The team focused on a type of structure that is deceptively common: a bridge pier founded on a group of piles, embedded in a slope affected by a slow-moving landslide. Unlike catastrophic, fast-moving slope failures that destroy bridges in seconds, slow-moving landslides creep at rates of millimeters to centimeters per year, often going unnoticed until cumulative deformation begins to distort the superstructure or crack the foundations. Yet these quiescent masses of soil are not necessarily benign. When an earthquake arrives, the weakened, sheared, and sometimes saturated landslide material can be reactivated, subjecting the piles to a combination of inertial forces from the shaking structure and kinematic forces from the moving ground. The study’s central question was deceptively simple: does the state of the slope before the earthquake matter for the pier’s seismic performance?

To answer it, the researchers built a nonlinear finite element model of the coupled soil-foundation-structure system, using a reference case study chosen precisely because it is paradigmatic of the numerous Italian bridges located in areas exposed to both seismic and hydrogeological hazards. Bridge piers, after all, may sit on the crest of a slope, along its face, or downstream of it, and the relative position of the bridge and the slope strongly influences the type and severity of the actions the structure must resist. The numerical model captured the essential mechanics of the problem: the nonlinear, strain-dependent behavior of the soil under cyclic loading, the interaction between the piles and the surrounding ground, and the dynamic response of the pier itself.

The analysis compared three distinct scenarios. In the first, the pier stands in a stable slope, representing the conventional design assumption in which the ground is competent and the only seismic demand comes from the shaking itself. In the second, the slope hosts a quiescent landslide that the earthquake reactivates, so the ground begins to move as the shaking progresses. In the third, the landslide is already active before the earthquake, meaning the piles have already accumulated deformation and stress from the creeping soil. This progression allowed the researchers to isolate the influence of pre-seismic slope conditions on the dynamic response of the pier, something that standard seismic assessment procedures, which typically assume stable ground, simply do not address.

The results, expressed in terms of maximum and residual displacements and rotations of the pier, show that the starting condition of the slope is far from a secondary detail. When the landslide is active before the earthquake, the piles enter the seismic event already stressed and deformed, and the ground movement during shaking adds kinematic demands on top of the inertial ones. The interaction between the two loading mechanisms can amplify displacements and, critically, leave the pier with larger residual deformations after the shaking stops. Residual displacement matters enormously for bridges, because permanent tilting or lateral shifting of a pier changes the geometry of the deck, alters load paths, and can compromise serviceability or trigger collapse even when the structure survives the earthquake itself.

Underpinning these findings is the physics of soil-structure interaction, a phenomenon that simplified design methods often reduce to a set of springs or, worse, ignore altogether. In reality, the piles, the surrounding soil and the pier form a single dynamic system whose response depends on the stiffness and damping of every component. Decades of research, from classical work on dynamic pile stiffness to modern studies of kinematic pile bending in layered soils, have shown that the ground is not a passive support but an active participant in the seismic response. The new study extends this understanding to the multi-hazard setting, demonstrating that the dynamic properties of a slope containing a landslide mass differ from those of a stable slope, and that these differences propagate directly into the demands on the foundation.

The Italian context gives the work particular urgency. The national landslide inventory compiled by the Institute for Environmental Protection and Research documents hundreds of thousands of landslide phenomena across the country, and recent research has catalogued extensive interactions between landslides and bridge foundations in Italian case studies. At the same time, Italy has endured repeated bridge failures, some linked to the degradation of structures subjected to unanticipated environmental actions. The national guidelines for classifying and managing the risk of existing bridges, introduced in 2020 and operationalized in subsequent years, pushed owners to assess their assets systematically, and recent technical guidance has begun to address landslide interaction explicitly. The new study provides a quantitative basis for that effort, showing what is at stake when a bridge pier’s foundation crosses a slowly moving mass of soil.

What makes the study especially valuable for practitioners is its methodological clarity. By using a nonlinear finite element approach within a single consistent model, the researchers could track the full path from static slope condition to dynamic seismic response, capturing the state of stress and strain in the soil at the moment the earthquake begins. This matters because the initial stress state governs how the soil stiffens or softens under cyclic loading, how pore pressures evolve, and how much permanent deformation accumulates. The approach also reflects the reality of earthquake-triggered landslide reactivation, a phenomenon documented in devastating detail after events such as the 2008 Wenchuan earthquake in China and the 2016 Kumamoto earthquakes in Japan, where seismically induced slope failures destroyed bridges that had performed adequately under shaking alone.

The broader message is a call for multi-hazard thinking in the assessment and retrofit of existing infrastructure. A bridge evaluated only for seismic loads, assuming stable ground, may be far more vulnerable than its safety factor suggests if it stands in the path of a slow-moving landslide. Conversely, retrofit strategies designed for landslide stabilization alone may leave the structure exposed to seismic demands that the modified soil-foundation system now transmits differently. The authors argue that accounting for soil-foundation-structure interaction is essential when assessing the seismic response of bridge piers in the presence of slow-moving landslides, and that a multi-hazard approach is needed to enhance both the assessment of existing bridges and the sustainability of retrofit strategies. As climate change alters rainfall patterns and slope hydrology, and as seismic hazard remains a permanent feature of the Mediterranean landscape, the quiet creep of a hillside may prove to be the hidden variable that determines whether the next earthquake is survivable for the bridges that carry our lifelines.

Subject of Research: Seismic response of pile-supported bridge piers founded in slopes affected by slow-moving landslides

Article Title: Seismic response of a pile-supported bridge pier under multi-hazard conditions in slow-moving landslides: a numerical investigation

Article References: Ambrosino, A., Servodio, M., Sica, S., Losanno, D., Parisi, F., & Santolo, A. S. D. (2026). Seismic response of a pile-supported bridge pier under multi-hazard conditions in slow-moving landslides: a numerical investigation. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02678-4

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02678-4

Keywords: soil-structure interaction, landslides, earthquake engineering, multi-hazard assessment, bridge piers, pile foundations, finite element analysis, slope stability, seismic retrofit, geotechnical engineering, infrastructure resilience, residual displacement

The earthquake struck within the Kunar-Spin Ghar fault system, a zone of active crustal deformation in the Hindu Kush region where the ongoing convergence between the Indian and Eurasian plates is absorbed through a complex interplay of strike-slip, reverse and transpressional faults. The event caused widespread infrastructure damage, triggered landslides and rock avalanches, and left visible surface deformation across terrain so steep and inaccessible that ground-based investigation was severely limited. For a region with a long and destructive seismic history but sparse instrumental coverage, the quake offered a rare and urgent opportunity to observe how deformation is actually distributed in this part of the collision zone.

Led by Hamedullah Torabi of Kabul Polytechnic University, with colleagues from institutions in Afghanistan, India, South Korea and the United Kingdom, the research team carried out field reconnaissance at accessible sites along the affected valleys. Their observations documented structural damage to buildings, ground cracks, slope failures, rock avalanches and newly emerged springs along the Kunar River valley. These ground effects, recorded in difficult and sometimes dangerous conditions, provided the essential field anchor for interpreting what the satellite data would later reveal. Emergent springs in particular can indicate changes in subsurface permeability caused by shaking and fault movement, offering clues about where the crust was disturbed.

The technological heart of the study lies in Persistent Scatterer Interferometric Synthetic Aperture Radar, or PSInSAR, a technique that tracks millimeter-scale ground movements over time by comparing radar reflections from stable features such as rock outcrops, buildings and boulders. The team analyzed time series of Sentinel-1A radar data acquired by the European Space Agency’s Copernicus mission between April and October 2025, processing both ascending and descending orbital passes. Because each viewing geometry is sensitive to a different combination of horizontal and vertical motion, combining the two allows researchers to decompose the observed radar signal into east-west and vertical components of surface displacement, effectively reconstructing a two-dimensional picture of how the ground moved during the earthquake period.

What emerged from the radar analysis was striking. Both the ascending and descending line-of-sight velocity fields revealed a laterally continuous deformation pattern extending for several tens of kilometres along the strike of the fault system. Decomposition of the signal showed dominant horizontal motion, consistent with the strike-slip and transpressional character of the region, accompanied by broader and spatially variable patterns of uplift and subsidence. In other words, the ground was not simply sliding along one clean break; it was warping, rising and sinking across a wide swath of terrain in a manner that reflects the distributed nature of the forces at work beneath the Hindu Kush.

Swath-profile analysis, which examines how velocities change across cross-sections of the deformed zone, pinpointed the strongest east-west velocity gradients south of the mapped Kunar Fault and within or adjacent to the Spin Ghar mountain-front structural corridor. This detail matters enormously. The most intense deformation did not coincide neatly with the fault trace that appears on existing maps. Instead, it spilled into neighboring structures, indicating that the earthquake-period deformation signal was shared among multiple interacting faults rather than released on a single rupture plane. The pattern is exactly what geologists would expect from distributed transpressional deformation, a regime in which crustal blocks are simultaneously squeezed and sheared, forcing strain to spread across networks of faults rather than concentrate on one master structure.

The concept of transpression, formally described in the structural geology literature in the 1980s, describes deformation that combines pure compression with a component of shear, producing complex fault geometries and strain partitioning. Eastern Afghanistan sits squarely within such a regime. The India-Eurasia collision, which has built the Himalaya and the Tibetan Plateau, transmits enormous compressive stresses deep into the Asian interior, and the Hindu Kush is one of the places where those stresses find release through intracontinental faulting. Previous studies, including GPS-based measurements of plate convergence partitioning in the Pamir-Hindu Kush region and historical catalogs of Afghan earthquakes, have long suggested the region is tectonically active, but the density of observations needed to map how strain is actually distributed has been lacking.

The new results carry a direct and uncomfortable message for seismic hazard assessment. Hazard models typically rely on mapped fault traces to define the locations and widths of potential rupture zones, and building codes and land-use planning follow from those definitions. If deformation in the Kunar-Spin Ghar system is distributed across a corridor tens of kilometres wide rather than focused on individual mapped faults, then hazard assessments based only on those traces may underestimate both the width of the active deformation zone and the spatial extent of ground deformation and secondary hazards such as landslides, rock avalanches and liquefaction. Communities located well away from any mapped fault trace could still sit within the zone of strongest shaking and ground failure in a future event.

The vulnerability of the region amplifies these concerns. Eastern Afghanistan combines steep, landslide-prone topography, dense rural populations living in unreinforced masonry construction, and limited institutional capacity for emergency response, a combination that recent earthquakes in the region have shown to be lethal. The study’s authors, along with earlier researchers who have called for greater earthquake resilience across Central Asia, argue that satellite-based deformation monitoring offers a practical path forward in terrain where traditional field mapping and dense seismic networks are difficult to establish. Because Sentinel-1 radar data are freely available through the Copernicus Open Access Hub, the approach demonstrated here could be extended systematically across Afghanistan and neighboring countries to build a more realistic picture of active deformation corridors.

The 2025 Asadabad-Kunar earthquake lasted only seconds, but its scientific legacy may prove durable. By pairing boots-on-the-ground observation with space-based radar, the research team has shown that the Hindu Kush does not obey the tidy assumption that earthquakes follow the fault lines drawn on maps. The active deformation zone is wider, more interconnected and more structurally complex than previously recognized, and the seismic hazard it poses is correspondingly broader. For the millions of people who live in the shadow of the Spin Ghar mountains, that widened hazard corridor is not an abstract geodynamic detail. It is a warning that the ground beneath their villages can move in places no map currently marks, and that planning for the next earthquake must account for a danger that is distributed, not localized.

Subject of Research: Distributed transpressional deformation and seismic hazard implications of the 2025 Mw 6.0 Asadabad-Kunar earthquake in eastern Afghanistan

Article Title: Evidence for distributed transpressional deformation and seismic hazard implications from the 2025 Mw 6.0 Asadabad- Kunar earthquake, Eastern Afghanistan

Article References: Torabi, H., Kandregula, R. S., Naik, S. P., Shnizai, Z., Ghildiyal, D., Chufal, V. S., & Kim, Y.-S. (2026). Evidence for distributed transpressional deformation and seismic hazard implications from the 2025 Mw 6.0 Asadabad- Kunar earthquake, Eastern Afghanistan. Natural Hazards, 122(18), Article 624. https://doi.org/10.1007/s11069-026-08397-y

Image Credits: AI Generated

DOI: 10.1007/s11069-026-08397-y

Keywords: Afghanistan, Hindu Kush, earthquake, transpressional deformation, PSInSAR, Sentinel-1A, Kunar fault, Spin Ghar, seismic hazard, India-Eurasia collision, strain partitioning, landslides

The study area covers roughly 2,400 square kilometers of mountainous terrain in the Albertine Rift, where altitudes climb from about 810 meters to nearly 3,470 meters from west to east. The climate is tropical with a bimodal rainfall regime: a long rainy season from October to February, a shorter one from March to June, and a dry spell from July to September. Annual rainfall totals between 1,000 and 1,300 millimeters, delivered both by convective storms associated with the Intertropical Convergence Zone and by orographic rain forced upward over the rugged relief. That combination of steep slopes, weathered soils, and intense precipitation makes the landscape inherently unstable, but the researchers emphasize that human activity has dramatically amplified the problem.

Decades of population growth, deforestation for agriculture and fuelwood, artisanal mining, and unregulated rural road construction have stripped hillslopes of their natural protection. Earlier regional studies had already suggested that anthropogenic disturbance interacts with natural controls such as slope gradient, elevation, and rainfall to drive slope failure, but no one had systematically tracked how landslide-affected land actually changed year by year in this part of the rift. The new inventory fills that gap by building a multi-temporal record rather than the single-snapshot surveys that have dominated previous mapping efforts in the eastern Congo.

The team’s primary tool was Google Earth Pro, whose free multi-temporal imagery allowed the researchers to digitize landslide scars as polygons and to distinguish newly initiated failures from the progressive widening of older ones. Because dense vegetation can hide landslide morphology from orbit, the satellite interpretation was cross-checked against archival records from local organizations, including the Action de Développement pour les Milieux Ruraux and the Mission Antiérosive, as well as student theses and field reports from the Institut Supérieur Pédagogique de Walungu. Finally, the researchers validated a representative sample of 904 landslide sites in the field, selected to span the full range of altitude, slope, soil type, land cover, and slope aspect across the study area, within the sectors accessible despite security constraints.

The validation exercise produced strikingly strong results. Of 870 landslides confirmed on the ground, 823 had been correctly identified in Google Earth imagery, while 47 were missed and 34 features were falsely flagged as landslides. That translates into a precision of 96 percent and a recall of 95 percent, figures that held almost identically for both shallow and deep-seated failures. The findings demonstrate that freely available virtual globe imagery, when systematically checked against ground truth, can support reliable landslide inventories in regions that cannot afford commercial very-high-resolution satellite data, although the authors caution that small, partially vegetated failures remain the weakest link in any image-based approach.

The inventory itself catalogued 2,088 landslides covering a total of 528 hectares. Shallow failures, predominantly earth flows, utterly dominate the record: 2,051 events, or 98.2 percent of the total, accounting for just over 79 percent of the affected area, with a mean individual footprint of only 0.20 hectares. Deep-seated landslides are rare, just 37 events, but disproportionately destructive, covering 109 hectares thanks to mean areas of nearly 3 hectares and a maximum of almost 24 hectares. Notably, 81 shallow failures occurred along roads and 46 within active artisanal mining perimeters, underscoring the imprint of infrastructure and extraction on slope stability.

To understand why landslides occur where they do, the team applied a Bayesian Weight of Evidence analysis within a geographic information system, testing seven conditioning factors: slope gradient, slope aspect, curvature, elevation, drainage density, land use and land cover, and soil type. A Chi-square test confirmed that every factor is statistically significantly associated with landslide occurrence, with slope degree showing the strongest dependence. The centered weight values reveal a clear threshold: slopes gentler than 20 degrees are consistently stable, with strongly negative weights, while susceptibility jumps sharply between 25 and 30 degrees, where the positive weight peaks at 3.14. Convex and planar curvatures, higher elevations above 1,800 meters, and positions 400 to 600 meters from stream channels, where fluvial incision undercuts steep valley sides, all show strong positive associations with failure.

The land cover results carry perhaps the most consequential message for policy. Forested and woodland terrain shows a strongly negative weight of minus 3.26, reflecting the protective role of dense root networks, rainfall interception, and evapotranspiration in binding soils together. Cropland and herbaceous cover, by contrast, shows a positive weight of 3.15, and built-up or bare soil surfaces a weight of 2.75. Soil type reinforces the pattern, with shallow Leptosols and deeply weathered Ferralsols both highly susceptible. Together, these relationships describe a coupled natural and human system in which terrain establishes the gravitational framework, drainage controls water movement, soils govern material strength, and vegetation removal dismantles the last line of defense.

The temporal record is equally sobering. The number of mapped landslides grew from 967 in 2015 to 2,088 in 2024, with 1,121 newly initiated failures over the decade and a cumulative net land loss of 278 hectares. The affected proportion of the study area rose from 0.104 percent to 0.220 percent. Activity was strikingly episodic rather than steady: quiet years such as 2017 and 2022 saw only about 3 and 2 hectares of new land loss respectively, while 2019, 2021, and 2024 delivered major pulses of 40, 76, and 100 hectares, the last corresponding to annual area growth of more than 23 percent. Importantly, part of the expansion reflects the progressive widening of existing failures, particularly deep-seated ones that continue deforming long after initial failure, meaning the inventory captures ongoing geomorphic adjustment rather than simply counting isolated new events.

The authors are careful to frame their conclusions as a baseline rather than a definitive predictive model. The Weight of Evidence approach quantifies spatial associations but cannot fully resolve interactions among factors, and the study did not quantitatively analyze rainfall triggers, a task the researchers say will require daily rainfall data and the derivation of local triggering thresholds to support early-warning systems. Armed conflict also prevented exhaustive field validation in some sectors, and the results cannot be directly generalized across the whole of eastern Congo. Still, the study delivers something the region has never had: a field-validated, decade-long, annually resolved account of how a tropical rift landscape is unraveling, and a demonstration that with free imagery, local archives, and determined fieldwork, even the world’s most data-scarce mountains can be brought into the scientific record. As populations keep growing and forests keep receding across the Albertine Rift, that record may prove essential for planning where people can safely build, farm, and live.

Subject of Research: Landslide inventory, dynamics, and predisposing factors in the tropical highlands of eastern Democratic Republic of Congo

Article Title: Landslide inventory and dynamics in the tropical highlands of eastern Democratic Republic of Congo

Article References: Richard, B. C., Jean-Claude, M. M., Léonard, M. K., & Karume, K. (2026). Landslide inventory and dynamics in the tropical highlands of eastern Democratic Republic of Congo. Environmental Challenges, 25, Article 101662. https://doi.org/10.1016/j.envc.2026.101662

Image Credits: AI Generated

DOI: 10.1016/j.envc.2026.101662

Keywords: landslides, Democratic Republic of Congo, South Kivu, Albertine Rift, Google Earth Pro, remote sensing, landslide susceptibility, Weight of Evidence, deforestation, land cover, shallow landslides, deep-seated landslides

The study draws on qualitative field data analysed through a critical-realist and political-economy lens, a methodological combination that allows the researchers to look beyond visible hazards and interrogate the hidden structures that produce them. Rather than treating landslides or dried springs as isolated technical failures, the authors trace them to entrenched mechanisms: political patronage networks that award contracts to allies, weak governance that fails to enforce safety codes, and a dominant narrative that equates infrastructure with development regardless of how it is built. These structures, the paper argues, are not background conditions but active causal engines behind Nepal’s growing disaster toll.

The empirical texture of the research is striking. The authors document bulldozer-led road construction that slices through unstable slopes without adequate drainage or retaining structures, a practice so aggressive that local communities have coined the term ‘dozer terrorism’ to describe it. They describe the annual fiscal-year budget rush, in which local governments scramble to spend allocated funds before the financial year closes, leading to projects approved and executed in weeks with minimal environmental assessment. Tunnel blasting for hydropower schemes has destabilised hillsides and drained the springs that mountain villages depend on for drinking water and irrigation. Unregulated extraction of sand, gravel, and stone from riverbeds and slopes further weakens the terrain, while unsafe settlement expansion pushes homes onto land that engineers would classify as hazardous.

The consequences are already visible across the landscape. The study records slope instability along newly cut road corridors, the drying of natural springs, displacement of communities, and biodiversity loss in fragile mid-hill environments. Crucially, the authors emphasise that these impacts do not remain confined to individual project sites. Disaster risk, they show, extends across roads, rivers, settlements, and entire infrastructure corridors, linking one community’s hazard to another’s downstream vulnerability. A road cut high on a ridge can deliver sediment and debris to villages far below; a tunnel that drains an aquifer can force families to abandon land their grandparents farmed for generations.

What makes the study analytically distinctive is its refusal to treat development as inherently safe or inherently risky. The authors argue that outcomes hinge on how, by whom, and under what conditions development is pursued. The same road, built with proper geological assessment, drainage design, and community consultation, can transform livelihoods; built hastily under patronage pressure, it becomes a scar that sheds landslides for decades. This reframing challenges both the triumphalist infrastructure narrative that dominates national politics and the simplistic view that all development in fragile mountains is destructive. The problem, in other words, is not development itself but the political economy that shapes its execution.

The critical-realist framework the researchers employ deserves attention in its own right. Drawing on the philosophy of Roy Bhaskar and the tradition of realist social science, the study seeks to identify the underlying generative mechanisms—patronage, fiscal incentives, institutional weakness—that produce observable events such as unsafe construction and subsequent slope failure. By blending this ontology with political-economy analysis, the authors offer what they describe as a methodological path for future research on the development-disaster interface, one that moves beyond correlational studies of hazards and toward explanations of why risky practices persist despite their known consequences.

The political-economy dimension of the analysis resonates with a broader international literature on disasters and corruption. Previous research has shown that corrupt practices in the construction industry, from substandard materials to rigged procurement, measurably increase disaster losses, and that the political economy of ‘natural’ disasters often determines who suffers and who profits. The Nepal study extends this line of inquiry into a mountain setting where the physical fragility of the terrain amplifies every governance failure. It also connects to earlier work by Nepali and international scholars documenting how road building in the Himalaya has repeatedly increased landslide activity, and how haphazard urbanisation in the Kathmandu Valley has followed a similar logic of risk creation.

The timing of the study is significant. Nepal’s post-2015 federal restructuring devolved substantial planning and budget authority to local governments, unleashing an unprecedented wave of rural infrastructure construction. While this decentralisation has delivered roads and electricity to communities long neglected by the centre, the new study suggests it has also multiplied the sites at which risk is being manufactured, often by local institutions that lack the technical capacity, environmental safeguards, or accountability mechanisms to build safely. The authors warn that disaster risk is likely to expand further as development penetrates ever more fragile landscapes and creates new exposure in places that previously had little built infrastructure at all.

The paper’s central prescription is correspondingly radical. Building mountain safety, the authors argue, demands more than coping capacity, early warning systems, or hazard management. It requires rethinking the very development processes that produce risk in the first place. Without a shift toward transparent, accountable, and risk-informed planning, Nepal’s present rural development model will, in the authors’ words, continue to normalise risk, reproduce disasters, and deepen vulnerabilities in the name of development. That means enforcing environmental impact assessment, curbing the fiscal-year spending rush, subjecting contract allocation to genuine public scrutiny, and treating geological and hydrological evidence as binding constraints rather than inconvenient formalities.

For the wider disaster research community, the study is a pointed reminder that the line between development and disaster is thinner than policy frameworks usually acknowledge. Every bulldozed slope, every blasted tunnel, and every budget-deadline project embeds decisions about risk into the physical landscape, decisions that will surface years later as landslides, floods, and displacement. The Nepal Himalaya, where some of the world’s most energetic tectonics meet some of the world’s most ambitious rural infrastructure ambitions, offers perhaps the sharpest available illustration of this development-disaster interface. Whether the region’s roads and dams become instruments of resilience or engines of catastrophe will depend not on the mountains, but on the politics that shape how they are built.

Subject of Research: Political economy of development-induced disaster risk creation in the Nepal Himalaya

Article Title: Development-disaster interface: Political economy of development-induced risk creation in the Nepal Himalaya

Article References: Development-disaster interface: Political economy of development-induced risk creation in the Nepal Himalaya. (n.d.). https://doi.org/10.1007/s13412-026-01139-3

Image Credits: AI Generated

DOI: 10.1007/s13412-026-01139-3

Keywords: Nepal, Himalaya, disaster risk, development, political economy, road construction, hydropower, landslides, critical realism, vulnerability, infrastructure governance, haphazard planning

The research team, led by Li Chuanyou of the State Key Laboratory of Earthquake Dynamics and Forecasting at the Institute of Geology, China Earthquake Administration, together with colleagues including Sun Kai, Li Junjie, Li Yanbao, and Liang Mingjian of the Earthquake Administration of Sichuan Province, conducted systematic field investigations around both epicenters. Their work combined geological mapping of surface deformation, documentation of earthquake environmental effects such as landslides and rockfalls, analysis of focal mechanism solutions, and relocation of aftershock sequences. This multi-pronged approach is essential in mountainous terrain like western Sichuan, where dense vegetation, steep topography, and limited road access make it difficult to trace active faults at the surface, and where the seismogenic structure of an earthquake often must be inferred indirectly from the pattern of damage and the distribution of aftershocks at depth.

The Lushan earthquake carried particular scientific weight because of its location and its history. The event occurred in the southwestern section of the Longmenshan fault zone, the same thrust belt that produced the catastrophic 2008 Wenchuan earthquake, a magnitude 7.9 disaster that killed nearly 90,000 people. It also occurred near the source area of the 2013 magnitude 7.0 Lushan earthquake, and from the moment the ground began shaking in June 2022, scientists debated two questions: was the new event simply an aftershock of the 2013 mainshock, and did it rupture within the so-called seismic gap that has long been identified between the Wenchuan and Lushan rupture zones? The Dayi gap, as it is sometimes called, is regarded by many researchers as a segment of the Longmenshan belt that has accumulated significant stress without releasing it, making it a candidate for a future large earthquake.

To resolve these questions, the team documented the distribution of coseismic effects across the epicentral region. Their surveys revealed a pronounced asymmetry. On the southeastern side of the epicenter, landslides and rockfalls triggered by the shaking were sporadic and small in scale. On the northwestern side, by contrast, the effects were far denser and larger, with the most severe concentration of landslides and secondary geologic impacts lining the Donghe River valley from the north of Baoxing County down to Yanjing township. This kind of asymmetric damage pattern is a classic diagnostic tool in earthquake geology: because shaking intensity and ground failure tend to be strongest on the hanging wall of a thrust fault and in the direction of rupture propagation, the distribution of landslides can point investigators toward the orientation and dip of the fault plane that slipped at depth.

When the field observations were combined with the focal mechanism solution of the mainshock and the relocated aftershock sequence, a coherent picture emerged. The seismogenic structure of the 2022 Lushan earthquake, the researchers conclude, is most likely a northwest-directed back-thrust fault situated between the Yanjing-Wulong fault and the Shuangshi-Dachuan fault. This structure is interpreted as a small secondary fault of the Shuangshi-Dachuan fault system rather than one of the primary through-going thrusts of the Longmenshan belt itself. The finding matters because it refines the long-running debate over the architecture of the southwestern Longmenshan zone, where multiple imbricated thrust sheets stack against the eastern margin of the Tibetan Plateau. It also bears directly on the seismic gap question: if the 2022 event broke a minor back-thrust rather than the main gap-forming structure, then the hazard represented by the gap itself may remain largely unaddressed by this moderate earthquake, a conclusion with significant implications for hazard assessment in the densely populated Sichuan Basin margin.

Nine days later and far to the northwest, the Maerkang earthquake swarm posed an entirely different set of puzzles. The magnitude 6.0 main event of the swarm occurred in the northwestern segment of the Songgang Fault, an area that has received comparatively little research attention and where interpretations of fault activity have varied widely. Unlike a classic mainshock-aftershock sequence, a swarm consists of many earthquakes of comparable size occurring over days to weeks without a single dominant event, a behavior often associated with complex fault geometry, fluid involvement, or an immature fault zone that has not yet developed a single smooth rupture surface. The Songgang Fault’s northwestern segment, the study finds, fits this description well: it is an immature section with a complicated internal structure, which helps explain why the swarm behaved the way it did.

One of the most intriguing results from Maerkang concerns the surface deformation itself. Damage to buildings, ground fissures, and landslides triggered by the swarm did not align along the main trace of the Songgang Fault, as one would expect if the primary fault had ruptured. Instead, the deformation formed a linear belt located east of, and nearly parallel to, the main fault trace. This offset pattern was a decisive clue. When the team integrated it with aftershock relocations and focal mechanism solutions, the conclusion became clear: the earthquake rupture did not occur along the main Songgang Fault at all, but along a branching fault situated to its east. In other words, even in a region where the mapped master fault appears to be the obvious suspect, the actual seismogenic structure turned out to be a subsidiary strand that had escaped detailed characterization, precisely because it is less prominent in the landscape and less studied in the literature.

Taken together, the two investigations point to a unifying interpretation. Both the magnitude 6.1 Lushan earthquake and the magnitude 6.0 Maerkang swarm occurred on secondary faults, and both are best understood as expressions of the same regional tectonic engine: the ongoing, unified movement of the Bayan Har block as it is squeezed eastward by the collision between India and Eurasia. The Bayan Har block has been responsible for a remarkable series of large earthquakes over the past two decades, including the 2008 Wenchuan event, the 2010 Yushu earthquake, the 2013 Lushan earthquake, the 2021 Maduo earthquake, and now the 2022 pair. As the block moves, stress is transferred to its boundaries and to the network of smaller faults that accommodate deformation within and around it, and the new study demonstrates that these smaller structures can fail in moderate earthquakes even when the major boundary faults remain locked.

The practical implications for seismic hazard assessment in western Sichuan are considerable. First, the results underscore that hazard maps built around major fault traces alone may underestimate the risk posed by unmapped or poorly characterized secondary faults, which are clearly capable of producing damaging magnitude 6 events. Second, the finding that the 2022 Lushan earthquake likely did not rupture the main seismic gap structure suggests that the gap remains a source of concern, and that stress in the southwestern Longmenshan belt may not have been meaningfully relieved by the recent event. Third, the Maerkang results show that immature fault zones with complex branching geometry can produce swarm-like sequences whose surface signatures are misleading, complicating rapid post-earthquake response and the siting of critical infrastructure such as dams, bridges, and hydropower stations, several of which are planned or operating along the rivers of this region. The authors’ field documentation, including the detailed mapping of landslide distributions along the Donghe River valley and the deformation belt east of the Songgang Fault, provides a valuable baseline dataset for engineers and planners.

More broadly, the study is a reminder of how much remains to be learned about the fine structure of active fault systems, even in regions that have been intensively studied after major disasters. The researchers acknowledge that the northwestern Songgang Fault segment, in particular, has seen limited prior investigation, and their work highlights the value of deploying field teams quickly after significant events, while surface evidence is fresh and before erosion, construction, and repair erase the record. By combining traditional geological fieldwork with modern seismological tools such as aftershock relocation and focal mechanism analysis, the team has shown that the earthquakes of western Sichuan cannot be understood fault by fault in isolation; they must be read as chapters in a single, ongoing story of crustal deformation driven by the Bayan Har block. As that block continues to move, the secondary faults it activates will remain an essential, and sometimes dangerous, part of the region’s seismic future.

Subject of Research: Seismogenic structures of the 2022 Lushan earthquake and Maerkang earthquake swarm in western Sichuan, China

Article Title: Seismogenic structures of the 2022 MS6.1 Lushan earthquake and the MS6.0 Maerkang earthquake swarm in western Sichuan, China

Article References: Chuanyou, L., Kai, S., Junjie, L., Yanbao, L., & Mingjian, L. (2026). Seismogenic structures of the 2022 MS6.1 Lushan earthquake and the MS6.0 Maerkang earthquake swarm in western Sichuan, China. Natural Hazards, 122(19), Article 640. https://doi.org/10.1007/s11069-026-08375-4

Image Credits: AI Generated

DOI: 10.1007/s11069-026-08375-4

Keywords: Lushan earthquake, Maerkang earthquake swarm, seismogenic structure, Longmenshan fault zone, Songgang Fault, Bayan Har block, secondary faults, aftershock relocation, focal mechanism, landslides, seismic gap, western Sichuan

The research, conducted by Juarez Antônio da Silva Júnior of the Federal University of Pernambuco, examined landslide occurrences recorded by Recife’s Civil Defense between 2015 and 2024. Rather than treating each neighborhood as an isolated unit, as conventional frequency counts and ordinary statistical models tend to do, the study measured whether landslides in one neighborhood were related to landslides in adjacent ones. The central tool was the Global Moran’s Index, a measure of spatial autocorrelation that quantifies whether similar values—here, landslide counts—sit closer together in space than chance would predict. Positive, significant values indicate clustering; values near zero indicate randomness.

The results were unambiguous. In most years of the historical series, the Global Moran’s Index was positive and statistically significant, ranging from moderate values of roughly 0.17 to 0.27 between 2015 and 2017, dipping during an attenuation period from 2018 to 2020, and then strengthening again to a peak of about 0.33 in 2023. In other words, throughout nearly the entire decade, neighborhoods with many landslides tended to be surrounded by other neighborhoods with many landslides, while quiet zones stayed quiet together. The risk, the analysis shows, is not diffuse across the city but concentrated in stable geographic poles.

To locate those poles precisely, the study turned to Local Indicators of Spatial Association, or LISA, a technique proposed by geographer Luc Anselin in 1995 that decomposes global autocorrelation into neighborhood-level clusters. LISA classifies each area into categories such as High-High, where a high-incidence neighborhood is surrounded by similarly high neighbors, or Low-Low, where low values cluster together, along with outlier categories where a unit diverges from its surroundings. The spatial weighting was built using Queen-type contiguity, meaning neighborhoods were considered neighbors if they shared a boundary or a vertex—an approach well suited to the irregular geometries of urban districts.

The local analysis revealed two large, statistically significant High-High hotspots at opposite ends of the municipality. In the North Zone, the neighborhoods of Guabiraba, Passarinho, Dois Unidos, Nova Descoberta, and Linha do Tiro emerged as chronic hotspots, classified as High-High in four to six of the ten years analyzed. In the South Zone, COHAB, Ibura, Jordão, and Barro showed recurring clusters, particularly in 2017, 2018, and above all 2022—a year of exceptional rainfall that produced the highest landslide count in the entire series, with some neighborhoods exceeding 50 occurrences and LISA values greater than 1 across broad contiguous areas. By contrast, central and coastal districts such as Boa Viagem, Pina, Graças, and Derby were dominated by Low-Low patterns, confirming consistently low risk in the flat, highly urbanized heart of the city.

Beyond mapping clusters in individual years, the study introduced two temporal indicators derived from the LISA results: the frequency of High-High classification and a persistence ranking that distinguishes chronic hotspots, significant in at least five of ten years, from episodic and intermittent ones. This persistence analysis showed that the northern hotspot is not a product of any single disaster but a structural condition—vulnerability that is rooted in time as well as space. Descriptive statistics reinforced the picture: neighborhoods such as Dois Unidos displayed extreme interannual swings, recording no cases in 2018, 104 cases in 2019, and only 2 in 2020, while Sen’s slope estimates suggested a modest overall downward trend in several historically critical areas, possibly reflecting municipal interventions.

The spatial patterns aligned closely with independent evidence. When the identified clusters were overlaid on landslide susceptibility maps prepared by the Geological Survey of Brazil (SGB/CPRM) and on the city’s continuous landslide monitoring map, the correspondence was strong. The CPRM maps classify the hilly terrain of the North and South zones as highly susceptible to mass movements, and it is precisely there that the chronic hotspots sit. The city’s own monitoring points, concentrated in the North, Northeast, and South administrative regions, coincide with the High-High clusters. This convergence between empirical occurrence data and model-based susceptibility mapping strengthens confidence that the statistical signals reflect genuine geotechnical and social conditions rather than artifacts of reporting.

The underlying drivers are as much social as geological. Recife, home to nearly 1.5 million people at a density of more than 6,800 per square kilometer, combines a humid tropical climate with steep slopes occupied by self-built housing. Studies cited in the paper document chaotic occupation, narrow streets, inadequate drainage, vegetation loss, and construction in permanent preservation areas in neighborhoods such as Passarinho, where urban growth reached 41 percent between 1975 and 2022 while vegetation cover fell by 30 percent. An estimated 207,000 residents live in at-risk areas, and Recife was ranked the fifth most impacted city by flash floods and landslides in terms of population in CEMADEN studies following the catastrophic May 2022 rains, which affected more than 200,000 inhabitants and caused dozens of deaths.

The methodological lesson extends beyond Recife. Spatial autocorrelation analysis has proven its value in fields from dengue epidemiology in Nepal to hepatitis A mapping in Indonesia and vegetation fragmentation studies in Zimbabwe, and recent work has integrated LISA with machine learning models to improve landslide prediction in China. By demonstrating that a decade of municipal civil defense records, freely available under an open data license and processed with open-source Python libraries such as GeoPandas and PySAL, can yield actionable risk intelligence, the study offers a replicable template for other cities with rugged terrain in the Brazilian Northeast and beyond.

The practical implications are direct. The author recommends prioritizing slope containment works, expanded drainage, vegetation recovery, control of irregular occupation, and relocation of families in imminent danger in the chronic northern hotspots, while reinforcing containment structures, permanent geotechnical monitoring, and contingency planning in the southern cluster. As climate change intensifies extreme rainfall events across the region, distinguishing chronic from episodic risk areas becomes essential for allocating scarce public resources. The decade of data from Recife delivers a clear message: landslide risk has an address, and prevention efforts should go precisely there.

Subject of Research: Spatiotemporal autocorrelation of landslide occurrences across neighborhoods of Recife, Brazil, from 2015 to 2024 using the Global Moran's Index and LISA.

Article Title: Spatiotemporal autocorrelation of landslides in neighborhoods of Recife, Brazil (2015–2024) based on the Moran and Lisa index

Article References: da Silva Júnior, J. A. (2026). Spatiotemporal autocorrelation of landslides in neighborhoods of Recife, Brazil (2015–2024) based on the Moran and Lisa index. Discover Geoscience, 4(1), Article 354. https://doi.org/10.1007/s44288-026-00722-z

Image Credits: AI Generated

DOI: 10.1007/s44288-026-00722-z

Keywords: landslides, spatial autocorrelation, Moran's Index, LISA, Recife, Brazil, spatial hotspots, urban risk, geotechnical instability, disaster risk management, GIS, susceptibility mapping

The Western Ghats are naturally susceptible to rainfall-triggered landslides because several risk factors overlap. The region has steep, deeply dissected terrain, weathered basaltic rocks and soil-like regolith that can lose strength when saturated. Miraswadi receives approximately 1,733 millimetres of rain annually, much of it during the southwest monsoon. During prolonged or unusually intense storms, water infiltrates the slope, raises groundwater levels and increases pore-water pressure between grains. That pressure reduces the friction and effective stress holding the material together, lowering its shear strength. Surface runoff can then concentrate in channels, erode exposed soil and mobilize loose debris. The July 2021 event occurred during an extreme rainfall episode that triggered thousands of landslides across Maharashtra’s Western Ghats. The local landscape also includes agricultural terraces, settlements, drainage modifications and other human changes that can redirect runoff or alter infiltration. The researchers did not identify these activities as the primary cause of the Miraswadi failure, but they concluded that such modifications may influence local susceptibility when combined with steep slopes, weathered materials and exceptional rainfall. Seismic activity in the nearby Koyna–Varna zone may contribute to long-term fracturing, although rainfall remains the principal trigger in this setting.

To reconstruct the terrain, the team flew a DJI Phantom 4 Pro equipped with a 20-megapixel, one-inch sensor camera at roughly 200 metres above ground level. The mission collected 283 georeferenced high-resolution images, with about 80 per cent forward overlap and 30 per cent side overlap between photographs. Overlapping images allow photogrammetry software to identify the same surface points from multiple viewpoints and calculate their three-dimensional positions. The resulting dataset produced an orthomosaic, a digital elevation model, contour information and a dense point cloud containing approximately 31 million points. Its mean ground sampling distance was 5.52 centimetres, meaning that individual image-derived cells represented only a few centimetres of ground surface. Image calibration was reported as 100 per cent successful, with a mean reprojection error of approximately 0.143 pixels. Handheld GPS measurements supplied ground control points to improve positional consistency and elevation calibration. The researchers emphasize that the products were intended primarily for relative geomorphological analysis rather than survey-grade geodetic measurement. Recreational-grade GPS accuracy and the absence of a pre-failure drone survey limit the precision with which surface movement and lost volume can be interpreted. Even so, the model provided sufficient detail to identify cracks, scarps, slumps and debris pathways across a hazardous slope.

The mapped landslide began approximately 125 metres northeast of Miraswadi on 23 July 2021. Its visible failure area covered about 1.34 hectares, while the associated debris spread extended across roughly 2.95 hectares. From crown to toe, the movement reached approximately 255 metres, with widths ranging from 112 to 162 metres. The researchers estimated that between 42,050 and 46,076 cubic metres of material had been displaced, presenting the result as a range because the pre-failure surface had to be reconstructed from surrounding undisturbed terrain. Morphological evidence suggests that the event began as a debris slide, in which weathered soil and rock moved downslope as a relatively coherent mass. Once the material entered a pre-existing second-order drainage channel, it became more confined and flow-like, evolving into a channelized debris movement. The terrain model divided the slope into an initiation zone between approximately 747 and 690 metres above mean sea level, a transport zone from about 690 to 665 metres, and a deposition zone from roughly 665 to 642 metres. The upper initiation area included steep slopes exceeding 45 degrees and locally surpassing 60 degrees. Lower gradients allowed transported soil, rock fragments and uprooted vegetation to accumulate across the broader depositional area.

The most consequential discovery was not confined to the old landslide scar. Immediately upslope of the habitation, researchers identified a deformation area containing three to four major tension cracks between approximately 70 and 90 metres long and up to half a metre wide. Several cracks coincided with localized ground settlement and slumping, with vertical displacement reaching about 0.5 metres. Their roughly slope-parallel alignment and position on a hillside directly above homes indicate that the ground has continued to adjust after the 2021 failure. A second area, above the original crown, contained two or three smaller cracks approximately 10 to 15 metres long and 0.1 metres wide. These may represent instability propagating upslope, although the study does not establish a precise rate or direction of movement. Field inspections confirmed active slumping, regolith displacement, minor scarps, surface undulations and additional cracks within the weathered soil. Tilting vegetation supplied another visible sign that the ground beneath roots may be shifting. The researchers carefully distinguish these observations from pre-failure warning signs: because the survey was conducted after the landslide, the features document ongoing post-failure deformation rather than proven precursors. Their location nevertheless matters for risk assessment. A hazard map drawn only around the original scar could overlook unstable ground that threatens the settlement from above.

The team also compared land use in satellite imagery from 2011 and 2022 to examine how the surrounding landscape had changed. Settlement area increased from approximately 8,014 square metres to 15,403 square metres, an expansion of about 92 per cent. Over the same period, terrace farming declined from about 454,746 to 409,114 square metres, while barren or fallow land decreased from approximately 115,372 to 105,709 square metres. Forest cover increased from about 170,695 to 218,601 square metres, suggesting that vegetation expanded overall even as localized changes occurred near the hamlet. The researchers observed the growth of residential structures, modifications to agricultural terraces and exposed soil surfaces, particularly on slopes northeast of the settlement where active instability was detected. These changes can affect how water travels across a hillside. A building platform, track, terrace or altered drainage line may concentrate runoff in one place, increase infiltration in another or remove material that previously protected the soil. The study does not claim that settlement growth caused the landslide. Instead, it presents human landscape modification as a factor that can interact with natural controls and increase exposure. In a small rural community, even modest expansion can place more homes, fields and livestock facilities beneath an unstable slope.

The findings have immediate implications for monitoring and preparedness, but the authors caution against treating their preliminary recommendations as final engineering plans. The deformation zone above the hamlet should receive continued attention, particularly during and after periods of intense rainfall. Repeated drone surveys could compare successive digital elevation models and orthomosaics to detect crack widening, new scarps, changing vegetation tilt or accelerated ground displacement. Field observations remain essential because dense vegetation, shadows and image geometry can obscure features in aerial data. Surface drainage management may reduce water concentration and infiltration in unstable areas, while vegetation-based measures could help control erosion and reinforce shallow soil. Retaining structures might be appropriate in selected locations, but their design would require detailed geotechnical, hydrogeological and engineering investigations. The study also identifies a potential temporary refuge area chosen using topography, distance from unstable slopes, access and proximity to agricultural and livestock resources. That site is not validated as a permanent rehabilitation location; no dedicated land-suitability, geotechnical or hydrogeological assessment was performed. Because many residents depend on farming and livestock and maintain strong ties to their homes, temporary evacuation during extreme rainfall may be more realistic than immediate permanent relocation. Warning signs such as widening cracks, renewed slumping or rapidly increasing deformation could help guide such decisions.

Miraswadi illustrates both the power and the limits of high-resolution remote sensing in landslide science. Regional susceptibility maps can identify broad patterns of danger, but they cannot always show whether a particular crack runs behind a house, whether a drainage channel links a scar to a settlement or whether deformation extends beyond a mapped failure. A drone can be deployed quickly over a relatively small area and generate detailed terrain information without exposing surveyors to the most hazardous ground. Yet a single post-event flight cannot reveal how fast the slope is moving, what is happening underground or whether another failure will occur. The study therefore calls for repeated UAV acquisitions combined with rainfall records, hydrological monitoring, geotechnical testing, geophysical surveys and analysis of rainfall thresholds. Such integration could turn a detailed snapshot into an early-warning system. For communities across the Western Ghats and other tropical mountain regions, the approach offers a practical way to document landslides after extreme storms and identify danger zones that remain active after the debris has stopped moving. In Miraswadi, the central message is straightforward: the end of a landslide’s visible movement does not necessarily mean the slope has stabilized. High-resolution mapping can make that hidden continuation visible before the next monsoon tests the hillside again.

Subject of Research: UAV mapping of landslide morphology and post-failure slope instability in Miraswadi, India

Article Title: UAV based assessment of landslide morphology and slope instability in Miraswadi, Western Ghats, India

Article References: Shirke, A. V., Khandge, A., Umrikar, B. N., & Asim, M. (2026). UAV based assessment of landslide morphology and slope instability in Miraswadi, Western Ghats, India. Discover Geoscience, 4(1), Article 334. https://doi.org/10.1007/s44288-026-00707-y

Image Credits: AI Generated

DOI: 10.1007/s44288-026-00707-y

Keywords: landslides, UAV mapping, Western Ghats, slope instability, debris flows, remote sensing, monsoon rainfall, hazard mitigation, based, assessment, landslide, morphology