POLITECNICO DI TORINO SCUOLA DI DOTTORATO Dottorato in Ambiente & Territorio

Abstract

Climate change impacts vary in degree according to sector and region. The effects of climate change are particularly adverse for sectors like agriculture and water management, which are dependent on climatic variables. Subsistence farmers in developing countries like Nepal, where agriculture is mainly rain-fed rural people mainly depend on natural based livelihood activities and rely on agriculture, forestry and natural bases and have very little resources, have weak adaptive capacity, and may be unable to cope with changing climatic conditions. These factors augment farmers’ vulnerability to climate change. Focusing on three different Village Development Committees from three different geographical regions – Pragatinagar of Nawalparasi from low land, Thumpokhara of Syangja from mid-land and Kagbeni of Mustang district from high land district, this study aims to explore the impacts of climate change on the vulnerability of farmers. Hence the objective of the study is to investigate the climate change vulnerability, existing livelihood adaptation practices and perception of local people about climate change, adaptive capacity and adaptation techniques in local level. Local level vulnerability assessment is very important to formulate suitable policy measures to address their livelihood. Household level vulnerability to climate change depends on different factors, so there is still uncertainty in methodology to measure vulnerability. However, this research has adopted the integrated vulnerability assessment concept and indicator method to study farmers’ vulnerability of the study areas utilizing the data collected from 219 households and secondary data. CARE’s Community- Based Adaptation Toolkit method and insight from quantitative and qualitative research methodology, household and key informant interviews, and observation and PRA techniques for data collection were also done. Different socioeconomic and biophysical factors were collected and classified into three classes (Exposure, Sensitivity and Adaptive Capacity). Principal component analysis (PCA) was used to prioritize the indicators.