A green roof experimental site in the Mediterranean climate: the storm water quality issue

2013 ◽  
Vol 68 (6) ◽  
pp. 1419-1424 ◽  
Author(s):  
Ilaria Gnecco ◽  
Anna Palla ◽  
Luca G. Lanza ◽  
Paolo La Barbera
Keyword(s):  
Atmospheric Deposition ◽  
Water Chemistry ◽  
Mediterranean Climate ◽  
Green Roof ◽  
Green Roofs ◽  
Storm Water ◽  
Water Runoff ◽  
Experimental Site ◽  
Storm Water Runoff ◽  
Runoff Quality

Since 2007, the University of Genoa has been carrying out a monitoring programme to investigate the hydrologic response of green roofs in the Mediterranean climate by installing a green roof experimental site. In order to assess the influence of green roofs on the storm water runoff quality, water chemistry data have been included in the monitoring programme since 2010, providing rainfall and outflow data. For atmospheric source, the bulk deposition is collected to evaluate the role of the overall atmospheric deposition in storm water runoff quality. For subsurface outflow, a maximum of 24 composite samples are taken on an event basis, thus aiming at a full characterization of the outflow hydrograph. Water chemistry data reveal that the pollutant loads associated with green roof outflow is low; in particular, solids and metal concentrations are lower than values generally observed in storm water runoff from traditional rooftops. The concentration values of chemical oxygen demand, total dissolved solids, Fe, Ca and K measured in the subsurface outflow are significantly higher than those observed in the bulk deposition (p < 0.05). With respect to the atmospheric deposition, the green roof behaviour as a sink/source of pollutants is investigated based on both concentration and mass.

scholarly journals Evaluating different machine learning methods to simulate runoff from extensive green roofs

2021 ◽  
Vol 25 (11) ◽  
pp. 5917-5935
Author(s):  
Elhadi Mohsen Hassan Abdalla ◽  
Vincent Pons ◽  
Virginia Stovin ◽  
Simon De-Ville ◽  
Elizabeth Fassman-Beck ◽  
...  
Keyword(s):  
Machine Learning ◽  
Green Roof ◽  
Green Roofs ◽  
Storm Water ◽  
Water Runoff ◽  
Learning Methods ◽  
Retention Model ◽  
Machine Learning Methods ◽  
Storm Water Runoff ◽  
Extensive Green Roofs

Abstract. Green roofs are increasingly popular measures to permanently reduce or delay storm-water runoff. The main objective of the study was to examine the potential of using machine learning (ML) to simulate runoff from green roofs to estimate their hydrological performance. Four machine learning methods, artificial neural network (ANN), M5 model tree, long short-term memory (LSTM) and k nearest neighbour (kNN), were applied to simulate storm-water runoff from 16 extensive green roofs located in four Norwegian cities across different climatic zones. The potential of these ML methods for estimating green roof retention was assessed by comparing their simulations with a proven conceptual retention model. Furthermore, the transferability of ML models between the different green roofs in the study was tested to investigate the potential of using ML models as a tool for planning and design purposes. The ML models yielded low volumetric errors that were comparable with the conceptual retention models, which indicates good performance in estimating annual retention. The ML models yielded satisfactory modelling results (NSE >0.5) in most of the roofs, which indicates an ability to estimate green roof detention. The variations in ML models' performance between the cities was larger than between the different configurations, which was attributed to the different climatic characteristics between the four cities. Transferred ML models between cities with similar rainfall events characteristics (Bergen–Sandnes, Trondheim–Oslo) could yield satisfactory modelling performance (Nash–Sutcliffe efficiency NSE >0.5 and percentage bias |PBIAS| <25 %) in most cases. However, we recommend the use of the conceptual retention model over the transferred ML models, to estimate the retention of new green roofs, as it gives more accurate volume estimates. Follow-up studies are needed to explore the potential of ML models in estimating detention from higher temporal resolution datasets.

scholarly journals AN ANALYSIS ON THE EFFICIENCY OF GREEN ROOF IN MANAGING URBAN STORMWATER RUNOFF

2021 ◽  
Vol 19 (17) ◽  
Author(s):  
Shazmin Shareena Ab. Azis ◽  
Muhammad Najib Mohamed Razali ◽  
Nurul Hana Adi Maimun ◽  
Nurul Syakima Mohd Yusoff ◽  
Mohd Shahril Abdul Rahman ◽  
...  
Keyword(s):  
Flash Flood ◽  
Meta Analysis ◽  
Green Roof ◽  
Drainage System ◽  
Green Roofs ◽  
Storm Water ◽  
Water Runoff ◽  
Extensive Green Roof ◽  
Storm Water Runoff ◽  
Urban Storm

Modernization has created new impervious urban landscape contributed to major catastrophe. Urban drainage system incapable to convey the excess rainwater resulting in flash flood due to heavy rainfall. The combination of green roof on building have tremendously proved to control stormwater efficiently. This study is conducted to review the efficiency of intensive and extensive green roof in reducing urban storm water runoff. This study identifies characteristic of green roof that contributes to lessening urban storm water runoff. Data was collected based on rigorous literature reviews and analyzed using meta-analysis. Overall, findings revealed intensive green roof performed better in reducing storm water runoff compared to extensive green roof. Green roof performance increases as the depth of substrate increased. Origanum and Sedum plants are both highly effective for intensive and extensive green roofs. The performance of green roof reduces as degree of roof slope increased.

scholarly journals Growing substrates for aromatic plant species in green roofs and water runoff quality: pilot experiments in a Mediterranean climate

2017 ◽  
Vol 76 (5) ◽  
pp. 1081-1089 ◽  
Author(s):  
Cristina M. Monteiro ◽  
Cristina S. C. Calheiros ◽  
Paulo Palha ◽  
Paula M. L. Castro
Keyword(s):  
Organic Matter ◽  
Plant Species ◽  
Urban Areas ◽  
Mediterranean Climate ◽  
Green Roof ◽  
Oxygen Demand ◽  
Green Roofs ◽  
Water Runoff ◽  
Aromatic Plant ◽  
Runoff Quality

Green roof technology has evolved in recent years as a potential solution to promote vegetation in urban areas. Green roof studies for Mediterranean climates, where extended drought periods in summer contrast with cold and rainy periods in winter, are still scarce. The present research study assesses the use of substrates with different compositions for the growth of six aromatic plant species – Lavandula dentata, Pelargonium odoratissimum, Helichrysum italicum, Satureja montana, Thymus caespititius and T. pseudolanuginosus, during a 2-year period, and the monitoring of water runoff quality. Growing substrates encompassed expanded clay and granulated cork, in combination with organic matter and crushed eggshell. These combinations were adequate for the establishment of all aromatic plants, allowing their propagation in the extensive system located on the 5th storey. The substrate composed of 70% expanded clay and 30% organic matter was the most suitable, and crushed eggshell incorporation improved the initial plant establishment. Water runoff quality parameters – turbidity, pH, conductivity, NH4+, NO3−, PO43- and chemical oxygen demand – showed that it could be reused for non-potable uses in buildings. The present study shows that selected aromatic plant species could be successfully used in green roofs in a Mediterranean climate.

Storm Water Runoff Mitigation Using a Green Roof

2009 ◽  
Vol 26 (2) ◽  
pp. 407-418 ◽  
Author(s):  
Daniel J. Bliss ◽  
Ronald D. Neufeld ◽  
Robert J. Ries
Keyword(s):  
Green Roof ◽  
Storm Water ◽  
Water Runoff ◽  
Storm Water Runoff

Green Roof Storm-Water Runoff Quantity and Quality

2013 ◽  
Vol 139 (4) ◽  
pp. 471-478 ◽  
Author(s):  
Susan Morgan ◽  
Serdar Celik ◽  
William Retzlaff
Keyword(s):  
Green Roof ◽  
Storm Water ◽  
Water Runoff ◽  
Storm Water Runoff

Effects of urbanization on storm water runoff quality: A limited experiment, Naismith Ditch, Lawrence, Kansas

1972 ◽  
Vol 8 (1) ◽  
pp. 135-140 ◽  
Author(s):  
Ernest E. Angino ◽  
Larry M. Magnuson ◽  
Gary F. Stewart
Keyword(s):  
Storm Water ◽  
Water Runoff ◽  
Storm Water Runoff ◽  
Runoff Quality

scholarly journals Developing an evaluation tool for green roof typologies

2021 ◽  
Author(s):  
Cameron Laidlaw
Keyword(s):  
Urban Environment ◽  
Green Roof ◽  
Green Roofs ◽  
Water Runoff ◽  
Evaluation Tool ◽  
Quality Maintenance ◽  
The Future ◽  
Criteria For Evaluation ◽  
Specific Project ◽  
Runoff Quality

Green roofs possess the potential to provide a plethora of benefits in the urban environment. The variability among the green roof typologies (intensive, extensive, and agriculture) leads to different benefits when one system is selected over another. By the collection and analyzing of metadata, an evaluation tool is developed to assist green roof designers to meet the goals of their specific project. Included criteria for evaluation are: water runoff quantity, water runoff quality, maintenance, amenity, and irrigation. The evaluation tool is designed to be compartmentalized, with each criteria treated independently, allowing further expansion, alteration, or refinement of the tool in the future.

scholarly journals Developing an evaluation tool for green roof typologies

2021 ◽  
Author(s):  
Cameron Laidlaw
Keyword(s):  
Urban Environment ◽  
Green Roof ◽  
Green Roofs ◽  
Water Runoff ◽  
Evaluation Tool ◽  
Quality Maintenance ◽  
The Future ◽  
Criteria For Evaluation ◽  
Specific Project ◽  
Runoff Quality

Green roofs possess the potential to provide a plethora of benefits in the urban environment. The variability among the green roof typologies (intensive, extensive, and agriculture) leads to different benefits when one system is selected over another. By the collection and analyzing of metadata, an evaluation tool is developed to assist green roof designers to meet the goals of their specific project. Included criteria for evaluation are: water runoff quantity, water runoff quality, maintenance, amenity, and irrigation. The evaluation tool is designed to be compartmentalized, with each criteria treated independently, allowing further expansion, alteration, or refinement of the tool in the future.

scholarly journals Effects of biochar usage and plant species selections on the storm water runoff mitigations by green roofs

2018 ◽  
Vol 44 (1) ◽  
pp. 69-74 ◽  
Author(s):  
MUGITA Junki ◽  
TSUCHIYA Kazuaki ◽  
MATSUOKA Tatsuya ◽  
YAMADA Susumu ◽  
OKURO Toshiya
Keyword(s):  
Plant Species ◽  
Green Roofs ◽  
Storm Water ◽  
Water Runoff ◽  
Storm Water Runoff
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