Natural disasters are too often presented as resulting from extreme natural phenomena affecting helpless populations, with people being insufficiently aware of the factors leading to disasters and of the existing strategies to mitigate their impacts. We developed a board game aimed at raising awareness about geohazards and disaster risk reduction strategies. The target groups are (1) secondary school students and citizens and (2) scientists and stakeholders involved in risk management activities. For the first group, the aim is to induce a better understanding of the geohazards and disasters they are confronted with in the media or in their daily lives; for the second, the objective is to generate discussion about risk management strategies. The game was tested with students in Belgium and with citizens, earth scientists, and risk managers in several African countries. Based on analysis of the most common game strategies observed, the players' reactions during the game, and their answers to a short questionnaire, we analyzed the main learning outcomes conveyed by this game. The game Hazagora appears to positively enhance the players' insights into processes involved in disasters. As such, the game is an effective, fun learning tool to introduce participants to the concepts of geohazards and disasters and to generate discussion.

Accurate precipitation data are fundamental for understanding and mitigating the disastrous effects of many natural hazards in mountainous areas. Floods and landslides, in particular, are potentially deadly events that can be mitigated with advanced warning, but accurate forecasts require timely estimation of precipitation, which is problematic in regions such as tropical Africa with limited gauge measurements. Satellite rainfall estimates (SREs) are of great value in such areas, but rigorous validation is required to identify the uncertainties linked to SREs for hazard applications. This paper presents results of an unprecedented record of gauge data in the western branch of the East African Rift, with temporal resolutions ranging from 30 min to 24 h and records from 1998 to 2018. These data were used to validate the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) research version and near-real-time products for 3-hourly, daily, and monthly rainfall accumulations, over multiple spatial scales. Results indicate that there are at least two factors that led to the underestimation of TMPA at the regional level: complex topography and high rainfall intensities. The TMPA near-real-time product shows overall stronger rainfall underestimations but lower absolute errors and a better performance at higher rainfall intensities compared to the research version. We found area-averaged TMPA rainfall estimates relatively more suitable in order to move toward regional hazard assessment, compared to data from scarcely distributed gauges with limited representativeness in the context of high rainfall variability.

Based on a literature review and two case studies, this article presents the difficulties inherent in the main disaster risk reduction conceptual models. The method used to highlight such evidence is to compare two programs on disaster risk reduction with mainstream conceptual models. The authors participated in these programs, which were confronted with the need to integrate contributions and insights from both earth and social sciences. Our analysis found that the existing main conceptual models were unable to do justice to disaster risk reduction needs. This finding encouraged us to critique these models. Further effort led us to present possible solutions to compensate for the shortcomings of current models while taking into account the contextualization and dynamics of phenomena, as well as grappling with the more explicit integration of hazards and hazard risk into model design.