Data shows that there has been a five-fold increase in the number of climate-related disasters that the world has witnessed over the last fifty years. Just between 2000 and 2019, 7,348 reported disasters caused 1.23 million deaths, affecting a population of 4.03 billion and causing economic losses to the tune of USD 2.97 trillion. Studies have also shown that quick-onset disasters such as floods, typhoons, and cyclones have resulted in more damages and loss of lives in the past two decades in the Asia Pacific region compared to other parts of the world (Neef & Pauli, 2021). The increasing frequency of climate-induced disasters and the rising magnitude of accompanying damages worldwide underlines the need to focus on disaster risk reduction and management responses.
Focussing specifically on India, the Emergency Events Database (EM-DAT) pertaining to natural disasters and their related damage costs for the period of 1990-2022 shows that the nation was among the worst affected countries in the world. The data suggests that floods and storms featured as the top two natural disasters in India between 1990 and 2022, comprising 53% and 27% respectively, while also accounting for the highest share of damage costs at 63.10% and 31.52% respectively. It is, therefore, critical to understand the havoc that each such instance wreaks on the economy and how best to increase the systemic adaptive capacity to meet the same. The present paper tries to contribute to the literature by estimating the direct and indirect impacts of disasters for certain case studies of floods and cyclone incidences in India. The paper builds the case for standardizing disaster reporting frameworks and also expounds on the need for integrating technologies in disaster management for constructing climate-resilient infrastructure.
Using the ICRIER Prakriti Disaster Management Model, a regional input-output (RIO) model to study the impact of disasters on local businesses and the economy, the paper assesses two disaster-affected states of India- Assam (flooding) and Andhra Pradesh (cyclones). The modelling exercise highlighted that even though the states differ in terms of the direct impact experienced (with Andhra Pradesh being affected twice as much), the indirect impacts were found to be manifold. Three key results emerge from the analysis. First, cyclone instances in Andhra Pradesh led to a loss of 1.53% in value of output in 2018-19, which is expected to rise in the future, as both the intensity and frequency of cyclones would increase with climate change. Second, despite its high direct losses, Assam was relatively much less affected when the loss of assets by private entities was accounted for. This may be reflective of the high annual frequency of flooding incidences in the state, and the state’s high resilience towards this risk. Third, the analysis of the two states revealed distinct loss profiles influenced by their developmental patterns, with Andhra Pradesh experiencing significant losses in the chemical sector, whereas Assam’s losses were mainly concentrated in water supply, rubber and plastics, and textiles industries.
