Adaptive agglomeration: Endogenous growth under planned flood retreat and re-urbanization

This project integrates fluvial flood risk projections (Yin et al., 2021) with urban growth modeling insights (Sheladiya & Patel, 2023) and remote sensing/GIS capabilities (El Gayar & Singh, 2024) in a spatial endogenous growth model where knowledge spillovers depend on urban form and connectivity. It compares three regimes: no retreat, uncoordinated retreat, and planned “adaptive agglomeration” that seeds new innovation hubs in safer zones with transit-oriented development and digital infrastructure. Unlike most assessments that tally flood damages as lost output/capital, this project asks if early, coordinated relocation can create productivity surges through modernized infrastructure and improved network topology—an unexpected upside channel. It leverages out-of-equilibrium macro dynamics to analyze transition paths, defaults, and public finance. Calibration uses country cases from Yin et al. (2021), with simulations of alternative spatial policies. Remote sensing validates changes in nighttime lights and land use post-relocation. The model endogenizes learning-by-doing in low-carbon transport networks to capture dynamic efficiency gains. This reframes adaptation as potentially growth-enhancing under the right spatial and financial architecture (e.g., green bonds targeted to new hubs). The impact is a rigorous case for “build back smarter, elsewhere” policies and quantifies when planned retreat yields higher long-run growth and lower risk-adjusted financing costs than defending in place.

References:

1. Assessing the economic impacts of future fluvial flooding in six countries under climate change and socio-economic development. Zhiqiang Yin, Yixin Hu, K. Jenkins, Yi He, Nicole Forstenhäusler, R. Warren, Lili Yang, Rhosanna Jenkins, D. Guan (2021). Climatic Change.
2. Leveraging Urban Growth Models (UGM) for Sustainable Urban Planning and Climate Resilient Cities: A Bibliometric Analysis. K. P. Sheladiya, Chetan R. Patel (2023). Journal of Scientometric Research.
3. Remote sensing and GIS application in agriculture and natural resource management economics. Attia El Gayar, Joginder Singh (2024). International Journal of Agricultural Invention.