Water scarcity is one of the most critical issues facing agriculture today. To understand how people manage the risk of water scarcity and growing pressures of increased climate variability, exploring perceptions of risk and how these perceptions feed into response behaviour and willingness to adapt is critical. This paper revisits existing frameworks that conceptualise perceptions of environmental risk and decision-making, and uses empirical evidence from an in-depth study conducted in Rajasthan, India, to emphasise how individual and collective memories, and experience of past extreme events shape current definitions and future expectations of climatic risks. In doing so, we demonstrate the value of recognising the role of local perceptions of water scarcity (and how they vary between and within households) in constructing social vulnerability. This expanded understanding of risk perception is critical for incentivising individual adaptation and strengthening local adaptation pathways.

This article explores intra‐household decision‐making in smallholder farmers' innovation uptake and use of outputs within a bargaining framework. Research was conducted in selected locations representing contrasting economic, social and agroclimatic environments in Uganda using a combination of qualitative and quantitative methods (including a survey of 531 farmers). Decision‐making in innovation processes was highly gendered and shaped by intra‐household allocation of production assets as well as social norms. The findings highlight the male capture of decision‐making regarding innovation uptake and use of outputs, especially for income‐generating crops, and that this can both reflect and reinforce gender inequalities in asset ownership. © 2020 The Authors. Journal of International Development published by John Wiley & Sons Ltd

Climate change and variability presents a challenge for rural communities in developing countries. Bridging organizations help align stakeholder and local perspectives and mediate communication that shapes adaptation responses. We argue that a first step for adaptation projects is to determine the nature of the climate norms and how climate is changing. This paper explores the degree to which development organizations in Kenya, Uganda and Tanzania used analysis of local historical climate information in project aims, planning and design. This included 67 participants, managing 102 community-level climate-related agricultural projects, and three NGO case studies. Most focused on low-regret options. The majority of projects enhanced awareness of climate change and variability, but only 7% had used historical climate information during planning. Instead, projects relied on general knowledge or farmers’ perceptions, which sometimes differ from analyzed historical climate information, potentially leading reinforcement of perceptions. It is vital that bridging organizations and policy makers value analyzed historical climate information when determining climate norms (including variability) and identify what data shows regarding how climate is changing. This is essential for planning with stakeholders the suitability of alternative crops and cultivars and ensuring other relevant environmental factors influencing agricultural production are considered.

SUMMARY: In order to identify factors that constrain or favour adoption of five crop or forage related and six animal husbandry technologies promoted by government to small-scale dairy farmers, a field survey was conducted with 115 farmers. A binary logistic regression model was fitted to identify socioeconomic and farm variables explaining the technology adoption. Factors that favoured technology adoption were based on perceived usefulness, productivity and benefits to the farm, farmer's skills and farm characteristics; moreover farmers were more willing to use technologies which required low levels of investment such as de-worming, vaccines, and data recording. Constraints were related to economic restrictions, lack of knowledge, lack of land, herd size, lack of extension advice, lack of information about government programmes, requirements associated with applying for government financial support, and technologies considered to be of little or no importance to the farm such as herbicides, artificial insemination (AI) and milking machines. Adoption of crop or forage related and animal husbandry technologies was significantly associated (p < 0.05) with socioeconomic (farmer's education, farmer's experience, farmer's wealth status) and farm characteristics (herd size, cows in production, milk yield, total hectares and technological level). It is concluded that the approach implemented in this study enables identification of key factors together with the communication approaches that have been successful.