TerraMosaic Daily Digest: June 10, 2026
Daily Summary
The June 10 papers are led by unusually direct evidence for high-energy slope disasters. A Science report on the Tracy Arm landslide-tsunami links glacial retreat, accelerating microseismicity, a 64 million cubic metre failure, a 481 m runup, and a days-long fjord seiche into a single process chain. The Zelunglung rock-ice avalanche study then resolves mobility as a temperature- and composition-sensitive problem: ice fraction, meltwater, and bed wetness govern whether an alpine mass movement remains frictionally limited or evolves into a long-runout river-blocking flow. A debris-flow slit-dam study complements these event reconstructions by showing how coarse-particle concentration and slope jointly control impact force and long-term retention.
The broader issue moves from event physics to operational inference. Xieliupo landslide monitoring combines L-band SAR pixel tracking, corner-reflector validation, kinematic partitioning, and runout scenarios for river-blocking risk. Time-series InSAR and hybrid deep learning are used to predict land subsidence in Donggugang, while basin-scale Sentinel-1 analysis tests whether brine extraction is associated with measurable deformation in the Salar de Atacama. Karst multi-hazard susceptibility mapping formalizes flood-triggered sinkholes as a coupled hazard rather than a single process. Flood papers sharpen the operational chain from building-scale pluvial risk and drainage-network design to SAR flood mapping, runoff process classification, storm-surge evolution, and streamflow-sediment regime shifts. Seismic and underground-engineering papers add micro-mechanical liquefaction precursors, temperature-dependent calcareous-sand liquefaction, cyclic sand failure modes, rock-mass discontinuity extraction, TBM geological prediction, tunnel joint cyclic damage, suction-anchor liquefaction capacity, and long-span bridge bearing uplift.
Key Trends
Five movements define the issue: complete slope-hazard process chains, auditable monitoring, coupled flood systems, seismic failure precursors, and rapidly changing coastal-cryospheric boundaries.
- High-energy slope hazards are being reconstructed as complete process chains: The Alaska fjord landslide-tsunami, Zelunglung rock-ice avalanche, Xieliupo landslide, and binary-size debris-flow impact study all connect preconditioning, triggering, mobility, impact, and downstream blockage or runup.
- Monitoring is becoming physically auditable rather than merely data-rich: L-band SAR offset tracking, TS-InSAR subsidence prediction, basin-scale Sentinel-1 deformation auditing, 3D point-cloud discontinuity extraction, UAV/GPS-free orthophoto mapping, and LiDAR waterline extraction make deformation or terrain state observable in process-relevant variables.
- Flood analysis is moving from maps to coupled urban and hydrologic systems: Building-scale pluvial risk, automated drainage design, storm-surge evolution, SAR flood mapping, hierarchical runoff-process modelling, and Yellow River sediment hysteresis treat flood hazard as a time-dependent network of water, sediment, exposure, and infrastructure.
- Seismic risk is being resolved below the structural-response scale: The Seismic Persistence Index for liquefaction, temperature-sensitive calcareous-sand tests, cyclic sand failure-state identification, suction-anchor pullout under liquefaction, bridge bearing uplift, tunnel-joint cyclic damage, and generalized PBEE resilience all identify failure precursors and recovery states that conventional fragility curves often hide.
- Coastal and cryospheric margins are emerging as linked hazard frontiers: Fjord megatsunami evidence, tropical-cyclone surge clustering, macrotidal sediment-stock reconstruction, nearshore wave learning, snow roughness measurement, and alpine trimline soil studies point to terrain and water boundaries where climate forcing rapidly changes hazard baselines.
Selected Papers
This issue centers on high-energy mass movement and operational hazard inference: fjord landslide-tsunami evidence, rock-ice avalanche mobility, debris-flow barrier impacts, landslide deformation and runout prediction, subsidence, karst multi-hazard susceptibility, pluvial and coastal flooding, seismic liquefaction, tunnel response, and coastal terrain monitoring. This issue contains 40 selected papers from 1,964 papers analyzed.
1. A 481-meter-high landslide-tsunami in a cruise ship-frequented Alaska fjord
Core Problem: Climate-conditioned fjord slopes can fail into increasingly trafficked waterways, but complete evidence linking precursory seismicity, failure volume, wave runup, and basin seiche remains rare.
Key Innovation: Documents a >64 million cubic metre Tracy Arm landslide, 481 m runup megatsunami, accelerating microseismicity, global seismic waves, and a days-long landslide-induced fjord seiche.
2. Factors regulating rock-ice avalanche mobility: insights from the 2020 Zelunglung event
Core Problem: Long-runout rock-ice avalanches in high mountains are controlled by ice, water, temperature, and bed wetness, but these controls are difficult to isolate from post-event deposits alone.
Key Innovation: Reconstructs the Zelunglung avalanche with field evidence and numerical modelling to quantify how ice-water fractions and wet beds regulate mobility and river blockage.
3. Impact behavior and long-term retention mechanism of binary-size debris flows against a slit dam
Core Problem: Boulder-rich debris flows can sharply amplify impact forces on slit dams, yet the role of coarse-particle concentration under different slopes is not well quantified.
Key Innovation: Uses coupled VOF-DEM modelling to resolve muddy fluid and coarse-grain phases and evaluate impact dynamics and long-term retention efficiency.
4. Spatiotemporal Deformation Monitoring and Failure-Runout Process Prediction of the Xieliupo Landslide
Core Problem: The Xieliupo landslide threatens river blockage in the tectonically active Bailong River Basin, but steep terrain limits conventional InSAR monitoring.
Key Innovation: Combines Lutan-1 L-band SAR offset tracking, time-series analysis, corner-reflector validation, deformation partitioning, and runout simulation scenarios.
5. A hybrid deep learning model for land subsidence prediction based on TS-InSAR: a case study of Donggugang
Core Problem: Uneven subsidence in Donggugang has caused cracks and building damage, requiring predictive models that separate long-term and periodic deformation components.
Key Innovation: Integrates SBAS-InSAR, wavelet decomposition, LSTM trend prediction, and CNN-Attention-BiLSTM periodic modelling for interpretable subsidence forecasting.
6. Multi-hazard susceptibility mapping in a karst context using a machine-learning method (MaxEnt)
Core Problem: Karst terrains can generate coupled hazards such as flood-triggered sinkholes, but multi-hazard susceptibility mapping has focused mainly on mountains, coasts, and volcanoes.
Key Innovation: Applies MaxEnt to characterize karst-specific multi-hazard susceptibility in the Val d'Orleans region of France.
7. Characterizing the micro-mechanical triggering of liquefaction via the Seismic Persistence Index
Core Problem: Liquefaction prediction needs micro-mechanical precursors that reveal instability before macroscopic collapse, beyond coordination-number metrics.
Key Innovation: Introduces the Seismic Persistence Index to quantify granular contact-network memory and identify abrupt pre-collapse changes in DEM simulations.
8. Efficient Method for Identification of Rock Mass Discontinuities Using 3D Point Cloud Data
Core Problem: Discontinuity geometry controls rock-mass strength and slope or tunnel stability, but extracting planes from dense point clouds remains computationally difficult.
Key Innovation: Builds a semi-automatic workflow using normal-vector estimation, curvature filtering, clustering, density-based segmentation, and PCA orientation fitting.
9. A high-resolution framework for urban pluvial flood risk mapping
Core Problem: Pluvial flood risk varies at building scale because hazard depth, social vulnerability, exposure, mobility, and accessibility do not coincide spatially.
Key Innovation: Implements the IPCC risk concept with hydrodynamic simulation, land use, drainage capacity, exposure, and socioeconomic vulnerability for Hamburg.
10. An end-to-end framework for semi-automated and cost-effective urban drainage system design: integrating deep learning, topology generation, and multi-objective optimization
Core Problem: Extreme rainfall and urbanization expose the limits of experience-based drainage design, which often lacks global optimization and cost-performance balance.
Key Innovation: Combines DeepLabv3+ land-use mapping, hydrological characterization, network topology generation, capacity calculation, and multi-objective optimization.
11. Characterization of tropical cyclone surge evolution
Core Problem: Surge timing and hydrograph shape influence coastal flooding and evacuation decisions, but risk analysis often reduces storms to peak water levels.
Key Innovation: Uses two decades of ADCIRC hindcasts and unsupervised clustering to classify physically interpretable tropical-cyclone surge-evolution patterns.
12. Near Real-Time Single-Image SAR Flood Mapping With Synthetic Pre-Event Reference: On-Demand COSMO-SkyMed Case Study
Core Problem: Emergency SAR flood mapping is often delayed or degraded when a suitable pre-event image is unavailable.
Key Innovation: Generates a physically consistent synthetic pre-event SAR baseline from soil-moisture and backscatter modelling to support near-real-time single-image flood mapping.
13. A hierarchical hybrid flood modeling framework: deconstructing runoff response into initiation states and generation processes
Core Problem: Flood models often compress runoff initiation and runoff generation into static parameters, masking process heterogeneity across events.
Key Innovation: Separates runoff initiation states from dominant generation mechanisms and uses interpretable machine learning to dynamically classify hydrologic response.
14. Shifts of Streamflow-Sediment Relationships Across Multi-Temporal Scales in the Yellow River
Core Problem: Streamflow-sediment coupling in large rivers changes across annual, monthly, and flood-event scales, affecting reservoir operation and basin management.
Key Innovation: Analyzes Yellow River streamflow-sediment load relationships and hysteresis patterns from the 1950s to 2022 across multiple temporal scales.
15. A generalized framework for performance-based earthquake engineering: integrated assessment of structural reliability and resilience
Core Problem: Conventional PBEE often separates damage exceedance from recovery, limiting treatment of repeated seismic loading and time-dependent resilience.
Key Innovation: Embeds damage and recovery in continuous-time Markov dynamics to jointly estimate reliability, resilience, and post-event restoration.
16. Predictive framework for liquefaction-induced pullout capacity of suction anchors in floating offshore wind systems
Core Problem: Floating offshore wind suction anchors may lose capacity under earthquake-induced liquefaction, but design frameworks for partial liquefaction remain limited.
Key Innovation: Uses 3D finite-element liquefaction analysis to derive predictive failure-envelope equations for suction-anchor pullout capacity.
17. Seismic-induced bearing uplift in long-span deck-type arch bridges: Analysis and mitigation under near-fault ground motions
Core Problem: Near-fault pulse-like ground motions can cause bearing uplift and collision in long-span arch bridges, but the mechanism is underexamined.
Key Innovation: Models bearing uplift stages under three-directional near-fault excitation and evaluates spandrel structural segmentation as mitigation.
18. Numerical investigation on hysteretic behavior and damage accumulation mechanism of segmental joints under cyclic loading conditions
Core Problem: Segmental shield-tunnel joints control seismic performance, but their cyclic hysteresis and damage accumulation are difficult to quantify.
Key Innovation: Develops a validated 3D finite-element model to resolve joint hysteresis, bolt plasticity, contact state, stiffness degradation, and energy dissipation.
19. Bayesian continual learning and dynamic uncertainty quantification framework for TBM geological prediction in non-stationary environments
Core Problem: TBM geological prediction degrades as ground conditions, sensor noise, and cross-line distributions change during long-distance tunnelling.
Key Innovation: Introduces Bayesian continual learning that updates geological prediction while separating epistemic uncertainty from aleatoric noise.
20. Assessing soil organic carbon stability along a toposequence as a function of water and tillage erosion by in-situ soil respiration measurements: A case study for a Belgian silt-loam cropland
Core Problem: Water and tillage erosion redistribute soil carbon along slopes, but the stability of eroded versus depositional carbon pools is not well constrained in situ.
Key Innovation: Uses toposequence sampling and in-situ soil respiration to link sediment transfer, carbon burial, mineralization rates, and organic matter recalcitrance.
21. Tracing soil redistribution rates following harvesting in northern hardwood forests using 239+240Pu isotopes
Core Problem: Whole-tree harvesting can accelerate erosion and deposition, yet long-term redistribution rates remain difficult to quantify in acidic forest soils.
Key Innovation: Applies plutonium isotopes as tracers to estimate post-harvest soil redistribution rates and validate geomorphic impacts decades after harvesting.
22. Enhanced Waterline Extraction From Airborne LiDAR Data Using Automated Density-Based Clustering
Core Problem: Shoreline monitoring from airborne LiDAR requires robust land-water interface extraction under variable terrain and hydrodynamic conditions.
Key Innovation: Uses automated density-based clustering to extract waterlines from airborne LiDAR and support coastal evolution monitoring.
23. Four decades of morphological changes at a macrotidal bay: High-resolution intertidal sediment stock monitoring and uncertainty quantification
Core Problem: Long-term intertidal sediment-stock monitoring needs uncertainty-aware DEM reconstruction from irregular satellite-derived waterlines.
Key Innovation: Develops an empirical uncertainty framework linking waterline availability to local elevation error and site-integrated volumetric uncertainty.
24. Physics-Guided Spatiotemporal Learning for Coastal Wave Peak Period Estimation from Video
Core Problem: Nearshore wave peak periods are central to coastal hazard assessment, but buoy and radar networks provide limited spatial coverage.
Key Innovation: Combines passive coastal video, sim-to-real transfer learning, and physics-informed regularization to estimate wave peak periods.
25. GROMS: GPS-free real-time UAV orthophoto mapping via terrain constraint monocular SLAM
Core Problem: Rapid UAV mapping in disaster terrain can fail where GPS is unavailable and image drift accumulates.
Key Innovation: Uses DEM and satellite imagery as map priors to constrain monocular SLAM and produce real-time orthophotos without GNSS or IMU measurements.
26. Characterizing snow roughness: A novel low-cost portable tool based on ChArUco board and digital photography
Core Problem: Snow roughness controls atmosphere-surface exchange, wind transport, and remote-sensing signals, but field measurement is often expensive.
Key Innovation: Builds a low-cost digital-photography and ChArUco-board system for high-resolution snow surface profiling under variable field conditions.
27. Prediction of Mode I Fracture Behavior of Granite Under NSCB Configuration Using a Multi-task Conditional Generative Adversarial Network and Phase-Field Method
Core Problem: Real-time assessment of granite fracture behavior is limited by expensive experiments and computationally heavy simulations.
Key Innovation: Links stochastic mesostructure reconstruction, phase-field fracture simulation, and multi-task conditional GAN prediction for crack paths and toughness.
28. Smart Earth for CO2 geological storage (CGS): A geophysical perspective on integrated multi-domain monitoring
Core Problem: CO2 storage integrity requires monitoring systems that integrate satellite, airborne, offshore, surface, and downhole observations rather than isolated sensors.
Key Innovation: Proposes a multi-domain Smart Earth architecture for geophysical monitoring and intelligent decision support in geological storage.
29. Novel cable stay reinforced offshore wind turbine resisting combined seismic, wind and wave loading
Core Problem: Large offshore wind turbines in seismic regions face coupled wind, wave, and earthquake loading that can exceed conventional monopile design assumptions.
Key Innovation: Tests cable-stay reinforcement for a 15 MW offshore wind turbine under combined seismic, wind, and wave load cases.
30. Seismic performance enhancement of a three-dimensional isolation system under near-fault ground motions: IDA-based fragility analysis
Core Problem: Near-fault earthquakes impose strong vertical and horizontal demands that conventional base isolation systems may not adequately reduce.
Key Innovation: Combines lead rubber bearings with a vertical ring-spring isolator and evaluates fragility through nonlinear time-history and IDA analyses.
31. Dynamic response and fragility assessment of nuclear piping systems under aircraft impact and beyond-design-basis seismic events
Core Problem: Nuclear piping safety under beyond-design-basis impact and seismic floor motions requires experimentally calibrated fragility assessment.
Key Innovation: Combines electromagnetic vibration tests, impact-induced excitation, finite-element calibration, and fragility analysis for nuclear piping assemblies.
32. Assessment of wind damage risk to urban trees through a real-time quantitative framework: a multi-disciplinary approach with a case study at Beijing Forestry University
Core Problem: Urban tree failures during extreme wind events threaten dense built environments, but risk assessment must connect defects, exposure, and canopy-level wind.
Key Innovation: Integrates GPR defect characterization, finite-element stability factors, CFD microscale wind prediction, and real-time forecast translation.
33. Basin-wide assessment of land deformation in the Salar de Atacama (2019-2024) and implications for monitoring under brine extraction
Core Problem: Centimeter-scale subsidence claims in the Salar de Atacama require basin-wide geodetic testing before deformation can be attributed to brine extraction.
Key Innovation: Uses Sentinel-1 SBAS-InSAR for 2019-2024 to show heterogeneous millimetre-scale motion, no clear basin-wide subsidence, and the need for integrated hydrogeological-geodetic monitoring.
34. Geochemical footprints of climate-driven increases in groundwater contributions in a Canadian Rocky mountain watershed
Core Problem: Mountain watersheds are changing as warming alters precipitation, streamflow sources, and groundwater contributions.
Key Innovation: Combines geochemical tracers, concentration-discharge relationships, mass balance, trend analysis, and causal inference to quantify groundwater increases.
35. Temperature-dependent liquefaction behavior of fiber-reinforced calcareous sand
Core Problem: Thermally active foundations and tropical calcareous sands require liquefaction models that account for coupled temperature, fiber content, and cyclic stress effects.
Key Innovation: Uses undrained cyclic triaxial tests to quantify temperature-dependent pore-pressure generation, stiffness degradation, damping, and a predictive model for fiber-reinforced calcareous sand.
36. Deformation Characteristics and Failure Patterns of Sands under Nonsymmetrical Cyclic Loading: Micromechanical Insights
Core Problem: Undrained sands under nonsymmetrical cyclic loading can fail through multiple modes that are difficult to distinguish using macroscopic response alone.
Key Innovation: Uses grain-scale simulations to link cyclic failure modes, fabric evolution, redundancy index, and contact-based state parameters for liquefaction-resistance characterization.
37. Drainage evolution, fluvial denudation and differential uplift of the Atlantic/Mediterranean watersheds, inferred from geomorphic metrics (Northern Spain)
Core Problem: Contrasting Atlantic and Mediterranean watersheds in northern Spain record differential uplift and denudation that condition long-term topographic evolution.
Key Innovation: Combines catchment-scale geomorphic metrics, eroded-volume estimates, and isostatic uplift calculations to interpret drainage evolution.
38. A systemic and anticipatory framework for underground urban space planning using foresight methods
Core Problem: Urban underground space planning remains fragmented despite its importance for climate adaptation, infrastructure resilience, and dense-city risk management.
Key Innovation: Compares foresight methods and integrates systems planning, transition management, and futures studies for anticipatory underground-space governance.
39. LCS-Net: a lightweight architecture for efficient coastal water segmentation
Core Problem: Near-shore water boundaries in high-resolution imagery are fragmented and shadowed, challenging edge-deployable segmentation for coastal monitoring.
Key Innovation: Introduces a lightweight coastal-water segmentation architecture using dynamic feature filtering and bypass compensation for efficient deployment.
40. Vegetation-dependent soil organic carbon fractions and their drivers at the southern margin of Eurasian permafrost
Core Problem: Permafrost degradation changes soil carbon stabilization, but vegetation controls on particulate and mineral-associated carbon remain uncertain.
Key Innovation: Compares wetland and forest soil profiles along the southern Eurasian permafrost margin to quantify vertical carbon fractions and drivers.