Assessing performance of porous pavements and bioretention cells for stormwater management in response to probable climatic changes.

The effectiveness of porous pavement (PP) and bio-retention cells (BCs) under the influence of potential climate change was investigated based on representative concentration pathways (RCPs). A case study of a test catchment in Guangzhou illustrated changes of peak runoff under various climate scenarios. There were distinct increases in runoff volume and peak discharge in response to RCP8.5 but only marginal increases in response to RCP2.6 (compared with present conditions). The performance of PP and BCs in terms of percentage reduction of runoff volume and peak discharge was examined for 1-, 10-, and 100-year return period and 1- and 6-h-duration storms under various climate scenarios. The effectiveness of PP and BCs varied non-linearly with the extent of PP and BCs adopted. In general, the fluctuation of hydrological performance of PP is greater than that of BCs in RCP2.6 and RCP8.5 (e.g., peak flow reductions range from -60% to 69% and from -22% to 9%, for 5% area of PP and BCs, respectively). And PP is more cost-effective for frequent storms using life cycle costing analysis. We find that PP and BCs could significantly reduce runoff volume and peak discharge in response to rainfall events with short return period, but not for heavy storms with longer return period.

[1]  H. Fowler,et al.  Future changes to the intensity and frequency of short‐duration extreme rainfall , 2014 .

[2]  S. Janhäll,et al.  An integrated method for assessing climate-related risks and adaptation alternatives in urban areas , 2015 .

[3]  R. Winston,et al.  Quantifying volume reduction and peak flow mitigation for three bioretention cells in clay soils in northeast Ohio. , 2016, The Science of the total environment.

[4]  Mo Wang,et al.  Future Scenarios Modeling of Urban Stormwater Management Response to Impacts of Climate Change and Urbanization , 2017 .

[5]  Slobodan P. Simonovic,et al.  A web-based tool for the development of Intensity Duration Frequency curves under changing climate , 2016, Environ. Model. Softw..

[6]  Emily Zechman Berglund,et al.  An integrated approach to place Green Infrastructure strategies in marginalized communities and evaluate stormwater mitigation , 2018 .

[7]  Bernard A Engel,et al.  Enhancing a rainfall-runoff model to assess the impacts of BMPs and LID practices on storm runoff. , 2015, Journal of environmental management.

[8]  Yang Yang,et al.  Optimizing surface and contributing areas of bioretention cells for stormwater runoff quality and quantity management. , 2018, Journal of environmental management.

[9]  C. Tung,et al.  Evaluating Future Joint Probability of Precipitation Extremes with a Copula-Based Assessing Approach in Climate Change , 2018, Water Resources Management.

[10]  W. Zhan,et al.  Assessing cost-effectiveness of specific LID practice designs in response to large storm events , 2016 .

[11]  Weiwei Shao,et al.  Integrated assessments of green infrastructure for flood mitigation to support robust decision-making for sponge city construction in an urbanized watershed. , 2018, The Science of the total environment.

[12]  T. Pape.  Taxonomy: Species can be named from photos , 2016, Nature.

[13]  Xiaohong Chen,et al.  Approach for evaluating inundation risks in urban drainage systems. , 2016, The Science of the total environment.

[14]  Huaizheng Li,et al.  Cost–effectiveness analysis on LID measures of a highly urbanized area , 2014 .

[15]  E. Barnes,et al.  Storm track processes and the opposing influences of climate change , 2016 .

[16]  Clint J. Keifer,et al.  Synthetic Storm Pattern for Drainage Design , 1957 .

[17]  M. Karamouz,et al.  Low-impact development practices to mitigate climate change effects on urban stormwater runoff: Case study of New York City , 2015 .

[18]  C. Hannay,et al.  Projected changes in tropical cyclone activity under future warming scenarios using a high-resolution climate model , 2018, Climatic Change.

[19]  Song‐You Hong,et al.  Assessment of future climate change over East Asia due to the RCP scenarios downscaled by GRIMs-RMP , 2014, Climate Dynamics.

[20]  Kirien Whan,et al.  Rapid attribution of the August 2016 flood-inducing extreme precipitation in south Louisiana to climate change , 2016 .

[21]  Tirupati Bolisetti,et al.  Multiobjective optimization of low impact development stormwater controls , 2018, Journal of Hydrology.

[22]  Keywan Riahi,et al.  A new scenario framework for climate change research: the concept of shared socioeconomic pathways , 2013, Climatic Change.

[23]  Chuanhao Wu,et al.  Assessing the Impact of Climate Change on the Waterlogging Risk in Coastal Cities: A Case Study of Guangzhou, South China , 2017 .

[24]  A. Palla,et al.  Hydrologic modeling of Low Impact Development systems at the urban catchment scale , 2015 .

[25]  Nien-Sheng Hsu,et al.  Optimization of low impact development layout designs for megacity flood mitigation , 2018, Journal of Hydrology.

[26]  C. Perrin,et al.  A review of efficiency criteria suitable for evaluating low-flow simulations , 2012 .

[27]  T. M. Chui,et al.  Rapid Assessment of Hydrologic Performance of Low Impact Development Practices under Design Storms , 2018 .

[28]  H. Qin,et al.  The effects of low impact development on urban flooding under different rainfall characteristics. , 2013, Journal of environmental management.

[29]  T. Fletcher,et al.  Interactions between design, plant growth and the treatment performance of stormwater biofilters , 2017 .

[30]  Patrizia Piro,et al.  Unsaturated hydraulic behaviour of a permeable pavement: Laboratory investigation and numerical analysis by using the HYDRUS-2D model , 2017 .

[31]  S. Tan,et al.  Conventional and holistic urban stormwater management in coastal cities: a case study of the practice in Hong Kong and Singapore , 2018 .

[32]  A. Langousis,et al.  Multifractal rainfall extremes: Theoretical analysis and practical estimation , 2009 .

[33]  Soon Keat Tan,et al.  Assessing hydrological effects and performance of low impact development practices based on future scenarios modeling , 2018 .

[34]  S. Tan,et al.  Application of constructed wetlands for treating agricultural runoff and agro-industrial wastewater: a review , 2017, Hydrobiologia.

[35]  Brian C. O'Neill,et al.  The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6 , 2016 .

[36]  C. Tebaldi,et al.  A comparison of U.S. precipitation extremes under RCP8.5 and RCP4.5 with an application of pattern scaling , 2018, Climatic Change.

[37]  Felipe J. Colón-González,et al.  Multimodel assessment of water scarcity under climate change , 2013, Proceedings of the National Academy of Sciences.

[38]  I. Chaubey,et al.  Effectiveness of Low Impact Development Practices: Literature Review and Suggestions for Future Research , 2012, Water, Air, & Soil Pollution.

[39]  L. Gunawardhana,et al.  A downscaling-disaggregation approach for developing IDF curves in arid regions , 2019, Environmental Monitoring and Assessment.

[40]  S. Hagemann,et al.  Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment , 2013, Proceedings of the National Academy of Sciences.

[41]  Troy R. Hawkins,et al.  Comparing Green and Grey Infrastructure Using Life Cycle Cost and Environmental Impact: A Rain Garden Case Study in Cincinnati, OH , 2015 .

[42]  P. Hamel,et al.  Source-control stormwater management for mitigating the impacts of urbanisation on baseflow: A review , 2013 .

[43]  Hoshin Vijai Gupta,et al.  Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling , 2009 .

[44]  Slobodan P. Simonovic,et al.  Equidistance Quantile Matching Method for Updating IDFCurves under Climate Change , 2014, Water Resources Management.

[45]  John Riverson,et al.  A watershed-scale design optimization model for stormwater best management practices , 2012, Environ. Model. Softw..

[46]  Soon Keat Tan,et al.  Assessing cost-effectiveness of bioretention on stormwater in response to climate change and urbanization for future scenarios , 2016 .

[47]  D. Mccarthy,et al.  Predicting long term removal of heavy metals from porous pavements for stormwater treatment. , 2018, Water research.

[48]  Hyun Il Choi,et al.  Assessment of Vulnerability to Extreme Flash Floods in Design Storms , 2011, International journal of environmental research and public health.

[49]  Junjie Cao,et al.  Assessments of joint hydrological extreme risks in a warming climate in China , 2016 .

[50]  Jiansheng Wu,et al.  Effectiveness of low-impact development for urban inundation risk mitigation under different scenarios: a case study in Shenzhen, China , 2018, Natural Hazards and Earth System Sciences.

[51]  Joeri Rogelj,et al.  Global warming under old and new scenarios using IPCC climate sensitivity range estimates , 2012 .

[52]  Hyun-Suk Shin,et al.  Developing a hydrological simulation tool to design bioretention in a watershed , 2017, Environ. Model. Softw..

[53]  Haifeng Jia,et al.  A closed urban scenic river system using stormwater treated with LID-BMP technology in a revitalized historical district in China , 2014 .

[54]  Bernard A. Engel,et al.  Optimal selection and placement of BMPs and LID practices with a rainfall-runoff model , 2016, Environ. Model. Softw..

[55]  Jun Xia,et al.  Effect of projected climate change on the hydrological regime of the Yangtze River Basin, China , 2017, Stochastic Environmental Research and Risk Assessment.

[56]  Wei Lu,et al.  A Parsimonious Framework of Evaluating WSUD Features in Urban Flood Mitigation , 2018 .

[57]  Ronghua Liu,et al.  Investigation of inducements and defenses of flash floods and urban waterlogging in Fuzhou, China, from 1950 to 2010 , 2018, Natural Hazards.

[58]  William Schroeer,et al.  Assessment of low impact development for managing stormwater with changing precipitation due to climate change , 2011 .

[59]  M. Sarrafzadeh,et al.  Effect of nitrifiers community on fouling mitigation and nitrification efficiency in a membrane bioreactor , 2018, Chemical Engineering and Processing - Process Intensification.

[60]  K. Takara,et al.  Evaluation of low impact development approach for mitigating flood inundation at a watershed scale in China. , 2017, Journal of environmental management.

[61]  Dongqing Zhang,et al.  Performance Evaluation of a Full‐Scale Constructed Wetland for Treating Stormwater Runoff , 2017 .

[62]  Jinda Qi,et al.  Effect of a Submerged Zone and Carbon Source on Nutrient and Metal Removal for Stormwater by Bioretention Cells , 2018, Water.

[63]  James Sherrard,et al.  Comparison of Maintenance Cost, Labor Demands, and System Performance for LID and Conventional Stormwater Management , 2013 .

[64]  J. Maršálek,et al.  Source-Based Modeling Of Urban Stormwater Quality Response to the Selected Scenarios Combining Future Changes in Climate and Socio-Economic Factors , 2016, Environmental Management.

[65]  J. Eom,et al.  The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview , 2017 .

[66]  H. Jia,et al.  Progress on environmental and economic evaluation of low-impact development type of best management practices through a life cycle perspective , 2019, Journal of Cleaner Production.

[67]  E. Wood,et al.  Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching , 2010 .

[68]  W. Hunt,et al.  Bioretention function under climate change scenarios in North Carolina, USA , 2014 .

[69]  T. M. Chui,et al.  Factors Influencing Stormwater Mitigation in Permeable Pavement , 2017 .

[70]  Shamsuddin Shahid,et al.  Uncertainty in Rainfall Intensity Duration Frequency Curves of Peninsular Malaysia under Changing Climate Scenarios , 2018, Water.

[71]  David M. Meko,et al.  Assessing the Risk of Persistent Drought Using Climate Model Simulations and Paleoclimate Data , 2014 .

[72]  Jin Zhang,et al.  An integrated assessment of urban flooding mitigation strategies for robust decision making , 2017, Environ. Model. Softw..

[73]  Q. Shao,et al.  Assessing the effects of adaptation measures on optimal water resources allocation under varied water availability conditions , 2018 .