Framing VRRSability Relationships among Vulnerability, Risk, Resilience, and Sustainability for Improving Geo-Information Evaluations within Geodesign Decision Support

Author:

Nyerges Timothy1,Gallo John A.2ORCID,Reynolds Keith M.3ORCID,Prager Steven D.4ORCID,Murphy Philip J.5ORCID,Li Wenwen6ORCID

Affiliation:

1. Department of Geography, University of Washington, Seattle, WA 98195, USA

2. Conservation Biology Institute, Corvallis, OR 97333, USA

3. US Department of Agriculture, Forest Service Research, Corvallis, OR 97331, USA

4. Bill & Melinda Gates Foundation, Seattle, WA 98109, USA

5. Info Harvest, Inc., Seattle, WA 98165, USA

6. School of Geographical Science and Urban Planning, Arizona State University, Tempe, AZ 85287, USA

Abstract

Improving geo-information decision evaluation is an important part of geospatial decision support research, particularly when considering vulnerability, risk, resilience, and sustainability (V-R-R-S) of urban land–water systems (ULWSs). Previous research enumerated a collection of V-R-R-S conceptual component commonalties and differences resulting in a synthesis concept called VRRSability. As a single concept, VRRSability enhances our understanding of the relationships within and among V-R-R-S. This paper reports research that extends and deepens the VRRSability synthesis by elucidating relationships among the V-R-R-S concepts, and organizes them into a VRRSability conceptual framework meant to guide operationalization within decision support systems. The core relationship within the VRRSability framework is ‘functional performance’, which couples land and water concerns within complex ULWS. Using functional performance, we elucidate other significant conceptual relationships, e.g., scale, scenarios and social knowledge, among others. A narrative about the functional performance of green stormwater infrastructure as part of a ULWS offers a practical application of the conceptual framework. VRRSability decision evaluation trade-offs among land and water emerge through the narrative, particularly how land cover influences water flow, which in turn influences water quality. The discussion includes trade-offs along risk–resilience and vulnerability–sustainability dimensions as key aspects of functional performance. Conclusions include knowledge contributions about a VRRSability conceptual framework and the next steps for operationalization within decision support systems using artificial intelligence.

Publisher

MDPI AG

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