This paper presents the validation of the End Point Rate (EPR) tool for QGIS (EPR4Q), a tool built-in QGIS graphical modeler for calculating the shoreline change with the end point rate method. The EPR4Q tries to fill the gaps in user-friendly and free open-source tools for shoreline analysis in a geographic information system environment since the most used software—Digital Shoreline Analysis System (DSAS)—although being a free extension, it is created for commercial software. Additionally, the best free, open-source option to calculate EPR is called Analyzing Moving Boundaries Using R (AMBUR); since it is a robust and powerful tool, the complexity can restrict the accessibility and simple usage. The validation methodology consists of applying the EPR4Q, DSAS, and AMBUR with different types of shorelines found in nature, extracted from the US Geological Survey Open-File. The obtained results of each tool were compared with Pearson’s correlation coefficient. The validation results indicate that the EPR4Q tool acquired high correlation values with DSAS and AMBUR, reaching a coefficient of 0.98 to 1.00 on linear, extensive, and non-extensive shorelines, proving that the EPR4Q tool is ready to be freely used by the academic, scientific, engineering, and coastal managers communities worldwide.

The high energetic wave climate of the North Atlantic Ocean causes important morphological changes at Figueira da Foz coastal system (W Portugal), which is comprised of sandy beaches and the Mondego estuary-inlet. The submerged sandbar at the inlet mouth is highly dynamic inducing short waves shoaling and breaking processes that can entail navigation problems towards the local harbor. Therefore, coastal dredging operations are performed to guarantee safe navigation. Nevertheless, these operations have a limited temporal effectiveness and require a high annual budget to be accomplished. The goal of this research is to seek long-life dredging alternatives using modeling tools (i.e., Delft3D model suite). Delft3D model is used to simulate the morphological evolution of five dredging scenarios during a three-month winter period under three wave climate scenarios. The bed level differences at the dredged area and at the inlet mouth for each scenario are analyzed in comparison with numerical solutions obtained in a reference scenario (i.e., no-dredging). Results highlight morphological changes at the dredged inlet and surrounding areas and their effectiveness in extending the operational lifetime of inlet dredged operations on dredging configuration and wave climate conditions. These findings are the basis for selecting the most suitable dredging scenario to this coastal region under current wave climate conditions.

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of free and open-source models to estimate the sea-level impact can contribute to improve coastal management. This study aims to develop and validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE)—a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the sea-level rise impact module of TerrSet—Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses the Bruun rule formula implemented in GEE and can determine the coastline retreat of a profile by creatting a simple vector line from topo-bathymetric data. The model shows a very high correlation (0.97) with a classical Bruun rule study performed in the Aveiro coast (NW Portugal). Therefore, the achieved results disclose that the GEE platform is suitable to perform these analysis. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific community.