Understanding the decision-making process in disaster risk monitoring and early-warning: A case study within a control room in Brazil

Abstract

warwick.ac.uk/lib-publications A B S T R A C TThe tasks of disaster risk monitoring and early warning are an important means of improving the efficiency of disaster response and preparedness. However, although the current works in this area have sought to provide a more accurate and better technological infrastructure of systems to support these tasks, they have failed to examine key features that may affect the decision-making. In light of this, this paper aims to provide an understanding of the decision-making process in control rooms for disaster risk monitoring and early warning. This understanding is underpinned by a conceptual framework, which has been developed in this work and describes factors that influence the decision-making. For doing so, data were collected through a series of semi-structured interviews and participatory observations and later evaluated with members of the control room of the Brazilian Center for Monitoring and Early Warning of Natural Disasters (Cemaden). The study findings provided a solid basis for designing the conceptual framework of the essential factors required by the decision-makers. These factors are separated into two groups: 1) the "dimensions" of decision-making (i.e., the type of hazard, the phase of the disaster risk, the location, and area of expertise of the operators) and the "pillars" of decision-making (i.e., the tasks, their required information, useful data sources, and the decision rule). Finally, the contributions achieved in this study may help operators to understand and propose proactive measures that could improve their decision-making, overcome uncertainties, standardize the team's decision-making, and put less pressure on operators.

“What is a Sociologist Doing Here?” An Unconventional People-Centered Approach to Improve Warning Implementation in the Sendai Framework for Disaster Risk Reduction

“…(3) partnerships with federal, state, and local agencies to exchange environmental data and information were formed; (4) computer scientists also developed a GIS visualization platform to receive these kinds of data; (5) people were hired to work in the monitoring room and to be part of the decisionmaking process in the warning chain, which also includes civil protection units at the federal, state, and municipal levels, as well as at-risk communities; (6) protocols for this warning chain were also necessary, especially because the roles and responsibilities of the organizations were not clear-the competition between governmental agencies (Lund 2006) was real; and (7) capacity building tutorials and educational materials on warning system implementation at local level were recognized as important, but there is no consensus about who is responsible for engaging people in warning system. Many of these steps and tasks were recommended in the warning system checklists published by the United Nations International Strategy for Disaster Reduction (UNISDR 2006a) and the World Meteorological Organization (WMO 2018); some barriers for their implementation were sporadically researched using questionnaires and interviews (Lumbroso et al 2016;Horita et al 2017Horita et al , 2018, but not the everyday practices and discourses of warning implementation during a period of time, as institutional ethnography permits. This article contributes to this debate, providing insights about the means of implementation of warning systems (Zia and Wagner 2015).…”

A Review of Studies on Participatory Early Warning Systems (P-EWS): Pathways to Support Citizen Science Initiatives

“…According to the authors, there are practical EWS participatory experiences reporting that rainfall data collected by communities are not being stored by the Meteorological Services (Šakić Trogrlić et al, 2017). In the same manner, Horita et al (2018), through a qualitative analysis of decision-making in monitoring control room, showed the importance of data from the communities as a supplementary source of information. This is more relevant and important when official data sources are insufficient, non-existent, or not well calibrated, which thus may lead to "operators deciding 'in the dark' without knowing the 'real' situation in the area; this occasionally may lead to devastating consequences due to a wrong decision" (Horita et al, 2018, p. 29).…”

Decision Making in Disaster Management Cycle of Natural Disasters: A Review

“…(Landry et al, 2016) Earthquake Nepal Lessons learned by decision-makers to be prepared and make the right decisions to avoid future complications. (Horita et al, 2018) All disasters Brazil The implementation of the control room in Brazil allows for structured decisions based on facts which resulted in good implication on the disaster system analysis system that followed. (Shafiai, 2016) Flood Malaysia Preparation for floods, current and post-flooded structured and structured decisions such as simulation exercises and inter-agency co-operation, facilitates the decisions that will be made during and after floods.…”

“…If the context or boundary of the decision making is fixed or where previous experience contributed to a more certain environment, then a structured type decision making can occur. This can be seen in the case of disaster management from within a control room in Brazil for various natural disasters (Horita et al, 2018). Structured decisions are made by the bottom management by confirming that each element is in accordance to the standard operation that has been outlined to decide whether it is indeed a disaster event.…”

“…Open Access: e-Journal authorities where subsequent outcome is faster response capabilities of rescue agencies and communities following accurate information (Horita et al, 2018). Another circumstance is when from previous experience the situation is more certain and predictable as in the case of three disaster events i.e.…”