Overuse of fertilizer has long been identified as a major issue in many parts of the world, including Sri Lanka. Sandy regosol soil and the shallow groundwater table in Kalpitiya, has aggravated the impacts of extensive fertigation, raising doubts on the long-term socioeconomic and environmental sustainability of intensive agricultural systems of the region. In this background, this study attempts to determine the driving factors influencing the overuse of fertilizer within the farming community in Kalpitiya. Primary data collected from face-toface interviews with 107 farmers from Kalpitya area using a pre-tested questionnaire was used to estimate a Bayesian probit model with sufficiently diffuse normally distributed priors. The model was estimated using a Random Walk Metropolis-Hastings sampling method, which iterated 125,000 times and 25,000 were discarded as burn-in. Results reveal that farmers who perceive that fertilizer has no effect on soil and groundwater tend to move away from fertilizer recommendations and are overusing. Farmers who are aware and believe that ground water is contaminated in the area tend to apply the recommended amount of fertilizer. In addition, larger farmers seem to apply recommended dosages than smaller farmers. Raising awareness through proper extension services and creating economic disutility by increased fertilizer costs coupled with the introduction of organic fertilizer could be recommended to circumvent the ill effects of overuse of fertilizer.

The importance of vulnerability and adaptive capacity has been frequently emphasized in explaining the societal aspects of climate change over the last few years. Developments in vulnerability research and consequent adaptation policies, have become a top priority in many countries. With the understanding of the significant importance of agriculture, numerous climate change assessments have been conducted to explore the vulnerability status of agricultural communities, whose livelihood is mostly dependent on natural resources. However, such studies are highly limited in Sri Lanka and the current study was aimed at developing a Socioeconomic Vulnerability Index (SeVI) for two climate change affected agricultural communities in Wanathawilluwa Divisional Secretariat Divisions (DSD) using the concept of "Sustainable Livelihoods Approach" under five specific assets, namely (1) human; (2) social; (3) physical; (4) natural and (5) financial. Fifty households from two Grama-Niladhari Divisions (GN) were surveyed to collect data on three vulnerability dimensions and 17 socioeconomic indicators. The SeVI aggregate was developed as a composite indicator index, where a relative weight was assigned to each indicator with a view of obtaining weighted average index scores. In addition, pentagons were developed for each community by analysing the five assets under 17 indicators. Results suggested that Mangalapura farming community (GN Division) was relatively more vulnerable and most exposed to natural hazards. This study suggests SeVI as a viable approach to assist the policymakers to identify the most vulnerable communities to climate change and thereby improve the early warning systems. Further, this SeVI can be promoted as a simple but effective tool for comparing socioeconomic vulnerability in hazard prone regions towards climate change.

Groundnut is a major commercial crop cultivated in Sri Lanka, especially in the dry zone depending on the monsoon seasons. However, groundnut cultivation has been significantly affected by contemporary challenges, such as irrigation, climate change, methods of land preparation and selection of good seeds, which require adoption of new technologies. Especially, seed production aspects for groundnut cultivation requires a higher attention to maintain the sustainability and cost-efficiency of the process. Nevertheless, farmers are reluctant in utilizing new technology, considering their dependency on traditional methods passed through previous generations. Therefore, the current study was conducted to determine the knowledge level of farmers on technology adoption in groundnut production. A total of one hundred farmers from Eravur Pattu DS division in Batticaloa district were recruited for the current study, based on the stratified random sampling technique. An interviewer administrated pre-tested structured questionnaire was used for data collection. Descriptive analysis techniques were used to summarize the socio-demographic data and the cultivation practices among the farmers. The Chi-square test of association was used identify the significant driving factors on the level of technology adoption by farmers for groundnut seed production. It was noted that around 52% of the farmers were characterized with a moderate level of technology adoption, followed by 37% of farmers denoting a higher technology adoption level in groundnut production. According to the Chi-square statistics, the technology adoption level in groundnut seed production among the studied farmers denoted significant associations with age (p=0.049), education level (p=0.015), monthly income (p=0.047), farming experience (p=0.005), and farming extent (p=0.006). Provision of more training programmes on technology adoption for groundnut farming, extension services and insurance schemes are important to promote the technology adoption among farmers for groundnut seed production.