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Sustainable engineering decisions toward nature-based solutions for flood protection infrastructure: An integrated system dynamics framework

  • University of New Hampshire
  • Stony Brook University

Research output: Contribution to journalArticlepeer-review

Abstract

Flood protection infrastructure is increasingly challenged by aging systems, climate impacts, and public expectations for environmentally conscious design. Although innovative approaches such as nature-based solutions (NBS) can enhance long-term reliability, ecosystem health, and community resilience, their adoption remains limited. Engineering decisions are still dominated by technical and regulatory constraints, with limited attention to behavioral and organizational factors. This study addresses this gap by developing an integrated system dynamics model (SDM) grounded in the Value-Belief-Norm (VBN) framework, Bass innovation diffusion, and information cascade theories. Using a mixed-methods approach, interviews and surveys with U.S. engineers, key behavioral drivers were identified. These insights were translated into feedback structures to simulate long-term changes in engineering norms and decisions as drivers to infrastructure reliability. Scenario analyses reveal that stronger community engagement, supportive policies, and enhanced collaboration accelerate NBS adoption and reduce resistance over time. Conversely, weak institutional support and conservative norms hinder transitions and reinforce eco-skeptical attitudes. The SDM-driven framework provides a dynamic lens through which cognitive and organizational factors in sustainable infrastructure transitions can be examined together, offering a foundation for evidence-based policy design, professional training, and data-driven model calibration.

Original languageEnglish
Article number112858
JournalReliability Engineering and System Safety
Volume276
DOIs
StatePublished - Dec 2026

Keywords

  • Engineering decisions
  • Flood protection infrastructure
  • Nature-based solutions
  • Risk perception
  • System dynamics modeling
  • Value-Belief-Norm theory

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