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This paper presents a detailed technical description of features added to the standard ORANI model to construct a CGE for Sri Lanka, namely, ORANI- SL. The model distinguishes between rain-fed and irrigated agricultural land and introduces water as a production factor. In addition, the new production structure offers the option of substitution between rain-fed and irrigated agricultural lands. The paper also describes the model's database and the steps of the data transformation process from the latest available input-output table of Sri Lanka to the ORANI-SL database, which is necessary for model simulation. The new model could be used to analyse the economy wide impacts of climate change in Sri Lanka, study the economic implications of increased irrigation capacity or sustainable water usage in Sri Lanka, and evaluate the efficacy of various other adaptive strategies to cope with the impacts of climate change. In addition this model can be easily adapted to another country.

This study developed a set of composite indices to analyse the vulnerability to climate change of the agricultural sector in Sri Lanka using the data between 2001 and 2018. The aim was to identify the level of vulnerability of the agricultural sector to climate risks at the country level, as a tool to better understand the variability and magnitude of impacts and adaptive capacities required to overcome the risks due to climate change. To calculate the indices, environmental and socio-economic indicators representing the conceptual components of vulnerability, namely, exposure, sensitivity, and adaptive capacity were selected based on previous studies. Secondary data were collected for the selected indicators and normalised considering the indicator's functional relationship to vulnerability. Normalised data were then weighted and aggregated using two weighting methods and two aggregation methods to calculate four vulnerability indices, in order to minimize the impact of the known limitations of the methodological approaches to create composite indices. The values for composite indices were standardised to the range 0-1 and divided into five levels of vulnerability based on equal intervals, which revealed a moderate level of agricultural vulnerability to climate change over the eighteen-year study period. The multidimensional assessment, further, revealed the upward trend of vulnerability due to the increased sensitivity of the system to climate change. Even though the adaptive capacity of the country has been strengthened in the recent past, it has a critical role to play in mitigating vulnerability. The study also suggests methods for predicting future vulnerability by replicating the calculations.