Coordinators: Dr. Akhouri Pramod Krishna Dr. C. Jeganathan

External Coordinator: Dr. Malay Mukul Earth Sciences IIT Bombay

Local Organising Committee: Dr. N. Patel Dr. V.S. Rathore Dr. Mili Ghosh nee Lala Dr. R.N.K. Sharma Mr. Nitish Kumar Sinha Support Acknowledgements: Research Scholars Project Fellows PG Students

FOREWORD

Many Himalayan towns are typically located along hill-tops and have undergone rapid growth and urbanization in the last decade. Their populations have grown manifold and multi-storeyed Reinforced Cement Concrete (RCC) structures abound in these towns in complete disregard to the seismic and landslide hazard associated with the Himalaya. Given that the housing sector in the Indian Himalaya is unorganized, it lacks an enforceable standard building code for these constructions. Consequently, many of these towns are built on fault zones and are spread over hill slopes that are steep. These towns are, therefore, vulnerable to both earthquakes and landslides as Himalaya is an active seismic zone. The recent September 18, 2011, 6.9 magnitude earthquake in Sikkim was a wake-up call for pending disaster. In the light of this situation there is an acute need to determine current areas of highest risk as well as to plan for future urbanization as well as relief and rescue strategies accordingly. This Brainstorming Workshop aims to develop a new methodology that integrates rheological and structural signatures of deformation in faulted rocks in the field of structural geology, quantification of contemporary slope motions using high precision static and Real Time Kinematic Global Navigation Satellite System (GNSS) and measurement of stability and steepness of slopes using Satellite and Drone based Remote Sensing and Digital topography, followed by the modelling of the fault-zone induced surface mass transport in the studied terrain. This will provide a base-map for establishing what slopes are most likely to fail and cause aseismic or seismically induced surface mass transport. We aim to develop and test this new integrated approach using townships affected by fault zones in the West Bengal state of Indian Eastern Himalaya as a case study and then extend the methodology to the other parts of the Indian Himalaya.

This National Brainstorming Workshop has brought together a number of Indian Researchers to deliberate upon the most effective way to carry out research in Himalayan towns in Darjeeling-Sikkim Himalaya to produce a hazard map that superimposes layers in a Geographic Information System (GIS). This would allow determination of the most vulnerable zones in the urbanized regions. Proposals will be formulated and put together during the Workshop and presented by potential PIs. A concept paper will be prepared to outline the roadmap for the development of the research theme on "Landslides and Human Environment: A New Approach to the Study of Fault related Hazards in Himalayan Towns".

Coordinators

Brief objective of the Workshop

Many Himalayan towns are typically located along hill-tops and have undergone rapid growth and urbanization in the last decade. Their populations have grown manifold and multi-storeyed Reinforced Cement Concrete (RCC) structures abound in these towns in complete disregard to the seismic and landslide hazard associated with the Himalaya. Given that the housing sector in the Indian Himalaya is unorganized, it lacks an enforceable standard building code for these constructions. Consequently, many of these towns are built on fault zones and are spread over hill slopes that are steep. These towns are, therefore, vulnerable to both earthquakes and landslides as Himalaya is an active seismic zone. The recent September 18, 2011, 6.9 magnitude earthquake in Sikkim was a wake-up call for pending disaster. In the light of this situation there is an acute need to determine current areas of highest risk as well as to plan for future urbanization as well as relief and rescue strategies accordingly. This Brainstorming Workshop aims to develop a new methodology that integrates rheological and structural signatures of deformation in faulted rocks in the field of structural geology, quantification of contemporary slope motions using high precision static and Real Time Kinematic Global Navigation Satellite System (GNSS) and measurement of stability and steepness of slopes using Satellite and Drone based Remote Sensing and Digital topography, followed by the modelling of the fault-zone induced surface mass transport in the studied terrain. This will provide a base-map for establishing what slopes are most likely to fail and cause aseismic or seismically induced surface mass transport. We aim to develop and test this new integrated approach using townships affected by fault zones in the West Bengal state of Indian Eastern Himalaya as a case study and then extend the methodology to the other parts of the Indian Himalaya.

Department of Remote Sensing

Department of Remote Sensing was established in 1997 with an aim to meet the increasing demand for qualified manpower in this rapidly developing field. Application of Remote Sensing/Geoinformatics techniques using tools such as Geographic Information System (GIS) and Global Positioning System (GPS) in various activities including resources evaluation, environmental monitoring and land use/land cover mapping etc has grown considerably during the last few decades and RS data products are increasingly being used for plan formulation at all levels. The benefits of space technology, both direct and indirect, have introduced new dimensions into the study and understanding of Earth’s processes and in improving the quality of life for the people living on it.An essential pre-requisite to partaking in these opportunities is the building of various indigenous capacities for the development and utilization of space science and technology.

About the Institute

For over five decades, BIT Mesra (located 16 kms from Ranchi, the Jharkhand state-capital) has been engaged in nurturing minds through a rich heritage of academic excellence. Essentially a hub of bustling student activities, the beautiful campus has been a second-home to thousands of students in their journey to challenge the times. Established in 1955 by the visionary-industrialist Mr. B.M. Birla, it is today one of the most premier engineering destinations in India.

Keeping up with the times has never been enough at BIT as it has mostly been either at the top of ranking surveys or the first among initiators of path breaking ideas. From the introduction of new academic programmes to re-structuring the current ones, from improving infrastructure to upgrading teaching skills, the students' welfare has always been the focal point in BIT's larger picture. As a result, the Institute enjoys an unsurpassed reputation in academia and corporate circles being the preferred manpower source for many industries not only in India but also abroad.

Campus highlights

Campus life is undoubtedly the most cherished memory for a student and BIT ensures that discipline is properly coupled with a more than adequate share of fun and excitement. Students share an open and transparent bond with the faculty and other staff members and everybody puts in their very best to make the Institute a great place to live and learn in. Completely residential, the campus is self- contained with excellent hostel facilities and hangout zones. Along with Undergraduate and Postgraduate Programmes, the Institute has sizeable number of registered students for Doctoral Programmes at present.

TECHNICAL SESSIONS

MARCH 16, 2020 DAY 1 0930-1000 Registration 1000-1045 Workshop Inauguration 1045-1115 High Tea TECHNICAL SESSION I INTRODUCTION Chair: A. P. Krishna 1115-1145 Outline and Motivation for the Workshop – Malay Mukul 1145-1215 Fault zones in the Himalaya and Himalayan towns – Abdul Matin 1215-1230 Tea Break and Discussions TECHNICAL SESSION II LANDSLIDES IN THE DARJILING-SIKKIM HIMALAYA Chair: Abdul Matin 1230-1300 Landslide Hazard in the Darjiling-Sikkim Himalaya – AP Krishna 1300-1330 Landslide Distribution in the Darjiling-Sikkim Himalaya – Praful Rao 1330-1430 LUNCH TECHNICAL SESSION III FAULT ZONES AND REMOTE SENSING Chair: Malay Mukul 1430-1500 Fault Zone architecture- Vinee Srivastava 1500-1530 Remote Sensing Techniques in detecting surface motions – Kuntala Bhusan 1530-1545 Tea Break and Discussions TECHNICAL SESSION IV DIGITAL TOPOGRAPHY Chair: C. Jeganathan 1545-1615 Digital Topography data and their uncertainties – Manas Mukul 1615-1645 Drone based high precision DEMs – D. Ramakrishnan 1645-1730 Discussions and Daily Round Up MARCH 17, 2020 Day 2 TECHNICAL SESSION V TECTONIC GEOMORPHOLOGY Chair: Malay Mukul 0945-1015 Tectonic Geomorphology signatures and drainage development in fault zones – Vimal Singh 1015-1045 Uncertainties in Geomorphic Indices and fault zones –Manas Mukul 1045-1100 Tea Break and Discussions TECHNICAL SESSION VI GNSS DATA AND MODELLING OF SLOPE STABILITY Chair: Purba Joshi 1100-1130 GNSS Technology in detecting surface motions – Sridevi Jade 1130-1200 Slope Stability monitoring and modelling –Maneesha V. Ramesh 1200-1215 Tea Break and Discussions TECHNICAL SESSION VII MODELLING AND SOCIETAL IMPACT Chair: Sridevi Jade 1215-1245 Modelling RTK GPS surface motions by Dislocations – Vinee Srivastava 1245-1315 Dissemination of landslide hazard results for societal benefit – G. Balamurugan 1315-1415 LUNCH 1415-1445 Optimal integration of tools and scientific insights for societal benefit -Purba Joshi 1445-1545 DISCUSSION AND RECOMMENDATIONS 1545-1600 Tea break 1600-1700 Valedictory Session

TABLE OF CONTENT

Sl. No Technical Session Topic Page No Modelling fault zone induced surface mass transport in 1 Himalayan orogenic terrains and fault related hazards 8-9 Technical Session 1 in Himalayan towns 2 Fault zones in the Himalaya and Himalayan towns 10-11 Landslide Hazard studies in the Darjeeling-Sikkim 3 13-17 Himalaya Technical Session 2 Living with landslides: the community’s perspective in 4 18-20 Kalimpong 5 Fault Zone Architecture 22-25 Technical Session 3 6 Remote Sensing technique in detecting surface motion 26-27 7 Digital Topography data and their uncertainties 29-31 Unmanned aerial vehicles and Ultra resolution remote Technical Session 4 8 sensing: Application potentials in mass movement 32-33 studies. Tectonic Geomorphology signature and drainage 9 35-37 characteristics in fault zone Technical Session 5 Uncertainties in Geomorphic Indices and fault zone 10 38-41 identification 11 GNSS based Landslide Hazard 43-46 Technical Session 6 Internet of Things System for real time monitoring and 12 47-49 early warning of Landslides Modelling of Real Time Kinematic Global Navigation 13 Satellite System (RTK-GNSS) derived surface 51-53 displacements and velocities by dislocations Technical Session 7 Dissemination of Landslide Hazard results for Societal 14 54-60 benefits Understanding the role of design and collaborative 15 61-62 model for innovation towards system-level 16 Workshop Moments in Pictures 64-69

TECHNICAL SESSION – I

INTRODUCTION

Chair – Dr. A.P. Krishna

Modelling fault zone induced surface mass transport in Himalayan orogenic terrains and fault related hazards in Himalayan towns

Malay Mukul Akhouri P. Krishna Department of Earth Sciences Department of Remote Sensing IIT Bombay, Powai Birla Institute of Technology MUMBAI 400076 Mesra, Ranchi 835215 [email protected] [email protected]

ABSTRACT KEYWORDS Many Indian Himalayan towns are typically located Fault zone, slope stability, surface mass transport, RTK- along hill-tops and have undergone rapid growth and GNSS urbanization in the last decade. Their populations have grown manifold and multi-storeyed Reinforced Cement Concrete (RCC) structures abound in these 1 Introduction towns in complete disregard to the seismic and This Brainstorming workshop aimed at integration of landslide hazard associated with these Himalayan modern geological understanding of the geometry and towns. The housing sector in the Indian Himalaya is kinematics of fault zones in the Himalayan region with unorganized and, therefore, it lacks an enforceable high precision Real Time Kinematic (RTK) and static standard building code for these constructions. Global Navigation Satellite System (GNSS), Remote Consequently, many of these towns are built on brittle Sensing tools, Electronics and Instrumentation. This fault zones and are spread over hill slopes that are will be supported by geological assessments to steep. These towns are, therefore, vulnerable to both investigate and model fault-zone induced surface mass earthquakes and landslides as the Himalaya is an active transport in heavily populated urbanized pockets in seismic zone. In the light of this situation, there is an the Himalaya. As most of the major Himalayan towns acute need to determine current areas of highest originated on hill tops and saddles and subsequently susceptibility and plan future urbanization as well as spilled over onto the surrounding hill slopes, the relief and rescue strategies accordingly. This assessment of aseismic and seismically induced Brainstorming workshop aimed to develop a new surface mass transport is critical in pre-empting integrated methodology to provide a base-map for possible landslides in these regions. Quantification of establishing which slopes are most likely to fail and topographic slope using remote sensing tools and high cause aseismic or seismically induced surface mass resolution RTK-GNSS for ground control is, therefore, transport. We aim to develop and test this new required in these towns to assess the most vulnerable integrated approach using townships affected by fault slopes. These results will be integrated with a detailed zones in the West Bengal state of Indian Eastern geological study of the lithological, rheological and Himalaya as a case study and then extend the structural nature and location of major faults in the methodology to the other parts of the Himalaya. region. We will aim to gain insight into the past Anomalies in the measured velocities of the network deformation behaviour of the faults as well as map out would point to potential slope failure so that remedial the spatial distribution of fault zone rocks within the action can be taken by civil engineers and authorities townships. The most vulnerable areas in the townships BEFORE aseismic slope failure. would be those with steepest slopes and fault rocks. These results and insights can then be integrated with modelling of possible failure and slip surfaces to create pointed out that high precision digital elevation maps to be used for urban planning in the next phase. models could be made using drones together with RTK-GNSS ground control points. The discussion then The project has the potential to prevent the loss of moved to Tectonic Geomorphology and Dr. Vimal human life and property in a crisis (such as Singh summarized the geomorphological signatures earthquakes and earthquake-induced or aseismic and drainage development in fault zones and Dr. landslides) and direct future urbanization and Manas Mukul pointed out how uncertainties in the urbanization policy and regulation in Himalayan digital topography data propagate to the computed townships. Geomorphic Indices using the data. Dr. Sridevi Jade then talked in detail about using GNSS Technology in 2 Brainstorming Workshop Presentations detecting surface motions along slopes. This was followed by a talk on slope stability monitoring and The outline and the aims of the workshop were first modelling by Dr. Maneesha V. Ramesh and possible laid out at the beginning by the organizers. The frontal modelling of surface displacement and velocity fields Darjiling Himalaya was the geographic region chosen using dislocations by Dr. Vinee Srivastava. Dr. G. to develop this integrated methodology. Therefore, Balamurugan then described his work on landslide the workshop began with an introduction to the hazard in the Darjiling Himalaya and its dissemination geology of the area. Prof. Abdul Matin summarized for societal benefit. Dr. Purba Joshi then concluded the fault zones seen in the Darjiling Himalaya and with a talk on how optimal integration of tools and pointed out that many Himalayan towns were located scientific insights for societal benefit is possible by on these towns. He went on to also summarize the designing a collaborative model. known landslide zones in the Darjiling Himalaya that follow fault zones. Prof. A. P. Krishna next talked about 3 Conclusions the Landslide Hazard studies that have been carried out in the Darjiling-Sikkim Himalaya. Wing Cmdr. The discussions during the workshop provided us with Praful Rao, who is the founder of ‘Save the Hills’ and the insight and the road map to develop an integrated part of the Integrated Mountain Initiative (IMI) that is proposal for submission to the MOES. A networked spread across 11 mountain states, talked about the project that uses a collaborative model design to landslide distribution in the Darjiling-Sikkim Himalaya develop a new integrated methodology will be from a valuable local perspective pointing out that developed to address this societally relevant problem landslide is probably the only natural hazard which and pre-empt future possible landslides in Himalayan causes loss of land and property. Dr. Vinee Srivastava towns. then talked about the contemporary understanding of fault zone architecture and pointed out the importance of mapping core and damage zones of a fault zone for slope stability studies as they directly control the rheological properties of the slope forming material. Dr. Kuntala Bhusan initiated the discussion on the use of remote sensing techniques for slope stability studies by summarizing the techniques used in detecting surface motions. This was followed by a discussion on digital topography. Dr. Manas Mukul talked about the verticaluncertainties associated with publically downloadable digital topography data and pointed out that these datasets contain outliers that must be eliminated in order to bring the uncertainties close to the mission goal. Prof. D. Ramakrishnan Fault zones in the Himalaya and Himalayan towns

Abdul Matin Formerly Professor of Geology University of Calcutta Kolkata, West Bengal, India [email protected]

ABSTRACT although, there are large part of the Himalayas where the details of imbricate thrust faults and duplex The continental collision between the Eurasian and structure, if any, yet to be worked out. In addition with the Indian plates has resulted in the formation of the the regional thrust faults and their imbricates, there Himalayas, the highest and most extensive orogenic are transverse fault zone (near-strike slip in nature), mountain range in the world. The Indus suture across the Himalayan trend, e.g., Gish Transverse zone represents the actual boundary between the Indian in Darjiling-Sikkim Himalaya (DSH)12, Kosi fault, which plate and the Eurasian plate. The Tibetan plateau, with are thought to have been developed along the higher extensive faulting, is a broad region of elevated order salient-recess boundaries in the first-order topography occur north of Himalayas. The Indian Himalayan salient. Therefore on the whole, there are continental crust and lithosphere have been thrust very large-scale (1000s of km) to smaller-scale (100s beneath the Eurasian crust across the entire width of to 10s of km) thrust faults and near strike-slip the Tibetan plateau. transverse faults all throughout the Himalayas. It is It is estimated that the original continental crust in the universally known that faults are weak zones, consists Himalayas has been shortened by 300 km or more. usually of fragile material, along and from which earth Strain in the crust is accommodated by both brittle material moves easily with a little triggering from and ductile mechanisms. The brittle upper crust was other Earth's processes. compressed and thickened by displacements on a In this structural background of Himalaya the series of thrust faults that form a thrust belt along focus is now on the human settlements in the with the folds within it; the fold-thrust complex is now Himalayas, particularly in the DSH. The large human known as the Himalayan fold-thrust belt. The wedge- settlements in towns and cities are distributed in the shaped Himalayan fold-thrust belt is bounded in the Himalayas in two segments - in the foothills and Lesser north by the South Tibetan Detachment zone (STD) Himalayas and in the low lying planes and hilly zones and the base of the wedge is marked by the basal in front of the Himalayas. In higher Himalaya towns Main Himalayan thrust (MHT). The fold-thrust belt with large human settlements are uncommon. Towns consists of five regional listric thrust faults and the and cities were grown historically on the availability of thrust sheets which sole into the MHT. The in the water, and usually of broad flat zones in different sequence of regional thrust faults from north to south parts of the Himalaya, however, they grew and are Main Central thrust (MCT), Munsiari thrust (MT), expanded in the neighbouring hilly areas as Ramgarh thrust (RT), Main Boundary thrust (MBT) and continuous zone or discontinuous clusters. The major Main Frontal thrust (MFT); in the north the MCT sheet towns which are sitting on the Himalayas from east to is bounded by the STD1. MFT is considered to be the west are: Itanagar and Tawang in Arunachal Pradesh, surface to near surface equivalent of the MHT 2,3,4. Thimpu, Paro, Haa, Punakha, Phuntsholing, Samtse, Apart from the regional thrusts, mentioned above, Sarpang, Chhukha in Bhutan Himalaya, Darjiling, there are a large number of imbricate thrust faults Kalimpong, Kurseong, Lava, Gorubathan in the (imbricate to the regional thrust) and duplex Darjiling Himalaya, Gangtok, Mangan, Jorthang, structures in different segments of the Himalayas, Namchi, Geyzing, Pelling, in Sikkim Himalaya, Tribeni, worked out in detail by different workers5, 6, 7, 8, 9,10,11 Kathmandu, Pokhra in Nepal Himalaya, Dehradun, continental underthrusting beneath southern Tibet. Almora, Ranikhet, Mussoorie, Pithoragarh, Uttarkashi, Nature, 366, 557–559. Nainital, Simla, Soaln, Srinagar, Leh and Ladakh in [3] Lave J. andAvouac JP, 2000. Fluvial incision and Western Himalaya. The list is not all inclusive, but tectonic uplift across the Himalayas of central Nepal some major towns mainly in the Himalaya. Apart from Journal of Geophysical Research, 106 (B11), 26561– the towns and cities sitting on the Himalayas, there 26591. are a large number of towns which are present just in [4] Bilham R. Gaur VK. and Molnar P, 2001. Himalayan front of the Himalayas. Out of these towns present seismic hazard. Science 293, both on the Himalayan mountain range as well as in 1442–1444. front of the mountains, many of them are sitting on or [5] Banerjee S, 2016. Structure and Kinematics of the very near to the regional and other thrust faults and Ramgarh Thrust Sheet, Darjiling-Sikkim Himalaya. on the transverse faults. Major roads and some Unpublished Ph. D. Thesis, University of Calcutta, railways connecting the town in the Himalaya run Kolkata. p. 220. across and along some of the faults. A large number of [6] Kundu A. Matin A and Mukul M, 2012. people live in these towns. If we look to the number Depositional environment and provenance of Middle of people living in large towns in Darjiling-Sikkim Siwalik sediments in Tista valley, Darjiling District, Himalaya, the figure according to the 2011 census Eastern Himalaya, Indian Journal of Earth System records the population in Darjiling town (1.32 lakh), Science, 121, 73–89. Kalimpong town (0.5 lakh), Kurseong (0.42 lakh), [7] Bhattacharyya K. and Mitra G, 2009. A new Gangtok (1 lakh). In 2020, the population is definitely kinematic evolutionary model for thegrowth of a much larger than the above figure. So we can roughly duplex - an example from the Rangit duplex, Sikkim estimate the huge number of people live in different Himalaya,India. Gondwana Research, 16, 697-715. Himalayan towns and in the towns in Himalayan [8] Long S. McQuarrie N. Tobgay T. Rose C. George mountain front. Himalayan fault zones typically Gehrels G. and Grujic D, 2010. Tectonostratigraphy of characterize brittle to brittle-ductile and ductile the Lesser Himalaya of Bhutan: Implications for the deformation. Brittle deformation results in cataclastic along-strike stratigraphic continuity of the northern rocks in the fault zones those are less strong than the Indian margin. Geological Society of America Bulletin, protolith. The town and the connecting roads and doi: 10.1130/B30202.1. railways are also vulnerable due to their locations on [9] DeCelles PG. Robinson DM. Quade J. Ojha T P. or near the fault zones because of weak basement Garzione CN. Copeland P. and Upreti B N, 2001. rocks. Large to small landslides and movement of Stratigraphy, structure, and tectonic evolution of the earth materials along and adjacent to the fault zones Himalayan fold-thrust belt in western Nepal. are common and that kills and dislodge a large Tectonics, 20, 487-509. number of people living in the towns and villages. [10] Srivastava P. and Mitra G, 1994. Thrust geometries and deep structure of the outer and KEYWORDS lesserHimalaya, Kumaon and Garhwal (India): Himalayan orogenic belt, Thrust faults, transverse Implications forevolution of the Himalayan fold-and- faults, Himalayan town thrust belt. Tectonics, 13, 89-109. [11] Srivastava V. Mukul M. and Barnes JB, 2016. Main REFERENCES Frontal thrust deformation and topographic growth of [1] Yin A. 2006. Cenozoic tectonic evolution of the the Mohand Range, northwest Himalaya. Journal of Himalayan orogen as constrained by along-strike Structural Geology, 93, 131–148. variation of structural geometry, exhumation history, [12] Mukul M. Jade S. Ansari K. and Matin A. 2014. and foreland sedimentation. Earth Science Review, 76, Seismotectonic implications of strike-slip earthquakes 1–131. in Darjiling-Sikkim Himlalaya. Current Science, 106, [2] Zhao W. and Nelson KD, 1993. Project INDEPTH 198-210. Team,. Deep seismic reflection evidence for

TECHNICAL SESSION – II

LANDSLIDES IN THE DARJILING-SIKKIM HIMALAYA

Chair – Dr. Abdul Matin

Landslide Hazard studies in the Darjeeling-Sikkim Himalaya Akhouri Pramod Krishna

Department of Remote Sensing

Birla Institute of Technology Mesra, Ranchi, Jharkhand (India) [email protected]

ABSTRACT study, assess, document and mitigate this Landslide is understood as movement of a mass of phenomenon. rock, debris or earth down a slope in hilly and KEYWORDS: Landslides, Darjeeling-Sikkim, Indian mountainous regions. Landslides commonly occur in Himalayan Region, Remote Sensing, Geoinformatics, conjunction with other major natural disasters, such Geospatial techniques as earthquakes, volcanic activity and floods or erosion caused by heavy rainfall. A landslide, in restricted Introduction sense of the word, is a rapid to very rapid down-slope One of the most frequently occurring natural hazards movement of soil or rock bounded by a more or less in the Darjeeling-Sikkim Himalaya is landslide (Fig. 1). discrete failure surface, which define the sliding mass. Human interference by way of denudation of natural An essential element of sliding is that the movement vegetation, agricultural operations, civil constructions takes place as a unit portion of land, which implies that like roads, irrigation channels, hydro-electric power there are no movements within the slipped block (the channels etc. often accelerate the process [1]. A internal movements). number of geo-environmental factors control such They are usually slow moving, but can damage or natural hazards and need to be understood for destroy structures founded on the moving mass. mitigation. In the Himalayas, each kilometer of road Rockslides occur when a rock mass slides on a requires displacement of 40 to 80 thousand cubic detachment surface. Darjeeling region in West Bengal meters of debris and generates unstable cut-slopes and Sikkim state falling within the Indian Hiamalayan [2]. Sikkim Himalayan region is characterized by high Region (IHR) suffer from this natural hazard denudation rates [3]. Channel blocking by the piling up frequently. of debris material coming from landslide body has There is temporal and spatial space of such two-fold hazardous effect- danger of flash floods occurrences which are experienced in these regions downstream and submergence upstream of good with varying magnitude of severity and impacts. There agricultural lands, buildings and roads [4]. Landslides are extensive studies undertaken using conventional produce both direct and indirect damage, they field-based methods as well as utilizing modern and endanger or even obstruct traffic and considerably advanced geospatial tools viz. Earth observing (EO) increase road maintenance costs [5]. remote sensing satellite data and geoinformatics for A number of studies have been undertaken to effective understanding of this natural disaster. understand including the one by this author entitled Investigations involving geospatial techniques Geo-environmental assessment of landslide hazards in involving high resolution satellite data are picking up parts of Sikkim Himalaya for mountain risk these days. There are various national level efforts to engineering evaluations using remote sensing and GIS techniques during the years 1999-2003 sponsored by Indian Space Research Organisation, Department of Space, Government of India [6]. Similarly, there had been many other studies by different research groups to assess the causative factors, hazard and risk zonation using conventional as well as advanced remote sensing/geospatial techniques. Such studies usually have been focused on generation of information on active landslides of significant dimensions in these regions. Geo-environmental set- up being investigated in such studies have the considerations of slope, lithology/rock characteristics, land use/land cover, drainage density, rainfall, soil physical properties such as soil moisture, water holding capacity, rate of percolation and soil texture etc. The analysis to follow have been mostly organized around a GIS platform in such study approaches.

Figure 2: Landslide scars captured on the Earth Observation satellites and an example of ground level condition

SPATIO-TEMPORAL ASSESSMENT OF LANDSLIDE SUSCEPTIBILITY

Modern geo-informatics tools like Remote Sensing and GIS for landslide hazard assessment and zonation can yield valuable information [7][8][9][10][11][12][13]. Hazard zonation of landslides refers to the division of land into homogeneous areas and the ranking of these areas

according to their degree of actual or potential hazard caused by mass movement or landslide. The landslide zonation maps specify areas of future possible occurrences or potential threats of landslides [14][15][16][17]. In common practice, zonation maps display the spatial distribution of hazard classes. The zonation involves evaluation of hazard and vulnerability to predict risk zones due to landslides. Interpretation of landslides from remote sensing data requires knowledge of the distinctive features associated with slopes and movements alongwith their image characteristics.

A representative flow diagram below shows an Figure 1: Visuals of typical landslides in Darjeeling-Sikkim Himalaya approach using spatio-temporal and statistical approach towards landslide hazard assessment (after metamorphic unit into other [19]. The Daling group of [6]): rocks is structurally dominated by a large-scale doubly plunging fold known as Sikkim dome which is elongated in NNE-SSW direction [20]. Rangit tectonic window, an important tectonic feature of this region occupies the western flank of this domal structure [21]. The tectonic base of the high grade gneisses over the Daling is modelised to represent the Main Central Thrust (MCT) which is tectonically active and this tectonic boundary separates the Lesser Himalaya from the Higher Himalaya [22]. Whereas, a moderate to steeply north dipping reverse fault Main Boundary Fault (MBF) separates the Lesser Hiamalaya with Sub- Himalaya [23]. The sedimentary palaeo-environment of deposition of sediment includes greywackes which form the basal member of the Daling metapelites [24].

IMPORTANT MOUNTAIN RISK ENGINEERING (MRE) CONCEPTS FOR MOUNTAIN HIGHWAYS Infrastructure such as road in the mountain areas cover significant locations of the region viz. Darjeeling- Sikkim. Several major/significant active landslides of significant dimensions exist along the highways in

Darjeeling-Sikkim region. From the point of view of HOST TERRAIN CONDITIONS natural hazard like landslides, avoidance, mitigation Darjeeling-Sikkim Himalaya experience the problem of and control at every stage is essential through suitable landslides and other forms of mass movements at location, design and construction. Roads are the single varied locations. This is supposed to be due to a most affordable infrastructure for mountain combination of factors, dominantly geological with inhabitants to connect with rest of the areas. Marginal fragile rock formation, unconsolidated soil materials stability conditions of slopes along various road coupled with high intensity precipitation and steeply segments, high traffic volumes along national and sloping topography. Since the work [18] in Darjeeling- state highways coupled with constraints of Sikkim Himalaya, most workers have divided Himalaya maintenance and management are the challenges. into a series of longitudinal tectonostratigraphic Host geo-environmental conditions considered domains 1. Sub-Himalaya, 2. Lesser Himalaya, 3. together with major landslide zones could lead to Higher Himalaya and 4. Tethys Himalaya separated by landslide hazard susceptibility zonation [LHSZ] with major dislocation zones. Gondwana rocks are help of suitable computational techniques [25]. Thus, structurally overlain by the metamorphic rocks in the prediction of landslides with spatial details using Darjeeling-Sikkim Himalaya and are termed as geoinformatics techniques are very useful for MRE Darjeeling rocks (mainly mica schists and gneisses). based mitigation plans [6][26]. Darjeeling structurally overlies the Daling and it was observed that there is a gradual passage from one ACKNOWLEDGMENTS [8] Van Westen, C.J. & Terlien, M.T.J., 1996. Author is thankful to the G.B. Pant Institute of Deterministic landslide hazard analysis in GIS – a case Himalayan Environment and Development study from Manizales (Colombia), Earth Surface (Autonomous Institute of Ministry of Environment & Processes and Landforms, vol. 21, pp. 853-868. Forests, GoI) where he worked earlier and could carry [9] Van Westen, C.J., Soeters, R. and Siimons, K., 2000. out field as well as geospatial assessments. Grateful Digital geomorphological landslide hazard mapping of acknowledgement to Birla Institute of Technology the Alpago area,Italy, JAG, vol. 2 (1), pp. 1-10. (BIT) Mesra for allowing to hold this National Level [10] Dai, F. & Lee, C.F., 2002. Landslides on natural Brainstorming Workshop and as my present terrain: physical characteristics and susceptibility Institution of affiliation for facilitating the Grantsame. mapping in Hong Kong, Mountain Research and support of the Ministry of Earth Sciences, GoI is Development, 22(1), pp. 40-47. gratefully acknowledged. [11] Krishna, A.P., 2000. Landslide management in the REFERENCES Himalayas, Geo Asia-Pacific, June-July issue, pp. 30-32. [1] Valdiya, K.S., 1992. Environmental problems in [12] Krishna, A.P., 1999. Landslide hazard assessment Himalaya: geological aspects, In: Himalayan in parts of Sikkim Himalaya utilizing remote sensing Environment and Development- Problms and techniques, In: Abstract proceeding of 2nd Perspectives, Gyanodaya Prakashan, Nainital, 161 P. International Symposium on Operationalisation of [2] Gupta, K.M., 1990. Himalaya: man and nature, Remote Sensing, 16-20 August 1999, ITC Netherlands Lancers Books, New Delhi, 277 P. and IIRS Dehradun. [3] Starkel, L. & Basu, S.R., 2000. Rains, landslides and [13] Krishna, A.P., 1997. Geologic remote sensing floods in the Darjeeling Himalaya, Indian National applications for landslide hazard assessment in parts th Science Academy, New Delhi, 168 P. of Sikkim Himalaya, India, In: Proc. 12 International Conference and Workshop on Applied Geologic [4] Virdi, N.S., Sah, M.P. and Bartarya, S.K., 1997. Mass Remote Sensing, Denver, Colorado, 17-19 November, wasting, its manifestations, causes and control: some 1997, vol.II, pp. 173-178. case histories from Himachal Himalaya, In: Agarwal, D.K. et al (eds.) Perspectives of mountain risk [14] Pachauri, A.K., 1998. Landslide hazard zonation engineering in the Himalayan region, Gyanodaya methodology for Himalaya: scope of application of Prakashan, Nainital, pp. 111-130. geological data and its integration with GIS and remote sensing, In: Proc. International Workshop- [5] Haigh, M.J., 1984. Landslide evaluation for highway cum-Training Programme on Landslide Hazard and maintenance in the Himalaya, Zeitschriff fur Risk Assessment and Damage Control for Sustainable Geomorphologie, SB 51, 17-37, pp. 80-93. Development, GoI & UNDP, CRRI, New Delhi, 6-11 [6] Krishna, A.P., 2003. Geo-environmental November, pp. 179-185. assessment of landslide hazards in parts of Sikkim [15] Krishna, A.P., 1998. Landslide hazard, Himalaya for mountain risk engineering evaluations vulnerability and risk assessment in parts of the Sikkim using RS and GIS techniques, RESPOND Project Report Himalaya – a GIS based approach, In: Proc. (unpublished), ISRO, DoS, GoI, 108 P. International Workshop-cum-Training Programme on [7] Van Westen, C.J., 1996. GIS in landslide hazard Landslide Hazard and Risk Assessment and Damage mapping, Kakani area, Nepal, Regional training on Control for Sustainable Development, GoI & UNDP, landslide hazard management and control in the CRRI, New Delhi, 6-11 November, pp. 162-168. Hindu-Kush Himalaya, May 14 to June 7, 1996, ICIMOD, Kathmandu, Nepal, 95P. [16] Mehrotra, G.S., Sarkar, S. & Kanungo, D.P., 1997. [25] Krishna, A.P. & Kumar, S., 2013. Landslide hazard Landslide hazard zonation in Garhwal and Sikkim assessment along a mountain highway in the Indian Himalaya. In: Agarwal, D.K. et al (eds.) Perspectives of Himalayan Region (IHR) using remote sensing and mountain risk engineering in the Himalayan region, computational models, Proceedings of SPIE - The Gyanodaya Prakashan, Nainital, pp. 131-142. International Society for Optical Engineering [17 Gupta, P., Anabalagan, R. & Murty, A.V.S.R., 1998. 10/2013; DOI:10.1117/12.2029080. Analytical studies of potentially unstable zones [26] Chang, K., Merghadi, A., Yunus, A.P. et al, identified by landslide hazard zonation (LHZ) mapping 2019. Evaluating scale effects of topographic variables in parts of Tehri-Garhwal Himalaya, India, In: Proc. in landslide susceptibility models using GIS-based International Workshop-cum-Training Programme on machine learning techniques. Sci Rep 9, 12296. Landslide Hazard and Risk Assessment and Damage Control for Sustainable Development, GoI & UNDP, CRRI, New Delhi, 6-11 November, pp. 83-95. [18] Gansser, A., 1964. Geology of the Himalayas, Inter Science Publishers, London, P. 289. [19] Mallet, F.R., 1875. On the geology and mineral resources of the Darjeeling district and western Duars, Mem. Geol. Surv. Ind., vol. 11, pp. 1-50. [20] Gangopadhyay, P.K. & Ray, S.S., 1980. Tectonic framework of the Rangit Window around Namchi, South Sikkim, Him. Geol., vol. 10, pp. 338-352. [21] Raina, V.K., 1976. The Rangit tectonic window – stratigraphy, structure and tectonic interpretation and its bearing on the regional stratigraphy, In: Proc. Him. Geol. Sem., New Delhi, pp. 36-42. [22] Acharya, S.K., 1989. The Daling Group- its nomenclature, tectono-stratigraphy and structural grain: with notes on their possible equivalents, In: Daling group and related rocks, Geol. Surve. Ind., Spl. Pub. No. 22, pp. 5-13. [23] Acharya, S.K., 1976. On the nature of the main boundary fault in the Darjeeling sub-Himalaya, In: Geol. Surv. Ind. Misc. Publ. No. 24 Part-II on recent geological studies in the Himalayas, pp. 395-408. [24] Bhattacharya, U., 1989. A note on the Daling- Darjeeling group of rocks of Sikkim Himalaya with special reference to its rock stratigraphy, sedimentary environment and tectono-metamorphic set-up, In: Daling group and related rocks, Geol. Surve. Ind., Spl. Pub. No. 22, pp. 25-30. Living with landslides: the community’s perspective in Kalimpong

Wg Cdr Praful Rao Nima Doma Lama SaveTheHills (STH) SaveTheHills (STH) Kalimpong Kalimpong

ABSTRACT • The consequences faced by the local residents Landslides are a recurrent phenomenon in the in the aftermath of a landslide event in their Himalaya.It is estimated that 30% of the world’s locality. landslides occur in the Himalaya (GSI Report It is evident that as populations and 1975)1,with their incidence being particularly high in infrastructures increase, social conditions fluctuate the Darjiling and Kalimpong districts of North and the relationship between man and his Bengal.When dealing with sensitive mountain regions, environment becomes more fragile and complex. it becomes apparent that the delicate ecosystem can Thus, it becomes paramount, at the very onset, to often be disturbed by frequent and irreversible acknowledge that the consequences of extreme human interferences. Kalimpong epitomises one such human pressure combined with the natural geological example of a fragile eco-region that is now veering fragility and extreme climatic aberrations make towards this dynamic instability, as a consequence of Kalimpong extremely susceptible to the landslide both natural and human causes. hazard.In a nutshell, the causes of landslides in Kalimpong district of West Bengal is highly Kalimpong can be summarised as: susceptible to the constant threat of landslides and earthquakes. Thus, it figures prominently as a “multi- NATURAL FACTORS hazard zone”. While the occurrence of landslides in Geology Kalimpong is not a recent phenomenon, it can be It is the trends of geological evolution and the noted that understanding the rise of and assessing the rising of the young fold mountains, leading to unstable vulnerability of this hazardous event is a relatively geological structures, tectonic disturbances, and the recent trend. parallel subsidence of the Himalayan foredeep etc The present paper attempts to make a holistic that makes this region so susceptible to landslides. study of landslide hazards in Kalimpongin the context of disruption of life, property, environment and Climate livelihoods, from the perspective of the local The seasonality of the monsoons along with the communityat the grassroot level. orographic factor greatly influences the frequency and Thus, an attempt has been made to provide: occurrence of landslides in Kalimpong. Moreover, the • The physical and geological factors that amount and intensity of rainfall is a major factor in trigger landslides in Kalimpong. triggering landslides in Kalimpong. A very high • The climatic factors. intensity of rainfall within a short span is not • History of landslides in the district. uncommon in the hills of Kalimpong.

• The anthropogenic pressures. ANTHROPOGENIC IMPACT the losses due to these disasters could have been Landuse averted. In order to reduce such casualties effectively The last three decades have witnessed an in the study area, the local communities’ attitudes of unprecedented growth of population in the entire disaster precaution and prevention plays a major role. Darjiling Himalaya and Kalimpong district is no This fact cannot and should not be ignored. Ifthe exception. With increasing population pressure, there perception of risk is understood by the residents of has been a marked change in the landuse patterns of these risk prone zones,effective strategies on the district. An analysis of the landuse change over the protective measures can be designed. Such strategies last 150 years makes it obvious that the forest cover is can then serve as a referencefor local authorities to in a precarious condition primarily due to the rapid prepare any anti-disaster risk strategies. Or else, Hans expansion of settlements, agricultural lands, Reiger has already sounded the alarm: “There is only construction of roads and expansion of urban centres. ONE Himalaya to Lose!” The haphazard and unplanned construction of buildings along with the exponential growth of traffic KEYWORDS multi hazard zone, dynamic instability, local movements, (at least five to seven times more), when community, natural factors, anthropogenic impact, in fact the length and patterns of the arterial roads watershed management have not been upgraded in the last 50 years, is a major cause of slope failures along roadways and yet, not a REFERENCES single study has been made in the Darjiling Himalaya 1. Dikshit, A. and Satyam, N. (2018); Estimations or the hills of Kalimpong, in the context of the carrying of rainfall thresholds for landslides capacity of roads with respect to geology vis-à-vis occurrences in Kalimpong, India, Innovative landslide occurrences in the region. Infrastructure Solutions; 3:24; https://doi.org/10.1007/s41062-018-0132-9, p. 1 Water Management 2. Dikshit, A., Sarkar, R. and Satyam, N. (2018); A major aspect of land use, which has not received Probabilistic approach towards Darjeeling prior attention, is the intensive network of primary, Himalayas landslides – A case study; Cogent secondary and tertiary nalas and jhoras extending Engineering 5; over the district. If pilot projects on watersheds, basin https://doi.org/10.1080/23311916.2018.153 and catchment management are conceived and 7539 “Implemented” – it would undoubtedly create a 3. Lama, N. D. and Lepcha (nee) Lama, I. (2018); controlled drainage system, consequently enabling Assessment of Social Vulnerability of the effective utilization of both water as well as land Community Development Blocks of Darjeeling resources, thereby alleviating the scourge of District, West Bengal, Disaster Management landslides in the district to a large extent. with reference to North Bengal, (ed. Sarkar, The Kalimpong Hills have witnessed an S), North Bengal University, pp. 57-59 increased frequency and severity of landslides in 4. Lepcha (nee) Lama, I. and Pramanik, R. (2014); recent times. These disasters have led to enormous Risk perception and attitudes towards damage of property and lives, both in terms of direct mitigation – A case study of Tindharia, and indirect costs each year. While there is mounting Darjeeling, Living with Hazards (ed. Sarkar. S.), scientific evidence that landslide events are on the rise in the Himalaya, the greater tragedy is that many of ISBN, 978-81-921692-6-2; North Bengal University, pp. 10-14 5. Rao, P. (2010); Landslides Hazards: The dire need for a comprehensive long term solution to the landslide problems at Chibo-Pashyor villages, Kalimpong, District Darjeeling, West Bengal; Geo-hazards in sub Himalayan North Bengal, (ed), ISBN, 978-81-91692-0-0; North Bengal University, pp. 76-82 6. Sarkar, S., (2010); Landslide Hazard in Darjeeling Himalaya, India, Geo-hazards in sub Himalayan North Bengal, (ed), ISBN, 978- 81-91692-0-0; North Bengal University, pp. 1- 3 7. Sinha, B.N., Verma, R.S., And Paul, D.K. (1975); Landslides in Darjeeling District, West Bengal and adjacent areas; Bulleting G.S.I Series B. No. 36 8. Starkel, L. and Basu, S., (2000); Rains Landslides and Floods in the Darjeeling Himalaya, NSA, New Delhi, pp. 12-15 9. http;//savethehills.blogspot.com/

TECHNICAL SESSION – III

FAULT ZONES AND REMOTE SENSING

Chair – Dr. Malay Mukul

Fault Zone Architecture

Vinee Srivastava Department of Earth and Environmental Sciences Indian Institute of Science and Education and Research (IISER) Bhopal, Madhya Pradesh, India [email protected]

ABSTRACT and Mitra, 1993). However, the FRDZ is more widely Tectonically active fold and thrust belts like Himalaya are accepted as fault damage zone especially in brittle fault not only always under seismic threat but also fight zones (Fig.2). continuously with landslide hazards. These regions contain several thrust faults and contemporary activity along them causes the seismic hazard. At thrust sheet- scale (1m-10km), propagation and slip along a fault surface and resultant deformation in the surrounding rocks produces fault zones that can extend for long distances ranging from meters to kilometer scale and can form thick zones with a distinctive geometry (e.g. Figure 1: A schematic diagram of an elastico-frictional Gudmundsson, 2011 and references therein). These are (brittle) thrust fault zone (HW: Fractured Hanging wall; zones of weakness as they consists highly fractured or HWRDZ: Hanging wall damage zone; FWRDZ: Footwall deformed fault zone rocks and several minor faults. related damage zone, FW: Fractured footwall) Slightest seismic activity, incessant rainfall, gravity, soil Fault damage zones can be classified into three main water oversaturation, ground water oversaturation categories based on their position relative to the fault affects the stability of slopes in these zones and can trigger surface : (1) tip damage zone, (2) wall rock damage zone, the landslides. Studying these fault zones in detail are and (3) linking damage zones (Fig 3, Kim et al., 2004; essential to assess the stability of these regions and Peacock et al., 2017). In thrust faults, for example, tip eventually assessing the landslide hazards in tectonically damage zone possess intersected fold axial surface and active regions like the Himalaya. fault tip, en-echelon veins, synthetic and antithetic faults, and horsetail structure (McGrath and Davison, 1995; KEYWORDS Peacock et al., 2017). Wall damage zone consists of Fault Core, Fault Damage Zone, Brittle/elastico-frictional, complex duplex and splays, folds (Boyer and Elliot, 1982; Ductile/Quasi plastic shear zone Perry, 1978; Peacock et al., 2017). 1. Geometry of Fault Zones A typical fault zone consists of a fault core (or a slip zone) with damage zones on either side of it (e.g. Shipton et al., 2006; Mitchell and Faulkner, 2009; Flinn, 1977; Aydin, 1978; Scholz, 1987; Evans, 1990; Cowie and Scholz, 1992; Chester et al., 1993; Caine et al., 1996; Sibson, 2003; Wibberley and Shimamoto, 2003; Kim et al., 2004; Gudmundsson, 2011) (Fig.1&2). The transition between the fault zone and the undeformed hanging wall and Figure 2. A half-a-kilometer fault zone consisting of a well- footwall has also been called the fault related deformation developed fault core and hanging wall damage zone zone (FRDZ) in quasi-plastic fault shear zones (Newman exposed in the Mohand Range, Dehradun Recess reached. Incohesive fault gouge in the core and incohesive (Srivastava et al., 2016). non-foliated fault breccias may form in the fault damage Linking damage zones exhibit folds and extensional zone near the surface (0-5 km) (Fig. 4, Sibson, 1977 ; pull-apart steps (Aydin, 1998) and isolated lens in Marshak and Mitra, 1988). At depths of 5-10 km, non- contractional steps (Nicol et al., 2002) in the linking faults. foliated but cohesive random fabric cataclasite series All fault types (strike-slip, normal, reverse/thrust) produce rocks form and may be classified by their matrix associated fault damage zones. These zones form via the percentage. Ultra-cataclasite with high matrix content initiation, propagation, and interaction of slip along fault (90-100%) represents maximum grain-size reduction that surfaces (e.g. Cowie and Scholz, 1992; McGrath and typically characterizes fault zone cores. Surrounding fault Davison, 1995) that can be modelled as single elastic damage zones are commonly characterized by cataclasite cracks or dislocations in elastico-frictional deformation (50-90%), protocataclasite (10-50%) and micro-, crush-, regime (Gudmundsson, 2011). The development of protobreccia (0-10%) (Sibson, 1977; Marshak and Mitra, different structures within these damage zones provide 1988; Gudmundsson, 2011 and references therein). valuable information about fault development (McGrath and Davison, 1995; Vermilye and Scholz, 1998, 1999), associated fluid flow (Martel and Boger, 1998), and earthquake initiation and termination (King, 1986; Aki, 1989; Thatcher and Bonilla, 1989; Kim et al., 2004).

Figure 4. Characteristic fault rocks of a shear/fault zone as a function of depth (After Sibson, 1977)

2.2. Quasi-plastic or ductile shear zone : Deformation Figure 3. Different types of damage zones (After Peacock mechanism and grain-size reduction in quasi-plastic shear et al., 2017) zones is predominantly governed by crystal-plastic or diffusion processes (Mitra, 1984). Unlike brittle fault zone, 2. Types of Shear zones and Fault zone rocks there is no discontinuity across the ductile shear zone, and There are two types of shear zones namely Elastico- shear strain magnitude varies smoothly across the zone frictional (brittle) shear and Quasi-plastic (ductile) shear (Marshak and Mitra, 1988). Cohesive, foliated mylonite zones. Elastico-frictional (brittle) and/or quasi-plastic series rocks are characteristic of ductile shear zone and (ductile) deformation processes occur via simple or sub- represents medium to high metamorphic grade of rocks simple shear within a fault zone and cause an overall (Fig. 4). Depending on the degree of deformation and reduction in grain-size (e.g. Passchier and Trouw, 2005; matrix proportion from the core to margin of shear zone, Blenkinsop, 2000). Fault zone rocks are classified by their mylonite rock types also vary across the zone. Progressive matrix content, grain size, cohesion, and degree of grain size reduction by dynamic recrystallization is foliation development (e.g. Sibson, 1977). characterized by mylonite (50-90%), augen mylonite (10- 2.1. Elastico-frictional (Brittle) deformation occurs at 50%), protomylonite (0-10%) in the damage zone and shallow crustal levels and generates fractured rocks ultramylonites (90-100%) in the core of ductile shear zone having random fabric (Sibson, 1977). Fault core rocks are (Marshak and Mitra, 1988; Sibson, 1977). highly deformed and crushed with maximum grain-size In summary, to assess the stability of a tectonically reduction. Deformation decreases and grain size increases active region we must know the lithological and structural away from the fault core until intact rock, unaffected by setting of the area. Specifically we need to identify fault the deformation, beyond the fault damage zone is zones because they directly affect the stabilty of the region as presence of highly deformed fault zone rocks University Press. Pp. 594. ISBN: 9780521863926 make the top layers weak and eventually unstable causing [12] Kim, Y. S., Peacock, D. C. P., Sanderson, D. J., 2004. Fault landslides that can affect the population and the damage zones. Journal of Structural Geology 26, 503–517. infrastructure in the region. [13] King, G.C.P., 1986. Speculations on the geometry of the initiation and termination processes of earthquake Acknowledgments rupture and its relation to morphology and geological VS thanks the organizers for the invitation to attend and structure. Pure Applied Geophysics 124, 567-585. be part of the “MOES funded National Brainstorming [14] Marshak, S., Mitra, G.,1988. Basic Methods of Structural session on modelling fault zone induced surface mass Geology, Prentice-Hall. Pp. 446. ISBN-10: 0130651788 transport in the Himalayan orogenic terrains for the [15] Martel, S.J., Boger, W.A., 1998. Geometry and study of Fault related hazards in Himalayan Towns.” BIT mechanics of secondary fracturing around small three- Mesra-Ranchi, March 16-17, 2020. dimensional faults in granitic rock. Journal of Geophysical References Research 103, 21299–21314. [1] Aki, K., 1989. Geometric features of a fault zone related [16] McGrath, A.G., Davison, I., 1995. Damage zone to the nucleation and termination of an earthquake geometry around fault tips. Journal of Structural Geology rupture. United States Geological Survey Open-File Report 17, 1011–1024. 89-315, 1-9. [17] Mitchell, T. M., Faulkner, D. R., 2009. The nature and [2] Aydin, A., 1978. Small faults formed as deformation origin of off-fault damage surrounding strike-slip fault bands in sandstone. Pure and Applied Geophysics 116 (4– zones with a wide Range of displacements: A field study 5), 913–930. from the Atacama fault system, northern Chile. Journal of [3] Aydin, A., 1988. Discontinuities along thrust faults and Structural Geology 31, 802–816. the cleavage duplexes. Geological Society of America, [18] Mitra, G.,1984. Brittle to ductile transition due to large Special Publication 222, 223-232. strains along the White Rock thrust, Wind River [4] Boyer, S.E., Elliott, D., 1982. Thrust systems. American Mountains, Wyoming. Journal of Structural Geology 6, 51- Association of Petroleum Geologists Bulletin. 61. [5] Caine, J. S., Evans, J. P., Forster, C. B., 1996. Fault zone [19] Mukul, M., 2005. Continental Deformation and Global architecture and permeability structure. Geology 24, Positioning System based Geodesy. Himalayan Geology 1125–1128. 26(1), 193-198. [6] Chester, F. M., Evans, J. P., Biegel, R. L., 1993. Internal [20] Newman, J., Mitra, G., 1993. Lateral variations in Structure and Weakening Mechanisms of the San Andreas mylonite zone thickness as influenced by fluid-rock Fault. Journal of Geophysical Research 98, 771–786. interactions, Linville falls fault, North Carolina. Journal of [7] Cowie, P. A., Scholz, C. H., 1992. Physical explanation for Structural Geology 15(7), 849-863. the displacement length relationship of faults, using a [21] Nicol, A., Gillespie, P. A., Childs, C., Walsh, J. J., 2002. post-yield fracture mechanics model. Journal of Structural Relay zones between mesoscopic thrust faults in layered Geology 14, 1133–1148. sedimentary sequences. Journal of Structural Geology 24, [8] Cowie, P. A., Shipton, Z. K., 1998. Fault tip displacement 709-727. gradients and process zone dimensions. Journal of [22] Passchier, C. W., Trouw, R. A. J., 2005. Microtectonics, Structural Geology 20(8), 983–997. Springer-Verlag Berlin Heidelberg. Pp. 366. ISBN -978-3- [9] Evans, J. P., 1990. Thickness displacement relationships 540-64003-5 for fault zones. Journal of Structural Geology 12(8), 1061– [23] Peacock, D.C.P., Dimmen, V., Rotevatn, A., Sanderson, 1065. D.J., 2017. A broader classification of damage zones. [10] Flinn, D., 1977. Transcurrent fault and associated Journal of Structural Geology 102,179-192. cataclasis in Shetland. Journal of the Geological Society of [24] Perry, W. J., 1978. Sequential deformation in the London 133, 231-248. Central Appalachians. American Journal of Science 278, [11] Gudmundsson, A., 2011. Rock Fractures in Geological 518–542. Processes, Cambridge [25] Scholz, C. H., 1987. Wear and gouge formation in brittle faulting. Geology 15 (6), 493–495. [26] Shipton, Z. K., Soden, A. M., Kirkpatrick, J. D., Bright, A. M., Lunn, R. J., 2006. How thick is a fault? Fault displacement-thickness scaling revisited. In: Abercrombie, R., Mcgarr, A., Di Toro, G., Kanamori, H. (Eds.), Radiated Energy and the Physics of Faulting. American Geophysical Union Monograph Series 170, 193-198. [27] Sibson, R. H., 1977. Fault rocks and fault mechanisms. Journal of the Geological Society of London 133, 191-213. [28] Srivastava, V., Mukul, M., Barnes, J.B., 2016. Main Frontal Thrust deformation and topographic growth of the Mohand Range, northwest Himalaya. Journal of Structural Geology 93, 131–148. [29] Thatcher, W., Bonilla, M. G., 1989. Earthquake fault slip estimation from geologic, geodetic and seismologic observations: implications for earthquake mechanics and fault segmentation. USGS Open-File Report 89-315, 386– 399. [30] Vermilye, J. M., Scholz, C. H., 1998. The process zone: a microstructural view of fault growth. Journal of Geophysical Research 103, 12223–12237. [31] Vermilye, J. M., Scholz, C. H., 1999. Fault propagation and segmentation: insight from the microstructural examination of a small fault. Journal of Structural Geology 21, 1623–1636. [32] Wibberley, C. A. J., Shimamoto, T., 2003. Internal structure and permeability of major strike-slip fault zones: the Median Tectonic Line in Mie Prefecture, southwest Japan. Journal of Structural Geology 25(1), 59–78. Remote Sensing technique in detecting surface motion

Kuntala Bhusan Dept of Space North Eastern Space Applications Centre, Govt of India Umiam-793103, Meghalaya [email protected]

ABSTRACT on unmanned aerial vehicle (UAV) as well as ground- Landslide is one of the most common forms of surface based SAR and terrestrial LiDAR placed in front of motion in the hilly terrains under the influence of landslide are also used to study landslide and its gravity. The term "landslide" describes a wide variety kinematics. Multi-temporal LiDAR images can quantify of processes that result in the downward and outward landscape changes caused by an active landslide. movement of slope forming materials composed of While ground based terrestrial laser scanner (TLS) can natural rock, soils, artificial fills or combinations of produce highly accurate 3 dimensional terrain details these materials [1]. The term landslide encompasses of a landslide area within a minute. Different events such as rock falls, topples, slides, spreads, techniques are used for 1) detection and classification creep and flows depending upon the rate and types of of landslides basically to prepare landslide inventory movement. Landslide is one of the widespread and maps, 2) monitoring landslide movement and 3) challenging geohazards worldwide which occurs in the analysis and prediction of slope failure to model mountainous terrains due to combine effect of several landslide susceptibility. However, in most of cases geological factors aided/triggered by rainfall, selection of RS data and technique is determined by earthquake as well as unscientific anthropogenic the scale and purpose of study apart from location, activities. It causes loss of lives and properties almost size, age and exposure condition of existing landslide. every year apart from disrupting communication links While selecting data emphasis is given on resolution and economic losses. Further, the cost of landslide (spatial and temporal), accuracy, swath and revisit damage keeps on increasing drastically as the pace of time of the sensor. SAR data which has ability to work urbanization intensifies on the geologically sensitive under all weather conditions is mostly used in slopes. combination with optical data for operational purpose. This is because SAR data are subject to Diverse air- or space borne remote sensing (RS) data distortion due to topographic affect and flight from active and passive sensors are being used to direction. The same can also be overcome by using study landslide for e.g., synthetic aperture radar both ascending and descending pass data from same (SAR), optical remote sensing data of various spatio- sensor. temporal resolution, light detection and ranging (LiDAR) etc. Very high-resolution imagery (QuickBird, One of the direct and straight forward approaches of IKONOS, CARTOSAT-1and 2) has become the best landslide study is preparation of inventory maps. A option now for landslide mapping and number of landslides inventory map records the location and operational sensors with similar characteristics is where known, the date of occurrence and the types of growing year by year [2]. Importance and limitations mass movement that have left discernable traces in an of various airborne, space borne and ground based RS area [3]. Apart from archive inventory, RS data plays data with varied spatio-temporal resolutions for a very important role in detection and mapping of all landslide mapping and monitoring are demonstrated the four types of geomorphological inventory for e.g., by eminent researchers worldwide. Sensors mounted historical, event, seasonal (figure 1) and multi Optical, SAR, LiDAR data have been well utilized in temporal. landslide research worldwide. Owing to their synoptic view, repetitive coverage, and scale variability RS data N N have evolved as one of the powerful tool to measure, analyze and monitor landslide processes.

KEYWORDS: Landslide, Remote Sensing, SAR, LiDAR

a b ACKNOWLEDGMENTS Author is thankful to the organizer of ‘National Figure 1: Example of a seasonal landslide inventory Brainstorming Workshop’ on Modeling Fault Zone (Resourcesat 1, LISS IV MX data of 2014; a. Pre- Induced Surface Mass Transport in Himalayan monsoon and b. Post-monsoon data) Orogenic Terrains for the Study of Fault Related Hazards in Himalayan Towns for allowing to share the Landslide inventory is a primary requirement for thoughts. The support provided by Director, NESAC to landslide susceptibility, hazard and risk assessment. attend the workshop is duly acknowledged. Identified triggering factor linked with a landslide incidence helps in establishing temporal relationship with the landslide and farther hazard assessment. REFERENCES Modeling of landslide susceptibility in an area is done [1] Varnes, D. J. 1978. Slope movement types and by evaluating the role of various geo-environmental processes. In: Special Report 176: Landslides: parameters as a causative factor of landslide. Usually, Analysis and Control (Eds: Schuster, R. L. & various geo-environmental parameters or factor Krizek, R. J.). Transportation and Road maps, namely, lithology, geomorphology, geological Research Board, National Academy of Science, structure-fault/lineament, landuse-landcover, Washington D. C., 11-33. drainage, soil etc are interpreted from optical RS data [2] Van Westen, C. J., Castellanos, E., Kuriakose, along with limited field checks. While topographic S.L., 2007. Spatial data for landslide parameters, namely, slope amount and aspect are susceptibility, hazard and vulnerability calculated from digital elevation model (DEM) derived assessment: An overview, Engineering either from stereo (optical), SAR data or from freely Geology. available DEM, namely, SRTM, CartoDEM, ASTER DEM [3] Guzzetti, F, Modini, AC, Cardinali, M, Fiorucci, etc of appropriate resolution. Inventory maps F,Santangelo, M, Chang, KT, (2012) Landslide prepared can be used for calculation of weights for the inventory maps: New tools for an old problem. factor maps during landslide susceptibility mapping as Earth Science Review 112, 42-66. well as for validation purpose in prediction modeling [4] Winser, B., Blaikie,P., Cannon, T., and Davis, I and in magnitude and frequency analysis for the 2004. At Risk Natural hazards, people’s hazard mapping. Depending upon the richness of vulnerability and disasters, 2nd ed. Routledge, inventory data, either direct (geomorphological, London, New York, 496. landslide distribution analysis) or indirect (statistical, [5] UNDP, 2004. A Global Report. Reducing knowledge driven, deterministic modeling) Disaster Risk. Challenge for Development, approaches are used for integration of factor maps UNDP, New York. followed by categorization of susceptibility classes. [6] NESAC. 2014. Technical Report and Atlas on Once the hazard map is available, it can be used to Remote Sensing and GIS based inputs for assess landslide risk in an area simply by multiplying hazard risk vulnerability assessment of hazard and vulnerability [4, 5, 6]. However, for this Guwahati city, Silchar,Dibrugarh towns and vulnerability need to be assessed separately for social, Dhemaji district, Assam. Vol I.Conference economic and infrastructure sectors. Name:ACM Woodstock conference

TECHNICAL SESSION – IV

DIGITAL TOPOGRAPHY

Chair – Dr. C. Jeganathan

Digital Topography data and their uncertainties

Manas Mukul School of Computer Applications Kalinga Institute of Industrial Technology Bhubaneshwar Odisha India [email protected]

ABSTRACT SRTM, DEM, Error, Outlier, Accuracy, GPS, GCP, GNSS The freely available global digital elevation data INTRODUCTION consist mainly of C-Band SRTM (Shuttle Radar Topography Mission), ASTER (Advanced Spaceborne The main objective of SRTM was to collect near-global Thermal Emission and Reflection Radiometer) and elevation data with a vertical accuracy of 16m with ALOS (Advanced Land Observing Satellite) digital 90% confidence. The linear error of 16m corresponds elevation models. The SRTM C-Band data in the 90m to a root mean error of ~10m [1], assuming a normal resolution (C90) has been available since 2003 and distribution of errors. The SRTM data were acquired used extensively in many fields of Earth Sciences. The using C-Band and X-Band antennae. The X-Band data C-Band SRTM data in 30m resolution (C30) were have limited coverage due to the lower swath width initially available only for North America. However, of the antenna compared to the C-Band antenna. The since 2016, the C30 SRTM data were released globally C90 SRTM data were available globally at a lower outside North America. SRTM X-Band data is also resolution of 90m. However, the C30 SRTM data were available in 30m resolution (X30) with a much lower also globally available from September 2014 [2]. Given coverage. This study presents the first global the widespread use of the SRTM dataset, an assessment of vertical accuracy of the SRTM data assessment of its accuracy is important. This study using high precision ground control points from the [3,4] uses ground control points from the International GNSS Service (IGS) Network. The IGS International GNSS Service (IGS) Network and control points have a better spread of data across the differential static GPS static stations (Figure 1) to continents than previous studies. The 'as is' SRTM data access the accuracy of SRTM C-Band and X-Band data consisted of ~14% outliers impacting the vertical at both the global and regional scales. The IGS consists accuracy of the SRTM data. On removal of these of a global network of satellite tracking stations that outliers, the accuracy of the SRTM datasets improved deploy dual-frequency GPS receivers in static mode to by over ~20 times to root mean square errors between provide high-quality post-processed point locations 10 - 11.5m, which was close to the SRTM mission goal spread throughout the globe. The elevation data of RMSE ~10m. The results indicate that the regional provided by the IGS stations have a standard error of assessment of SRTM data is essential to understand 16mm. There are 427 such IGS stations spread the vertical accuracy and quoting a LE90 of 16m is throughout the globe for which the SRTM elevation unrealistic. A regional assessment of the SRTM data data is available. The highly accurate point locations of from the Indian subcontinent, including the these stations are the best possible locations of ICPs Himalayas, using differential GPS static stations, also on Earth. Therefore, these points can be used as indicated similar results. The SRTM errors in the Global GCP's whose elevations can be used to assess Higher Himalayas, especially in the void regions, were the quality of SRTM heights. The IGS network data very high. The SRTM errors also increased with were used for the first time to globally assess the increasing elevation and undulating terrain. The SRTM quality of the SRTM product by comparing elevation data contained a systematic error in all the datasets data from the SRTM dataset with the high-quality and filtering the outliers improved the quality of the elevation data available at the IGS stations [3]. The DEMs. results from the IGS stations were compared to the first global assessment study [5] of SRTM, which has KEYWORDS been used as a standard for SRTM vertical accuracy potential coefficient model EGM96 algorithm [3]. The since 2006. For the regional assessment of the Indian X-Band SRTM data were referenced to the WGS84 sub-continent [3], 221 GCPs were obtained using dual- vertical datum and were available as ellipsoidal frequency, differential-static GPS. The stations heights. From the total 427 IGS stations, only 335 IGS consisted of both in the continuous mode and the stationswere considered as the SRTM elevations were campaign mode. either not available for the remaining or the stations were redundant. These 335 IGS stations were used for the global assessment of SRTM data. The statistical analysis of the errors consisted of normality test, outlier analysis and computation of RMSE, mean error, standard deviation, mean absolute error, and standard error. The data sets were also grouped into continents and analyzed separately. For the regional assessment [4] of the Indian sub-continent 221 high precision (5 decimal places) GCPs were obtained from the differential-static GPS survey. The dataset was also separated into Himalayan foreland (elevation <300m), Himalayan foothills (elevation between 300-200m), Higher Himalayan (elevation >2000m) and Peninsular India and analyzed separately. The systematic bias from all the datasets were removed by shifting the pixel values by a magnitude of the mean error. Figure 1: IGS and Static GPSGCP distribution (Mukul et al., 2015; 2016; 2017) RESULTS

METHODOLOGY The results of the statistical analysis of the global 'as is' SRTM data, using IGS stations, indicated high RMSE The 4.1 version C90 data for the study was of 232.6m, 274.5m and 186.5m, for X30, C90, and C30 downloaded from the Consultative Group for data respectively (Table 1). The high RMSE from all International Agriculture Research Consortium for the three datasets were due to the presence of Spatial Information (CGIAR-CSI) website outliers. The X-Band data had 21 outliers, whereas, (http://srtm.csi.cgiar.org) as 5 degree × 5 degree tiles the C90 and C30 data had 44 and 48 outliers in GeoTiff file format whereas the C30 data were respectively. Outliers consisted of ~14% of the data. downloaded using the USGS Earth Explorer Interface On filtering the outliers, the accuracy of all the SRTM (http://earthexplorer.usgs.gov/) in the GeoTiff format datasets improved by over ~20 times. The RMSE of the as 1 degree × 1 degree tiles. The base C90 SRTM data filtered X30 dataset was 11.5m, whereas the RMSE of containing voids were also downloaded from the both C90 and C30 datasets were 10.3m and close to USGS Earth Explorer Interface to study the accuracy of the SRTM mission goal of RMSE ~10m. The results interpolated void heights in the Himalaya. The X30 from the global assessment did not corroborate well SRTM data were obtained from the German with the first assessment of SRTM data carried out in Aerospace Center (DLR) server 2005 [5]. For the regional assessment of SRTM data, (ftp://taurus2.caf.dlr.de/) on the Earth Observation the ‘as is’ RMSE of the X30, C90, and C30 were 9.18m, on the WEB (EOWEB) interface as 0.25 × 0.25-degree 47.24m, and 23.53m, which decreased to 8m, 10.14m tiles. The C-Band SRTM elevations were available as and 14.38 respectively (Figure 2), once the outliers orthogonal heights as they referenced the EGM96 and data in the void region were filtered. The same vertical datum and were converted to the ellipsoidal trend existed in the Higher Himalaya, Himalayan heights by adding the geoid heights using the foreland, Himalayan foothill, and the peninsular India region. The correction of the mean bias further improved the accuracy of the datasets.

CONCLUSIONS

• The ‘as is’ SRTM data does not adhere to the SRTM goal of LE90 16m due to the presence of outliers. • The SRTM data contains regions of no-data of ‘voids’ in the Higher Himalayas. The void filling algorithms are more effective in the C30 dataset when compared to the C90 dataset. • The accuracy of the SRTM data decreases with the increase in elevation and in regions of high Figure 2: Errors from the regions in the Indian sub- undulations. continent (Mukul et al., 2017) • The outlier and void filtered SRTM data comply with the SRTM goal. Bias correction REFERENCES also improves the accuracy of the datasets. [1] Authority TV, 1998. Geospatial Positioning • Overall, the C30 global dataset is more accurate than C90 and should replace the C90 Accuracy Standards Part 3: National Standard for dataset. Spatial Data Accuracy. National Aeronautics and Space Administration: Virginia, NV, USA. [2] Mukul M, Srivastava V and Mukul M, 2016. Table 1: Errors from the global assessment using IGS Accuracy analysis of the 2014–2015 Global Shuttle GCPs (Mukul et al., 2016) Radar Topography mission (SRTM) 1 arc-sec C- Band height model using international Global Navigation Satellite System Service (IGS) network. Journal of Earth System Science. 2016 Jul 1;125(5):909-17. [3] Mukul M, Srivastava V and Mukul M, 2015. Analysis of the accuracy of shuttle radar topography mission (SRTM) height models using international global navigation satellite system service (IGS) network. Journal of Earth System Science. 2015 Aug 1;124(6):1343-57. [4] Mukul M, Srivastava V, Jade S and Mukul M, 2017.

Uncertainties in the shuttle radar topography mission (SRTM) Heights: Insights from the Indian Himalaya and Peninsula. Scientific reports. 2017 Feb 8; 7:41672. [5] Rodriguez E, Morris CS and Belz JE, 2006. A global assessment of the SRTM performance. Photogrammetric Engineering & Remote Sensing. 2006 Mar 1;72(3):249-60. Unmanned Aerial Vehicles and Ultra Resolution Remote Sensing: Application Potentials in Mass Movement Studies

Ramakrishnan Desikan Department of Earth Sciences Indian Institute of Technology Powai, Mumbai - 400076 [email protected]

ABSTRACT This necessitates monitoring of vulnerable slopes for Ultra high resolution remote sensing using the potential risk and its likely stability for any emerging technology of a drone platform is of interventions. Frequent monitoring of the slopes immense use in landslide hazard related mitigation requires measurements ranging from point detail to and management. This technique is superior to both spatial scales and accordingly deployment of varied satellite data based and field based approaches in techniques and associated instrumentations. landslide study as it permits rapid and easily updatable In order to observe the evolution of the landslide by high resolution data acquisitions and hence, improves analyzing the kinematics of the movement, very often the capabilities of detection, mapping and monitoring. the measurement of the superficial displacements UAV based remote sensing can be effectively used to (i.e., deformation mapping or monitoring of a generate very accurate primary and derived spatial landslide) is necessary. However, large variations in maps of very high resolution (1:100) pertinent to geomorphological, geological, geo-mechanical, and landslide such as displacement rate, topography, land geotechnical conditions hamper any tailor made use, geology, slope, aspect etc. Combination of visible technique and associated instrumentation in and IR sensors on-board an UAV enable a broad range understanding the kinematics and related kinetics. of applications with a far higher degree of detail and Typical techniques and tools used in kinematics accuracy than satellite data, and higher efficiency and analysis of landslide includes: spatial completeness than methods employing classic (1) ground-based geodetic techniques, e.g., electronic geodetic measurements. The time series data over a theodolites, electronic distance measurement, dual landslide not only permit the measurement of the frequency instruments, three-dimensional positioning displacement vectors of a landslide but also facilitate systems, automatic levels, digital levels, zenith angle Stress Distribution Modelling & Kinematic Analysis of methods, and total station instruments; slopes. (2) satellite based geodetic techniques, e.g., global positioning systems (GPS) and real-time kinematics

(RTK) GPS); Introduction (3) geotechnical techniques, e.g., extensometers, Understanding mass movement and its mechanisms is inclinometers, piezometers, strain meters, pressure very important in landslide hazards mitigation and cells, geophones, tilt meters, and crack meters; and management. The most important aspect of landslide (4) high resolution remote sensing techniques hazard reduction not only depends on spatio- involving imaging in optical (including laser) and temporal information about frequency and microwave regions from ground-aerial and satellite distribution of landslides, and of their predisposing platforms. and triggering factors, but also on the quantification In this presentation, the advantages of ultra- and understanding of landslide kinematics and the resolution optical (visible and thermal) imaging underlying mechanical processes (Esker et al., 2018). onboard Unmanned Aerial Vehicles (UAV) and supported field based measurements (DGPS) in estimating the landslide displacement vectors and evolving a generic spatial model in mitigating the hazard was discussed using the following primary and derived spatial data: Primary Data Products • Ultra high resolution 2D Mosaics • Ortho-corrected Aerial Photos • Ultra high Resolution Digital Surface Models (DSM) • High Resolution (vertical Accuracy < 20cm) Point clouds and Digital Elevation Model • Topography corrected, high Resolution Landuse/Landcover Maps • Time series data • Surface and Subsurface Anomalies

Derived Products • Estimation of Displacement vectors • Surface Deformation & Changes (Fracture, Landuse, topography) • Slope Map Conclusions • Aspect Map For efficiently arresting the potential and active • Fracture/Fault/ Joint Map (Lineament landslides, it is necessary to map and understand the kinematics at ultra high resolution. This often requires Map?) generation of operational scale maps in 1:50 to 1:100 • Soil Moisture & Fracture Moisture scales. Time series maps on such scale are not possible changes using satellite images and it is very cumbersome to • Estimation volume and tonnage of generate using field based techniques. Further, field slipped /potentially slipping rock/soil based data generation is discrete and involves mass extrapolation. Under these circumstances, time lapse deformation mapping using UAV is extremely useful in Methodology generating precise spatial details on displacement The proposed methodology includes (Figure1) vectors and potential plane of failures. This in turn can 1. Data Acquisition – Time series data acquisition from help in estimating the volume of rock mass likely to field and drone platforms & their processing to move and evolve suitable restraining/ mucking understand the kinematics and related kinetics techniques. Thus the UAV based remote sensing can 2. Evolving a generic model be of immense use in evolving practical solutions for

landslide mitigation and management.

REFERENCES [1] Esker,R., Aydm, A. and Hubt, J. (2018) Unmanned aerial vehicle (UAV)-based monitoring of a landslide: Gallenzerkogel landslide (Ybbs-Lower Austria) case study, Environ Monitoring and Assessment (2018) 190: 28.

TECHNICAL SESSION – V

TECTONIC GEOMORPHOLOGY

Chair – Dr. Malay Mukul

Tectonic Geomorphology signatures and drainage characteristics in fault zones

Vimal Singh Department of Geology University of Delhi, Delhi [email protected]

ABSTRACT Identification of faults is one of the key aspects in In past three decades, tectonic geomorphology has Tectonic Geomorphology. Active faults give rise to become the focus of most of the earth surface process different types of landforms, such as fault scarps, studies. Identification of active faults forms an tilted or folded surfaces/terraces, strath terraces, important part of such studies because it can help in river offsets, subsidence features etc., and each type predicting the predominant processes in these areas. of fault can give rise to a specific assemblage of Geologists have used various geomorphic markers to landforms [1]. Thus, tectonic geomorphologists have identify the fault zones, out of which rivers are very found certain geomorphic features useful for the significant because they are very sensitive and can identification of active faults or deformation in a react to any small change in their system. region; these geomorphic features are known as Rivers can be used to identify fault zones in various geomorphic markers [2]. Geomorphic markers are ways including investigation of their longitudinal identifiable geomorphic features that can act as a profiles, channel morphology, and landform reference against which changes related to associations around them. The vertical adjustment of deformation can be gauged. In general, they have the rivers to changes in baselevel have profound known geometry and high preservation potential [2]. impact on the hillslope processes and since, the rivers They include fault scarps, topographic breaks, river react strongly to the extreme events, it is important to terraces (unpaired, tilted, warped, or truncated), knick understand the connectivity of a river with the points (developed due to sudden change in slope of adjacent hill slopes. It provides crucial information the river), lacustrine shorelines, linear features like about the earth surface processes active in the region ridges, rivers etc. of fault zone during the extreme event. 2. Rivers as geomorphic markers KEYWORDS The morphology and other characteristics of a river Tectonic geomorphology, geomorphic marker, river depends upon several parameters viz, discharge, profile, river response. slope, sediment load, sediment size, channel bed material, bank stability, and vegetation. The fact that 1. Introduction a river’s flow and characteristics depends on the intricate balance between these parameters, makes Tectonics is one of the primary driving forces in the them very sensitive to any kind of changes in the river development of landscape. Investigation of the link system [1]. A river can manifest changes in several between the landforms and tectonics has given rise to ways. For example, a river can change from straight to the field of ‘Tectonic Geomorphology’ in which we are meandering due to change in slope, or it can change either concerned with the landforms produced by the from meandering to braided due to changes in slope tectonic processes or apply geomorphic principles to solve a tectonic problem [1]. and sediment load. A river can be analyzed for decreases and the river reacts by dropping its changes in its morphology or slope as well. sediment. On the other hand, if the slope increases in the downstream part and disturbs the steady-state of River profiles have been used widely in the field of the river, it starts to meander and increases its length Tectonic Geomorphology for identification of faults or so that the slope is maintained. Apart from the deformation. It can be investigated in several ways, changes in the morphological characteristics, rivers viz., longitudinal stream profile, Hack profile, Stream- also give rise to certain landforms in the area of Length gradient index (SL index), Steepness index deformation. For example, terraces develop where (Ksn), and Chi analysis. The longitudinal profile of a the river crosses the uplift axis and unpaired terraces river is the oldest technique used to investigate a develop in the areas experiencing tilting. river, in which change in a river slope can be visualized. However, in large river systems, the rivers It is now known that the behaviour of a river, i.e., often operate on a slope of 1/100th of degree and a aggradation and incision, depends up on the small change on that slope would not be possible concentration of the sediments in the water column through qualitative analysis. Therefore, Hack [3] of the river segment such that increased sediment suggested drawing the river profile on a semi- concentration leads to aggradation, and decreased logarithmic scale such that distance is plotted on the sediment concentration results in incision. Thus, logarithmic scale; this analysis highlighted any processes like landslides cause an increase in the changes along the river. Also, a geomorphic indices sediment concentration of a river and often, we called Stream Length (SL) index was identified to encounter braided rivers close to the landslide zones. quantitatively assess the river profile, with sudden high or low values indicating anomalies [3]. Later, Further, the width of a river can also be used to assess development of high speed computing and availability the change in the river processes. In mountainous of the digital topography, facilitated time-efficient region, the rivers mostly flow over bedrock and in such analysis of the profiles and also, led to the areas the bank stability is the function of erodibility of development of morphometric parameters like the rock. It is observed that the presence of faults also Steepness index and Chi values. Such indices helped in controls the bank stability because the intense visualizing the potential interactions and sensitivity of fracturing and pulverisation of rocks in the fault zones the terrain. make them more erodible, as a result, the rivers are relatively wider in such zones. Moreover, the faulting Morphological changes in the rivers also helps in the also leads to the development of landslides that identification of underlying processes in several cases. increase the sediment concentration in the fault zone, Through flume experiments it has been shown that a thus facilitating aggradation. rivers sinuosity changes with the slope and the threshold values at which they change vary for the 3. Connectivity rivers with different sediment load [4]. Experiments In general, most of the natural hazard investigations have also shown that a river responds to the uplift, are carried out in isolation which hinders our ability to subsidence and tilting by means of changing its develop a holistic spatio-temporal understanding of morphology [5]. For example, a river crossing an the earth surface processes. In context of fluvial uplifting area would become braided in the upstream system, connectivity is defined as the exchange of and meandering in the downstream, of the uplift axis. water, sediment, and biota between different This occurs because when the slope upstream of the components of the river landscape [6]. The physical uplift axis decreases, the carrying capacity of the river contact between the components is termed as the structural connectivity and transfer of material the Fig.1: Diagram showing the change in connectivity functional connectivity [7]. Based on the structural during normal event and extreme event. and functional connectivities four types of connectivities have been identified - a) actively connected system, b) Inactive connected system, c) REFERENCES partially active connected system, and d) [1] Edward A. Keller, and Nicholas Pinter. 2002. Active disconnected system [7]. In mountainous terrains, the Tectonics - Earthquakes, Uplift, and Landscape. rivers are in general disconnected with the hill slopes Prenti ce Hall, New Jersey, US. during low discharge conditions, whereas, during high [2] Douglas W. Burbank, and Robert S. Anderson. discharge conditions these two components (viz., river 2012. Tectonic Geomorphology. Wiley-Blackwell, and hill slopes) get connected. However, there can be West Sussex, UK. several river segments in which these two [3] J. T. Hack. 1973. Stream-profile analysis and components could still be disconnected. In such stream-gradient indices. United Geological Survey segments, the two components may get connected Journal of Research, 1, 421-429. during the extreme events (Fig. 1), thereby facilitating [4] Stanley A. Schumm and H.R. Khan. 1972. the functional connectivity. During extreme events, Experimental study of channel patterns. Geological the rivers and the hill slopes get strongly connected Society of America Bulletin, 83, 1755-1770. and move enormous volume of sediment that results [5] Shunji Ouchi. 1985. Response of alluvial river to in the change of the functional and morphological slow active tectonic movement. Geological Society characteristics of the river. Investigations of the rivers of America Bulletin, 96, 504-515. can help in predicting the changes that a river can [6] Paul Blanton and W. Andrew Marcus. 2009. experience due to extreme event [8]. Therefore, earth Railroads, roads and lateral disconnection in the surface processes should also be investigated from river landscapes of the continental United States. the connectivity perspective. Geomorphology, 112, 212-227.

[7] Vikrant Jain, and Sampat K. Tandon. 2009.

Conceptual assessment of (dis)connectivity and its

application to the Ganga River dispersal system.

Geomorphology, 118, 349-358.

[8] Rahul Devrani, Vimal Singh, Simon M. Mudd, and Hugh D. Sinclair. 2015. Prediction of flash-flood hazard impact from Himalayan River profile. Geophysical Research Letters, 42(14), 5888-5894.

Uncertainties in Geomorphic Indices and Fault Zones identification

Manas Mukul School of Computer Applications Kalinga Institute of Industrial Technology, Bhubaneshwar, Odisha [email protected]

ABSTRACT having fault gouge were low compared to the high The Shuttle Radar Topography Mission (SRTM) data resistant rocks across the MT and MCT sheets. High SL has been used extensively for computing geomorphic index values in a fault zone containing low resistant indices to study the evolution of topography, rocks signify neotectonic activity. The uncertainty of landscape, and neotectonics without considering the the SL indices from the Gorubathan sub-basins also uncertainties. This study computes the uncertainties increased with the channel length. The variations in of the corrected SRTM data using Real-Time Kinematic the SL values were difficult to recognize beyond the (RTK) Global Positioning System (GPS) ground control channel length of 20 kms. points (GCP) and investigates its impact on the KEYWORDS: Uncertainties, Geomorphic Indices, normalized, unnormalized, dimensional, and non- Stream Length Gradient Index, RTK, GPS, DEM, SRTM dimensional geomorphic indices from the Relli river basin and the sub-basins of the Gorubathan region of India. The results indicate the SRTM 30 m resolution INTRODUCTION data were significantly more accurate than the SRTM

90 m resolution data. The normalized and non- The availability of global digital elevation data gives an dimensional geomorphic indices such as the relief opportunity to quantitatively study the Earth’s ratio (Rh), hypsometric integral (HI), basin elongation landscape, which is shaped by the interaction (Re), and valley floor width-to-height ratio (Vf) are between topography building and topography statistically indistinguishable within (1σ) uncertainty reducing processes. The computation of geomorphic when computed using SRTM 30 m and SRTM 90 m indices from the SRTM data has helped quantitative resolution data. However, the stream length gradient tectonic geomorphology become an important index (SL), is not nondimensional and is sensitive to discipline in studying the evolution of SRTM height uncertainty that is directly proportional topography. The SRTM 90 m resolution data has been to the longitudinal channel length. Therefore, widely used to compute the geomorphic indices for knickpoints identified using SL index from longitudinal geomorphological studies without taking into account profiles of rivers must be examined for statistical the accuracy of the data. Consequently, the significance. From the Relli River basin, three knick- uncertainties associated with the geomorphic indices points were identified out of which two were were unknown. The SRTM ‘as is’ data contain large statistically insignificant with high uncertainties. The errors as the accuracy of the SRTM data is adversely statistically significant knick-point indicated the effected in higher elevation regions, densely reactivation of the Munsiari Thrust (MT) /MCT2 fault vegetated regions and regions of voids. All these zone by out-of-sequence neotectonics. The result factors are likely to introduce uncertainties in the from the Gorubathan basins indicated that geomorphic indices computed from the SRTM data. In deformation in the Gorubathan recess had generated this study, we first assess the accuracy of 90 m, 30 m an active, but mature landscape. The signatures of and corrected 30 m SRTM data using GCPs acquired active deformations were preserved in the middle of through RTK GPS survey and subsequently use it for the fan surfaces away from the river valleys. The SL computing the geomorphic indices [1, 2]. Using the index values across the Gish Transverse fault zone uncertainties of the three SRTM datasets, we next compute the uncertainties associated with the typically used to identify neotectonics in river basins. geomorphic indices in the Relli River basin and The uncertainties of the indices were also computed Gorubathan sub-basins by error propagation (Figure by applying the basic principles of the propagation of 1). We then use the results to study the neotectonics uncertainties [6]. The vertical uncertainty of the DEM in the Relli basin and the Gorubathan sub-basins. was obtained from the results of the elevation error analysis, whereas the horizontal uncertainty of 8.8 m was used from the literature for Eurasia [3].

RESULTS

The results from the accuracy assessment of the SRTM 90 m, 30 m, and corrected 15 m DEMs indicated the 15 m DEM to be the most accurate with RMSE of 5.88 m and 4.43 m for Relli and Gorubathan regions, Figure 1: Location of the Relli basin and the respectively. The 90 m SRTM DEM with RMSE greater Gorubathan sub-basins [1, 2] than 10 m was the least accurate. The uncertainties of the normalized and non-dimensional indices (Relief METHODOLOGY Ratio, Drainage Basin Asymmetry, Basin Elongation Ratio, Hypsometric Integral, and Valley floor width-to- We downloaded the 90 m and 30 m SRTM raster data height ratio) did not impact the result of the indices. from the CGAIR and USGS websites in the GeoTiff file However, the uncertainties of the stream length format and clipped them to our study region. To gradient index, which is non-normalized and a assess the SRTM vertical accuracy, GCPs were dimensional index, increased with the increase in the obtained by RTK GPS field surveys. We used 119 and channel length. The uncertainties of the SL index from 941 GCPs to assess the uncertainty of the SRTM data the Relli basin ranged between 13 - 350 m, 5 - 135 m, in the Relli basin and Gorubathan sub-basins and 5 -104 m for SRTM 90 m, 30 m, and corrected 15 respectively. These locations were measured on m data, respectively (Table 1). Three anomalous SL accessible paths following the standard methodology index values known as knickpoints were obtained [3]. The elevations of multiple GCPs within a single 90 from the Relli basin (A, B, and C). However, the m or 30 m pixel were averaged out to avoid knickpoints at B and C were statistically insignificant redundancy. The errors obtained for the SRTM 90 m due to high uncertainties. and 30 m data were subjected to statistical analysis to compute the uncertainty of the ‘as is’ SRTM DEM. The errors were further analyzed to identify outliers [4, 5].

The outlier filtered dataset was also used to re- compute the uncertainty of the filtered DEM. We further corrected the 30 m SRTM data by re-sampling to a higher 15 m resolution and removing the mean error bias obtained from the statistical analysis of the re-sampled data using the GCPs. Using the 90 m, 30 m, and corrected 15 m SRTM DEMs, the Relli River basin was delineated. However, for the 31 Gorubathan sub- basins only 30 m and corrected 15 m SRTM DEM were used. The delineated watersheds were used to compute and compare the geomorphic indices Table 1: Stream Length Gradient Index from the Relli basin [1] Channel No C90 SL (m) C30 SL (m) C15 SL (m) Length (km) 226.14 ± 1 2.5 230.07 ± 5.36 230.51 ± 4.16 13.90 392.18 ± 391.59 ± 2 5 390.26 ± 12.50 41.81 16.12 521.27 ± 521.69 ± 3 7.5 474.10 ± 20.77 69.43 26.77 865.57 ± 898.32 ± 4 10 (Point A) 883.93 ± 29.11 97.35 37.53 547.40 ± 537.40 ± 5 12.5 535.46 ± 37.13 124.14 47.86 523.74 ± 524.99 ± 6 15 527.43 ± 45.81 153.16 59.05 Figure 2: Longitudinal profiles with stream gradient 508.41 ± 490.47 ± 7 17.5 489.02 ± 53.92 index values from the sub basins falling in the Gish 180.27 69.50 Transverse Zone [2] 499.34 ± 523.06 ± 8 20 501.88 ± 62.50 208.98 80.57 518.30 ± 586.84 ± 9 22.5 473.85 ± 70.21 CONCLUSIONS 234.75 90.51 928.82 ± 874.26 ± 10 25 (Point B) 868.78 ± 79.61 • The vertical uncertainty of the 30 m SRTM 266.19 102.63 27.5 (Point 822.95 ± 721.57 ± DEM is the lowest and can be further reduced 11 710.18 ± 87.45 C) 292.39 112.73 by correcting the DEM using resampling and 676.43 ± 621.67 ± 12 30 593.22 ± 97.05 mean bias correction. 324.50 125.11 682.29 ± 625.32 ± 488.13 ± 13 32.5 347.30 133.90 103.87 • The uncertainties of normalized and non- dimensional indices do not impact the result The results from the study of uncertainties of indices of the indices. from the Gorubathan region and the Relli Basin were consistent. The uncertainties of the normalized and • The stream length gradient index is a very non-dimensional indices did not impact the result, effective tool to identify tectonic deformation whereas, the uncertainty of the SL index increased or lithological variations. downstream and was very high for any statistical significance beyond the channel length of 20 kms.The • The SL gradient analysis is significant only for knickpoints obtained from the sub-basins were smaller streams as the uncertainty of the SL mapped against the major faults (Gish Transverse values is directly proportional to the stream Zone, Munsiari thrust, Main Boundary thrust, length. Ramgarh thrust, Main Frontal thrust) in the sub-basins REFERENCES and analyzed (Figure 2). The SL values across the Gish

Transverse Zone were low in the range between 35 - [1] Mukul M, Srivastava V and Mukul M, 1997. Out-of- 623 m (Figure 2). The MT and MCT sheets contained sequence reactivation of the Munsiari thrust in the high SL values with the highest SL value of 3334 in the Relli River basin, Darjiling Himalaya, India: Insights MCT sheet consisting of highly resistant High-grade from Shuttle Radar Topography Mission digital gneisses in the Jaldhaka River basin. elevation model-based geomorphic indices. Geomorphology. 2017 May 1; 284:229-37. [2] Srivastava V, Mukul M and Mukul M, 2017. Quaternary deformation in the Gorubathan recess: Insights on the structural and landscape evolution in the frontal Darjiling Himalaya. Quaternary International. 2017 Dec 30; 462:138-61. [3] Rodriguez E, Morris CS and Belz JE, 2006. A global assessment of the SRTM performance. Photogrammetric Engineering & Remote Sensing. 2006 Mar 1; 72(3):249-60. [4] Mukul M, Srivastava V and Mukul M, 2016. Accuracy analysis of the 2014–2015 Global Shuttle Radar Topography mission (SRTM) 1 arc-sec C- Band height model using international Global Navigation Satellite System Service (IGS) network. Journal of Earth System Science. 2016 Jul 1; 125 (5):909-17. [5] Mukul M, Srivastava V and Mukul M, 2015. Analysis of the accuracy of shuttle radar topography mission (SRTM) height models using international global navigation satellite system service (IGS) network. Journal of Earth System Science. 2015 Aug 1; 124 (6):1343-57. [6] Taylor J, 1997. Introduction to error analysis, the study of uncertainties in physical measurements. 1997 Aug.

TECHNICAL SESSION – VI

GNSS DATA AND MODELLING OF SLOPE STABILITY

Chair – Dr. Purba Joshi

GNSS based Landslide Hazard

Sridevi Jade Chief Scientist, CSIR-4PI (Formerly CSIR-CMMACS), Bangalore-560037

[email protected]

300m and relative positioning static (mm INTRODUCTION accuracy)and kinematic (cm accuracy) for baseline length of 3000m. The methodology used for these Precise Positioning using Global Navigation Satellite positioning strategies are different with advantages System (GNSS) is used an as important tool for surface and disadvantages based on the application and deformation studies with millimeter level accuracy accuracy requirements. aiding in natural hazard assessment e.g earthquake, landslides, cloudbursts etc…(Figure 1). GNSS GNSS Studies comprises of currently operational global (GPS, Glonass, Galileo, Beidou) and regional ( QZSS, Navic) satellite systems, augmentation systems, space GPS/GN Geology/Tectonics Seismology segment, ground infrastructure and GNSS receivers. Currently only Global Positioning System(GPS) of United States of America and Glonass of Russia are Tropospher Crustal Velocity fully operational and the rest are in different phases e & Indian reference of operation. Position of any point on the earth’s frame surface is determined by measuring the distance Stress-strain between the satellite and the receiver on the ground Precipitable Total Electron Content which is defined as Range i.e travel time of GPS signal Water Vapor (PWV) (TEC) times the speed of light. Since the associated errors Landslide Studies of the GPS system (satellite orbit and clock errors, Earthquake troposphere and ionosphere delay of the signal, Extreme Rainfall Hazard Cloudburst multipath, receiver noise and receiver clock error) are required to be resolved to get the exact range and Natural Hazards hence the measured range is termed as Psuedorange.

GPS observables are defined as Code and Phase Figure 1: Flowchart for GNSS based Natural Hazard studies Psuedorange depending whether the measured range is obtained using the code or phase of the LANDSLIDE DEFORMATION USING GNSS- A CASE transmitted GPS signal. Position is obtained from GPS STUDY observables after elimination/reducing the associated errors using point positioning (static & kinematic) with In the past two decades GNSS technology [1, 2] is meter level accuracy, differential positioning being widely used for landslide hazard mapping [3, 4] kinematic with cm level accuracy within a radius of and to monitor deformation of active landslides to sub cm accuracy [5, 6] both as a complement and an analysis center in real time and processed to give near alternative to the traditional surveying . The real time surface deformation. This requires setting up advantage of GNSS technology is its ability to provide of a continuous ( 24X 7) GNSS network and a economical, all weather precise near real time dedicated analysis center. In the static/post deformation measurements which can be integrated processing mode position of campaign and base with Terrestrial Laser Scanner (TLS) measurements stations needs to be measured 2 to 3 days periodically and GIS maps to generate landslide hazard maps.. to monitor the landslide movement. GNSS position measurements are typically made either in continuous mode (24 hrs a day for 365 days A case study of two active landslides in seismically a year), in campaign mode ( 2 -3 days for 2 to 3 times active Gharwal Himalayas of Uttarakhand region, a year) and kinematic mode (single day located in Pipalkoti on national highway from Chamoli measurements repeated 2 to 3 times a year). These to Badrinath along the river Alaknanda is detailed here measurements over a period of time give precise (Figure2). To monitor these landslides reference GPS surface velocities of GNSS points in static, kinematic station (LSLI) is installed in a relatively stable region and real time kinematic mode (RTK). This information within aerial distance of 1 km from landslides and can be used to develop three dimensional dynamical campaign GPS points are installed in the landslide 1 models for landslides and to generate strain maps for and landslide 2 respectively (Figure 2) to measure the landslide hazard assessment. displacement solely due to landslide motion. GPS data at landslide points [5, 6] is collected at a regular For landslide hazard mapping of 100-500 sq km , a interval of 3 months for a period of 4 years. GPS data few continuous GNSS stations are established within is processed using GAMIT-GLOBK software [7, 8] to this region where there are no landslide related calculate the relative landslide motion in cm w.r.t movements to serve as base stations. A dense reference station and also strain rates (Ɛ ) in each campaign network in the region is established and landslide (Figure 2). GNSS campaign measurements are carried out every 3 to 6 months for 2 to 3 days. GNSS data thus collected is analysed in post processing mode to determine surface GNSS velocities in the region for a period of 1- 3 years. Strain maps for this region are generated using the precise GNSS velocities which help in delineating the active, critical and subcritical landslides.

Monitoring surface deformation of a specific active landslide in near real time and post processing mode requires establishment of continuous and campaign network spatially covering the landslide with a base station located outside the landslide deformation zone. The continuous network gives the deformation in near real time and the campaign network gives the deformation in post processing mode. For near real time monitoring of a active landslide GNSS data from the continuous network need to transferred to the selection of network points for GNSS continuous and campaign measurements, factors/variables like rock type, slope angle, precipitation, drainage, tectonic features, seismic activity, extent of urbanization, surface deformation etc.. effecting the landslide activity in the region, deformation analysis and interpretation of results. There is a urgent need to focus on such integrated study to develop complete, comprehensive realistic landslide hazard assessment models for high landslide risk areas.

Since Himalayas have high seismic activity, the hilly towns have a danger of being hit by earthquakes and multiple seismically induced landslides. In addition to these, towns are prone to landslides that result from processes that result out of climatic, geomorphologic or anthropogenic factors as well as human settlements. These call for an entirely new, town- specific landslide hazard assessment to make

landslide hazard assessment and mitigation realistic and to take it to a level where the information can be Figure 2: GPS monitoring of active landslides –a case study used for decision making and operation issues related to town-planning in the Himalayan regions. The SUMMARY integrated modelling approach detailed above can be

used for the landslide hazard assessment of these GNSS measured displacement as detailed above is towns. This would require a rare combination of integrated with the geology, geomorphology and modeling skills and individual expertise in GNSS geotechnical information of the region to identify the geodesy, geology and geotechnical areas and would old, stable and active landslides in the region. In make a difference in developing a realistic landslide addition, GNSS derived deformation can be integrated hazard assessment methodology and model. This with satellite images of the study area to give would go a long way in saving loss to property and complete picture of spatio-temporal landslide related lives due to landslides in the urban settlements in deformation in the region. Based on this presently Himalayan region if these hazard maps are used for active landslides in the region should be earmarked location of these settlements and identified design for specific monitoring using digital terrian images, procedures. satellite images, TLS and GNSS measurements covering the entire surface of landslide to provide ACKNOWLEDGEMENTS deformation data in a continuous spatial-temporal My thanks to Mr. T.S. Shurngeshwara for replotting domain. The real big challenge is to integrate and the figures to suit the extended abstract. I model all this data both qualitatively and acknowledge the support of Head, CSIR-4PI for the quantitatively and assess the landslide hazard in a GNSS Programme. more realistic manner. This requires expertise in GNSS geodesy, geology, geophysics and geotech right from REFERENCES

[1] Wang G, Philips D, Joyce J and Rivera F. O., 2011. The Integration of TLS and Continuous GPS to Study Landslide Deformation: A Case Study in Puerto Rico, Journal of Geodetic Science, 1(1), 25- 34 DOI: 10.2478/v10156-010-0004-5. [2] Gili, Josep A., Jordi Corominas, Joan Rius, 2000. Using Global Positioning System techniques in landslide monitoring. International Journal of Engineering Geology (Elsevier). Vol. 55, pp. 167– 192 . [3] Shantanu Sarkar, Debi Prasanna Kanungo & Shaifaly Sharma, 2013. Landslide hazard assessment in the upper Alaknanda valley of Indian Himalayas. Geomatics, Natural Hazards and Risk. DOI: 10.1080/19475705.2013.847501. [4] Sridevi Jade and Sarkar. S,1993. Statistical Models for slope instability Classification. International Journal of Engineering Geology (Elsevier), No 36(1), 91-98. [5] Shrungeshwara T S, Chiranjeevi Vivek G, Pavithra N R, Anil Kumar M, Neelu Sharma, Shantanu Sarkar & Sridevi Jade, 2015. Landslide Deformation Studies in Uttarakhand, India. CSIR-4PI Technical Report. TR-CM-1501. [6] Shrungeshwara T S, Chiranjeevi Vivek G, Anil Kumar Maletha, Shantanu Sarkar, Sridevi Jade, Landslides studies using Global Positioning System (GPS), 2018. Sustainable development of natural resources, R.K. Books, New Delhi, ISBN: 978-93- 82847-243. [7] T. A. Herring, R. W. King, M. A. Floyd, S. C. McClusky, 2015. GAMIT Reference Manual, GPS Analysis at MIT, Release 10.6 . [8] T. A. Herring, M. A. Floyd, R. W. King, S. C. McClusky, 2015. GLOBK Reference Manual, Global Kalman filter VLBI and GPS analysis program, Release 10.6.

Internet of Things System for Real-Time Monitoring and Early Warning of Landslides

Maneesha Vinodini Ramesh Amrita Center for Wireless Networks & Applications Amrita School of Engineering, Amritapuri Amrita Vishwa Vidyapeetham, India [email protected]

ABSTRACT use of Internet of Things (IoT) and machine learning Restraining from disasters like landslides, earthquake (ML) techniques. An IoT based landslide monitoring are unfeasible, however their potential impact on and early warning system is designed, developed and humans, livestock and property can be limited. In this deployed in landslide prone terrains of Western Ghats paper, we have briefed on Internet of Things (IoT) and North Eastern Himalayas, India. The IoT system is based landslide monitoring system and the designed for continuous data collection and application of data analytics and machine learning monitoring of vital parameters of landslides, from techniques for early warning. hostile, resource constrained landslide prone areas. Machine learning algorithms and artificial intelligence KEYWORDS based decision models are integrated to develop IoT, Landslides, Monitoring, Early warning thresholds for heterogeneous sensor systems, and utilizing its results along with weather forecast to develop an efficient and reliable landslide early 1 Introduction warning. Landslides are catastrophic events with direct impact on the socio-economic systems of the affected community. David Petley’s dataset on landslide 2 IoT system for Landslide Early Warning fatality provides insight into the statistics and the trend of landslides [6]. As per Petleys dataset, a total We have designed & deployed IoT system for landslide of 40,123 non-seismically triggered landslides were monitoring and early warning which integrates recorded in a span of ten years from 2002 to 2013. monitoring of multiple parameters [5], [6]. The system Also a linearly increasing trend of the number of is deployed in two locations: Anthoniar Colony, landslide fatalities are seen over years. Landslide is a Munnar, Kerala and Chandmari, Gangtok, Sikkim, complex phenomenon involving many causative India, due to their high susceptibility to landslides. In parameters including rainfall. Monitoring one vital each of these locations, we have installed multiples parameter related to landslide will not suffice the sensors to measure the following parameters: 1) need of forecasting landslide with certainty. Most of rainfall; 2) soil moisture; 3) pore pressure; 4) the research in landslide monitoring is based on movement; 5) vibration. Integrating the multiple rainfall threshold models. Even though rainfall is one sensors (i.e., rain gauge, moisture sensor, pore of the major parameter contributing to landslides, pressure sensor, strain gauges, inclinometer, and rainfall intensity thresholds on a certain location alone geophone) in specific patterns at different soil layers may not be able to provide the chances for landslide is collectively referred to as the Deep Earth Probe with high accuracy. (DEP). A wireless sensor node is connected to the DEP to continuously collect data from this complex and To overcome the above challenge and provide reliable comprehensive arrangement of heterogeneous warning for landslides, we have discussed about the sensors. This entire set-up including the DEP and the intelligent algorithms for network management is • Adaptive learning models called the Intelligent Wireless Probe (IWP) as shown in • Now casting and Forecasting of vital Figure 1 parameters like pore-water pressure and factor of safety of the hill The landslide occurrence due to slope instability • Pore-water pressure threshold model usually covers very large areas of the hilly terrain. Hence, one IWP may not be adequate to The real-time data from the IoT system is provides the cover the entire area. Additionally, the influence of rainfall thresholds and Factor of Safety of the slope, landslide-triggering parameters varies at different which will be utilized to provide automated alerts to regions of the mountain. Therefore we have deployed the early warn the relevant stakeholders. The multiple IWP’s at crown, middle, and toe, regions of reliability of this system is enhanced by integrating the terrain. adaptive learning techniques, to learn the relation existing between different vital parameters from the real-time data and historic data. The knowledge learned is used to forecast the vital parameters 24 hours ahead of the time from the real-time data. During harsh environmental conditions and disaster scenarios, when the real-time data is unavailable, the learned knowledge can be used to predict the expected values of the vital parameters from the rainfall forecast information.

4 Real-time validation During the recent Kerala floods in 2018, our system was able to forewarn for landslides both reliably and successfully. Figure 2 below shows that the rainfall Figure 1: (a) Intelligent Wireless Probe (IWP), (b) One intensity has crossed the threshold for 1 hour, 1 day, of the Intelligent Wireless Probe deployed in Munnar, 3 days, 5 days and 7 days durations. The Yellow zone in the figure indicates the threshold crossing region. Kerala, India This clearly conveys that due to the antecedent rainfall conditions and the torrential rainfall, the area has 3 Data analytics & Machine learning for Landslide become vulnerable to imminent landslides. Early Warning

To provide reliable early warnings, we have taken into account the input from vital parameters such as rainfall, moisture, pore-water pressure, and movement. We have enhanced the reliability of decision making by not only considering the input from other vital parameters but also introducing data analytics, machine learning algorithms and forecasting technologies applied to IoT data [1,2,3]. The following Figure 2: Rainfall intensity-duration threshold plots models are implemented which aids in decision for hourly, daily, 3/5/7/15 days durations making and early warning. From the start of monsoon rain in 2018, the pore • Rainfall threshold models pressure sensors at different locations has shown a rise in pore pressure values by more than 50 units of • Fault diagnostic system kPa at some depths and more than 80 units of kPa at some other depths. This has resulted in reduction in detection of Disasters and partly funded by young the slope stability. Snapshots from the real streaming Faculty Research Fellowship under Visvesvaraya PhD software for a period of 8th August, 2018 to 9th scheme. We undertook this work following our August, 2018 for the Factor of Safety of DEP-5 in recognition as the ”World Center of Excellence in Munnar is shown in Figure 3. In Figure 3, yellow region landslide disaster risk reduction”, conferred to us by indicates the region, where the Factor of safety has the IPL- ”International Programme on Landslides” in crossed the threshold. August 2017. The authors would also like to Apart from 2018, we have also successfully provided acknowledge the contributions of the entire landslide warnings in 2009, 2011, 2013 and 2019. Over the team in our research center for their support in years, we have developed statistical analysis and machine learning algorithms from the data for various aspects. providing reliable and accurate warnings, which we REFERENCES were able to validate successfully during the 2018, 2019 flood and landslides in Kerala. [1] Harilal, G.T., Madhu, D., Ramesh, M.V. and Pullarkatt, D., 2019. Towards establishing rainfall thresholds for a real-time landslide early warning system in Sikkim, India. Landslides, 16(12), pp.2395-2408. [2] Hemalatha, T., Ramesh, M.V. and Rangan, V.P., 2017, May. Adaptive learning techniques for landslide forecasting and the validation in a real world deployment. In Workshop on World Landslide Forum (pp. 439-447). Springer, Cham [3] Hemalatha, T., Ramesh, M.V. and Rangan, V.P., 2019. Effective and accelerated forewarning of Figure 3: Factor of Safety (FoS) corresponding to landslides using wireless sensor networks and location DEP-5 in Munnar deployment site machine learning. IEEE Sensors Journal, 19(21), pp.9964-9975. [4] Ramesh, M.V. and Vasudevan, N., 2012. The deployment of deep-earth sensor probes for landslide detection. Landslides, 9(4), pp.457-474. 4 Conclusion [5] Ramesh, M.V., 2014. Design, development, and In this extended abstract, we have briefly discussed deployment of a wireless sensor network for about the IoT based landslide monitoring and early detection of landslides.Ad Hoc Networks, 13, pp.2- warning system, the need for multi parameter sensing 18. to deliver reliable early warnings. We have also [6] Petley, D., 2012. Global patterns of loss of life from discussed about the learning models that we have landslides. Geology, 40(10), pp.927-930. implemented. The real-time validation during the 2018 floods and landslides are also discussed.

ACKNOWLEDGEMENT The authors would like to express their immense gratitude to Sri. Mata Amritanandamayi Devi (AMMA), Chancellor, Amrita Vishwa Vidyapeetham, who gave us the motivation and inspiration to pursue this research work. This work is partly funded by Ministry of Earth Sciences (MoES), Government of India under the project titled “Advancing Integrated Wireless Sensor Networks for Real-time monitoring and

TECHNICAL SESSION – VII

MODELLING AND SOCIETAL IMPACT

Chair – Dr. Sridevi Jade

Modelling of Real Time Kinematic Global Navigation Satellite System (RTK-GNSS) derived surface displacements and velocities by dislocations

Vinee Srivastava Department of Earth and Environmental Sciences Indian Institute of Science and Education (IISER) Bhopal, Madhya Pradesh, India [email protected]

ABSTRACT formulations. Dislocations used for the modelling Seismically active fold and thrust belts like the ranged from vertical or strike-slip associated point Himalaya host natural hazards such as eartquakes and source induced surface displacement (Steketee, 1958) landslides. High serene beautiful peaks of the to deep seated inclined finite shear fault of arbitrary Himalayan mountains contain several geological elastic constant medium induced strain field (Iwasaki thrusts. These peakes result from deformational events and Sato, 1979). Okada, (1985) provided analytical during great earthquakes and aseismic deformation. solutions for surface deformation due to slip along The topography in fold and thrust belts result from fault strike, dip (normal and reverse) slip faults in an elastic related folding mechanisms such as fault propagation or half-space typically used to work out the causative fault bend folding or duplexing. Fault zones also make plane during earthquake occurrences (Okada, 1985). the top layer of the surface weak and additional factors The following formulation (Okada, 1985) is used in the such as rainfall, steepness of the slopes, soil saturation, dislocation modelling - gravity together with human activity cause landslides in 1.2. Displacement field due to a dislocation in an elastic the Himalaya. These landslides have been studied to half-space asses the hazard, impact on the population, Internal displacement field due to a single force in infrastrucrure and to devise mitigation strategies for the homogenous half-space is given by Okada, (1992). In the future. Fault-related topographic growth in a fault- Cartesian co-ordinate system, the displacement field is propagation setting can be modelled by Boundary ui (x1, x2, x3) due to slip on a dislocation Δuj (ξ1, ξ2, ξ3) j th Element Method (BEM) simulation of the measured surface in an isotropic medium (Fig.1). Let ui be the i th RTK-GNSS based topographic profile using dislocation component of displacement at (x1, x2, x3) due to the j (fault) based numerical modelling in Coulomb 3.3 (Lin direction point force of magnitude F at (ξ1, ξ2, ξ3). This and Stein, 2004; Toda et al., 2005). RTK-GNSS based can be expressed using formulas by Mindlin, (1936) or displacement profiles can also be quantified in a Press, (1965): j j j j landslide prone area to assess slope stability in the ui (x1, x2, x3) = ui A (x1, x2, - x3) - ui A (x1, x2, x3) + ui B (x1, x2, j region. The possible plane of failure (dislocation) along x3) + x3ui C (x1, x2, x3) a slope can also be simulated using BEM based where, j dislocation modelling using surface RTK-GNSS derived 1. ui A (x1, x2, - x3) = displacement field due to velocity /displacement field. single force placed at (ξ1, ξ2, ξ3) in an infinite medium j KEYWORDS 2. ui A (x1, x2, x3) = contribution from an image Real time Kinematic GNSS, Forward modelling, source of the given point force placed at (ξ1, Dislocation modelling, Landslide, Boundary Element ξ2, -ξ3) in the infinite medium (surface Method (BEM) deformation) j j 3. ui B (x1, x2, x3) and ui C (x1, x2, x3) = measured

1.1.Dislocation Theory depth dependent Dislocation modelling was first used by Steketee, 2 2 2 2 If R = (x1- ξ1) +(x2- ξ2) +ξ3 then the displacement (1958) & Rongved and Fransier, (1958) in seismology to equations (Okada, 1985) can be expressed as: For Dip study deformation in an isotropic homogeneous semi- Slip - infinite medium using numerous theoretical  2 F 11 fault/dislocation simulates the measured or observed u1 =()() x1 − 1 x 2 − 2  − 4 R3 +  RR− 2 ()3 “cumulative” coseismic displacement field. The 22 2 F 11()xx2−− 2  ()2 2 observed displacement is considered as d, G(m) is an u2 = + + − 4 RR3 +− R  RR− 2 3 ()3 influence function of finite rectangular fault/failure  2 F 3  1 plane parameters (length, width, strike, dip, top-depth) ux3 =()2 − 2  − − 4 RRR3 +− ()  3 and s the slip on the fault/failure plane. Fault type decides the slip motion. For example, in strike-slip faults (1.1) Okada, 1985) slip is purely strike-slip, in normal fault normal/down dip slip and in thrust fault the slip is only reverse slip. If the fault is oblique, then the slip on the rectangular dislocation is given by: S = s.cosα + s.sinα (1.5) where S is total slip and α is the rake of fault. The relation between deformation field and the source geometry can be expressed by the following observation equation (Okada, 1985): d = s.G(m) + ε (1.6)

ε = d - s.G(m) (1.7) Figure 1: Geometry of the rectangular source model where, d, deformation field, G, Green function also (Okada, 1985) known as influence function, (dependent on length, width, depth, dip angle, and cartesian co-ordinates of If (ξ/, η/) is an arbitrary coordinate on a fault/failure the finite dislocation) deformation vector, m is the surface, then for a finite rectangular fault with length L source geometry (dislocation length, width, depth, and width W, the deformation field can be derived by strike, dip), s is slip along the rectangular dislocation. taking x = x - ξ/, y = y - η/cos δ and d = d - η/sin δ and Since rupture created by the earthquake on the fault is applying the following integration equation: 퐿 푊 not totally rectangular, ε represents an error. In the 푑휉′ 푑휂′ (1.2) ∫0 ∫0 forward modelling we try to minimize the error or (Okada,1985) ε →0, then where λ, μ are Lame’s constants and δ is dip angle. Let 푑̂ = 푠̂퐺(푚̂) (1.8) / / x - ξ = ξ, p - η = η, (Sato and Matsu’ura, 1974) then above where 푑̂ represents modeled displacement, 푠̂ the equation becomes: 푚̂ 푥−퐿 푝−푊 modeled slip and the modeled parameters. ∫푥 푑휉 ∫푝 푑휂 (1.3) Boundary Element Method (BEM) based forward where, p = y cos δ + d sin δ. modelling can be using in Coulomb 3.3 (Toda et al., The result can be condensed into compact forms as a 2005). This method provides the approximate function numerical solution of the boundary integral equations f (ξ, η) and expressed as: (1.4) discussed above (Okada, 1985). BEM provides 푓(휉, 휂) = 푓(푥, 푝) − 푓(푥, 푝 − 푊) − 푓(푥 − 퐿, 푝) + 푓(푥 approximate solution of boundary value problem of the − 퐿, 푝 − 푊) differential equation in the domain parametrized by a finite set of parameters on the boundary. The inputs 1.3. Forward Modelling that need to be given to Coulomb 3.3, are estimates of A forward model simulates observables for a given length, width, dip angle, top depth, strike slip and dip set of model parameters. Forward problem comprises slip of the modeled fault plane as well as the co- set of differential equations with initial and/or ordinates of the trace of the fault plane. boundary conditions, solution of which (the forward 2. Real Time Kinematic Differential Global Navigation solution) is used for simulation of observables. Forward Satellite Systems (RTK-GNSS) Survey modelling can be used to simulate the measured Digital displacement/velocity data can be collected vertical displacement field or the topography using using RTK-GNSS through field surveys in a tectonically parameters for a causative rectangular dislocation (or active region like the Himalaya. Differential positioning fault/failure surface proxy). The slip along the causative with GNSS is a real-time positioning technique where one that simulates the measured displacement/ two or more receivers are used. High-precision Real velocity field best. Time Kinematic differential GNSS technique involves ACKNOWLEDGMENTS one stationary base or reference receiver with known co-ordinates and one roving receiver to determine the VS thanks the organizers for the invitation to attend and unknown co-ordinates. The reference station calculates be part of the “MOES funded National Brainstorming the position errors at any given time by comparing the session on modelling fault zone induced surface mass measured and known positions of the known base transport in the Himalayan orogenic terrains for the station and transmits the error to the remote roving study of Fault related hazards in Himalayan Towns.” BIT receiver in real time (Fig. 2). The remote receiver Mesra – Ranchi, March 16-17, 2020. corrects its calculated position value with this error REFERENCES value and improves its position accuracy with the help [1] Abidin, H., Andreas, H., Surono, M., Hendrasto, M., of the base station and eventually is used to quantify 2004. On the Use of GPS Survey Method for Studying displacement/velocity field. The accuracy of RTK-GNSS Land Displacements on the Landslide Prone Areas. obtained during the field measurements is 5-10 cm. FIG Working Week, 21–13. [2] Lin, J., Stein, R.S., 2004. Stress triggering in thrust and subduction earthquakes and stress interaction between the southern San Andreas and nearby thrust and strike-slip faults. Journal of Geophysical Research 109. [3] Mindlin, R. D., 1936. Force at a point in the interior of a semi-infinite solid, Physics 7, 195-202. Figure 2: (A) Schematic diagram of Real Time Kinematic [4] Okada,Y., 1985. Surface deformation due to shear Differential Global Navigation Satellite System (RTK- and tensile faults in a half-space. Bulletin of the DGNSS) during field surveys. (B) Principle of GPS Survey Seismological Society of America 75(4), 1135-1154. Method for Landslide Monitoring (after Abidin et al., [5] Press, F., 1965. Displacements, strains and tilts at 2004). tele-seismic distances, Journal of Geophysical Research 70, 2395-2412. 3. Slope stability assessment and numerical modelling [6] Rongved, L., Frasier J. T., 1958. Displacement of the along-slope displacement and velocity fields to discontinuity in the elastic half-space, Journal of identify the future plane of failure Applied Mechanics 25, 125-128. To assess the slope stability and identify the plane [7] Sato, R., Matsu'ura M., 1974. Strains and tilts on the of future failure, RTK-GNSS survey can be run in surface of a semi-infinite medium, Journal of Physics campaign mode by computing the position of the same of the Earth 22, 213-221. location at regular intervals in a landslide prone region. [8] Steketee, J. A., 1958. On Volterra's dislocation in a Displacement of these locations (if any) will determine semi-infinite elastic medium, Canadian Journal of the velocity over the period of measurement. These Physics 36, 192-205. RTK-GNSS measured displacement/velocity field can [9] Toda, S., Stein, R. S., Richards-Dinger, K., Bozkurt, S., then be modelled three dimensionally using BEM based 2005. Forecasting the evolution of seismicity in dislocation modelling. southern California: Animations built on earthquake In summary, to pre-empt the failure plane along a stress transfer. Journal of Geophysical Research 110, slope, an initial estimate of the plane parameters B05S16. (length, width, depth, dip angle, strike and dip slip) [10] Iwasaki, T., Sato R., 1979. Strain field in a semi- along a finite rectangular dislocation, is taken to do infinite medium due to an inclined rectangular fault, dislocation modelling. The results are subsequently Journal of Physical Earth 27, 285-314. compared with the measured displacement/ velocity profile. To match the measured and modeled profiles dislocation parameters, are varied. The best solution is Dissemination of Landslide Hazard Results for Societal Benefits

Balamurugan Guru† Sanchari Ghosh Somnath Bera Centre for Geoinformatics, JTSDS Centre for Geoinformatics, JTSDS Centre for Geoinformatics, JTSDS Tata Institute of Social Sciences Tata Institute of Social Sciences Tata Institute of Social Sciences Mumbai, Maharashtra, India Mumbai, Maharashtra, India Mumbai, Maharashtra, India [email protected] [email protected] [email protected] †Corresponding author

ABSTRACT 1 Introduction The Himalayan mountainous area is one of the most The frequency of landslides in the Himalayas is high dangerous in terms of recurrence of landslides. Most [1], [2] and highest in Kalimpong and next in the of the landslides have occurred in this region even in Kurseong block of Darjeeling district in West Bengal. the recent past due to incessant rainfall, especially The frequency of landslides increases with the advent during the monsoons and earthquakes. Communities of the monsoon season. Each landslide is bound to lose their properties; families were getting separated trigger another in the nearby zones. The landslides due to landslide impact. When communities have to usually cover a small area due to geological properties be shifted and relocated or at least sheltered till their of the area and most of them occur in the insides of houses are constructed elsewhere or they are the slopes [2], [3]. Constant, rapid and increasing allocated land elsewhere, it causes unrest among the urbanization and the development of the tourism communities. Hence, requires an appropriate sector in this region have further led to a significant landslide hazard mapping at micro level, which is burden on the carrying capacity of the mountainous supported to carry out the proper mitigation region [4], [5]. Growing rate of population as well as measures as well as early warning system. Hazard increasing number of built-up in the hilly regions has mapping is incorporated in order to design a majorly augmented the impact of landslides [6], [7]. mitigation framework. This involves the mapping of all The coping capacities of the local people clash with the past and present landslide sites in the region that the construction of the final mitigation measures of contain details such as the type of landslide, year, the government measures and this is because of the depth, velocity, slope and classification. For long gap of time between the recurrence of each community safety needs an effective landslide early landslides and the incapacity of the local authorities to warning system, geological and meteorological take immediate measures. “The inhabitants consider monitoring networks, communication and accurate landslides a manmade disaster caused by susceptibility maps are essential. Investing in indiscriminate urbanization and developmental infrastructure that supports early warning systems is activities [8].” The perception of landslides as a hazard required for effective preparedness, response and may exist but the choices of the people are limited. mitigation of landslides. Mountainous terrain seldom leaves enough space for KEYWORDS civilizations to develop, let alone spread as and when the population increases [5], [7]. These types of Landslide, Risk, Vulnerability, Hazard, Resilience, terrain are also more susceptible to hazards and their Himalaya impacts than plain lands. The community’s risk tolerance in such a limited scope of options relatively become the first to launch planned rescue increases as well. operations and debris removal. This is especially so when major ways of transport and The landslide susceptibility mapping is supported to communication or the access to some basic facility identify the areas that are prone to different levels of gets hampered. The need for immediate action is landslides and classified from very high to low or free relevant in such situations. zone [9], [10]. The causative factors for landslide ● Rehabilitation: Moving entire households or susceptibilities vary place to place depending upon rehabilitation of entire communities to safer the different geological, soil, geomorphological, zones. This is a highly unlikely process though groundwater, drainage, fault, slope, rainfall etc. [11], since land in mountainous areas is very limited [12], [13], [14], [15]. Mitigation measures for and the scope for reconstruction is less. landslides should aim towards using indigenous ● Reconstruction: Bridges, houses, lampposts, etc., resources. The basic principles for mitigation again, are parts of infrastructure that are crucial to the should be “avoidance”, “alerting”, “averting” and livelihoods and lives of local people. “adopting”. The mitigation strategies that are ● Retrofitting: Existing structures are made currently in place in the Himalayas, with a focus on the stronger, such as thickening of walls, heightening areas, which are prone to landslides. Often the local of floors, dumping more material on subsided residents come up with unscientific temporary land to raise platforms, etc. measures to reduce the impact of the landslide and ● Drainage Systems: The more educated and retain the land that is left. These measures and coping influential people usually reconstruct their capacities more often than not are expected to fail drainage and sewerage systems, such that the even by the people themselves. The use of traditional weaker slopes around their place of habitation are knowledge is common, especially in rural areas to not affected by relatively large runoff flows, detect steady and stable slopes and construction of especially during the monsoons. houses using light material. The drainage and 2.2 Urban Coping Capacities sewerage channels for each house are also altered in some cases. This sort of work has been given priority Among the coping capacities of urban communities by NGOs in the region and the consequent spread of residing in zones of recurring landslides, the following knowledge has to lead to the correction of these are the most common in Districts: channels. ● Reinforcements: Urban communities believe in reinforcing slopes through constructional 2 Community Capacities in Landslide Regions methods rather than rehabilitating. The locations 2.1 Rural Coping Capacities closer to the centre of the city are obviously more economically viable. More houses are constructed Among the coping capacities of rural communities on open slopes and at the foot of the slopes to residing in zones of recurring landslides, the following ensure they are reinforced and cannot move. are the most common in the area of Himalayas ● Backups: In order to tackle situations where the especially Kalimpong and Darjeeling Districts: access to certain basic facilities is hampered, ● Debris Removal: Instead of waiting for the urban areas usually have backups in place. For officials to come and take care of all the debris example generators or inverters for electricity, removals, sometimes the local responders smaller clinics instead of the inaccessible or disaster management. This includes usage of Radio, overflowing hospitals, etc. Television, Telephone, Short Message Service, Cell ● River Training: Many a times, rivers around the Broadcasting, Cellular Mobile Telephone System, region are trained, or their flow direction is Satellite Radio, Armature Radio, Community Radio, changed (slightly), such that they not only provide Wireless Local Loop, Siren, GIS tools, Internet and economic benefits for the region itself, and also Social Networking etc. In this section, we will speak put minimum pressure on the weaker rocks and more about the use of ICTs in disaster situations. slopes of the region. During landslide, response starts with early warning. Even though there are ground/ satellite based There exist gaps in communication between the technologies, which can provide information and officials and the people who reside in the landslide warning of disasters, dissemination of the information prone zones. Challenges with regards to the remains the key point. An effective early warning Settlement Memorandum exist in terms of system can save thousands of lives. Most effective displacement due to the loss of land because of tools for early warning dissemination seem to be landslides. These will have to be sorted through policy mobile phones, even in the developing world. Other changes and planning for such eventualities. technologies such as television and radio are also The problems related to mitigation strategies only efficient, but mobile phones are the most accessible being structural in nature have to be worked upon. media at any time. The Cell Broadcasting technology Structural mitigation measures can only be effective is one of the most effective and advanced in issuing up to a time. Without a clear channel of warnings through mobile phones. Through the Cell communication between those affected by recurrent Broadcasting technology, a message can be sent by landslides and those attempting to place relevant the operator/administrator to all the mobile phones mitigation measures in place, there can be no progress in a particular locality, if needed even to the whole made. country, immediately. GSM, CDMA3, UMTS and D- ● Protection of existing development and AMPS phones have this capability. This system is infrastructure, either by retrofitting or by at successful because it is unaffected by the heavy traffic, least testing their resistance to damage in which usually tends to occur during a disaster terms of the particular landslide zones in situation. The technology has been used not only for which they fall. early warning, but also for information dissemination ● Educating people about insurance and loss. at the immediate aftermath.

3 Societal Benefits 3.2 Landslide Mitigation

3.1 Information and Communication Technology In the mitigation and preparedness process, certain (ICT) guidelines are laid down for effective landslide hazard management. In this regard, building codes, safety ICT has a significant role to play when it comes to procedures etc are established, documented and responding to landslides particularly in the phase of shared with the concerned personnel. Further, early warning systems. Especially in today’s modern procedures like resource mapping, planning, era, the use of information and communication inventory lists etc. are prepared and integrated onto a equipment has become vital for disaster response. GIS platform for monitoring and analysis. These are There are multiple ICT tools, which can be used in not time bound but the accuracy and proper updates response. This is specially required for the ICT in the for data is strictly time bound for the accurate data to incident response system (IRS). be used for analysis. Here the application of prediction, which derived from modeling tools for risk Here, the need for ICT is highlighted with the or trend analyses form an essential component. The requirements of coordination in various relief users rely heavily on the Internet for data collection agencies whether government, NGO or international. and sharing in all these processes. In the preparedness For the purpose of damage assessment and process, training is provided with different forms of rehabilitation planning, the GIS platform as part of ICT media and then the early warning and alert systems seems the most appropriate because “timely are designed within the community and then the information on the occurrence, progression and response plans are modified as per the community. regression of disasters during the various phases are For example, in a remote area, the response will essential for effective management of disasters and definitely be delayed since communication is delayed this can be derived by integrating the real-time aero- and transportation to and from these areas is mostly space imageries with the corresponding ground difficult to access in normal conditions and this is information (usually available on Geographic aggravated in the disaster situation. Information System (GIS) platform linked with Global Positioning System (GPS)). The obvious advantage for 3.3 Landslide Response generating such a dynamic map, unlike static maps, is Landslide response, the transport facility options are availability of real-time information depicting the provided to access the impacted areas, distribution of cause and effect relationship, that are extremely relief materials, damage assessments, mobilization of helpful to the disaster managers at every level of resources including humans, mapping the temporary Disaster Management administration, including the shelters, and rescue operations. In this phase the community”. communications between the response teams and to the different stakeholders including the general public 4 Early Warning System (EWS) are become important, more over reliable An important aspect of landslide hazard management information from ground, rapid, communications plan involves the set-up of an appropriate emergency among response teams and to the general public management system, in which EWS is considered as configurable, and controlled access communication is an essential part. It can be defined as the method for essential for effective landslide response operations. providing timely and effective information about the During this phase, the Internet becomes slow in the hazard probability so that affected people could take affected area due to traffic and most often it is not preventive measures to be safe from impacts of the available due to infrastructure damage. In India, a hazard on their lives and property. As defined by the National Disaster Response Network is being set up in UNISDR, there are four major elements identified in order to meet the ICT demands during the response an early warning system: information of the risk, phase. This includes the portable satellite hazard monitoring, gathering and sharing of communication devices, wireless radios, HAM radios, information and immediate response. With increasing etc. There is also a need for radio-procedure codes to population, landslide susceptibility is also increasing in be established between various response regions, which thereby calls for a wider organizations for complete coordination and effective implementation of landslide early warning system [16], [17], [18]. Globally, there are examples of EWS essential component of an early warning system for for landslides such as the Japanese EWS for debris landslides is the real time monitoring of the hazard. It flows, the EWS by the Hong Kong Government, and could also include hydrological monitoring if the other EWS in the USA, CANADA, Brazil, and New causal factor is rain in the region. Such regions require Zealand. An example can be taken of the alarm system the installation of rain gauges to keep real time in the Rhone Valley of Southern France, where sirens updates of rainfall [18], [19], [20], [21]. Additional data and lights are used at the major footpaths to spread regarding rain estimation or storm-like weather warning and awareness. In Italy, an EWS is used since conditions can be gained from weather radar or 2008 that shows real time updates on a graphical satellite techniques for those regions that face platform using the software called SMART - Shallow landslides due to rain or storm. Landslide Movement Announced through Rainfall 5 Community Resilience Thresholds. In North America, the use of Doppler radar to assess rainfall is used to issue landslide “It is the intersection of humanity with landslide warnings for vulnerable regions. Owing to the activity that regenerates a natural land-forming current situation of disasters all over the world, there process into a potential hazard” [22]. The idea that is a need for cooperation, coordination and sharing of they refer to here is that only when those conducting information on EWS. Incorporation of an early their day-to-day activities in the region are unable to warning system into policies at all levels is essential to cope properly with the landslides as a process of land ensure better response mechanisms. There are formation, does it actually turn into a potential elements that define an early warning system which hazard. In these areas though measuring and includes, the details of the expected hazard, the comparing institutional performance in household- region that will be affected, what actions should be based scale is difficult due to the fact that the location taken, how long will the disaster impact, and of the households is in different sites in the same emergency contact details. For a landslide, administrative unit [23]. The coping capacities of the instructions are required to be shared with local local people clash with the construction of the final police, fire fighters, paramilitary forces and medical mitigation measures of the government measures and teams. To get information regarding the landslide this is because of the long gap of time between the susceptibility, use of landslide probability maps can be recurrence of each landslides and the incapacity of the done for forecasts that indicate regions that are at local authorities to take immediate measures. The risk, the intensity of rainfall and the duration of rainfall people themselves are capable of building or and accessible evacuation routes or emergency rebuilding infrastructure that is absolutely necessary shelters. Landslide probability or susceptibility maps to their livelihoods and lives. Yet, these measures provide information where the landslides might occur. more often than not, tend to be temporary in nature, Usually a scale of 1:25000-1:100000 is used to create given that the communities mostly make use of local landslide hazard maps for preparedness and planning labour and resources. Communities are resilient in purposes. Also, by the use of GIS technology, overlay their own manner, but with the necessary of maps can be created for landslide probability and reinforcements and resources from the administrative intense rainfall in a region [22]. This would help in authorities, all their efforts have to be started anew identifying the areas that are at a greater risk from after every incidence of recurring landslides. landslides during high rainfall situations. Most 6 Conclusions Many times, the coping capacities of the people allow [2] Ramakrishnan D, Ghosh MK, Vinuchandran R and them to develop mitigation structures in the zones Jeyaram A. 2005. Probabilistic Techniques, GIS and where the officials have approved the construction of Remote Sensing in Landslide Hazard Mitigation: A certain mitigation structures. Due to this gap in case Study from Sikkim Himalayas, India. Geocarto communication and planning, an unnecessary amount International. Vol. 20 (4), 1-6. , of time is spent going two steps back, removing [3] Sajinkumar KS and Anbazahagan S. 2015. temporary mitigation strategies and building Geomorphic appraisal of landslides on the technically stronger ones. There exist gaps in windward slope of Western Ghats, southern India. communication between the officials and the people Natural Hazards, v.75(1), pp.953-973. DOI: 10.1007/s11069-014-1358-2. who reside in the landslide prone zones. Challenges [4] Choi KY and Cheung RW. 2013. Landslide disaster with regards to the Settlement Memorandum exist in prevention and mitigation through works in Hong terms of displacement due to the loss of land because Kong. Journal of Rock Mechanics and Geotechnical of landslides. These will have to be sorted through Engineering, 5(5), 354-365. policy changes and planning for such eventualities. [5] Hinotoli V Sema, Balamurugan Guru and Ramesh The problems related to mitigation strategies only Veerappan. 2017. Fuzzy gamma operator model for being structural in nature have to be worked upon. preparing landslide susceptibility zonation Structural mitigation measures can only be effective mapping in parts of Kohima town, Nagaland, India. up to a time. For example, the protection of existing Modelling Earth Systems and Environment, development and infrastructure, either by retrofitting Springer. 3(2): 499-514. DOI: 10.1007/s40808-017- or by at least testing their resistance to damage are 0317-9 terms of the structural mitigations in landslide prone [6] Balamurugan Guru, Ramesh Veerappan and areas. Non-structural measures are also equally Touthang Mangminlen 2016. Landslide important in the part of landslide risk reduction such Susceptibility zonation mapping using frequency as educating the local community about personal as ratio and fuzzy gamma operator models in part of well as property insurance, awareness, health care NH-39, Manipur, India. Natural Hazards, Springer. schemes, and losses. Requires developing an effective 84(01): 465-488. DOI:10.1007/s11069-016-2434-6. Early Warning System in the region, which is need to [7] Balamurugan Guru, Ramesh Veerappan, Francis be addressed as urgent based. Sangma and Somnath Bera 2017. Comparison of probabilistic and expert-based models in landslide ACKNOWLEDGMENTS susceptibility zonation mapping in part of Nilgiri The authors are expressing sincere thanks to Prof. District, Tamil Nadu, India. Spatial Information Malay M, IIT Bombay, Prof. Krishna and Prof. Research, Springer. DOI: DOI: 10.1007/s41324- Jaganathan from BIT, Ranchi for their constant 017-0143- support and MoES, Government of India for their 1. https://link.springer.com/article/10.1007/s4132 financial support to attend the meeting. 4-017-0143-1 [8] Alcántara-Ayala I and Moreno AR. 2016. Landslide REFERENCES risk perception and communication for disaster risk [1] Kanungo DP, Arora, MK, Gupta RP and Sarkar S. management in mountain areas of developing 2008. Landslide risk assessment using concepts of countries: a Mexican foretaste. Journal of danger pixels and fuzzy set theory in Darjeeling Mountain Science, 13(12), 2079-2093. Himalayas. Landslides, 5(4), 407-416. 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Understanding the role of design and collaborative model for innovation towards system-level intervention∗ Purba Joshi IDC School of Design Indian Institute of Technology Bombay Mumbai, Maharashtra, India [email protected]

ABSTRACT The core team members are responsible for Design plays a vital role in bridging the gap between developing the system's components, technological interventions and users. The user- communicating, and collaborating with the network. centric design approach helps simplify the product or In this case, the team may begin with geologists, GPS the system interface, making it more efficient and marking expert, remote sensing experts, sensor easier to use [1]. It approaches an intervention from developers, and product designer and further add the user perspective, understands the challenges experts to fill the gap in developing the system. The faces by various stakeholders, and further translates it core team would be responsible for facilitating into a product or system that is functional, usable, and implementation, pilot testing of the complete system, desirable. Whereas the technical innovators usually and gathering input for further refinements. achieve the function, it is converted into usable, The Expert team is responsible for reviewing and acceptable, and more desirable form by the designers evaluating the ideas and implemented products and [1]. systems for feasibility and effectiveness. It would have Knowledge is the key element to development and technical experts not directly involved in the innovation. One person or a team with single development of the product and system, though their expertise cannot design and develop a system for expertise is required for its success, ocall field experts, masses. A successful system requires interventions people from finance and marketing, and material and and innovations brought together with the experts manufacturing. from various fields. It is equally essential to have a The external team serves the advisory role. It may proper model to bring these experts together. The have people from ministry and local governing bodies, collaborative model for innovation provides the manufacturers, various experts, and users. They bring guidelines for such collaborations. The model can help in new knowledge, a broader perspective, and vast team members transform their ideas into an experiences to the collaborative efforts [2]. integrated system that can be deployed, used, and Designated members from each field should be maintained by the users and stakeholders. appointed to ensure good interactivity among the The collaborative model for innovation consists of 3 teams for the successful development and interdependent teams with defined roles; Core team, implementation of the system. They would be expert team, and external team, as shown in figure-1 continuously involved throughout the project and will [2]. It is crucial to identify the collaborators and be committed to the entire timeline. Regular online resources committed to knowledge acquisition for meetings for brainstorming and scheduled offline each team to ensure the right type of intervention at meetings at a commonplace would further facilitate each stage. steady growth and help curb delays and roadblocks. The proposed collaborative model can aid in bringing together a large team from various institutes with a common goal and facilitate its smooth functioning. It will help bring in clarity by defining the role and deliverables from each member and facilitate knowledge brokering.

KEYWORDS Collaboration, Collaborative model, System design

Figure 1: Collaborative model for innovation proposed by Chakravarthy and Karpe (2020)

REFERENCES [1] Bryan Lawson. 2005. How designers think (4th ed.). Architectural Press, New York, NY. [2] B. K. Chakravarthy and Rohan Karpe. 2020. Collaborative Model for Entrepreneurial Innovation. https://www.researchgate.net/publication/34104 2411.

WORKSHOP MOMENTS IN PICTURES

Workshop Moments in Pictures