Development of Resilience Roadmap for Rio Grande Valley
Lead PI:
Ali Nejat

Located along the US-Mexico border in the southeastern corner of the state of Texas, the Rio Grande Valley (RGV), has long experienced major flooding due to its low-lying lands and proximity to the Gulf of Mexico. The flooding problem is rooted in a number of issues across the built, natural, and social environments, including rapid urbanization and associated increase in impervious cover as well as the prevalence of older developments that do not account for hydrology, and unincorporated communities known as colonias that are without drainage infrastructure. These typically low-lying communities, not ideal for residential development, have been home to thousands of families with deep social attachment to place. Despite multiple mitigation efforts by local authorities, the flooding problem persists. Because of future climate variability, flooding events like these are more likely and will continue to present challenges. A lack of a thorough resilience plan and an integrative decision support system to cope with natural and anthropogenic hazards, coupled with insufficient resources, have made the area more vulnerable, particularly to consecutive disasters. This study holistically approaches the flooding problem through convergence research that brings together community stakeholders and an interdisciplinary research team with the objective to develop a resilience roadmap focused on viable adaptation strategies. The project aims to be as inclusive as possible of the community by providing multiple opportunities for community participation in the project ranging from community forums, focus groups, and surveys.

The goal of this planning grant is to establish a foundation for convergence and inclusive problem-solving across researchers, practitioners, and stakeholders through transdisciplinary research aimed at addressing complex problems from the lens of societal needs. This is to be achieved through various community data collection methods from residents and policymakers to collect data on their needs, challenges, priorities, flooding perceptions, and openness to adaptation strategies. Parallel to community survey, technical data related to flooding including morphology of the subsurface will be collected to facilitate analysis of technical feasibility of potential adaptation strategies tailored to community needs as extracted from stakeholder preference analysis. Results from this planning grant would form the foundation for development of a spatially-explicit decision support systems/community adaptation plan capable of integrating climate, hydrology, land use, and socioeconomic data with quantitative models to help decision-makers evaluate flood risks under various future development scenarios and establish a knowledge base that can be used by other regions experiencing rapid urbanization and climate change threats.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Ali Nejat
Ali Nejat is an associate professor of construction engineering at Texas Tech University. Nejat’s research is focused on modeling the dynamics of post-disaster housing and household recovery. His work in developing an agent-based model of collective housing recovery was recognized with a National Science Foundation (NSF) CAREER award in 2015. Nejat's research has been published in various well-known disaster-related social science and engineering journals.
Performance Period: 10/01/2021 - 09/30/2024
Institution: Texas Tech University
Award Number: 2126701