The African coast contains heritage sites of ‘Outstanding Universal Value’ that face increasing risk from anthropogenic climate change. Here, we generated a database of 213 natural and 71 cultural African heritage sites to assess exposure to coastal flooding and erosion under moderate (RCP 4.5) and high (RCP 8.5) greenhouse gas emission scenarios. Currently, 56 sites (20%) are at risk from a 1-in-100-year coastal extreme event, including the iconic ruins of Tipasa (Algeria) and the North Sinai Archaeological Sites Zone (Egypt). By 2050, the number of exposed sites is projected to more than triple, reaching almost 200 sites under high emissions. Emissions mitigation from RCP 8.5 to RCP 4.5 reduces the number of very highly exposed sites by 25%. These findings highlight the urgent need for increased climate change adaptation for heritage sites in Africa, including governance and management approaches, site-specific vulnerability assessments, exposure monitoring, and protection strategies.

Probabilistic flood forecasting requires flood models that are simple and fast. Many of the modelling applications in the literature tend to be complex and slow, making them unsuitable for probabilistic applications which require thousands of individual simulations. This article focusses on the development of such a modelling approach to support probabilistic assessment of flood hazards, while accounting for forcing and system uncertainty. Here, we demonstrate the feasibility of using the open-source SWMM (Storm Water Management Model), focussing on Can Tho city, Mekong Delta, Vietnam. SWMM is a dynamic rainfall-runoffsimulation model which is generally used for single event or long-term (continuous) simulation of runoffquantity and quality and its application for probabilistic riverflow modelling is atypical. In this study, a detailed SWMM model of the entire Mekong Delta was built based on an existing ISIS model containing 575 nodes and 592 links of the same study area. The detailed SWMM model was then systematically reduced by strategically removing nodes and links to eventually arrive at a level of detail that provides sufficiently accurate predictions of water levels for Can Tho for the purpose of simulating urban flooding, which is the target diagnostic of this study. After a comprehensive assessment (based on trials with the varying levels of complexity), a much reduced SWMM model comprising 37 nodes and 40 links was determined to be able to provide a sufficiently accurate result while being fast enough to support probabilistic future flood forecasting and, further, to support flood risk reduction management.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Climate change (CC) is likely to affect the thousands of bar-built or barrier estuaries (here referred to as Small tidal inlets - STIs) around the world. Any such CC impacts on the stability of STIs, which governs the dynamics of STIs as well as that of the inlet-adjacent coastline, can result in significant socio-economic consequences due to the heavy human utilisation of these systems and their surrounds. This article demonstrates the application of a process based snap-shot modelling approach, using the coastal morphodynamic model Delft3D, to 3 case study sites representing the 3 main STI types; Permanently open, locationally stable inlets (Type 1), Permanently open, alongshore migrating inlets (Type 2) and Seasonally/Intermittently open, locationally stable inlets (Type 3). The 3 case study sites (Negombo lagoon – Type 1, Kalutara lagoon – Type 2, and Maha Oya river – Type 3) are all located along the southwest coast of Sri Lanka.
After successful hydrodynamic and morphodynamic model validation at the 3 case study sites, CC impact assessment are undertaken for a high end greenhouse gas emission scenario. Future CC modified wave and riverflow conditions are derived from a regional scale application of spectral wave models (WaveWatch III and SWAN) and catchment scale applications of a hydrologic model (CLSM) respectively, both of which are forced with IPCC Global Climate Model output dynamically downscaled to ~50 km resolution over the study area with the stretched grid Conformal Cubic Atmospheric Model CCAM. Results show that while all 3 case study STIs will experience significant CC driven variations in their level of stability, none of them will change Type by the year 2100. Specifically, the level of stability of the Type 1 inlet will decrease from ‘Good’ to ‘Fair to poor’ by 2100, while the level of (locational) stability of the Type 2 inlet will also decrease with a doubling of the annual migration distance. Conversely, the stability of the Type 3 inlet will increase, with the time till inlet closure increasing by ~75%. The main contributor to the overall CC effect on the stability of all 3 STIs is CC driven variations in wave conditions and resulting changes in longshore sediment transport; not Sea level rise as commonly believed.

The complexity of quantifying ecosystem services in monetary terms has long been a challenging issue for economists and ecologists. Many case specific valuation studies have been carried out in various parts of the World. Yet, a coherent review on the valuation of coastal ecosystem services (CES), which systematically describes fundamental concepts, analyzes reported applications, and addresses the issue of climate change (CC) impacts on the monetary value of CES is still lacking. Here, we take a step towards addressing this knowledge gap by pursuing a coherent review that aims to provide policy makers and researchers in multidisciplinary teams with a summary of the state-of-the-art and a guideline on the process of economic valuation of CES and potential changes in these values due to CC impacts. The article highlights the main concepts of CES valuation studies and offers a systematic analysis of the best practices by analyzing two global scale and 30 selected local and regional case studies, in which different CES have been valued. Our analysis shows that coral reefs and mangroves are among the most frequently valued ecosystems, while sea-grass beds are the least considered ones. Currently, tourism and recreation services as well as storm protection are two of the most considered services representing higher estimated value than other CES. In terms of the valuation techniques used, avoided damage, replacement and substitute cost method as well as stated preference method are among the most commonly used valuation techniques. Following the above analysis, we propose a methodological framework that provides step-wise guidance and better insight into the linkages between climate change impacts and the monetary value of CES. This highlights two main types of CC impacts on CES: one being the climate regulation services of coastal ecosystems, and the other being the monetary value of services, which is subject to substantial uncertainty. Finally, a systematic four-step approach is proposed to effectively monetize potential CC driven variations in the value of CES.

Climate change triggers major alterations to coastal zones worldwide. Quantification of these adverse impacts to coastal ecosystems is often done on a coarse scale of global regions. Consistent local scale estimates of physical impacts on ecosystems and monetary assessment of associated losses are scarce, especially in developing countries. With aim of facilitating such assessment, which is increasingly required, here we propose a coherent three-step framework and subsequently apply it to quantify potential sea level rise-driven alterations in the monetary value of ecosystem services in the coastal area of Semarang in Indonesia. Within this framework, we (1) quantify the present value of coastal ecosystem services by using economic valuation techniques; (2) identify the potential impacts of relative sea level rise (RSLR)-induced inundation on ecosystem services (for the year 2100 inundation scenarios); and (3) monetize these impacts by developing a novel scenario-based approach. The results show that full inundation (scenario A with 4 m RSLR) poses a median loss of 90% (US$ 2.8 – 3.5) and 25% (US$ 90 – 113) to the present art and fishery values per hectare, while amenity service is expected to lose upto 50% (US$ 3700 – 5400) of its present value. Additionally, recreation value of the coastal ecosystems in three selected sites (Marina and Maron beaches, and Plumbon estuary) will decrease by 70% (US$ 15,460 – 19,820) per hectare. However, in scenario B (RSLR of 1.1 m) with a 50% inundated area, these losses are estimated approximately 40% less than for scenario A. It is expected that researchers and policy makers may apply this approach in their areas of interest to gain a better understanding of the likely costs of sea level rise-driven environmental damages along coasts, ultimately contributing to the sustainable management of coastal environment in Indonesia and possibly in other developing countries.

This paper focuses on utilizing Sentinel 2 MSI datasets to generate satellite-derived bathymetry (SDB) maps at a resolution of 10 m for two temporally varying datasets of the study region of Ameland Inlet, located in The Netherlands, by using support vector regression (SVR) technique. The relative performance of Landsat 8 OLI (30 m) datasets with SVR technique is also assessed to demonstrate the complementary nature of these freely available medium-resolution imageries. Further, the root mean square error and mean absolute error between the retrieved and measured bathymetries are estimated and reported to evaluate the capability of SVR in estimating depths. It is evident that the SDBs thus generated using this machine learning approach provide dependable estimations of depths that can further be utilized for various coastal engineering studies.

Nearshore sandbar patterns can affect the hydrodynamics and, as a result, the beach morphodynamics in the nearshore zone. Hence, spatial and temporal variability in the sandbars can influence beach accretion and erosion. Understanding the variability of the sandbar system can therefore be crucial for informed coastal zone management. So far, the methods to study sandbar dynamics mainly include datasets of video observations or occasional bathymetric surveys. However, at most locations around the world, these types of data are not or only scarcely available. In this paper we present an alternative method to analyze long-term sandbar variability by means of freely available satellite imagery. These images are globally available since the 1980’s and, thus, have the potential to be applicable at any location in the world. Here, we will illustrate the methodology by means of a case study at Anmok beach at the South Korean East coast.

Sand nourishments are presently widely applied to maintain or enhance coastal safety and beach width. Over the last decades, global sand nourishment volumes have increased greatly, and the demand for nourishments is anticipated to increase further in coming decades due to sea level rise. With the increase in nourishment size and the request for more complex nourishment shapes, an adequate prediction of the morphodynamic evolution is of major importance. Yet, neither the skill of current state-of-the-art models for such predictions nor the primary drivers that control the evolution are known. This article presents the results of a detailed numerical modelling study undertaken to examine the model skill and the processes governing the initial morphological response of the Sand Engine and the adjacent coastline. The process-based model Delft3D is used to hindcast the first year after completion of the mega-nourishment. The model reproduces measured water levels, velocities and nearshore waves well. The prediction of the morphological evolution is consistent with the measured evolution during the study period, with Brier Skill Scores in the ‘Excellent’ range. The model results clearly indicate that the sand eroded from the main peninsular section of the Sand Engine is deposited along adjacent north and south coastlines, accreting up to 6 km of coastline within just one year. Analysis of model results further show that the erosional behaviour of the Sand Engine is linearly dependent on the cumulative wave energy of individual high energy wave events, with the duration of a storm event being more dominant than the maximum wave height occurring during the storm. The integrated erosion volume due to the 12 events with the highest cumulative wave energy density accounts for about 60% of the total eroded volume of the peninsula, indicating that the less energetic wave events, with a higher probability of occurrence, are also important for the initial response of the Sand Engine. A structured model experiment using the verified Delft3D model indicates that wave forcing dominates the initial morphological response of the Sand Engine, accounting for approximately 75% of the total erosion volume in the first year. The vertical tide is the second most important factor accounting for nearly 17% of the total erosion volume, with surge, wind and horizontal tide playing only a minor role.

This study presents some recent developments in coastal morphological modeling focusing on flexible meshes, flexible coupling between models operating at different time scales, and a recently developed morphodynamic model for the intertidal and dry beach. This integrated modeling approach is applied to the Sand Engine mega nourishment in The Netherlands to illustrate the added-values of this integrated approach. A seamlessly coupled modeling system for Delft3D and AeoLiS has been developed and applied to compute the first years of evolution of the Sand Engine, both for the subaqueous and subaerial areas. The subaqueous bed level changes have been computed with the new Flexible Mesh version of Delft3D, resulting in comparable accuracy levels as to the standard Delft3D version. The integrated morphodynamic prediction of both subaqueous and subaerial reveals a qualitative behavior which is very similar to observations. Model results confirm that after the first year after construction the sand supply for aeolian transports is predominantly from the intertidal area. The AeoLiS model results indicate a significant intertidal erosion volume of about 230,000 m3 over the five year period, which is a not to be neglected volume, especially in multiyear or decadal predictions. Interestingly, the model results show that the spit, developed by the wave-related processes, is also subject to aeolian transports acting on the emerged spit during lower tides. The seamlessly coupled models are now able to combine the dry beach behaviour with subaqueous morphodynamic evolution, which is important in medium-term to decadal morphodynamic predictions but also relevant for designing such sandy solutions incorporating lakes, lagoons, and relief.

Tidal inlets are of great societal importance and are also the most morphologically dynamic regions in the coastal zone. Therefore, they are of great scientific interest. Their behaviour is governed by the delicate balance of oceanic processes such as tides, waves and mean sea level (MSL), and fluvial/estuarine processes such as riverflow. All of these processes can be significantly affected by climate change (CC) processes, which may result in negative physical impacts such as inlet closure/relocation, creation of new inlets, erosion of the coast adjacent to the inlet etc. Although CC impacts on some large tidal inlets (e.g. Wadden Sea inlets) have received some attention recently, the potential CC impacts on small tidal inlets (STIs) remain virtually unknown to date. Furthermore, whether currently available predictive tools are capable of simulating CC impacts on these systems also remains unknown. These knowledge gaps are a serious threat to effective adaptation to CC in STI environments. Just, this study attempts to investigate the potential range of CC impacts on the stability (i.e. closed/open state and locational stability) of STIs via the application of a sophisticated process based morphodynamic model (Delft3D) to strategically selected schematised inlet morphologies and forcing conditions.Results indicate that CC driven variations in system forcing are likely have profound impacts on inlet stability and also show that a process based coastal morphodynamic model (eg. Delft3D) is suitable for investigating potential CC impacts at small tidal inlets.

Low-frequency (infragravity) wave dynamics on a fringing coral reef were investigated using the numerical model XBeach (Roelvink et al., 2009). First, the skill of the model was evaluated in one- and two-dimensions based on its predictions of short waves (0.04-0.2. Hz), infragravity waves (0.004-0.04. Hz) and water level measurements (tidal and wave setup) obtained during a 2009 field study at Ningaloo Reef in Western Australia. The model calibration was sensitive to friction coefficients for short waves and current/infragravity bed friction, which were assumed independent in this model study. Although the one-dimensional cross-shore model captured the gradients in the dominant hydrodynamic processes at the site, a high current/IG bed friction coefficient was required. This resulted in an overestimation and a phase lag between the observed and predicted wave setup signal. In the two-dimensional model, a lower (more realistic) current/infragravity wave friction coefficient was required to achieve optimum performance due to the presence of significant reef and lagoon mean flows in the model, which led to reduced setup across the reef. The infragravity waves were found to propagate from the surf zone across the reef in a dominantly cross-shore direction towards the shore, but with substantial frictional damping. The infragravity waves were strongly modulated also over the reef by tidal depth variations, primarily due to the variability in frictional dissipation rates when the total water depth over the reef varied. Two mean wave-driven circulation cells were observed in the study area, with cross-shore flow becoming more alongshore-dominated before exiting the system via the two channels in the reef. The results reveal that short waves dominated bottom stresses on the forereef and near the reef crest; however, inside the lagoon, infragravity waves become increasingly dominant, accounting up to 50% of the combined bottom stresses.

Probabilistic estimates for coastal storm erosion volumes are increasingly being sought by contemporary risk based coastal zone management frameworks. Such estimates can be obtained via probabilistic models that incorporate a structural function element which calculates storm erosion (i.e. storm erosion model). Intuitively, the more sophisticated the storm erosion model embedded in the probabilistic model, the more accurate and robust the probabilistic storm erosion volumes should be, albeit at significant additional computational cost. This study assesses the relative performance of three storm erosion models with varying levels of complexity when embedded within Callaghan et al.'s (2008a) probabilistic framework for estimating storm erosion. The storm models tested are: the analytical Kriebel and Dean (1993) model, the more complex semi-empirical SBeach model and the highly complex and process-based XBeach model.The probabilistic model is applied at data rich Narrabeen beach, Australia. Kriebel and Dean (1993) and SBeach are used 'on-line' in the probabilistic simulations, while XBeach is used with an innovative off-line tabulation approach to facilitate reasonable computational times. SBeach is calibrated for a mid-range erosion event while XBeach is validated for the same single erosion event as well as for all measured storm erosion volumes during the 30. year study period. The Kriebel and Dean (1993) model is used with recommended parameter settings and therefore does not require calibration.When both SBeach and XBeach are calibrated against the single erosion event, SBeach provides the most accurate and robust probabilistic estimates of storm erosion. However, when XBeach is calibrated using the entire erosion volume data series, the results improve significantly raising the accuracy and robustness of the probabilistic estimates of storm erosion volumes obtained with XBeach to be on par with those obtained with SBeach. However, only XBeach predicts storm erosion volumes with the physically more plausible behaviour of a downward concave tail shape when plotted as cross-shore beach-erosion volume on a vertical linear axis against return period on a horizontal logarithmic axis.The simulation time (on a standard single processor) when using the simple Kriebel and Dean (1993) model is about 1. day, whereas for SBeach (on-line) and XBeach (tabulation), the simulation time is about 1000. h. However, the physically more plausible and the more accurate and robust results that can be obtained with SBeach or XBeach justifies the additional computational cost.

Low-frequency (infragravity) wave dynamics on a fringing coral reef were investigated using the numerical model XBeach (Roelvink et al, 2009). First, the skill of the one-dimensional model was evaluated based on its predictions of short waves (0.04-0.2 Hz), infragravity waves (0.004-0.04 Hz) and water level measurements (tidal elevation and wave setup) obtained during a 2009 field study at Ningaloo Reef in Western Australia. The model calibration was sensitive to friction coefficients for short waves and current / infragravity bed friction, which were assumed independent in this model study. The infragravity waves were found to be generated primarily in the surf zone through the breakpoint generation mechanism rather than through offshore forcing. The infragravity waves were also strongly modulated over the reef by tidal depth variations, primarily due to the variability in frictional dissipation rates when the total water depth over the reef varied. The results revealed that short waves dominated bottom stresses on the forereef and near the reef crest; however, inside the lagoon, infragravity waves become increasingly dominant, accounting up to 50% of the combined bottom stresses.

The coastal system consists of a sub-aqueous and a sub-aerial zone which can be separated by a border. At this border sediment exchange takes place from one zone to the other. This paper hypothesizes that conditions and therefore sediment exchange at this border are dependent on active profile characteristics. To analyze morphological developments due to combined marine and aeolian processes data acquired at a measurement site located along the southwest Holland coast is exploited. Based on the monthly morphological profile measurements the border between the marine and aeolian zone is determined. It is found that during accretive conditions the vertical location of this border, and with that the conditions near the border, is dependent not on the foreshore slope of the surf/swash zone as expected but on the slope of the entire active profile.

The well-known empirical relationship between the equilibrium cross-sectional area of tidal inlet entrances (A) and the tidal prism (P), first developed by O'Brien (1931), has been extensively reviewed. Our theoretical investigations indicate that a unique A-P relationship should only be expected for clusters of inlets that are phenomenological similar (i.e. fairly similar hydrodynamic and morphological conditions), and that the exponent q in the A-P relation should be larger than 1. However, relevant published data available to date do not clearly support this theoretical finding. A re-analysis of the available data sets by Stive et al. (2009) indicated that they may not be sufficiently reliable to verify our theoretical finding with regard to q>1 due to the violation of the condition of phenomenological similarity, and possibly also due to violating the initial definitions given by O'Brien (1931) in estimating the tidal prism. The resolution of this issue is important because slightly different values of q result in significantly variable values for the equilibrium cross-sectional area of the tidal entrance. This may have significant implications in determining the true stable equilibrium entrance cross-sectional area. Here we present a re-analysis of the available data with a focus on determining the phenomenological dependencies of the A-P relationship. The available A-P data from the US Pacific, Atlantic and Gulf coasts (Jarrett, 1976 and Powell, 2003) have been re-scrutinized and categorized following the above mentioned phenomenological similarity criteria, viz. similar tidal range, similar sediment size, similar littoral transport and similar hydraulic radius. All together, some 20 different categories were considered and A-P relationships were obtained for each category. Generally, high correlations were found between the stable inlet predicted by each A-P relationship and the corresponding data. However, only in a limited number of categories were they significantly better than the correlations for the complete datasets. Finally, we point out that only in a number of categories the q value associated with the A-P relationship exceeded unity as suggested by the theoretical derivations. In the majority of categories the q value associated with the A-P relationship does not exceed unity. This is truly disappointing, and we have no physical explanation for this and consider this issue unresolved.