Application of LiDAR-Derived Data using Multi-Criteria Evaluation (MCE) and Stochastic Modelling; A Flood Risk Analysis of the Mersey River, Nova Scotia

Abstract

The Maritime province of Nova Scotia has seen coastal flooding become a more frequent phenomenon during the past decades due to the changing climate regime. This has influenced the interest provincial and federal governments have in flood risk modelling, who often incorporate Geographic Information Systems (GIS) as useful tools in their analysis. Incorporating LiDAR-derived digital elevation models (DEMs) in their workflows is the next step in hydrological analysis, as LiDAR-derived DEMs offer high resolution data for the analysis of flood risk without the need to rely on biotic or hydrological data. This study aims to follow this theme in order to model the effects of inland flooding in the low relief landscape of the Mersey River, located in Queen’s County, Nova Scotia, and its effects on the infrastructure built along the river network. The analysis included multi-criteria evaluation (MCE) methods coupled with a stochastic simulation approach in order to determine areas where vulnerability is the most certain. Results indicated that high flood risk is present in urbanized areas within 1 km of the Mersey River at a low degree of uncertainty, making them the best candidates for flood-preventive measures. The accuracy provided by LiDAR-derived DEMs supported a high-quality workflow for the MCE and DEM error analysis, proving their utility for floodplain delineation. The addition of historical and hydrological data to future projects could build on the results presented in this study, adding more to the literature on flood risk modelling along the Mersey River.