.
Key Innovation: A time-varying resilience function is developed to account for the spatiotemporal variation of aftershock seismicity and the damage accumulation of structures.
34. Probabilistic assessment of dynamic urban evacuation-sheltering functionality under typhoons based on interdependent road-shelter network
Core Problem: Assessing the functionality of urban evacuation-sheltering systems (UESS) during typhoons, considering the dynamic degradation due to physical damage and traffic demand.
Key Innovation: A holistic functionality metric capturing temporal variations in evacuation timeliness and shelter availability, combined with a probabilistic assessment framework for UESS.
35. RayExtract: A fast, scalable method for tree volume reconstruction from terrestrial laser scanning
Core Problem: Accurate tree volume and structure estimation for forest biomass and ecosystem investigations using Terrestrial Laser Scanning (TLS).
Key Innovation: RayExtract, a novel method reconstructing woody volume from TLS data using morphological rules (Self-Similarity and Leonardo’s Rule) to automate tree structural metrics extraction without leaf classification.
36. A snow properties-aware deep learning framework for penetration bias estimation of TanDEM-X DEMs over ice sheets
Core Problem: Inaccurate assessment of glacier volume and snow depth due to radar wave penetration variability in TanDEM-X DEMs.
Key Innovation: A deep learning framework combining snow facies segmentation and penetration bias regression, improving accuracy of TanDEM-X DEMs over ice sheets.
37. Probabilistic mapping of high-intensity forest fire potential via time series machine learning and remote sensing-informed fire spread simulations
Core Problem: Challenges in forecasting large-scale fire behavior characteristics, limiting spatial estimations of high-intensity forest fire potential (HIFFP).
Key Innovation: Integration of fire spread simulations and machine learning (ML) algorithms to enhance HIFFP estimations through multi-step time-series forecasting on fire rate of spread and fireline intensity at regional scales.
38. Soil moisture retrieval from Sentinel-1: Lessons learned after more than a decade in orbit
Core Problem: Accurate large-scale soil moisture observation is difficult due to sparse in situ networks and cloud cover limitations for optical sensors. Sentinel-1 SAR offers all-weather, day/night observations, but soil moisture retrieval faces challenges from vegetation, surface roughness, and model limitations.
Key Innovation: Reviews the application of C-band SAR observations from Sentinel-1 for high-resolution near-surface soil moisture estimation, discusses limitations, and recommends multi-sensor data integration, refined models, and advanced AI techniques.
39. Flood pulse monitoring in wetlands with multi-temporal Sentinel-1 interferometric coherence data: Application to the Okavango Delta (Botswana)
Core Problem: Characterizing hydrological dynamics in flood-pulsed wetlands is critical for understanding these sensitive ecosystems, but traditional methods are limited. The study explores the potential of Sentinel-1 InSAR coherence time series to monitor flood propagation in the Okavango Delta.
Key Innovation: Uses interferometric coherence time series from Sentinel-1 to quantify the seasonality of coherence, relating it to land cover and flood frequency. Develops a normalized seasonal index and change-detection approach to map flood pulses and their arrival dates with high accuracy.
40. A Spatially Masked Adaptive Gated Network for multimodal post-flood water extent mapping using SAR and incomplete multispectral data
Core Problem: Accurate and timely mapping of flood water extent is crucial for disaster management, but multispectral data is often incomplete due to cloud cover. Adaptive integration of SAR and MSI data for water extent mapping remains underexplored.
Key Innovation: A Spatially Masked Adaptive Gated Network (SMAGNet) that uses SAR data as the primary input and integrates complementary MSI data through feature fusion, enhancing robustness to missing data in flood mapping.
41. Mapping oil spills under varying sun glint conditions using a diffusion model with spatial-spectral-frequency constraints
Core Problem: Detecting marine oil spills using optical remote sensing is challenging due to sun glint, which masks spectral features and causes contrast reversals.
Key Innovation: A Spatial-Spectral Attention Conditioned Diffusion Probabilistic Model with Dual-branch Frequency Parser (OSS-Diff) that disentangles contrast variations and amplifies discriminative features for identifying oil emulsification states.
42. Satellite images reveal reduced lake chlorophyll concentration and eutrophication in China
Core Problem: Monitoring lake water quality and trophic states over large areas is essential, but requires analyzing long-term data to assess the impact of environmental policies and climate change.
Key Innovation: Analyzing Landsat imagery from 1990-2020 to assess changes in chlorophyll-a concentration and trophic states in over 1138 large lakes in China, revealing a decline in average chlorophyll-a concentration after 2010.
43. Explainable spatiotemporal deep learning for subseasonal super-resolution forecasting of Arctic sea ice concentration during the melting season
Core Problem: Accurate, high-resolution forecasting of Arctic sea-ice concentration (SIC) during the melting season is crucial for climate monitoring and polar navigation, yet remains hindered by the system’s complex dynamics.
Key Innovation: MSS-STFormer, an explainable multi-scale spatiotemporal Transformer, integrates environmental factors and specialized modules to enhance spatiotemporal representation and physical consistency for subseasonal SIC super-resolution forecasting.
44. Major improvements in spaceborne early fire detection and small-fire FRP retrieval with the meteosat third generation flexible combined imager
Core Problem: Detecting landscape fires early and accurately is crucial for effective fire management, but current geostationary satellites have limitations in spatial, temporal, and radiometric characteristics.
Key Innovation: Applying an active fire detection algorithm to Meteosat Third Generation (MTG) Flexible Combined Imager (FCI) data, demonstrating earlier fire detection, increased active fire pixel detections, and improved FRP retrievals compared to previous systems.
45. Satellite remote sensing and field analyses of megaripples and dunes in the Skeleton Coast National Park, Namibia
Core Problem: Understanding the morphology and dynamics of aeolian bedforms is crucial for reconstructing current and past environmental settings, but requires integrating satellite remote sensing with field observations.
Key Innovation: Investigating the morphology and dynamics of megaripples and barchan dunes in Namibia's Skeleton Coast National Park using satellite remote sensing, reanalysis wind data, and field observations, revealing insights into sediment transport mechanisms and ripple morphometry.
46. Detecting utility-scale solar installations and associated land cover changes using spatiotemporal segmentation of Landsat imagery
Core Problem: Utility-scale solar development leads to land-use and land-cover change (LULCC), particularly deforestation, impacting carbon dynamics.
Key Innovation: A change detection framework integrating Continuous Change Detection and Classification (CCDC) with Simple Non-Iterative Clustering (SNIC) to map utility-scale solar development and related forest disturbances.
47. Bridging spatio-temporal gaps in ALS data using Landsat time series and forest disturbance-recovery metrics via multi-task neural networks
Core Problem: Inconsistencies in timing, coverage, methodologies, and data quality of National Forest Inventories (NFIs) highlight the need for a more harmonized and spatially detailed approach to forest monitoring.
Key Innovation: A novel approach relying on fully connected neural networks to integrate Landsat satellite time series and forest disturbance and recovery metrics with ALS data to predict forest height metrics.
48. Automatic gully mapping using deep learning with boundary-stratified sampling and pixel balancing optimization: a case study of the Yuanjiang dry-hot valley
Core Problem: Automatic gully mapping in steep, heterogeneous terrain is challenging due to complex morphology and small gully area proportion.
Key Innovation: A gully classification strategy distinguishing clear vs. unclear boundaries, combined with pixel-balancing to improve deep learning-based gully mapping accuracy.
49. Impact of plateau pika burrows on soil water infiltration: Insights from controlled experiments and numerical simulation
Core Problem: High-density plateau pika activity alters soil properties and hydrological processes, but the ecohydrology of pika burrows is poorly understood.
Key Innovation: Sandbox experiments and COMSOL simulations demonstrate preferential flow in rodent burrows, quantifying the influence of burrow structure and density on water infiltration.
50. Terrace abandonment enhances rather than diminishes hydrological functioning in karst terraces by reshaping soil pore structure
Core Problem: Terrace abandonment impacts karst soil hydrology, but the pore-scale mechanisms are unclear.
Key Innovation: NMR analysis shows vegetation recovery fosters finer, better-connected pore networks, enhancing soil hydrological function.
51. Quantifying glacier and snow shrinkage: future water stress in Northern Tien Shan, Central Asia
Core Problem: Global warming accelerates glacier and snow shrinkage in the Tien Shan, impacting soil moisture and hydrological processes.
Key Innovation: A glacier-expanded Variable Infiltration Capacity model (VIC-CAS) was developed to project the impacts of meltwater changes on soil moisture and hydrological processes.
52. Rapid retreat of tropical glaciers in Puncak Jaya, Papua: Four decades of change observed from Landsat Imagery, 1980–2024
Core Problem: Climate change is heavily affecting the cryosphere ecosystem, specifically the glaciers in Puncak Jaya.
Key Innovation: Landsat imagery shows that the glacier area has decreased by 97% over 44 years, and predicts the glaciers will disappear by 2030.
53. Field data-based safety assessment and probabilistic deformation prediction of existing metro tunnels under adjacent excavation
Core Problem: Excavation-induced stratum disturbance threatens metro tunnel integrity and safety.
Key Innovation: Data-driven approach using extreme gradient boosting for deformation prediction and principal component analysis for safety assessment, enabling dynamic risk mapping.
54. Dynamic behavior of ultra-low friction in tunnel-surrounding blocky rock mass under multi-period dynamic loads: Experimental and modeling analysis
Core Problem: Instability of deep rock mass due to dynamic loadings and ultra-low friction effects.
Key Innovation: Experimental and numerical (DDA) analysis of rock mass instability under multi-period dynamic loads, revealing friction reduction and failure stages.
55. Field data-based safety assessment and probabilistic deformation prediction of existing metro tunnels under adjacent excavation
Core Problem: Excavation-induced stratum disturbance threatens metro tunnel integrity and safety.
Key Innovation: Data-driven approach using extreme gradient boosting for deformation prediction and principal component analysis for safety assessment, enabling dynamic risk mapping.
56. Impact of aftershocks on the response of a post-mainshock damaged metro station structure in seismic subsidence site
Core Problem: Aftershocks exacerbate damage to metro stations in seismic subsidence sites.
Key Innovation: Finite element modeling of post-mainshock metro station collapse under aftershocks, quantifying displacement and damage increment ratios, and proposing a modified damage index.
57. Dynamic behavior of ultra-low friction in tunnel-surrounding blocky rock mass under multi-period dynamic loads: Experimental and modeling analysis
Core Problem: Instability of deep rock mass due to dynamic loadings and ultra-low friction effects.
Key Innovation: Experimental and numerical (DDA) analysis of rock mass instability under multi-period dynamic loads, revealing friction reduction and failure stages.
58. Research and insights on time-dependent reinforcement and collaborative load-bearing control technology for roadways in extremely soft stratum
Core Problem: Large deformation and instability in roadways due to rheological behavior of extremely soft surrounding rock.
Key Innovation: Time-dependent reinforcement support system with collaborative load-bearing control, validated through FLAC3D simulations and field tests, significantly reducing roof subsidence and crack evolution.
59. An interpretable and adaptive tunnel water inflow prediction method using data augmentation and AHP-Enhanced OP-LightGBM
Core Problem: Accurate prediction of tunnel water inflow is critical for ensuring construction safety and risk control in tunnel engineering.
Key Innovation: An intelligent prediction framework that integrates data augmentation, model optimization, interpretability, and online deployment, and additionally possesses strong adaptability to dynamic field conditions.
60. Deciphering the time-dependent behavior of underground rock tunnels: Insights from a generalized non-associative thermo-viscoplastic damage model
Core Problem: Time-dependent deformation of underground rock tunnels in coupled geopressure and geothermal environments.
Key Innovation: A novel non-associative thermo-viscoplastic damage model is proposed within the thermodynamic framework for characterizing the rock creep behavior.
61. Groundwater inflow into tunnels: semi-empirical methods for estimating steady state inflow associated with excavation induced drawdown
Core Problem: Estimation of groundwater inflow is essential for tunnel design and construction; however, analytical solutions used in current engineering practice have limited applicability, especially in cases where drawdown of the water table occurs due to excavation associated drainage.
Key Innovation: The study proposes two novel methods for estimating inflow into tunnels based on drawdown: one for inflow into shallow tunnels where full drawdown of the water table occurs (trench-like inflow), and one for inflow into moderately deep tunnels, where partial drawdown of the water table occurs.
62. Plastic-hardening constitutive model-based hybrid machine learning framework for three-dimensional tunnel deformation prediction
Core Problem: Accurately predicting tunnel deformation induced by excavation is critical for ensuring urban underground safety and optimizing reinforcement schemes.
Key Innovation: This study proposes a hybrid machine-learning framework that integrates particle swarm optimization (PSO), convolutional neural networks (CNN), and extreme gradient boosting (XGBoost).
63. TTM: A concise yet effective surface reconstruction approach for tunnel point cloud from mobile mapping system
Core Problem: Tunnels are critical infrastructure, the surface reconstruction of their point cloud is essential for applications such as reality capture BIM and digital twin systems.
Key Innovation: This paper proposes TTM (topology transfer meshing), a concise yet efficient surface reconstruction method for MMS-acquired tunnel point clouds.
64. Dynamic response of an underwater single-tube double-track tunnel under high-speed train loads: experimental and numerical investigation
Core Problem: The single-tube double-track underwater tunnel has gained prominence in recent years due to its practicality. Given the unique structural configuration, systematic investigation into the dynamic responses of this type of tunnels under train loads holds substantial practical value.
Key Innovation: This study adopts a technical route combining physical model testing and numerical simulation, conducting systematic research on the coupled scenario of “high water pressure–high-speed train load–large-diameter tunnel–single-tube double-track”.
65. A thin-shell model for densely packed pre-reinforcement shell structures in weak rock tunnels
Core Problem: Pipe roofs, horizontal jet grouting piles, and analogous pre-reinforcement technologies form a continuous thin shell composed of densely arranged cylindrical elements, herein defined as the densely packed pre-reinforcement shell structure. These structures are critical for weak rock tunnels.
Key Innovation: To overcome this limitation, a densely packed pre-reinforcement shell model is developed using elastic thin-shell theory, incorporating nonlinear governing equations that resolve coupled longitudinal–transverse load-bearing mechanisms.
66. A novel reinforced concrete lining with an induced crack for high-pressure tunnels: Numerical simulation
Core Problem: Reinforced concrete linings are extensively employed in hydraulic tunnel construction due to their well-established technology, rapid installation, and cost-effectiveness. However, under high internal water pressure, these linings are prone to tensile cracking, with crack characteristics and widths significantly influencing seepage behavior and long-term durability.
Key Innovation: To address this, we propose a novel reinforced concrete lining featuring an induced crack, strategically designed to guide cracking at a predetermined location.
67. Simulation and treatment for water leakage in tunnel lining model through self-healing materials
Core Problem: Tunnel lining structures commonly develop cracks and water leakage. Treatment materials are susceptible to secondary damage from structural stress and deformation.
Key Innovation: The purpose of this study is to assess the applicability of high-toughness self-healing materials for treating water leakage in tunnel lining structures and examines the performance of the lining after secondary damage.
68. Mechanical behavior of disjointed concrete pipes under combined traffic loads and groundwater fluctuations
Core Problem: Frequent road collapses in Guangzhou, China, have been linked to disjoints in underground drainage pipes. Clarifying the mechanical behavior of disjointed pipes under complex service conditions is of critical significance for targeted rehabilitation.
Key Innovation: This study focuses on concrete drainage pipes during the initial stage of disjoint, wherein significant erosion of the surrounding soil has not yet developed. The combined effects of traffic loads and groundwater level fluctuations were considered.
69. Distribution characteristics and spatial correlation analysis of defects in in-service metro shield tunnels: A case study
Core Problem: Metro shield tunnels in service are often plagued by interconnected defects that undermine structural integrity and operational safety.
Key Innovation: This study focuses on an 18.5-km metro tunnel with 8 years of operation, employing 3D laser scanning data to investigate five key defects including leakage, cracks, dislocations, spalling, and convergence.
70. A temperature-dependent nonlinear model for estimation of tunnel roof stability in unsaturated soils
Core Problem: Tunnel roof stability is a hot topic in engineering practice and has been investigated through an analytical manner. Nonetheless, less attention has been paid to consider unsaturated soils under non-isothermal conditions.
Key Innovation: An upper bound analysis procedure with considerations of temperature and unsaturated soil properties is proposed for this specific purpose.
71. Dynamic response of an underground structure subjected to internal erosion and seismic densification via centrifuge shaking table tests
Core Problem: Internal erosion–induced seismic failure of unstable strata can significantly redistribute internal forces in underground structures, potentially causing damage.
Key Innovation: This study investigates how internal erosion, represented by fines loss in gap-graded sands, affects the static and seismic behavior of soil–structure systems.
72. Deterioration and damage characteristics of rock masses within the fluctuating zone, Three Gorges Reservoir Area, China
Core Problem: Water level fluctuation in the Three Gorges Reservoir Area causes deterioration and damage to rock masses, leading to instability of submerged rocks.
Key Innovation: Comprehensive analysis using sonic CT imaging, field surveys, drilling, and underground television to reveal deterioration characteristics and the role of reservoir water level fluctuation (RWLF) in causing chemical corrosion and mechanical damage.
73. Seismic response and energy release of simulated faults with varying morphology and pre-stress under impact disturbance
Core Problem: Understanding the seismic response of fault surfaces under impact disturbances to predict induced seismicity.
Key Innovation: Direct shear experiments on simulated faults with varying morphology using a biaxial Hopkinson bar system, combined with high-speed 3D-DIC and rock CT, to quantify dynamic deformation, failure characteristics, and energy release.
74. A microplane-enhanced quasi-bond method with a dual-mechanism fracture criterion for mixed-mode failure in rock-like materials
Core Problem: Modeling mixed-mode fracture in rock-like materials, particularly for geohazard predictions.
Key Innovation: Integration of microplane theory into a quasi-bond method with a dual-mechanism fracture criterion to capture tensile and shear crack behavior, validated against notched beams and extended to jointed rock slopes for step-path fracture network evolution.
75. Evaluation and analysis of the ductile dynamic response of mountain tunnels based on shaking table tests
Core Problem: Assessing the seismic performance and damage patterns of cast-in-place horseshoe-shaped mountain tunnels under dynamic loading.
Key Innovation: Development of a method to directly measure ductile displacement time-history in tunnels using shaking table tests, providing displacement and maximum deformation rate (MDR) control indices for different burial depths.
76. Study on dynamic early warning method for coal and gas outburst disasters based on data mining and unsupervised clustering
Core Problem: Extracting effective early-warning information from gas concentration monitoring data for coal and gas outburst disasters.
Key Innovation: Application of EN-TSFRESH for feature extraction from gas concentration data, combined with unsupervised clustering methods (hierarchical clustering) for classifying datasets and identifying high-risk events correlated with drilling cuttings weight.
77. Prediction of mud cake formation on shield cutterheads based on multi-source monitoring data integrated with deep learning method
Core Problem: Dynamic and accurate prediction of mud cake formation on shield cutterheads during tunneling.
Key Innovation: Integration of a Transformer–LSTM deep learning model with real-time shield monitoring data and geological information to predict cutterhead mud cake rate, achieving high predictive performance.
78. Rock mass discontinuity trace mapping using a voxel-based morphology-topology framework
Core Problem: Existing point cloud-based methods for discontinuity trace mapping face challenges in trace connectivity and topological relationships.
Key Innovation: A voxel-based morphology-topology approach is proposed to enhance spatial connectivity and refine trace details in rock mass discontinuity mapping, improving the topological connectivity rate.
79. A method for mechanical properties identification of nonlinear joints based on deep learning in time-frequency domain
Core Problem: Determining mechanical properties of nonlinear joints is challenging.
Key Innovation: A deep learning method using CNNs on wavelet time-frequency spectrograms is proposed to identify the mechanical properties of nonlinear joints.
80. Integrating non-stationarity into extreme rainfall risk assessment: A GAMLSS-based framework for large-scale region
Core Problem: Neglecting non-stationarity of extreme rainfall in disaster risk assessment may underestimate potential risks.
Key Innovation: A framework incorporating non-stationarity into potential risk assessment of extreme rainfall using GAMLSS.
81. Improved flash drought forecasting and attribution: A spatial-temporal causality-aware deep learning approach
Core Problem: Flash droughts pose significant challenges to water resource management and agricultural sustainability, making it imperative to improve their predictability.
Key Innovation: A deep learning framework that integrates a spatial–temporal causality-aware module into a CNN-LSTM hybrid architecture to enhance flash drought prediction.
82. Steeper spatiotemporal distribution of extreme precipitation intensity in urban than rural regions
Core Problem: Urban flooding is highly sensitive to the organization of precipitation, but it remains unclear how urbanization alters these structure-related characteristics of extreme precipitation across time and space.
Key Innovation: Examines the urbanization-induced asymmetric spatiotemporal reorganization of extreme precipitation during the rainy season.
83. Impacts of severe land use changes on the hydrology of snow dominated catchments in southern Quebec
Core Problem: Understanding hydrological response to land use changes in snow-dominated catchments.
Key Innovation: Evaluates hydrological response to extreme land use changes using regional climate simulations and hydrological models, assessing impacts on flood events.
84. Development and verifications of rock bolts with axial-bending coupling deformation and bolt-rock interface effect in discontinuous deformation analysis (DDA)
Core Problem: Rock bolting is a crucial reinforcement measure, but its simulation in jointed rock masses requires accurate modeling of bolt-rock interaction.
Key Innovation: A rock bolt model is developed within DDA, incorporating axial-bending coupling and bolt-rock interface effects, verified through pull-out and shear tests, and applied to jointed rock tunnel simulation.
85. Numerical simulation of cone penetration tests in loose unsaturated soils
Core Problem: Cone penetration tests (CPTu) in unsaturated soils are affected by partial saturation, but the underlying mechanisms are not well understood.
Key Innovation: PFEM simulation of CPTu in unsaturated soils using a finite strain elasto-plastic critical state model, exploring the effect of suction and permeability on cone response.
86. A discrete element approach for simulating progressive fracturing in geothermal reservoirs via a new cohesive crack model
Core Problem: Modeling complex thermo-hydro-mechanical (THM) behaviors in fractured geothermal energy storage systems requires sophisticated modeling of fracture deformations.
Key Innovation: A new cohesive crack model for DEM is proposed, allowing flexible adjustment of post-peak tension behavior and capturing progressive fracture evolution under cyclic THM loadings.
87. Phase field modeling of fracture propagation upon cavity pressurization in layered rock
Core Problem: Understanding fracture propagation in layered rocks is essential for predicting fracture geometry and optimizing subsurface operations.
Key Innovation: A phase-field modeling framework investigates the effects of stiffness contrast, fracture energy release rate, and in-situ stress on fracture propagation around pressurized cavities in layered rock systems.
88. Roof stability analysis of deep buried tunnel based on the spatial discretization technique
Core Problem: Roof collapse is common in tunnels excavated by the drill-and-blast method, and previous collapse mechanisms do not fully capture the real collapse characteristics.
Key Innovation: New 2D and 3D collapse mechanisms of deep buried tunnel roofs are generated using the spatial discretization technique and tensile strength cut-off criterion.
89. A grain-based phase-field method for simulating compressive-fatigue fracture in heterogeneous brittle rocks
Core Problem: Numerical prediction of compressive-fatigue fracture in heterogeneous brittle rocks under cyclic loading is a challenge.
Key Innovation: A mixed-phase field model, grounded in a grain-based methodology, is introduced for simulating fatigue damage and fracture processes in heterogeneous brittle rocks.
90. Correlation between liquefaction resistance and shear wave velocity of sand-gravel mixtures: An experimental investigation
Core Problem: Evaluating liquefaction potential in gravelly soils, which is challenging but crucial for infrastructure safety in earthquake-prone areas.
Key Innovation: Developed laboratory-based correlations between cyclic resistance ratio (CRR) and shear wave velocity (Vs) specific to sand-gravel mixtures, considering both gravel content and relative density.
91. Risk assessment of power infrastructure vulnerability to seismic hazards in China
Core Problem: Assessing the seismic risk to China's power infrastructure, which is critical for resource allocation and resilience management.
Key Innovation: Developed a county-level quantitative framework integrating multi-source data, China-specific fragility functions, and terrain-dependent reconstruction costs to assess seismic risk to power infrastructure.
92. Seismic response of offshore wind turbine supported by tetrapod piled jacket foundations in clays considering scour
Core Problem: Examining the influence of seismic spectral properties and scour depth variations on the dynamic behavior of offshore wind turbines (OWTs) with tetrapod-piled jacket foundations.
Key Innovation: Utilized advanced 3D finite element modeling to examine the influence of seismic spectral properties and scour depth variations on the dynamic behavior of offshore wind turbines (OWTs) in clays.
93. Experimental and numerical investigation on seismic behavior of precast segmental CFDST bridge piers under tridirectional near-fault ground motions
Core Problem: Understanding the seismic behavior of post-tensioned precast segmental concrete-filled double-skin steel tubular (CFDST) bridge piers under near-fault ground motions.
Key Innovation: Combined experimental shaking table tests and refined OpenSees finite element modeling to investigate the seismic behavior of precast segmental CFDST bridge piers under tridirectional near-fault ground motions.
94. Nonlinear response analysis of seismic wave scattering characteristics for three-dimensional real terrain
Core Problem: Accurately characterizing the influence of complex terrain on seismic wave scattering and site amplification effects.
Key Innovation: Proposed a nonlinear seismic response calculation method that accounts for actual surface topography using a three-dimensional geometric model based on a digital elevation model (DEM) and the improved Drucker-Prager elastoplastic constitutive model.
95. Seismic vulnerability analysis of cable-stayed bridge based on kernel function improved response surface method
Core Problem: Improving the computational efficiency and accuracy of seismic vulnerability analysis for bridges considering parameter randomness.
Key Innovation: Introduced an improved response surface method based on kernel functions (KPLS-RSM) to better capture the nonlinear relationship between samples and responses in seismic vulnerability analysis of cable-stayed bridges.
96. A poroelastic half-space model for dynamic pile–soil interaction problem
Core Problem: Investigating the dynamic response of saturated soil around a vertically vibrating pile, which is important for vibration isolation and seismic testing interpretation.
Key Innovation: Proposed a poroelastic half-space soil model excited by known vibration (P-HEKV) solution scheme to analyze the dynamic response of saturated soil around a vertically vibrating pile.
97. Bayesian inversion method for soil layer velocity structures based on the earthquake horizontal-to-vertical spectral ratio and its applications
Core Problem: Improving the assessment of uncertainty in soil layer parameter inversion using the earthquake horizontal-to-vertical spectral ratio (HVSR).
Key Innovation: Proposed a Bayesian inversion method for soil layer velocity structures that combines Bayesian principles with the earthquake horizontal-to-vertical spectral ratio (EHV) forward algorithm.
98. Assessment of wind-wave-earthquake misalignment for offshore wind turbines in 3D geomorphological complex soil conditions, with soil-monopile interaction analysis
Core Problem: Investigating the dynamic response of monopile offshore wind turbines (MOWTs) subjected to combined wind, wave, and seismic loading, focusing on the assessment of wind–wave–earthquake directional misalignment.
Key Innovation: Used a validated 3D finite element (FE) model to simulate soil-structure interaction (SSI) under complex loading conditions, incorporating site-specific subsurface features and a novel integration of Pareto analysis and the Response Surface Method (RSM).
99. Seismic fragility assessment of 100 m3 elevated water tanks on shallow foundation considering simplified fluid–structure–soil interaction models
Core Problem: Investigating the seismic fragility of reinforced concrete elevated water tanks (EWTs) considering fluid–structure interaction (FSI) and soil–structure interaction (SSI).
Key Innovation: Employed a nonlinear modeling framework that incorporates confined material behavior, fluid–structure interaction (FSI), and soil–structure interaction (SSI) to analyze EWTs under varying conditions.
100. A novel method for efficient generation of 3D large-scale random fields via MEOLE
Core Problem: Efficiently simulating 3D large-scale random fields (RFs) for slope engineering, addressing computational load and efficiency issues.
Key Innovation: Modified Expansion Optimal Linear Estimation (MEOLE) method, incorporating 3D rotational anisotropy for realistic simulation of inclined layered slopes.
101. Behavior of piled rafts crossing reverse fault zones: Experimental and numerical evidence for setback strategies
Core Problem: Characterizing failure mechanisms of piled rafts in fault-affected areas and developing targeted setback strategies.
Key Innovation: Integrated centrifugal testing and numerical modeling to analyze piled raft response at key surface exposure locations of free-field fault rupture zones, proposing setback criteria.
102. Dynamic stability and ballast movement characteristics of steep-gradient rack railway track under traction load
Core Problem: Steep gradients in rack railways cause dynamic instability of ballasted tracks under traction, risking operational safety. Existing studies lack microscopic mechanical behavior insights.
Key Innovation: Coupled vehicle-track dynamic model with discrete element method to analyze track response under varying traction, vehicle loads, and gradients, validated against field data.
103. Investigation of particle migration and drainage behavior in railway ballast induced by multiphase flow using a coupled VOF-DEM approach
Core Problem: Ballast fouling reduces drainage efficiency, impacting track operation. Understanding the interaction between fouling, fluid flow, and particle migration is crucial.
Key Innovation: Coupled DEM-CFD model for multiphase fluid flow to investigate fine particle migration and drainage in ballast, considering fouling index, profile, and cohesive energy density.
104. The influence of tunnel floor heave induced by high water pressure on the mechanical response of ballastless track
Core Problem: Tunnel floor heave (TFH) in high water pressure environments affects high-speed railway safety. Water-induced mudstone swelling impacts track structure.
Key Innovation: Refined finite element simulation model considering cohesive zone model and concrete damage plastic to study the influences of confining pressures and inverted arch thicknesses.
105. Experimental and theoretical study on the shield tunneling model for gas-bearing strata based on image processing
Core Problem: Gas reservoirs pose risks during shield tunneling. Understanding the deformative mechanism of gas-bearing soils induced by shield excavation is vital.
Key Innovation: Physical model tests simulating gas-bearing strata with PIV analysis to study support pressure, pore pressure, and surface settlement, improving column hole shrinkage theory.
106. Analysis of scour-driven performance loss in battered drilled-shaft bridge foundations in a Korean macrotidal-estuary case
Core Problem: Scour in macrotidal estuaries causes performance loss in bridge foundations. High-resolution hydrographic surveys are needed to assess the impact.
Key Innovation: Fusing hydrographic surveys with nonlinear pile-soil interaction analysis to reconstruct construction-stage performance loss and local failures of battered drilled-shaft bridge foundations.
107. Field test and numerical simulation study of geogrid reinforced gradient pile-supported embankment for controlling the settlement of bridge approach on expressways
Core Problem: Differential settlement between bridge abutments and embankments leads to expressway bridgehead bumps. Existing research hasn't fully explored the influence of pile spacing, geogrid configuration, and pile arrangement on soil arching and differential settlement.
Key Innovation: Detailed field monitoring and finite element simulation of geogrid-reinforced floating pile-supported embankments to control bridge approach settlement, optimizing pile spacing and geogrid layers.
108. Mechanism and deformation characteristics of stress isolation method in controlling differential settlement of the subgrade widening over soft soil foundation
Core Problem: Differential settlement in subgrade widening projects on soft soil foundations. Conventional methods are not effective enough.
Key Innovation: Introducing a Stress Isolation Method using steel sheet piles to hinder lateral stress transfer, reducing settlement and horizontal displacement in the existing subgrade.
109. A Simplified Model to Predict Critical Shear Stress in Plastic Soils for Bridge Scour
Core Problem: Accurate prediction of bridge scour requires estimating critical shear stress of plastic soils, but existing models have limitations and require numerous soil parameters.
Key Innovation: Developing a simplified empirical model using electrical resistivity and other soil parameters to predict critical shear stress, improving bridge scour prediction accuracy.
110. Failure area change estimation and tunnel face pressure characteristics of large soil-covering tunnel tests
Core Problem: Estimating tunnel face earth pressure is essential for determining limit support pressure in shield tunneling, and the accuracy depends on the appropriate setting of the failure zone prism.
Key Innovation: Proposing an improved method for estimating the height of the failure zone prism using a logistic equation, validated by tunnel tests with large soil cover ratios.
111. Observed performances and spatial effects of a set of 40 m ultra-deep rectangular excavations in Shanghai soft soils
Core Problem: Deep excavations in urban environments induce deformations and environmental impacts, requiring careful monitoring and understanding of spatial effects.
Key Innovation: Presenting observed performances of five ultra-deep rectangular excavations in Shanghai soft soils, analyzing spatial effects and providing valuable reference for future designs.
112. Unified pseudo-static seismic reduction factors for shallow foundations via an earth-pressure framework
Core Problem: Evaluating seismic bearing capacity of shallow foundations requires a physically consistent method, and classical earth pressure theory can be leveraged.
Key Innovation: Developing a unified method for evaluating seismic bearing capacity based on earth pressure theory, deriving seismic reduction factors in a consistent manner.
113. Geo-mechanical performance of copper slag-infused hybrid geopolymer for stabilising sandy soils under static and cyclic loads
Core Problem: Traditional soil stabilizers like Ordinary Portland Cement (OPC) contribute heavily to carbon emissions, while single-source geopolymers often face limitations in long-term performance.
Key Innovation: Investigating the efficiency of a hybrid geopolymer treatment for sandy soil by incorporating alkali-activated copper slag with a small dosage of OPC to improve strength and stability compared with conventional OPC and single-source copper slag geopolymers.
114. Triaxial creep behaviors of sericite phyllite using data optimization method subjected to loading–unloading cycles
Core Problem: Layered rocks in underground engineering exhibit significant creep effects, leading to localized fractures or long-term instability of surrounding rock masses.
Key Innovation: Investigating the anisotropic creep behavior of sericite phyllite through cyclic loading–unloading creep experiments and proposing a data optimization method based on plastic inheritance.
115. Investigation of equivalent strength parameters of soil-rock mixture using numerical manifold method
Core Problem: Determining equivalent strength parameters of soil-rock mixtures (SRMs) for slope stability assessment.
Key Innovation: Using the numerical manifold method (NMM) to determine equivalent cohesion and internal friction angle of SRMs, considering rock content, size, shape, and orientation.
116. Shakedown analysis of red mudstone fill material with different water contents
Core Problem: Estimating the deformation stability of railway subgrade made of red mudstone fill material (RMF).
Key Innovation: Proposing an energy-based criterion to determine shakedown limits of RMF, considering the effect of water content and microfabric differences.
117. Evaluation of spatial variability characteristics based on anisotropic modes of random fields
Core Problem: Modeling random fields with a focus on analyzing anisotropic spatial variability for geotechnical applications.
Key Innovation: Introducing a new anisotropy index (LS AI) to quantify anisotropy based on autocorrelation length and principal axes orientation within the variogram.
118. A novel coupled progressive corrosion–water hammer inrush model for deep coal seam floors
Core Problem: Understanding and controlling water inrush disasters in deep coal mines.
Key Innovation: Developing a progressive corrosion fracture mechanics (PCFM) model induced by water hammer effects to analyze factors influencing water inrush from concealed faults.
119. An explainable deep learning approach to enhance the prediction of shield tunnel deviation
Core Problem: Improving the prediction accuracy and interpretability of shield position deviations during tunnel construction.
Key Innovation: Introducing an explainable deep learning framework using the Informer model with enhanced attention mechanisms (EAMInfor) and DeepLIFT for feature importance analysis.
120. Ground settlement induced by piggyback shield tunnelling in spatially variable soils: 3D random finite-element modelling
Core Problem: Analyzing ground response to piggyback tunneling in spatially variable soils to improve settlement predictions.
Key Innovation: Developing a 3D random finite element model with Monte Carlo simulations to evaluate the impact of spatial variability on ground settlement and tunnel deformation.
121. Tunnel ahead prospecting methods and intelligent interpretation of adverse geology: A review
Core Problem: Improving geological prospecting and identification of adverse geological features in tunnel construction.
Key Innovation: Reviewing recent advancements in tunnel geological ahead prospecting methods, including airborne, tunnel-based, and borehole-based approaches, and intelligent inversion methods using multi-source data fusion and AI.
122. Time series prediction of tunnel surrounding rock deformation using CPO-CLA integrated model
Core Problem: Predicting tunnel surrounding rock (TSR) deformation, which exhibits time- and space-dependent behavior.
Key Innovation: Applying the crested porcupine optimizer (CPO) to optimize the time series of TSR deformation and proposing an integrated model incorporating CNN, LSTM, and attention mechanism (ATT).
123. Improving Sandstorm Simulations by Parameterizing Form Drag From Subgrid Sand Dunes Using 30‐m‐Resolution Terrain Data
Core Problem: Inaccurate simulation of sandstorms due to inadequate representation of sand dune form drag in weather models.
Key Innovation: Implementation of a sand dune drag scheme in WRF-Chem using 30-m resolution terrain data, reducing wind bias and improving PM10 concentration accuracy.
124. Deciphering the drivers of direct and indirect damages to companies from an unprecedented flood event: A data-driven, multivariate probabilistic approach
Core Problem: The 2021 flood in Germany caused severe damage to companies, and it is important to identify the key factors driving direct damage and business interruption.
Key Innovation: Using probabilistic models to identify key factors driving direct damage and business interruption, highlighting the crucial role of preparedness and early warnings.
125. Paleoseismic history of the intermountain Rieti Basin (Central Apennines, Italy)
Core Problem: Understanding the seismic history of the Rieti Basin in Central Italy, which has been largely overlooked in earthquake studies despite being surrounded by active faults.
Key Innovation: Discovery of evidence of 15 ancient earthquakes over the past ca. 20,000 years through trench analysis, revealing clustered earthquake patterns and potential magnitudes of up to 6.5.
126. A new, high-resolution global reef island database (GRID) with implications for coastal vulnerability
Core Problem: Low-lying coral reef islands face increasing threats from rising sea levels, storms and coastal change.
Key Innovation: The first global map of more than thirty-four thousand reef islands using publicly accessible global spatial and environmental data.
127. Earthquake Catalog and Continuous Waveforms from a Two-Week Distributed Acoustic Sensing experiment on Kefalonia Island, Greece
Core Problem: Creating a detailed catalog of small earthquakes is important for understanding seismic activity.
Key Innovation: Using distributed acoustic sensing (DAS) data with permanent seismic stations to construct a detailed catalog of small earthquakes.
128. Mapping pan-Arctic riverine particulate organic carbon from space (1985 to 2022)
Core Problem: Understanding changes in fluvial particulate organic carbon (POC) concentrations and fluxes in pan-Arctic rivers.
Key Innovation: Satellite-based analysis of POC concentrations and fluxes in pan-Arctic rivers from 1985 to 2022, revealing a net increase in POC export to the Arctic Ocean, driven by increased precipitation and atmospheric warming.
129. Experimental study on critical conditions of ground collapse caused by leakage of pressurized hydraulic pipelines in sandy formations
Core Problem: Urban ground collapse due to pipeline leakage in sandy formations.
Key Innovation: Physical experiments identifying critical conditions for ground collapse and a predictive model based on surface subsidence monitoring.
130. Accelerated Glacier Area Loss and Extinction of Small Glaciers in the Bhutanese Himalaya over the Past Five Decades
Core Problem: Lack of up-to-date glacier inventory and analysis of glacier changes in the Bhutanese Himalaya.
Key Innovation: Three glacier inventories (1976, 1998, 2024) derived from multi-source satellite imagery, revealing accelerated glacier area decrease and extinction.
131. Remote Sensing, Vol. 18, Pages 303: All-Weather Flood Mapping Using a Synergistic Multi-Sensor Downscaling Framework: Case Study for Brisbane, Australia
Core Problem: Timely, high-resolution flood mapping is limited by infrequent satellite revisits and cloud cover.
Key Innovation: Synergistic fusion of data from multiple sensors (Visible Infrared Imaging Radiometer Suite, Advanced Himawari Imager, and Advanced Microwave Scanning Radiometer 2) using surface water fraction as a common variable and downscaling with flood susceptibility and topography information.
132. Remote Sensing, Vol. 18, Pages 301: A Robust Deep Learning Ensemble Framework for Waterbody Detection Using High-Resolution X-Band SAR Under Data-Constrained Conditions
Core Problem: Accurate delineation of inland waterbodies is critical for hydrological monitoring and disaster response, but optical imagery is limited by cloud cover. SAR provides consistent observations, but water/non-water surfaces can be difficult to differentiate.
Key Innovation: A deep learning-based ensemble framework for waterbody detection using high-resolution X-band SAR imagery, incorporating auxiliary geospatial features (height above nearest drainage, slope, and land cover) and combining the outputs of multiple segmentation models.
133. Remote Sensing, Vol. 18, Pages 281: FWISD: Flood and Waterfront Infrastructure Segmentation Dataset with Model Evaluations
Core Problem: Post-disaster damage assessment requires rapid methods, but current remote sensing datasets lack the spatial resolution for detailed evaluation of waterfront infrastructure.
Key Innovation: A new dataset (FWISD) constructed from high-resolution unmanned aerial vehicle imagery captured after a major hurricane, with semantic labels designed to distinguish between intact and damaged structures.
134. Remote Sensing, Vol. 18, Pages 276: Hydrological Changes Drive the Seasonal Vegetation Carbon Storage of the Poyang Lake Floodplain Wetland
Core Problem: Understanding the impacts of hydrological changes on vegetation carbon storage in floodplain wetlands.
Key Innovation: Assessment of seasonal distribution and carbon storage of plant communities in Poyang Lake wetlands using field surveys, literature, and remote sensing data to investigate the impacts of environmental factors.
135. Remote Sensing, Vol. 18, Pages 275: Impacts of Climate Change, Human Activities, and Their Interactions on China’s Gross Primary Productivity
Core Problem: Understanding the spatio-temporal dynamics and driving mechanisms of Gross Primary Productivity (GPP) in China's ecosystems in response to climate change and human activities.
Key Innovation: Quantifying the contributions and interactions of climate, vegetation, topography, and human factors on GPP using the Mann-Kendall test and SHapley Additive exPlanations (SHAP) with GPP data from 2001-2020.
136. Remote Sensing, Vol. 18, Pages 262: Spatiotemporal Characteristics and Attribution of Global Wildfire Burned
Core Problem: A comprehensive understanding of the long-term spatiotemporal characteristics and influencing factors of global wildfires remains limited.
Key Innovation: Analysis of spatiotemporal patterns and influencing factors of wildfires from 1982 to 2018 using a global satellite-derived burned area (BA) product, classifying fire-prone regions based on climate and identifying key drivers.
137. Remote Sensing, Vol. 18, Pages 264: High-Frequency Monitoring of Explosion Parameters and Vent Morphology During Stromboli’s May 2021 Crater-Collapse Activity Using UAS and Thermal Imagery
Core Problem: Volcanic activity at Stromboli fluctuates, and heightened activity can trigger hazardous events like crater collapses. Monitoring changes in geophysical parameters and explosive activity is crucial.
Key Innovation: Integrating high-frequency thermal imaging and high-resolution unmanned aerial system (UAS) surveys to quantify eruption parameters and vent morphology surrounding the May 2021 crater-rim failure, revealing changes in explosion rate, spattering rate, and vent activity prior to the collapse.
138. Remote Sensing, Vol. 18, Pages 267: A Multi-Temporal Sentinel-2 and Machine Learning Approach for Precision Burned Area Mapping: The Sardinia Case Study
Core Problem: Escalating threat of wildfires necessitates rigorous monitoring to mitigate environmental and socio-economic risks. Burned area (BA) mapping is crucial for understanding fire dynamics.
Key Innovation: Develop a high-resolution detection framework specifically calibrated for Mediterranean environmental conditions, ensuring the production of consistent and accurate annual BA maps using Sentinel-2 MSI time series and a Random Forest classifier.
139. Remote Sensing, Vol. 18, Pages 250: Spatiotemporal Dynamics and Drivers of Potential Winter Ice Resources in China (1990–2020) Using Multi-Source Remote Sensing and Machine Learning
Core Problem: Monitoring of ice cover changes is important for climate change studies, but consistent, large-scale, long-term monitoring is challenging.
Key Innovation: A simple and transferable “surface water + land surface temperature (LST)” framework on Google Earth Engine to map potential winter ice area across China from 1990 to 2020.
140. Remote Sensing, Vol. 18, Pages 227: Generative Algorithms for Wildfire Progression Reconstruction from Multi-Modal Satellite Active Fire Measurements and Terrain Height
Core Problem: Wildfire spread prediction models diverge from observed wildfire progression during multi-day simulations, motivating the need for measurement-based assessments of wildfire state and improved data assimilation techniques.
Key Innovation: A conditional Wasserstein Generative Adversarial Network trained on simulations of historic wildfires from the coupled atmosphere–wildfire model WRF-SFIRE, with corresponding measurements for training.