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Hydrological Modeling of Green Roofs Runoff by Nash Cascade Model

Author(s):




Medium: journal article
Language(s): en 
Published in: The Open Civil Engineering Journal, , n. 1, v. 13
Page(s): 163-171
DOI: 10.2174/1874149501913010163
Abstract: Background:

Green roofs (GRs) technology has gained increasing interest in recent years since it offers multiple benefits to urban environments, citizens and buildings. Eco-covers can capture some water nutrient pollutants, filter air pollutants and moderate the urban heat island effect. Beyond these benefits, abundant literature stresses the role played by the GRs from the hydrological perspective. They allow to face the increasing stress on the traditional urban drainage systems by reducing the annual stormwater runoff. In light of this, the hydrological behavior prediction of a vegetated cover is essential for urban planners, policy makers and engineers in order to quantify runoff mitigation potential so as to optimize their application.

Objective:

The aim of the present research is to meet this need by testing the accuracy of Nash cascade model in predicting the stormwater production of GR systems.

Materials and Methods:

The proposed model has been calibrated against hourly data of thirteen rainfall-runoff events observed at two experimental sites, both located within the campus of the University of Salerno, southern Italy. Event scale model calibration, aimed at the identification of the storage coefficient parameter, has been based on the optimization of a number of error statistics.

Results and Conclusion:

Despite its simplicity, the investigated model appears adequately to be able to predict the runoff production from the experimental green roofs with a good degree of accuracy, as described by the Nash-Sutcliffe Efficiency index, which ranges between 0.54 and 0.94.

Copyright: © 2019 Nataliya Krasnogorskaya et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

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  • About this
    data sheet
  • Reference-ID
    10380655
  • Published on:
    18/11/2019
  • Last updated on:
    22/11/2019