A CHANS Approach to Investigating Post-Disaster Recovery Potential in Rural Japan

Jessica Ann Diehl, Kazuo Asahiro, Yun Hye Hwang, Taiga Hirashima, Lingchang Kong, Zhe Wang, Haomu Yao, Puay Yok Tan

Research output: Contribution to journalArticlepeer-review

Abstract

Natural disaster recovery is a critical issue in rural Japan, yet repairing infrastructure, stabilising landscapes, and aiding those displaced is exceedingly expensive. Restoration of disaster affected landscapes mainly focuses on infrastructure repair, with less attention to socio-ecological activities pre-and post-disaster. The absence of integrated socio-ecological perspectives to disaster restoration creates missed opportunities for approaches more sensitive to local needs and resources. Coupled human and natural systems (CHANS) frameworks attempt to bridge social and natural sciences with the effect that interactions between human and natural systems can emerge that might not be apparent by studying them separately. However, application of CHANS frameworks in the context of natural disaster recovery in rural Japan is limited, and more consideration of the challenges is needed. The aim of this paper is to describe the design of a CHANS project and summarize lessons learned in applying this complex framework. The CHANS project comprised four graduate student projects investigating different topics related to landslide recovery and future disaster vulnerability after the Northern Kyushu Heavy Rainfall in July 2012 event in rural Japan. For lessons learned, we suggest CHANS projects to be designed as a nested hierarchy of research questions, aims, objectives, and hypotheses to enable deeper synthesis at a higher level. Despite limitations in the design of our CHANS project, triangulation of data enabled us to conclude meaningful findings. When faced with limited resources, it is impossible to design a complex study accounting for all relevant factors, but a CHANS approach can enable integrated socio-ecological insights and foster innovative solutions for improving resource management and cost-effectiveness of disaster recovery plans.

Original languageEnglish
Pages (from-to)453-463
Number of pages11
JournalJournal of Disaster Research
Volume17
Issue number3
DOIs
Publication statusPublished - 2022

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Engineering (miscellaneous)

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