Modeling of the hydrological performance of Green roofs in tropical Andean cities using SWMM
DOI
https://doi.org/10.22507/pml.v14n1a2
Document Type
Article
Publication Date
1-1-2019
Publication Title
Produccion y Limpia
Abstract
Introduction. Hydrological modeling is a tool that allows analyzing the effect of different weather conditions on the retention capacity of green roofs in intertropical areas. Objective. The SWMM software's capacity is assessed in order to represent the hydrological dynamics of green roofs under experimental conditions in the Colombian Andes. Materials and methods. From the results of an extensive monitoring of a green roof module located at the Universidad de los Andes, Bogotá, a sensitivity analysis is conducted and a model is implemented, calibrated and validated. The validated model is used to assess the green roof behavior for simulation with continuous storms and storms with different intensity, frequency and duration. Results. It is demonstrated that the calibrated model is able to satisfactorily reproduce the runoff percolated through the green roof with efficiency indexes close to 0.80 for the Nash-Sutcliffe index (NSE) and less than 6 % for the runoff volume error index (RVE). From simulation results, it was determined that an increase of 30 % in initial saturation can decrease the retention capacity of the green roof between 10 % and 17 % for simulated storms. Conclusion. The SWMM software is capable of representing the dynamics of an experimental green roof in the conditions of the Colombian Andes when it is properly calibrated and validated. Therefore, this model could be a useful tool to perform regional analyzes regarding the implementation of this type of SUDS in intertropical cities.
Volume
14
Issue
1
First Page
46
Last Page
60
ISSN
19090455
Recommended Citation
Tabares Catimay, Jeniffer; Gallo Martínez, Laura Marely; and Mancipe Muñoz, Néstor Alonso, "Modeling of the hydrological performance of Green roofs in tropical Andean cities using SWMM" (2019). Scopus Unisalle. 181.
https://ciencia.lasalle.edu.co/scopus_unisalle/181
Identifier
SCOPUS_ID:85078141608