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Changing climate has increasingly become a challenge for smallholder farmers. Identification of technical, institutional and policy interventions as coping and adaptation strategies and exploring risks of their adoption for smallholder farms are the important areas to consider. The aim of the present study was to carry out an in-depth analysis of adaptation strategies followed and the associated risk premium in technology adoption.

The study was carried out in the dryland systems of three Indian states – Andhra Pradesh, Karnataka and Rajasthan – and was based on a survey of 1,019 households in 2013. The flexible moment-based approach was used for estimating the stochastic production function, which allowed estimation of the relative risk premium that farmers are willing to pay while adopting the technologies to avoid crop production risks.

In all the three states, the risk premium (INR ha⁻¹) was higher for farm mechanization compared to supplemental irrigation, except in the case of Andhra Pradesh. The higher the level of technology adoption, the higher the risk premium that households have to pay. This can be estimated by the higher investment needed to build infrastructure for farm mechanization and supplemental irrigation in the regions. The key determinants of technology adoption in the context of smallholder farmers were climatic shocks, investment in farm infrastructure, location of the farm, farm size, household health status, level of education, married years, expected profit and livestock ownership.

Quantification of the risk premium in technology adoption and conducting associated awareness programs for farmers and decision-makers are important to strengthen evidence-based adoption decisions in the dryland systems of India.

Researchers and policymakers are figuring out the adaptation technologies to cope with the changing climate. Adaptation strategies for crop production followed by the farmers at selected study locations had ranged from 6-30 per cent only, and this was mainly due to lack of awareness about the actual cost associated with adaptation and non-adaptation of these strategies.

Hence, this study aims to address the cost of adaptation for rice using joint probability distribution of rainfall and crop prices.

Cost of adaptation varied from INR2,389 to 4,395/ha for System of Rice Intensification (SRI); INR646 to 1,121/ha for alternate wetting and drying (AWD) and INR8,144 to 8,677/ha for well irrigation (WI), whereas expected cost for not using these technologies has ranged from INR6,976 to 9,172/ha for SRI; INR4,123 7,764/ha for AWD and INR10,825 to 17,270/ha for WI. Hence, promotion of the adaptation technologies itself will minimize the income losses to the farmers.

Even though, there are many ways for farmers (other than technology), to adapt to climate change (such as out-migration to cities, selling farm assets, focus on children’s education, etc.), this report, given the framework of the major research study undertaken, addresses only farm-level adaptation of the technologies to enhance farm income.

Public–private partnership in providing the technologies at cheaper costs, capacity building in handling the technologies and creating awareness about the technologies to minimize the expected cost of adaptation are suggested to improve the adoption level.