Engineering Geology最新文献

{"title":"Freeze-thaw migration behavior of scree deposits in the cold regions: Insight from physical model test","authors":"Weibo Li ,&nbsp;Qinglu Deng ,&nbsp;Pengju An ,&nbsp;Zhiyao Zhou ,&nbsp;Kun Fang","doi":"10.1016/j.enggeo.2025.108018","DOIUrl":"10.1016/j.enggeo.2025.108018","url":null,"abstract":"<div><div>In cold regions, the migration of soil and rock particles during freeze-thaw cycles results in uniquely patterned ground. Migration mechanisms of rock particles with inverse grading in talus are still unclear in scree deposits. Here, we designed a physical model test using a camera, a displacement meter, and a thermometer to investigate the migration behavior and related migration mechanisms of scree deposits by freeze-thaw cycles. The results show that the downward displacement of small particles was 16 to 26 times greater than that of large particles, causing small particles to aggregate downward and large particles to be exposed at the surface, thereby exhibiting the phenomenon of inverse grading. The freeze-thaw cycles process causes particles to move and rotate, which leads to smaller particles migrating along the widening gaps between larger particles. Finally, the mechanism of “freeze-thaw microseismicity” in talus is proposed to explain the migration process of scree deposits through freeze-thaw cycles in cold regions.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"350 ","pages":"Article 108018"},"PeriodicalIF":6.9,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Permafrost thawing characterization in engineering scale by multi-geophysical methods: A case study from the Tibet Plateau","authors":"Junkai Ge ,&nbsp;Huaifeng Sun ,&nbsp;Rui Liu ,&nbsp;Zhiyou Huang ,&nbsp;Bo Tian ,&nbsp;Lanbo Liu ,&nbsp;Ziqiang Zheng","doi":"10.1016/j.enggeo.2025.108012","DOIUrl":"10.1016/j.enggeo.2025.108012","url":null,"abstract":"<div><div>The freeze-thaw cycles in permafrost regions significantly impact infrastructure stability. While satellite sensing provides a broad perspective for engineering site selection, it lacks the in-depth assessments. Geophysical methods can effectively provide valuable insights into the states of permafrost thawing, but any single method has limitations. To address this, we applied an integrated geophysical approach using ground-penetrating radar (GPR), electrical resistivity tomography (ERT), ambient-noise seismic interferometry (ANSI), and Unmanned Aerial Vehicle (UAV)-based infrared imaging to assess permafrost conditions in the Tuotuo River Basin, Qinghai-Tibet Plateau. Our multi-method survey delineated thawed zones and active layers. The results revealed that a large-scale thawed zone was primarily caused by surface heat absorption, rain infiltration, and sandy soil conditions. We also evaluated the strengths and limitations of each geophysical method, demonstrating their complementarity in permafrost detection. These findings provide a valuable reference for geophysical site assessments and help mitigate engineering risks in permafrost areas.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"350 ","pages":"Article 108012"},"PeriodicalIF":6.9,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-source data-based quantitative risk analysis of road networks to slow-moving landslides","authors":"D. Peduto ,&nbsp;G. Nicodemo ,&nbsp;D. Luongo ,&nbsp;L. Borrelli ,&nbsp;D. Reale ,&nbsp;S. Ferlisi ,&nbsp;G. Fornaro ,&nbsp;G. Gullà","doi":"10.1016/j.enggeo.2025.108011","DOIUrl":"10.1016/j.enggeo.2025.108011","url":null,"abstract":"<div><div>The paper addresses the quantitative risk analysis for a state road crossing an area of southern Italian Apennines diffusively affected by slow-moving landslides. In this area, Palaeozoic gneissic rocks suffering from intense weathering processes, which produce complex and deep weathering profiles, are present, and this determines severe predisposing conditions to deep-seated slow-moving landslides. Although not directly threatening human lives, for years these slope instabilities have been causing damage and temporary traffic interruptions or limitations to many road sections. To pursue a sustainable landslide risk management, a method that fully exploits multi-disciplinary data consisting of geological-geomorphological features, geotechnical characterization of geomaterials, both conventional (i.e. GPS and inclinometer) and remote sensing (i.e. MT-DInSAR) displacement measurements, in-situ and virtual (i.e. Google Street View images) surveys, and probabilistic tools (i.e. fragility and vulnerability curves) is implemented. As a novelty, such a rich dataset allows overcoming some limitations of the (few) previous studies in the scientific literature on the analysis of the risk posed by slow-moving landslides to roads by exploiting <em>i)</em> the multi-temporal recording of the road damage to catch the response of the infrastructure (i.e. both the road pavement and the side retaining structures) with time, and <em>ii)</em> the association of the cumulative landslide-induced displacements with the corresponding damage in order to feed empirical forecasting tools for consequence analyses. The thorough knowledge of the slow-moving landslides and their interaction with the exposed roads are implemented within the proposed method to assess the direct economic losses in terms of repair costs, should no countermeasures or mitigation works be implemented in due time. Considering that the studied area resembles very typical conditions of inner roads in hilly and mountain areas of southern Italy, the method can represent a valuable tool for decision makers to prioritize money allocation for risk adaptation and mitigation actions for roads in similar geo-environmental contexts.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"350 ","pages":"Article 108011"},"PeriodicalIF":6.9,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contact-dependent inertial number and μ(I) rheology for dry rock-ice granular materials","authors":"Yuhao Ren ,&nbsp;Fei Cai ,&nbsp;Qingqing Yang ,&nbsp;Zhiman Su","doi":"10.1016/j.enggeo.2025.107995","DOIUrl":"10.1016/j.enggeo.2025.107995","url":null,"abstract":"<div><div>To gain a deep understanding of the dynamics of dry rock-ice granular flows, the local rheology was investigated numerically. For mono-disperse granular materials, theoretically, the <em>μ</em>(<em>I</em>) rheology describes the relationship between the effective friction coefficient <em>μ</em> and inertial number <em>I</em>, and the solid volume fraction <em>Φ</em> depends linearly on the inertial number. The generality of these two relationships, however, remains unclear for the dry rock-ice granular materials that are dispersed in particle size, density, and surficial friction coefficient. This work numerically investigated the rock-ice mixtures flowing down a tilting flume using the discrete element method. A contact-dependent averaging method was proposed to determine the local inertial number integrating the contribution of all binary contacts. Moreover, a method was developed to predict the proportions of rock-rock, rock-ice, and ice-ice type of contacts, based on the coordination number. Specifically, the inter-phase coordination number ratio approaches the product of the inter-phase size and number ratios, enabling accurate predictions of contact proportions. The simulations demonstrate the numerical applicability of the <em>μ</em>(<em>I</em>) rheology and linear <em>Φ</em>(<em>I</em>) dependence to the bi- or poly-disperse dry rock-ice granular materials. Ice fragmentation significantly enhances the mixture mobility due to the increasing prevalence of ice-related contacts which exhibit lower friction. Compared with the commonly used volume-fraction averaged inertial number, the contact-proportion averaged inertial number incorporates local contact information, and its effect becomes more pronounced at higher size ratios and lower number ratios. These results underscore the importance of the particle dispersity of rock-ice granular materials, particularly in the case with substantial differences in particle size and number. The findings offer particle-scale insights for future research on friction and melting in rock-ice avalanches, while they need validation with experiments or field data.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"350 ","pages":"Article 107995"},"PeriodicalIF":6.9,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143632083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning-based inversion framework for fractured media characterization by assimilating hydraulic tomography and thermal tracer tomography data: Numerical and field study","authors":"Cihai Chen ,&nbsp;Yaping Deng ,&nbsp;Jiazhong Qian ,&nbsp;Haichun Ma ,&nbsp;Lei Ma ,&nbsp;Jichun Wu ,&nbsp;Hui Wu","doi":"10.1016/j.enggeo.2025.107998","DOIUrl":"10.1016/j.enggeo.2025.107998","url":null,"abstract":"<div><div>Accurate characterization of fractured media is fundamental in the geological and geotechnical engineering applications such as coal mine production, deep geological disposal and enhanced geothermal systems (EGS). However, traditional inversion strategies are limited in their ability to characterize high-dimensional and non-Gaussian fractured media. Furthermore, a significant amount of observation well was employed during the inversion process in the previous studies. In this work, we proposed a joint inversion framework based on deep learning technique to overcome the limitations of the traditional strategies and the challenge of excessive use of observation wells. The convolutional variational autoencoder (CVAE) network was trained to parameterize the fractured media. After that, the ensemble smoother with multiple data assimilation (ESMDA) combined with the CVAE to characterize fractured media assimilating the hydraulic tomography (HT) and thermal tracer tomography (TT) data. A numerical study using four observation points validates the framework's reliability. The characterization errors for single-data cases are 16.9 % (HT) and 18.1 % (TT), decreasing to 16.7 % when both types of data are incorporated, demonstrating the synergies of multisource data. Sequentially, the framework is extended to the real-world scenario. The results show that our framework can effectively characterize the fractured media, capturing more features while addressing the challenge posed by excessive use of observation wells through the integration of multisource data. Our framework provides valuable insights into the characterization of fractured media in the practical engineering applications and highlights the benefits of multisource data assimilation.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"350 ","pages":"Article 107998"},"PeriodicalIF":6.9,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterizing uncertainty and variability in shear wave velocity profiles from the Italian seismic microzonation studies","authors":"Federico Mori ,&nbsp;Giuseppe Naso ,&nbsp;Amerigo Mendicelli ,&nbsp;Giancarlo Ciotoli ,&nbsp;Chiara Varone ,&nbsp;Massimiliano Moscatelli","doi":"10.1016/j.enggeo.2025.107997","DOIUrl":"10.1016/j.enggeo.2025.107997","url":null,"abstract":"<div><div>This study investigates the variability and uncertainty of shear wave velocity (Vs) with depth, focusing on the standard deviation of the natural logarithm of Vs (σlnVs) using a dataset of nearly 15,000 profiles from the Italian seismic microzonation studies. Seismic microzone clusters (SM), defined by geological and geophysical homogeneity, and geographical clusters (GC), based on survey density, were compared to evaluate their effectiveness in characterizing σlnVs variability.</div><div>Spatial correlation analyses were performed to define high-quality SM clusters, ensuring strong internal geological and geophysical consistency with a maximum pairwise distance of 4.5 km between Vs profiles. Results demonstrate that SM clusters reduce σlnVs uncertainty by 14 % within the first 30 m, 9 % from 30 to 50 m, and 4 % from 50 to 80 m compared to GC clusters, highlighting the value of geological and geophysical refinement. These results can support a more accurate randomization of Vs profiles with depth in local seismic response analyses using 1D simulation codes, improving the reliability of site-specific seismic hazard assessments. The findings are validated against literature uncertainty thresholds, confirming the robustness of the SM approach.</div><div>By analyzing 1120 SM clusters, this study offers a comprehensive framework for propagating uncertainties in seismic response simulations and surpasses the limitations of localized case studies.</div><div>The large dataset of Vs profiles, associated with SM clusters, is publicly available at <span><span>https://doi.org/10.5281/zenodo.11263471</span><svg><path></path></svg></span> (<span><span>Mori et al., 2024</span></span>).</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"350 ","pages":"Article 107997"},"PeriodicalIF":6.9,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of morphological features and mechanical behavior of jointed limestone subjected to wet-dry cycles and cyclic shear in drawdown areas of the Three Gorges Reservoir","authors":"Qiang Xie ,&nbsp;YuCheng Chen ,&nbsp;Zhangrui Wu ,&nbsp;Haiyou Peng ,&nbsp;Xiang Fu ,&nbsp;Yuxin Ban","doi":"10.1016/j.enggeo.2025.107990","DOIUrl":"10.1016/j.enggeo.2025.107990","url":null,"abstract":"<div><div>Reservoir drawdown induces cyclic water level fluctuations, exposing geomaterials in drawdown areas to repetitive wet-dry cycles and cyclic shearing forces. Understanding the deterioration mechanisms of geomaterials under these conditions is crucial for ensuring the long-term stability of the geomaterials in drawdown areas. This study systematically explores the deterioration mechanisms of jointed limestone from the Three Gorges Reservoir region under these dual effects. Employing three-dimensional white light scanning and EDS (energy dispersive spectroscopy) technology, the morphological and chemical evolution of rock joints was quantitatively characterized. The modified JRC-JCS (joint roughness coefficient-joint wall compressive strength) model was utilized to predict shear strength. The findings reveal that with the increase of wet-dry cycles and cyclic shears times, the surface of joints becomes progressively smoother, and the deterioration rate of shear strength gradually decreases. Cyclic shear primarily damages micro-protrusions, while wet-dry cycling affects both protruding and recessed areas through the dissolution of soluble mineral crystals. Compared with other typical model, the modified JRC-JCS model demonstrated better accuracy in predicting shear strength. The findings reveal the deterioration mechanisms of geomaterials in drawdown areas, providing essential insights for assessing the long-term stability of jointed rock mass in these regions.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"350 ","pages":"Article 107990"},"PeriodicalIF":6.9,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient probabilistic tunning of large geological model (LGM) for underground digital twin","authors":"Wei Yan ,&nbsp;Caiyan Yang ,&nbsp;Ping Shen ,&nbsp;Wan-Huan Zhou","doi":"10.1016/j.enggeo.2025.107996","DOIUrl":"10.1016/j.enggeo.2025.107996","url":null,"abstract":"<div><div>Urban large geological models (LGMs) are essential for characterizing subsurface conditions for underground digital twins, facilitating informed decision-making. Incorporating uncertainty and efficient tuning methods for LGMs are indispensable technologies for enhancing reliability with dynamic geotechnical databases, yet these aspects are not fully addressed in current studies. This research proposes a novel framework to develop the first probabilistic tunable LGM, integrating local stratification knowledge and real borehole measurements. Local stratifications are collected from experienced engineering geologists and interpreted as virtual boreholes. These virtual boreholes are inputted into the stratum-informed random field-based method (SI-RFB) to develop geological prior for the LGM. Then, the spatial sequential Bayesian updating (SSBU) algorithm is utilized to partially tune the LGM with on-site borehole data. The influence zones of updating are mathematically predetermined based on project-specific borehole spacing. The effectiveness of the proposed framework is demonstrated through a simulated 3D case referencing a site in Macao. Furthermore, the proposed model is applied to develop a tunable urban LGM for the landfill region in the Macao Peninsula covering 6.4 km². The results emphasize the framework's ability to effectively tune the LGM, enhancing details and reducing uncertainty. Importantly, the method is computationally efficient, accounting only for up to 0.3 % of the conventional reconstruction cost for the same area, thereby providing an economically viable solution for underground digital twins.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"350 ","pages":"Article 107996"},"PeriodicalIF":6.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flash flood impacts and vulnerability mapping at catchment scale: Insights from southern Apennines","authors":"Giovanni Forte ,&nbsp;Melania De Falco ,&nbsp;Antonio Santo ,&nbsp;Dipendra Gautam ,&nbsp;Nicoletta Santangelo","doi":"10.1016/j.enggeo.2025.107988","DOIUrl":"10.1016/j.enggeo.2025.107988","url":null,"abstract":"<div><div>Flash floods are frequent natural hazard events in many parts of the world. Generally, they occur in small catchments drained by torrential streams that feed alluvial fans or fan deltas. In the Mediterranean region, these phenomena are particularly common during the spring and autumn seasons, often causing significant damage to buildings, infrastructures, agriculture, and sometimes resulting in fatalities and injuries. To better understand and manage the potential consequences of these events on physical systems, probabilistic damage quantification is essential. Fragility functions, which describe the probability of reaching or exceeding a specific damage state based on an intensity measure, are valuable tools for assessing damage conditioned on the intensity of a natural hazard. While such curves are widely reported and extensively applied, there is a notable lack of interdisciplinary methodologies for their development and integration into broader risk management frameworks. This gap often leaves initiatives such as flood insurance premium planning, probabilistic loss estimation, and flood risk management reliant on uninformed or generic tools.</div><div>This study proposes an interdisciplinary approach to developing flood fragility functions using post-event flash flood damage data. The event that occurred on 14–15 October 2015 in Solopaca – Paupisi area (Benevento, Italy) is adopted as the case study. The reactivation of alluvial fan lobes is analyzed together with the recorded rainfalls. It is based on the processing of post-event field data acquired with classical and remote sensing technologies such as UAV imagery. Impact mapping is then conducted to depict the spatial extent of the flash flood. The event is then characterized in terms of inundation depth and thickness of mobilized material and grain size distribution. The area of the event and the thickness of the deposits are considered to estimate the transported solid volumes. Finally, the damage incurred to buildings and respective inundation depth is assembled to construct flash flood fragility functions. The outcomes of this study can be used in numerical flow model calibration and validation as well as flash flood risk assessment and management initiatives. The fragility functions developed in this study can serve as a tool for loss assessment, resilient construction prioritization, and insurance premium planning. The interdisciplinary approach developed and implemented in this study will be insightful to many other regions across the world in terms of flash flood mitigation planning.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"350 ","pages":"Article 107988"},"PeriodicalIF":6.9,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time-series InSAR landslide three-dimensional deformation prediction method considering meteorological time-delay effects","authors":"Jichao Lv,&nbsp;Rui Zhang,&nbsp;Xin Bao,&nbsp;Renzhe Wu,&nbsp;Ruikai Hong,&nbsp;Xu He,&nbsp;Guoxiang Liu","doi":"10.1016/j.enggeo.2025.107986","DOIUrl":"10.1016/j.enggeo.2025.107986","url":null,"abstract":"<div><div>Landslide deformation prediction is a critical component of disaster early warning systems and significantly contributes to disaster prevention and mitigation. However, the high cost of traditional deformation monitoring equipment limits its extensive application across large areas. Furthermore, existing landslide deformation prediction methods often overlook the nonlinear influence of meteorological conditions. This study introduces a novel framework for predicting three-dimensional landslide deformations by employing time-series interferometric synthetic aperture radar (InSAR), which accounts for the time-delay effects of meteorological factors. First, the framework leverages ascending and descending orbit time-series InSAR technology to generate three-dimensional deformation data for landslides. Subsequently, the deformation data were decomposed into trend and periodic components using the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method. An autoregressive integrated moving average (ARIMA) model was developed for trend prediction, and an improved unscented Kalman filtering (UKF) model was developed for the periodic component. The prediction of the periodic component uses a second-order Taylor series and adaptive adjustments of observation and process noise covariance matrices to create a UKF deformation prediction model that incorporates meteorological time-delay effects. The method's effectiveness was validated through experiments on the Xiongba and Sela landslides in Gongjue County, Tibet. Results demonstrated that ascending and descending orbit time-series InSAR technology can accurately detect three-dimensional deformation, revealing maximum deformation rates of 43.81 cm/year for the Xiongba landslide and 31.83 cm/year for the Sela landslide. For the trend component, the ARIMA model achieved a correlation coefficient (R²) exceeding 0.9 and root mean square error (RMSE) below 1.0 cm across multiple monitoring points. Regarding the periodic component, the framework's reliability was first confirmed through simulation experiments. Further analyses of the Xiongba and Sela landslides revealed that rainfall and temperature exhibit distinct time-delay effects on deformation. Incorporating meteorological data into the improved UKF model significantly enhanced the prediction accuracy, yielding R² values between 0.8 and 0.9, with the RMSE and mean square error (MAE) outperforming those of the long short-term memory (LSTM) and recurrent neural network (RNN) comparison models. Overall, the proposed framework offers vital technical support for risk prediction and early warning of large-scale landslide disasters, facilitating more accurate landslide forecasting.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"350 ","pages":"Article 107986"},"PeriodicalIF":6.9,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}