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.

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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.@en

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.@en

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.@en

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.@en

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.@en

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.@en

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.@en

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.

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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.@en

Morphology is the study of forms, whether of animals, plants or words; coastal morphology is the study of coastal forms. Some of these forms are hard (like rock) and do not move much. Others, such as beaches, dunes, channels, sandbars, shoals, are made of mud, sand, or even gravel and move all the time. Understanding and predicting these motions are what coastal morphologists try to do.
The approach we take depends on the scale of the problem or process we are interested in. This scale ranges from small-scale ripples to entire tidal inlets or coast lines. The larger the length scale, the larger the timescale; the upper beach profile can adapt to a storm in hours; the coastline around a port can take decades to adapt, and the effects of closing a tidal inlet can be felt for many centuries.
In coastal engineering, morphology is a core discipline. It is needed to assess damage to beaches, dunes, and barrier islands during extreme events; it is needed to understand and mitigate coastal erosion; it is important in the design of ports, to assess impact on the coast and estimate dredging requirements for the navigation channel and basins; it is needed in the design and impact studies of land reclamations and finally, it provides scenarios to use in coastal zone management.
In this chapter, we will first discuss different types of coastal morphology models. We will then zoom in and focus on process-based modeling in more detail. First, the fundamentals of process-based modeling are described, which is followed by short descriptions of the commonly used types of process-based models. Subsequently, a number of modeling approaches considering different scales, from storm-event modeling to long-term modeling of estuaries are presented. We conclude by discussing some future directions.@en