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Earthquakes come without warming, and often cause massive devastation, resulting not only in the loss of property but also of lives. Many of the survivors suffer from intense and lasting psychological trauma. This book covers the experience of recent earthquakes in India, and what has been learnt (and what we have failed to learn) in the process of managing the aftermath in each case. This includes immediate medical attention, long-term mental health care, and the reconstruction of housing and infrastructure in both rural and urban areas. The experiences of the contributors, many of whom have actively contributed their expertise to disaster management and recovery, help us understand what problems require a swift response and which aspects should be based on detailed analyses keeping in mind local conditions. Reconstruction is seen as offering an opportunity to rebuild society such that all sections of the population are empowered and brought into the community's decision-making process. It is also an opportunity to develop construction techniques that are suited to local materials and skills but are also more earthquake-resistant than the old. And finally, there is the realisation that the best first responders are local community groups which need to be nurtured, and trained in crisis management and risk mitigation.

\"How do urban communities in Asian cities experience the impacts of urbanisation and climate change? This book throws light on the ongoing processes of rapid urban transformation in many cities in developing countries, with particular reference to cities such as Chennai in India. Due to increasing demands on infrastructures and urban services, cities in developing countries are often pushed to the edge of collapse even when not in times of disaster. While such cities try to implement measures to safeguard the well-being of their citizens, looming impacts of climate change such as increasingly frequent and intense natural hazards pose new and additional challenges to their urban communities. This book connects critical issues relating to the general functioning of cities with climate-related disasters with the concept of resilience. Furthermore, this research takes a pro-solution stance, and demonstrates that individuals can form collective power to deliver added value before, during and after a disaster. The concept of resilience is applied to determine whether an urban community would be affected or damaged during a climate-related disaster, and to what extent.\"

Natural disasters such as earthquakes endanger human lives and infrastructure, particularly in urban areas. With the advancements in science and technology in understanding natural hazards, recent studies have attempted to mitigate them by mapping the risks using geospatial technology. In this paper, we attempt to integrate the multi-criteria decision-making (MCDM) models, namely the Analytical Hierarchy Process (AHP) and the Criteria Importance Through Inter-criteria Correlation (CRITIC), besides using the artificial neural network (ANN) to assess the seismic risk in the eastern coast of India. The AHP-CRITIC technique is used to evaluate the earthquake coping capacity and vulnerability and has been further used to generate a training base for earthquake probability mapping by ANN. The earthquake probability and spatial intensity information are used to develop the hazard map. Following that, integrating vulnerability, hazard and coping capacity spatial information assessed earthquake risk. Our results indicate that approximately 5% of the study area is at high risk, whilst more than 11% of the population is at high risk due to seismic induced hazards. The area under the curve of the receiver operating characteristic curve is 0.85, which indicates reliable results. The results of this study may help various agencies involved in planning, development and disaster mitigation to develop seismic hazard mitigation methods by better understanding their impacts on the eastern coastal region of India.

Landslides are the most destructive geological hazard in the hilly regions. For systematic landslide mitigation and management, landslide evaluation and hazard zonation is required. Over the past few decades several techniques have been developed that can be used for landslide evaluation and zonation. These techniques can broadly be classified into qualitative and quantitative approaches. Qualitative approaches include geomorphological analysis and heuristic techniques whereas quantitative approaches include statistical, artificial intelligence and deterministic techniques. In quantitative techniques prediction for landslide susceptibility is based on the actual realistic data and interpretations. Further, the quantitative techniques also overcome the subjectivity of qualitative approaches. Each of these techniques may consider different causative factors and utilizes various means for factor evaluation and analysis. When compared, each of these techniques has its own advantage and disadvantage over other techniques. The selection of appropriate technique for landslide hazard evaluation and zonation is very crucial. The factors that need to be considered to adopt an appropriate approach are; investigation purpose, the extent of the area to be covered, the type of mapping units, the scale of map to be produced, type of data to be used, type of landslides, availability of resources, capability and skill set of an evaluator and the accessibility to the study area. The main aim of this article is to present a comprehensive review on various techniques and approaches available for landslide susceptibility and hazard zonation mapping. Further, attempt is also made to assess the effectiveness of these techniques in landslide hazard zonation studies.

Uatzau basin in northwestern Ethiopia is one of the most landslide-prone regions, which characterized by frequent high landslide occurrences causing damages in farmlands, non-cultivated lands, properties, and loss of life. Preparing a Landslide susceptibility mapping is imperative to manage the landslide hazard and reduce damages of properties and loss of lives. GIS-based frequency ratio, information value, and certainty factor methods were applied. The landslide inventory map was prepared from detailed fieldwork and Google Earth imagery interpretation. Thus, 514 landslides were mapped, and out of which 359 (70%) of landslides were randomly selected keeping their spatial distribution to build landslide susceptibility models, while the remaining 155 (30%) of the landslides were used to model validation. In this study, six factors, including lithology, land use/cover, distance to stream, slope gradient, slope aspect, and slope curvature were evaluated. The effects of the landslide factor of slope instability were determined by comparing with landslide inventory raster using the GIS environment. The landslide susceptibility maps of the Uatzau area were categorized into very low, low, moderate, high and very high susceptibility classes. The landslide susceptibility maps of the three models validated by the ROC curve. The results for the area under the curve (AUC) are 88.83% for the frequency ratio model, 87.03% for certainty factor, and 84.83% of information value models, which are indicating very good accuracy in the identification of landslide susceptibility zones of a region. From these resulted maps, it is possible to recommend, the statistical methods (Frequency Ratio, Information Value, and Certainty Factor Methods) are adequate to landslide susceptibility mapping. The landslide susceptibility maps can be used for regional land use planning and landslide hazard mitigation purposes.

Over the past decade, the Delhi (National Capital Region, NCR) has witnessed significant growth and has emerged as a vital center for commerce and education. This rapid urbanization owes itself to its strategic location, connecting important cities like Gurugram, Faridabad, Noida, Sonipat, and Rohtak. However, its proximity to active geological features such as the Main Himalayan Thrust (MHT), Main Boundary Thrust (MBT), and Main Central Thrust (MCT), the city has been susceptible to devastating earthquakes, making it imperative to conduct a comprehensive probabilistic seismic hazard assessment for the Delhi NCR area. To perform this assessment, a homogenized earthquake database from 1720 to 2023 within a 300 km radius of the epicenter of Delhi was utilized. This data enabled the calculation of peak ground acceleration (PGA) and Spectral Acceleration (Sa) at different time periods, representing 50%, 20%, 10%, 5%, and 2% probabilities of exceedance in 50 years at the bedrock level. A logic tree approach, incorporating Ground Motion Prediction Equations (GMPEs) with appropriate weighted factors, was applied to ensure accuracy. The findings of the updated seismic hazard assessment reveal that Delhi and its neighboring cities are highly vulnerable to seismic hazards, with expected PGA values of 0.10 g, 0.18 g, 0.26 g, 0.33 g, and 0.48 g for the respective probabilities of exceedance. These results are comparable with the Indian code IS:1893 Part I and Malhotra’s (2005) standards that validate their reliability. Furthermore, the seismic hazard results have been used to create a deaggregation plot, which helps to quantify the contributions of seismic sources in terms of magnitude and epicentral distance. This comprehensive understanding of seismic hazards in Delhi and its adjoining regions will aid in implementing appropriate measures to enhance preparedness and mitigate potential risks.

The Himalayan region and hilly areas face severe challenges due to landslide occurrences during the rainy seasons in India, and the study area, i.e., the Rudraprayag district, is no exception. However, the landslide related database and research are still inadequate in these landslide-prone areas. The main purpose of this study is: (1) to prepare the multi-temporal landslide inventory map using geospatial platforms in the data-scarce environment; (2) to evaluate the landslide susceptibility map using weights of evidence (WoE) method in the Geographical Information System (GIS) environment at the district level; and (3) to provide a comprehensive understanding of recent developments, gaps, and future directions related to landslide inventory, susceptibility mapping, and risk assessment in the Indian context. Firstly, 293 landslides polygon were manually digitized using the BHUVAN (Indian earth observation visualization) and Google Earth® from 2011 to 2013. Secondly, a total of 14 landslide causative factors viz. geology, geomorphology, soil type, soil depth, slope angle, slope aspect, relative relief, distance to faults, distance to thrusts, distance to lineaments, distance to streams, distance to roads, land use/cover, and altitude zones were selected based on the previous study. Then, the WoE method was applied to assign the weights for each class of causative factors to obtain a landslide susceptibility map. Afterward, the final landslide susceptibility map was divided into five susceptibility classes (very high, high, medium, low, and very low classes). Later, the validation of the landslide susceptibility map was checked against randomly selected landslides using IDRISI SELVA 17.0 software. Our study results show that medium to very high landslide susceptibilities had occurred in the non-forest areas, mainly scrubland, pastureland, and barren land. The results show that medium to very high landslide susceptibilities areas are in the upper catchment areas of the Mandakini river and adjacent to the National Highways (107 and 07). The results also show that landslide susceptibility is high in high relative relief areas and shallow soil, near thrusts and faults, and on southeast, south, and west-facing steep slopes. The WoE method achieved a prediction accuracy of 85.7%, indicating good accuracy of the model. Thus, this landslide susceptibility map could help the local governments in landslide hazard mitigation, land use planning, and landscape protection.

The northeastern region of India is one of the six most seismically active convergent plate tectonic areas in the world. The north–south convergence along the Indo-Tibetan Himalayan Ranges and the east–west subduction within the Indo-Burma Ranges create a complex stress regime, resulting in significant seismic activity and a history of great/large earthquakes. The region’s intricate strain patterns, active faults, and potential seismic gaps underscore the need for detailed subsurface studies to effectively assess seismic hazards and impending seismicity. Geophysical research is essential for understanding the region’s geodynamic evolution, seismotectonics, and mineral resources. This manuscript reviews the geological and tectonic settings of the region and summarizes recent geophysical studies, including seismic, gravity, magnetic, and magnetotelluric surveys conducted in the Assam Valley and adjacent areas (within latitudes 24.5–28.5° N and longitudes 89–97.5° E). The review highlights key findings on hydrocarbon-bearing sediments, the configuration of the crystalline basement, the heterogeneous structures of the crust and upper mantle, and seismic discontinuities. By synthesizing these results, the review aims to enhance the understanding of seismic hazards in Northeast India, guide mitigation strategies, and identify key knowledge gaps to direct future research efforts.

Spatio-temporal evolution of post-seismic landslides and debris flows provides a new perspective to understand post-earthquake evolution of geological environments and landscapes, and to instruct cascaded catastrophic hazard mitigation and post-disaster reconstruction. However, limited earthquake events have been investigated for post-earthquake geohazard evolution. This work reports the geohazard evolution after the 2017 M s 7.0 Jiuzhaigou earthquake considering the effects of the earthquake, geology, terrain, meteorology, hydrology, and human engineering activity. Some new viewpoints are suggested. (1) Landslide and debris flow activity intensified in the first year following the earthquake under the effects of the antecedent earthquake, precipitation, fault tectonics, human engineering activity, and fluvial networks. (2) Landslide and debris flow activity declined rapidly in the second year as a result of dramatically reduced sediments, declined rainfall, and self-healed slopes. (3) The significant decay of landslide and debris flow activity and the prominent reduction of loose deposits indicate that the geological environment was gradually restoring. (4) Although the hazard effect mitigation and geological environment restoration were ongoing (in the absence of rainstorm events) to attain a new balance, the geoenvironment has not returned to the pre-earthquake level because of widespread unrecovered geohazards and the remaining loose deposits on hillslopes or in channels. (5) The geological environment after the Jiuzhaigou earthquake may re-equilibrate and return to the pre-earthquake level more quickly than after the Kashmir, Chi-Chi, Gorkha, Wenchuan, and Murchison earthquakes. This work provides new knowledge pertaining to geohazard evolution after a strong earthquake and to profound impacts of a catastrophic earthquake on geological environment and landscape.