Recent research suggested that the digital elevation models can be considered, as an alternative to the altimetry data. However, the water prohibits the ability of monitoring the construction the waterbed, due to the loss of the returning signal. The elevation models have therefore a flat surface, which prohibits the extraction of the water level and volume variability.

The goal of this thesis was to develop a tool, that uses the elevations where no flatting had occurred, and create a linear representation of the shape of the lake or reservoir. The following research question was formulated:

What is the potential of applying elevation models to monitor the volume levels of lakes and reservoirs, when replacing the flat elevations with extrapolated depths?

The case study comprised of two parts. First, the validation of the water level extraction was conducted for pre-selected lakes and reservoirs. The results showed an average RMSE of 4.10 [m]. When analysing the distribution of lakes and reservoirs data, the RMSE was centred at 1.27 [m] (NED and ALOS) and 3.70 [m] (SRTM). The comparison between the three considered elevation models, showed a minor improvement regarding the relative water level. At the same time, it demonstrated that the number of waterbodies that can be monitored increases when applying the developed tool.

The second part of the case study aimed at providing an insight in the potential of applying the DEM for estimating the volume variability. An analysis of the USGS in-situ data compared to the results, showed that the overall RMSE decreased for each considered model. From the same analysis, the relative time-series could be determined for each model i.e., in case the minimum amount of surface area was available and in case the water level variation was significantly noticeable.

The results from this work indicated the potential of the global elevation models to monitor the volume levels of lakes and reservoirs. The developed tool demonstrated that elevations can be extrapolated, which would fit a more realistic shape of the reservoir at areas where the bathymetry was flattened or not found.

Accurate information for extracting the water level and assessing the volume variability of lakes and reservoirs currently depends on extensive hydrographic surveys. This work provides guidelines for an alternative method: the Linear Bathymetry for Digital Elevation Models tool.

As models are becoming more dominant for the prediction of sea level rise, a review of how this method type is operating is needed. Hence, for this thesis the research objective was to what degree of accurateness is the VM6_C model estimating the relative sea-level during the late Holocene of Sardinia and Crete? To support this question, the following three sub-questions were formulated: 1. What is the influence of components of the simplified sea-level equation in Sardinia and Crete? 2. What are the current tectonic trends for these locations? 3. To what extend can the archaeological sites at these locations be used for validating the model? The analysis for answering these questions, were divided into two case studies with three different acquisition methods: paleo data (1), GPS stations (2) and the VM6_C current rate of change (3). The accurateness was reviewed by comparing the computed trends and relative sea level heights of both these methods and case studies. This resulted in a rate of change of RSL by paleo data by Crete of 0.6173 mm/yr, whilst Sardinia had 1.297 [mm/yr]. In comparison the difference between the paleo and model data was respectively 0.45 [mm/yr] for Crete and for Sardinia is 1.03 [mm/yr]. The tectonic movement of both islands was concluded to be both subsiding at a millimetre magnitude. Therefore, the conclusion was drawn that the sea level was rising relative to the structures, yet the island was subsiding over time. Finally, the accurateness was reviewed by comparing the average difference between the historic sea level of the paleo data and the VM6_C model. Henceforth the variation was respectively -0.4302 [m] for Sardinia and -1.550 [m]. Thus, according to the results, the model has a higher accurateness relative to the paleo data when measuring at tectonic stable locations, however the trend can be better estimated at tectonic active locations. Which can be caused by the temporal resolution of paleo sites.