Scalability and Sustainability in Uncertain Environments: Recovery from the Nepal Earthquakes, April 25 and May 12, 2015.

Abstract:

Decision making in disaster recovery involves both rapid scaling up of resources and personnel from external sources, to rebuild a damaged community, and consequent scaling down of this influx of new actors, organizations, and resources as the community returns to daily operations. How to integrate new concepts, technologies, and resources into communities to rebuild the social, economic, and political infrastructure in stronger, more sustainable ways, as well to reconstruct the damaged technical infrastructure represents a challenging set of problems for any community. This problem is critical in environments exposed to recurring risk of interacting hazards that characterize metropolitan regions today. This analysis will examine the process of decision making that is being initiated at national, regional, district, and municipal levels in Nepal following the April 25 and May 12, 2015 Earthquakes as a field study of this process in action. We will build on an initial brief reconnaissance trip to Nepal, June 30 – July 10, 2015, just as response operations were ending and the transition to recovery was beginning. It will capture this transition process to identify the organizational structure through which it operates and the communication and coordination processes that enhance or impede the development of sustainable, disaster-resilient communities as they recover from disaster. We will collect three types of data from different sources, and use appropriate methods of analysis for each type of data. For documentary analysis, we will trace the logic of governmental action for managing risk and recovering from disaster that is stated in public laws, policies, and documents. For electronic media, we will use content analysis to identify key actors, organizations, transactions, and interactions among actors, and conduct a network analysis, using standard measures of centrality, distance, closeness, and clustering. We will use expert interviews and satellite maps to validate findings from other methods of analysis. We anticipate developing a Bayesian Influence Diagram to identify strategies of action and points where the process can be strengthened to achieve the intended results of rebuilding sustainable, disaster resilient communities at different scales of operation in a complex, national system.