Among the impacts of climate change in West Africa, coastal erosion is the most threatening disaster apart from floods and the increase in temperatures. The southern coast of the Dakar region, as part of the most threatened coastal zones in West Africa, records the most current coastal damages in Dakar due to its coastline dynamics and low-lying area. This paper investigates the influences of the topography and slope of the beach on shoreline dynamics using remote sensing, cartographic tools and statistical methods such as linear regression. It also states the important role of geomorphologic structures in shoreline dynamics. It was conducted in three littoral cells (Mbao, Bargny and Toubab Dialaw) along the southern coast of Dakar. It helps to understand better the role that topography, slope and geomorphology play in coastal dynamics. The Modified Normalized Difference Water Index (MNDWI) was employed to delineate the coastlines before computing the dynamic rate of the coastline using Digital Shoreline Analysis System (DSAS) software. After that, the topography and slope were determined using a digital elevation model (DEM). Then, the correlation between the coastline dynamic, topography and slope was analyzed using the coefficient of correlation and linear regression model. In the Mbao and Bargny littoral cells where the geomorphology is mostly dominated by soils little or not evolved in situ, there is a significant relationship between the coast line dynamic, topography and slope with a coefficient of correlation of about 0.63 and 0.87, respectively. The relationship is not significant in Toubab Dialaw, where the topography and slope are high, and the geomorphology is mainly characterized by a category of sandstone, with a coefficient of 0.15. We conclude that topography, slope and geomorphology play an important role in the shoreline dynamics in the study area.

Pouye, I.; Adjoussi, D.P.; Ndione, J.A., and Sall, A., 2024. Evaluation of the economic impact of coastal erosion in Dakar region. Journal of Coastal Research, 40(1), 193–209. Charlotte (North Carolina), ISSN 0749-0208. Besides the environmental impacts, climate change negatively affects the economic value of coastal zones. Coastal erosion, which is one of its impacts, causes damage to people living along the coast. The narrowing of the beach due to erosion leads to socio-economic damage by reducing the areas where economic activities are carried out. As a result, livelihoods, human settlements, and economic activities such as fishing, tourism, and industry are disrupted. The evaluation of the economic impacts of coastal erosion is timely and relevant. This study aims to economically investigate the most affected coastal areas in Dakar region in 2030 and 2040. It also allows for the identification of localities that need protective infrastructure to prevent economic losses from coastal erosion. The assessment is done by estimating the economic value of the beach using multilinear regression, an econometric forecasting model. Software such as R, Excel, ArcGIS, and Digital Shoreline Analysis System were used in this study. The results show that, due to coastal erosion, the district municipalities along the coast of Dakar will record a loss estimated at 38,507,856,000 FCFA in 2030 and 57,822,698,000 FCFA in 2040. The results of this study suggest that the parameters such as Beach Width, Lost Areas, Coastal Length, Dynamic Rate, Littoral Areas, Built Areas, Proximity to Town, Coastal Vulnerability Index, Number of Buildings, Number of Hotels, Number of Industries, Number of Fishing Points, and Road Length play an important role on littoral value. Coastal erosion will be among the most threatening disasters in the Dakar region if the “do nothing” option is adopted as an adaptation measure.

Owing to its unique physical and socio-economic characteristics, the Saint Louis region stands out as one of the most susceptible areas in Senegal to the adverse impacts of coastal erosion. The dynamics of erosion in this region are significantly influenced by the Langue de Barbarie (LB), a sand spit formed at the mouth of the Senegal River. Initially, in 2003, a 4 m wide artificial breach was strategically introduced to mitigate flooding; however, sediment dynamics expanded it to 6 km by 2020, thereby affecting the entire region. This study delves into the coastline change of the LB, specifically divided into three zones (LB-1, LB-2, and LB-3), spanning the period from 1994 to 2042. Leveraging Geographic Information System (GIS) and remote sensing techniques, our investigation reveals that, prior to the breach’s creation, the average dynamic coastline rates in zones LB-1, LB-2, and LB-3 were estimated at 4.4, 5.9, and 4.4 m/year, respectively. Subsequent to the breach, these rates shifted to −1.2, 8.4, and −2.7 m/year, with the most significant erosion observed alongshore of LB-3 at −6.6 m/year during the period 2002–2012. Projecting into 2032, LB-1 and LB-3 are anticipated to experience erosion rates of −11.5 and −26.8 m/year, respectively, while the LB-2 records an estimated accretion rate of 8.41 m/year. Eroded areas are expected to total 571,458 m², while accumulated areas are expected to total 67,191 m². By 2042, zones LB-1, LB-2, and LB-3 are expected to experience erosion rates of −23 and −53.6 m/year, resulting in the erosion of 1,021,963 m² and the accumulation of 94,930 m² with a dynamic rate of 168.2 m/year in zone LB-3. These results have significant implications for solving the urgent issue of coastal erosion in LB.

In the past two decades, several floods have affected people and their properties in Burkina Faso, with unprecedented flooding occurring in Ouagadougou in September 2009. So far, most studies have focused on Ouagadougou and surrounding localities and have paid little attention to other flood-prone regions in Burkina Faso. Consequently, there is a data and knowledge gap regarding flood risk in the Haut-Bassins region, which in turn hinders the development of mitigation strategies and risk reduction measures in affected communities. This study demonstrates how data collected at the household level can be used to understand flood risk and its components at the village level in this data-scarce region. Using an indicator-based method, we analyzed both flood risk and flood risk perception at the village level. Moreover, we determined the factors influencing flood risk perception at the household level using an ordered logit model. We found that 12 out of the 14 villages in our sample group had experienced high levels of flood risk. The management of runoff from the nearest urban areas as well as poorly designed civil engineering infrastructures, such as roads, were highlighted by households as significant factors that increased their vulnerability. Additionally, we found that the perceived flood risk consistently exceeds the estimated flood risk, with an insignificant positive correlation between both risk indices. Regression results indicate that flood risk perception is mainly influenced by informational and behavioral factors of households. The findings of this study can provide valuable information to municipal and regional authorities involved in disaster risk management within the study area. Moreover, our/this method is transferable to other data-scarce regions.

The Gambia’s coastline, known for its unique ecosystems and vital role in the country’s economy through fisheries, tourism, and agriculture, is becoming increasingly vulnerable as a result of the combined effects of climate change and human activity. This coastline sustains an important portion of the population by providing livelihoods and contributing to food security, as well as housing critical infrastructure including ports, urban areas, and tourism hubs. However, as climate change intensifies pre-existing vulnerabilities, such as increased sea-level rise, coastal erosion, and extreme weather events, these socio-economic assets are becoming more and more vulnerable. As a result, this study focused on investigating the physical vulnerability of the coastline in the context of climate change. The vulnerability assessment was conducted using the coastal vulnerability index approach, utilising a combination of oceanographic data, remote sensing, and field observations. The research outcomes supported the identification of key areas at risk and examined the contributing factors such as tidal ranges, storm surges, and human activities. The findings highlight the immediate and long-term threats to coastal communities, infrastructure, and natural habitats. Due to the vulnerability provided by geological and geomorphological factors, the average Coastal Vulnerability Index (CVI) score of 29 indicates a high level of exposure to coastal hazards from Buniadu Point to Barra. From Banjul to Cape Point, the average coastline dynamic rate is positive at 0.21 m/year, indicating some accretion. Despite this, the CVI score of 22 indicates significant vulnerability to coastal hazards from Bald Cape to Salifor Point. The study also explored potential mitigation and adaptation strategies to enhance coastal resilience to sea-level rise, coastal erosion, and flooding. Integrated and sustainable strategies were outlined to support policy-making and community-based initiatives towards safeguarding coastal regions of The Gambia against the backdrop of climate change.

In the past two decades, several floods have affected people and their properties in Burkina Faso, with the unprecedented flooding occurring in Ouagadougou in September 2009. So far, most studies have focused on Ouagadougou and surrounding localities and have paid little attention to other flood-prone regions in Burkina Faso. Specifically, there is a data and knowledge gap about the flood risk in the Haut-Bassins region, which in turn hampers the development of mitigation strategies and risk reduction measures in communities. This study demonstrates how data collected at the household level can be used to understand flood risk and its components at the village level in this data-scarce region. Using an indicator-based method, we analyze both flood risk and flood risk perception at the village level. Moreover, we determine the factors influencing flood risk perception at the household level using an ordered logit model. We find that 12 out of the 14 villages considered, experience high levels of flood risk. The management of runoff from the nearest urban areas and poorly designed civil engineering infrastructures, such as roads, were highlighted by the households as significant factors that increase their vulnerability. Hence, dependencies in space and between urban and rural areas may play a substantial role in modifying risk. The perceived flood risk consistently exceeds the estimated flood risk, with an insignificant positive correlation between both risk indices. Regression results indicate that flood risk perception is mainly influenced by informational and behavioral factors of the households. The findings of this study can provide valuable information to municipal and regional authorities involved in disaster risk management in the study area. Moreover, the method is transferable to other data-scarce regions