Geo-based model of intrinsic resilience to climate change: an approach to nature-based solution

Riffat Mahmood (), Li Zhang, Guoqing Li and Munshi Khaledur Rahman
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Riffat Mahmood: Chinese Academy of Sciences
Li Zhang: Chinese Academy of Sciences
Guoqing Li: Chinese Academy of Sciences
Munshi Khaledur Rahman: Georgia Southern University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2022, vol. 24, issue 10, No 21, 11969-11990

Abstract: Abstract A substantial amount of researches have been done on the understanding and assessment of resilience from multiple perspectives, e.g., ecological, social, economic, and disaster management; however, recent international approach is trending toward more systematic and comprehensive risk assessment processes. Pivotal element of such approach is to emphasizing on promoting resilience in the face of climate change impacts. Conceptualization and identification of parameters to assess climate change resilience is one of the remaining challenges that academia is facing. Reviewing the principles of the climate change resilience highlighted in the literature, the goal of this study is to introduce a theoretical model about the climate change resilience concept to facilitate and enhance future climate change resilience-related researches. The model proposed in this study is named as the climate change resilience of place (C-CROP) model, a geo-based model which is designed to assess climate change resilience for any geographic region with an approach to the incorporation of nature-based solution (NBS). C-CROP model considers vulnerability, exposure, sensitivity to climate change on one side; another side is co-benefit, climate proofing, and disservices of proposed NBS. An operational framework of the C-CROP model is also proposed, that allows spatially explicit assessment of climate change resilience in real world by developing an indicator-based framework and comprehensive mapping using the geospatial approach. Therefore, this model includes vulnerability hotspots identification; better understanding of the pathways of resilience; and solutions (i.e., NBS) to infer the impacts and effectiveness of resilience-building interventions.

Keywords: C-CROP model; Resilience; Vulnerability; Adaptive capacity; Climate change (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10668-021-01925-9

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