Addressing the impact of sea-level rise in coastal areas requires sustainable management strategies based on informed decision-making, and thus a shoreline projection is important. This research explores methods to improve shoreline change projections by obtaining a long-term shoreline change trend, empirically from \acrfull{sds} observations, and implementing a coastal impact model to project the future shoreline. We defined a heuristic approach to obtain a clean-\enquote{primary}- shoreline-change signal from all raw \acrshort{sds} observations that are available at transect. Long-term trend analysis from the primary shoreline-change signals results in a more accurate long-term shoreline-change trend. The improvement is also observed in Truc Vert, a meso-tidal case previously well known for low \acrshort{sds} accuracy, where the primary series results in accurate long-term shoreline trend regimes. Our projections in open sandy transects show that long-term trends predominantly influence shoreline change patterns and regimes compared to the retreat due to sea level rise. Using input comparable to the input of an earlier study, projections in seven out of eight regions indicate less retreat, except in North Carolina where the regional sea-level rise projections are relatively high. Compared to a hybrid, physics- and process-based, model, our projections showed higher progradation and erosion in \enquote{hot spots}, revealing limitations in linear trend extrapolation for capturing non-linear shoreline behaviour. We can conclude that future shoreline-change projections can be improved by using more accurate long-term shoreline-change trends. The framework's applicability is best suited to open sandy beaches with minimal human intervention. This highlights the need for better coastal typology classification that formalizes the concept of coastal type and coastal squeeze in the backshore of the beach. The outlook for the development of the shoreline projection framework is to explore the non-linear behaviour of shoreline change. This can be captured by decomposing the primary shoreline-change series into different signals that better represent the shoreline-change behaviour.

Over the period 1901-2012, the average global sea surface temperature has increased by 0.89 °C due to climate change and it is expected to increase consistent with global warming. As a consequence, marine ecosystems have become more susceptible to change in species and ocean chemistry. Due to the increase in sea surface temperature, the ocean pH has decreased in all regions. The main driver for this development is the uptake of approximately 30% of anthropogenic carbon dioxide (CO2) by oceans (IPCC, 2014). In a warming ocean, populations of warm-water species grow and populations of cold-water species decline. Furthermore, declines in coral growth are observed (Poloczanska et al., 2016).

Marine cloud brightening is a proposed way to counteract climate change. This geo-engineering technique brightens clouds by spraying aerosols in the air which act as cloud condensation nuclei in order to form cloud droplets. As a result, the albedo of the brightened cloud increases and more sunlight is reflected, reducing the global mean temperature (Latham et al., 2012). Although it is a potential way to counteract climate change, marine cloud brightening has never been applied on a large scale. Also, little is known about its feasibility.

We determined how physical properties of sea salt aerosols, specifically the aerosol mean geometric radius, the aerosol number concentration and the modal standard deviation of the initial aerosol spectrum, relate to the albedo of the brightened cloud using a numerical cloud parcel model with input parameters (Glassmeier et al., 2020). For six different values of the initial aerosol mean geometric radius, the initial aerosol number concentration and the modal standard deviation of the initial aerosol spectrum, i.e. the variability in aerosol radius, three output variables were generated in time and height. These output variables were the mean radius of cloud droplets, the cloud droplet number and the relative supersaturation. The differences caused by varying the input parameters were interpreted for the output variables. Also, we generated the albedo for the six different values of each input parameter mentioned.

The cloud droplet number depends on the aerosol number concentration. The higher the number, the more cloud droplets are formed. The cloud albedo does not depend on the initial aerosol mean geometric radius. The moment of activation depends on the initial aerosol mean geometric radius and the initial aerosol number concentration. The growth of the cloud droplets is mainly driven by condensation when variability in aerosol radius is small. The higher the initial aerosol number concentration, the higher the albedo of the brightened cloud. When the variability in radius is bigger, collision-coalescence occurs as the spectrum of cloud droplets consists of bigger radii which tend to collide and coalesce. This leads to bigger and heavier droplets which precipitate due to an increased mass, resulting in a decrease in cloud droplet number and a decrease in cloud albedo.

To conclude, three relations between physical properties of sea salt aerosol and the cloud albedo were found. First, the aerosol mean geometric radius at start does not affect the cloud albedo. Secondly, we found that the higher the aerosol number concentration, the higher the cloud albedo. Furthermore, a higher modal standard deviation of the initial aerosol spectrum leads to a lower cloud albedo.

We recommend further research on other types of aerosols, like organic matter and algae, and the effect of external forcing, like wind, on cloud brightening.

In the southeast of Spain heavy storms can occur in the late summer and early autumn, during which great amounts of rain pours down. During a storm that took place in September 2019, over 300 mil- limetres of rain fell in just five hours. Throughout the 2019 flooding event, the Rambla de la Carrasquilla has overflowed its banks and the adjacent agricultural lands flooded and large amounts of water ac- cumulated in the streets of Los Nietos. Since the 2019 flood, improvements to the river system of the Rambla de la Carrasquilla have been made. For instance: a relatively small culvert was replaced with a bigger one in 2021, to increase the discharge capacity. Due to global warming, the probability of occurrence of the heavy storms will increase and thus the probability of flooding. However, the lack of historical data makes it hard to assess the influence of different storms and the replacement of the cul- vert on future floods. Numerical models can be used to make predictions of floodings and gain insight in storm impacts. The aim of this report is summarized by the question: How can the flood areas and peak water levels of the Rambla de la Carrasquilla and its catchment be obtained by simulating three different scenarios based on peak discharges using HEC-RAS models?. At first a spatial analysis of the river system was done using QGIS. Hereafter a 1D and 2D model were constructed with the help of a Digital Terrain Model (DTM). QGIS and RiverGIS were used to define the geometry of the system for the 1D model, where the 2D model geometry was constructed in HEC-RAS itself. The dimensions of the structures in the river were measured using photogrammetry, due to which dimensions could be obtained with an absolute error of around 2 cm. Fieldwork was carried out to estimate the surface roughness of the main channel and parts of the flood plains.
The results consist of different floodmaps that were made using 1D and 2D HEC-RAS models with different settings and boundary conditions. For the 1D model, one run was done using a single reach for the whole river and another including a bifurcation for the downstream part of the river. It can be concluded that the 1D model approach is not very suitable for our research as it is unable to accurately construct the flooded areas. The 2D model performed better and thus was used to further investigate the influence of different model parameters and inputs. Important take-away points are that the time step is of large influence for finding a stable solution, which is found around Δ𝑡 = 1 [second] in this report. The influence of the surface roughness of the river bed and floodplains was investigated by using Manning’s n. These results showed clearly that a higher value for Manning’s n leads to a larger flooded area. When investigating the influence of structures (two bridges, a pipeline and a culvert) on the flooded area, it is found that the structures do not have a great influence. The reason for this is that at critical points, the river already overflows its banks when the flow is not hindered by these structures. Adding the structures makes this only slightly worse. Furthermore, the 2021 culvert only showed a slight improvement in flooded area with respect to the 2019 culvert.
In order to further calibrate the HEC-RAS models, a comparison was made with floodmaps that were constructed by the Spanish government. Both studies show similar results, although the government used a Digital Terrain Model with a higher resolution, which can have a large impact on the outcome. However, this government study cannot be used for validation of the models in this research, as the results are based on hypothetical situations instead of empirical data as well.
For further research it is recommended to investigate more accurate hydrological boundary conditions, based on empirical rainfall data. For both boundary conditions a constant value was taken, but the behaviour over time could change the output of the results. Besides that, it could be interesting to study the exact effect of using a Digital Terrain Model with a higher resolution for the Rambla de la Carrasquilla. As this can have a direct influence on the size of the flooded area. Furthermore, the approaches used in this research can be used for investigating different flood mitigation solutions. These solutions, for example heightening of the river banks or widening of the bed, can be implemented in the 2D model before applying them in real life.

In this study an analysis of the efficacy of using satellite data, in the form of InSAR measurements, as an extension of the volcanic monitoring network on Saba and St. Eustatius is performed. For this research, data from three different satellites that operate at three different wavelengths are available: ALOS-2 (L-band SAR), Sentinel-1 (C-band SAR) and PAZ (X-band SAR). The data are analysed through the formation of interferograms that are obtained using the Delft Object-oriented Radar Interferometric Software (DORIS) and Persistent Scatterer Interferometry (PSI) performed following the Delft Persistent Scatterer Interferometry (DePSI) algorithm.
The interferograms and PSI results differ strongly per satellite and are affected by the combined impact of several factors. In this study the impact of the misalignment of the master image used in the generation of the interferograms with respect to the Digital Elevation Model (DEM) is discussed, as well as the impact of the incidence angle, the spatial resolution, the temporal resolution, the perpendicular baseline, the number of available images and the wavelength.
The interferograms of ALOS-2 are of a good quality, however the low temporal resolution makes studying fast surface deformation difficult. However, they could be used to study surface changes in retrospect or to study slower processes, such as the pressurisation of a magma chamber, causing gradual surface deformation. The
low spatial resolution makes the interferograms of Sentinel-1 difficult to interpret and the interferograms for the PAZ data currently show too large amounts of decorrelation to study surface deformations.
The PSI analysis produces reliable results for Sentinel-1. The estimated linear deformation for the Persistent Scatterers (PS) shows constant values over both islands, which are centred around 0 mm/y and have low standard deviations. Therefore it is assumed, based on the data and prior knowledge about the area, that there is currently no deformation on either of the islands. The PSI analyses for the other two satellites do not provide reliable results, because the number of available images in the stacks is too low (only 10-12 images compared to the 116-123 available images for Sentinel-1). The PAZ data might be used in the future, when more images are available, however the low temporal resolution of the ALOS-2 data means that an appropriate stack cannot be acquired within the design lifetime of the satellite.
The ALOS-2 interferograms and the PSI analysis for Sentinel-1 could thus at present be a useful addition to the ground-based monitoring network. When a larger stack of data for PAZ is available, the PSI analysis could potentially be conducted again in order to determine its use as a volcanic monitoring tool.

TheAmazon-Orinoco river plume is a buoyant freshwater lens of 1.2 × 10⁶km², which has been traced over 2000 km from the Amazon river mouthinto the Caribbean Sea and along the Lesser Antilles. The river plume iswarmer than the surrounding open-ocean waters, with temperaturedifferences up to 1.5 ∘C caused by a stratification-induced barrier layerinhibiting vertical mixing and coloured matter increasing solar energyabsorption. Due to its magnitude, the river plume affects thehydrodynamics and the oceanic conditions in the Western Tropical NorthAtlantic (WTNA) substantially, but its variations on interannual time scales andthe corresponding relation to local sea-surface temperature (SST) are notwell understood. The Caribbean Sea is a region of high ecological value as itis home to extensive coral reefs, which are especially sensitive topersistent high SST. Therefore, this study investigates the interannualvariability of the Amazon-Orinoco river plume and its relationship to SSTsin the Caribbean Sea and the WTNA. It is hypothesised that fresh anomaliesof the river plume salinity pattern are indicative of a more extensivetransportation of the heat contained in the river plume. As a result, itis expected that interannual variations of dominant river plume pathwaysaffect the magnitude and location of anomalous SSTs. To test thishypothesis, model reanalysis fields of oceanic conditions from 1993 to 2017are used to conduct statistical analyses. In this context, the river plumevariability is determined using specific regions of freshwater influenceestablished using Empirical Orthogonal Function (EOF) analysis ofanomalous sea-surface salinity (SSS). Cross-correlations analysis relatingthese EOF modes of with atmospheric processes show that the interannualvariability of the river plume is dominated by wind-inducedadvective transport and -mixing. Strong winds along the Brazilian shelfare related locally increased SSS, while a weak southward component makesfor extensive spreading of the low-salinity plume waters. Additionally, weshow that high river discharge affects SSS east of the Lesser Antillesafter a lag of three months. Through its modulation of these atmosphericprocesses, there is a strong indication that the El Niño-SouthernOscillation affects SSS variability in the main along-shelf northwestplume pathway, with low SSS 1–9 months after a La Niña event. DecreasedSSS are found in phases 2 and 3 of the Madden-Julian Oscillation, whileincreased SSS was observed in phases 6 and 7. However, the evidence forthis relation is weak and should be investigated in further research.
The results show that, opposed to the hypothesis,a more extensive river plume is not associated with higher SSTs in theCaribbean Sea. However, strong correlations are found between river plumesurface area and SSTs at a lag of 1 year. Based upon results of previousstudies, we argue that the river plume has the ability to pre-heat themixed layer in the WTNA leading to extreme temperatures in the followingyear. It is wise to conduct a Lagrangian parcel back-tracking experimentto verify this mechanism.

Coastal bays in the Caribbean accommodate different marine ecosystems, including seagrass meadows and coral reefs, which provide important ecosystem services. However, these marine ecosystems are endangered. Seagrass ecosystems have a key role in coastal bays, but despite their alarming rates of loss, they receive little attention compared to other marine ecosystems. This study aims to provide a better understanding of the role of seagrass ecosystems in coastal bays by assessing their impact on the morphodynamic behavior. In order to achieve this, an existing hydrodynamic model has been extended to include morphodynamics. Two different bays have been investigated: Baie Orientale and Baie de l’Embouchure (St. Martin). These bays represent a partially exposed and fully sheltered bay, respectively. Both regular wave conditions, as well as extreme storm conditions, have been investigated to understand the consequences of seagrass loss on coastal erosion for different environmental climates. The coastal erosion has been found to be more prominent in the exposed region, whereas the more sheltered areas are more resilient. The erosion takes place in shallow waters but remains limited under regular swell conditions. The increased wave energy, during the extreme storm event, increases the erosion rates considerably. However, the regular swell conditions are normative in shaping the morphological development of these coastal bays when longer timescales are considered. The seagrass counters erosion most effectively in the foreshore and much less in deeper regions. Removal of seagrass in the foreshore (between 1-3m) halves the sediment stabilization. In contrast, the sediment stabilization increases if the meadows are able to spread especially towards the shore. In addition, the wave energy and waveform have a significant impact on the sediment stabilization. The stabilization typically decreases for higher and shorter (storm) waves, whereas it increases for smaller and longer (swell) waves. The long-distance interactions between seagrass meadows and coral reefs have led to their mutual coexistence, which is also found to be beneficial for the erosion control of the coastal bays. The dissipation of wave energy on top of the reefs fosters the sediment stabilization by seagrass. Moreover, the impact of the reefs on sediment stabilization also increases in the presence of seagrass meadows due to the additional drag exerted by the seagrass. The seagrass meadows are typically more effective under swell waves, whereas the reefs are more dominant in the dissipation of storm waves. Seagrass meadows and coral reefs form thus a synergy, in which the stabilization of sediments provided by the individual ecosystems is facilitated, reinforced, and complemented by the proximate presence of the other ecosystem. Finally, the role of seagrass on sediment stabilization has been explored under climate change. The coastal erosion increases for the considered sea-level rise scenarios. The impact of the seagrass on sediment stabilization decreases when the bays, seagrass and reef ecosystems are not able to keep up with sea-level rise. The synergy between seagrass and reefs emphasizes that the responses of both ecosystems are of importance for the future of tropical sheltered bays and should therefore not be managed in isolation.

The Greenland Ice Sheet is the world’s second largest ice sheet, storing an equivalent of 7.3 meters of sea level rise. Due to climate change, the Greenland ice sheet is currently losing mass at an accelerated rate. Ice sheet models are used to project long term melt of the ice sheet, which are often forced by output from climate models. Most of the multi-millennium time scale ice sheet simulations conducted in the past used SMB calculations based on empirical relationships between melt and temperature (Positive-Degree Day schemes). In this thesis, I address the question of the future evolution of the Greenland ice sheet by means of an ice sheet model forced with an elevation dependent SMB field that accounts for the energy available for melt. This work focuses on key variables such as ice thickness, ice area, velocity and contribution to eustatic sea level rise, and assesses the reversibility of the mass loss. For this thesis, I performed uncoupled CISM2.1 simulations which were forced by the elevation- SMB field from a coupled CESM-CISM simulation. The coupled simulation used to force the ice sheet has a length of 160 years and a CO2 concentration that is increased with 1% per year from pre-industrial levels and capped at 4 times CO2. Time segments with 2x, 3x and 4x pre-industrial CO2 concentrations of this CESM-CISM run were used to force the ice sheet on multi-millennium time-scales. In addition, a Recovery from 4x CO2 was conducted in which the pre-industrial forcing from a coupled CESM-CISM simulation is re-introduced after 55% mass loss. The 2x, 3x and 4x CO2 scenarios resulted in a cumulative sea level rise of 0.49 m, 3.0 m, and 8.2 m by year 4,000. The 2x CO2 scenario resulted in limited retreat and stability within 4,000 years. No stability of the ice sheet was attained by year 8,000 in the 3x CO2 simulation, with a final Mass Balance of -108.8 Gt/yr (0.30 ± mm/yr). The 4x CO2 simulation resulted in the complete deglaciation of the ice sheet within 3,000 years. Despite the lower initial topography compared to the pre-industrial ice sheet, the Recovery from 4x CO2 simulation resulted into expansion of the ice sheet. Within 4,000 years, the mass increased from 46% to 67% relative to the pre-industrial ice sheet.