Indexing climatic and environmental exposure of refugee camps with a case study in East Africa

This study presents a novel approach to systematically measure climatic and environmental exposure in refugee camps using remote sensing and geospatial data. Using a case study of seventeen refugee camps across five countries in East Africa, we develop a climatic and environmental exposure index to quantify each camp's exposure relative to a population of simulated camp locations within the hosting country. Our results show that seven of seventeen refugee camps are within the upper two quartiles of exposure relative to a simulated population, suggesting that more than six-hundred thousand refugees living in these camps face elevated exposure compared to other potential camp locations. This method stands to improve the process of gathering and analyzing climatic and environmental data on geographically remote humanitarian spaces in a reliable, low-cost, and standardized manner. Automation and refinement of this index could enable real-time updates on climatic and environmental exposure to support decision-making related to disaster risk reduction in refugee camp management.

Evaluating the usefulness of VGI from Waze for the reporting of flash floods

Using volunteered geographic information (VGI) to supplement disaster risk management systems, including forecasting, risk assessment, and disaster recovery, is increasingly popular. This attention is driven by difficulties in detection and characterization of hazards, as well as the rise of VGI appropriate for characterizing specific forms of risk. Flash-flood historical records, especially those that are impact-based, are not comprehensive, leading to additional barriers for flash-flood research and applications. In this paper we develop a method for associating VGI flood reporting clusters against authoritative data. Using Hurricane Harvey as a case study, VGI reports are assimilated into a spatial analytic framework that derives spatial and temporal clustering parameters supported by associations between Waze’s community-driven emergency operations center and authoritative reports. These parameters are then applied to find previously unreported likely flash flood-events. This study improves the understanding of the distribution of flash flooding during Hurricane Harvey and shows potential application to events in other areas where Waze data and reporting from official sources, such as the National Weather Service, are available.

The effectiveness of forecast-based humanitarian assistance in anticipation of extreme winters: a case study of vulnerable herders in Mongolia

This paper presents evidence relating to a forecast-based cash and non-food item distribution among vulnerable herder households during the 2017-18 dzud (extreme winter) season in Mongolia, and analyses the results of a quasi-experimental study evaluating its impacts. An innovative approach in disaster risk reduction, forecast-based financing (FbF) can have short- and long-term benefits to vulnerable households but remains understudied. The paper contributes information on a multimodal FbF programme offering one-off cash grants and in-kind veterinary kits. The data found significant effects of reduced mortality and increased offspring survival in some types of livestock, and that the timing of FbF assistance is crucial, as reported early assistance correlated to positive outcomes in terms of reduced animal mortality. These findings can be used to design more effective FbF interventions, to understand better the appropriateness of FbF designs, and to use early warnings and early actions to help people prepare and withstand disasters such as dzuds.

Multiple Hazard Uncertainty Visualization Challenges and Paths Forward

Making decisions with uncertainty is challenging for the general public, policymakers, and even highly trained scientists. Nevertheless, when faced with the need to respond to a potential hazard, people must make high-risk decisions with uncertainty. In some cases, people have to consider multiple hazards with various types of uncertainties. Multiple hazards can be interconnected by location, time, and/or environmental systems, and the hazards may interact, producing complex relationships among their associated uncertainties. The interaction between multiple hazards and their uncertainties can have nonlinear effects, where the resultant risk and uncertainty are greater than the sum of the risk and uncertainty associated with individual hazards. Effectively communicating the uncertainties related to such complicated systems should be a high priority because the frequency and variability of multiple hazard events due to climate change continue to increase. However, the communication of multiple hazard uncertainties and their interactions remains largely unexplored. The lack of practical guidance on conveying multiple hazard uncertainties is likely due in part to the field’s vast expanse, making it challenging to identify entry points. Here, we offer a perspective on three critical challenges related to uncertainty communication across various multiple hazard contexts to galvanize the research community. We advocate for systematic considerations of multiple hazard uncertainty communication that focus on trade-offs between complexity and factors, including mental effort, trust, and usability.