The resiliency of coral reef islands to changing environments associated with climate change is controlled by the delicate balance between the import and export of sediment. The majority of the sediment is derived from coral reefs for which the stability of these islands is directly related to reef health. Understanding the sediment signature and its drivers is essential to assess island resiliency. We performed a study on sediments from the islands Eva and Fly in the Exmouth Gulf, Australia. We analysed the grainsize distribution and the abundance of sediment producers in order to desribe and discriminate the spatial distribution of these sediment characteristics and performed statistical analysis to identify corresponding key environmental drivers. We found that the sediments were typically course sand-sized (500 − 1000 [μm]) and the dominant constituent is reef-derived sediment. The median grainsize of Eva island (549 [μm]) is nearly equal to the median grainsize of Fly island (540 [μm]). The standard deviation of the grain size distribution of the sediments from Eva island was much larger than at Fly island. However, analysis of variance showed there were no significant differences between islands (Eva/Fly), hydrodynamic regimes (high/low), distance to shore (inshore/offshore) and local habitat (reef/no reef). Furthermore, a distance-based redundancy analysis showed no key environmental driver responsible for the distribution in grainsize and composition of the sediment. The environmental factors which were analyses were depth, temperature, pH, dissolved oxygen content and the oxidation-reduction potential. The spatiotemporal scales that were studied are potentially smaller than the scales on which climate change effects act, which explains the absence of significant spatial differences or key environmental drivers. Based on these findings it is not possible to assess the resiliency of Eva and Fly islands, however a study from Perry et al. (2011) found that islands with their particular characteristics (sand-sized and coral-dominated) are expected to undergo major morphological change under a range of predicted climate change scenarios. This research provides a baseline for future studies to assess the stability of Eva and Fly islands or sedimentological research other reef-derived islands.

Knowledge of seafloor topography (bathymetry) is increasingly important as coastal environments are unprecedentedly stressed by climate change and anthropogenic pressure. The bathymetry of shallow nearshore waters is yet marginally monitored due to costly and time-intensive survey techniques. Methods to obtain satellite derived bathymetry (SDB) have become increasingly valuable. Mapping temporal change is however challenging, because the majority of these methods remain heavily dependent on situ observations. This thesis introduces an SDB approach to estimate temporal bathymetric changes, which omits the need for synchronous in situ data. The approach is based on a reference image correction method that enables direct comparison of multitemporal imagery and temporal extrapolation of a conventionally-trained bathymetry estimation model (BEM). Research focused on pre-processing multispectral imagery, developing a bathymetry estimation model and estimating bathymetry for times of absent in situ data. The proposed method is demonstrated with a case study in the Dutch Wadden Sea; a site characterised by dynamic morphology, high turbidity and homogeneous bottom type. A log-linear estimation model is obtained by linear regression on in situ observations and the three visible bands of Sentinel-2 imagery. Scarcity of high-quality Sentinel-2 imagery is managed by combing multiple images into a six-month composite. The availability of two sets of vaklodingen in situ observations allowed for training and testing two bathymetry estimation models (BEM 2016 and BEM 2019) and for cross-validating the depth estimates after a three-year extrapolation of these models. Bathymetry is estimated for times of absent in situ data by temporal extrapolation of the two estimation models. The extrapolation showed estimation of shallow bathymetric structures in up to four metre water depth with an RMSE of approximately one metre. Additionally, the migration direction of these bathymetric structures is successfully estimated. Within the tested three-year time frame, predictive power did not decrease. These results imply that estimation performance is governed by composite quality and predictive power of the bathymetry estimation model. The limited influence of temporal extrapolation on estimation performance suggests that the availability of high-quality satellite imagery and one set of non-synchronous in situ observations is sufficient to estimate bathymetry for times of absent in situ data. The proposed method potentially provides a tool for mapping temporal bathymetric changes of nearshore zones across the globe.

Natural occurring arsenic contamination of shallow aquifer groundwater is a problem affecting millions of people worldwide. Long term exposure to high concentrations results in severe medical conditions. On-going research into the origin and spread of the problem, risk mitigation and problem solving is of great importance. Sediment eroded and transported from mountains adsorbs arsenic (As) from river water onto its iron oxyhydroxides coatings. The geomorphology of the river is related to the concentration of As in shallow aquifers. Helicoidal flow in a meandering river leads to erosion of the cut bank in the outer bend and accumulation of sediment at the point bar in the inner bend. The result is an asymmetrical depth profile. The process of meandering and avulsion sometimes leads to the complete abandonment of a part of the river’s channel. This still-standing water body is known as an oxbow lake. Fine sediment settles from suspension and the oxbow lake gradually fills up with silt and clay. A clay plug forms, surrounding the sands of the adjacent point bar. Clay filled oxbow lakes formed by meandering rivers are high in organic content and the anoxic conditions in the hypolimnion are considered the source for the release of the adsorbed arsenic. Under reducing conditions the As is released from its solid state by microbial respiration. In the geomorphological setting of meandering rivers, abandoned channels and point bar, this process of reductive dissolution is the generally accepted release mechanism for arsenic. This research aims to provide insight in the potential arsenic volume in Holocene clay plugs in Ganges River floodplains and to present ideas on the migration processes of arsenic from clay plug to adjacent point bar. Migration of dissolved As occurs by advection and by diffusion. Satellite data from Google Earth Pro was used to simulate clay plugs with a Matlab model. The simulated data was used for the calculations of the surface area of the clay plug, the volume of the clay plug, the potential volume of As and the contact area between the clay plug and adjacent point bar. These geometric properties and concentrations of As were used to apply Fick’s first law to estimate the initial diffusion flux and the initial discharge. The surface area of the twenty selected clay plugs vary from 10! to 10! m2. The corresponding volumes are in the order of magnitude of 10! to 10! m3. The calculated As volumes range within the orders of 10! to 10! kg. The initial diffusion flux was calculated and ranges approximately between 15-300 g/m2year. For the volume calculations the exact shape of the depth profile turned out to be of little influence. For calculations of the contact area and thus the diffusion flux estimations, the true profile is crucial. In-situ sampling would provide data to minimize uncertainties and improve results.