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A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Natural Hazards".

Deadline for manuscript submissions: closed (31 March 2026) | Viewed by 23928

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Prof. Dr. Dimitrios Nikolopoulos

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Department of Industrial Design and Production Engineering, University of West Attica, Petrou Ralli & Thivon 250, GR 122 44 Aigaleo, Greece
Interests: fractal analysis; fractal dimension; long-memory; Hurst exponent; DFA; symbolic dynamics; R/S analysis; entropy; Tsallis entropy; earthquakes; pre-seismic precursors; radon; radon progeny; radon in soil; kHz-MHz electromagnetic radiation and ionising radiation physics; radiation dosimetry; radiation exposure; radiation protection and X-rays
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Dr. Samuele Segoni

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Department of Earth Sciences, University of Firenze, Via La Pira, 4, I-50121 Firenze, Italy
Interests: prediction and mapping of landslide hazards; physically based models for the triggering of shallow landslides; landslide susceptibility maps; rainfall thresholds for landslide triggering; regional-scale landslide early warning systems; civil protection; land planning; landslide risk assessment
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Dr. Danilo Godone

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National Research Council, Research Institute for Hydrogeological Prevention and Protection, Strada delle Cacce 73, 10135 Turin, Italy
Interests: natural hazards; monitoring; geomatics; remote sensing; glaciers; cryosphere
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Dr. Giovanna Vessia

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Department of Engineering and Geology (InGeo), Università degli Studi G. d'Annunzio Chieti e Pescara, Pescara, Italy
Interests: seismic microzonation; empirical rainfall threshold applied to shallow landslides; geostatistical methods applied to hazard mapping and geotechnical subsoil characterization; stability numerical analyses of rock cavities
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Dr. Leonhard Blesius

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Department of Geography & Environment, San Francisco State University, 1600 Holloway Avenue, HSS Bldg, Room 283, San Francisco, CA 94132, USA
Interests: environmental systems analysis; fluvial geomorphology; natural hazard; landslides
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Special Issue Information

Dear Colleagues,

Natural hazards such as earthquakes, landslides, volcanic eruptions, floods, droughts, and storms continue to pose significant challenges to both human societies and natural ecosystems. These hazards, whether abrupt or evolving over time, present complex challenges that require interdisciplinary approaches to understand, predict, and manage their impacts.

This collection aims to gather a diverse range of studies related to geological, environmental, hydro-meteorological, oceanographic, climatological, and biological hazards, as well as those that develop gradually or emerge suddenly. Research that focuses on modeling and forecasting natural hazards, as well as cross-disciplinary approaches addressing hazard assessment, mitigation strategies, emergency response, and post-disaster recovery, are particularly welcome.

We welcome contributions from researchers worldwide, with a focus on ground-based investigations, in situ instrumentation, remote sensing techniques, and innovative methodologies. We look forward to receiving high-quality submissions and engaging with research that makes a real impact.

Prof. Dr. Dimitrios Nikolopoulos
Dr. Samuele Segoni
Dr. Danilo Godone
Dr. Giovanna Vessia
Dr. Leonhard Blesius
Guest Editors

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Keywords

hazard assessment
risk mitigation
emergency response
forecasting techniques
post-disaster recovery
in situ instrumentation
remote sensing
hazard modeling
geological hazards
environmental hazards
resilience strategies

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Published Papers (11 papers)

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Research

24 pages, 23496 KB

Open AccessArticle

Shear Behavior and Strength Model for the Ice-Rock Interface with Different Roughnesses

by Shipeng Hu, Tiantao Li, Weiling Ran, Jian Guo, Shihua Chen, Jing Yuan and Hao Jing

Geosciences 2026, 16(3), 132; https://doi.org/10.3390/geosciences16030132 - 23 Mar 2026

Viewed by 345

Abstract

The ice–rock interface shear mechanism is fundamental to understanding ice–rock avalanche hazards. This study conducts a series of direct shear tests under various normal stresses to analyze the mechanical response and acoustic emission (AE) evolution of the interface, establishing a shear strength prediction model. Results indicate that the roughness significantly affects mechanical properties and AE responses: as the roughness increases, the shear strength, cohesion, and internal friction angle improve significantly, while peak AE ringing counts and energy exhibit an increasing trend. During failure, the proportion of shear cracks decreases while tensile cracks increase, reflecting a shift in crack development modes driven by the roughness. Based on AE characteristics and stress–displacement relations, the shear failure process is categorized into five stages: initial, crack development, crack propagation, crack coalescence, and residual stages. Incorporating the effects of the roughness and cementation force, a shear mechanical model was established. Experimental data verify the model’s rationality; however, its applicability may be limited when the roughness is excessively high. Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Natural Hazards)

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18 pages, 3291 KB

Open AccessArticle

Detecting Anomalies in Radon and Thoron Time Series Data Using Kernel and Wavelet Density Estimation Methods

by Muhammad Rafique, Awais Rasheed, Muhammad Osama, Adil Aslam Mir, Dimitrios Nikolopoulos, Kyriaki Kiskira, Aftab Alam, Georgios Prezerakos, Aqib Javed, Panayiotis Yannakopoulos, Christos Drosos, Georgios Priniotakis, Nikitas Gerolimos, Michail Papoutsidakis, Kimberlee Jane Kearfott and Saeed Ur Rahman

Geosciences 2026, 16(2), 64; https://doi.org/10.3390/geosciences16020064 - 2 Feb 2026

Viewed by 756

Abstract

Long-term monitoring of radon (²²²Rn) and thoron (²²⁰Rn) radioactive gases has been used in earthquake forecasting. Seismic activity before earthquakes raises the levels of these gases, causing abnormalities in the baseline values of radon and thoron time series (RTTS) data. This study reports applications of kernel density estimation (KDE) and wavelet-based density estimation (WBDE) to detect anomalies in radon, thoron, and meteorological time-series data. Anomalies appearing in the RTTS data have been assessed for their potential correlation with seismic events. Using KDE and WBDE, radon anomalies were observed on 12 March, 15 August, 17 September, in the year 2017, and 19 January 2018. Thoron anomalies were recorded on 12 March, 15 August, 17 September 2017, and 28 February 2018. Irregularities in RTTS were observed several days before seismic events. Anomalies in RTTS, detected using KDE, successfully correlated five out of nine seismic events while WBDE identified four anomalies in RTTS which were successfully correlated with the corresponding seismic events. The wavelet transform has been used to reduce noise at higher decomposition levels in radon and thoron time series. Findings of the study reveal the potential of radon and thoron time series that can be used as precursors for earthquake forecasting. Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Natural Hazards)

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16 pages, 3834 KB

Open AccessArticle

Background Seismicity Highlights Tectonic Asperities

by Alexey Ostapchuk and Ilmir Nugmanov

Geosciences 2026, 16(1), 38; https://doi.org/10.3390/geosciences16010038 - 11 Jan 2026

Viewed by 983

Abstract

The heterogeneity of a tectonic fault interface controls both the spatial features of seismicity and the locations of the foci of shallow earthquakes. Strong earthquakes are associated with ruptures of asperities. We present the Seismogenic Patches Detection (SPAD) algorithm to analyze background seismicity to reveal tectonic asperities. In the first stage, the algorithm detects background seismicity based on the nearest-neighbor method. In the second stage, fuzzy clustering of the background mode is performed. Dense clusters of background seismicity, called seismogenic patches, can be interpreted as tectonic asperities. The SPAD algorithm does not use a priori data about the localizations of strong earthquakes. Using SPAD, we analyzed the seismicity of the Kamchatka segment of the Kuril–Kamchatka subduction zone for the period from 1 January 1990 to 23 September 2025. The Kamchatka regional seismic catalog includes 39,104 events, and the magnitude of completeness Mc equals 3.0. We have identified seven seismogenic patches with a size of 170–270 km. Seismogenic patches correlate with the tectonic asperity determined by the maps of the slip distributions for the four largest earthquakes—Mw7.5 (8 June 1993), Mw7.8 (5 December 1997), Mw8.8 (30 July 2025), and Mw7.8 (13 September 2025). Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Natural Hazards)

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21 pages, 15032 KB

Open AccessArticle

The SISMIKO Monitoring Network and Insights into the 2024 Seismic Swarms on the Ionian Side of the Calabrian Arc

by Antonio Costanzo, Marina Pastori, Adriano Cavaliere, Ezio D’Alema, Lucia Margheriti, Simone Marzorati, Milena Moretti, Davide Piccinini, Mario Anselmi, Samer Bagh, Marco Colasanti, Fabio Criscuoli, Sergio Falcone, Anna Gervasi, Angelo La Regina, Matteo Migliari, Alfonso Ruffo, Ivano Carluccio and Mario Locati

Geosciences 2025, 15(11), 436; https://doi.org/10.3390/geosciences15110436 - 14 Nov 2025

Cited by 1 | Viewed by 1049

Abstract

Following the Mw 5.0 earthquake of 1 August 2024, which struck the Ionian sector of north-central Calabria (southern Italy), the SISMIKO emergency group of INGV deployed a temporary seismic network to enhance coverage of the National Seismic Network. This improved configuration enabled the relocation of over 1300 aftershocks and the identification of a second swarm near Cirò, active since May and reactivated after mid-August. A machine learning workflow was applied for automatic phase picking, event association, and relocation, producing a high-resolution catalogue. The seismicity of both sequences aligns with the NW-trending Rossano–San Nicola shear zone but reveals distinct rupture patterns: the Pietrapaola sequence, targeted by the SISMIKO deployment, shows compact hypocentral clustering, while the Cirò swarm displays more scattered seismicity. The analysis of the catalogue reveals a two-slope temporal decay of aftershocks and relatively low completeness magnitudes. Source geometry inferred from hypocentre distributions and INGV focal mechanisms supports the structural interpretation. Overall, the machine learning-based catalogue proved effective for near-real-time analysis and offers new insights into the active tectonic framework of the Calabrian Arc. Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Natural Hazards)

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29 pages, 12422 KB

Open AccessEditor’s ChoiceArticle

Real-Time Foreshock–Aftershock–Swarm Discrimination During the 2025 Seismic Crisis near Santorini Volcano, Greece: Earthquake Statistics and Complex Networks

by Ioanna Triantafyllou, Gerassimos A. Papadopoulos, Constantinos Siettos and Konstantinos Spiliotis

Geosciences 2025, 15(8), 300; https://doi.org/10.3390/geosciences15080300 - 4 Aug 2025

Cited by 3 | Viewed by 7175

Abstract

The advanced determination of the type (foreshock–aftershock–swarm) of an ongoing seismic cluster is quite challenging; only retrospective solutions have thus far been proposed. In the period of January–March 2025, a seismic cluster, recorded between Santorini volcano and Amorgos Island, South Aegean Sea, caused considerable social concern. A rapid increase in both the seismicity rate and the earthquake magnitudes was noted until the mainshock of M_L = 5.3 on 10 February; afterwards, activity gradually diminished. Fault-plane solutions indicated SW-NE normal faulting. The epicenters moved with a mean velocity of ~0.72 km/day from SW to NE up to the mainshock area at a distance of ~25 km. Crucial questions publicly emerged during the cluster. Was it a foreshock–aftershock activity or a swarm of possibly volcanic origin? We performed real-time discrimination of the cluster type based on a daily re-evaluation of the space–time–magnitude changes and their significance relative to background seismicity using earthquake statistics and the topological metric betweenness centrality. Our findings were periodically documented during the ongoing cluster starting from the fourth cluster day (2 February 2025), at which point we determined that it was a foreshock and not a case of seismic swarm. The third day after the M_L = 5.3 mainshock, a typical aftershock decay was detected. The observed foreshock properties favored a cascade mechanism, likely facilitated by non-volcanic material softening and the likely subdiffusion processes in a dense fault network. This mechanism was possibly combined with an aseismic nucleation process if transient geodetic deformation was present. No significant aftershock expansion towards the NE was noted, possibly due to the presence of a geometrical fault barrier east of the Anydros Ridge. The 2025 activity offered an excellent opportunity to investigate deciphering the type of ongoing seismicity cluster for real-time discrimination between foreshocks, aftershocks, and swarms. Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Natural Hazards)

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13 pages, 902 KB

Open AccessArticle

The Role of Disorder in Foreshock Activity

by Giuseppe Petrillo

Geosciences 2025, 15(6), 226; https://doi.org/10.3390/geosciences15060226 - 15 Jun 2025

Viewed by 1138

Abstract

Foreshocks, observed before some large earthquakes, remain debated in terms of their origins and predictive value. While aftershocks fit well within bottom-up triggering models like ETAS, foreshocks may arise from distinct preparatory processes. Observations suggest real seismic catalogs exhibit more foreshocks than ETAS predicts, and laboratory experiments show that fault heterogeneity enhances foreshock activity. Here, I use a numerical model that reproduces key statistical properties of seismicity to investigate the role of fault heterogeneity. My simulations confirm that increasing interface disorder promotes foreshocks, aligning with laboratory findings and suggesting that fault complexity influences seismic precursors. Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Natural Hazards)

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19 pages, 6998 KB

Open AccessArticle

Two Opposite Change Patterns Before Small Earthquakes Based on Consecutive Measurements of Hydrogen and Oxygen Isotopes at Two Seismic Monitoring Sites in Northern Beijing, China

by Yuxuan Chen, Fuqiong Huang, Leyin Hu, Zhiguo Wang, Mingbo Yang, Peixue Hua, Xiaoru Sun, Shijun Zhu, Yanan Zhang, Xiaodong Wu, Zhihui Wang, Lvqing Xu, Kongyan Han, Bowen Cui, Hongyan Dong, Boxiu Fei and Yonggang Zhou

Geosciences 2025, 15(6), 192; https://doi.org/10.3390/geosciences15060192 - 22 May 2025

Viewed by 1176

Abstract

In comparison with conventional hydrological parameters such as water levels and temperatures, geochemical changes induced by earthquakes have become increasingly important. It should be noted that hydrogen (δ²H) and oxygen isotopes (δ¹⁸O) offer the greatest potential as precursor proxies of earthquakes. Here, we conducted high-resolution sampling (weekly, 59 samples), measuring consecutive δ²H and δ¹⁸O levels at the two sites of the WLY well and SS spring in the Yan-Huai Basin of Beijing from June 2021 to June 2022. During the period of this sampling, several small earthquakes of ML > 1.6 occurred in Beijing. We used statistical methods (analysis of variance) to test the significant differences, used Self-Organizing Maps (SOMs) for data clustering, and then used Bayesian Mixing Models (MixSIAR) to calculate the proportions of the source contributions. We found significant four-stage patterns of change processes in δ²H and δ¹⁸O at both sites. The WLY well exhibited a distinct four-stage variation pattern: initial stable development (WT1) followed by a rapid rise (WT2) and sudden fall (WT3) before the small earthquakes, and finally gradual stabilization after earthquakes (WT4). In contrast, the SS spring displayed an inverse pattern, beginning with stable development (ST1), then undergoing a rapid falling (ST2) and sudden rising (ST3) before the small earthquakes, and finally stabilizing through stepwise reduction after the earthquakes (ST4). The most likely mechanisms were differences in the time of rupture between the carbonate in WLY and granite in SS under sustained stress. The stress induced source mixing of fluid from the surface or deeper groundwater-source reservoirs. The hypothesis was supported by the MixSIAR model, calculating the variational proportion of source contributions in the four stages. This work permitted the use of high-resolution isotopic data for statistical confirmation of concomitant shifts during the earthquakes, provided the mechanisms behind them, and highlighted the potential for the consecutive monitoring of hydrogen and oxygen isotopes indicators in earthquake-prediction studies. Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Natural Hazards)

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15 pages, 14363 KB

Open AccessArticle

Sedimentary Diversity of Tsunami Deposits in a River Channel Associated with the 2024 Noto Peninsula Earthquake, Central Japan

by Rina Okada, Koji Umeda, Keigo Motegi, Takanobu Kamataki and Tadashi Amano

Geosciences 2025, 15(4), 153; https://doi.org/10.3390/geosciences15040153 - 17 Apr 2025

Viewed by 2011

Abstract

A comprehensive analysis of modern tsunami deposits offers a valuable opportunity to elucidate the characteristics of paleo-tsunami deposits. On 1 January 2024, a tsunami was generated by a magnitude 7.6 seismic event and subsequently struck the Noto Peninsula in central Japan. In order to create a facies model of the tsunami deposits in terrestrial and riverine environments, field surveys were conducted on both the onshore and sandbars within the river channel in the Nunoura area on the northeastern Noto Peninsula. Terrestrial tsunami deposits were observed up to several hundred meters inland, with a slight decrease in thickness of several centimeters with distance from the shoreline. In terrestrial settings, the presence of a substantial silty layer overlying a graded sandy layer is indicative of ponded stagnant water from the tsunami wave. In contrast, riverine tsunami deposits are thicker and more extensive than terrestrial sediments, containing both gravels and shell fragments. An erosional surface develops between deposits of run-up and backwash flows, but a mud drape is not observed. Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Natural Hazards)

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18 pages, 1727 KB

Open AccessArticle

Comparison of Backprojection Techniques for Rupture Propagation Modelling of the M_w = 7.8 Mainshock Earthquake near Kahramanmaras and the M_w = 7.5 Second-Largest Mainshock near Elbistan, Turkey, 2023

by Dimitrios Nikolopoulos, Mahmood Sultan, Aftab Alam, Demetrios Cantzos, Georgios Priniotakis, Michail Papoutsidakis, Farhan Javed, Georgios Prezerakos, Jamil Siddique, Muhammad Ali Shah, Muhammad Rafique and Panayiotis Yannakopoulos

Geosciences 2025, 15(4), 146; https://doi.org/10.3390/geosciences15040146 - 14 Apr 2025

Cited by 1 | Viewed by 2118

Abstract

This paper utilises teleseismic Z-component data to investigate rupture propagation, extent, and velocity for two very destructive earthquakes in the East Anatolian Fault Zone (EAFZ): the

M_{w}

= 7.8 earthquake near Kahramanmaras and the largest (

M_{w}

= 7.5 s) aftershock [...] Read more.

This paper utilises teleseismic Z-component data to investigate rupture propagation, extent, and velocity for two very destructive earthquakes in the East Anatolian Fault Zone (EAFZ): the

M_{w}

= 7.8 earthquake near Kahramanmaras and the largest (

M_{w}

= 7.5 s) aftershock at Elbistan (both on 6 February 2023). The extent of the rupture is modelled with beamforming and multichannel signal classification. The teleseismic data are derived from agencies in USA and Canada. The rupture of the

M_{w}

= 7.8 earthquake is found to be bi-directional towards the northeast and southwest. Three rupture segments are identified for the Kahramanmaras earthquake between 34.5°–37.5° longitude and 37.0°–37.5° latitude, and another three are identified for the Elbistan earthquake between 36.5°–38.0° longitude and around 38.5° latitude. A total of 299 km is covered in 185 s with rupture velocities between 3.1 km/s and 3.4 km/s. Additionally, the mainshock’s splay and the second-largest aftershock’s rupture are also bidirectional, covering 150 km within 46 s. Five velocity segments are identified, three for the Kahramanmaras and two for the Elbistan earthquakes. Beamforming is efficient for identifying the velocity segments. The findings provide new insights on the evolution of the spatio-temporal rupture of the EAFZ and may serve as a basis for long-term earthquake hazard planning in the area. Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Natural Hazards)

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10 pages, 248 KB

Open AccessArticle

Vibrations of an Elastic Half-Space

by Bogdan Felix Apostol

Geosciences 2025, 15(4), 144; https://doi.org/10.3390/geosciences15040144 - 9 Apr 2025

Cited by 3 | Viewed by 1381

Abstract

We report on the resolution of the vibration problem for a homogeneous and isotropic elastic half-space (the Lamb problem), with application to the seismic tensorial force. We assume a homogeneous and isotropic half-space with a localized force which produces vibrations. The solution is achieved by introducing vector plane-wave functions. Explicit results are given for an isotropic tensorial force and a half-space with free surface. The contribution of the Rayleigh surface waves to vibrations is analyzed in the special case of a temporal-impulse force, where the solution exhibits unphysical features, as expected: it extends over the entire free surface and time domain, with a (scissor-like) double-wall propagating both in the future and the past. Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Natural Hazards)

17 pages, 25358 KB

Open AccessEditor’s ChoiceArticle

Examining the Influence of Different Inventories on Shallow Landslide Susceptibility Modeling: An Assessment Using Machine Learning and Statistical Approaches

by Helen Cristina Dias, Daniel Hölbling and Carlos Henrique Grohmann

Geosciences 2025, 15(3), 77; https://doi.org/10.3390/geosciences15030077 - 20 Feb 2025

Cited by 5 | Viewed by 1892

Abstract

Shallow landslides are one of the most common natural hazards in Brazil and worldwide. Susceptibility maps are powerful tools to analyze the spatial probability of shallow landslide occurrences. The outputs of susceptibility maps strongly depend on the type of landslide inventory used. The aim of this study is to examine the influence of different inventories on shallow landslide susceptibility modeling using the different methods LR, SVM, and XGBoost. Three different shallow landslide inventories were compiled following a single extreme rainfall event in the Ribeira Valley, São Paulo, Brazil. The results indicate that inventories generated through different landslide detection methods and imagery produce diverse susceptibility maps, as evidenced by the calculated Cohen’s Kappa coefficient values (0.33–0.79). The agreement among the models varied depending on the specific model: LR exhibited the highest agreement (0.79), whereas SVM (0.36) and XGBoost (0.33) showed lower numbers. Conversely, the accuracy numbers suggest that XGBoost achieved the highest success rate in terms of AUC (85–78%), followed by SVM (82–76%), and LR (80–71%). Inventories obtained through different detection methods, using distinct datasets, can directly influence the susceptibility assessment, leading to varying classifications of the same area. These findings demonstrate the importance of well-established landslide mapping criteria. Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Natural Hazards)

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