ArXiv TLDR

Optimising Urban Flood Resilience

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2604.18620

James Mckenna, Christos Iliadis, Vassilis Glenis

cs.NE

TLDR

A new optimization tool couples a hydrodynamic model with an evolutionary algorithm to efficiently design urban Blue-Green Infrastructure for flood resilience.

Key contributions

  • Presents a novel multi-objective optimization tool for urban Blue-Green Infrastructure (BGI) design.
  • Couples a state-of-the-art hydrodynamic model for accurate property-scale flood vulnerability analysis.
  • Features a bespoke evolutionary algorithm designed to minimize simulations, ensuring computational practicality.
  • Automates BGI design, offering decision-makers optimal solutions for informed investment decisions.

Why it matters

This tool offers a more accurate and efficient way to design Blue-Green Infrastructure, crucial for managing increasing urban flood risks due to climate change. It provides decision-makers with robust, optimized solutions, surpassing limitations of simplified models and traditional design practices.

Original Abstract

Due to the increasing frequency and severity of storm events, driven by the escalation of anthropogenic climate change and urban expansion, there is a requirement for increasingly efficient flood risk management strategies. While Blue-Green Infrastructure (BGI) offers a sustainable solution for managing flood risk, optimal implementation is challenging. To help overcome this challenge, this study presents a novel multi-objective optimisation tool that couples a state-of-the-art hydrodynamic model with a bespoke evolutionary algorithm. The use of a fully dynamic hydrodynamic model enables the tool to accurately evaluate the effectiveness of proposed BGI features with respect to property scale flood vulnerability and hazard analysis. This contrasts with alternative approaches which utilise simplified models, which can only reliably predict inundation extents, thus the proposed optimisation tool provides greater certainty regarding the optimality of the solutions. As a hydrodynamic simulation is required to evaluate each candidate solution, the bespoke evolutionary algorithm is specifically designed to minimise the number of simulations required, ensuring the tool is computationally practical. The effectiveness of the tool in this regard is validated via the derivation of exact convergence measures, for a tractable search space, and via comparisons with benchmark algorithms, for an intractable search space. Compared with traditional design practices, the proposed tool offers an automated approach capable of efficiently exploring a wide range of solutions, providing decision-makers with a set of optimal solutions from which they can make informed investment decisions. The presented methods provide a robust framework for optimising a variety of BGI features in complex urban environments.

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