Articles | Volume 19, issue 5
https://doi.org/10.5194/nhess-19-999-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-19-999-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 May 2019
Research article |
| 07 May 2019
| 07 May 2019
Landslide susceptibility mapping by using a geographic information system (GIS) along the China–Pakistan Economic Corridor (Karakoram Highway), Pakistan
Neotectonics and Natural Hazards, RWTH Aachen University, Lochnerstr. 4–20, 52056 Aachen, Germany
Department of Earth Sciences, COMSATS Information Technology, Abbottabad, Pakistan
Peter Biermanns
Neotectonics and Natural Hazards, RWTH Aachen University, Lochnerstr. 4–20, 52056 Aachen, Germany
Rashid Haider
Geological Survey of Pakistan, Islamabad, Pakistan
Klaus Reicherter
Neotectonics and Natural Hazards, RWTH Aachen University, Lochnerstr. 4–20, 52056 Aachen, Germany
Related authors
Rashid Haider, Sajid Ali, Gösta Hoffmann, and Klaus Reicherter
Nat. Hazards Earth Syst. Sci., 24, 3279–3290, https://doi.org/10.5194/nhess-24-3279-2024, https://doi.org/10.5194/nhess-24-3279-2024, 2024
Short summary
Short summary
The coastlines bordering the Arabian Sea have yielded various tsunamites reflecting its high hazard potential and recurrences. My PhD project aims at the estimation and zonation of the hazards and risks associated with. This publication is a continuation of the previous publication (Haider et al., 2023), which focused on hazard estimation through a multi-proxy approach. This part of the study estimates the risk potential through integrated tsunami inundation analysis.
Alejandro Jiménez-Bonilla, Lucía Martegani, Miguel Rodríguez-Rodríguez, Fernando Gázquez, Manuel Díaz-Azpíroz, Sergio Martos, Klaus Reicherter, and Inmaculada Expósito
Hydrol. Earth Syst. Sci., 28, 5311–5329, https://doi.org/10.5194/hess-28-5311-2024, https://doi.org/10.5194/hess-28-5311-2024, 2024
Short summary
Short summary
We conducted an interdisciplinary study of the Fuente de Piedra playa lake's evolution in southern Spain. We made water balances for the Fuente de Piedra playa lake's lifespan. Our results indicate that the Fuente de Piedra playa lake's level moved and tilted south-west, which was caused by active faults.
Rashid Haider, Sajid Ali, Gösta Hoffmann, and Klaus Reicherter
Nat. Hazards Earth Syst. Sci., 24, 3279–3290, https://doi.org/10.5194/nhess-24-3279-2024, https://doi.org/10.5194/nhess-24-3279-2024, 2024
Short summary
Short summary
The coastlines bordering the Arabian Sea have yielded various tsunamites reflecting its high hazard potential and recurrences. My PhD project aims at the estimation and zonation of the hazards and risks associated with. This publication is a continuation of the previous publication (Haider et al., 2023), which focused on hazard estimation through a multi-proxy approach. This part of the study estimates the risk potential through integrated tsunami inundation analysis.
Claudia Finger, Marco P. Roth, Marco Dietl, Aileen Gotowik, Nina Engels, Rebecca M. Harrington, Brigitte Knapmeyer-Endrun, Klaus Reicherter, Thomas Oswald, Thomas Reinsch, and Erik H. Saenger
Earth Syst. Sci. Data, 15, 2655–2666, https://doi.org/10.5194/essd-15-2655-2023, https://doi.org/10.5194/essd-15-2655-2023, 2023
Short summary
Short summary
Passive seismic analyses are a key technology for geothermal projects. The Lower Rhine Embayment, at the western border of North Rhine-Westphalia in Germany, is a geologically complex region with high potential for geothermal exploitation. Here, we report on a passive seismic dataset recorded with 48 seismic stations and a total extent of 20 km. We demonstrate that the network design allows for the application of state-of-the-art seismological methods.
Peter Biermanns, Benjamin Schmitz, Silke Mechernich, Christopher Weismüller, Kujtim Onuzi, Kamil Ustaszewski, and Klaus Reicherter
Solid Earth, 13, 957–974, https://doi.org/10.5194/se-13-957-2022, https://doi.org/10.5194/se-13-957-2022, 2022
Short summary
Short summary
We introduce two up to 7 km long normal fault scarps near the city of Bar (Montenegro). The fact that these widely visible seismogenic structures have never been described before is even less surprising than the circumstance that they apparently do not fit the tectonic setting that they are located in. By quantifying the age and movement of the newly discovered fault scarps and by partly re-interpreting local tectonics, we introduce approaches to explain how this is still compatible.
Christoph Grützner, Simone Aschenbrenner, Petra Jamšek
Rupnik, Klaus Reicherter, Nour Saifelislam, Blaž Vičič, Marko Vrabec, Julian Welte, and Kamil Ustaszewski
Solid Earth, 12, 2211–2234, https://doi.org/10.5194/se-12-2211-2021, https://doi.org/10.5194/se-12-2211-2021, 2021
Short summary
Short summary
Several large strike-slip faults in western Slovenia are known to be active, but most of them have not produced strong earthquakes in historical times. In this study we use geomorphology, near-surface geophysics, and fault excavations to show that two of these faults had surface-rupturing earthquakes during the Holocene. Instrumental and historical seismicity data do not capture the strongest events in this area.
Sarah Mader, Joachim R. R. Ritter, Klaus Reicherter, and the AlpArray Working Group
Solid Earth, 12, 1389–1409, https://doi.org/10.5194/se-12-1389-2021, https://doi.org/10.5194/se-12-1389-2021, 2021
Short summary
Short summary
The Albstadt Shear Zone, SW Germany, is an active rupture zone with sometimes damaging earthquakes but no visible surface structure. To identify its segmentations, geometry, faulting pattern and extension, we analyze the continuous earthquake activity in 2011–2018. We find a segmented N–S-oriented fault zone with mainly horizontal and minor vertical movement along mostly NNE- and some NNW-oriented rupture planes. The main horizontal stress is oriented NW and due to Alpine-related loading.
Christopher Weismüller, Rahul Prabhakaran, Martijn Passchier, Janos L. Urai, Giovanni Bertotti, and Klaus Reicherter
Solid Earth, 11, 1773–1802, https://doi.org/10.5194/se-11-1773-2020, https://doi.org/10.5194/se-11-1773-2020, 2020
Short summary
Short summary
We photographed a fractured limestone pavement with a drone to compare manual and automatic fracture tracing and analyze the evolution and spatial variation of the fracture network in high resolution. We show that automated tools can produce results comparable to manual tracing in shorter time but do not yet allow the interpretation of fracture generations. This work pioneers the automatic fracture mapping of a complete outcrop in detail, and the results can be used as fracture benchmark.
Christopher Weismüller, Janos L. Urai, Michael Kettermann, Christoph von Hagke, and Klaus Reicherter
Solid Earth, 10, 1757–1784, https://doi.org/10.5194/se-10-1757-2019, https://doi.org/10.5194/se-10-1757-2019, 2019
Short summary
Short summary
We use drones to study surface geometries of massively dilatant faults (MDFs) in Iceland, with apertures up to tens of meters at the surface. Based on throw, aperture and structures, we define three geometrically different endmembers of the surface expression of MDFs and show that they belong to one continuum. The transition between the endmembers is fluent and can change at one fault over short distances, implying less distinct control of deeper structures on surface geometries than expected.
Sascha Schneiderwind, Jack Mason, Thomas Wiatr, Ioannis Papanikolaou, and Klaus Reicherter
Solid Earth, 7, 323–340, https://doi.org/10.5194/se-7-323-2016, https://doi.org/10.5194/se-7-323-2016, 2016
Short summary
Short summary
Palaeoseismological research uses historical earthquakes to verify seismic hazard assessment. Earthquakes of magnitude M > 5.5 likely produce surface ruptures that can be preserved in the subsurface. Buried soils or progressive displacements are the main targets of trenching studies. However, the recognition of these features is challenging for inexperienced researchers. Here a workflow is presented which applies remote sensing and geophysical techniques to verify layer distinction.
M. Kettermann, C. Grützner, H. W. van Gent, J. L. Urai, K. Reicherter, and J. Mertens
Solid Earth, 6, 839–855, https://doi.org/10.5194/se-6-839-2015, https://doi.org/10.5194/se-6-839-2015, 2015
Short summary
Short summary
This paper combines fieldwork, ground-penetrating radar (GPR) and remote sensing in the jointed and faulted grabens area of Canyonlands National Park, Utah, USA. GPR profiles show that graben floors are subject to faulting, although the surface shows no scarps. We enhance evidence for the effect of preexisting joints on the formation of dilatant faults and provide a conceptual model for graben evolution. Correlating paleosols from outcrops and GPR adds to estimates of the age of the grabens.
M. Kehl, E. Eckmeier, S. O. Franz, F. Lehmkuhl, J. Soler, N. Soler, K. Reicherter, and G.-C. Weniger
Clim. Past, 10, 1673–1692, https://doi.org/10.5194/cp-10-1673-2014, https://doi.org/10.5194/cp-10-1673-2014, 2014
B. Wagner, T. Wilke, S. Krastel, G. Zanchetta, R. Sulpizio, K. Reicherter, M. J. Leng, A. Grazhdani, S. Trajanovski, A. Francke, K. Lindhorst, Z. Levkov, A. Cvetkoska, J. M. Reed, X. Zhang, J. H. Lacey, T. Wonik, H. Baumgarten, and H. Vogel
Sci. Dril., 17, 19–29, https://doi.org/10.5194/sd-17-19-2014, https://doi.org/10.5194/sd-17-19-2014, 2014
Related subject area
Landslides and Debris Flows Hazards
The vulnerability of buildings to a large-scale debris flow and outburst flood hazard cascade that occurred on 30 August 2020 in Ganluo, southwest China
Optimizing rainfall-triggered landslide thresholds for daily landslide hazard warning in the Three Gorges Reservoir area
Brief communication: Monitoring impending slope failure with very high-resolution spaceborne synthetic aperture radar
Size scaling of large landslides from incomplete inventories
InSAR-informed in situ monitoring for deep-seated landslides: insights from El Forn (Andorra)
A coupled hydrological and hydrodynamic modeling approach for estimating rainfall thresholds of debris-flow occurrence
More than one landslide per road kilometer – surveying and modeling mass movements along the Rishikesh–Joshimath (NH-7) highway, Uttarakhand, India
An integrated method for assessing vulnerability of buildings caused by debris flows in mountainous areas
Temporal clustering of precipitation for detection of potential landslides
Shallow-landslide stability evaluation in loess areas according to the Revised Infinite Slope Model: a case study of the 7.25 Tianshui sliding-flow landslide events of 2013 in the southwest of the Loess Plateau, China
Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall
Evaluating post-wildfire debris-flow rainfall thresholds and volume models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA
Predicting Deep-Seated Landslide Displacements in Mountains through the Integration of Convolutional Neural Networks and Age of Exploration-Inspired Optimizer
Addressing class imbalance in soil movement predictions
Assessing the impact of climate change on landslides near Vejle, Denmark, using public data
Predicting the thickness of shallow landslides in Switzerland using machine learning
Analysis of three-dimensional slope stability combined with rainfall and earthquake
Assessing landslide damming susceptibility in Central Asia
Invited Perspectives: Integrating hydrologic information into the next generation of landslide early warning systems
Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico
Evaluation of debris-flow building damage forecasts
Characteristics of debris-flow-prone watersheds and debris-flow-triggering rainstorms following the Tadpole Fire, New Mexico, USA
Morphological characteristics and conditions of drainage basins contributing to the formation of debris flow fans: an examination of regions with different rock strength using decision tree analysis
Characterizing the scale of regional landslide triggering from storm hydrometeorology
Comparison of debris flow observations, including fine-sediment grain size and composition and runout model results, at Illgraben, Swiss Alps
Simulation analysis of 3D stability of a landslide with a locking segment: a case study of the Tizicao landslide in Maoxian County, southwest China
Space–time landslide hazard modeling via Ensemble Neural Networks
Optimization strategy for flexible barrier structures: investigation and back analysis of a rockfall disaster case in southwestern China
Comparison of conditioning factors classification criteria in large scale statistically based landslide susceptibility models
Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment
Slope Unit Maker (SUMak): an efficient and parameter-free algorithm for delineating slope units to improve landslide modeling
Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling
Limit analysis of earthquake-induced landslides considering two strength envelopes
Exploratory analysis of the annual risk to life from debris flows
A new analytical method for stability analysis of rock blocks with basal erosion in sub-horizontal strata by considering the eccentricity effect
Rockfall monitoring with a Doppler radar on an active rockslide complex in Brienz/Brinzauls (Switzerland)
Landslide initiation thresholds in data-sparse regions: application to landslide early warning criteria in Sitka, Alaska, USA
Lessons learnt from a rockfall time series analysis: data collection, statistical analysis, and applications
The concept of event-size-dependent exhaustion and its application to paraglacial rockslides
Coastal earthquake-induced landslide susceptibility during the 2016 Mw 7.8 Kaikōura earthquake, New Zealand
Characteristics of debris flows recorded in the Shenmu area of central Taiwan between 2004 and 2021
Semi-automatic mapping of shallow landslides using free Sentinel-2 images and Google Earth Engine
The role of thermokarst evolution in debris flow initiation (Hüttekar Rock Glacier, Austrian Alps)
Accounting for the effect of forest and fragmentation in probabilistic rockfall hazard
Comprehensive landslide susceptibility map of Central Asia
The influence of large woody debris on post-wildfire debris flow sediment storage
Statistical modeling of sediment supply in torrent catchments of the northern French Alps
A data-driven evaluation of post-fire landslide susceptibility
Deciphering seasonal effects of triggering and preparatory precipitation for improved shallow landslide prediction using generalized additive mixed models
Brief communication: The northwest Himalaya towns slipping towards potential disaster
Li Wei, Kaiheng Hu, Shuang Liu, Lan Ning, Xiaopeng Zhang, Qiyuan Zhang, and Md. Abdur Rahim
Nat. Hazards Earth Syst. Sci., 24, 4179–4197, https://doi.org/10.5194/nhess-24-4179-2024, https://doi.org/10.5194/nhess-24-4179-2024, 2024
Short summary
Short summary
The damage patterns of the buildings were classified into three types: (I) buried by primary debris flow, (II) inundated by secondary dam-burst flood, and (III) sequentially buried by debris flow and inundated by dam-burst flood. The threshold of the impact pressures in Zones (II) and (III) where vulnerability is equal to 1 is 84 kPa and 116 kPa, respectively. Heavy damage occurs at an impact pressure greater than 50 kPa, while slight damage occurs below 30 kPa.
Bo Peng and Xueling Wu
Nat. Hazards Earth Syst. Sci., 24, 3991–4013, https://doi.org/10.5194/nhess-24-3991-2024, https://doi.org/10.5194/nhess-24-3991-2024, 2024
Short summary
Short summary
Our research enhances landslide prevention using advanced machine learning to forecast heavy-rainfall-triggered landslides. By analyzing regions and employing various models, we identified optimal ways to predict high-risk rainfall events. Integrating multiple factors and models, including a neural network, significantly improves landslide predictions. Real data validation confirms our approach's reliability, aiding communities in mitigating landslide impacts and safeguarding lives and property.
Andrea Manconi, Yves Bühler, Andreas Stoffel, Johan Gaume, Qiaoping Zhang, and Valentyn Tolpekin
Nat. Hazards Earth Syst. Sci., 24, 3833–3839, https://doi.org/10.5194/nhess-24-3833-2024, https://doi.org/10.5194/nhess-24-3833-2024, 2024
Short summary
Short summary
Our research reveals the power of high-resolution satellite synthetic-aperture radar (SAR) imagery for slope deformation monitoring. Using ICEYE data over the Brienz/Brinzauls instability, we measured surface velocity and mapped the landslide event with unprecedented precision. This underscores the potential of satellite SAR for timely hazard assessment in remote regions and aiding disaster mitigation efforts effectively.
Oliver Korup, Lisa V. Luna, and Joaquin V. Ferrer
Nat. Hazards Earth Syst. Sci., 24, 3815–3832, https://doi.org/10.5194/nhess-24-3815-2024, https://doi.org/10.5194/nhess-24-3815-2024, 2024
Short summary
Short summary
Catalogues of mapped landslides are useful for learning and forecasting how frequently they occur in relation to their size. Yet, rare and large landslides remain mostly uncertain in statistical summaries of these catalogues. We propose a single, consistent method of comparing across different data sources and find that landslide statistics disclose more about subjective mapping choices than trigger types or environmental settings.
Rachael Lau, Carolina Seguí, Tyler Waterman, Nathaniel Chaney, and Manolis Veveakis
Nat. Hazards Earth Syst. Sci., 24, 3651–3661, https://doi.org/10.5194/nhess-24-3651-2024, https://doi.org/10.5194/nhess-24-3651-2024, 2024
Short summary
Short summary
This work examines the use of interferometric synthetic-aperture radar (InSAR) alongside in situ borehole measurements to assess the stability of deep-seated landslides for the case study of El Forn (Andorra). Comparing InSAR with borehole data suggests a key trade-off between accuracy and precision for various InSAR resolutions. Spatial interpolation with InSAR informed how many remote observations are necessary to lower error in a remote sensing re-creation of ground motion over the landslide.
Zhen Lei Wei, Yue Quan Shang, Qiu Hua Liang, and Xi Lin Xia
Nat. Hazards Earth Syst. Sci., 24, 3357–3379, https://doi.org/10.5194/nhess-24-3357-2024, https://doi.org/10.5194/nhess-24-3357-2024, 2024
Short summary
Short summary
The initiation of debris flows is significantly influenced by rainfall-induced hydrological processes. We propose a novel framework based on an integrated hydrological and hydrodynamic model and aimed at estimating intensity–duration (ID) rainfall thresholds responsible for triggering debris flows. In comparison to traditional statistical approaches, this physically based framework is particularly suitable for application in ungauged catchments where historical debris flow data are scarce.
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci., 24, 3207–3223, https://doi.org/10.5194/nhess-24-3207-2024, https://doi.org/10.5194/nhess-24-3207-2024, 2024
Short summary
Short summary
The Himalayan road network links remote areas, but fragile terrain and poor construction lead to frequent landslides. This study on the NH-7 in India's Uttarakhand region analyzed 300 landslides after heavy rainfall in 2022 . Factors like slope, rainfall, rock type and road work influence landslides. The study's model predicts landslide locations for better road maintenance planning, highlighting the risk from climate change and increased road use.
Chenchen Qiu and Xueyu Geng
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-156, https://doi.org/10.5194/nhess-2024-156, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
We proposed an interated method with the combination of a physical vulnerability matric and a machine learning model to estimate the potential physical damage and associated economic loss caused by future debris flows based on the collected historical data on the Qinghai-Tibet Plateau regions.
Fabiola Banfi, Emanuele Bevacqua, Pauline Rivoire, Sérgio C. Oliveira, Joaquim G. Pinto, Alexandre M. Ramos, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 24, 2689–2704, https://doi.org/10.5194/nhess-24-2689-2024, https://doi.org/10.5194/nhess-24-2689-2024, 2024
Short summary
Short summary
Landslides are complex phenomena causing important impacts in vulnerable areas, and they are often triggered by rainfall. Here, we develop a new approach that uses information on the temporal clustering of rainfall, i.e. multiple events close in time, to detect landslide events and compare it with the use of classical empirical rainfall thresholds, considering as a case study the region of Lisbon, Portugal. The results could help to improve the prediction of rainfall-triggered landslides.
Jianqi Zhuang, Jianbing Peng, Chenhui Du, Yi Zhu, and Jiaxu Kong
Nat. Hazards Earth Syst. Sci., 24, 2615–2631, https://doi.org/10.5194/nhess-24-2615-2024, https://doi.org/10.5194/nhess-24-2615-2024, 2024
Short summary
Short summary
The Revised Infinite Slope Model (RISM) is proposed using the equal differential unit method and correcting the deficiency of the safety factor increasing with the slope increasing when the slope is larger than 40°, as calculated using the Taylor slope infinite model. The intensity–duration (I–D) prediction curve of the rainfall-induced shallow loess landslides with different slopes was constructed and can be used in forecasting regional shallow loess landslides.
Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley
Nat. Hazards Earth Syst. Sci., 24, 2359–2374, https://doi.org/10.5194/nhess-24-2359-2024, https://doi.org/10.5194/nhess-24-2359-2024, 2024
Short summary
Short summary
Fire can dramatically increase the risk of debris flows to downstream communities with little warning, but hazard assessments have not traditionally included estimates of inundation. We unify models developed by the scientific community to create probabilistic estimates of inundation area in response to rainfall at forecast lead times (≥ 24 h) needed for decision-making. This work takes an initial step toward a near-real-time postfire debris-flow inundation hazard assessment product.
Francis K. Rengers, Samuel Bower, Andrew Knapp, Jason W. Kean, Danielle W. vonLembke, Matthew A. Thomas, Jaime Kostelnik, Katherine R. Barnhart, Matthew Bethel, Joseph E. Gartner, Madeline Hille, Dennis M. Staley, Justin K. Anderson, Elizabeth K. Roberts, Stephen B. DeLong, Belize Lane, Paxton Ridgway, and Brendan P. Murphy
Nat. Hazards Earth Syst. Sci., 24, 2093–2114, https://doi.org/10.5194/nhess-24-2093-2024, https://doi.org/10.5194/nhess-24-2093-2024, 2024
Short summary
Short summary
Every year the U.S. Geological Survey produces 50–100 postfire debris-flow hazard assessments using models for debris-flow likelihood and volume. To refine these models they must be tested with datasets that clearly document rainfall, debris-flow response, and debris-flow volume. These datasets are difficult to obtain, but this study developed and analyzed a postfire dataset with more than 100 postfire storm responses over a 2-year period. We also proposed ways to improve these models.
Jui-Sheng Chou, Hoang-Minh Nguyen, Huy-Phuong Phan, and Kuo-Lung Wang
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-86, https://doi.org/10.5194/nhess-2024-86, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
This study enhances landslide prediction using advanced machine learning, including new algorithms inspired by historical explorations. The research accurately forecasts landslide movements by analyzing eight years of data from Taiwan's Lushan Mountain, improving early warnings and potentially saving lives and infrastructure. This integration marks a significant advancement in environmental risk management.
Praveen Kumar, Priyanka Priyanka, Kala Venkata Uday, and Varun Dutt
Nat. Hazards Earth Syst. Sci., 24, 1913–1928, https://doi.org/10.5194/nhess-24-1913-2024, https://doi.org/10.5194/nhess-24-1913-2024, 2024
Short summary
Short summary
Our study focuses on predicting soil movement to mitigate landslide risks. We develop machine learning models with oversampling techniques to address the class imbalance in monitoring data. The dynamic ensemble model with K-means SMOTE (synthetic minority oversampling technique) achieves high precision, high recall, and a high F1 score. Our findings highlight the potential of these models with oversampling techniques to improve soil movement predictions in landslide-prone areas.
Kristian Svennevig, Julian Koch, Marie Keiding, and Gregor Luetzenburg
Nat. Hazards Earth Syst. Sci., 24, 1897–1911, https://doi.org/10.5194/nhess-24-1897-2024, https://doi.org/10.5194/nhess-24-1897-2024, 2024
Short summary
Short summary
In our study, we analysed publicly available data in order to investigate the impact of climate change on landslides in Denmark. Our research indicates that the rising groundwater table due to climate change will result in an increase in landslide activity. Previous incidents of extremely wet winters have caused damage to infrastructure and buildings due to landslides. This study is the first of its kind to exclusively rely on public data and examine landslides in Denmark.
Christoph Schaller, Luuk Dorren, Massimiliano Schwarz, Christine Moos, Arie C. Seijmonsbergen, and E. Emiel van Loon
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-76, https://doi.org/10.5194/nhess-2024-76, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
We developed a machine learning-based approach to predict the potential thickness of shallow landslides to generate improved inputs for slope stability models. We selected 21 explanatory variables including metrics on terrain, geomorphology, vegetation height, and lithology and used data from two Swiss field inventories to calibrate and test the models. The best performing machine learning model consistently reduced the mean average error by least 17 % compared to previously existing models.
Jiao Wang, Zhangxing Wang, Guanhua Sun, and Hongming Luo
Nat. Hazards Earth Syst. Sci., 24, 1741–1756, https://doi.org/10.5194/nhess-24-1741-2024, https://doi.org/10.5194/nhess-24-1741-2024, 2024
Short summary
Short summary
With a simplified formula linking rainfall and groundwater level, the rise of the phreatic surface within the slope can be obtained. Then, a global analysis method that considers both seepage and seismic forces is proposed to determine the safety factor of slopes subjected to the combined effect of rainfall and earthquakes. By taking a slope in the Three Gorges Reservoir area as an example, the safety evolution of the slope combined with both rainfall and earthquake is also examined.
Carlo Tacconi Stefanelli, William Frodella, Francesco Caleca, Zhanar Raimbekova, Ruslan Umaraliev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 24, 1697–1720, https://doi.org/10.5194/nhess-24-1697-2024, https://doi.org/10.5194/nhess-24-1697-2024, 2024
Short summary
Short summary
Central Asia regions are marked by active tectonics, high mountains with glaciers, and strong rainfall. These predisposing factors make large landslides a serious threat in the area and a source of possible damming scenarios, which endanger the population. To prevent this, a semi-automated geographic information system (GIS-)based mapping method, centered on a bivariate correlation of morphometric parameters, was applied to give preliminary information on damming susceptibility in Central Asia.
Benjamin B. Mirus, Thom A. Bogaard, Roberto Greco, and Manfred Stähli
EGUsphere, https://doi.org/10.5194/egusphere-2024-1219, https://doi.org/10.5194/egusphere-2024-1219, 2024
Short summary
Short summary
Early warning of increased landslide potential provides situational awareness to reduce landslide-related losses from major storm events. For decades, landslide forecasts relied on rainfall data alone, but recent research points to the value of hydrologic information for improving predictions. In this article, we provide our perspectives on the value and limitations of integrating subsurface hillslope hydrologic monitoring data and mathematical modeling for more accurate landslide forecasts.
Rex L. Baum, Dianne L. Brien, Mark E. Reid, William H. Schulz, and Matthew J. Tello
Nat. Hazards Earth Syst. Sci., 24, 1579–1605, https://doi.org/10.5194/nhess-24-1579-2024, https://doi.org/10.5194/nhess-24-1579-2024, 2024
Short summary
Short summary
We mapped potential for heavy rainfall to cause landslides in part of the central mountains of Puerto Rico using new tools for estimating soil depth and quasi-3D slope stability. Potential ground-failure locations correlate well with the spatial density of landslides from Hurricane Maria. The smooth boundaries of the very high and high ground-failure susceptibility zones enclose 75 % and 90 %, respectively, of observed landslides. The maps can help mitigate ground-failure hazards.
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 24, 1459–1483, https://doi.org/10.5194/nhess-24-1459-2024, https://doi.org/10.5194/nhess-24-1459-2024, 2024
Short summary
Short summary
Debris flows are a type of fast-moving landslide that start from shallow landslides or during intense rain. Infrastructure located downstream of watersheds susceptible to debris flows may be damaged should a debris flow reach them. We present and evaluate an approach to forecast building damage caused by debris flows. We test three alternative models for simulating the motion of debris flows and find that only one can forecast the correct number and spatial pattern of damaged buildings.
Luke A. McGuire, Francis K. Rengers, Ann M. Youberg, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Ryan Porter
Nat. Hazards Earth Syst. Sci., 24, 1357–1379, https://doi.org/10.5194/nhess-24-1357-2024, https://doi.org/10.5194/nhess-24-1357-2024, 2024
Short summary
Short summary
Runoff and erosion increase after fire, leading to a greater likelihood of floods and debris flows. We monitored debris flow activity following a fire in western New Mexico, USA, and observed 16 debris flows over a <2-year monitoring period. Rainstorms with recurrence intervals of approximately 1 year were sufficient to initiate debris flows. All debris flows initiated during the first several months following the fire, indicating a rapid decrease in debris flow susceptibility over time.
Ken'ichi Koshimizu, Satoshi Ishimaru, Fumitoshi Imaizumi, and Gentaro Kawakami
Nat. Hazards Earth Syst. Sci., 24, 1287–1301, https://doi.org/10.5194/nhess-24-1287-2024, https://doi.org/10.5194/nhess-24-1287-2024, 2024
Short summary
Short summary
Morphological conditions of drainage basins that classify the presence or absence of debris flow fans were analyzed in areas with different rock strength using decision tree analysis. The relief ratio is the most important morphological factor regardless of the geology. However, the thresholds of morphological parameters needed for forming debris flow fans differ depending on the geology. Decision tree analysis is an effective tool for evaluating the debris flow risk for each geology.
Jonathan P. Perkins, Nina S. Oakley, Brian D. Collins, Skye C. Corbett, and W. Paul Burgess
EGUsphere, https://doi.org/10.5194/egusphere-2024-873, https://doi.org/10.5194/egusphere-2024-873, 2024
Short summary
Short summary
Landslides are a global issue that results in deaths and economic losses annually. However, it is not clear how storm severity relates to landslide severity across large regions. Here we develop a method to estimate the footprint of landslide area and compare this to meteorologic estimates of storm severity. We find that total storm strength does not clearly relate to landslide area. Rather, landslide area depends on soil wetness and smaller storm structures that can produce intense rainfall.
Daniel Bolliger, Fritz Schlunegger, and Brian W. McArdell
Nat. Hazards Earth Syst. Sci., 24, 1035–1049, https://doi.org/10.5194/nhess-24-1035-2024, https://doi.org/10.5194/nhess-24-1035-2024, 2024
Short summary
Short summary
We analysed data from the Illgraben debris flow monitoring station, Switzerland, and we modelled these flows with a debris flow runout model. We found that no correlation exists between the grain size distribution, the mineralogical composition of the matrix, and the debris flow properties. The flow properties rather appear to be determined by the flow volume, from which most other parameters can be derived.
Yuntao Zhou, Xiaoyan Zhao, Guangze Zhang, Bernd Wünnemann, Jiajia Zhang, and Minghui Meng
Nat. Hazards Earth Syst. Sci., 24, 891–906, https://doi.org/10.5194/nhess-24-891-2024, https://doi.org/10.5194/nhess-24-891-2024, 2024
Short summary
Short summary
We developed three rock bridge models to analyze 3D stability and deformation behaviors of the Tizicao landslide and found that the contact surface model with high strength parameters combines advantages of the intact rock mass model in simulating the deformation of slopes with rock bridges and the modeling advantage of the Jennings model. The results help in choosing a rock bridge model to simulate landslide stability and reveal the influence laws of rock bridges on the stability of landslides.
Ashok Dahal, Hakan Tanyas, Cees van Westen, Mark van der Meijde, Paul Martin Mai, Raphaël Huser, and Luigi Lombardo
Nat. Hazards Earth Syst. Sci., 24, 823–845, https://doi.org/10.5194/nhess-24-823-2024, https://doi.org/10.5194/nhess-24-823-2024, 2024
Short summary
Short summary
We propose a modeling approach capable of recognizing slopes that may generate landslides, as well as how large these mass movements may be. This protocol is implemented, tested, and validated with data that change in both space and time via an Ensemble Neural Network architecture.
Li-Ru Luo, Zhi-Xiang Yu, Li-Jun Zhang, Qi Wang, Lin-Xu Liao, and Li Peng
Nat. Hazards Earth Syst. Sci., 24, 631–649, https://doi.org/10.5194/nhess-24-631-2024, https://doi.org/10.5194/nhess-24-631-2024, 2024
Short summary
Short summary
We performed field investigations on a rockfall near Jiguanshan National Forest Park, Chengdu. Vital information was obtained from an unmanned aerial vehicle survey. A finite element model was created to reproduce the damage evolution. We found that the impact kinetic energy was below the design protection energy. Improper member connections prevent the barrier from producing significant deformation to absorb energy. Damage is avoided by improving the ability of the nets and ropes to slide.
Marko Sinčić, Sanja Bernat Gazibara, Mauro Rossi, and Snježana Mihalić Arbanas
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-29, https://doi.org/10.5194/nhess-2024-29, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
The paper focuses on classifying continuous landslide conditioning factors for susceptibility modelling, which resulted in 54 landslide susceptibility models that tested 11 classification criteria in combination with five statistical methods. The novelty of the research is that using stretched landslide conditioning factor values results in models with higher accuracy and that certain statistical methods are more sensitive to the landslide conditioning factor classification criteria than others.
Sudhanshu Dixit, Srikrishnan Siva Subramanian, Piyush Srivastava, Ali P. Yunus, Tapas Ranjan Martha, and Sumit Sen
Nat. Hazards Earth Syst. Sci., 24, 465–480, https://doi.org/10.5194/nhess-24-465-2024, https://doi.org/10.5194/nhess-24-465-2024, 2024
Short summary
Short summary
Rainfall intensity–duration (ID) thresholds can aid in the prediction of natural hazards. Large-scale sediment disasters like landslides, debris flows, and flash floods happen frequently in the Himalayas because of their propensity for intense precipitation events. We provide a new framework that combines the Weather Research and Forecasting (WRF) model with a regionally distributed numerical model for debris flows to analyse and predict intense rainfall-induced landslides in the Himalayas.
Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, and Matthew M. Crawford
Nat. Hazards Earth Syst. Sci., 24, 1–12, https://doi.org/10.5194/nhess-24-1-2024, https://doi.org/10.5194/nhess-24-1-2024, 2024
Short summary
Short summary
Dividing landscapes into hillslopes greatly improves predictions of landslide potential across landscapes, but their scaling is often arbitrarily set and can require significant computing power to delineate. Here, we present a new computer program that can efficiently divide landscapes into meaningful slope units scaled to best capture landslide processes. The results of this work will allow an improved understanding of landslide potential and can help reduce the impacts of landslides worldwide.
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023, https://doi.org/10.5194/nhess-23-3805-2023, 2023
Short summary
Short summary
The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
Di Wu, Yuke Wang, and Xin Chen
EGUsphere, https://doi.org/10.5194/egusphere-2023-2318, https://doi.org/10.5194/egusphere-2023-2318, 2023
Short summary
Short summary
This paper proposed 3D limit analysis for seismic stability of soil slopes to address the influence of earthquake on slope stabilities with nonlinear and linear criteria. Comparison results illustrated that the use of linear envelope leads to the non-negligible overestimation of steep slope stability and this overestimation will be significant with the increasing earthquake. Earthquake has a smaller influence on slope slip surface with nonlinear envelope than that with linear envelope.
Mark Bloomberg, Tim Davies, Elena Moltchanova, Tom Robinson, and David Palmer
EGUsphere, https://doi.org/10.5194/egusphere-2023-2695, https://doi.org/10.5194/egusphere-2023-2695, 2023
Short summary
Short summary
Debris flows occur infrequently, with average recurrence intervals (ARIs) ranging from decades to millennia. Consequently, they pose an underappreciated hazard. We describe how to make a preliminary identification of debris flow-susceptible catchments, estimate threshold ARIs for debris flows which pose an unacceptable risk to life, and identify the "window of non-recognition" where debris flows are infrequent enough that their hazard is unrecognised, yet frequent enough to pose a risk to life.
Xushan Shi, Bo Chai, Juan Du, Wei Wang, and Bo Liu
Nat. Hazards Earth Syst. Sci., 23, 3425–3443, https://doi.org/10.5194/nhess-23-3425-2023, https://doi.org/10.5194/nhess-23-3425-2023, 2023
Short summary
Short summary
A 3D stability analysis method is proposed for biased rockfall with external erosion. Four failure modes are considered according to rockfall evolution processes, including partial damage of underlying soft rock and overall failure of hard rock blocks. This method is validated with the biased rockfalls in the Sichuan Basin, China. The critical retreat ratio from low to moderate rockfall susceptibility is 0.33. This method could facilitate rockfall early identification and risk mitigation.
Marius Schneider, Nicolas Oestreicher, Thomas Ehrat, and Simon Loew
Nat. Hazards Earth Syst. Sci., 23, 3337–3354, https://doi.org/10.5194/nhess-23-3337-2023, https://doi.org/10.5194/nhess-23-3337-2023, 2023
Short summary
Short summary
Rockfalls and their hazards are typically treated as statistical events based on rockfall catalogs, but only a few complete rockfall inventories are available today. Here, we present new results from a Doppler radar rockfall alarm system, which has operated since 2018 at a high frequency under all illumination and weather conditions at a site where frequent rockfall events threaten a village and road. The new data set is used to investigate rockfall triggers in an active rockslide complex.
Annette I. Patton, Lisa V. Luna, Joshua J. Roering, Aaron Jacobs, Oliver Korup, and Benjamin B. Mirus
Nat. Hazards Earth Syst. Sci., 23, 3261–3284, https://doi.org/10.5194/nhess-23-3261-2023, https://doi.org/10.5194/nhess-23-3261-2023, 2023
Short summary
Short summary
Landslide warning systems often use statistical models to predict landslides based on rainfall. They are typically trained on large datasets with many landslide occurrences, but in rural areas large datasets may not exist. In this study, we evaluate which statistical model types are best suited to predicting landslides and demonstrate that even a small landslide inventory (five storms) can be used to train useful models for landslide early warning when non-landslide events are also included.
Sandra Melzner, Marco Conedera, Johannes Hübl, and Mauro Rossi
Nat. Hazards Earth Syst. Sci., 23, 3079–3093, https://doi.org/10.5194/nhess-23-3079-2023, https://doi.org/10.5194/nhess-23-3079-2023, 2023
Short summary
Short summary
The estimation of the temporal frequency of the involved rockfall processes is an important part in hazard and risk assessments. Different methods can be used to collect and analyse rockfall data. From a statistical point of view, rockfall datasets are nearly always incomplete. Accurate data collection approaches and the application of statistical methods on existing rockfall data series as reported in this study should be better considered in rockfall hazard and risk assessments in the future.
Stefan Hergarten
Nat. Hazards Earth Syst. Sci., 23, 3051–3063, https://doi.org/10.5194/nhess-23-3051-2023, https://doi.org/10.5194/nhess-23-3051-2023, 2023
Short summary
Short summary
Rockslides are a major hazard in mountainous regions. In formerly glaciated regions, the disposition mainly arises from oversteepened topography and decreases through time. However, little is known about this decrease and thus about the present-day hazard of huge, potentially catastrophic rockslides. This paper presents a new theoretical framework that explains the decrease in maximum rockslide size through time and predicts the present-day frequency of large rockslides for the European Alps.
Colin K. Bloom, Corinne Singeisen, Timothy Stahl, Andrew Howell, Chris Massey, and Dougal Mason
Nat. Hazards Earth Syst. Sci., 23, 2987–3013, https://doi.org/10.5194/nhess-23-2987-2023, https://doi.org/10.5194/nhess-23-2987-2023, 2023
Short summary
Short summary
Landslides are often observed on coastlines following large earthquakes, but few studies have explored this occurrence. Here, statistical modelling of landslides triggered by the 2016 Kaikōura earthquake in New Zealand is used to investigate factors driving coastal earthquake-induced landslides. Geology, steep slopes, and shaking intensity are good predictors of landslides from the Kaikōura event. Steeper slopes close to the coast provide the best explanation for a high landslide density.
Yi-Min Huang
Nat. Hazards Earth Syst. Sci., 23, 2649–2662, https://doi.org/10.5194/nhess-23-2649-2023, https://doi.org/10.5194/nhess-23-2649-2023, 2023
Short summary
Short summary
Debris flows are common hazards in Taiwan, and debris-flow early warning is important for disaster responses. The rainfall thresholds of debris flows are analyzed and determined in terms of rainfall intensity, accumulated rainfall, and rainfall duration, based on case histories in Taiwan. These thresholds are useful for disaster management, and the cases in Taiwan are useful for global debris-flow databases.
Davide Notti, Martina Cignetti, Danilo Godone, and Daniele Giordan
Nat. Hazards Earth Syst. Sci., 23, 2625–2648, https://doi.org/10.5194/nhess-23-2625-2023, https://doi.org/10.5194/nhess-23-2625-2023, 2023
Short summary
Short summary
We developed a cost-effective and user-friendly approach to map shallow landslides using free satellite data. Our methodology involves analysing the pre- and post-event NDVI variation to semi-automatically detect areas potentially affected by shallow landslides (PLs). Additionally, we have created Google Earth Engine scripts to rapidly compute NDVI differences and time series of affected areas. Datasets and codes are stored in an open data repository for improvement by the scientific community.
Simon Seelig, Thomas Wagner, Karl Krainer, Michael Avian, Marc Olefs, Klaus Haslinger, and Gerfried Winkler
Nat. Hazards Earth Syst. Sci., 23, 2547–2568, https://doi.org/10.5194/nhess-23-2547-2023, https://doi.org/10.5194/nhess-23-2547-2023, 2023
Short summary
Short summary
A rapid sequence of cascading events involving thermokarst lake outburst, rock glacier front failure, debris flow development, and river blockage hit an alpine valley in Austria during summer 2019. We analyze the environmental conditions initiating the process chain and identify the rapid evolution of a thermokarst channel network as the main driver. Our results highlight the need to account for permafrost degradation in debris flow hazard assessment studies.
Camilla Lanfranconi, Paolo Frattini, Gianluca Sala, Giuseppe Dattola, Davide Bertolo, Juanjuan Sun, and Giovanni Battista Crosta
Nat. Hazards Earth Syst. Sci., 23, 2349–2363, https://doi.org/10.5194/nhess-23-2349-2023, https://doi.org/10.5194/nhess-23-2349-2023, 2023
Short summary
Short summary
This paper presents a study on rockfall dynamics and hazard, examining the impact of the presence of trees along slope and block fragmentation. We compared rockfall simulations that explicitly model the presence of trees and fragmentation with a classical approach that accounts for these phenomena in model parameters (both the hazard and the kinetic energy change). We also used a non-parametric probabilistic rockfall hazard analysis method for hazard mapping.
Ascanio Rosi, William Frodella, Nicola Nocentini, Francesco Caleca, Hans Balder Havenith, Alexander Strom, Mirzo Saidov, Gany Amirgalievich Bimurzaev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 23, 2229–2250, https://doi.org/10.5194/nhess-23-2229-2023, https://doi.org/10.5194/nhess-23-2229-2023, 2023
Short summary
Short summary
This work was carried out within the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project and is focused on the first landslide susceptibility analysis at a regional scale for Central Asia. The most detailed available landslide inventories were implemented in a random forest model. The final aim was to provide a useful tool for reduction strategies to landslide scientists, practitioners, and administrators.
Francis K. Rengers, Luke A. McGuire, Katherine R. Barnhart, Ann M. Youberg, Daniel Cadol, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 23, 2075–2088, https://doi.org/10.5194/nhess-23-2075-2023, https://doi.org/10.5194/nhess-23-2075-2023, 2023
Short summary
Short summary
Debris flows often occur after wildfires. These debris flows move water, sediment, and wood. The wood can get stuck in channels, creating a dam that holds boulders, cobbles, sand, and muddy material. We investigated how the channel width and wood length influenced how much sediment is stored. We also used a series of equations to back calculate the debris flow speed using the breaking threshold of wood. These data will help improve models and provide insight into future field investigations.
Maxime Morel, Guillaume Piton, Damien Kuss, Guillaume Evin, and Caroline Le Bouteiller
Nat. Hazards Earth Syst. Sci., 23, 1769–1787, https://doi.org/10.5194/nhess-23-1769-2023, https://doi.org/10.5194/nhess-23-1769-2023, 2023
Short summary
Short summary
In mountain catchments, damage during floods is generally primarily driven by the supply of a massive amount of sediment. Predicting how much sediment can be delivered by frequent and infrequent events is thus important in hazard studies. This paper uses data gathered during the maintenance operation of about 100 debris retention basins to build simple equations aiming at predicting sediment supply from simple parameters describing the upstream catchment.
Elsa S. Culler, Ben Livneh, Balaji Rajagopalan, and Kristy F. Tiampo
Nat. Hazards Earth Syst. Sci., 23, 1631–1652, https://doi.org/10.5194/nhess-23-1631-2023, https://doi.org/10.5194/nhess-23-1631-2023, 2023
Short summary
Short summary
Landslides have often been observed in the aftermath of wildfires. This study explores regional patterns in the rainfall that caused landslides both after fires and in unburned locations. In general, landslides that occur after fires are triggered by less rainfall, confirming that fire helps to set the stage for landslides. However, there are regional differences in the ways in which fire impacts landslides, such as the size and direction of shifts in the seasonality of landslides after fires.
Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Francesco Marra, Robin Kohrs, Jason Goetz, Volkmar Mair, and Massimiliano Pittore
Nat. Hazards Earth Syst. Sci., 23, 1483–1506, https://doi.org/10.5194/nhess-23-1483-2023, https://doi.org/10.5194/nhess-23-1483-2023, 2023
Short summary
Short summary
We present a novel data-driven modelling approach to determine season-specific critical precipitation conditions for landslide occurrence. It is shown that the amount of precipitation required to trigger a landslide in South Tyrol varies from season to season. In summer, a higher amount of preparatory precipitation is required to trigger a landslide, probably due to denser vegetation and higher temperatures. We derive dynamic thresholds that directly relate to hit rates and false-alarm rates.
Yaspal Sundriyal, Vipin Kumar, Neha Chauhan, Sameeksha Kaushik, Rahul Ranjan, and Mohit Kumar Punia
Nat. Hazards Earth Syst. Sci., 23, 1425–1431, https://doi.org/10.5194/nhess-23-1425-2023, https://doi.org/10.5194/nhess-23-1425-2023, 2023
Short summary
Short summary
The NW Himalaya has been one of the most affected terrains of the Himalaya, subject to disastrous landslides. This article focuses on two towns (Joshimath and Bhatwari) of the NW Himalaya, which have been witnessing subsidence for decades. We used a slope stability simulation to determine the response of the hillslopes accommodating these towns under various loading conditions. We found that the maximum displacement in these hillslopes might reach up to 20–25 m.
Cited articles
Ahmad, A. and Quegan, S.: Analysis of Maximum Likelihood Classification on
Multispectral Data, Appl. Math. Sci., 6, 6425–6436,
https://doi.org/10.12988/ams.2013.34214, 2012.
Ahmed, B.: Landslide susceptibility mapping using multi-criteria evaluation
techniques in Chittagong Metropolitan Area, Bangladesh, Landslides, 12,
1077–1095, https://doi.org/10.1007/s10346-014-0521-x, 2015.
Ahmed, M. F., Rogers, J. D., and Ismail, E. H.: A regional level preliminary
landslide susceptibility study of the upper indus river basin, Eur. J. Remote
Sens., 47, 343–373, https://doi.org/10.5721/EuJRS20144721, 2014.
Akgun, A., Dag, S., and Bulut, F.: Landslide susceptibility mapping for a
landslide-prone area (Findikli, NE of Turkey) by likelihood-frequency ratio
and weighted linear combination models, Environ. Geol., 54, 1127–1143,
https://doi.org/10.1007/s00254-007-0882-8, 2008.
Ali, S., Schneiderwind, S., and Reicherter, K.: Advancing Culture of Living
with Landslides, edited by: Mikoš, M., Casagli, N., Yin, Y., and Sassa,
K., Springer International Publishing, Cham, Switzerland, 2017.
Ambraseys, N., Lensen, G., Moinfart, A., and Penningtons, W.: The Pattan
(Pakistan) earthquake of 28 December 1974: field observations The
earliesknownt earthquakes of the Northwest Frontier Provinces (NWFP)
Geological and tectonic setting Evidence of regional Quarternary and Recent
movements, Q. J. Eng. Geol. Hydrogeol., 14, 1–16, 1981.
Arizapa, J. L., Combalicer, E. A., and Tiburan, C. J. L.: Landslide
Susceptibility Mapping of Pagsanjan – Lumban Watershed using GIS and
Analytical Hierarchy Process, Ecosyst. Dev. J., 5, 23–32, 2015.
Ayalew, L., Yamagishi, H., and Ugawa, N.: Landslide susceptibility mapping
using GIS-based weighted linear combination, the case in Tsugawa area of
Agano River, Niigata Prefecture, Japan, Landslides, 1, 73–81,
https://doi.org/10.1007/s10346-003-0006-9, 2004.
Ayalew, L., Yamagishi, H., Marui, H. and Kanno, T.: Landslides in Sado Island
of Japan: Part II. GIS-based susceptibility mapping with comparisons of
results from two methods and verifications, Eng. Geol., 81, 432–445,
https://doi.org/10.1016/j.enggeo.2005.08.004, 2005.
Bacha, A. S., Shafique, M., and van der Werff, H.: Landslide inventory and
susceptibility modelling using geospatial tools, in Hunza-Nagar valley,
northern Pakistan, J. Mt. Sci., 15, 1354–1370,
https://doi.org/10.1007/s11629-017-4697-0, 2018.
Bachri, S. and Shresta, R. P.: Landslide hazard assessment using analytic
hierarchy processing (AHP) and geographic information system in Kaligesing
mountain area of Central Java Province Indonesia, 5th Annu. Int. Work. Expo
on Sumatra Tsunami Disaster Recover, 23–24 November 2010, Banda Aceh,
Indonesia, 2010.
Barchi, M., Brozzetti, F., and Lavecchia, G.: Analisi strutturale egeometrica
dei bacini della media valle del Tevere e dellavalle umbra, Boll. Soc. Geol.
Ital., 110, 65–76, 1993.
Basharat, M., Shah, H. R., and Hameed, N.: Landslide susceptibility mapping
using GIS and weighted overlay method: a case study from NW Himalayas,
Pakistan, Arab, J. Geosci., 9, 1–19, https://doi.org/10.1007/s12517-016-2308-y, 2016.
Bishop, M. P., Shroder, J. F., Bonk, R., and Olsenholler, J.: Geomorphic
change in high mountains: A western Himalayan perspective, Global Planet.
Change, 32, 311–329, https://doi.org/10.1016/S0921-8181(02)00073-5, 2002.
Brenning, A.: Spatial prediction models for landslide hazards: review,
comparison and evaluation, Nat. Hazards Earth Syst. Sci., 5, 853–862,
https://doi.org/10.5194/nhess-5-853-2005, 2005.
Burg, J. P., Jagoutz, O., Dawood, H., and Shahid Hussain, S.: Precollision
tilt of crustal blocks in rifted island arcs: Structural evidence from the
Kohistan Arc, Tectonics, 25, 1–13, https://doi.org/10.1029/2005TC001835, 2006.
Butt, A., Shabbir, R., Ahmad, S. S., and Aziz, N.: Land use change mapping
and analysis using Remote Sensing and GIS: A case study of Simly watershed,
Islamabad, Pakistan, Egypt. J. Remote Sens. Sp. Sci., 18, 251–259,
https://doi.org/10.1016/j.ejrs.2015.07.003, 2015.
Canuti, P., Garduño, V. H., Garzonio, C. A., and Iotti, A.: Slope
evolution and mass movements in the Mt. Amiata region (Tuscany, Italy), in:
International Workshop on environmental Volcanology, 35–36, Riassunto, 1993.
Cardinali, M., Galli, M., Guzzetti, F., Reichenbach, P., and Borri, G.:
Relazioniframovimenti diversantee fenomenitettonicinel bacino del Torrente
Carpina (Umbria settentrionale), Geogr. Fis. eDinamica Quat., 17, 3–17,
1994.
Cardinali, M., Ardizzone, F., Galli, M., Guzzetti, F., and Reichenbach, P.:
Landslides triggered by rapid snow melting: the December 1996–January 1997
event in Central Italy, in: Proceedings Plinius Conference '99,
14–16 October 1999, Maratea, Italy, 439–448, 2000.
Coco, L. and Buccolini, M.: The Effect of Morphometry, Land-use and Lithology
on Landslides Susceptibility: An Exploratory Analysis, IOS Press, 779–784,
https://doi.org/10.3233/978-1-61499-580-7-779, 2015.
Deng, X., Li, L., and Tan, Y.: Validation of Spatial Prediction Models for
Landslide Susceptibility Mapping by Considering Structural Similarity, ISPRS
Int. J. Geo-Information, 6, 103, https://doi.org/10.3390/ijgi6040103, 2017.
Derbyshire, E., Fort, M., and Owen, L. A.: Geomorphological hazards along the
Karakoram Highway: Khunjerab Pass to the Gilgit River, northernmost Pakistan,
Erdkunde, 55, 49–71, https://doi.org/10.3112/erdkunde.2001.01.04, 2001.
Ding, L., Qasim, M., Jadoon, I. A. K., Khan, M. A., Xu, Q., Cai, F., Wang,
H., Baral, U., and Yue, Y.: The India–Asia collision in north Pakistan:
Insight from the U-Pb detrital zircon provenance of Cenozoic foreland basin,
Earth Planet. Sc. Lett., 455, 49–61, https://doi.org/10.1016/j.epsl.2016.09.003, 2016.
DiPietro, J. A. and Pogue, K. R.: Tectonostratigraphic subdivisions of the
Himalaya: A view from the west, Tectonics, 23, TC5001,
https://doi.org/10.1029/2003TC001554, 2004.
Dramis, F., Garzonio, C. A., Leoperdi, S., Nanni, T., Pontoni, F., and
Rainone, M. L.: Damage due to landslides in the ancient village of Sirolo
(Marche, Italy): preliminary analysis of risk mitigation on the historical
site., in: Int. Symp. Eng. Geol. of Ancient Work, Monuments and Historical
Sites, 19–23 September 1988, Athens, Greece, 1988.
Ellen, S. D., Mark, R. K., Cannon, S. H., and Knifong, D. L.: Map of
Debris-flow Hazard in the Honolulu District of Oahu, Hawaii, U.S. Geological
Survey, Washington, D.C., USA, 1993.
Escape, C. M., Alemania, M. K., Luzon, P. K., and Felix, R.: Comparison of
various remote sensing classification methods for landslide detection using
ArcGIS, UP NOAH Cent, available at:
https://center.noah.up.edu.ph/comparison-of-various-remote-sensing-classification-methods-for-landslide-detection-using-arcgis/
(last access: 5 March 2017), 2013.
Fawcett, T.: An introduction to ROC analysis, Pattern Recognit. Lett., 27,
861–874, https://doi.org/10.1016/j.patrec.2005.10.010, 2006.
Fayaz, A., Latif, M., and Khan, K. S. A.: Landslide Evaluation and
Stabilization Between Gilgit ans Thakot Along the Karakoram Highway,
Geological Survey of Pakistan, Islamabad, Pakistan, 1985.
Fressard, M., Thiery, Y., and Maquaire, O.: Which data for quantitative
landslide susceptibility mapping at operational scale? Case study of the Pays
d'Auge plateau hillslopes (Normandy, France), Nat. Hazards Earth Syst. Sci.,
14, 569–588, https://doi.org/10.5194/nhess-14-569-2014, 2014.
Google Earth Pro: Jijal, Pakistan (October 18, 2014).
35∘2′39.38′′ N, 72∘56′22.80′′ E, Eye alt 3.40 km,
2019 CNES/Airbus, available at: https://www.google.com/earth/, last
access: 9 June 2017a.
Google Earth Pro: Raikot Bridge, Pakistan (October 18, 2014).
35∘28′6.88′′ N, 74∘32′57.44′′ E, Eye alt 5.74 km,
2019 CNES/Airbus, available at: https://www.google.com/earth/, last
access: 9 June 2017b.
Google Earth Pro: Attabad, Pakistan (October 18, 2014).
36∘17′33.18′′ N, 74∘46′29.82′′ E, Eye alt
11.69 km, 2019 Digit. Globe, available at:
https://www.google.com/earth/, last access: 9 June 2017c.
Goudie, A. S., Brunsden, D., Collins, D. N., Derbyshire, E., Ferguson, R. I.,
Hashnet, Z., Jones, D. K. C., Per-Rott, F. A., Said, M., Waters, R. S., and
Whalley, W. B.: The geomorphology of the Hunza Valley, Karakoram mountains,
Pakistan, Int. Karakoram-Project, 2, 359–411, 1984.
Guzzetti, F., Carrara, A., Cardinali, M., and Reichenbach, P.: Landslide
hazard evaluation: A review of current techniques and their application in a
multi-scale study, Central Italy, Geomorphology, 31, 181–216,
https://doi.org/10.1016/S0169-555X(99)00078-1, 1999.
Guzzetti, F., Cardinali, M., Reichenbach, P., and Carrara, A.: Comparing
landslide maps: A case study in the upper Tiber River basin, central Italy,
Environ. Manage., 25, 247–263, https://doi.org/10.1007/s002679910020, 2000.
Guzzetti, F., Mondini, A. C., Cardinali, M., Fiorucci, F., Santangelo, M.,
and Chang, K. T.: Landslide inventory maps: New tools for an old problem,
Earth-Sci. Rev., 112, 42–66, https://doi.org/10.1016/j.earscirev.2012.02.001, 2012.
Hewitt, K.: Catastrophic landslides and their effects on the Upper Indus
streams, Karakoram Himalaya, northern Pakistan, Geomorphology, 26, 47–80,
https://doi.org/10.1016/S0169-555X(98)00051-8, 1998.
Hu, X. and Cruden, D.: Buckling deformation in the Highwood Pass, Alberta,
Can. Geotech. J., 30, 276–286, 1993.
Intarawichian, N. and Dasananda, S.: Analytical hierarchy process for
landslide susceptibility mapping in lower Mae Chaem watershed, Northern
Thailand, Suranaree J. Sci. Technol., 17, 277–292, 2010.
Jade, S.: Estimates of plate velocity and crustal deformation in the Indian
subcontinent using GPS geodesy, Curr. Sci., 86, 1443–1448, 2004.
Kamp, U., Growley, B. J., Khattak, G. A., and Owen, L. A.: GIS-based
landslide susceptibility mapping for the 2005 Kashmir earthquake region,
Geomorphology, 101, 631–642, https://doi.org/10.1016/j.geomorph.2008.03.003, 2008.
Kanwal, S., Atif, S., and Shafiq, M.: GIS based landslide susceptibility
mapping of northern areas of Pakistan, a case study of Shigar and Shyok
Basins, Geomat. Nat. Haz. Risk, 5705, 1–19,
https://doi.org/10.1080/19475705.2016.1220023, 2016.
Kartiko, R. D., Brahmantyo, B., and Sadisun, I. A.: Slope and Lithological
Controls on Landslide Distribution in West, in: International Symposium on
Geotechnical Hazards: Prevention, Mitigation and Engineering Response, Utomo,
Tohari, Murdohardono, Sadisun, April 2006, Yogyakarta, Indonesia, 177–184,
2006.
Khan, H., Shafique, M., Khan, M. A., Bacha, M. A., Shah, S. U., and
Calligaris, C.: Landslide susceptibility assessment using Frequency Ratio, a
case study of northern Pakistan, Egypt. J. Remote Sens. Sp. Sci., 22, 11–24,
https://doi.org/10.1016/j.ejrs.2018.03.004, 2018.
Khan, K. S. A., Fayaz, A., Latif, M., and Wazir, A. K.: Rock and Debris
Slides Between Khunjrab Pass and Gilgit along the Karakoram Highway,
Geological Survey of Pakistan, Islamabad, Pakistan, 1986.
Khan, K. S. A., Latif, M., Fayaz, A., Khan, N. A., and Khan, S. Z.:
Geological Roadlog along the Karakorum Highway from Islamabad to Khunjrab
Pass, Geological Survey of Pakistan, Islamabad, Pakistan, 2000.
Khan, K. S. A., Fayaz, A., Hussain, M., and Latif, M.: Landslides Problems
and Their Mitigation along the Karakoram Highway, 1st ed., Geological Survey
of Pakistan, Islamabad, Pakistan, 2003.
Khan, M. A., Jan, M. Q., Windley, B. F., Tarney, J., and Thirlwall, M. F.:
The Chilas mafic-ultramafic igneous complex; the root of the Kohistan island
arc in the Himalaya of northern Pakistan, Geol. Soc. Am. Spec. Pap., 232,
75–94, 1989.
Komac, M.: A landslide susceptibility model using the Analytical Hierarchy
Process method and multivariate statistics in perialpine Slovenia,
Geomorphology, 74, 17–28, https://doi.org/10.1016/j.geomorph.2005.07.005, 2006.
Lee, S.: Application of logistic regression model and its validation for
landslide susceptibility mapping using GIS and remote sensing data, Int. J.
Remote Sens., 26, 1477–1491, https://doi.org/10.1080/01431160412331331012, 2005.
Lee, S., Chwae, U., and Min, K.: Landslide susceptibility mapping by
correlation between topography and geological structure: The Janghung area,
Korea, Geomorphology, 46, 149–162, https://doi.org/10.1016/S0169-555X(02)00057-0, 2002.
Lee, S., Ryu, J.-H., Won, J.-S., and Park, H.-J.: Determination and
application of the weights for landslide susceptibility mapping using an
artificial neural network, Eng. Geol., 71, 289–302,
https://doi.org/10.1016/S0013-7952(03)00142-X, 2004.
Malek, Ž., Zumpano, V., Schröter, D., Glade, T., Balteanu, D., and
Micu, M.: Scenarios of land cover change and landslide susceptibility: An
example from the buzau subcarpathians, romania, Eng. Geol. Soc. Territ., 5,
743–746, https://doi.org/10.1007/978-3-319-09048-1_144, 2015.
MonaLisa, Khwaja, A. A., Jan, M. Q., Yeats, R. S., Hussain, A., and Khan, S.
A.: New data on the Indus Kohistan seismic zone and its extension into the
Hazara-Kashmir Syntaxis, NW Himalayas of Pakistan, J. Seismol., 13, 339–361,
https://doi.org/10.1007/s10950-008-9117-z, 2009.
Nilsen, T. H., Wright, R. H., Vlasic, T. C., and Spangle, W.: Relative slope
stability and land-use planning. Selected examples from the San Francisco Bay
region, California., US Geol. Surv. Prof. Pap., 944, 1–96, available at:
http://www.scopus.com/inward/record.url?eid=2-s2.0-0018731268&partnerID=tZOtx3y1
(last access: 11 July 2017), 1979.
Ohlmacher, G. C. and Davis, J. C.: Using multiple logistic regression and GIS
technology to predict landslide hazard in northeast Kansas, USA, Eng. Geol.,
69, 331–343, https://doi.org/10.1016/S0013-7952(03)00069-3, 2003.
Park, S., Choi, C., Kim, B., and Kim, J.: Landslide susceptibility mapping
using frequency ratio, analytic hierarchy process, logistic regression, and
artificial neural network methods at the Inje area, Korea, Environ. Earth
Sci., 68, 1443–1464, https://doi.org/10.1007/s12665-012-1842-5, 2013.
Pourghasemi, H. R. and Rossi, M.: Landslide susceptibility modeling in a
landslide prone area in Mazandarn Province, north of Iran: a comparison
between GLM, GAM, MARS, and M-AHP methods, Theor. Appl. Climatol., 130,
609–633, https://doi.org/10.1007/s00704-016-1919-2, 2017.
Pourghasemi, H. R., Pradhan, B., and Gokceoglu, C.: Application of fuzzy
logic and analytical hierarchy process (AHP) to landslide susceptibility
mapping at Haraz watershed, Iran, Nat. Hazards, 63, 965–996,
https://doi.org/10.1007/s11069-012-0217-2, 2012.
Pourghasemi, H. R., Beheshtirad, M., and Pradhan, B.: A comparative
assessment of prediction capabilities of modified analytical hierarchy
process (M-AHP) and Mamdani fuzzy logic models using Netcad-GIS for forest
fire susceptibility mapping, Geomat. Nat. Haz. Risk, 7, 861–885,
https://doi.org/10.1080/19475705.2014.984247, 2016.
Pradhan, B., Lee, S., and Buchroithner, M. F.: Remote Sensing and GIS-based
Landslide Susceptibility Analysis and its Cross-validation in Three Test
Areas Using a Frequency Ratio Model, Photogramm. Fernerkun., 2010, 17–32,
https://doi.org/10.1127/1432-8364/2010/0037, 2010.
Rahim, I., Ali, S. M., and Aslam, M.: GIS Based Landslide Susceptibility
Mapping with Application of Analytical Hierarchy Process in District Ghizer,
Gilgit Baltistan Pakistan, J. Geosci. Environ. Prot., 06, 34–49,
https://doi.org/10.4236/gep.2018.62003, 2018.
Reichenbach, P., Busca, C., Mondini, A. C., and Rossi, M.: The Influence of
Land Use Change on Landslide Susceptibility Zonation: The Briga Catchment
Test Site (Messina, Italy), Environ. Manage., 54, 1372–1384,
https://doi.org/10.1007/s00267-014-0357-0, 2014.
Reis, S.: Analyzing land use/land cover changes using remote sensing and GIS
in Rize, North-East Turkey, Sensors, 8, 6188–6202, https://doi.org/10.3390/s8106188,
2008.
Restrepo, C. and Alvarez, N.: Landslides and their contribution to land-cover
change in the mountains of Mexico and Central America, Biotropica, 38,
446–457, https://doi.org/10.1111/j.1744-7429.2006.00178.x, 2006.
Roslee, R., Mickey, A. C., Simon, N., and Norhisham, M. N.: Landslide
Susceptibility Analysis (Lsa) Using Weighted Overlay Method (Wom) Along the
Genting Sempah To Bentong Highway, Pahang, Malays. J. Geosci., 1, 13–19,
https://doi.org/10.26480/mjg.02.2017.13.19, 2017.
Rozos, D., Bathrellos, G. D., and Skillodimou, H. D.: Comparison of the
implementation of rock engineering system and analytic hierarchy process
methods, upon landslide susceptibility mapping, using GIS: A case study from
the Eastern Achaia County of Peloponnesus, GREECE, Environ. Earth Sci., 63,
49–63, https://doi.org/10.1007/s12665-010-0687-z, 2011.
Ruff, M. and Czurda, K.: Landslide susceptibility analysis with a heuristic
approach in the Eastern Alps (Vorarlberg, Austria), Geomorphology, 94,
314–324, https://doi.org/10.1016/j.geomorph.2006.10.032, 2008.
Rwanga, S. S. and Ndambuki, J. M.: Accuracy Assessment of Land Use/Land Cover
Classification Using Remote Sensing and GIS, Int. J. Geosci., 08, 611–622,
https://doi.org/10.4236/ijg.2017.84033, 2017.
Saaty, R. W.: The analytic hierarchy process-what it is and how it is used,
Math. Model., 9, 161–176, https://doi.org/10.1016/0270-0255(87)90473-8, 1987.
Saaty, T. L.: How to make a decision: The analytic hierarchy process, Eur. J.
Oper. Res., 48, 9–26, https://doi.org/10.1016/0377-2217(90)90057-I, 1990.
Sarkar, S. and Kanungo, D. P.: An integrated approach for landslide
susceptibility mapping using remote sensing and GIS, Photogramm. Eng. Remote
Sens., 70, 617–628, https://doi.org/10.14358/PERS.70.5.617, 2004.
Searle, M. P., Khan, M. A., Fraser, J. E., Gough, S. J., and Jan, M. Q.: The
tectonic evolution of the Kohistan-Karakoram collision belt along the
Karakoram Highway transect, north Pakistan, Tectonics, 18, 929–949, 1999.
Shahabi, H. and Hashim, M.: Landslide susceptibility mapping using GIS-based
statistical models and Remote sensing data in tropical environment, Sci.
Rep., 5, 9899, https://doi.org/10.1038/srep09899, 2015.
Shit, P. K., Bhunia, G. S., and Maiti, R.: Potential landslide susceptibility
mapping using weighted overlay model (WOM), Model. Earth Syst. Environ., 21,
1–10, https://doi.org/10.1007/s40808-016-0078-x, 2016.
Soeters, R. and van Westen, C. J.: Slope instability recognition, analysis,
and zonation, in: Landslides, investigation and mitigation, edited by:
Turner, A. K. and Schuster, R. L., Washington, D.C., USA, 1996.
Süzen, M. L. and Doyuran, V.: A comparison of the GIS based landslide
susceptibility assessment methods: Multivariate versus bivariate, Environ.
Geol., 45, 665–679, https://doi.org/10.1007/s00254-003-0917-8, 2004.
Taherynia, M. H., Mohammadi, M., and Ajalloeian, R.: Assessment of Slope
Instability and Risk Analysis of Road Cut Slopes in Lashotor Pass, Iran, J.
Geol. Res., 2014, 1–12, https://doi.org/10.1155/2014/763598, 2014.
Tahirkheli, R. A. K. and Jan, M. Q.: Geology of Kohistan, Karakorum Himalaya,
northern Pakistan, Geol. Bull. Univ. Peshawar, Pakistan, 11, 1–30, 1979.
Treloar, P. J., Petterson, M. G., Jan, M. Q., and Sullivan, M. A.: A
re-evaluation of the stratigraphy and evolution of the Kohistan arc sequence,
Pakistan Himalaya: implications for magmatic and tectonic arc-building
processes, J. Geol. Soc., 153, 681–693, https://doi.org/10.1144/gsjgs.153.5.0681,
1996.
Ulbricht, K. A., Teotia, H. S., and Civco, D. L.: Supervised Classification
to Land Cover Mapping in Semi-Arid Environment of NE Brazil Using Landsat-TM
and SPOT Data, Int. Arch. Photogramm. Remote Sens., 29, 821–821, available
at:
http://www.isprs.org/proceedings/XXIX/congress/part7/821_XXIX-part7.pdf
(last access: 16 February 2016), 1993.
USGS Earthquake Catalog: USGS Earthquake Catalog, Earthq. Cat., available at:
https://earthquake.usgs.gov/earthquakes/search/, last access: 23 July
2017.
Vakhshoori, V. and Zare, M.: Is the ROC curve a reliable tool to compare the
validity of landslide susceptibility maps?, Geomat. Nat. Haz. Risk, 9,
249–266, https://doi.org/10.1080/19475705.2018.1424043, 2018.
Vallejo, G. L. and Ferrer, M.: Geological Engineering, 1st ed., CRC
Press/Balkema, AK Leiden, the Netherlands, 2011.
van Westen, C. J., van Asch, T. W. J., and Soeters, R.: Landslide hazard and
risk zonation - Why is it still so difficult?, Bull. Eng. Geol. Environ., 65,
167–184, https://doi.org/10.1007/s10064-005-0023-0, 2006.
Varnes, D. J.: Slope movements types and processes, in: Landslides analysis
and control, edited by: Schuster, R. L. and Krizek, R. J., Washington, D.C.,
USA, 1978.
Wang, Q., Li, W., Chen, W., and Bai, H.: GIS-based assessment of landslide
susceptibility using certainty factor and index of entropy models for the
Qianyang county of Baoji city, China, J. Earth Syst. Sci., 124, 1399–1415,
2015.
Williams, M. P.: The Geology of the Besham area, North Pakistan: Deformation
and Imbrication in the footwall of the Main Mantle Thrust, Geol. Bull. Univ.
Peshawar, 22, 65–82, 1989.
Yalcin, A.: GIS-based landslide susceptibility mapping using analytical
hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons
of results and confirmations, Catena, 72, 1–12,
https://doi.org/10.1016/j.catena.2007.01.003, 2008.
Zeitler, P. K.: Cooling history of the NW Himalaya, Pakistan, Tectonics, 4,
127–151, https://doi.org/10.1029/TC004i001p00127, 1985.
Zhiquan, Y. and Yingyan, Z.: Types and Space Distribution Characteristics of
Debris Flow Disasters Along China-Pakistan Highway, Electron. J. Geotech.
Eng., 21, 191–200, 2016.
Zhou, S., Chen, G., Fang, L., and Nie, Y.: GIS-based integration of
subjective and objective weighting methods for regional landslides
susceptibility mapping, Sustain., 8, 1–15, https://doi.org/10.3390/su8040334, 2016.
Short summary
The Karakoram Highway (KKH) is an important physical connection between Pakistan and China. Landslides have been a major threat to its stability since its construction. After the announcement of the China–Pakistan Economic Corridor (CPEC), KKH has had more importance. Geoscientists from research institutions in both countries are assessing landslide hazard and risk along the highway. In a PhD project, this paper will be followed by a detailed analysis of mass movements along the highway.
The Karakoram Highway (KKH) is an important physical connection between Pakistan and China....
Special issue
Altmetrics
Final-revised paper
Preprint