The use of high resolution ground-based light detection and ranging (LiDAR) datasets provides spatial density and vertical precision for obtaining highly accurate Digital Surface Models (DSMs). As a result, the reliability of flood damage analysis has improved significantly, owing to the increased accuracy of hydrodynamic models. In addition, considerable error reduction has been achieved in the estimation of first floor elevation, which is a critical parameter for determining structural and content damages in buildings. However, as with any discrete measurement technique, LiDAR data contain object space ambiguities, especially in urban areas where the presence of buildings and the floodplain gives rise to a highly complex landscape that is largely corrected by using ancillary information based on the addition of breaklines to a triangulated irregular network (TIN). The present study provides a methodological approach for assessing uncertainty regarding first floor elevation. This is based on: (i) generation an urban TIN from LiDAR data with a density of 0.5 points·m⁻², complemented with the river bathymetry obtained from a field survey with a density of 0.3 points·m⁻². The TIN was subsequently improved by adding breaklines and was finally transformed to a raster with a spatial resolution of 2 m; (ii) implementation of a two-dimensional (2D) hydrodynamic model based on the 500-year flood return period. The high resolution DSM obtained in the previous step, facilitated addressing the modelling, since it represented suitable urban features influencing hydraulics (e.g., streets and buildings); and (iii) determination of first floor elevation uncertainty within the 500-year flood zone by performing Monte Carlo simulations based on geostatistics and 1997 control elevation points in order to assess error. Deviations in first floor elevation (average: 0.56 m and standard deviation: 0.33 m) show that this parameter has to be neatly characterized in order to obtain reliable assessments of flood damage assessments and implement realistic risk management.

This paper presents the implementation of a learning methodology following a student-centred approach. The methodology is based on the use of project based and cooperative learning and mainly consists of commissioning students to prepare a presentation on a topic of their subject. Students work in groups, and later must deliver a real lecture to their colleagues. The proposed methodology was applied across 7 years and its implementation was monitored via day-to-day observations, annual surveys, the gathering of direct feedback as well as by analysing the students’ academic performance. Results show the ability of the proposed learning methodology to enhance motivation and engagement of students, facilitate the improvement of four soft skills (team-working, practical thinking, effective communication and critical thinking), eliminate absenteeism and facilitate long-term retention of the knowledge and skills acquired in a subject.