Réponse de shoreline à forçage océanique multi-échelle à partir d’images vidéo

The aim of this study was to develop a methodology to statistically assess the shorelineresilience to storms at different time scales for a storm-dominated mid-latitude beach(Biscarrosse, France). On a pilot base, storm-free tropical Jamestown beach (Ghana) was alsoanalysed. 6-years (2007-2012) of continuous video-derived shoreline data and hindcastedhydrodynamics were analysed. Wave climate is dominated by storms (Hs>5% exceedancelimit) and their seasonal fluctuations; 75% of storms occur in winter with more than 60identified storms during the study period. A multiple regression on 36 storms shows thatwhereas current and previous storm intensity have predominant role on current storm impact,tide and sandbar play a major role on the post-storm recovery. An ensemble average on poststormrecovery period shows that Biscarrosse beach recovers rapidly (9 days) to individualstorms, and sequences of storms (clusters) have a weak cumulative effect. The results point outthat individual storm recurrence frequency is key. If the interval between two storms is lowcompared to the recovery period, the beach becomes more resilient to the next storms; and thefirst storm in clusters has larger impact than following ones. Shoreline responds in decreasingorder at seasonal, storm frequency and annual timescales at Biscarrosse. The EOF methodshows good skills in separating uniform and non-uniform shoreline dynamics, showing theirdifferent temporal variability: seasonal and short-term scales dominate first EOF (2D) andsecond (3D) modes, respectively.The shoreline at Jamestown was studied on pilot base from 2013-2014. Water level channgesplay a major role on shoreline changes. Waves estimates from video are in good agreement withhindcasts. This study shows the potential of the technique, to be replicated elsewhere in WestAfrica with all its diversity and regional climate variability through a coastal observationnetwork.Le but de cette étude était de développer une méthodologie pour évaluer la résilience des littoraux aux évènements de tempêtes, à des échelles de temps différentes pour une plage située à une latitude moyenne (Biscarrosse, France). Un site pilote des tropiques, la plage de Jamestown (Ghana), non soumis aux tempêtes, a également été analysé. 6 ans (2007-2012) de données sur la position du trait de côte,obtenues quotidiennement par imagerie vidéo, ainsi que les prévisions hydrodynamiques (ECMWF EraInterim) ont été analysées. Le climat de vagues est dominé par les tempêtes (Hs> 5% de seuil de dépassement) et leurs fluctuations saisonnières; 75% des tempêtes se produisent en hiver, et plus de 60tempêtes ont été identifiées au cours de la période d'étude. Une régression multiple, montre qu’alors que les intensités des tempêtes actuelle et précédente ont un rôle majeur sur l'impact de la tempête, la marée et les barres sableuses jouent un rôle majeur sur la récupération de plage. La position moyenne du trait de côte calculée sur la période de récupération post-tempête montre que la plage de Biscarrosse se reconstruit rapidement (9 jours) après un évènement isolé et que les séries de tempêtes (clusters) ont un effet cumulatif diminué. Les résultats indiquent que le récurrence individuelle des tempêtes est clé. Si l'intervalle entre deux tempêtes est faible par rapport à la période de récupération, la plage devient plus résistante aux tempêtes suivantes; par conséquent, la première tempête d’une série a un impact plus important que les suivantes. Le trait de côte répond, par ordre décroissant, aux évènements saisonniers,à la fréquence des tempête et aux d’échelle annuelle. La méthode EOF montre de bonnes capacité à séparer la dynamique « uniforme » et « non-uniforme » du littoral et décrit différentes variabilités temporelles: les échelles saisonnières et à court terme dominent, respectivement, la première EOF (2D)et le second mode (3D). Le littoral de Jamestown a été étudié comme base d’un projet pilote entre 2013-2014. Les fluctuations du niveau de l'eau jouent un rôle prédominant sur l’évolution de la position du trait de côte. Les vagues et les estimations des marées obtenues par l’exploitation d’images vidéo sont corrélées avec les données de prévisions. Cette étude pionnière montre que cette technique peut être généralisée à toute l’Afrique de l'Ouest en tenant compte des multiples diversités et de la variabilité du climat régional, à travers un réseau d'observations

Shoreline response to multi-scale oceanic forcing from video imagery

Le but de cette étude était de développer une méthodologie pour évaluer la résilience des littoraux aux évènements de tempêtes, à des échelles de temps différentes pour une plage située à une latitude moyenne (Biscarrosse, France). Un site pilote des tropiques, la plage de Jamestown (Ghana), non soumis aux tempêtes, a également été analysé. 6 ans (2007-2012) de données sur la position du trait de côte,obtenues quotidiennement par imagerie vidéo, ainsi que les prévisions hydrodynamiques (ECMWF EraInterim) ont été analysées. Le climat de vagues est dominé par les tempêtes (Hs> 5% de seuil de dépassement) et leurs fluctuations saisonnières; 75% des tempêtes se produisent en hiver, et plus de 60tempêtes ont été identifiées au cours de la période d'étude. Une régression multiple, montre qu’alors que les intensités des tempêtes actuelle et précédente ont un rôle majeur sur l'impact de la tempête, la marée et les barres sableuses jouent un rôle majeur sur la récupération de plage. La position moyenne du trait de côte calculée sur la période de récupération post-tempête montre que la plage de Biscarrosse se reconstruit rapidement (9 jours) après un évènement isolé et que les séries de tempêtes (clusters) ont un effet cumulatif diminué. Les résultats indiquent que le récurrence individuelle des tempêtes est clé. Si l'intervalle entre deux tempêtes est faible par rapport à la période de récupération, la plage devient plus résistante aux tempêtes suivantes; par conséquent, la première tempête d’une série a un impact plus important que les suivantes. Le trait de côte répond, par ordre décroissant, aux évènements saisonniers,à la fréquence des tempête et aux d’échelle annuelle. La méthode EOF montre de bonnes capacité à séparer la dynamique « uniforme » et « non-uniforme » du littoral et décrit différentes variabilités temporelles: les échelles saisonnières et à court terme dominent, respectivement, la première EOF (2D)et le second mode (3D). Le littoral de Jamestown a été étudié comme base d’un projet pilote entre 2013-2014. Les fluctuations du niveau de l'eau jouent un rôle prédominant sur l’évolution de la position du trait de côte. Les vagues et les estimations des marées obtenues par l’exploitation d’images vidéo sont corrélées avec les données de prévisions. Cette étude pionnière montre que cette technique peut être généralisée à toute l’Afrique de l'Ouest en tenant compte des multiples diversités et de la variabilité du climat régional, à travers un réseau d'observations.The aim of this study was to develop a methodology to statistically assess the shorelineresilience to storms at different time scales for a storm-dominated mid-latitude beach(Biscarrosse, France). On a pilot base, storm-free tropical Jamestown beach (Ghana) was alsoanalysed. 6-years (2007-2012) of continuous video-derived shoreline data and hindcastedhydrodynamics were analysed. Wave climate is dominated by storms (Hs>5% exceedancelimit) and their seasonal fluctuations; 75% of storms occur in winter with more than 60identified storms during the study period. A multiple regression on 36 storms shows thatwhereas current and previous storm intensity have predominant role on current storm impact,tide and sandbar play a major role on the post-storm recovery. An ensemble average on poststormrecovery period shows that Biscarrosse beach recovers rapidly (9 days) to individualstorms, and sequences of storms (clusters) have a weak cumulative effect. The results point outthat individual storm recurrence frequency is key. If the interval between two storms is lowcompared to the recovery period, the beach becomes more resilient to the next storms; and thefirst storm in clusters has larger impact than following ones. Shoreline responds in decreasingorder at seasonal, storm frequency and annual timescales at Biscarrosse. The EOF methodshows good skills in separating uniform and non-uniform shoreline dynamics, showing theirdifferent temporal variability: seasonal and short-term scales dominate first EOF (2D) andsecond (3D) modes, respectively.The shoreline at Jamestown was studied on pilot base from 2013-2014. Water level channgesplay a major role on shoreline changes. Waves estimates from video are in good agreement withhindcasts. This study shows the potential of the technique, to be replicated elsewhere in WestAfrica with all its diversity and regional climate variability through a coastal observationnetwork

Quantifying Mangrove Extent Using a Combination of Optical and Radar Images in a Wetland Complex, Western Region, Ghana

The classification of mangrove forests in tropical coastal zones, based only on passive remote sensing methods, is hampered by mangrove complexities, topographical considerations, and cloud cover effects, among others. This paper reports on a study that combines optical and radar data to address the challenges of distinguishing mangrove stands in cloud-prone regions. The Google Earth Engine geospatial processing platform was used to extract multiple scenes of Landsat surface reflectance Tier 1 and synthetic aperture radar (C-band and L-band). The images were enhanced by creating a feature that removes clouds from the optical data and using speckle filters to remove noise from the radar data. The random forest algorithm proved to be a robust and accurate machine learning approach for mangrove classification and assessment. Classification was evaluated using three scenarios: classification of optical data only, classification of radar data only, and combination of optical and radar data. Our results revealed that the scenario that combines optical and radar data performed better. Further analysis showed that about 16.9% and 21% of mangrove and other vegetation/wetland cover were lost between 2009 and 2019. Whereas water body and bare land/built-up areas increased by 7% and 45%, respectively. Accuracy was evaluated based on the three scenarios. The overall accuracy of the 2019 classification was 98.9% (kappa coefficient = 0.979), 84.6% (kappa coefficient = 0.718), and 99.1% (kappa coefficient = 0.984), for classification of optical data only, classification of radar data only, and combination of optical and radar data, respectively. This study has revealed the potential to map mangroves correctly, enabling on-site conservation practices in the climate change environment

Assessment of Land Use/Land Cover Change and Morphometric Parameters in the Keta Lagoon Complex Ramsar Site, Ghana

The rapid urbanization, industrialization, agricultural activities, and increasing trend of some natural hazards, such as climate change, particularly in coastal areas, necessitate the continual assessment of critical but fragile ecosystems like that of the Keta Lagoon Complex Ramsar Site (KLCRS). This productive ecosystem in Ghana faces serious threats from intensive exploitation, physical modification, changes in water regime, and water pollution. The current study employed geospatial and intensity analysis to assess the pattern of land use/land cover (LULC) change for almost the past three decades and morphometric parameters of the KLCRS landscape. Landsat Satellite images for 1991, 2007, and 2020 were acquired to uncover the pattern of LULC change, while morphometric changes were assessed using global Advance Space Thermal Emission and Radiometer (ASTER) digital elevation model (DEM) data and the spatial analyst tools in GIS software. The result established that the acceleration of land transformation was intensive between 2007 and 2020, which could be linked to population growth and increased socio-economic activities. There was a net gross gain of built-up that originated largely from the conversion of marsh, dense vegetation, and cultivated land. Prior to this period, cultivated land recorded net gain (125.51 km2) between 1991 and 2007, whereas dense vegetation and marshland showed a net loss of 151.37 km2 and 2.44 km2, respectively. The gain of cultivated land largely targeted marshland in both time intervals. The construction of saltpans contributed largely to the small increase in water extent. The morphometric analysis revealed the groundwater potential of the KLCRS. The low-lying nature of the landscape makes the area susceptible to coastal flooding. The trend of the observed changes could invariably affect the ecological integrity of the landscape, hence suggesting the need for immediate preparation and implementation of marine and coastal spatial plans by relevant stakeholders

Know to Predict, Forecast to Warn: A Review of Flood Risk Prediction Tools

Flood prediction has advanced significantly in terms of technique and capacity to achieve policymakers’ objectives of accurate forecast and identification of flood-prone and impacted areas. Flood prediction tools are critical for flood hazard and risk management. However, numerous reviews on flood modelling have focused on individual models. This study presents a state-of-the-art review of flood prediction tools with a focus on analyzing the chronological growth of the research in the field of flood prediction, the evolutionary trends in flood prediction, analysing the strengths and weaknesses of each tool, and finally identifying the significant gaps for future studies. The article conducted a review and meta-analysis of 1101 research articles indexed by the Scopus database in the last five years (2017–2022) using Biblioshiny in r. The study drew an up-to-date picture of the recent developments, emerging topical trends, and gaps for future studies. The finding shows that machine learning models are widely used in flood prediction, while Probabilistic models like Copula and Bayesian Network (B.N.) play significant roles in the uncertainty assessment of flood risk, and should be explored since these events are uncertain. It was also found that the advancement of the remote sensing, geographic information system (GIS) and cloud computing provides the best platform to integrate data and tools for flood prediction. However, more research should be conducted in Africa, South Africa and Australia, where less work is done and the potential of the probabilistic models in flood prediction should be explored

Understanding the Complexities of Human Well-Being in the Context of Ecosystem Services within Coastal Ghana

The understanding of the complexities of human well-being (HWB) within the ecosystem service (ES) context is fundamental to the development of management plans to sustain the flow of ecosystem services (ESs) for HWB. However, research on HWB in the context of ecosystem services is still underrepresented on Africa’s coast. Primary data were collected from 794 household heads in six communities within Ghana’s eastern coastal zone. A sequential logistics regression model was used to assess the effect of the interactions between ESs, socio-economic conditions, and contextual factors on HWB. Respondents’ well-being varied across the study communities, with high well-being reported by 63% of respondents from Anloga and low well-being by 77% in Kedzi. A strong association was found between HWB and relevant characteristics of respondents including marital status, years lived in a community, subjective social position (SSP), main livelihood source, income class, access to a reliable credit facility, and being a member of a local community group. Gender was not a significant predictor of HWB levels. For the effect of ESs on HWB, we found that respondents who had high contentment with provisioning and cultural ESs were more likely to have high well-being as opposed to respondents who had low contentment. Respondents who had low to moderate contentment with regulatory ESs were more likely to have high well-being, but the contextual factors condensed the significance of this relationship. Findings suggest the implementation of deliberate actions to maintain or restore vital ecosystem functions and services for sustainable well-being in coastal communities

Linking human perception and scientific coastal flood risk assessment (Anlo Beach Community, Ghana)

International audiencePolicymakers concerned with coastal management issues have recently focused their efforts on how people perceive flood risk. Understanding the public's perception of risk has become an essential component of contemporary flood risk management, as it provides a basis for designing practical and effective flood mitigation strategies. This study was conducted in Anlo Beach, one of the most vulnerable coastal communities in Ghana. It investigated household perceptions of flood risk and examined them against independent physical measures that assess exposure. In parallel, multivariate regression analysis was conducted to identify and establish the key factors influencing household perceptions of flood risk in the study area. The results showed that two variables, previous flood experience (data collected through the social survey) and factual exposure (assessed through GIS measurements), played an important role in determining the level of flood risk reported by households. In particular, the relationship between previous flooding experience and perceived level of coastal flood risk was both positive and statistically significant. Socio-demographic factors did not have a significant influence on risk reporting. We conclude that perception variables collected through social surveys can be used as proxy indicators of environmental risks when physical measures are not available. Biases based on the socio-economic status of respondents may exist, but they do not outweigh information derived from people's factual relationships with the environment. Further studies on the above factors would support flood risk reduction measures in the study area and West Africa, particularly in light of climate change

Social perceptions of coastal hazards in the Anlo Beach Community in the Western Region of Ghana

International audienceDue to climate change, coastal areas are becoming increasingly susceptible to more frequent and severe environmental catastrophes that endanger the health, safety, and way of life of coastal dwellers. Understanding the social perceptions of risk and hazard-related concerns can help in the development of adaptive capacity and associated management strategy preferences. This study employed structured questionnaires to obtain basic information on how the households of the Anlo Beach fishing community in the Western region of Ghana perceived and responded to coastal hazards. The respondents ranked coastal erosion and salinization first and second, ahead of seawater flooding and other hazards in terms of important risks in the study area. Responses illustrated high levels of knowledge and awareness about coastal hazards but low levels of trust in government and commitments in terms of taking personal mitigation measures. To varying degrees, respondent characteristics such as length of residency and occupancy status are positively and significantly associated with coastal hazard perception whereas the level of education was negative. Generally, the findings illustrated the need for better education and awareness campaigns about self-mitigation actions such as discontinuing beach sand utilization and exploiting mangroves as firewood, and embracing the restoration of mangrove ecosystems. More importantly, the government should reconsider her earlier shelved plan of relocating the entire community to a safer location

Social perceptions of coastal hazards in the Anlo Beach Community in the Western Region of Ghana

International audienceDue to climate change, coastal areas are becoming increasingly susceptible to more frequent and severe environmental catastrophes that endanger the health, safety, and way of life of coastal dwellers. Understanding the social perceptions of risk and hazard-related concerns can help in the development of adaptive capacity and associated management strategy preferences. This study employed structured questionnaires to obtain basic information on how the households of the Anlo Beach fishing community in the Western region of Ghana perceived and responded to coastal hazards. The respondents ranked coastal erosion and salinization first and second, ahead of seawater flooding and other hazards in terms of important risks in the study area. Responses illustrated high levels of knowledge and awareness about coastal hazards but low levels of trust in government and commitments in terms of taking personal mitigation measures. To varying degrees, respondent characteristics such as length of residency and occupancy status are positively and significantly associated with coastal hazard perception whereas the level of education was negative. Generally, the findings illustrated the need for better education and awareness campaigns about self-mitigation actions such as discontinuing beach sand utilization and exploiting mangroves as firewood, and embracing the restoration of mangrove ecosystems. More importantly, the government should reconsider her earlier shelved plan of relocating the entire community to a safer location

Two and three-dimensional shoreline behaviour at a MESO-MACROTIDAL barred beach

The present work investigates cross-shore shoreline migration as well as its alongshore variability (with deformation) on timescales of days to years using 6 years of time-averaged video images. The variability of the shoreline is estimated through empirical statistical methods with comprehensive reference to three scales of variability. At the meso-to macro-tidal barred Biscarrosse beach, shoreline responds in decreasing order at seasonal (winter/summer cycles, 52%), event (storms, 28%) and inter-annual scales. Whereas seasonal evolution is dominated by wave climate modulation, short-term evolution is influenced by tidal range and surf-zone sandbar characteristics. The influence of tide range and sandbars increases when timescale decreases. This is even more the case for the alongshore deformation of the shoreline which is dominated by short-term evolution. An EOF analysis reveals that the first mode of shoreline change time series is associated with cross-shore migration and explains 58% of the shoreline variability. The rest of the modes are associated to deformation which explain 42% of shoreline variabilityThe first author is co-funded by SCAC (French embassy in Ghana) and ARTS-IRD programs. Authors acknowledge the Region Aquitaine for financially supporting the installation of the video system at Biscarrosse. This research has received support from French grant through ANR COASTVAR: ANR-14-ASTR-0019. RR is supported by the AXA Research fund and the Deltares Harbour, Coastal and Offshore Engineering Research Programme ‘Bouwen aan de Kust’. BB is supported by French BAgence Nationale de la Recherche^ through project CHIPO (ANR-14-ASTR-0004-01