Socioeconomic vulnerability assessment of coastal villages and buildings along Andhra Pradesh East Coast of India

Climate change is a global phenomenon that has enhanced sea-level rise and aggravated the prevailing coastal hazards that make coasts more vulnerable. The socioeconomic vulnerability of villages for the entire Andhra Pradesh state and buildings at the selected locations along the Andhra Pradesh coast is estimated to understand the level of risk due to exposure. This study attempts to understand the reality of grassroots communities/households and derive vulnerability indicators that affect coastal communities. In this regard, (1) the exposure index (EI), (2) coastal cumulative vulnerability index (CCVI), and (3) socioeconomic vulnerability indexes are calculated. EI is calculated based on oceanogenic multi-hazard zones (MHZ) estimated using the long-term extreme water levels, shoreline change rate, sea-level change rate, and high-resolution topographic data. The cumulative coastal vulnerability index (CCVI) and socioeconomic vulnerability index (SEVI) are calculated for all villages and buildings in the selected villages. A total of 16 socioeconomic risk indicators from the village census of 2001 and ten indicators from the survey at the building level are used in the study. The current study suggests 23 villages comprising 6000 households associated with 0.022 million people under the very high SEVI category. Four villages comprising 1000 households associated with 3000 people are in the very high cumulative vulnerability index category. Nineteen hundred eighty-five buildings in the selected parts of the study area had a very high SEVI. One hundred and forty-five buildings in the village chosen had very high SEVI. The brief policy interventions and alternate livelihood options are discussed in this paper. The decision matrix generated at the village and building levels will help decision makers identify the contributing risk indicators for each village/building for appropriate resilience interventions.