IAHS2022-257, updated on 22 Sep 2022
IAHS-AISH Scientific Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Water resources management as a coupled hydro-environmental and social-equity-based optimization framework

Cyndi Vail Castro
Cyndi Vail Castro
  • University of Illinois at Urbana-Champaign, Department of Civil & Environmental Engineering, Urbana, IL, United States of America (cynthiavail11@gmail.com)

Nature-based solutions (NBSs) use earthen materials to mimic natural stormwater flow by increasing levels of greenspace within the built environment. Research has demonstrated the capability of NBSs to address overlapping issues of societal well-being, including improvements in mental and physical health, social vulnerability, sense of well-being, and socio-economics. However, existing NBS planning frameworks emphasize hydro-environmental modeling and cost-benefit analysis for regional spatial allocation. Social conditions are only incorporated at preliminary planning stages through visualization of geospatial hotspots and are not embedded directly within the optimization model. By relying on metrics of hydro-environmental mitigation, the unique spatial exposures of social deprivation that could benefit from NBSs are not well-captured. Water dynamics and social well-being are highly entangled, and we necessitate improved methods for combining hydrological and social characteristics in a robust manner. Here, a novel framework is proposed and demonstrated that integrates hydro-environmental modeling, economic efficiency, and social deprivation using a dimensionless Gini coefficient. Hydro-environmental risk and social disparity are combined within a common measurement unit to capture variation across spatial domains and to optimize fair distribution across the study area. Advances in neighborhood-scale datasets for measuring social deprivation are leveraged to improve fundamental, multi-objective planning in human-water systems. A case study in the White Oak Bayou watershed in Houston, Texas, USA is used to demonstrate how the optimal spatial allocation of NBSs is location-dependent with varying tradeoffs amidst overlapping goals (e.g., stormwater runoff mitigation, water quality abatement, economic efficiency, and equity-based allocation). The composite Gini coefficient demonstrates how water resources planning may be addressed as a holistic system of human-water phenomena to minimize tradeoffs across disparate domains while improving social justice.


How to cite: Vail Castro, C.: Water resources management as a coupled hydro-environmental and social-equity-based optimization framework, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-257, https://doi.org/10.5194/iahs2022-257, 2022.