Flood zones detection using a runoff model built on Hexagonal shape based cellular automata

TL;DR

This paper introduces a 3D GIS-based runoff modeling approach using cellular automata to detect flood zones, aiding urban planning and flood prevention in complex terrains.

Contribution

It presents a novel 3D GIS and cellular automata methodology for flood zone detection, integrating runoff simulation with visualization.

Findings

Effective flood zone detection in a case study area

Reduction of spatial complexity using CA indices

Visualization of runoff dynamics in 3D GIS environment

Abstract

This article presents a 3D geographic information systems (GIS) modeling and simulation of water flow in a landscape defined by a digital terrain model, provided by some available geolocation APIs. The proposed approach uses a cellular automata based algorithm to calculate water flow dynamic. The methodology was tested on a case study area of 27kmx19km located in Tangier, north of Morocco. In fact, we aim to detect flood zones in order to prevent problems related to space occupation in urban and rural regions. Some indices can be deduced from the stream shape using Cellular Automata (CA) based approach that can reduce the complexity related to space structures with multiple changes. A spatiotemporal simulation of the runoff process is provided using 3D visualization that we can pair with geographical information system tools (GIS). The 3D GIS modeling approach that was developed for the analyses of flood zones detection using a runoff model based on cellular automata was comprised of three main steps: Input (collection of data), calculation (CA tool) and visualization (3D simulation).