Coasts are constantly under the pressure of hydrodynamic conditions such as waves, tides, and storms. In the Netherlands, sand nourishments are executed every few years in order to maintain the country’s sandy beaches for purposes of safety, recreation, and ecology. In order to determine where to carry out these nourishments, the whole sandy coastline of the Netherlands is measured annually by Rijkswaterstaat. This annual survey, called JAarlijkse KUStmetingen (JARKUS), monitors where (increasing) erosive trends appear or persist and, due to its timespan (dating back to 1843), is a valuable dataset to understand the evolution of the Dutch coast. However, this measurement survey is restricted to its annual frequency and is costly. The use of optical satellite imagery for measuring land cover types and geographic features is rapidly becoming more popular due to their high temporal frequency and relatively low costs (due to the public availability of some satellite missions, such as NASA’s Landsat and ESA’s Sentinel-2 missions). This research studied the possibilities of using optical satellite imagery for measuring beach width dynamics in addition to the existing measurement campaigns.

In this study, we derived the Satellite-Derived Beach Width (SDBW) as the cross-shore distance between the Satellite-Derived Shoreline (SDS) and the Satellite-Derived Vegetation line (SDV). We adopted a widely used and validated method for SDS detection and adapted this method to establish the SDV detection method. The SDS and SDV are derived from optical satellites by deriving vectors from the border between two contrasting land cover types that are identified by differences in (sun)light reflectance values. The SDS and is derived from the contrast between water and land, the SDV from the contrast between and sand/sediment and vegetation. The SDBW data was measured from both composite and individual satellite images. The different techniques are suited for different applications, and both have their advantages and disadvantages. A composite image is an image that is composed of a sequence of individual satellite images available within a set window. E.g., a composite is the average image of all those images. Recent research showed that, at the cost of temporal resolution, composite images are suited for analysis of long-term (structural) shoreline trends since they mitigate certain factors influencing image quality (such as clouds and cloud shadows, waves and tides, and satellite instrument errors). Individual images are better suited for analyses of short-term dynamics since they provide instantaneous measurement data. However, they are hampered more by the factors mentioned above, and hence need to be screened before use...

For the transportation of the produced energy at offshore windfarms to the onshore grid, export cables have to be installed in the sea bed. Usually, at first trenches are dredged, in which approximately one month later the cables are installed. During this period the trench should remain sufficiently open to install the cables, fulfilling the depth requirements. This thesis focusses on the influence of sand wave fields on the sedimentation rate. It is investigated how trench sedimentation can best be assessed: with a simple model in combination with an extensive probabilistic assessment, or with a more complex model in which a less detailed probabilistic assessment is possible. The research is based on a case study at the Borssele Wind Farm Zone, for which the sedimentation rate is determined during the month April.
The sedimentation is primarily caused by a reduction in (the perpendicular-directed) flow velocity. Shifting of shoals or banks does not occur during the short timescale. The same holds for the sand waves, which do not migrate significantly during this time. Under influence of bedload transport however, the largest sedimentation rates are found for trenches around the sand wave crest. Closer to the troughs, less sedimentation can be expected.
During the probabilistic assessment of the trench sedimentation in flat bathymetries, it was found that the uncertainty obtained by Latin Hypercube Sampling (LHS) with an 2DV-model is reduced compared to the Monte Carlo-analysis (MC-analysis) in SedPit: the median is for both cases 0.06m, the 5-95 percentiles are 0.03m-0.09m and 0.04m-0.13m respectively. Including (idealized) sand wave perturbations in the 2DV-model, increases the range of the P05-P95 values for in trench sedimentation to 0.01 and 0.13m.
Based on the results, it is concluded that SedPit can be used as first assessment tool for the trench sedimentation, since it covers the range obtained with the more complex 2DV-model. The main advantage is the limited computation time of around 1.5 hours, compared to around 48 hours with the sand wave model. On the other hand, the 2DV-model is able to produce more accurate results.
The siltation rate in trenches located at sand wave crests is underestimated by SedPit compared to the results obtained from the 2DV-model. The opposite holds for trenches located at sand wave troughs, in which more sedimentation is predicted by SedPit. Adjusting the calibration parameter of sand transport in SedPit within the ranges provided in Van Rijn (2013) (0.5 for a sand wave trough and 1.0 for a sand wave crest), can at most decrease the difference between the models. For trenches located near a sand wave crest or trough, it is therefore advised to use at least the 2DV-model to assess trench sedimentation.
Furthermore, the 2DV-model can only be used in the case of perpendicular flow with respect to the trench-axis. Inclusion of the sand wave processes, which act in the 2DV-direction, for non-perpendicular flows therefore requires 3D modelling.

The world's coasts are at risk: an estimated 24% of the world's beaches are eroding. Extreme events such as storms continuously threaten the coastal region and pose a serious risk of coastal flooding. Under the influence of climate change, the seaward pressures are only expected to increase. Sea level rise is accelerating, storm intensities and frequencies will increase, and precipitation will become more extreme. At the same time human pressures such as coastal tourism and rapid urbanisation impose stresses to the coastal system. An estimated 23% of the world's population lives in the coastal zone where natural hazards cause a direct flood risk. Protection of the coastal region becomes more and more relevant. Coastal management strategies need to take the local circumstances into account. Therefore, a good understanding of the coastal zone is needed, but especially in data-poor regions there is a lack of geomorphological information such as slope and grain size. This thesis presents an alternative approach for acquiring this data with the ability to run on a global scale using remote sensing technologies. Remote sensing, satellite imagery in particular, has proven to be a promising new technology to monitor coastal regions at large temporal and spatial scales and is applied here to determine coastal slopes and sediment sizes. The approach has shown promising results and paves the way for an estimate of the grain size at beaches around the world. Some hurdles remain to be taken but the ability to do measurements of coasts around the globe using satellite imagery will change the way we study our coasts forever. This research is a major step forwards in the global monitoring of the world's coast, but only shows the beginning of the endless possibilities.

In the field of coastal engineering computational models are a commonly used tool to gain insight in dynamics of a coastal system, to gain insight in or hindcast the historical development or can be used as engineering tool to assess the efficiency and consequences of a proposed coastal measure. A new coastline model, called ShorelineS, is under development which promises to be applicable for long term simulations on geometric complex coastlines or unstable beach regimes where, for example, spit formation may arise. This new model aims to overcome the gap between existing relatively simple coastline models and more advanced coastal area models. In this thesis the applicability of this new model on spit formation was assessed. A study case in Lobito (Angola), were a natural spit has formed, was used for this purpose. Three research objectives are of interest in this thesis: 1) getting insight in the relevant processes regarding spit formation (in general and for the Lobito spit) 2) validate the longshore sediment transport module of ShorelineS and 3) asses (and improve) the spit formation in ShorelineS. An inventory of existing spit formations around the world and a detailed modelling study (XBeach) on the transport rates around a spit showed that especially the bimodality of the wave climate is an important process influencing the final shape of the spit. Regarding the calculation of the longshore sediment transport it was found that for the modelling of the wave transformation a distinction should be made between the static fixed offshore depth contours and the dynamically changing nearshore depth contours for changing coastline orientations. This distinction is essential to consistently and correctly determine the breaking wave parameters which directly influences the longshore sediment transport calculations. This distinction was implemented in ShorelineS using the concept of a so called ‘dynamic boundary’. The spit formation in ShorelineS was assessed by means of hindcasting the historical spit formation of the Lobito spit using the ShorelineS model. Continuing on the previous finding it was found that the coastal orientation for which the longshore transport is maximum, which reflects the direction in which a spit migrates, should be derived on the actual, spatial and temporal variating, transport curves. This in contrast to the theoretical fixed angle as suggested by Ashton et al. which was previously used in ShorelineS. Both the implementation of the dynamic boundary and the routine to find the actual (variable) angle of maximum transport were needed to be able to correctly hindcast the observed spit formation. With the current, underlying, model assumptions it is not possible to correctly model the local decay of longshore sediment transport along the head of the spit. The width and local shape of the spit is therefore controlled by the so called ‘upwind correction’ routine in ShorelineS. This routine was updated to prevent the grid resolution dependency which originally directly controlled (forced) the resulting spit width. With this updated routine the spit width is based on an average (expected) spit width. This new routine should be considered as a proof-of-concept, further research is required to further develop this routine and find ways to include some kind of feedback mechanism in the model between the forcing, shape and the resulting LST over the head of the spit.

Today's coastal zones are densely inhabited as the majority of the world's population lives in these attractive areas. The shorelines in coastal zones are shaped by complex spatial and temporal variable interactions between natural forcings like changes in mean sea-level, tides, wave and wind conditions, and storm surges. Besides, natural hazards such as coastal erosion, tropical cyclones, hurricanes, typhoons, floods, salt intrusion and tidal surges threaten a major part of the world's population. Furthermore, climate change is likely to increase the risk of natural hazards. As a response, humans changed the world's shorelines and the forcing-driven processes that work on them, to increase protection against hazards and keep supporting their activities. These human interventions are deployed discontinued in time, disperse spatially and might result in negative consequences leading to human-induced hazards. This research focuses on one particular hazard to coastal communities, coastal erosion, which is extended to a term referred to as shoreline evolution by incorporating coastal accretion as well. Up till now, detailed local-scale studies are able to expose human and natural drivers of shoreline evolution and provide a possibility to make a step towards intentional rather than accidental coastal engineering. Digital imaging and, more recently introduced, satellite imagery proved to be a promising new technology to measure and monitor shoreline evolution at bigger temporal and spatial scales. Nevertheless, the opportunity to develop a model that exposes the drivers of shoreline evolution on a planetary scale remains unexplored. This is due to the required computational effort as well as the large variability in coastal systems around the world. With an ever-increasing data availability, data-driven models incorporating Machine Learning (ML) proved to be an efficient alternative approach to heavy computing classical process-driven models in civil engineering practice. Next to this, a coastal classification can be used as a means to inventory the aforementioned variability. Therefore, the research objective in this study is to explore the possibility of exposing and classifying the drivers of shoreline evolution on a planetary scale, by employing ML on satellite imagery. Approximately 390.000 km of shoreline is analyzed for the past 33 years. This resulted in a statistically derived classification of natural and human-induced sandy shoreline evolution. By elaborating on this classification, it is found that natural and human-induced shoreline evolution accounts for approximately 16 and 25% of the total of globally exposed and classified shoreline evolution signals respectively. All outcomes in this research can support detailed local scale investigations and therefore provide an enhanced opportunity to make a step towards intentional rather than accidental coastal engineering. Hence, it is concluded that the developed and applied methods that employ ML on satellite imagery can be used to expose and classify (in)direct human and natural influences on sandy shoreline evolution using spatial and temporal characteristics on a planetary scale. 57% of the shoreline evolution signals is present in a regime with complex and combined (compound) influences, which still requires (rather than supports) local scale investigations to determine the correct influence or driver. More research is required to elaborate on the opportunities that can enhance insight in the compound regime, to improve the obtained results and advance the applicability of this study.

Due to climate change and sea level risethe coastal zones are getting exposed to increasing risks   like coastalrecession, putting in risk human lives and coastal infrastructure being worthbillions of dollars. Low lying countries like the Netherlands are consideredmore vulnerable to the effects of sea level rise. Large parts of the Dutchcoast have been eroding for centuries and nourishments schemes of approximately12 million m³ have been implemented annually in order to maintainthe coastline as it was in 1990. However, the future dune erosion will further increasedue to the impacts of climate change and hence the adaptation strategies shouldbe in line with the accelerated sea level rise and the possible effects thatmay bring. The most commonly used method to assess sealevel rise impacts on shorelines is the Bruun rule. However,Bruun rule’s deterministic nature cannot align with the risk-based framework thatcoastal zone management requires nowadays. This necessity initiated thedevelopment of a process-based model, the Probabilistic Coastline Recession(PCR) model, estimating the future coastal recessions in a probabilisticapproach. In this research, the PCR framework wasapplied at eleven locations along the Holland coast, in the Netherlands, underthree different SLR scenarios, the RCP4.5, RCP8.5 and Deltascenario. The availabilityof coastal profile data (from 1965 until now) and coastline position data (from1843 till 1980) made the Holland coast an ideal location to explore and extendthe applicability of the PCR framework. The most relevant assumptions for thiscoast were identified and explored. The recovery rate of the dune was a weakpoint of the PCR model and Holland coast was an interesting area to be tested.Three approaches of calibrating the natural recovery rate of the dunes werefollowed. In addition, the alongshore sediment transport which was assumednegligible to the previous case studies, in this work it was integrated intothe PCR model and pointed out that its contribution is important to the PCR.  For the eleven selected coastal profiles,20,000 simulations of 81 years (2020-2100) have been conducted and for everysimulation the most landward position of the coastline in every calendar yearhas been recorded. Hence, an empirical distribution of coastline recession forevery future year has been constructed. The ranges of the expected retreats in2100 (relative to 2020) for the different SLR scenarios are:0.5 m-155 m (for RCP4.5), 6 m-194 m (for RCP8.5) and18 m-172 m (for Deltascenario), corresponding to the 50 %exceedance probability values of the cumulative distribution function of thecoastline retreat. The average values of the coastal retreat for 2100 are 61 m,73 m and 97 m for RCP4.5, RCP 8.5, and Deltascenario respectively.The relevant average erosion volume by 2100 are 1664 m³/m,2005 m³/m and 2665 m³/m. According to thefindings, in 2100 the relative increase in volume loss along the entire theHolland coast is expected to be 95 %, 121 % and 173 %respectively for RCP4.5, 138 % for RCP8.5 and 195 % for Deltascenario.Finally, the results were compared to those raised from the Bruun rule method. Accordingto the findings, the majority of the profiles showing an erosive trend in thepast (before the ‘hold-the-line’ policy) raised slightly more conservativeresults when implementing the PCR model rather than when applying the Bruunrule method- especially under the Deltascenario. On the other hand, theBruun rule method is more conservative than PCR model for most of the accretiveprofiles. The PCR model can now be explored tolocations where the longshore sediment transport is not negligible. Theapproach followed in this study allows investigating the ability of the modelfor future coastal retreat estimates when a construction of a hard defence structureor a port may change abruptly the longshore sediment transport. Last, this studyadvances the PCR framework and can be a valuable assistance in the course offurther improving the model.  

Due to sea level rise and subsidence of land, coastal erosion is a serious problem in the Netherlands. And nourishments are common solutions to mitigate coastal erosion. Over the last decades, many studies have been focusing on individual nourishment performance to help us increase understanding of it. However, it is still not clear for us how the nourishments behave under different parameters (such as water depth of the nourishment crest, wave heights or nourishment size etc). This thesis tests the impact of different parameters on the erosion rate of the nourishments through measured data and numerical model simulations.

Seaports are important maritime commercial facilities and key hubs for national and global trades. There is a growing need for seaborne transport and, hence, seaport facilities, especially in emerging economies due to economic and population growth, such as in Africa. In sedimentary environments, port construction may induce coastal impacts regarding up-drift accretion and down-drift erosion. These coastal impacts potentially increase risks such as harbour siltation and coastal area erosion. To mitigate or even avoid these risks in the pre-construction stage, coastline evolution around ports needs to be well-understood. Analysis of long-term shoreline position data around existing ports can provide this understanding. However, long-term in-situ shoreline position data around ports are often unavailable or inaccessible, especially in emerging economies which are often data poor. Nevertheless, nowadays a growing database of satellite images provides these data on a global scale for the last decades. Furthermore, the launch of Google Earth Engine cloud computing platform in 2016 enabled accessibility and efficient processing of these satellite images. This development allows building an evidence database for shoreline positions around African seaports. With this database, coastline evolution trends around all ports can be analysed, inter-compared and related to environmental and port characteristics to derive lessons for future port development.
According to the World Port Index, 165 African seaports (after excluding river ports, offshore platforms and anchorages from 266 African ports) are identified. Only 125 ports at sandy coastlines, where SDS detection has been validated, are focused in this research. The results from this study show that coastline evolution, especially coastal area erosion, around the majority of African seaports is limited by the narrow sandy beach and rocky substratum of Afro-trailing coasts. However, there are still some ports at sediment-rich coasts having dramatic erosion and/or siltation hazards. After analysing common characteristics of these high-hazard ports, lessons are learnt for port development. Regarding site selection and breakwater design, ports with massive river sediment supply and/or ports at open coasts have larger negative coastal impacts. For coasts with river sediment supply, it is better to construct ports at the up-drift side of the river mouth to avoid interruption of river supplied sediment transport, which is found helpful for ports around West Mediterranean Sea. Shoreline management plan should be coupled with methods to maintain or increase river sediment supply, which can be learnt from shoreline retreating around ports in West Africa. Furthermore, to reduce coastal impacts around ports, port breakwaters at open coasts should be carefully designed regarding length and orientation to achieve a smaller shore-normal projected length, especially when the gross longshore wave power is massive. Regarding mitigation methods for coastline evolution impacts, shoreline protection structures are effective in reducing erosion hazards in the time scale of 30 years. Extension of the port breakwater (s) can be a temporary solution to mitigate the potential siltation problem but to reduce the down-drift erosion problem at the same time, sediment by-pass system, which is proved to be successful in South African ports, can be designed.

Evolution of coastline position under the influence of natural and anthropogenic processes is directly linked to the development of seaside societies. In the context of coastal zone management, process-based morphodynamic models are often used topredict coastline evolution and support the decision-making process for adaptation/mitigation strategies. Frequently, the processes driving themorphodynamic evolution transcend the applicability limits of a single model. In those cases, model ensembles can be used to estimate coastline change under the joint effect of the relevant processes. However, model output and in extent the aggregated result are characterised by uncertainty originating among others from forcing variability and parameter imprecision. The increasing exposure ofc oastal societies to coastal recession risks and emergence of risk-informed coastal zone management create the need for aggregated coastal recessionestimates with quantified uncertainty. This study investigates different statistical methods for forcing and parameter uncertainty quantification around coastline change estimates from process-based morphodynamic models. Subsequently a numerical convolution approach for the aggregation of the probabilistic coastal recession estimates from multiple models was formulated to account for the combined uncertain effect of processes acting on different timescales. The methods of this study were applied on Anmok beach, South Korea, a coastal stretch experiencing erosion caused by long, intermediate and short timescale processes. Available UNIBEST-CL+ and Delft3D model schematizations from theCoMIDAS research program, capable of simulating the relevant processes, were utilised. Following a literature review, two methods were considered applicable for process-based morphodynamic models: Standard Monte Carlo (SMC) and Latin Hypercube Sampling (LHS). The application of both methods on the UNIBEST-CL+model schematisation enabled the evaluation of their relative performance based on the precision of the different coastline change estimates achieved for the different sample sizes. Only LHS was applied on the Delft3D model schematisation due to computational demands limitations. Subsequently,the scenario-based approach currently used for the aggregation of multi-modelcoastline change outputs was extended to explicitly account for the uncertainties quantified in the individual model outputs. A numerical convolution approach, using Monte Carlo sampling, was suggested for linear super position of the contributing probability distribution functions. The advantages of this approach include speed, ease of implementation,comprehensibility and high resolution even at the tails of the aggregated distributions. Utilising this approach, the effect of alternative interventions (combinations of various breakwater designs with a small-scale nourishment) on the coastline change probabilities was quantified. The results showed that both methods (i.e., SMC and LHS) with adequate sampling can produce probability distribution outputs for coastline change when applied to the process-based models. SMC remains the most suitable method for coastline change uncertainty quantification for models with small simulation durations. The method gives quantified estimates of the precision, enabling the achievement specific target precisions, with the respective computational cost. For the smaller sample sizes used, LHS gave better precision results, proving more suitable for models with longer computational time. On the downside, without extra iterations of the procedure only upper estimates of the achieved precision for a specific sample size can be obtained. The probabilistic aggregation framework presented in this thesis has several advantages compared to the scenario-based approach currently used. It allowsfor quantified coastline change uncertainty estimates with the respective precision estimates and provides the distribution of the uncertainty across its range, information that could not be derived using the scenario-based approach. Different coastline change percentile estimates or confidence intervals with practical use to decision makers and the likelihood of any coastline change realisation of interest can be evaluated. The probabilistic uncertainty quantification and aggregation framework is believed to be useful for intervention assessment and comparison. It allows for the assessment of uncertainty around the morphological response under the combined effect of the processes acting on the coast with/without the intervention and thus the evaluation of the probabilistic intervention impact. Different interventions can be compared in terms of the probability of inducing desired/undesired morphodynamic realisations as well as in terms of the uncertainty range in the coastline change estimates.

Shore-normal breakwaters are constructed in coastal zones both for beach protection (erosion reduction) and port development (wave sheltering). These breakwaters have an effect on the waves, the (wave-driven) currents and hence, the sediment transport along the coast. The waves and tide force an equilibrium sediment transport along the coast in a natural unaltered coast. When breakwaters are constructed this sediment transport in the alongshore direction is (partially) blocked. This results in accretion at the updrift side of the breakwater and coastline retreat at the lee-side. Coastal erosion behind a breakwater can result in floods, destroy property or simply narrow the beach. Not only the short term effects of these structures (what happens during and short after construction) is important to know, also the long term effects need to be known; because the breakwaters are build for decades coastal influence of these breakwaters needs to be known for these time-scales as well. Therefore it is relevant to investigate the scale (in time and space) of these adverse effects beforehand.

In coastal engineering, numerical models are used to predict the impact of coastal constructions like breakwaters. High detailed models which take for all physical processes into account will result in accurate predictions but result in large computation times. Simplified models have smaller computation times and are more suitable for coastal impact predictions on larger spatial (10 - 100 km) and temporal (decades) scale. The objective of the thesis is to improve the coastline change predictions of models at decadal scale by reviewing the common practice and a new, very fast, module for lee-side wave computations and investigating different wave processes that can improve the wave modelling. This research will focus on (1) understanding of what wave processes are important for the coastline change and (2) advise on what models to use for which conditions and how to the improve model predictions.

The approach of this thesis is triple. First five different modelling approaches for wave modelling are compared, varying in computation time and usability, to a very accurate model that will be used as ground truth. The wave conditions will vary in direction and both wind waves and swell waves will be modelled. From this step de accuracy of these models for different wave conditions can be analyzed. The second step is to get an better understanding of the processes that are involved with the wave modelling. This information can be used to improve the accuracy of model approaches with high computation times. The last step is to see how this relates to sediment transport and thus the coastline change at the lee-side of a breakwater.

This can be concluded after the investigation of 3 wave model (SWASH, SWAN and the Kamphuis module)


SWAN model approach is for cases with wind waves a good model approach: the wave height, wave direction and the sediment transport are well representative. Also the setup differences are very similar to the ground truth model.
SWAN is not very accurate for cases with a small directional spreading. For these cases the diffraction is more important and there is not enough wave energy in the sheltered area nor is the wave direction well represented.
Kamphuis with Snellius (refraction) is for the case with a wide directional spreading, given the computation speed, pretty good. For the cases with a small directional spreading the wave height is not accurate.


The conclusions related to the influence of the wave processes are:


The refraction is investigated by comparing the Kamphuis module (which does not incorporate refraction) with the ground truth model. When Snell's law was applied to the kamphuis module the model results did show good results. Therefore the refraction is (especially outside the sheltered zone) very important to the wave direction.
There is a large difference for cases with small and large directional spreading. The SWAN model gives results can can be expected when no diffraction is present. Directional spreading both influences the wave height directly behind the breakwater as well as the influence lengt of the breakwater.
Diffraction does not play an important role for wind waves. The large directional spreading results in much smaller energy differences between the sheltered and the non-sheltered zone. Even SWAN without diffraction gives a good representation for wind waves. For swell waves however this is very different.Then diffraction is very important. There is a much larger difference in wave energy between the shelterd and the non-shelterd zone and for a good representation a model that can coop with diffraction is a must.
Current induced refraction of the waves has influences for waves of an incoming agle 0 to 30 degrees because this will result in rip currents along the breakwater that turn the waves up to an extra 10 to 15 degrees.



The relative sediment transport of the five modelling aproaches was also analyzed. The sediment transport proxy for the five modelling approaches showed that SWAN computes the wave height and direction well for wind waves. For swell waves however the model did not show good results. The reason is that there is no diffraction in SWAN, the diffraction computations with SWAN did not show much improvements either.

The sediment transportation proxy for the Kamphuis module with Snellius where expected to be good for wind waves, because the wave height and wave direction where well represented. However the length of the erosion pit was much smaller and also the shape of the erosion pit is very different from the other two models.

Numerical process-based morphodynamic models are widespread in coastal engineering practice and have become the new standard when it comes to assessing the impact of natural or man-made structures on coastal environments. The most common practice among engineers is to focus on a single spatial and time scale, which means either neglecting certain processes under the assumption that they will average out, or performing detailed simulations for short time-spans in order to optimize the normally limited computational resources. Despite the efforts from several authors, at the moment there is a lack of a clear methodology which would allow incorporating the relevant physical phenomena only when required, hence optimizing the computational effort.

The above leads to the main research objective of this thesis: to gain insight in what is the added value of coupling process based morphodynamic models, regarding the morphological impacts near the beach. For this purpose two models that were originally conceived to resolve different timescales are selected; XBeach as a storm model, and the new suite from Deltares, Delft3D-Flexible Mesh (D3D-FM) as a long-term morphodynamic model. The area selected as study site is Anmok beach, located at the east coast of South Korea. The coastal erosion at this location is not yet well understood (mainly due to human interventions and storms) plus the micro-tidal wave-dominated environment makes this location ideal for this study. Recent researches on this site have found that there is a delicate balance between the stormy and calm periods, where the high energy wave events are the main drivers of local morphology.

One of the main findings in this thesis is that the coupling of independently calibrated models does not necessarily provide better morphodynamic results than the results obtained by running each model separately. Including different processes such as infragravity waves or Eulerian mass transport (which enhances the offshore sediment transport in the surf zone) during highly energetic events tend to generate large supratidal beach erosion. However, the post-storm recovery mechanisms present in long-term morphodynamic models are not sufficient to bring the sediment back to the beach. Therefore, it is recommended to include all the relevant physical processes (storm erosion and post storm recovery mechanisms) when following a coupling approach in order to have a coherent morphodynamic balance. Furthermore, the coupling of models can play an important role in identifying which processes are missing or are not fully represented by the different modelling packages.

The erosive effect of cumulative storms was shown to be relevant in the short to medium term and might become a key parameter when defining, for instance, the worst case scenario regarding shoreline retreat. Despite the fact that uncoupled long-term morphodynamic models produce better average results in the case of Anmok beach, the implementation of a coupled scheme was proven to be important when the erosion due to cumulative storm effects cannot be neglected.

Among the advantages of using D3D-FM for this work is the implementation of the Basic Model Interface, which meant an important reduction in bookkeeping efforts and the possibility to seamlessly couple D3D-FM with XBeach. This procedure allowed for the incorporation of more complex phenomena (such as infragravity waves) with an acceptable increase in computational time.

A research version of Delft3D (D3D) with specialized sediment transport equations in the swash zone was tested in an attempt to enhance the post-storm recovery mechanisms. The results obtained are promising in the sense that the accretion of the shoreline and lower dry beach was reasonably enhanced, especially when considering all the limitations involved in modelling the morphodynamics of the swash zone with a stationary wave model. Another important conclusion is that these models were capable of depositing the sediments at the lower backshore at best. Hence, there is still the need of a mechanism/process capable of transporting the sediments farther upslope into the dry beach or dunes, such as aeolian transport.

The decision to undergo with a coupled or uncoupled approach depends on case-by-case basis. For current practice, it is recommended to develop a coupled simulation in the medium-term, where both storms and calm periods have significant effects and where the intra seasonal variation could be a parameter of interest. For short-term simulations, an uncoupled storm model (e.g. XBeach) is recommended as is the most accurate for such a time span. For long-term simulations, the general recommendation is to run an uncoupled long-term model such as D3D. In this case the storm erosion and post-storm recovery processes are expected to average out, being the long-term model the most suitable package to obtain average morphological results.

For future work it is recommended to add an aeolian process-based model and incorporate the swash zone sediment transport module into D3D-FM as this would move us one step closer towards the development of a fully coupled model where all the relevant processes (storm erosion, post storm recovery and aeolian transport) are included.

Predictions of coastal morphology evolution are necessary to assess engineering solutions as well as understand coastal systems behaviors. Among the tools used to predict morphological evolution are the process-based models that make use of physical laws and empirical knowledge. Such models account for a considerable range of coastal processes and are rather complex, hence demanding substantial computational time. Usually, when using complex process-based models, reducing the size of the input parameters, named input reduction, is made necessary in order to reduce the computational effort.
The scope of the present study is to understand the influence of reduced wave climate on simulated morphological evolution. Input reduction algorithms, sequencing methods, number of cases and duration of the reduced wave climate were investigated and evaluated with a 1D (cross-shore) brute force simulation of 3.3 years in Noordwijk, Netherlands. Noordwijk is a wave-dominated sandy beach characterized by a double sandbar system that has an inter-annual net offshore migration. The assessment of the methods was carried out through cumulative skill scores, temporal evolution of profile perturbations (bars and troughs) and profiles at the end of the simulation.
Furthermore, the findings on the Dutch coast were validated with a 1 year-long, 1D (cross-shore) brute force simulation in Anmok beach, South Korea. Anmok is a wave-dominated sandy beach with crescentic bars in the nearshore morphological evolution.
One of the conclusions of the present study is that input reduction methods that have more control on the definition of bins such as pre-definition of wave height and wave direction bins perform better than methods that are based fully on the statistical properties of the wave dataset. Also, the order of the wave cases in the reduced wave climate must resemble at its best the natural variability of the full wave climate. Finally, a less robust reduced wave climate (with less representative wave conditions) applied in a smaller timescale performs better in terms of morphology than a more robust reduced wave climate (with more representative wave conditions) applied in longer time-scales.