Quantifying Loss and Damage from Disasters: Evidence from Super-cyclone Amphan in Indian east-coastal district

Amidst the backdrop of changing climate and increasing disasters, a wide array of mitigation and adaptation responses exist for disaster management. However, residual impacts often arise from insufficient mitigation and inadequate adaptation, known as Loss and Damage (L&D). While existing literature has estimated loss and damage, independently on each capital asset by econometric, or Damage and Loss Assessment, Post Disaster Needs assesment methods, limited research has estimated residual “Loss and Damage” on livelihood assets through vulnerability lenses, and synthesized the linkages among capital assets, and the impacts after adopting mitigation and adaptation measures.

This study addresses this research gap by quantifying economic and non-economic L&D from 2020 super-cyclone Amphan, in South Twenty-Four Parganas, one of India’s highest-risk coastal districts, while accounting for the compounding effects of the concurrent interacting hazard, COVID-19 pandemic. Using the extended Sustainable Livelihoods Approach, a household survey has been conducted across the highest vulnerable community development blocks in this district, to derive the first and second-order economic (human, physical, and financial capital) and non-economic (social and natural capital) L&D estimates across three damage severity levels-low, moderate and high.

While Poisson regression models are used to estimate L&D to human and physical capital, Heckman’s sample selection model is adopted to estimate L&D to financial capital, proxied by change in agricultural income. Non-economic L&D estimates on social and natural capital are quantified using Multivariate Probit model. Regression estimates find that the households faced greatest L&D to human and physical capital in high damage, with second-order estimates being lower than first-order. However, the coping measures bearing high costs, increased second-order L&D to human capital in low and moderate damage. Risk reduction measures effectively minimized L&D to physical capital in low and moderate damage. L&D estimates of financial capital, indicate that the coping measures reduced second-order impacts for low (INR 1140), and high damage (INR 942) households. Among the non-economic L&D estimates, social capital erodes from low to moderate damage [(+93.5) to (+20) percentage-points (first-order); (-3.5) to (-4.5) percentage-points (second-order)]. However, second-order L&D to natural capital exceeds first-order, with relatively lower estimates in moderate damage.

Overall, the findings highlight the crucial and significant role of livelihood diversification in minimizing economic and non-economic L&D. Besides, government support, inter-village trust, and resilient housing significantly reduce economic L&D. Perception of riskiness of house location, household income, and recovery from past cyclone significantly determine non-economic L&D. These insights will guide stakeholders to understand effectiveness of adaption and mitigation measures, necessary to reduce vulnerability and build resilience during overlapping hazards.