Study of the Effect of an Environmentally Friendly Flood Risk Reduction Approach on the Oman Coastlines during the Gonu Tropical Cyclone (Case Study: The Coastline of Sur)

Abstract

Tropical cyclones may be destructive in the coastal region, such as the Gonu tropical cyclone, which affected the Arabian Peninsula and parts of southern Iran in 2007. In this study, a coupled MIKE 21/3 HD/SW (hydrodynamic/spectral wave) model was used to simulate the inland flooding inside the Sur port during the Gonu tropical cyclone. The MIKE 21 Cyclone Wind Generation (CWG) tool was utilized to generate the cyclone’s wind and pressure field. The required input data were obtained from the International Best Track Archive for Climate Stewardship (IBTrACS) and imported into the CWG tool. In this study, the wind and pressure fields were compared between the analytical vortex model and European Centre for Medium-Range Weather Forecasts (ECMWF) data during the Gonu cyclone passage. Moreover, by developing a new model, artificial Mangroves’ effect on inland flooding was investigated. The results show that, contrary to the ECMWF data, the analytical vortex models well captured the storm event’s wind and pressure field. Furthermore, the flood hazard is calculated based on the inundation depth, flow velocity, and area’s vulnerability. The flood hazard map shows that 5% of the coast is at high-risk, 49% is at medium-risk, and 46% is at low-risk class in the Sur port. By applying Mangroves as flood risk reduction, the high-risk area is almost completely removed. However, medium and low-risk zones increase by 50% and 50%, respectively. This information could be helpful in disaster risk reduction and coastal management in the future.

Spatial Analysis and Risk Evaluation for Port Crisis Management Using Integrated Soft Computing and GIS-Based Models: A Case Study of Jazan Port, Saudi Arabia

“…By assessing the liability for major accidents in specific regions of a port, researchers seek to delineate zones of extreme risk, high risk, medium risk, and low risk, providing decision makers with a nuanced understanding of the spatial distribution of vulnerabilities [19]. In recent years, the integration of soft computing techniques and geographic information system (GIS)-based models has emerged as a promising approach to enhance the effectiveness of spatial analysis and risk evaluation in port management [20,21].…”

Evaluation of Hybrid Soft Computing Model’s Performance in Estimating Wave Height

“…Given the capabilities of mathematical models with the help of numerical simulation, using these methods in predicting wave properties at sea is appropriate. Since the forecast wave parameters are essential for the design of coastal structures and for naval operations, diferent methods such as semiempirical methods such as Coastal Engineering Manual (CEM) and Sverdruv Munk Bretschneider (SMB) and numerical models such as MIKE21, Wavewatch III, and SWAN were used [22,23]. Soft computing methods such as Artifcial Neural Networks (ANNs), fuzzy inference systems, decision trees, and genetic algorithms are also used.…”

Novel Ocean Wave Height and Energy Spectrum Forecasting Approaches: An Application of Semi-Analytical and Machine Learning Models

“…However, numerical models have been developed to predict wave characteristics under different environmental conditions [24,25]. For instance, Boussinesq models have been used extensively to predict wave conditions in coastal and offshore zones [26].…”