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Optimizing Green Infrastructure Design and Placement for Integrated Urban Watershed Management

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Urban Water Management".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 6579

Special Issue Editors

Department of Civil Engineering, University of Minnesota Duluth, Duluth, MN, USA
Interests: urban hydrology and hydraulics; stormwater management; data-model integration

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Guest Editor
Department of Civil Engineering, The University of Hong Kong, Hong Kong, China
Interests: stormwater management; machine learning; hydrological modeling

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Guest Editor
Department of Civil Engineering, University of Minnesota Duluth, Duluth, MN, USA
Interests: solute transport; soil and water conservation; stormwater management

Special Issue Information

Dear Colleagues,

Green infrastructure (GI) has gained traction as a preferred stormwater management practice for its ability to mimic natural hydrologic conditions and remove stormwater pollutants. However, as a decentralized infrastructure, the performance of GI is highly variable and dependent on the local context. At the same time, trends in land development and climate variability can mask the system-wide benefit of GI and increase the difficulty of detecting and evaluating the integrated, watershed-scale hydrologic impact of GI. The emergence of data-driven analytics, advanced hydrologic models, and optimization techniques provides advanced tools to address this challenge. The objective of this Special Issue is to synthesize recent advances in data, instrumentation, modelling, and analysis focused on optimizing the integrated, system-wide benefit of GI at watershed scales. Interdisciplinary research is particularly welcomed.

Dr. Kun Zhang
Dr. Yang Yang
Dr. Gustavo H. Merten
Guest Editors

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Keywords

  • urban watershed: green infrastructure
  • nature-based solutions
  • stormwater management
  • stormwater runoff
  • hydrologic modelling
  • machine learning
  • optimization
  • low impact development
  • sustainable drainage systems

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Published Papers (4 papers)

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Research

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14 pages, 3741 KiB  
Article
A Modified Manning’s Equation for Estimating Flow Rate in Grass Swales under Low Inflow Rate Conditions
by Jianlong Wang, Rongting Qiu, Xu Xia, Xiaoning Li, Changhe Zhang and Wenhai Wang
Water 2024, 16(11), 1613; https://doi.org/10.3390/w16111613 - 5 Jun 2024
Viewed by 781
Abstract
As green infrastructure has evolved, grass swales have become integral components of stormwater management. Manning’s equation is commonly used to describe the hydraulic characteristics of grass swales. However, due to flow loss from infiltration, grass swales often deviate from the assumptions of Manning’s [...] Read more.
As green infrastructure has evolved, grass swales have become integral components of stormwater management. Manning’s equation is commonly used to describe the hydraulic characteristics of grass swales. However, due to flow loss from infiltration, grass swales often deviate from the assumptions of Manning’s equation, potentially leading to significant errors in grass swale flow rate calculations. In this study, we systematically investigated changes in flow rates in grass swales under various constant inflow rate conditions. The results indicated that the suitability of using Manning’s equation to estimate flow rate in grass swales varies with inflow rate. At an inflow rate of 3.00 m3/h, the discrepancy between the measured and the estimated flow rates by Manning’s equation was the smallest, ranging from −0.24 to 0.19 m3/h. At lower inflow rates (1.00 to 2.00 m3/h), Manning’s equation underestimated the flow rates by 0.16 to 0.47 m3/h; at higher rates (4.00 m3/h), it overestimated the flow rates by 0.01 to 0.61 m3/h. Considering infiltration losses as the primary cause of these errors, we proposed an improved Darcy’s formula for estimating the infiltration rates in grass swales, along with a modified Manning’s equation for more accurate flow rate calculations. The modified Manning’s equation provides enhanced accuracy in calculating flow rates in grass swales compared to the traditional version. Full article
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13 pages, 3106 KiB  
Article
Catchment-Scale Hydrologic Effectiveness of Residential Rain Gardens: A Case Study in Columbia, Maryland, USA
by Benjamin J. Daniels and Jon Alan Yeakley
Water 2024, 16(9), 1304; https://doi.org/10.3390/w16091304 - 3 May 2024
Cited by 1 | Viewed by 1486
Abstract
To mitigate the adverse impacts of urban stormwater on streams, watershed managers are increasingly using low-impact development and green infrastructure (LID-GI) stormwater control measures, such as rain gardens—vegetated depressional areas that collect and infiltrate runoff from rooftops and driveways. Their catchment-scale performance, however, [...] Read more.
To mitigate the adverse impacts of urban stormwater on streams, watershed managers are increasingly using low-impact development and green infrastructure (LID-GI) stormwater control measures, such as rain gardens—vegetated depressional areas that collect and infiltrate runoff from rooftops and driveways. Their catchment-scale performance, however, can vary widely, and few studies have investigated the cumulative performance of residential rain gardens for event runoff control in intermediate-sized (i.e., 1–10 km2) suburban catchments. We modeled three years of continuous rainfall-runoff from a 3.1 km2 catchment in Columbia, MD, USA, using the Storm Water Management Model (SWMM). Various extents of rain garden implementation at residential houses were simulated (i.e., 25%, 50%, 75%, and 100% coverage) to determine the effects on peak flow, runoff volume, and lag time. On average, treating 100% of residential rooftops in the catchment reduced peak flows by 14.3%, reduced runoff volumes by 11.4%, and increased lag times by 3.2% for the 223 rainfall events during the simulation period. Peak flow reductions were greater for smaller storm events (p < 0.01). Our results show that residential rain gardens can significantly improve the runoff response of suburban catchments, and that they represent an effective and relatively low-cost option for urban watershed management and restoration. Full article
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31 pages, 3715 KiB  
Article
Assessing the Lifecycle Environmental Resilience of Urban Green Infrastructures Coping with Acute Disturbances and Chronic Stresses
by Fei Xue, Bo Luan, Yue Fan, Shiqi Xie, Xiaomin Yang, Jianing Luo and Ruxuan Zheng
Water 2024, 16(8), 1162; https://doi.org/10.3390/w16081162 - 19 Apr 2024
Viewed by 1392
Abstract
Urban green infrastructure (UGI), a key component of nature-based solutions (NbSs), plays a vital role in enhancing urban resilience. Nonetheless, the absence of a thorough resilience evaluation for UGI has hindered the efficacy of its design and implementation. This article proposes an innovative [...] Read more.
Urban green infrastructure (UGI), a key component of nature-based solutions (NbSs), plays a vital role in enhancing urban resilience. Nonetheless, the absence of a thorough resilience evaluation for UGI has hindered the efficacy of its design and implementation. This article proposes an innovative urban environmental resilience index (ERI) framework designed to evaluate the lifecycle performance of UGI. First, a coupled environmental resilience evaluation system is proposed that encompasses indicators for the adaptation to acute disturbances and the mitigation of chronic pressures. Second, the inventive formulas for calculating the environmental resilience index are presented, which establish the weighting of indicators through Delphi-analytic hierarchy process (AHP) analysis, and the Storm Water Management Model (SWMM), GaBi, and i-Tree models are employed for the quantitative assessment. Third, four representative UGI scenarios in urban built-up areas have been selected for comparative analysis and in-depth discussion by calculating the resilience index. This research presents UGI solutions as adaptive measures for “Black Swan” events and “Gray Rhino” phenomena, offering significant case studies and methodological frameworks which will inform future endeavours in green and sustainable urban development. Full article
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Review

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18 pages, 4639 KiB  
Review
Global Paradigm Shifts in Urban Stormwater Management Optimization: A Bibliometric Analysis
by Mo Wang, Zhiyu Jiang, Rana Muhammad Adnan Ikram, Chuanhao Sun, Menghan Zhang and Jianjun Li
Water 2023, 15(23), 4122; https://doi.org/10.3390/w15234122 - 28 Nov 2023
Cited by 1 | Viewed by 2278
Abstract
Amidst the growing urgency to mitigate the impacts of anthropogenic climate change, urban flooding stands out as a critical concern, necessitating effective stormwater management strategies. This research presents a bibliometric analysis of the literature on urban stormwater management optimization from 2004 to 2023, [...] Read more.
Amidst the growing urgency to mitigate the impacts of anthropogenic climate change, urban flooding stands out as a critical concern, necessitating effective stormwater management strategies. This research presents a bibliometric analysis of the literature on urban stormwater management optimization from 2004 to 2023, with the aim of understanding how the field has responded to these escalating challenges. Aiming to map the evolution and current state of the field, this study employed a methodical approach, using CiteSpace to analyze publication trends, authorship patterns, and geographical distributions, as well as keyword and citation dynamics. The findings reveal a marked increase in research activity after 2014, with significant contributions observed between 2019 and 2022. Key research themes identified include low-impact development, green infrastructure, and stormwater management, with a notable shift towards hybrid grey–green infrastructure solutions that combine traditional and ecological elements. The prevalence of terms such as ‘best management practices’ and ‘Green Roofs’ in recent publications indicates a growing emphasis on practical, case-study-based research, particularly in green infrastructure technologies like bioretention cells. These insights underscore the field’s movement towards pragmatic, multi-objective optimization frameworks with tangible applications, guiding future research directions in this increasingly complex domain. Full article
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