Risk management and climate adaptation literature focuses mainly on reducing the impacts of, exposure to, and vulnerability to extreme events such as floods and droughts. Posttraumatic stress disorder is one of the most important impacts related to these events, but also a relatively under‐researched topic outside original psychopathological contexts. We conduct a survey to investigate the mental stress caused by floods. We focus on hydrological, individual, and collective drivers of posttraumatic stress. We assess stress with flood‐specific health scores and the GHQ‐12 General Health Questionnaire. Our findings show that the combination of water depth and flood velocity measured via a Hazard Class Index is an important stressor; and that mental health resilience can be significantly improved by providing the population with adequate information. More specifically, the paper shows that psychological distress can be reduced by (i) coordinating awareness of flood risks and flood protection and prevention behavior; (ii) developing the ability to protect oneself from physical, material and intangible damage; (iii) designing simple insurance procedures and protocols for fast recovery; and (iv) learning from previous experiences.

We analyse the way French farmers manage production risks, especially the risk of drought. To this end, we assess the role of irrigation in farmers’ risk management. Based on the European Farm Accountancy Data Network data, we jointly estimate farmers' attitudes to risk and their production decisions. We correct for sample selection bias and endogeneity. Results of the probit model show that irrigation technology serves as a self-insurance. Results of the joint estimation show that irrigating farmers have higher means but lower variance of profits than non-irrigating farmers. However, for already irrigating farmers, using more water volumes increases the variance of outcome.

By aggregating semi‐quantitative mind maps from multiple agents, fuzzy cognitive mapping (FCM) allows developing an integrated, cross‐sectoral understanding of complex systems. However, and especially for FCM based on individual interviews, the map‐building process presents potential pitfalls. These are mainly related to the different understandings of the interviewees about the FCM semantics as well as the biases of the analyst during the elicitation and treatment of data. This paper introduces a set of good practice measures to increase transparency and reproducibility of map‐building processes in order to improve credibility of results from FCM applications. The case study used to illustrate the proposed good practices assesses heatwave impacts and adaptation options in an urban environment. Agents from different urban sectors were interviewed to obtain individual cognitive maps. Using this set of data, we suggest good practices to collect, digitalize, interpret, pre‐process and aggregate the individual maps in a traceable and coherent way. © 2018 The Authors Systems Research and Behavioral Science published by International Federation for Systems Research and John Wiley & Sons Ltd