Incorporação de Imageamento aéreo de alta resolução em modelos hidrodinâmicos para geração de manchas de inundação em um trecho de rio rural

Abstract

Developing countries, such as Brazil, have faced a significant increase in the frequency of flooding events due to factors such as accelerated city growth, increased population density, lack of adequate urban planning and inadequate land use. According to the World Meteorological Organization, climate and water-related disasters, such as floods and inundations, have been responsible for 45% of deaths and 74% of global economic losses in the last 50 years. The frequency of relevant studies and research on the subject has constantly increased, analyzing these aspects, mainly regarding extreme events, water resource management and land use and occupation management. The use of models that can analyze and predict river behavior situations and scenarios, among these models, is the HEC-RAS (River Analysis System of the Center for Hydrological Engineering) platform for external water studies. Therefore, the present work objective performed a hydrodynamic simulation of a flood patch, using the HEC-RAS model, in a stretch of a rural river in northeastern Brazil. The trained river region corresponds to a branch of the Cupissura River, in Itambé, Pernambuco, where flow and level monitoring has been carried out. The methodology changed in two main subdivisions, the preparation of the data that involved the modification of a DTM (digital terrain model), results from photogrammetric imaging, to compose the river channel, and the insertion of this data together with other monitoring data in the HEC-RAS platform. Flood spots were discovered from the original DTM and modified with the insertion of the channel, which presented expected behavior in hydraulic terms, however, with a discrepancy of approximately 17% in terms of area, increasing the importance of more in-depth analyses on the generation of digital elevation models in flood simulations, as well as comparisons through different methods aiming at a more detailed understanding of the results.