Analysis of flood modeling through innovative geomatic methods

Abstract

[EN] A suitable assessment and management of the exposure level to natural flood risks necessarily requires an exhaustive knowledge of the terrain. This study, primarily aimed to evaluate flood risk, firstly assesses the suitability of an innovative technique, called Reduced Cost Aerial Precision Photogrammetry (RCAPP), based on a motorized technology ultra-light aircraft ULM (Ultra-Light Motor), together with the hybridization of reduced costs sensors, for the acquisition of geospatial information. Consequently, this research generates the RC-APP technique which is found to be a more accurate–precise, economical and less time consuming geomatic product. This technique is applied in river engineering for the geometric modeling and risk assessment to floods. Through the application of RC-APP, a high spatial resolution image (orthophoto of 2.5 cm), and a Digital Elevation Model (DEM) of 0.10 m mesh size and high density points (about 100 points/m2), with altimetric accuracy of -0.02 ± 0.03 mhave been obtained. These products have provided a detailed knowledge of the terrain, afterward used for the hydraulic simulation which has allowed a better definition of the inundated area, with important implications for flood risk assessment and management. In this sense, it should be noted that the achieved spatial resolution of DEM is 0.10 m which is especially interesting and useful in hydraulic simulations through 2D software. According to the results, the developed methodology and technology allows for a more accurate riverbed representation, compared with other traditional techniques such as Light Detection and Ranging (LiDAR), with a Root-Mean-Square Error (RMSE ± 0.50 m). This comparison has revealed that RC-APP has one lower magnitude order of error than the LiDAR method. Consequently, this technique arises as an efficient and appropriate tool, especially in areas with high exposure to risk of flooding. In hydraulic terms, the degree of detail achieved in the 3D model, has allowed reaching a significant increase in the knowledge of hydraulic variables in natural waterways.