Assessing the Extent of Flood-Prone Areas in a South-American Megacity Using Different High Resolution DTMs
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Case Study: The Extreme Event of March 2019
2.3. Dataset and Computer Settings
2.4. HEC-RAS
2.4.1. Theoretical Foundation
2.4.2. HEC-RAS Simulation
2.5. Validation
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Year (Descending Order) | Number of Events Per Year | Dates of Occurrence (Day/Month) | |||
---|---|---|---|---|---|
2022 | 4 | 02/02 | 17/02 | 01/03 | 12/03 |
2021 | 1 | 18/11 | |||
2020 | 3 | 08/01 | 19/02 | 24/02 | |
2019 | 3 | 04/02 | 15/02 | 10/03 | |
2018 | 2 | 17/10 | 23/11 | ||
2017 | 3 | 06/02 | 06/04 | 27/11 | |
2016 | 2 | 15/02 | 06/06 | ||
2015 | 1 | 27/01 | |||
2012 | 2 | 17/01 | 28/11 | ||
2011 | 2 | 15/11 | 14/12 | ||
2010 | 1 | 17/02 | |||
2008 | 1 | 21/02 | |||
2005 | 1 | 11/01 | |||
2002 | 1 | 28/11 | |||
2000 | 2 | 12/01 | 26/01 |
Finer DTM | Finer DTM | Finer DTM | Finer DTM | |
---|---|---|---|---|
Computing intervals | 1 s | 15 s | 30 s | 60 s |
Mean (m) | 0.805 | 0.806 | 0.806 | 0.808 |
Standard deviation (m) | 1.215 | 1.215 | 1.215 | 1.215 |
Range (m) | 4.910 | 4.909 | 4.910 | 4.913 |
Minimum (m) | –1.552 | –1.552 | –1.551 | –1.549 |
Maximum (m) | 3.357 | 3.358 | 3.359 | 3.364 |
Missing points | 5 | 5 | 5 | 5 |
Computation time (hh:mm:ss) | 02:40:30 | 00:55:32 | 00:30:24 | 00:16:58 |
Finer DTM with Refined Channel Mesh | Finer DTM with Refined Channel Mesh | Finer DTM with Refined Channel Mesh | Finer DTM with Refined Channel Mesh | |
---|---|---|---|---|
Computing intervals | 1 s | 15 s | 30 s | 60 s |
Mean (m) | 0.809 | 0.810 | 0.811 | 0.813 |
Standard deviation (m) | 1.210 | 1.210 | 1.210 | 1.210 |
Range (m) | 5.038 | 5.038 | 5.039 | 5.040 |
Minimum (m) | –1.626 | –1.625 | −1.624 | –1.621 |
Maximum (m) | 3.412 | 3.413 | 3.414 | 3.420 |
Missing points | 5 | 5 | 5 | 5 |
Computation time (hh:mm:ss) | 21:08:20 | 02:50:31 | 01:37:39 | 00:50:59 |
EMPLASA DTM | EMPLASA DTM | EMPLASA DTM | EMPLASA DTM | |
---|---|---|---|---|
Computing intervals | 1 s | 15 s | 30 s | 60 s |
Mean (m) | 0.591 | 0.591 | 0.592 | 0.596 |
Standard deviation (m) | 0.966 | 0.966 | 0.966 | 0.964 |
Range (m) | 4.493 | 4.493 | 4.492 | 4.484 |
Minimum (m) | –1.577 | –1.576 | –1.575 | –1.566 |
Maximum (m) | 2.917 | 2.917 | 2.917 | 2.917 |
Missing points | 3 | 3 | 3 | 3 |
Computation time (hh:mm:ss) | 03:13:51 | 00:50:46 | 00:30:51 | 00:19:46 |
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Escobar-Silva, E.V.; Almeida, C.M.d.; Silva, G.B.L.d.; Bursteinas, I.; Rocha Filho, K.L.d.; de Oliveira, C.G.; Fagundes, M.R.; Paiva, R.C.D.d. Assessing the Extent of Flood-Prone Areas in a South-American Megacity Using Different High Resolution DTMs. Water 2023, 15, 1127. https://doi.org/10.3390/w15061127
Escobar-Silva EV, Almeida CMd, Silva GBLd, Bursteinas I, Rocha Filho KLd, de Oliveira CG, Fagundes MR, Paiva RCDd. Assessing the Extent of Flood-Prone Areas in a South-American Megacity Using Different High Resolution DTMs. Water. 2023; 15(6):1127. https://doi.org/10.3390/w15061127
Chicago/Turabian StyleEscobar-Silva, Elton Vicente, Cláudia Maria de Almeida, Gustavo Barbosa Lima da Silva, Ingobert Bursteinas, Kleber Lopes da Rocha Filho, Cleber Gonzales de Oliveira, Marina Refatti Fagundes, and Rodrigo Cauduro Dias de Paiva. 2023. "Assessing the Extent of Flood-Prone Areas in a South-American Megacity Using Different High Resolution DTMs" Water 15, no. 6: 1127. https://doi.org/10.3390/w15061127