Optimizing nature-based solutions by combining social equity, hydro-environmental efficiency, and economic costs through a novel Gini coefficient

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Authors

Cyndi Castro 

Abstract

A robust multi-functional decision support system for widespread planning of nature-based solutions (NBSs) must incorporate components of social equity. NBS systems advance social well-being through enhanced levels of greenspace, which have been shown to improve physical health (e.g., heart disease, diabetes), mental health (e.g., post-traumatic stress disorder, depression), and socio-economics (e.g., property values, aesthetics, recreation). However, current optimization frameworks for NBSs rely on stormwater quantity abatement and, to a lesser extent, economic costs and environmental pollutant mitigation. Therefore, the objective of this study is to explore how strategic management strategies associated with NBS planning may be improved, while considering the tripartite interactions between hydrological, environmental, and societal conditions. Here, a large-scale NBS watershed was calibrated to local conditions using standard hydro-environmental modeling (i.e., EPA’s SWMM) and optimized on the basis of stormwater abatement, pollutant load reduction, and economic efficiency. The spatial allocation of possible NBS features was integrated with properties of social equity through a novel framework involving the Area Deprivation Index (ADI) and a composite Gini coefficient. By embedding social equity into the fabric of the NBS planning process, we provide an opportunity for improving social justice and spurring further community buy-in toward a balanced system. This study demonstrates how the optimal spatial placement of NBSs is location-dependent according to both the physical and human properties of the watershed.

DOI

https://doi.org/10.31223/X5HS68

Subjects

Civil and Environmental Engineering, Civil Engineering, Computational Engineering, Engineering, Environmental Studies, Geographic Information Sciences, Geography, Nature and Society Relations, Operations Research, Systems Engineering and Industrial Engineering, Physical and Environmental Geography, Social and Behavioral Sciences, Systems Engineering

Keywords

Gini coefficient, Lorenz curve, Nature-based solutions, water resources planning, multi-objective optimization

Dates

Published: 2021-11-15 11:47

Last Updated: 2021-11-15 16:47

License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data Availability (Reason not available):
The modeling data used for this study is openly available in the Zenodo data repository, DOI: 10.5281/zenodo.5676315.

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