Abstract

In the contemporary landscape, the aftermath of each weather-related disaster triggers swift estimations of economic losses, often accompanied by attributions of increased frequency or intensity of such events. The prompt assignment of blame for weather-related disaster losses is a complex endeavor, as discerning the precise role of climate change proves challenging due to the intricacy arising from intertwining climate alterations with societal transformations, contributing to the evolving dynamics of disaster impacts. In parallel, assessing disaster loss and damage is crucial, especially in vulnerable areas prone to natural disasters, such as the Himalayan region, as it is highly susceptible to climate-induced events and potentially severe consequences for the environment and human settlements. The study focuses on the state of Uttarakhand in India, aiming to comprehensively understand the interplays between climate change, societal shifts, and economic repercussions following weather-related calamities. The primary objective is to develop a detailed loss inventory for Uttarakhand, specifically focusing on past events, types of losses, and their spatial distribution. The methodology thoroughly examines secondary sources, data from the Em-Dat database, government reports, and relevant research articles. This comprehensive approach enables understanding of weather-related disaster losses, considering the impacts of climate change and societal changes in the region. The study also employs a robust time-series analysis methodology to unravel the temporal and spatial distribution of disasters due to extreme events, recognizing their significance in shaping disaster dynamics. The analysis aims to identify vulnerable rural and urban clusters within Uttarakhand, provide valuable insights into the spatial patterns of specific loss types, and map high-risk areas within Uttarakhand, contributing to proactive disaster mitigation strategies. This information is crucial for adapting disaster response and recovery strategies, allowing for the effective allocation of resources based on the unique needs of affected regions by integrating loss inventory creation, time-series analysis, and vulnerability mapping. The findings are expected to not only deepen our understanding of the complex interplays between climate change, societal shifts, and disaster losses but also provide actionable insights for mitigating the impact of future weather-related calamities in the Himalayan region, particularly in the state of Uttarakhand.

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