A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Method to Establish Intense Rainfall Equations Based in Geoprocessing
Method to Establish Intense Rainfall Equations Based in Geoprocessing de Almeida et al.
https://orcid.org/http://orcid.org/0000-0002-4501-134X
https://orcid.org/http://orcid.org/0000-0003-2894-2481
https://orcid.org/http://orcid.org/0000-0002-7957-6402
https://orcid.org/http://orcid.org/0000-0002-4306-8334
https://orcid.org/http://orcid.org/0000-0002-6457-421X
The knowledge of heavy rainfall is essential for watershed management and hydraulic structure design. Heavy rainfall is characterized by an equation derived from sub-daily rainfall series that relates the rainfall’s intensity, duration, and frequency (IDF equation). This paper proposes a geoprocessing model to obtain the parameters for the IDF equations for places without rainfall data. IDF equations, from the literature, were used to obtain maximum rainfall intensity (im) for 96 combinations of durations and return periods. These ims were spatially interpolated, and the IDF parameters were established for each pixel through non-linear multiple regression. The performance of three different interpolators (inverse distance weighting, Kriging, and random forest) was evaluated. The analysis showed that spatialization by inverse distance weighting had the best performance to establish IDF Eqs. (3% of mean absolute percentage error), followed by random forest (8%) and Kriging (16%).
Method to Establish Intense Rainfall Equations Based in Geoprocessing
Method to Establish Intense Rainfall Equations Based in Geoprocessing de Almeida et al.
https://orcid.org/http://orcid.org/0000-0002-4501-134X
https://orcid.org/http://orcid.org/0000-0003-2894-2481
https://orcid.org/http://orcid.org/0000-0002-7957-6402
https://orcid.org/http://orcid.org/0000-0002-4306-8334
https://orcid.org/http://orcid.org/0000-0002-6457-421X
The knowledge of heavy rainfall is essential for watershed management and hydraulic structure design. Heavy rainfall is characterized by an equation derived from sub-daily rainfall series that relates the rainfall’s intensity, duration, and frequency (IDF equation). This paper proposes a geoprocessing model to obtain the parameters for the IDF equations for places without rainfall data. IDF equations, from the literature, were used to obtain maximum rainfall intensity (im) for 96 combinations of durations and return periods. These ims were spatially interpolated, and the IDF parameters were established for each pixel through non-linear multiple regression. The performance of three different interpolators (inverse distance weighting, Kriging, and random forest) was evaluated. The analysis showed that spatialization by inverse distance weighting had the best performance to establish IDF Eqs. (3% of mean absolute percentage error), followed by random forest (8%) and Kriging (16%).
Method to Establish Intense Rainfall Equations Based in Geoprocessing
Method to Establish Intense Rainfall Equations Based in Geoprocessing de Almeida et al.
https://orcid.org/http://orcid.org/0000-0002-4501-134X
https://orcid.org/http://orcid.org/0000-0003-2894-2481
https://orcid.org/http://orcid.org/0000-0002-7957-6402
https://orcid.org/http://orcid.org/0000-0002-4306-8334
https://orcid.org/http://orcid.org/0000-0002-6457-421X
The knowledge of heavy rainfall is essential for watershed management and hydraulic structure design. Heavy rainfall is characterized by an equation derived from sub-daily rainfall series that relates the rainfall’s intensity, duration, and frequency (IDF equation). This paper proposes a geoprocessing model to obtain the parameters for the IDF equations for places without rainfall data. IDF equations, from the literature, were used to obtain maximum rainfall intensity (im) for 96 combinations of durations and return periods. These ims were spatially interpolated, and the IDF parameters were established for each pixel through non-linear multiple regression. The performance of three different interpolators (inverse distance weighting, Kriging, and random forest) was evaluated. The analysis showed that spatialization by inverse distance weighting had the best performance to establish IDF Eqs. (3% of mean absolute percentage error), followed by random forest (8%) and Kriging (16%).
Method to Establish Intense Rainfall Equations Based in Geoprocessing
Method to Establish Intense Rainfall Equations Based in Geoprocessing de Almeida et al.
Environ Model Assess
de Almeida, Laura Thebit (author) / Cecílio, Roberto Avelino (author) / Pruski, Fernando Falco (author) / dos Santos, Gerson Rodrigues (author) / Abreu, Marcel Carvalho (author)
Environmental Modeling & Assessment ; 30 ; 141-155
2025-02-01
15 pages
Article (Journal)
Electronic Resource
English
Method to Establish Intense Rainfall Equations Based in Geoprocessing
| Springer Verlag | 2025
Local and remote geoprocessing applications
| Online Contents | 1999
Automated Well Permitting via GIS Geoprocessing Tools
| British Library Conference Proceedings | 2010
AN ARCHITECTURE FOR AN ENVIRONMENTAL PROCESS CONTROLLER BASED ON GEOPROCESSING
| British Library Conference Proceedings | 2009