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Beach Response to Wave Forcing from Event to Inter-Annual Time Scales at Grand Popo, Benin (Gulf of Guinea)

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Beach Response to Wave Forcing from Event to Inter-Annual Time Scales at Grand Popo, Benin (Gulf of Guinea) water Article Beach Response to Wave Forcing from Event to Inter-Annual Time Scales at Grand Popo, Benin (Gulf of Guinea) Grégoire Abessolo Ondoa 1,2,*, Frédéric Bonou 2,3,4, Folly Serge Tomety 2,3,4, Yves du Penhoat 2,3,4, Clément Perret 2,3,4, Cossi Georges Epiphane Degbe 3 and Rafael Almar 2 1 Fishery Resources Laboratory, University of Douala, BP 2701 Douala, Cameroon 2 LEGOS (Université Paul Sabatier de Toulouse/CNRS/CNES/IRD), 31400 Toulouse, France; [email protected] (F.B.); [email protected] (F.S.T.); [email protected] (Y.d.P.); [email protected] (C.P.); [email protected] (R.A.) 3 Institut de Recherches Halieutiques et Océanologiques du Bénin, 03 BP 1665 Cotonou, Benin; [email protected] 4 International Chair in Mathematical Physics and Applications/Unesco Chair, University of Abomey-Calavi, 01 BP 526 Cotonou, Benin * Correspondence: [email protected]; Tel.: +237-699-76-73-34 Received: 31 March 2017; Accepted: 16 June 2017; Published: 21 June 2017 Abstract: This paper assesses the morphological storm-event impact, seasonal cycles, trends of wave forcing, and beach’s response at the coastal area of Grand Popo, Benin. Three and a half years’ worth of data were collected from 2013 to 2016, using a video system calibrated with field data collected during a 10 day experiment. A comparison was carried out with Wavewatch III IOWAGA wave hindcast data. The along-shore-averaged shoreline position exhibited a seasonal pattern, which was related more to the average wave height than the average storm intensity. Storms occur in austral winter (June, July, August, and September). Based on 12 storms, the results revealed that the average storm duration was 1.6 days, with a mean erosion of 3.1 m. The average post-storm beach recovery duration was 15 days, and the average recovery rate was 0.4 m/day. The impact of storms was more or less amplified depending on the eroding and accreting periods of the wave climate. There was an inter-annual eroding trend of about −1.6 m/year, but the causes of this trend could not be explained. Keywords: shoreline; waves forcing; storms; resilience; post-storm recovery; Bight of Benin; seasonal cycle; trend 1. Introduction The coastal zone of West Africa is under increasing pressure of overpopulation, as it is a zone of economic interest. Human settlements and livelihood activities have been developing on the shores of the Atlantic Ocean, where the beach evolution varies according to a wide range of different temporal and spatial scales. In this region, beaches are microtidal and swell-dominated environments, where waves and tides are the main drivers of nearshore dynamics [1]. Several findings suggest that along wave-dominated coastlines, regionally-varying wave climates will have an increasing impact on the shoreline in the coming decades, and cannot be ignored in forecasting shoreline variability [2–4]. This highly dynamic behaviour is essentially due to the fact that sandy coasts can undergo adjustments in form and processes, which can change rapidly. Periods of accretion and erosion are generally associated with low- and high-energy wave conditions, respectively, but they also exhibit strong site-specific variations [5]. For many coastal regions, both sea-level rise and changes in the storm-wave climate would result in coastal erosion and an increased frequency with a high intensity of coastal flooding. Storm-events represent a major factor of modulating short- and medium-term morphological Water 2017, 9, 447; doi:10.3390/w9060447 www.mdpi.com/journal/water Water 2017, 9, 447 2 of 13 evolutions of many sandy shorelines. In the event of changing storm regimes associated with climate change [6], it is important to understand the potential effects of storms on beaches, and how they recover after these high-energy events. Many studies have been carried out on assessing the impact of storms, beaches’ responses, and post-storm morphological adjustments in storm-dominated coastlines [6–12]. Managing erosion-induced problems will depend on the resilience of the beach to extreme events, and universal threshold conditions are not likely to be found [5]. Establishing storm thresholds is difficult, especially because they are generally site-specific [11,13]; this is as well as the beach recovery period [7], which has not yet been clearly addressed in the literature. Available literature regarding beaches’ responses to storms on tropical microtidal coastlines and the potential impacts of climate change remains scarce. Along the wave-dominated coastlines of the Gulf of Guinea, the influence of South Atlantic high-energy swells drives strong, eastward longshore sediment transport [14,15]. This littoral drift in the Bight of Benin is one of the largest in the world, with estimations of approximatively 400,000–1,000,000 m3/year [16]. This transport is mostly driven by swell waves due to the Southern Annular Mode (SAM), rather than wind waves due to the Inter-Tropical Convergence Zone (ITCZ) [15]. This equatorial fluctuation presents a large seasonal and inter-annual variability as well as wave climate [14]. This implies a high seasonal variability in the beaches’ responses to equatorial Atlantic forcing, given that seasonal processes dominate the shoreline changes due to seasonal variations of the wave height at several specific sites [5,17]. These findings need to be confirmed, but few measurements are available on the high-frequency evolution of shoreline and beach states in the West and Central African regions. This study assesses different time scales of beach responses to wave forcing at Grand Popo Coast, Benin, using video-derived shoreline and wave evolution data over a 3.5 year observation period (February 2013 to August 2016). We first investigate an average beach response during and after storm-events. Secondly, we evaluate the impact of storm durations and recurrence with seasonal variability. And finally, we estimate the inter-annual trends. 2. Data and Methods 2.1. Study Area Located in the Gulf of Guinea, Benin, near the border with Togo, Grand Popo Beach is an ocean-open, sandy stretch of coast facing the South Atlantic Ocean [18]. The beach is far enough from the influence of the major cities: Cotonou (80 km away), and Lome (60 km away). In the last three years, some fields of groynes have been constructed near the town of Anèho, 20 km updrift [19] (see Figure1b). The beach dynamics are dominated by the influence of oblique waves (South/Southwest) of moderate energy (mean significant wave height Hs = 1.36 m; mean peak period Tp = 9.4 s). The longshore sediment transport is primarily driven by swell waves (South/Southwest and South/Southeast) generated in the Southern Hemisphere trade-wind region (30–35◦ S and 45–60◦ S), rather than wind waves (Southwest) generated locally in the Gulf of Guinea [14–16,20], as shown in Figure1a. Tides are semi-diurnal with a microtidal range from 0.8 to 1.8 m for neap and spring tides, respectively. The sediment size is medium-to-coarse: 0.4 to 1 mm (median grain size D50 = 0.6 mm). Grand Popo Beach is an intermediate low tide terrace (LTT) to reflective beach [14,18,20], according to the classification proposed in [21]. Water 2017, 9, 447 3 of 13 Water 2017, 9, 447 3 of 13 Figure 1. StudyStudy site: site: (a (a) )The The regions regions of of major major generations generations of ofswells swells and and wind wind waves waves impinging impinging on the on theGulf Gulf of Guinea of Guinea are indicated are indicated by grey by greyovals, ovals, and their and theirmajor major directions directions of propagation of propagation by the by black the blackarrows. arrows. (b) Focus (b) in Focus the Bight in the of Bight Benin, of with Benin, major with citi majores of Cotonou cities of Cotonou and Lomé. and Black Lom arrowsé. Black represent arrows representthe longshore the longshore sediment sediment transport transport directions. directions. The red Thepoint red (2.0° point E, (2.05.5°◦ N)E, 5.5gives◦ N) the gives location the location of the ofWW3 the WW3model modeloutput. output. (c) Permanent (c) Permanent video camera video camera on a 15 on m ahigh 15 m semaphore high semaphore at Grand at GrandPopo Beach, Popo Beach,Benin. Benin. 2.2. Video System and Data InIn February 2013,2013, aa low-costlow-cost videovideo systemsystem waswas installedinstalled onon thethe top of a tower of the Navy Forces of Benin in Grand Popo, about 70 m from the shor shorelineeline [[22].22]. The system was composed of a VIVOTEK IPIP 73617361 cameracamera (1600(1600 ×× 728728 pixels), which collected data continuously at 2 Hz. An on-site computer processedprocessed the the raw raw images images and and stored stored three three types types of secondary of secondary images images every every 15 min: 15 snapshots, min: snapshots, cross- cross-shoreshore time-stacks, time-stacks, and 15 and min 15 time min exposure time exposure (or time (orx) timex)images images (Figure (Figure 2) [22].2 Twenty)[ 22]. Twenty ground groundcontrol controlpoints were points taken were with taken GPS with to GPSprocess to process image geo-rect image geo-rectificationification [23], by [23 applying], by applying the method the method of direct of directlinear lineartransformation transformation [24]. This [24 ].consists This consists of a matrix, of a matrix, which whichgives the gives relation the relation between between image imagepixels pixelsand control and control points points by taking by taking into account into account the position the position of the of camera the camera and andthe correction the correction due dueto the to thecamera camera lens lens distortion distortion [25]. [25 ].
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