3^rd International Conference on Natural Hazards and Disaster Management October 23-24, 2019 Tokyo,Japan

Biography:

Aniruddha Sengupta is currently working as a Professor of Civil Engineering at IIT Kharagpur, India. His research interests are in Soil-Structure Interaction, Landslide Mitigation and Earthquake Engineering.

Abstract:

Recently, an Indo-Norway collaborative study has been launched to look into the possibility of earthquake induced landslides along two strategic roadways: Gangtok to Changu Lake and Gangtok to Lachung within the Indian state of Sikkim. The state of Sikkim in India and its adjoining region are known to be the part of ‘Alpine-Himalayan global seismic belt’, a seismically very active area of the world. This region has already experienced four great earthquakes of magnitude higher than Mw=8.0 in 1897, 1905, 1934 and 1950, apart from several other large earthquakes in the densely populated region like 1905, Mw=7.5, Kangra earthquake, 2005, Mw=7.6, Kashmir earthquake, 2015, Mw=7.8 and Mw=7.3, Nepal earthquakes. The occurrence of earthquakes in the area is mainly due to the tectonic activity along well-known faults in the Himalayas, namely, Main Boundary Thrust (MBT) and Main Central Thrust (MCT). In addition to these, the prominent tectonic features in Sikkim and nearby areas are the two near parallel, NNW–SSE trending Tista and Gangtok lineaments, the WNW–ESE trending Goalpara lineament and the SW–NE trending Kanchenjunga lineament. The selection of ground motions with known probability of occurrence is an important input for the dynamic analyses of the existing slopes along the above two roadways. Thus, a probabilistic seismic hazard analysis of the areas within Sikkim is performed using the updated earthquake catalog, modified seismic sources (area source) and next-generation attenuation models. A commercially available software ‘EZ-FRISK’ is utilized to generate the total hazard curve (expressed as the annual probability of exceedance versus Peak Ground Acceleration (PGA)) and Uniform Hazard Spectra (UHS) at bedrock level. The values of peak ground accelerations and spectral acceleration for the two roadways within Sikkim for a return periods of 2474.9 years, 475 years and 97.9 years are obtained.

                                                                                  sengupta@civil.iitkgp.ac.in

                                                                          sauravmishra.kumar@gmail.com

Biography:

Rajni Hiroshima has completed her Graduation at the University of Tokyo. She is currently pursuing her Master studies at the Industrial Institute of Science, Tokyo University, Japan.

 rajnihiroshima@gmail.com

Abstract:

Peat soils can be found in many countries around the world; 2,000km² through Hokkaido, whereas in Sri Lanka 5% to 10% of land area is covered by peat soil. The process of urbanization has created the need to utilize those areas in construction. However, construction over peaty soils always creates special problems due to their poor engineering properties. Low shear strength is a major problem often causing stability problems in peat soils. In order to prevent such failures, peat ground should be improved using appropriate techniques. Soil reinforcements with natural fibers are highly used successful ground improvement method. Among all-natural fibers, Coconut Coir (CC) has the highest tensile strength and it is highly recommended as a ground improvement. Its high content of lignin (40%) enhances the strength of treated soil. Moreover, this natural fiber is widely available in Sri Lanka. In this study, CC which is made out of coconut husks is used as an additive material for soil stabilization. The main objective of this study is to utilize CC as an environmentally friendly partially replacing material of cement for peat ground improvement. Unconfined Compressive Strength (UCS) of specimens under different CC and OPC contents is compared. DCC shows higher water absorption. During the absorption, coir is able to penetrate to soil mixture and it increases the interaction between soil particles. Higher UCS can be attained using DCC. Water content looks like rely on the rate of hydration by vary OPC composition. UCS of the soil increases significantly with the increase of Coconut Coir content and curing period. Coconut coir can be used for replacing the utilization of cement amount partially for peat ground stabilization. Thus, the lower consumption of cement can contribute to greener earth by reducing the greenhouse gas emissions in construction.

Biography:

R Sudarmai is currently working as an Associate Professor at Department of Electronics and Communication Engineering, Avinashilingam Institute for Home Science and Higher Education for Women. 

                                                                                            shanthicivil@gmail.com

Abstract:

Wireless Sensor Networks consists of a large number of sensor nodes, which are scalable, low cost, flexible, and easily deployable operated by energy constraint battery. WSN nodes play major role in the prediction of disaster in an effective manner by using different sensors such as rainfall, soil moisture, pore pressure, vibration and tilt. Landslides are one of the most common problems globally and India as well. Indian hill masses are prone to landslides from low hazard to severe landslide hazard. The Nilgiris district situated in the southern part of India on the Western Ghats is prone to High to Severe Landslide Hazard. The historical landslide inventory analysis of this area clearly reveals that the future landslide occurrence in the district is multifold and disastrous. Hence, efficient system for the detection and early warning is necessary in these areas. In this paper, heterogeneous cluster architecture as shown in Fig 1   is proposed by which the different sensors aggregate the data from the heterogeneous sensors, processing is carried by the cluster head nodes. The processed data are transmitted to the sink node. The energy efficient routing protocol is introduced which reduces the energy consumption by multifold.

Biography:

Harikrishnan is currently pursuing Ph.D in Social Work at Mizoram University, Aizawl, Mizoram, India. He had completed MSW from Amrita Vishwa Vidyapeetham University, Tamil Nadu

Abstract:

Aranmula is acknowledged by the United Nations Development Programme (UNDP) as a Heritage Village due to Uthirattathi Boat race and Aranmula Mirror which are unique to this Village and not based on environmental or physical features. The present rapid assessment was to understand impact on flood in Aranmula Heritage Zone and study carried out on the 1^st & 2^nd week of September 2018 after the flood in Kerala. A cross sectional survey design was carried out through a rapid assessment of Palliyodams (snake boats), traditional artisans, worship places, traditional houses etc. The participants or sites in the study consist of 52 Palliyodakaras (villages), 21 flood-affected Aranmula Mirror Artisans, traditional houses, around 50 worship places in the Aranmula Heritage Zone. Both qualitative and quantitative method was used for data collection and analysis. The study found that the flood creates huge damages to the livelihoods in the heritage sites. It has affected the Palliyodams, Palliyodapura (Boat Sheds), Adayabharanam (boat ornaments), Palliyoda nayambukal (rudder-oar) and Palliyodakkadavu (snake boat landing area). Majority of the Palliyodams need an overall maintenance and a little less than half of the Aranmula Mirror Artisans have lost materials during the flood. There is a need to revive the livelihood and heritage of the Aranmula people as well as promote & prevent the tangible and intangible culture through a comprehensive plan.

Biography:

R Sudarmai is currently working as an Associate Professor at Department of Electronics and Communication Engineering, Avinashilingam Institute for Home Science and Higher Education for Women

Abstract:

Wireless Sensor Networks consists of a large number of sensor nodes, which are scalable, low cost, flexible, and easily deployable operated by energy constraint battery. WSN nodes play major role in the prediction of disaster in an effective manner by using different sensors such as rainfall, soil moisture, pore pressure, vibration and tilt. Landslides are one of the most common problems globally and India as well. Indian hill masses are prone to landslides from low hazard to severe landslide hazard. The Nilgiris district situated in the southern part of India on the Western Ghats is prone to High to Severe Landslide Hazard. The historical landslide inventory analysis of this area clearly reveals that the future landslide occurrence in the district is multifold and disastrous. Hence, efficient system for the detection and early warning is necessary in these areas. In this paper, heterogeneous cluster architecture as shown in Fig 1   is proposed by which the different sensors aggregate the data from the heterogeneous sensors, processing is carried by the cluster head nodes. The processed data are transmitted to the sink node. The energy efficient routing protocol is introduced which reduces the energy consumption by multifold. 

                                                                                                                                                                                                                                                                                                                                                    sudarelakkiya@gmail.com

Biography:

Gliceto Olarte Dagondon is an Bantay Pasipiko & Director of GREEN Mindanao Association.

Abstract:

Engagement with local communities and governments on conservation, land rights and coastal management past three decades encountered incessant El Nino/La Nina, flooding and droughts impinging sustainability goals. Common projects are situated in coastal areas and mountain regions facing Pacific. The anticipatory planning’s and investigating “REINA” disaster with over 6 thousand casualties in 2004 and preparing for recurrence. Peers in NGO’s, government and communities popularized practical DRR learning experiences and forecasting. Series of mega disasters ensued with over 10 thousand casualties from typhoons Washi-Bopha-Haiyan. Weather warning system, forecasting and climate prediction of government, academic and international agencies was revolutionized by civil society, India players and social media communities. A record million people been evacuated; however, casualties remained high including recent events. Forecasting and prediction remained handicapped and compromised by business as usual pursuits, consideration to economic interest and complexities in DRRM protocols and accountabilities. Intelligence deficient forecasting and predicting resulted into inaccurate advisory common with “Habagat” southwest monsoon and tropical depressions. Lack of climate and weather instrumentation in South China Sea provides opportunity to match western Pacific global system. Migration of warning system from simple 1 to 5 typhoon signal-scale into descriptive categories not well understood and embraced. Upgrading and downgrading of storm categories been taken for granted, not situated on real-time and real-location and lacking local information and participation. Common errors after successive heavy rainfall days, accumulated precipitation were not factored into forecasting and predicting flooding and landslide incidents

Biography:

Kyle Burke Pfeiffer is the Manager of the National Preparedness Analytics group within the Decision and Infrastructure Sciences Division at Argonne National Laboratory. 

Abstract:

Situational awareness of the operational status of specific, critical supply and demand nodes following a major disaster may inform response and recovery activities based on the ability of an infrastructure asset or system to support core facility operations. Near-real-time analysis of infrastructure dependency information is a computationally intensive process that has generally been observed informally by public safety officials. While system-level information may be desired, it has been beyond the capabilities of most local public safety and emergency management agencies. To address this problem, a Grass-roots Infrastructure Dependency Model (GRID-M) was developed to enable near-real-time analysis of physical infrastructure dependencies of specific supply and demand nodes within four lifeline sectors: electricity, natural gas, water, and wastewater. The operational status of each node can be characterized as operational, partially operational, or not operational. These statuses are obtained by matching real-time outage or disruption data from utility providers with predetermined specific coping strategies based on a preincident limited infrastructure survey for specific assets within a network. This information can also be paired with a limited damage assessment to provide awareness of the accessibility to, and physical state of, each node within supply chains of interest. GRID-M displays all outputs within a Geographic Information Systems environment with additional prepopulated layers such as real-time traffic and demographic information of the affected communities. As such, GRID-M may be used following a major disaster to support the identification of priority response and recovery objectives based on the disruptions of critical local supply chains and their relationship with affected communities.

Biography:

Naiyana Sahavechaphan has worked at National Electronics and Computer Technology Center. Her current research focuses on the data stream management and analytics, mainly but not limited to epidemiological and environmental domains.

Abstract:

Weather observations have played an essential role in several domains such as agricultural and environmental sciences. In modern weather stations, observations are automatically sensed and transmitted via a wireless link to a centralized database in a timely fashion. Each individual station, in particular, sits on its own surrounding area and consists of (1) meteorological sensors to measure environmental observations (i.e., temperature, rain and humidity); mainboard to control the work process; energy source (i.e. solar cell and battery) to drive the work process and communication network to transmit observations from field to server. Here, it is likely that sensors can malfunction, battery degrades, communication is poor, rain gauge is blocked etc. Consequently, observations could be anomalous, delayed or missing. It should be noted that the more accurate, complete and in-time observations, the more effective and reliable are their applications. It is thus vital to always maintain weather stations such that the accurate, complete and in-time observations are promising. Here, we term this promising as weather station health. We believe that the health of weather stations should be real-time evaluated and then reported to the corresponding officials for timely maintenance plan and action. In this work, we thus propose TanPibut health which is a software system that holistically evaluates the health of weather stations. Specifically, it evaluates a set of observations starting from the current moment back to a specified period based on the qualified, missing and delayed observations. The evaluation result is given with the numerical value ranging from 0.0 to 1.0 for the worst to the best station health.

Biography:

Naiyana Sahavechaphan has worked at National Electronics and Computer Technology Center. Her current research focuses on the data stream management and analytics, mainly but not limited to epidemiological and environmental domains.

Abstract:

Weather observations have played an essential role in several domains such as agricultural and environmental sciences. In modern weather stations, observations are automatically sensed and transmitted via a wireless link to a centralized database in a timely fashion. Each individual station, in particular, sits on its own surrounding area and consists of (1) meteorological sensors to measure environmental observations (i.e., temperature, rain and humidity); mainboard to control the work process; energy source (i.e. solar cell and battery) to drive the work process and communication network to transmit observations from field to server. Here, it is likely that sensors can malfunction, battery degrades, communication is poor, rain gauge is blocked etc. Consequently, observations could be anomalous, delayed or missing. It should be noted that the more accurate, complete and in-time observations, the more effective and reliable are their applications. It is thus vital to always maintain weather stations such that the accurate, complete and in-time observations are promising. Here, we term this promising as weather station health. We believe that the health of weather stations should be real-time evaluated and then reported to the corresponding officials for timely maintenance plan and action. In this work, we thus propose TanPibut health which is a software system that holistically evaluates the health of weather stations. Specifically, it evaluates a set of observations starting from the current moment back to a specified period based on the qualified, missing and delayed observations. The evaluation result is given with the numerical value ranging from 0.0 to 1.0 for the worst to the best station health.