Christian Arnhardt | British Geological Survey (original) (raw)

Papers by Christian Arnhardt

… 2010, held 2-7 May …, 2010

EGU General Assembly Conference Abstracts, Apr 1, 2019

AIMS geosciences, 2016

Mass movement processes of bedrock slopes are highly dependent on the orientations of structural ... more Mass movement processes of bedrock slopes are highly dependent on the orientations of structural discontinuities within the rock mass. The associated hazards are typically defined by the orientation of structures and associated mechanisms of slope failure such as planar sliding, wedge sliding and toppling. A typical rock mass with multiple weak surfaces, or discontinuities, may form a consistent pattern over a range of spatial scale. The type of hazard resulting from the pattern of discontinuities will vary according to the angle and direction of the slope face. Assessing the risk of rock slope instability involves understanding of the complex three-dimensional structural features of the rock mass. Recent developments in stereographic methods show advantages are gained by representing wedges by linking great circles rather than showing the intersection line on the stereograph. We applied these methods to three rock slopes where active mass movement has occurred. The case studies include a large rock slide-debris avalanche in the Philippines, coastal cliffs in Australia and mining excavation slopes in Ghana, West Africa.

Solid Earth, Sep 4, 2020

Understanding the impact of fracture networks on rock mass properties is an essential part of a w... more Understanding the impact of fracture networks on rock mass properties is an essential part of a wide range of applications in geosciences from understanding permeability of groundwater aquifers and hydrocarbon reservoirs to erodibility properties and slope stability of rock masses for geotechnical engineering. However, gathering high-quality, oriented-fracture datasets in the field can be difficult and time-consuming, for example, due to constraints on field work time or access (e.g. cliffs). Therefore, a method for obtaining accurate, quantitative fracture data from photographs is a significant benefit. In this paper we describe a method for generating a series of digital fracture traces in a geographic information system (GIS) environment, in which spatial analysis of a fracture network can be carried out. The method is not meant to replace the gathering of data in the field but to be used in conjunction with it, and it is well suited when field work time is limited or when the section cannot be accessed directly. The basis of the method is the generation of the vector dataset (shapefile) of a fracture network from a georeferenced photograph of an outcrop in a GIS environment. From that shapefile, key parameters such as fracture density and orientation can be calculated. Furthermore, in the GIS environment more complex spatial calculations and graphical plots can be carried out such as heat maps of fracture density. Advantages and limitations compared to other fracture network capture methods are discussed.

Engineering Geology, Mar 1, 2012

Applying the method nanoseismic monitoring to the fast-moving mudslide in Super-Sauze (French Alp... more Applying the method nanoseismic monitoring to the fast-moving mudslide in Super-Sauze (French Alps) we observed different types of seismic events caused by varying slope dynamics. We identified signals caused by rockfalls in the source area of the slope, and different types of signals, which had obviously been generated by material failure within the unstable part of the mudslide. Signal analysis and further investigations, e.g. the analysis of magnitude-frequency distribution and simultaneous measurements by nanoseismic monitoring and extensometer devices, revealed the generation of the observed seismic signals: fracture processes, i.e. slide quakes, within the unstable sediments and the development of fissures at the slope's surface. The spatial distribution of the epicenters (slide quakes), respectively the estimated source area (fissure development), correlates well with parts of the slope moving with higher velocities at the surface. Most of these signals were generated close to the in-situ crests, which are mostly covered by the mudslide material today, indicating specific dynamics in these particular slope areas.

<p>Forecasting rainfall-induced landslides, whilst challenging, is increasi... more <p>Forecasting rainfall-induced landslides, whilst challenging, is increasingly important due to the impact these hazards can have on society. The difficulty in forecasting arises from the inherent variability of geo-environmental factors and the scale at which underlying processes operate. The availability of data required to develop and validate thresholds for operational purposes is often limited. In regions where data (e.g. meteorological, or geotechnical) is sparse or incomprehensive, it is important to have a framework to systematically fuse the incomplete datasets to aid the development of a threshold model or to supplement an existing preliminary trigger threshold model.</p><p>For this study, a bespoke conceptual hydrological model called the ‘BGS water balance model’ is used in Nilgiris (Tamil Nadu state, India) to integrate the ground and meteorological information for informed decision making on the landscape saturation condition. This simple conceptual model with applicability over a large area provides an approximation of the degree of saturation value that can be used to map the potential antecedent wetness pathway leading to the initiation of landslides.</p><p>In this session, the BGS water balance model features along with the study area geological characteristics, landslide controls, input datasets and sensitivity analysis will be discussed. Further, we will show the results of the back-analysed landslides and explore the value of this approach in the context of landslide forecasting.</p>

<p>This research describes the development ... more <p>This research describes the development and pro-forma of a landslide tracker methodology (structure of questions and photos) to support local reporting of landslides in India, thus enhancing modelling of susceptibility to future landslides and India Landslide Early Warning Systems. This methodology aids in the collection of timely and representative information about landslide events using local people before such information is lost due to human clearance works or natural processes (further erosion, vegetation cover). In the framework of the UK NERC/FCDO funded LANDSLIP project ‘Landslide multi-hazard risk assessment, preparedness and early warning in South Asia', a collaboration of government, academic and NGO scientists/practitioners from India and UK co-designed a questionnaire in both paper and mobile app proforma called the ‘Landslide Tracker’. The Landslide Tracker was developed as a tool for gathering landslide information from different levels of local users (e.g., local officials, NGOs, students) to enhance landslide inventories in the test sites of Darjeeling and Nilgiris, India. Different users, supporting data capture within the project, have different levels of understanding and knowledge about landslides. The Tracker was developed with three user levels to reflect this variation in landslide expertise. Level 1 is available in paper format and Levels 1 to 3 in a freely available Google Play app developed by Amrita University “Landslide Tracker”. Level 1 of the landslide tracker represents all users where the expertise level is not known or assumed to be limited; this comprises the most basic landslide information. This group of non-specialists represents the majority group of people capturing data within each study area. Information submitted by this user group, due to the limited knowledge and understanding of landslides in a geological context, might be assumed to have the highest degree of uncertainty and potentially the greatest amount of false information. The questions for this group utilise a simplified lexicon, with (i) location, data and time, (i) pictures of landslide material, (iii) landslide type, with finally (iv) generalised impact information. Level 2 represents more specialist users with a higher advanced understanding of landslides either from their background training/proficiency or users that have undergone training. In general, these people are asked the same questions as in Level 1, but a more technical vocabulary is used, and more detailed information is requested, like the size of landslides. Level 3 is for trained landslide experts. They are asked a wide range of landslide questions, reflecting internationally recognised landslide glossaries and definitions, and based on the current methodology used by the Geological Survey of India. With the help of two NGOs (Keystone and Save the Hills) and the Geological Survey of India, the developed proforma (paper and mobile app), have undergone field testing. Feedback from this phase of development was essential for the improvement and update of the pro-forma.  Efforts during the most recent Monsoon by the partners has resulted in over 500 landslide records being collected in the two test sites by either the app or in paper format.</p>

<p>Monsoons are characterised by the widesp... more <p>Monsoons are characterised by the widespread occurrence of  landslides. Tracking each landslide event, developing early warning thresholds, understanding triggers, and initiating disaster rescue and relief efforts are complex for researchers and administration. The ever increasing landslides demand real-time data collection of events to enhance disaster management. In this work we designed and developed a dedicated crowd sourced mobile application, for systematic way of collection, validation, summarization, and dissemination of landslide data in real-time. This unique design of mobile app uses a scalable real-time data collection methodology for tracking landslide events through citizen science, and is available on Google Play Store for free, and at http://landslides.amrita.edu, with software conceived and developed by Amrita University in the context of the UK NERC/FCDO funded LANDSLIP research project (http://www.landslip.org/). This work implemented a structured database that integrates heterogeneous data such as text, numerical, GPS location, landmarks, and images. This methodology enables real-time tracking of landslides utilizing the details such as GPS location, date & time of occurrence, images, type, material, size, impact, area, geology, geomorphology, and comments in real-time. The mobile application has been uniquely designed to avoid missing landslide events and to handle the tradeoff between real-time spatial data collection without compromising the reliability of the data.  To achieve this a multi level user account was created based on their expert levels such as Tracker, Investigator, Expert.  A basic tracking form is presented for the Tracker level, and an extensive form is presented to the Expert level. The reliability of landslide data enhances as the user level increases from Tracker to Expert. Unique UI designs have been utilized to capture, and track the events. The tracking interface is divided into multiple screens; the main screen captures the landslide location through GPS enabled map interface and captures the date/time of the occurrence. Three additional screens capture images, additional details and comments. The 40 questions for landslide event collection used by the Geological Survey of India has been adapted through the collaborative effort of LANDSLIP partners to collect the additional details. The submitted landslides are immediately available for all users to view. The User can view entered landslides through the landslide image listing, Google maps interface, or tabular listing. The landslides can be filtered by date/time and other parameters. The mobile app is designed to be intuitive and fast, and aims to increase awareness about landslide risk through the integrated short documents, and videos. It has guidelines for safety, capturing images, mapping, and choosing the data from the multiple options. The uniqueness of the proposed methodology is that it enhances community participation, integrates event data collection, event data organizing, spatial and temporal summarization, and validation of landslide events and the impact. It pinpoints, maps and alerts real-time landslide events to initiate right disaster management activities to reduce the risk level. The Landslide tracker app was released during the 2020 monsoon season, and more than 250 landslides were recorded through the app.</p>

EGU General Assembly Conference Abstracts, May 1, 2010

Monitoring systems in landslide areas are important elements of effective Early Warning structure... more Monitoring systems in landslide areas are important elements of effective Early Warning structures. Data acquisition and retrieval allows the detection of movement processes and thus is essential to generate warnings in time. Apart from the precise measurement, the reliability of data is fundamental, because outliers can trigger false alarms and leads to the loss of acceptance of such systems. For the monitoring of mass movements and their risk it is important to know, if there is movement, how fast it is and how trustworthy is the information. The joint project "Sensorbased landslide early warning system" (SLEWS) deals with these questions, and tries to improve data quality and to reduce false alarm rates, due to the combination of sensor date (sensor fusion). The project concentrates on the development of a prototypic Alarm-and Early Warning system (EWS) for different types of landslides by using various low-cost sensors, integrated in a wireless sensor network (WSN). The network consists of numerous connection points (nodes) that transfer data directly or over other nodes (Multi-Hop) in real-time to a data collection point (gateway). From there all the data packages are transmitted to a spatial data infrastructure (SDI) for further processing, analyzing and visualizing with respect to end-user specifications. The ad-hoc characteristic of the network allows the autonomous crosslinking of the nodes according to existing connections and communication strength. Due to the independent finding of new or more stable connections (self healing) a breakdown of the whole system is avoided. The bidirectional data stream enables the receiving of data from the network but also allows the transfer of commands and pointed requests into the WSN. For the detection of surface deformations in landslide areas small low-cost Micro-Electro-Mechanical-Systems (MEMS) and positionsensors from the automobile industries, different industrial applications and from other measurement technologies were chosen. The MEMS-Sensors are acceleration-, tilt-and barometric pressure sensors. The positionsensors are draw wire and linear displacement transducers. In first laboratory tests the accuracy and resolution were investigated. The tests showed good results for all sensors. For example tilt-movements can be monitored with an accuracy of +/-0,06°and a resolution of 0,1°. With the displacement transducer change in length of >0,1mm is possible. Apart from laboratory tests, field tests in South France and Germany were done to prove data stability and movement detection under real conditions. The results obtained were very satisfying, too. In the next step the combination of numerous sensors (sensor fusion) of the same type (redundancy) or different types (complementary) was researched. Different experiments showed that there is a high concordance between identical sensor-types. According to different sensor parameters (sensitivity, accuracy, resolution) some sensor-types can identify changes earlier. Taking this into consideration, good correlations between different kinds of sensors were achieved, too. Thus the experiments showed that combination of sensors is possible and this could improve the detection of movement and movement rate but also outliers. Based on this results various algorithms were setup that include different statistical methods (outlier tests, testing of hypotheses) and procedures from decision theories (Hurwicz-criteria). These calculation formulas will be implemented in the spatial data infrastructure (SDI) for the further data processing and validation. In comparison with today existing mainly punctually working monitoring systems, the application of wireless sensor networks in combination with low-cost, but precise micro-sensors provides an inexpensive and easy to set up monitoring system also in large areas. The correlation of same but also different sensor-types permits a good data control. Thus the sensor fusion is a promising tool to detect movement more reliable and thus contributes essential to the improvement of Early Warning Systems.

Scientific Investigations Report, Oct 3, 2008

The 5G RuralDorset project (https://5gruraldorset.org/) was a large (£9M; 2020-2022), multi-disci... more The 5G RuralDorset project (https://5gruraldorset.org/) was a large (£9M; 2020-2022), multi-disciplinary project funded by the UK Department for Culture, Media and Sport that aimed to understand how 5G mobile network technologies could address some specific challenges in rural communities in Dorset, UK: public safety, economic growth, food production and environmental. Work Package X aimed to develop and trial a novel landslide monitoring system for coastal cliffs using 5G/NB-IoT (Narrow Band - Internet of Things) technologies. The system comprised a set of small, fully autonomous, highly integrated and power efficient sensing devices that were able to collect sensory data to identify landslide activity and landslide movement. These data were transmitted wirelessly using 5G/NB-IoT to a cloud-based Data Management Platform, where they were presented to the end user over a web interface for processing by Machine Learning algorithms. It is important to note that the term ‘Internet of...

EAGE-GSM 2nd Asia Pacific Meeting on Near Surface Geoscience and Engineering, 2019

Journal of Glaciology

Glacial ripping involves glaciotectonic disintegration of rock hills and extensive removal of roc... more Glacial ripping involves glaciotectonic disintegration of rock hills and extensive removal of rock at the ice-sheet bed, triggered by hydraulic jacking caused by fluctuating water pressures. Evidence from eastern Sweden shows that glacial ripping caused significant subglacial erosion during the final deglaciation of the Fennoscandian ice sheet, distinct from abrasion and plucking (quarrying). Here we analyse the ice drag forces exerted onto rock obstacles at the base of an ice sheet, and the resisting forces of such rock obstacles: glaciotectonic disintegration requires that ice drag forces exceed the resisting forces of the rock obstacle. We consider rock obstacles of different sizes, shapes and fracture patterns, informed by natural examples from eastern Sweden. Our analysis shows that limited overpressure events, unfavourable fracture patterns, low-transmissivity fractures, slow ice and streamlined rock hamper rock hill disintegration. Conversely, under fast ice flow and fluctuat...

<p>Forecasting rainfall-induced landslides, whilst challenging, is increasi... more <p>Forecasting rainfall-induced landslides, whilst challenging, is increasingly important due to the impact these hazards can have on society. The difficulty in forecasting arises from the inherent variability of geo-environmental factors and the scale at which underlying processes operate. The availability of data required to develop and validate thresholds for operational purposes is often limited. In regions where data (e.g. meteorological, or geotechnical) is sparse or incomprehensive, it is important to have a framework to systematically fuse the incomplete datasets to aid the development of a threshold model or to supplement an existing preliminary trigger threshold model.</p><p>For this study, a bespoke conceptual hydrological model called the ‘BGS water balance model’ is used in Nilgiris (Tamil Nadu state, India) to integrate the ground and meteorological information for informed decision making on the landscape saturation condition. This simple conceptual model with applicability over a large area provides an approximation of the degree of saturation value that can be used to map the potential antecedent wetness pathway leading to the initiation of landslides.</p><p>In this session, the BGS water balance model features along with the study area geological characteristics, landslide controls, input datasets and sensitivity analysis will be discussed. Further, we will show the results of the back-analysed landslides and explore the value of this approach in the context of landslide forecasting.</p>

<p>Here we present a methodology for the mapping of landslide domains, usin... more <p>Here we present a methodology for the mapping of landslide domains, using as a case study East Sikkim district (964 km<sup>2</sup>, population of 283,583 in 2011), a landslide-prone region in northeast India. Landslide domains are defined as regions with similar physical and environmental characteristics that specifically drive landslide dynamics. The methodology given here is more systematic than what has previously been used and draws on information on landslide factors inferred from landscape variables. Commonly used landslide factors are divided into three groups: preconditioning, preparatory, and triggering factors. Elevation data, geology, and landslide inventory information are used to provide information on the landslide factors in the study region. Data from the neighbouring and geologically similar regions of East Sikkim district are used to enhance landslide inventory information in the study region, effectively doubling the number of landslides in the inventory from 210 to 440 mapped landslides. We iterate over each of the landslide factor groups and for each iteration either map a new landslide domain boundary or enrich the information of the landslide domains. As a result, we map four landslide domains in East Sikkim district, India, with a size ranging from 81 km<sup>2</sup> to 394 km<sup>2</sup>. The domains have been further enriched using information on rainfall and earthquakes. Each landslide domain describes the typology of landslides and the general geomorphology and land use. The landslide domains in East Sikkim district can be used for (i) describing landslide processes homogenously; (ii) illustrating landslide processes for training or stakeholder engagement; and (iii) as a starting point for the construction of landslide susceptibility maps and landslide early warning that actively draws from the landslide processes that can be found in the region.</p>

Proceedings Of The 16th Multidisciplinary Conference On Sinkholes And The Engineering And Environmental Impacts Of Karst, 2020

Ordovician Hawthornden Schist and metamorphosed Silurian Kuala Lumpur Limestone, capped to the we... more Ordovician Hawthornden Schist and metamorphosed Silurian Kuala Lumpur Limestone, capped to the west by the Kenny Hill Formation (Carboniferous to Permian quartzite and phyllite) and bounded on the east and west by Triassic granitic hills. The structural geology is complex, and the depth of weathered bedrock extends to 40 meters or more. Alluvial tin, derived from the granite ranges was trapped between karst pinnacles where they remained exposed. Consequently, the Silurian limestone is largely buried by a range of sediment types, including the Kenny Hill Formation, placer deposits and alluvium associated with the Klang Valley.

The danger from landslide hazards to people and infrastructures is still rising worldwide. Due to... more The danger from landslide hazards to people and infrastructures is still rising worldwide. Due to the progressive development of urban areas and infrastructure, more and more people settle in environments that are or become endangered by mass movements. This situation is being complicated by the fact that the dependency of our society on a functioning infrastructure and number of human or objects in endangered areas increases at the same time. Early warning and alarm systems are an efficient tool to face landslide hazards and reduce the risks from landslides, especially where no other mitigation strategies are suitable. However the available technologies are comparatively expensive and not very flexible. Moreover the systems normally represent the state of technology and do not focus the user needs (people centred). The joint project »A Sensor-based Landslide Early Warning System (SLEWS)« aims at a systemic development of a prototyping alarm- and early warning system for different types of landslides utilizing ad hoc wireless sensor networks and spatial data infrastructure technologies according to OGC (Open Geospatial Consortium) guidelines for real-time monitoring. Therefore, SLEWS investigates and simulates the whole chain from data gathering and acquisition, evaluation and interpretation, up to data analysis, visualization and data supply for different end users. Besides the technical aspects of alarm and early warning systems, the demands of the users and requirements for an effective warn management are further important research fields within the project.

… 2010, held 2-7 May …, 2010

EGU General Assembly Conference Abstracts, Apr 1, 2019

AIMS geosciences, 2016

Mass movement processes of bedrock slopes are highly dependent on the orientations of structural ... more Mass movement processes of bedrock slopes are highly dependent on the orientations of structural discontinuities within the rock mass. The associated hazards are typically defined by the orientation of structures and associated mechanisms of slope failure such as planar sliding, wedge sliding and toppling. A typical rock mass with multiple weak surfaces, or discontinuities, may form a consistent pattern over a range of spatial scale. The type of hazard resulting from the pattern of discontinuities will vary according to the angle and direction of the slope face. Assessing the risk of rock slope instability involves understanding of the complex three-dimensional structural features of the rock mass. Recent developments in stereographic methods show advantages are gained by representing wedges by linking great circles rather than showing the intersection line on the stereograph. We applied these methods to three rock slopes where active mass movement has occurred. The case studies include a large rock slide-debris avalanche in the Philippines, coastal cliffs in Australia and mining excavation slopes in Ghana, West Africa.

Solid Earth, Sep 4, 2020

Understanding the impact of fracture networks on rock mass properties is an essential part of a w... more Understanding the impact of fracture networks on rock mass properties is an essential part of a wide range of applications in geosciences from understanding permeability of groundwater aquifers and hydrocarbon reservoirs to erodibility properties and slope stability of rock masses for geotechnical engineering. However, gathering high-quality, oriented-fracture datasets in the field can be difficult and time-consuming, for example, due to constraints on field work time or access (e.g. cliffs). Therefore, a method for obtaining accurate, quantitative fracture data from photographs is a significant benefit. In this paper we describe a method for generating a series of digital fracture traces in a geographic information system (GIS) environment, in which spatial analysis of a fracture network can be carried out. The method is not meant to replace the gathering of data in the field but to be used in conjunction with it, and it is well suited when field work time is limited or when the section cannot be accessed directly. The basis of the method is the generation of the vector dataset (shapefile) of a fracture network from a georeferenced photograph of an outcrop in a GIS environment. From that shapefile, key parameters such as fracture density and orientation can be calculated. Furthermore, in the GIS environment more complex spatial calculations and graphical plots can be carried out such as heat maps of fracture density. Advantages and limitations compared to other fracture network capture methods are discussed.

Engineering Geology, Mar 1, 2012

Applying the method nanoseismic monitoring to the fast-moving mudslide in Super-Sauze (French Alp... more Applying the method nanoseismic monitoring to the fast-moving mudslide in Super-Sauze (French Alps) we observed different types of seismic events caused by varying slope dynamics. We identified signals caused by rockfalls in the source area of the slope, and different types of signals, which had obviously been generated by material failure within the unstable part of the mudslide. Signal analysis and further investigations, e.g. the analysis of magnitude-frequency distribution and simultaneous measurements by nanoseismic monitoring and extensometer devices, revealed the generation of the observed seismic signals: fracture processes, i.e. slide quakes, within the unstable sediments and the development of fissures at the slope's surface. The spatial distribution of the epicenters (slide quakes), respectively the estimated source area (fissure development), correlates well with parts of the slope moving with higher velocities at the surface. Most of these signals were generated close to the in-situ crests, which are mostly covered by the mudslide material today, indicating specific dynamics in these particular slope areas.

<p>Forecasting rainfall-induced landslides, whilst challenging, is increasi... more <p>Forecasting rainfall-induced landslides, whilst challenging, is increasingly important due to the impact these hazards can have on society. The difficulty in forecasting arises from the inherent variability of geo-environmental factors and the scale at which underlying processes operate. The availability of data required to develop and validate thresholds for operational purposes is often limited. In regions where data (e.g. meteorological, or geotechnical) is sparse or incomprehensive, it is important to have a framework to systematically fuse the incomplete datasets to aid the development of a threshold model or to supplement an existing preliminary trigger threshold model.</p><p>For this study, a bespoke conceptual hydrological model called the ‘BGS water balance model’ is used in Nilgiris (Tamil Nadu state, India) to integrate the ground and meteorological information for informed decision making on the landscape saturation condition. This simple conceptual model with applicability over a large area provides an approximation of the degree of saturation value that can be used to map the potential antecedent wetness pathway leading to the initiation of landslides.</p><p>In this session, the BGS water balance model features along with the study area geological characteristics, landslide controls, input datasets and sensitivity analysis will be discussed. Further, we will show the results of the back-analysed landslides and explore the value of this approach in the context of landslide forecasting.</p>

<p>This research describes the development ... more <p>This research describes the development and pro-forma of a landslide tracker methodology (structure of questions and photos) to support local reporting of landslides in India, thus enhancing modelling of susceptibility to future landslides and India Landslide Early Warning Systems. This methodology aids in the collection of timely and representative information about landslide events using local people before such information is lost due to human clearance works or natural processes (further erosion, vegetation cover). In the framework of the UK NERC/FCDO funded LANDSLIP project ‘Landslide multi-hazard risk assessment, preparedness and early warning in South Asia', a collaboration of government, academic and NGO scientists/practitioners from India and UK co-designed a questionnaire in both paper and mobile app proforma called the ‘Landslide Tracker’. The Landslide Tracker was developed as a tool for gathering landslide information from different levels of local users (e.g., local officials, NGOs, students) to enhance landslide inventories in the test sites of Darjeeling and Nilgiris, India. Different users, supporting data capture within the project, have different levels of understanding and knowledge about landslides. The Tracker was developed with three user levels to reflect this variation in landslide expertise. Level 1 is available in paper format and Levels 1 to 3 in a freely available Google Play app developed by Amrita University “Landslide Tracker”. Level 1 of the landslide tracker represents all users where the expertise level is not known or assumed to be limited; this comprises the most basic landslide information. This group of non-specialists represents the majority group of people capturing data within each study area. Information submitted by this user group, due to the limited knowledge and understanding of landslides in a geological context, might be assumed to have the highest degree of uncertainty and potentially the greatest amount of false information. The questions for this group utilise a simplified lexicon, with (i) location, data and time, (i) pictures of landslide material, (iii) landslide type, with finally (iv) generalised impact information. Level 2 represents more specialist users with a higher advanced understanding of landslides either from their background training/proficiency or users that have undergone training. In general, these people are asked the same questions as in Level 1, but a more technical vocabulary is used, and more detailed information is requested, like the size of landslides. Level 3 is for trained landslide experts. They are asked a wide range of landslide questions, reflecting internationally recognised landslide glossaries and definitions, and based on the current methodology used by the Geological Survey of India. With the help of two NGOs (Keystone and Save the Hills) and the Geological Survey of India, the developed proforma (paper and mobile app), have undergone field testing. Feedback from this phase of development was essential for the improvement and update of the pro-forma.  Efforts during the most recent Monsoon by the partners has resulted in over 500 landslide records being collected in the two test sites by either the app or in paper format.</p>

<p>Monsoons are characterised by the widesp... more <p>Monsoons are characterised by the widespread occurrence of  landslides. Tracking each landslide event, developing early warning thresholds, understanding triggers, and initiating disaster rescue and relief efforts are complex for researchers and administration. The ever increasing landslides demand real-time data collection of events to enhance disaster management. In this work we designed and developed a dedicated crowd sourced mobile application, for systematic way of collection, validation, summarization, and dissemination of landslide data in real-time. This unique design of mobile app uses a scalable real-time data collection methodology for tracking landslide events through citizen science, and is available on Google Play Store for free, and at http://landslides.amrita.edu, with software conceived and developed by Amrita University in the context of the UK NERC/FCDO funded LANDSLIP research project (http://www.landslip.org/). This work implemented a structured database that integrates heterogeneous data such as text, numerical, GPS location, landmarks, and images. This methodology enables real-time tracking of landslides utilizing the details such as GPS location, date & time of occurrence, images, type, material, size, impact, area, geology, geomorphology, and comments in real-time. The mobile application has been uniquely designed to avoid missing landslide events and to handle the tradeoff between real-time spatial data collection without compromising the reliability of the data.  To achieve this a multi level user account was created based on their expert levels such as Tracker, Investigator, Expert.  A basic tracking form is presented for the Tracker level, and an extensive form is presented to the Expert level. The reliability of landslide data enhances as the user level increases from Tracker to Expert. Unique UI designs have been utilized to capture, and track the events. The tracking interface is divided into multiple screens; the main screen captures the landslide location through GPS enabled map interface and captures the date/time of the occurrence. Three additional screens capture images, additional details and comments. The 40 questions for landslide event collection used by the Geological Survey of India has been adapted through the collaborative effort of LANDSLIP partners to collect the additional details. The submitted landslides are immediately available for all users to view. The User can view entered landslides through the landslide image listing, Google maps interface, or tabular listing. The landslides can be filtered by date/time and other parameters. The mobile app is designed to be intuitive and fast, and aims to increase awareness about landslide risk through the integrated short documents, and videos. It has guidelines for safety, capturing images, mapping, and choosing the data from the multiple options. The uniqueness of the proposed methodology is that it enhances community participation, integrates event data collection, event data organizing, spatial and temporal summarization, and validation of landslide events and the impact. It pinpoints, maps and alerts real-time landslide events to initiate right disaster management activities to reduce the risk level. The Landslide tracker app was released during the 2020 monsoon season, and more than 250 landslides were recorded through the app.</p>

EGU General Assembly Conference Abstracts, May 1, 2010

Monitoring systems in landslide areas are important elements of effective Early Warning structure... more Monitoring systems in landslide areas are important elements of effective Early Warning structures. Data acquisition and retrieval allows the detection of movement processes and thus is essential to generate warnings in time. Apart from the precise measurement, the reliability of data is fundamental, because outliers can trigger false alarms and leads to the loss of acceptance of such systems. For the monitoring of mass movements and their risk it is important to know, if there is movement, how fast it is and how trustworthy is the information. The joint project "Sensorbased landslide early warning system" (SLEWS) deals with these questions, and tries to improve data quality and to reduce false alarm rates, due to the combination of sensor date (sensor fusion). The project concentrates on the development of a prototypic Alarm-and Early Warning system (EWS) for different types of landslides by using various low-cost sensors, integrated in a wireless sensor network (WSN). The network consists of numerous connection points (nodes) that transfer data directly or over other nodes (Multi-Hop) in real-time to a data collection point (gateway). From there all the data packages are transmitted to a spatial data infrastructure (SDI) for further processing, analyzing and visualizing with respect to end-user specifications. The ad-hoc characteristic of the network allows the autonomous crosslinking of the nodes according to existing connections and communication strength. Due to the independent finding of new or more stable connections (self healing) a breakdown of the whole system is avoided. The bidirectional data stream enables the receiving of data from the network but also allows the transfer of commands and pointed requests into the WSN. For the detection of surface deformations in landslide areas small low-cost Micro-Electro-Mechanical-Systems (MEMS) and positionsensors from the automobile industries, different industrial applications and from other measurement technologies were chosen. The MEMS-Sensors are acceleration-, tilt-and barometric pressure sensors. The positionsensors are draw wire and linear displacement transducers. In first laboratory tests the accuracy and resolution were investigated. The tests showed good results for all sensors. For example tilt-movements can be monitored with an accuracy of +/-0,06°and a resolution of 0,1°. With the displacement transducer change in length of >0,1mm is possible. Apart from laboratory tests, field tests in South France and Germany were done to prove data stability and movement detection under real conditions. The results obtained were very satisfying, too. In the next step the combination of numerous sensors (sensor fusion) of the same type (redundancy) or different types (complementary) was researched. Different experiments showed that there is a high concordance between identical sensor-types. According to different sensor parameters (sensitivity, accuracy, resolution) some sensor-types can identify changes earlier. Taking this into consideration, good correlations between different kinds of sensors were achieved, too. Thus the experiments showed that combination of sensors is possible and this could improve the detection of movement and movement rate but also outliers. Based on this results various algorithms were setup that include different statistical methods (outlier tests, testing of hypotheses) and procedures from decision theories (Hurwicz-criteria). These calculation formulas will be implemented in the spatial data infrastructure (SDI) for the further data processing and validation. In comparison with today existing mainly punctually working monitoring systems, the application of wireless sensor networks in combination with low-cost, but precise micro-sensors provides an inexpensive and easy to set up monitoring system also in large areas. The correlation of same but also different sensor-types permits a good data control. Thus the sensor fusion is a promising tool to detect movement more reliable and thus contributes essential to the improvement of Early Warning Systems.

Scientific Investigations Report, Oct 3, 2008

The 5G RuralDorset project (https://5gruraldorset.org/) was a large (£9M; 2020-2022), multi-disci... more The 5G RuralDorset project (https://5gruraldorset.org/) was a large (£9M; 2020-2022), multi-disciplinary project funded by the UK Department for Culture, Media and Sport that aimed to understand how 5G mobile network technologies could address some specific challenges in rural communities in Dorset, UK: public safety, economic growth, food production and environmental. Work Package X aimed to develop and trial a novel landslide monitoring system for coastal cliffs using 5G/NB-IoT (Narrow Band - Internet of Things) technologies. The system comprised a set of small, fully autonomous, highly integrated and power efficient sensing devices that were able to collect sensory data to identify landslide activity and landslide movement. These data were transmitted wirelessly using 5G/NB-IoT to a cloud-based Data Management Platform, where they were presented to the end user over a web interface for processing by Machine Learning algorithms. It is important to note that the term ‘Internet of...

EAGE-GSM 2nd Asia Pacific Meeting on Near Surface Geoscience and Engineering, 2019

Journal of Glaciology

Glacial ripping involves glaciotectonic disintegration of rock hills and extensive removal of roc... more Glacial ripping involves glaciotectonic disintegration of rock hills and extensive removal of rock at the ice-sheet bed, triggered by hydraulic jacking caused by fluctuating water pressures. Evidence from eastern Sweden shows that glacial ripping caused significant subglacial erosion during the final deglaciation of the Fennoscandian ice sheet, distinct from abrasion and plucking (quarrying). Here we analyse the ice drag forces exerted onto rock obstacles at the base of an ice sheet, and the resisting forces of such rock obstacles: glaciotectonic disintegration requires that ice drag forces exceed the resisting forces of the rock obstacle. We consider rock obstacles of different sizes, shapes and fracture patterns, informed by natural examples from eastern Sweden. Our analysis shows that limited overpressure events, unfavourable fracture patterns, low-transmissivity fractures, slow ice and streamlined rock hamper rock hill disintegration. Conversely, under fast ice flow and fluctuat...

<p>Forecasting rainfall-induced landslides, whilst challenging, is increasi... more <p>Forecasting rainfall-induced landslides, whilst challenging, is increasingly important due to the impact these hazards can have on society. The difficulty in forecasting arises from the inherent variability of geo-environmental factors and the scale at which underlying processes operate. The availability of data required to develop and validate thresholds for operational purposes is often limited. In regions where data (e.g. meteorological, or geotechnical) is sparse or incomprehensive, it is important to have a framework to systematically fuse the incomplete datasets to aid the development of a threshold model or to supplement an existing preliminary trigger threshold model.</p><p>For this study, a bespoke conceptual hydrological model called the ‘BGS water balance model’ is used in Nilgiris (Tamil Nadu state, India) to integrate the ground and meteorological information for informed decision making on the landscape saturation condition. This simple conceptual model with applicability over a large area provides an approximation of the degree of saturation value that can be used to map the potential antecedent wetness pathway leading to the initiation of landslides.</p><p>In this session, the BGS water balance model features along with the study area geological characteristics, landslide controls, input datasets and sensitivity analysis will be discussed. Further, we will show the results of the back-analysed landslides and explore the value of this approach in the context of landslide forecasting.</p>

<p>Here we present a methodology for the mapping of landslide domains, usin... more <p>Here we present a methodology for the mapping of landslide domains, using as a case study East Sikkim district (964 km<sup>2</sup>, population of 283,583 in 2011), a landslide-prone region in northeast India. Landslide domains are defined as regions with similar physical and environmental characteristics that specifically drive landslide dynamics. The methodology given here is more systematic than what has previously been used and draws on information on landslide factors inferred from landscape variables. Commonly used landslide factors are divided into three groups: preconditioning, preparatory, and triggering factors. Elevation data, geology, and landslide inventory information are used to provide information on the landslide factors in the study region. Data from the neighbouring and geologically similar regions of East Sikkim district are used to enhance landslide inventory information in the study region, effectively doubling the number of landslides in the inventory from 210 to 440 mapped landslides. We iterate over each of the landslide factor groups and for each iteration either map a new landslide domain boundary or enrich the information of the landslide domains. As a result, we map four landslide domains in East Sikkim district, India, with a size ranging from 81 km<sup>2</sup> to 394 km<sup>2</sup>. The domains have been further enriched using information on rainfall and earthquakes. Each landslide domain describes the typology of landslides and the general geomorphology and land use. The landslide domains in East Sikkim district can be used for (i) describing landslide processes homogenously; (ii) illustrating landslide processes for training or stakeholder engagement; and (iii) as a starting point for the construction of landslide susceptibility maps and landslide early warning that actively draws from the landslide processes that can be found in the region.</p>

Proceedings Of The 16th Multidisciplinary Conference On Sinkholes And The Engineering And Environmental Impacts Of Karst, 2020

Ordovician Hawthornden Schist and metamorphosed Silurian Kuala Lumpur Limestone, capped to the we... more Ordovician Hawthornden Schist and metamorphosed Silurian Kuala Lumpur Limestone, capped to the west by the Kenny Hill Formation (Carboniferous to Permian quartzite and phyllite) and bounded on the east and west by Triassic granitic hills. The structural geology is complex, and the depth of weathered bedrock extends to 40 meters or more. Alluvial tin, derived from the granite ranges was trapped between karst pinnacles where they remained exposed. Consequently, the Silurian limestone is largely buried by a range of sediment types, including the Kenny Hill Formation, placer deposits and alluvium associated with the Klang Valley.

The danger from landslide hazards to people and infrastructures is still rising worldwide. Due to... more The danger from landslide hazards to people and infrastructures is still rising worldwide. Due to the progressive development of urban areas and infrastructure, more and more people settle in environments that are or become endangered by mass movements. This situation is being complicated by the fact that the dependency of our society on a functioning infrastructure and number of human or objects in endangered areas increases at the same time. Early warning and alarm systems are an efficient tool to face landslide hazards and reduce the risks from landslides, especially where no other mitigation strategies are suitable. However the available technologies are comparatively expensive and not very flexible. Moreover the systems normally represent the state of technology and do not focus the user needs (people centred). The joint project »A Sensor-based Landslide Early Warning System (SLEWS)« aims at a systemic development of a prototyping alarm- and early warning system for different types of landslides utilizing ad hoc wireless sensor networks and spatial data infrastructure technologies according to OGC (Open Geospatial Consortium) guidelines for real-time monitoring. Therefore, SLEWS investigates and simulates the whole chain from data gathering and acquisition, evaluation and interpretation, up to data analysis, visualization and data supply for different end users. Besides the technical aspects of alarm and early warning systems, the demands of the users and requirements for an effective warn management are further important research fields within the project.