Earthquake in Assam and North Bengal and COVID19 in India

Earthquake in Assam and north Bengal in IndiaOn April 28, 2021, a 6.4 Richter scale earthquake affected the Sonitpur district of Assam, the tremors of which were felt in north Bengal and other parts of North-East India, as reported by the National Centre for Seismology1. Six more tremors followed the first shake 2. There were reports of widespread damage to buildings and other structures from across Assam, mostly in the central and western towns of Tezpur, Nagaon, Guwahati, Mangaldoi, Dhekiajuli, and Morigaon3. Again on May 3rd, 2021, an earthquake was felt in the Sonitpur district of Assam with a 3.7 magnitude on the Richter scale4. Assam disaster management authority reported that 10 people from 4 districts suffered physical injuries since the first attack on April 28, 2021, and some more time will be needed to know about the actual amount of damage that had taken place5. According to the National Centre for Seismology, the area affected by the earthquake is seismically very active and falls in the highest seismic hazard zone where the Indian tectonic plate subducts with the Eurasian plate because of which there are high chances of future quakes as well6.

Community preparedness for volcanic hazards at Mount Rainier, USA

Lahars pose a significant risk to communities, particularly those living near snow-capped volcanoes. Flows of mud and debris, typically but not necessarily triggered by volcanic activity, can have huge impacts, such as those seen at Nevado Del Ruiz, Colombia, in 1985 which led to the loss of over 23,000 lives and destroyed an entire town. We surveyed communities around Mount Rainier, Washington, United States, where over 150,000 people are at risk from lahar impacts. We explored how factors including demographics, social effects such as perceptions of community preparedness, evacuation drills, and cognitive factors such as risk perception and self-efficacy relate to preparedness when living within or nearby a volcanic hazard zone. Key findings include: women have stronger intentions to prepare but see themselves as less prepared than men; those who neither live nor work in a lahar hazard zone were more likely to have an emergency kit and to see themselves as more prepared; those who will need help to evacuate see the risk as lower but feel less prepared; those who think their community and officials are more prepared feel more prepared themselves; and benefits of evacuation drills and testing evacuation routes including stronger intentions to evacuate using an encouraged method and higher self-efficacy. We make a number of recommendations based on these findings including the critical practice of regular evacuation drills and the importance of ongoing messaging that focuses on appropriate ways to evacuate as well as the careful recommendation for residents to identify alternative unofficial evacuation routes.

Landslide Hazard Zonation and Evaluation around Debre Werk Town, North West Ethiopia

The present research was conducted in the town of Debre Werk, East Gojjam, North West Ethiopia, with the ultimate aim of conducting a Landslide Hazard Zonation and Evaluation. To reach this aim, the Slope Stability Susceptibility Evaluation Parameter (SSEP) rating system was adopted to zone and evaluate the landslide status of the area. This rating system was done by considering the parameters of intrinsic and external triggering factors that cause landslides. Systematic and detailed fieldwork had been undertaken as a justification. Secondary data, on the other hand, was required to define the general conditions of the area and to gain a thorough understanding of the field of study. Ratings for intrinsic parameters in the SSEP system include slope morphometry, relative relief, slope content, geological structures/discontinuities, land use land cover, groundwater, and external parameters include erosion, seismicity, and manmade activities. Individual facet-wise ratings for intrinsic causative factors and external triggering factors ratings are summarized to evaluate the landslide hazard zonation of an environment. The sum of all causative parameter ratings will give evaluated landslide hazards (ELH). Therefore, the research was carried out by dividing the study area into 70 facets. Then 85 landslide incidents in the study area were investigated. From 85 landslides, 39 districts showed past landslides, 23 showed active landslides and the remaining 23 districts showed signs of landslides. The delineated 70 facets were categorized into 3 landslide hazard zones. There are about 73.3km2 (27.2%) of the study area within the low hazard zone, 140.8km2 (52.1%) within the moderate hazard zone, and the remaining 55.9km2 (20.7%) within the high hazard zone. Based on the findings of SSEP, it can be deduced that the present research area is highly susceptible to landslide and requires special attention during rainy seasons. Finally, the validity of the prepared LHZ map was checked by overlaying the inventory map over the produced LHZ map. The overlap map shows that 17 districts showing active landslides, 2 districts showing signs of landslides, and 5 districts showing past landslide activities fall into high hazard zones. Likewise, 5 districts showing active landslides, 3 districts showing signs of landslides, and 28 districts showing past landslides fall into moderate hazard zones. The remaining 1 district showing active landslides, 18 districts showing signs of landslides, and 6 districts showing past landslide activities fall into moderate hazard zones.

A multi-temporal landslide inventory and hazard zonation using relative effect method along the Mughal road Shopian, India

Landslide inventory and thematic data are of utmost importance in the domain of landslide hazard mapping. The union territory of Jammu and Kashmir, India surrounded by the Himalayan and the Pir-Panjal mountain range is prone to landslides and has already caused havoc at many places. The present study aims to provide the landslide inventory of the Mughal Road, Shopian, which lies in the Pir Panjal range of Kashmir valley. Multidate satellite data of the years 2008 to 2020 are utilized to create an inventory of landslides in this area.The use of high-resolution satellite imagery made it possible to delineate the shallow as well as the deep landslides along the roadside where they occur frequently. To understand the landslide causes, a statistical technique, relative effect method has been implemented in this study. This method helped in mapping the hazard zone areas. The relative effect of each causative factor on landslides is determined by calculating the ratio of coverage and slide which were analyzed in GIS environment. The resulting landslide hazard zone map has been classified as very low, low, moderate, high and very high zones. Out of the total area, 12.62% is critical to landslides, 21.45% is highly prone and 24.84% is moderately prone while 21.94% is low and 19.13% is very low prone to landslides. The outcome of this susceptibility modeling will be beneficial for handling and monitoring the forthcoming landslides as well as the fortification of the general public and environmental hazards of the study area. It will also help the planners in the development around the study area.

Landslide Hazard Zonation and Evaluation Around Debre Markos Town, NW Ethiopia—A GIS-Based Statistical Approach

The main goal of this research was to perform a landslide hazard zonation and evaluation around Debre Markos town, North West Ethiopia, found about 300 km from the capital city Addis Ababa. To achieve the aim, a GIS-based probabilistic statistical technique was used to rate the governing factors, followed by geoprocessing in the GIS setting to produce the landslide hazard zonation map. In this research, eight internal causative and external triggering factors were selected: slope material (lithology and soil mass), elevation, aspect, slope, land use land cover, curvature, distance to fault, and distance to drainage. Data were collected from field mapping, secondary maps, and digital elevation models. Systematic and detailed fieldwork had been done for image interpretation and inventory mapping. Accordingly, the past landslides map of the research area was prepared. All influencing factors were statistically analyzed to determine their relationship to previous landslides. The results revealed that 17.15% (40.60 km2), 25.53% (60.45 km2), 28.04% (66.39 km2), 18.93% (44.83 km2), and 10.36% (24.54 km2) of the research area falls under no hazard, low hazard, moderate hazard, high hazard, and very high hazard respectively. The validation of the landslide hazard zonation map reveals that 1%, 2%, 3%, and 94% of past landslides fall in no hazard zone, low hazard, moderate hazard zone, and high hazard or very high hazard zones respectively. The validation of the landslide hazard zonation map thus, it has been adequately demonstrated that the adopted approach has produced acceptable results. The defined hazard zones can practically be utilized for land management and infrastructure construction in the study area.

Forecasting of Hazard Zone due to Storm Surge Using SIND Model

We have developed the SIND (scientific interpolation for natural disasters) model to forecast natural hazard zone for storm surge. Most previous studies have been conducted to predict hazard zone with numerical simulations based on various scenarios. It is hard to predict hazard zone for all scenarios and to respond immediately because most numerical models are requested a long simulation time and complicated postprocess, especially in coastal engineering. Thus, in this study, the SIND model was developed to overcome these limitations. The principal developing methods are the scientific interpolation for risk grades and trial and error for parameters embedded in the governing equation. Even designed with hatch files, applying disaster characteristics such as the risk propagation, the governing equation for storm surge in coastal lines was induced from the mathematical solver, COMSOL Multiphysics software that solves partial differential equations for multiple physics using FEM method. The verification process was performed through comparison with the official reference, and the accuracy was calculated with a shape similarity indicating the geometric similarity of the hazard zone. It was composed of position, shape, and area criteria. The accuracy of about 80% in terms of shape similarity was archived. The strength of the model is high accuracy and fast calculation time. It took only less than few seconds to create a hazard map for each scenario. As future works, if the characteristics of other disasters would be understood well, it would be able to present risk propagation induced from each natural disaster in a short term, which should help the decision making for EAP.

Mapping Fluctuations of Hispar Glacier, Karakoram, using Normalized Difference Snow Index (NDSI) and Normalized Difference Principal Component Snow Index (NDSPCSI)

Investigation of the fluctuations in the snow-covered area of the major glaciers of the Karakoram range is essential for proper water resource management in Pakistan, since its glaciers are responding differently to the rising temperatures. The objective of this paper is to map snow covered area of Hispar glacier in Hunza river basin for the years 1990, 2010 and 2018. Two techniques, (NDPCSI) Normalized Difference Principal Component Snow Index and (NDSI) Normalized Difference Snow Index were used. Hispar glacier of the Hunza basin has lost 114 km2 of its ice cover area, during the last 28 years, with an alarming annual retreat rate of 1.67 km2 of glacier ice from 1990 to 2018. Hunza basin experienced a +1°C rise in both mean minimum and mean maximum temperature during 2007 to 2018.as a result, Karakorum ice reserves have been affected by rising temperature of the region. Due to temperature rise, retreat of snowcovered area of Hispar, Karakoram mountain range shows a shift in the cryospheric hazard zone.

Flood hazard zoning in Ngan Sau, Ngan Pho river basin, Ha Tinh province using GIS and analytical hierarchical process

This paper introduces the AHP method integrated with GIS technology to provide information for flood hazard analysis in the Ngan Sau and Ngan Pho river basins. The factors ìnluencing the occurrence of floods in a study area include slope, rainfall, drainage density, soil, relative slope length, and land cover. These data are used for establishing a flood hazard zone map in a GIS environment. The obtained results indicate that the two main causes of flooding are rainfall and slope with weights of 45% and 25.5%, respectively. The resultant map has shown about 82.78% of the total catchment area is having a high and very high probability of flood and areas under high flood hazard only covers 17.22% of the study area. The validation of the flood hazard zone map was conducted based on flood evens in the field. The results showed that the AHP technique and GIS are reliable methods for the assessment of the flood hazard potential, specifically in spare-data regions.