Mangroves can provide coastal protection by attenuating waves, currents, and trapping sediment (Menéndez et al., 2020; Bao, 2011). The effect of mangroves on the hydrodynamics depends on their size, location, density, distribution and morphology of the vegetation (Mendez and Losada, 2004). Mangrove loss during storm events will therefore impact the coastal protection. The soil-root interaction and influences of soil properties in the resistance of a mangrove tree against failure is neglected in most studies of flood protection by mangroves, due to a lack in understading.

This thesis improves the understanding of the soil-root interaction by deriving the schematization for multiple failure mechanisms in comparison with field observations. Firstly, the wind and wave forces are modelled to determine the different loads in the forest. Secondly, a novel schematization was developed of different failure mechanisms considering the soil properties and root system. All results are developed for a case study of a fringe forest in Demak, existing of Avicennia marina rooted in a silty, saturated soil. To be able to determine the difference between the seaward and landward edge of the forest, the width of the forest is increased to 500 meter. Also, due to a lack of information on the mechanical strength of Avicennia m., the mechanical properties of Rhizophora m. are used, which will overestimate the resistance due to the higher wood density of Rhizophora m. (Manguriu et al., 2013).

The results show that the drag forces were largely influenced by the tree architecture (such as vegetation width and height), forest density and inundation of the tree. Larger wind and wave forces, and therefore a larger moment occured if the width of the vegetation increased. If the height of the tree increases, a smaller part of the canopy is submerged. This leads to a decreased area that is exposed to waves and therefore a declined wave force. A higher tree does enlarge the area subjected to wind forces, resulting in an increased total moment. Overall, the 2.8-meter tree analysed in this thesis experienced the largest horizontal forces and moment at the seaward edge of the forest due to the relatively large water depth at this location. Furthermore, the maximum horizontal force and moment shift to the landward edge for larger trees due to the increase of wind contribution. To investigate the stability under these loads, the different failure mechanisms need to be inspected.

The failure mechanisms of root breakage and slippage are not important because of the high safety factors and no observations in the field. The failure mechanism trunk breakage also showed a high safety factor, contradictiory to field observations pulling willow trees. The model results and field observations showed that a combination of upwind soil uplift and bending of roots was found most likely to occur. For this failure mechanism, the roots are schematized as beams with a spring-support on the leeward side of the trunk. The roots are exposed to the weight of the overlying soil and the overturning moment. The model showed that an increase in the participation angle α or root diameter, or increase in root length results in larger stresses in the windward roots. The amount of uplift enlarges when the root diameter or root length increases or the participation angle decreases. The modulus of subgrade reaction and modulus of elasticity influence the distribution of the overturning moment over the leeward and windward roots. The largest difference between the moment inside the leeward and windward roots is found with a high modulus of elasticity or high modulus of subgrade reaction. This difference is in agreement with the contrasting reaction between soil types as stated in literature (Dupuy et al., 2007).

The results show the dependence of the different failure mechanisms on soil and root properties, but also on the forest architecture. This research shows that the incorporation of mangrove stability in wave attenuation models cannot be neglected. Using an effective stress approach, instead of a total stress approach as in this thesis, would provide extra information, such as soil behaviour in time during loading. It is therefore recommended to measure pore pressures under static or cyclic loading, resulting in the progression of the effective stress over time. The inclusion of more accurate soil descriptions would enable reducing uncertainty in nature-based solutions and enables to describe the soil-root reaction to loading over time.

The wave attenuation of vegetation plays an increasingly important role in flood control in coastal areas. Past studies have found that the interaction of waves with vegetation mainly depends on hydraulic conditions and vegetation characteristics. Therefore, it is necessary to build vegetation models and quantify vegetation characteristics related to wave attenuation. Mangroves are one of the typical tropical intertidal vegetation. This study aimed to test the potential of using a low-cost, convenient smartphone-based structure-from-motion with multi-view stereo-photogrammetry (SfM-MVS) to accurately measure mangrove parameters related to wave attenuation.

SfM-MVS is a computer vision technique in which the point cloud coordinates of an object can be calculated from a series of 2D photos to generate a 3D point cloud model. This study first tested the optimal photography distance （about 25cm） and optimal weather conditions （cloudy and no sunlight） using the smartphone-based SfM-MVS method. Then, based on the optiaml usage conditions, 3Dpoint cloud models of 10 individual mangrove samples were reconstructed using this method, then the mangrove parameters related to wave attenuation were estimated according to the model: linear parameters (tree height, crown diameter, stem diameter, branches diameter) and the frontal area at a certain height. The true values of these parameters were measured using traditional hand measurements to evaluate smartphone-based SfM-MVS-derived parameter estimates.

The results show that the estimation of the linear parameters of the mangroves generally achieves high accuracy (RMSE of tree height, canopy diameter, stem diameter and thick branch diameter are all lower than 15%). There were significant negative biases in the estimates of tree height and crown diameter, and no significant biases in the estimates of stems and branches. The results of linear regression show that there is a strong positive correlation between the estimated values of all parameters and the true values. There are large errors and negative biases in the estimates of the frontal area at different heights. Overall, RMSE of frontal area at a certain height is 45.58% with a bias of -38.83%. This result showed that the SfM-MVS model resulted in a large underestimation of the frontal area at each height. A series of analyses showed that the main reason for the large error in the frontal area at a certain height was that the terminal branches with the lowest branch order (smallest diameter) were difficult to visualize in the SfM-MVS model. And this part of the branches actually occupies a large proportion of the frontal area.

This study demonstrates that smartphone-based SfM-MVS is capable of estimating mangrove tree height, canopy diameter, stem diameter, and thick branch diameter. Its accuracy is comparable to other existing methods such as TLS, ALS, camera-based SfM-MVS. However, the resolution is insufficient for very thin branches (<=5mm), which makes the method inaccurate in estimating the frontal area at a certain height. Factors such as photography distance and ambient lighting can affect the accuracy of the model. Compared with the currently used remote sensing technologies such as TLS, the smartphone-based SfM-MVS has the advantages of low cost, high flexibility, and low difficulty for those who lack professional knowledge or training, which makes it an alternative with great potential.

Knowledge of nearshore bathymetry is crucial for every aspect of the blue economy. Currently, it is expensive to obtain nearshore bathymetry at regional scales, and therefore this data is not available for many coasts. The data scarcity occurs especially in the global south and big ocean states that are at the highest risk from climate change. Currently the only global bathymetric dataset, GEBCO, provides depth data at approximately a 500 m resolution. This data is of limited accuracy in the nearshore zone because the source data is sparse in nearshore areas. Recent research has found that NASA’s ICESat-2, launched in 2018 to study the cryosphere, can incidentally capture bathymetric data. Some studies have been done in small sites, but the potential for a global product has not yet been investigated. This thesis proposes a method of using GEBCO data as a starting point and incorporating ICESat-2 data via a Kalman filter. This results in a product with a downscaled spatial resolution and improved accuracy without requiring any in-situ data. If other local bathymetry data is available, it can be added as input to the Kalman filter or used for validation of the method. Recent studies in lidar remote sensing have shown that ICESat-2 can capture nearshore bathymetry at depths of up to 20 me in tracks 0–3 km apart, provided atmospheric conditions are good and the water is sufficiently clear. Hence, this data could provide a source of high-resolution bathymetric depth profiles in tropical areas and possibly at higher latitudes. This research project proposes an automated processing chain, written in python, for extracting bathymetry points from the lidar data based on the density of the photon returns in the underwater zone. This method can reliably identify points containing bathymetric signal. To downscale the data using a Kalman filter, first global data from GEBCO is clipped to the area of interest, and then resampled bilinearly to 50 m resolution. Then, the ICESat-2 photon data for the area is processed to generate point estimates of bathymetric depth. To fill in the gaps between these point estimates, the bathymetric points are subsampled and interpolated to the same resolution as the GEBCO data using a universal kriging interpolator. This interpolator results in a raster of the estimated depth, and a raster of the estimated uncertainty. To update the interpolated GEBCO grid, the Kalman gain is calculated for each raster cell and using the Kalman state equation a new bathymetry grid is produced. If other data is available, the process can be applied recursively with other depth and uncertainty grids, allowing the Bayesian combination of any number of bathymetry datasets for the site. To validate the method, the improvement in RMSE is calculated between the resulting bathymetry grid and previously validated, high-accuracy survey data. The validation has been applied at several global test sites to verify that the method is generalizable to other regions. Validation sites are chosen based on the availability of validation data from either USGS survey or survey data from Van Oord projects. The approach was found to improve RMSE compared to validation data by up to 34% in some test sites. However, other sites showed marginal improvement, or increased RMS error. The results of this research could allow easier methods of characterizing nearshore bathymetry in remote areas. It could also be extended to include temporal variation – as more bathymetric data becomes available, it could be used to measure the dynamic changes of coastal systems. However, the method is limited by strict water clarity requirements and missing data due to atmospheric conditions. Despite these limitations, it could potentially be expanded to create a downscaled global bathymetry dataset of clearwater areas.

Coastal flood risk is expected to increase over the 21st century as a result of climate change and economic growth, which makes low-lying regions especially vulnerable. Global screening techniques are needed for a more widespread use of NBS in these flood prone coastal regions. This research expands on the current assessments done by developing a quantitative global screening method that evaluates the costs and benefits for two defence approaches; 1) increasing the dike height, 2) a hybrid solution that includes increasing of the dike height in combination with restoring mangroves and/or corals. The screening method is based on Van Oord’s Climate Risk Overview tool, in which, globally, coastal hotspots are indicated that have a predefined risk of flooding in the 21st century. The steps added by my screening method include; 1) determining which
NBS can be applied depending on the local physical conditions, 2) determining the costs for both NBS and conventional hard solutions, 3) determining the increase/decrease in flood risk of the different interventions for current and future conditions, 4) monetizing additional benefits that NBS provide, 5) assessing the benefits and costs to determine if NBS are the most optimal solution. The results of this global method are inherently limited by several simplifying assumptions and by the lack of high resolution local data, which influences the cost/risk estimates and corresponding site identification. For 2.6-3.3% of the coastal hotspots, NBS can reduce the investment costs in addition to being cost-beneficial. There is potential for expanding this work by adding sea grasses, salt marshes and oyster reefs as vegetated foreshore systems, and by including more thresholds to make the criterion for potential sites to apply NBS more strict.

Degrading mangrove forests and coinciding erosive coastlines is an urgent global concern. Mangroves are essential for their interaction with hydrodynamic and sediment processes at mangrove-mud coasts. Earlier on, solutions were sought in building ’hard’ structures, such as concrete sea walls, to lower incoming wave energy and enhance sedimentation to restabilize erosive coastlines and bring back mangroves. As these approaches proved to be counterproductive and even accelerate destabilization of the coastline, nature-based solutions might provide a new path to a durable solution. A pilot project was initiated in Demak, Indonesia, where several permeable brushwood and bamboo dams were constructed near the receding coastline. The open structure of the dams allows sediment to flow through, while they decrease wave heights by dissipation. This creates calmer conditions behind the dams and allows mud to settle. The deposition of fine sediments enhances a rise in nearshore bedlevel and provides nursery ground for mangroves to reestablish, realizing a first step towards rehabilitation of the mangrove ecosystem and restabilizing the coastline. A conceptual 2DH process-based model, using Delft3D FM, was created to analyse the effect of permeable structures under changing boundary conditions at various shorelines. Three boundary conditions were varied to see the influence on dam performance: wave height, wave direction and suspended sediment concentration. A decrease or increase in wave height resulted in similar rise in bedlevel elevation behind the dams. Without the dams, an increase in wave height increased the tidal flat elevation and steepened the foreshore, inducing a concave profile shape. Placing the dams on the tidal flat induces extra rise in elevation, but won’t mitigate the erosion of the foreshore. Smaller wave heights tend to reshape the profile towards a more convex profile. When dams are implemented on, an increase in bedlevel behind the dams occurs. The waves stir up sediment at the tidal flat boundary which are redistributed by the tidal currents forming a more convex profile. The dams could be placed best close to the shoreline to allow for the natural redistribution of the sediment when at the same time induce a rise in bedlevel for mangroves to reestablish. Altering the nearshore sediment supply affects the dam performance significantly. The dam performance increases for lower sediment supplies. Dams reduce erosion due to decreased sediment input, but it is likely a short-term solution. For higher sediment supplies, the coastline can more effectively restore by itself and the dams reduce in efficacy. The model results show an increase in dam performance for increasing wave angles (shore-normal to shore-parallel). The bed shear stress is decreased more effectively for smaller wave angles, but also reduce the sediment concentration behind the dams. With the many distinctive boundary conditions at mangrove-mud coasts in mind, the simplified model setup is made easily adaptable to enable future use of the model. Based on the model setup for Demak and the model results in this research, an improvement on the computational grid is suggested before applying the model to other coastal sites.