Dynamic Evacuation Route Planning for Flood-Prone Coastal Odisha Using GIS and Least-Cost Path Analysis
Abstract
Objectives: To evolve suitable approach for developing dynamic flood evacuation plans to overcome the shortcomings of traditional static evacuation planning in the studied area. Method: Due to its high vulnerability to flooding and storm surges of the Baitarani River, and because of frequent occurrence of cyclones and river floods, the Bhadrak district of Odisha state was selected as the study site. An innovative GIS-based flood evacuation route planner model was proposed for generating dynamic flood evacuation routes. This new flood evacuation route planner makes use of the A* least-cost path (LCP) algorithm using a composite cost function involving flood depth, digital elevation model (DEM), road accessibility, and land-cover friction. This dynamic model was assessed for its performance under four hazard scenarios: Dry Baseline, Baitarani River Spillages, Cyclone Yaas Storm Surge, and Systemic Extreme Catastrophe. In addition, several sensitivity analysis studies were conducted to investigate the impact of the accessibility of shelters and the effect of spatial factors on evacuation performance. Findings: The devised route planner effectively adapts itself to all of the hazard scenarios, including the highly risky Systemic Extreme Catastrophe scenario, where it is able to come up with feasible detours for evacuation even with 33.72% reduction in route safety certainty and a greater than 300% rise in travel time when compared to the Dry Baseline scenario. Sensitivity analysis showed that terrain elevation is the key factor affecting the route safety, accounting for variability of up to 15%, while flood hazard distance comes second. Novelty: This study presents a novel dynamic GIS-based approach to creating flood evacuation routes using the A* Least Cost Path algorithm together with a multi-criteria cost function. Different from other static approaches to flood evacuation routing, this framework dynamically reacts to the hazard situation and creates adaptive safe routes for evacuation, thus being an applicable decision-support system for disaster risk management. Keywords: Flood Evacuation Planning, Geographic Information Systems (GIS), A* Algorithm, Multi-Criteria Decision Analysis (MCDA), Least Cost Path, Compound Flooding, Disaster Risk Reduction