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Under climate change, sea-level rise and increasing storm surge intensity will increase the likelihood of floods for low-lying coastal areas. Therefore, Coastal Flood Vulnerability Assessments (CFVA) are necessary to inform decision making for coastal management, where applicable. Two types of tools, hydrodynamic models and Geographic Information Systems (GIS), are commonly employed for these evaluations. Using Pigeon Point, Southwest Tobago, as a case study, this paper compares the application of both to determine the best approach for CFVA that can be used to guide coastal management. For hydrodynamic modelling, available and surveyed data on bathymetry, topography and tides along with current and future estimates of mean sea-level were used to create a structured and an unstructured grid model via the LISFLOOD-FP and TELEMAC-2D codes, respectively. For the GIS assessment, a coastal digital elevation model was developed using the same data on bathymetry and elevation. These models were used to project the present and future impact of storm surges on coastal flood extent at Pigeon Point. Outputs generated were compared and analysed within a GIS. Using predictions from TELEMAC-2D (full shallow water equations) as the baseline for comparison, average results acquired revealed that projections generated by all three models were consistent (less than 5.00% difference in flood predictions). To add certainty to the modelling results, all models were used to simulate an observed spring high tide event for model validation purposes. The Root Mean Squared Error (RMSE) was calculated as an indication of model performance. RMSE values indicated that all models were consistent and matched well to the field observations. However, further analysis revealed that inherent in the use of GIS for CFVA is hydraulic connectivity issues due to exclusion of flow dynamics, which leads to over-estimation in flood extent. Acknowledging the theory that over-estimation leads to over-management, it is suggested that hydrodynamic models are better suited for detailed CFVA, while GIS can be used rapidly as a potential indicator of flood exposure for large sites. [ABSTRACT FROM AUTHOR]

This paper examines whether the application of spatially-distributed versus static friction in hydrodynamic modelling increases the accuracy of predicted coastal flood extent using Pigeon Point, southwest Tobago, as a case in point. A two-dimensional hydrodynamic flood model is created from acquired and surveyed bathymetric, topographic and tidal data via the LISFLOOD-FP model code. Using a Landsat 8 image of the study area, a Maximum Likelihood (ML) supervised classification was performed to distinguish different land cover classes within the study site. The classified Landsat 8 image was further processed by assigning friction values to each land cover class to create a spatially-distributed friction file in ASCII format for use in LISFLOOD-FP. Using the flood model developed, simultaneous simulations were performed to assess the impact of storm surges (varying levels) on coastal flood extent at Pigeon Point utilising a static friction value, which broadly defined the area (i.e., 0.02), and the spatially-distributed friction file generated. Model outputs were compared to determine the extent of difference in flood prediction obtained from the application of static versus spatially-distributed friction through a Geographic Information System (GIS) based analysis. The flood model developed was subsequently applied to simulate an observed spring tide event using both static and spatially-distributed friction value(s) defined and model performance in each case was evaluated using the Root Mean Squared Error (RMSE) approach. Collated results indicated that using spatially-distributed over static friction do not increase accuracy of predicted coastal inundation extent, nor improve model performance. However, it appears to provide more insight on flood timings, which can be useful for coastal management. [ABSTRACT FROM AUTHOR]