| Full text | |
| Author(s): |
Escobar-Silva, Elton Vicente
;
de Almeida, Claudia Maria
;
da Silva, Gustavo Barbosa Lima
;
Bursteinas, Ingobert
;
da Rocha Filho, Kleber Lopes
;
de Oliveira, Cleber Gonzales
;
Fagundes, Marina Refatti
;
de Paiva, Rodrigo Cauduro Dias
Total Authors: 8
|
| Document type: | Journal article |
| Source: | WATER; v. 15, n. 6, p. 19-pg., 2023-03-01. |
| Abstract | |
Current forecasts estimate that almost 68% of the global population will be living in urban centers by 2050. As a result, the increase in impermeable surface area can result in severe hydrological impacts, such as the increase in surface runoff and the frequency of floods and their magnitude. Thus, this work analyzes the performance of the hydrodynamic model HEC-RAS for assessing the extent of flood-prone areas, using two digital terrain models (DTM) with different spatial resolutions (5 and 0.50 m). Four different computing intervals (1, 15, 30, and 60 s) were adopted aiming to evaluate the simulations outputs performance. Additionally, reported data by the civil defense are used for calibration and validation. In general, the model showed to be a powerful tool in the identification of susceptible areas to urban flooding. The simulated results in this work provide crucial geographic information when identifying spots with the highest risk of flooding, which should receive priority attention during such events. The simulations with a spatial resolution of 5 m showed the flood maps with the largest coverage of the flooded points (278 points out of 286-97.20%), within the shortest computation times. We highlight that the more refined DTM derived from spatial images did not produce the best flood simulation compared to the DTM with a spatial resolution of 5 m derived from orthoimages. (AU) | |
| FAPESP's process: | 21/11435-4 - Scenario-based projections of future urban floods by means of a loose-coupling between a CA-based urban land use change model and a hydrodynamic model: a case study in São Caetano do Sul (SP) |
| Grantee: | Elton Vicente Escobar Silva |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 20/09215-3 - Identification of pervious and impervious surface areas (ISA) using GEographic Object-Based Image Analysis (GEOBIA) and deep learning as input to drive a forecast model of urban growth |
| Grantee: | Cláudia Maria de Almeida |
| Support Opportunities: | Regular Research Grants |