India, a predominantly rural country, relies on agriculture, with smallholder farmers owning a small portion of cultivable land. Maharashtra, a major cotton-growing region, faces water scarcity and drought events, leading to low crop yields and farmer indebtedness, followed by high suicide rates. Micro irrigation, such as drip and sprinkler systems, can improve water use productivity and mitigate the impacts of climate change on farmers’ incomes and thus livelihoods. Psychosocial factors play a crucial role in farmers’ decisions to adopt irrigation technologies. Incorporating both contextual and psychosocial factors provides deeper insights into the adoption processes of various irrigation systems. The RANAS model has been recognized for behavior change strategies in developing countries and was applied in this research. It integrates psychosocial factors and is used to examine the impact of psychosocial factors on behavioral outcomes. Regression analysis was performed on survey data in order to identify the factors that are assumed to have the ability to explain irrigation and micro irrigation adoption behavior. Four models were created, each focusing on a specific irrigation system: overall uptake, furrow irrigation, sprinkler irrigation, and drip irrigation. This approach allowed for a deeper understanding of the influential factors for different irrigation systems and avoided the generalization of the results. In an attempt to broaden the understanding that can be obtained from regression results, qualitative, open-ended field interviews were conducted with farmers and key informants. The field insights revealed how the local context dynamics influence the factors that have a predictive capability on the adoption of micro irrigation systems. Farmers’ adoption of drip irrigation systems is influenced primarily by their confidence in financial capabilities and technical skills. However, the adoption of sprinkler irrigation systems is more complex. In addition to financial and technical considerations, farmers also consider factors such as easy access to water sources, concerns about future water availability, and descriptive norms, i.e. the actions other farmers take. This indicates that the barrier to adopting drip systems is mainly financial, while the adoption of sprinkler systems also involves to a certain extent normative influence and water-related concerns. The RANAS method is effective in identifying predictive variables for micro irrigation adoption by breaking down the complex problem into manageable components. However, it has limitations. It overlooks the dynamic nature of the adoption process and fails to consider the significance of factors at different stages of behavior change. It also underestimates the role of economic and institutional constraints, which can influence farmers’ investment capacities and perceptions. Additionally, the methods reliance on the design of survey questions may introduce bias and affect the reliability of the interpreted empirical data. Field insights highlight the significance of context-specific factors and the integration of economic capacities in farmers' adoption decisions. Economic stability is crucial for implementing micro irrigation systems, and financially vulnerable farmers may be risk-averse toward new technology. Community support and reduced risk perception can facilitate adoption. Examining profit margins and market prices provides a better understanding of adoption than just income. Considering practical aspects such as crop suitability and awareness of climate change and market dynamics further explain adoption choices. Trust-building is essential to enhance farmers' willingness to adopt irrigation systems.