Green infrastructure optimization to achieve pre-development conditions of a semiarid urban catchment

2019 ◽  
Vol 5 (6) ◽  
pp. 1157-1171 ◽  
Author(s):  
Hessam E. Tavakol-Davani ◽  
Hassan Tavakol-Davani ◽  
Steven J. Burian ◽  
Brian J. McPherson ◽  
Michael E. Barber
Keyword(s):  
Green Infrastructure ◽  
Stormwater Runoff ◽  
Environmental Benefits ◽  
Design Approach ◽  
Urban Catchment ◽  
Runoff Reduction ◽  
Infrastructure Design

The introduced hydrologically comprehensive green infrastructure design approach exceeds conventional stormwater runoff reduction goals in terms of common environmental benefits.

Implications of Urban Sustainability, Socio-Ecosystems, and Ecosystem Services

2020 ◽  
pp. 31-53
Author(s):  
José G. Vargas-Hernández ◽  
Karina M. Pallagst
Keyword(s):  
Ecosystem Services ◽  
Green Infrastructure ◽  
Natural Capital ◽  
Urban Sustainability ◽  
Well Being ◽  
Environmental Benefits ◽  
Growth Strategies ◽  
Green Growth ◽  
Infrastructure Design ◽  
Literature Reviews

This chapter aims to analyze the implications that urban sustainability, socio-ecosystems, and ecosystem services have as the bases to design the urban green growth strategies. The method used is the analytic based on the theoretical and conceptual literature reviews on the topics described. Urban sustainability and environmental performance integrates biodiversity and socio-ecosystems for the provision of better quality ecosystem services supported by green infrastructure design into the green projects aimed to achieve economic and environmental benefits. It is concluded that the ecosystem services and human well-being may suffer irreversible severe declines if sustainability is not built based on biodiversity of socio ecosystems, green infrastructure, and natural capital.

scholarly journals Multi-Objective Model-Based Assessment of Green-Grey Infrastructures for Urban Flood Mitigation

Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 110
Author(s):  
Carlos Martínez ◽  
Zoran Vojinovic ◽  
Arlex Sanchez
Keyword(s):  
Green Infrastructure ◽  
Overland Flow ◽  
Flood Damage ◽  
Optimal Number ◽  
Rainfall Runoff ◽  
Urban Catchment ◽  
Model Based ◽  
Model Domain ◽  
Infiltration Processes ◽  
2D Model

This paper presents the performance quantification of different green-grey infrastructures, including rainfall-runoff and infiltration processes, on the overland flow and its connection with a sewer system. The present study suggests three main components to form the structure of the proposed model-based assessment. The first two components provide the optimal number of green infrastructure (GI) practices allocated in an urban catchment and optimal grey infrastructures, such as pipe and storage tank sizing. The third component evaluates selected combined green-grey infrastructures based on rainfall-runoff and infiltration computation in a 2D model domain. This framework was applied in an urban catchment in Dhaka City (Bangladesh) where different green-grey infrastructures were evaluated in relation to flood damage and investment costs. These practices implemented separately have an impact on the reduction of damage and investment costs. However, their combination has been shown to be the best action to follow. Finally, it was proved that including rainfall-runoff and infiltration processes, along with the representation of GI within a 2D model domain, enhances the analysis of the optimal combination of infrastructures, which in turn allows the drainage system to be assessed holistically.

scholarly journals The projected impacts of smart decline on urban runoff contamination levels

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Rui Zhu ◽  
Galen Newman
Keyword(s):  
Land Use ◽  
Green Infrastructure ◽  
Prediction Models ◽  
Stormwater Runoff ◽  
Baseline Scenario ◽  
Vacant Land ◽  
Smart Decline ◽  
Contamination Levels ◽  
Indirect Impacts

AbstractThere has been mounting interest about how the repurposing of vacant land (VL) through green infrastructure (the most common smart decline strategy) can reduce stormwater runoff and improve runoff quality, especially in legacy cities characterized by excessive industrial land uses and VL amounts. This research examines the long-term impacts of smart decline on both stormwater amounts and pollutants loads through integrating land use prediction models with green infrastructure performance models. Using the City of St. Louis, Missouri, USA as the study area, we simulate 2025 land use change using the Conversion of Land Use and its Effects (CLUE-S) and Markov Chain urban land use prediction models and assess these change’s probable impacts on urban contamination levels under different smart decline scenarios using the Long-Term Hydrologic Impact Assessment (L-THIA) performance model. The four different scenarios are: (1) a baseline scenario, (2) a 10% vacant land re-greening (VLRG) scenario, (3) a 20% VLRG scenario, and (4) a 30% VLRG scenario. The results of this study illustrate that smart decline VLRG strategies can have both direct and indirect impacts on urban stormwater runoff and their inherent contamination levels. Direct impacts on urban contamination include the reduction of stormwater runoff and non-point source (NPS) pollutants. In the 30% VLRG scenario, the annual runoff volume decreases by 11%, both physical, chemical, and bacterial pollutants are reduced by an average of 19%, compared to the baseline scenario. Indirect impacts include reduction of the possibility of illegal dumping on VL through mitigation and prevention of future vacancies.

Urban Hazard Adaptation: Efficiency of a Green Infrastructure in an Italian metropolis

2021 ◽  
Author(s):  
Francesco Busca ◽  
Roberto Revelli
Keyword(s):  
Climate Change ◽  
Green Infrastructure ◽  
Local Governments ◽  
Sustainable Use ◽  
Point Of View ◽  
Environmental Benefits ◽  
Atmospheric Pollutants ◽  
Water Runoff ◽  
Water Shortages ◽  
Economic Point

<p>In recent years, safeguarding approaches and environmental management initiatives have been adopted both by international institutions and local governments , aimed at sustainable use of natural resources and their restoration, in order to manage hazard level of climate change consequences (urban flooding, droughts and water shortages, sea level rise, issues with food security).</p><p>Cities represent the main collectors of these effects, consequently they need to implement specific adaptation plans mitigating consequences of such future events: Green Infrastructures (G.I.) fall within the most effective tools for achieving the goal. In the urban context, they also identify themselves as valid strategies for biodiversity recovery and ecological functions.</p><p>This work analyzes the role of a G.I. in an urban environment, with the aim of quantifying Ecosystem Services (E.S.) provided by vegetation: through usage of <em>i-Tree</em>, specific software suite for E.S. quantification, the sustainability offered by “Le Vallere” park, a 34-hectares greenspace spread between municipalities of Turin and Moncalieri (Italy), was analyzed, in collaboration with the related management institution (<em>Ente di gestione delle Aree Protette del Po torinese</em>). The study, carried out using two specific tools (<em>i-Tree Eco and i-Tree Hydro</em>), focuses on different aspects: carbon sequestration and storage, atmospheric pollutants reduction, avoided water runoff and water quality improvement are just some of the environmental benefits generated by tree population. Tools enable to carry out the analysis also from an economic point of view, evaluating monetary benefits brought by the green infrastructure both at present day and in the future,  taking into account climate change effects through projections based on the regional climatic model COSMO-CLM (RCP 4.5 and RCP 8.5 scenarios).</p><p>The work led to deepen potential held by the greenspace, helping the cooperating management institution  to plan future territorial agenda and to find innovative approaches for an integrated and sustainable hazard control.</p>

Anthosart Green Tool: Selecting Species for Green Infrastructure Design

2021 ◽  
pp. 151-163
Author(s):  
Patrizia Menegoni ◽  
Riccardo Guarino ◽  
Sandro Pignatti ◽  
Claudia Trotta ◽  
Francesca Lecce ◽  
...  
Keyword(s):  
Green Infrastructure ◽  
Infrastructure Design

scholarly journals Socio-Economic Assessment of Green Infrastructure for Climate Change Adaptation in the Context of Urban Drainage Planning

2020 ◽  
Vol 12 (9) ◽  
pp. 3792 ◽  
Author(s):  
Luca Locatelli ◽  
Maria Guerrero ◽  
Beniamino Russo ◽  
Eduardo Martínez-Gomariz ◽  
David Sunyer ◽  
...  
Keyword(s):  
Decision Making ◽  
Green Infrastructure ◽  
Waste Water Treatment ◽  
Economic Assessment ◽  
Environmental Benefits ◽  
Urban Drainage ◽  
Combined Sewer Overflows ◽  
Damage Reduction ◽  
Combined Sewer ◽  
Sewer Overflows

Green infrastructure (GI) contributes to improve urban drainage and also has other societal and environmental benefits that grey infrastructure usually does not have. Economic assessment for urban drainage planning and decision making often focuses on flood criteria. This study presents an economic assessment of GI based on a conventional cost-benefit analysis (CBA) that includes several benefits related to urban drainage (floods, combined sewer overflows and waste water treatment), environmental impacts (receiving water bodies) and additional societal and environmental benefits associated with GI (air quality improvements, aesthetic values, etc.). Benefits from flood damage reduction are monetized based on the widely used concept of Expected Annual Damage (EAD) that was calculated using a 1D/2D urban drainage model together with design storms and a damage model based on tailored flood depth–damage curves. Benefits from Combined Sewer Overflows (CSO) damage reduction were monetized using a 1D urban drainage model with continuous rainfall simulations and prices per cubic meter of spilled combined sewage water estimated from literature; other societal benefits were estimated using unit prices also estimated from literature. This economic assessment was applied to two different case studies: the Spanish cities of Barcelona and Badalona. The results are useful for decision making and also underline the relevancy of including not only flood damages in CBA of GI.

scholarly journals Configuring Green Infrastructure for Urban Runoff and Pollutant Reduction Using an Optimal Number of Units

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1528 ◽  
Author(s):  
Carlos Martínez ◽  
Arlex Sanchez ◽  
Roberto Galindo ◽  
Aelaf Mulugeta ◽  
Zoran Vojinovic ◽  
...  
Keyword(s):  
Green Infrastructure ◽  
Urban Runoff ◽  
Optimal Number ◽  
Volume Reduction ◽  
Pollution Load ◽  
Flood Volume ◽  
Runoff Reduction ◽  
Trade Offs ◽  
Load Peak ◽  
Peak Runoff

Green infrastructure (GI) has been regarded as an effective intervention for urban runoff reduction. Despite the growing interest in GI, the technical knowledge that is needed to demonstrate their advantages, cost, and performance in reducing runoff and pollutants is still under research. The present paper describes a framework that aims to obtain the optimal configuration of GI (i.e., the optimal number of units distributed within the catchment) for urban runoff reduction. The research includes an assessment of the performance of GI measures dealing with pollution load, peak runoff, and flood volume reduction. The methodological framework developed includes: (1) data input, (2) GI selection and placement, (3) hydraulic and water quality modelling, and (4) assessing optimal GI measures. The framework was applied in a highly urbanized catchment in Cali, Colombia. The results suggest that if the type of GI measure and its number of units are taken into account within the optimisation process, it is possible to achieve optimal solutions to reduce the proposed reduction objectives with a lower investment cost. In addition, the results also indicate a pollution load, peak runoff, and flood volume reduction for different return periods of at least 33%, 28%, and 60%, respectively. This approach could assist water managers and their stakeholders to assess the trade-offs between different GI.

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