Model Details, Parametrization, and Accuracy in Daily Scale Green Roof Hydrological Conceptual Simulation

Mirka Mobilia,Antonia Longobardi

doi:10.3390/atmos11060575

Abstract

In time, several models with different complexity have been proposed to predict the retention performances of a green roof. In the current study three conceptual models of increasing complexity in descriptive details, are calibrated and compared to experimental data. The proposed approaches consist of daily scale hydrological models, based on water balance equations, where the main processes and variables accounted for are the precipitation input, the evapotranspiration losses, and the maximum water storage capacity. Model detail increase is achieved moving from an approach using potential evapotranspiration and constant storage threshold to an approach using actual evapotranspiration and a variable storage threshold. The main findings confirm on one side the role played by evapotranspiration modeling and, on the other side, the good accuracy achieved, in a minimal calibration requirement approach, through the modeling of basic and elemental processes.

Highlights

In the relatively recent past, many scientific studies have demonstrated the potential of green roofs (GR) in pursuing the concept of sustainable stormwater management [1,2,3,4]
Further complexity arises from the considered particular hydrological processes and especially from the modeled evapotranspiration loss, as discussed in many recent works, as it directly impacts the green roof retention performances [13,14,15,16]
Mod A and mod as a climate forcing for the GR model, not dependent on the stored water depth V

Summary

Introduction

In the relatively recent past, many scientific studies have demonstrated the potential of green roofs (GR) in pursuing the concept of sustainable stormwater management [1,2,3,4]. This technology induces important hydraulic benefits compared to a traditional roof, such as a decrease in runoff volume, peak discharge attenuation [5,6], and an increase in the peak delay [7,8].

Methods

Results

Conclusion