Type de contrat: CDD
Durée: 4-6 months
Lieu de travail: Belvaux
We are seeking a highly motivated individual to join the “Environmental Research and Innovation” (ERIN) department. With a team of more than 170 scientists and engineers from life science, environmental science, and IT science, the department has the necessary interdisciplinary knowledge and skills to tackle major environmental challenges our society is facing today: climate change mitigation, ecosystem resilience, sustainable energy systems, efficient use of renewable resources, environmental pollution prevention and control. The successful candidate will integrate the “Remote sensing and natural resources modelling” group. The collaboration between the teams’s remote sensing scientists and hydraulic modellers is targeting the extraction of hydrology-related information from satellite Earth Observation (EO) data as well as the reduction of numerical modelling-based hydrological predictions.
Enhanced methods for monitoring temporal and spatial variations of water depth in rivers and floodplains are very important in operational water management. Currently, variations of water elevation can be estimated indirectly at the land-water interface using sequences of satellite EO imagery in combination with topographic data. In recent years high-resolution digital elevation models (DEM) and satellite EO data have become more readily available at global scale. The successful applicant will join our internationally leading team working on developing a recently introduced approach for efficiently converting remote sensing-derived flood extent maps into water depth maps using a floodplain’s topography information. These developments should enable large scale and near real-time applications and only require readily available EO data, a DEM and the river network as input data. The ongoing research targets the implementation of a hierarchical split-based approach that subdivides a drainage network into segments of variable length with evidence of uniform flow. Further testing should evaluate the impact of the resolution and accuracy of the EO data and the DEM on the results. For this reason different DEM data sets, including the recently published high resolution high precision TanDEM-X data set, will be considered in the processing chain. Moreover, different satellite EO data sets, such as Sentinel-1, TerraSAR-X and Envisat ASAR will be used and results inter-compared. A comprehensive evaluation of the obtained water depth maps with hydrodynamic model results and in situ measured water level recordings will be carried out on a number of test sites in the United Kingdom and Mozambique.