|Cycle 3 (2014 Deadline)
Integrated local emergency response policy improvement and capacity building for advance-early warning system in the face of near-field tsunami risk
U.S. Partner: Louise K. Comfort, University of Pittsburgh
Project Dates: September 2014 to October 2018
Critical Countdown: Using Local Data to improve Tsunami Warnings
This research project will focus on utilization and integration of a logic model and new public management and network to improve the near-shore tsunami early warning system and enhance local emergency response policy. The use of the logic model and new public management in this research project will provide tools for assessing and mapping the cognitive behavior of people during tsunami evacuations, which will help improve tsunami emergency response policy. While utilization of network theory in this research will provide real-time assessment, further research is needed regarding the performance of an early warning system and its subsequent emergency response to a disaster. Such real-time monitoring can be used to improve the performance of evacuation, as well as provide support to disaster victims. The research team will investigate how multiple parties and organizations with a disaster response-related mandate are able to coordinate and cooperate with each other effectively. Utilization of Social Network Analysis (SNA) in this research project will advance the scientific understanding of emergency response operations and evacuation.
The results of this research project are expected to influence and enhance emergency response policy in the study area and can be useful for development of the disaster management sector in Indonesia. The outcomes of this research project are expected to improve the capacity of government officials, non-governmental organizations, and local communities to prepare for and respond to disasters, especially in terms of emergency operation and response, through a combination of technocratic and participatory approaches. Findings and lessons learned from this research can also be transmitted to both the U.S. and global context and can also serve as a model on how to develop an integrated early disaster warning and emergency response.
Overall Summary of Project Activities
|Harkunti P. Rahayu (center) presented results of PEER research at the May 2017 4th Annual Meeting of Indonesian Association of Disaster Experts - Indonesia (photo courtesy of Dr. Rahayu).|
This PEER project achieved significant results and impact at four case study cities (Padang, Pariaman, Agam and Pesisir Selatan) including: updated risk assessment and evacuation plans; revised disaster management plans; and capacity building on preparedness and early warning systems for tsunamis. The team also developed the Social Network Analysis and Logic Model of People’s Cognitive Behavior models to improve downstream warning chains and to provide policy briefs on tsunami disaster risk reduction. The results from the Social Network Analysis model demonstrated that some policies and the initial response capacity of each city/regency were detrimental to the network structure. For instance, the quality of networks in Padang City, which follow its Mayor Regulation 14/2010 that requires public-private cooperation with a media company, are very different from that of the Agam Regency, which did not establish such regulation or cooperation. The research also suggested similarities in terms of a disconnect between (formal) tsunami early warning systems (TEW) and local organizations such as schools, mosques, and Community-based Disaster Preparedness Groups (Kelompok Siaga Bencana/KSBs) that are found across cities/regencies and can have a great impact in tsunami response. Accordingly, the main recommendation from the model in this case is to include those organizations in the city/regency-level policy on tsunami early warning and enhance their capacities to deliver warning information.
The People’s Cognitive Behavior model was developed to improve downstream warning chains and to provide policy briefs on tsunami disaster risk reduction (DRR). The logic model of people’s minds is able to structure all hindering and assisting factors needed to increase people’s ability and willingness to evacuate based on natural phenomena and/or tsunami early warning notifications. Based on the Natural Warning (earthquake reasoning) logic model, the findings found that 35.10 % people prefer immediate over delayed evacuation (34.86%), but 30.04% of people did not want to evacuate at all. The main factor that people considered when debating the evacuations was the difference between the order and method of the planned evacuation (36.65%) versus the vulnerability and chaos (23.11%) of an unplanned evacuation. By combining the Natural Warning and TEW of logic models, the team determined that the knowledge factor was paramount in people’s decision to evacuate immediately (30.34%) while the decision to never evacuate was governed by the reason factor (34.50%). The numerical logic model is able to show the degree of correlation among those factors to achieve the objective of cultural component of TEW. The overall model was able to be used for assessing the level of city preparedness toward tsunamis, as well as for policy development to achieve tsunami preparedness in cities.
The ITB PEER team adopted the above research results to improve the Padang City Mayor Decree on Tsunami Early Warning Systems (Perwako No. 14/2010) and this obtained highest appreciation from PEER’s partners. The key components of this team’s success were: (1) using innovative, holistic and in-depth research approaches; (2) using a participatory approach to engage all related stakeholders during process development; and (3) having opportunity to utilize the Indian Ocean Wave Tsunami Exercise ’16 (IOWave’16) on September 7, 2016 to test the improved standard operating procedure (SOP) of the tsunami early warning system and emergency response of Padang City.
The team’s work directly led to the signing of two MoU’s for disaster mitigation and education between the Padang city mayor and ITB rector, one in December 2016 and the other in January 2015. The lessons learned from this team’s research are excellent and easy to replicate in other tsunami prone cities in Indonesia and other regions. To attract those target cities, the ITB PEER team has documented all process development in the form of technical guidelines and videos for socialization and dissemination. This will allow their research to have a greater impact at both national and regional levels. By developing these videos and guidelines, it is expected that an understanding of how this team’s success was achieved and the lessons learned for SOP improvement on tsunami early warning systems and emergency response will generate global awareness about a need to base disaster risk reduction policy development on scientific research and data.
The replication of this approach to other tsunami-prone cities/regencies in Indonesia will increase the country’s overall disaster resilience toward tsunamis. The multimedia product shows how science answers the challenges of local regions and governments, and how to secure local government and other stakeholders’ commitment towards implementing the research results. Ultimately, this will provide an impact on increasing global awareness of DRR research. In the global context, since Indonesia parallels the US in the field of disaster management, the findings of this research presented in the multimedia can be useful and user-friendly for sector management development in both Indonesia and the US.
Link to news article on the PEER team's field work in West Sumatra in August 2015 (in Bahasa Indonesia)
Link to news article about the team's participation in IOWave'16 and preparatory activities in September 2016 (in English)
Back to PEER Science Cycle 3 Grants