Icebergs drifting through the Southern Ocean release fresh water and nutrients. This has local impacts on surrounding ecosystems and sea ice formation. On a global scale, salinity patterns and ocean circulation are affected. In addition,
tudying icebergs as a proxy for ice shelves in a warming climate can help predict future climate impacts and sea level rise. Furthermore, drifting icebergs can pose a threat to ship navigation and offshore projects. In the past, icebergs have been tracked mostly manually, a time-consuming and labour-intensive task. The most widely used data source for this is Synthetic Aperture Radar (SAR), as icebergs often have a much higher backscatter than their surroundings. A few attempts have been made to automatically track icebergs, but these methods do not allow tracking of icebergs that are only partially visible in a satellite image. In this study, a new method is proposed based on partial contour recognition using the contours’ curvature, a technique derived from the matching of ancient pottery fragments. Since the automatic tracking of multiple icebergs requires a large amount of data and computational resources, the web-based environment of Google Earth Engine is used. The new method, called the Contour Curvature (CC) method, is based on three main steps. (1) Detection of icebergs using Simple Non-Iterative Clustering (SNIC) in combination with a threshold function. (2) The icebergs targets are filtered using an area and solidity filter. (3) Among the remaining targets, the best match is selected by comparing the curvature function of the contour with the reference iceberg. The performance of the algorithm is tested by automatically tracking 15 icebergs and comparing
the results to the existing Centroid Distance Histogram (CDH) method. The overall performance of the CC method can be attributed in large part to the inclusion of the area and the solidity filter, with the latter serving as an overall shape filter. For small icebergs (< 10 km2), both the CC and CDH method perform poorly, due to the abundance of icebergs in this range. For medium to large icebergs (10 to 1000 km2), the methods show similar performance with one method occasionally outperforming the other method. For large icebergs (> 1000 km2), the CC method performs better. Since these icebergs are often only partially visible, this leads to strong deviations in the histogram used in the CDH method, making this method less suitable for these situations. Since the CC method allows for partial contour recognition, these icebergs can still be identified. Furthermore, due to the wide variety of backscatter conditions, the detection method occasionally fails to distinguish icebergs from their surroundings.

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.