Tài liệu International low impact development conference china 2016 lid applications in sponge city projects

Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. International Low Impact Development Conference China 2016 Applications in Sponge City Construction Proceedings of the International Low Impact Development Conference China 2016 EDITED BY Haifeng Jia, Ph.D., P.E., D.WRE; Shaw L. Yu, Ph.D.; Robert Traver, Ph.D., P.E., D.WRE; Huapeng Qin, Ph.D.; Junqi Li, Ph.D.; and Mike Clar, P.E., D.WRE Beijing, China June 26–29, 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. INTERNATIONAL LOW IMPACT DEVELOPMENT CONFERENCE CHINA 2016 LID APPLICATIONS IN SPONGE CITY PROJECTS PROCEEDINGS OF THE INTERNATIONAL LOW IMPACT DEVELOPMENT CONFERENCE CHINA 2016 June 26–29, 2016 Beijing, China SPONSORED BY Chinese Civil Engineering Society Chinese Water Industry Society Chinese Academy of Engineering—Division of Civil, Hydraulic, and Architecture Engineering Environmental and Water Resources Institute of ASCE EDITED BY Haifeng Jia, Ph.D., P.E., D.WRE Shaw L. Yu, Ph.D. Robert Traver, Ph.D., P.E., D.WRE Huapeng Qin, Ph.D. Junqi Li, Ph.D. Mike Clar, P.E., D.WRE Published by the American Society of Civil Engineers Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. 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Front cover: The editors would like to thank the Beijing Tsinghua Tongheng Urban Planning & Design Institute for its permission for using the cover photo. International Low Impact Development Conference China 2016 Preface Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. The 2016 International Low Impact Development (LID) Conference was successfully held at the China National Conference Center in Beijing, China during June 26-29, 2016. The conference brought together experts and scholars from more than 23 countries and regions to Beijing, China. A total of nearly 800 papers were submitted, of which 576, through rounds of peer reviews, were selected and presented at the conference. There were 6 topical tracks, 4 special sessions and 4 keynote presentations. The major theme of the conference was theory and practice of LID and green infrastructure (GI) application, which provided timely and valuable information for the implementation of the “Sponge City” projects, a major urban water management initiative, in China. The conference papers were reviewed by members of the program committee and selected authors were invited to submit their papers for possible publication in the ASCE Proceedings. Manuscripts submitted were reviewed by proceeding editors listed below: Haifeng Jia, Tsinghua University Shaw L. Yu, University of Virginia Robert Traver, Villanova University Huapeng Qin, Peking University Shenzhen Graduate School Junqi Li, Beijing University of Civil Engineering and Architecture Mike Clar, Ecosite Inc. The papers approved for inclusion in the Proceedings are grouped into the following major tracks:  LID and Urban Planning & Design  LID/GI Research & Development  Urban Water Infrastructure System Design & Optimization  LID/GI Practices – Case Studies and Recent Advances Acknowledgements We acknowledge the sponsorship and financial support provided for the conference. Efforts by all the authors, editors and assistance by EWRI and the ASCE Publications are greatly appreciated. © ASCE iii International Low Impact Development Conference China 2016 Contents Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Urban Hydrology and Water Systems Temporal and Spatial Variations of Extreme Precipitation and Flood Thresholds in Qinghe Basin in Beijing, China ............................................................................1 Li Lu, Xuebiao Pan, Lizhen Zhang, and Xingyao Pan The Effects of Low Impact Development Practices on Urban Stormwater Management .................................................................................................................................12 Na Li, Qian Yu, Jing Wang, and Xiaohe Du The Impact of Focused Recharge with LID Devices on Groundwater Dynamics and Water Quality under Natural Rainfall Conditions .........................................21 Zhonghua Jia, Qing Xu, Wan Luo, and Shuangcheng Tang Assessment of Stormwater Management and Storage Capacity for Urban Green Space in Shanghai City ........................................................................................27 Bingqin Yu, Shengquan Che, and Jiankang Guo Index System of Urban Rainwater Collection and Utilization in Beijing City under Low Impact Development...........................................................................37 Anping Shu, Xing Zhou, Donglian Kong, Lu Tian, and Li Huang Verification of the Effectiveness of BMP Techniques in a Long Time Period Using Trend Analysis ......................................................................................................45 Zijing Liu and Yuntao Guan Application of LID Attribute Index Evaluation Method in the Design of Urban Stormwater Control ....................................................................................................57 Jiangyun Li, Wang Sheng, Qing Chang, and Yi Zhou Comparative Analysis of Different Evapotranspiration Estimation Methods Used in a Raingarden in Auckland, New Zealand ....................................................66 Tingting Hao, Asaad Shamseldin, Keith Adams, and Bruce Melville Concurrent Potential for Flooding Risk Reduction of Decentralized Rainwater Management System .................................................................................................76 Donggeun Kwak, Minju Lee, Soyoung Baek, and Mooyoung Han Urban Runoff Simulation and Analysis Modeling of Streamflow in an Underdrain System of Vegetated Dry Swales ....................................................................................................................................85 Sidian Chen, Huapeng Qin, and Shuxiao Li © ASCE iv International Low Impact Development Conference China 2016 Stochastic Long Time Series Rainfall Generation Method ......................................................92 Yi Zhou, Yu Shang, Jiangyun Li, and Qiufeng Tang Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Effects of Low Impact Development Practices on the Mitigation of Nutrient Pollution in Deep Bay, China ....................................................................................100 Sidian Chen, Mingfeng Zheng, Huapeng Qin, and Xueran Li Modeling of Bioretention Systems’ Hydrologic Performance: A Case Study in Beijing .................................................................................................................108 Meishui Li, Xiaohua Yang, Lei Chen, and Zhenyao Shen Estimating Water Quality Capture Volume for LID Designs Using a Mechanical Wash-Off Model ......................................................................................118 Qi Zhang, Fang Yang, and Zhijie Zhao Distribution Analysis for Non-Point Source Pollution Control Programs Using Multivariate Statistical Analysis Methods ..................................................126 Zijing Liu and Yuntao Guan Study on Spatial Characteristics and Load of Urban Non-Point Source Pollution Based on Geostatistical Model .....................................................................137 Sheng Xie, Kai Yang, Yong Peng Lyu, Chen Zhang, Yue Che, and Lei Ding Rainfall-Storage-Pump-Discharge (RSPD) Model for Sustainable and Resilient Flood Mitigation .................................................................................................152 Duc Canh Nguyen and Moo Young Han Runoff Characteristics on LID Combination Type in the New Development Site Using XPSWMM .........................................................................................162 Donggeun Kwak, Hyunwoo Kim, and Mooyoung Han Runoff LID Control Technology Isolation and Characterization of a PYR-Degrading Bacterial Consortium for Bioaugmentation in Bioretention Systems ...................................................172 Dongqi Wang, Zhangjie Yang, Jiaqi Shan, Enyu Liu, Guodong Chai, Chan Li, Xiaohua Lin, Wen Dong, Huaien Li, and Jiake Li Evaluation of the Effects of Low Impact Development on Base Flow in an Urbanized Watershed Using HSPF .......................................................................179 Qi Zhang, Zhijie Zhao, and Huapeng Qin Groundwater Replenishment Analysis of Rainfall Collected via an Ecological Detention Facility ...............................................................................................186 Fengqing Guo, Yuntao Guan, and Tanaka Hiroaki © ASCE v International Low Impact Development Conference China 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Reinvent of a New Public Toilet Wastewater Treatment System Using Forward Osmosis as the Key Unit: A Resources Close-Loop Model in Urban LID ..................................................................................................................194 Yangyu Xu, Lu Zhou, and Qibo Jia LID-Based Ecological Planting Groove for Road Runoff Purification Research ......................................................................................................................................204 Xuexin Liu, Xueping Chen, Shaoyong Lu, Xinzhu Xiong, Shuohan Gao, and Yaping Kong Green Building and Green Roofs How to Construct Green Roofs on the Tops of Existing Buildings: A Case Study in Shanghai .........................................................................................................214 Tianqing Luo, Yining Su, and Libin Chen Behavior of Soil Moisture in a Retentive Green Roof System ...............................................223 Saerom Yoon, Juyoung Lee, and Mooyoung Han Impact Study of Thermal Environment on Integration of Extensive Green Roof Techniques in Northwestern Arid Regions of China .........................................231 Yajun Wang, Rajendra Prasad Singh, Dafang Fu, and Junyu Zhang Sponge Cities and Landscapes Traditional Pattern of Mountain-Water-City and Its Contemporary Enlightenment: Changshou District of Chongqing as a Case................................................241 Lu Guo Landscape-Scale Simulation Analysis of Waterlogging and Sponge City Planning for a Central Urban Area in Fuzhou City, China ..........................................251 Shaoqing Dai, Jiajia Li, Shudi Zuo, Yin Ren, and Huixian Jiang Adaptation to Water: A Study on Bamboo Landscape System with Low Impact Development .........................................................................................................261 Renwu Wu, Jun Zheng, Yan Shi, Fan Yang, and Zhiyi Bao A Balance of Landscape Architectural Planning and Design among Antiterrorism Concern with Nature, Cultural, or Socio-Economic Ecosystem Services.....................................................................................................................267 Kaitai Lin Case Studies Optimization Study of Urban Stormwater Runoff Control BMPs Scheme Based on SUSTAIN ......................................................................................................278 Yifan Zeng, Xiaodong Long, Zimu Jia, Weihua Zeng, and Jianbin Shi © ASCE vi International Low Impact Development Conference China 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Comparison of Stormwater Management in the Community Park between China and Singapore: A Case Study of Hillside Eco Park and Crescent and Pioneer Hall .................................................................................................289 Mo Wang, Dong Qing Zhang, Ya Wang, Jin Su, Jian Wen Dong, and Soon Keat Tan Effects of Land Use and Rainfall Characteristics on River Pollutions: A Case Study of Xili Reservoir Watershed in Shenzhen, China ...........................................304 Lixun Zhang, Bo Zhao, and Yuntao Guan Low Impact Stormwater Management Development at Rutgers University ....................................................................................................................................318 Seth Richter, Christian Roche, and Qizhong Guo Sponge City Construction and Management Strategies Low Impact Thinking of the Spongy City Construction in Built-Up Areas from the Perspective of Sustainable Urban Design .....................................................328 Xili Han, Wenqiang Zhao, Linus Zhang, and Peter Siostrom Challenges and Future Improvements to China’s Sponge City Construction ...............................................................................................................................339 Hong Wang, Xiaotao Cheng, Li Man, Na Li, Jing Wang, and Qian Yu A CFD-Based Level Sensor Location Optimization Method for Overflow Discharge Estimation in CSOs .................................................................................352 Hexiang Yan, Kangqian Zhao, Gislain Lipeme Kouyi, Tao Tao, Kunlun Xin, and Shuping Li Value and Rational Use of Landform Resources in Low Impact Development ...............................................................................................................................363 Dehua Mao, Wen Liu, and Min Yang The Application of Adaptive Design Strategies in Urban Green Stormwater Infrastructure Development ................................................................................372 Wei Zhang, Jack Ahern, and Xiaoming Liu Hydrologic Design and Economic Benefit Analysis of Rainwater Harvesting Systems in Shanghai, China ..................................................................................381 Shouhong Zhang and Xueer Jing A New Approach to Urban Water Environment Protection: Leasing Mode and Its Risk Management of Urban Rivers and Lakes Pollution Control Projects under Public-Private Partnership Model ...................................................390 Zhixuan Wu, Lu Zhou, Yi Zhou, and You Zhou © ASCE vii International Low Impact Development Conference China 2016 Temporal and Spatial Variations of Extreme Precipitation and Flood Thresholds in Qinghe Basin in Beijing, China Li Lu1; Xuebiao Pan2; Lizhen Zhang3; and Xingyao Pan4 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. 1 Agricultural Meteorological Dept., College of Resources and Environmental Sciences, China Agriculture Univ., P.O. Box 100193, Yuanmingyuan Xi Rd. No. 2, Haidian District, Beijing; Dept. of Beijing East-to-West Water Diversion Project, Beijing Water Authorities Bureau, P.O. Box 100192, Qinghe Rd. No. 189, Haidian District, Beijing. E-mail: [email protected] 2 Agricultural Meteorological Dept., College of Resources and Environmental Sciences, China Agriculture Univ., P.O. Box 100193, Yuanmingyuan Xi Rd. No. 2, Haidian District, Beijing (corresponding author). E-mail: [email protected] 3 Agricultural Meteorological Dept., College of Resources and Environmental Sciences, China Agriculture Univ., P.O. Box 100193, Yuanmingyuan Xi Rd. No. 2, Haidian District, Beijing. Email: [email protected] 4 Beijing Water Sciences and Technology Institute, P.O. Box10004, Chegongzhuang Xi Rd. No. 21, Haidian District, Beijing. E-mail: [email protected] ABSTRACT Extreme weather frequently causes torrential rains and flooding in modern cities, e.g., Beijing, which are much sensitive and fragile to flooding disasters because of high population density. In this study, we aimed to quantify the temporal and spatial distribution of extreme precipitation in Qinghe Basin in Beijing and to develop optimal flood management thresholds by using precipitation records from 1986 to 2014 in two sites of the region. The time that maximum precipitation occurs in a year differed temporally and spatially and mainly concentrated in July and August. Extreme precipitation amount covered 41.7% of total precipitation in a month during flood season. Rain days of rainstorms were on average 1.7 d and 87% of them concentrated in July and August and were more in upstream than that in downstream. Precipitation intensity (SDII) during flood season was on average 11.7 mm d1 and highest (15.1 mm d1) in July. SDII during critical flood control period increased in upstream during recent 30 years and implied a high flood risk in the future. The spatial distribution of precipitation intensity was significantly different. Our results at basin level would help city authorities designing optimal flood control constructions, drainage facilities, and warning systems. KEY WORDS: climate variation; flood control; precipitation intensity; rain events; urban area INTRODUCTION Meteorological and secondary disasters happened frequently due to the extreme weather under climate change in the world especially during 21 century. Under climate change, the maximum of total precipitation and extreme rain events from 1950 to 2014 occurred in 1990s and 2000s, and the extreme rain events would continuously increase according to the report of Intergovernmental Panel on Climate Change (IPCC) (2014). Since meteorological disasters cause significant social and economic losses, governments, civil societies, organizations and the public therefore pay great concern to the managements of the disasters for the alleviation of the negative influences of climate changes. Extreme weathers frequently cause torrential rains and flooding in modern cities, e.g. Beijing © ASCE 1 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. International Low Impact Development Conference China 2016 and Shanghai, which are more sensitive and fragile to flooding disasters because of high population density. The average annual cost of natural disasters was 200 to 400 billion Yuans from 1949 to 1989 and gradually increased due to the climate changes. The safety of big cities, including managements, lives and properties, is greatly threatened by seeping in streets, rainwater intrusion into underground facilities and other damages caused by extreme precipitation events. “Metropolis Disease” due to extreme precipitations were frequently reported by public media. For example, a heavy rain of 170 mm in one day, with a maximum precipitation of 541 mm in Hebeizhen in Fangshan District, attacked Beijing on July 21, 2012, which broke a historical record of single rain station in Beijing. Nearly 600 million m3 rainwater concentrated in a 2000 km2 area in Fangshan District during 10 hours, which equaled that the Kunming Lake in Summer Palace was poured down once every 3 minutes. The highest rainstorm warning grade with “Orange Degree” and “Level II” of Flood Control Emergency were announced. The direct economic losses were as high as 11.8 billion Yuan, and 119.28 million populations were greatly affected. Total 9.48 million people were transferred to safe regions in emergency, and 79 people were died during this terrible event. More than 10 thousands of houses collapsed, 940 enterprises were discontinued, and 361 kilometers embankments were damaged. The huge losses from this extreme precipitation event were partially due to the limitation knowledge on the relationship between extreme rain and flood occurrence in a big city. Temporal and spatial distribution of precipitation intensity in relation to the land use types and population density would significantly affect the alarm threshold. However, such important studies are lagged. Average annual rainstorm days in China showed a slight but not significant increasing trend in the past half century (Zhi et al., 2006; Min and Qian, 2008; Feng et al., 2008; Zou et al., 2009; Chen et al., 2010). The frequency and intensity of extreme precipitation over total rainfall events increased in most of China, while the rainfall days tended to be decreasing, and annual rainstorm days slightly increased with high differences in temporal and spatial distribution (Zhai et al., 2005; Wang and Zhai, 2008). Heavy rainfall in summer reduced in the north of China (Wang and Yan, 2009). The frequency and intensity of extreme precipitation events decreased in North China (Alexander et al., 2006; Wang et al., 2012). The frequency of precipitations during 1954 to 2006 reduced in North China; however, that of heavy rain did not too (Tu et al., 2010). The extreme precipitation intensity and frequency of big cities in north of China were increased more than in surrounding agricultural areas (Wang and Zhai, 2009). Although the extreme precipitation amount, days and intensity in Beijing showed a downward trend from 1981 to 2010 (You et al. (2009), the highest precipitation intensity occurred in 2012. That implies increased variations of precipitations in Beijing, thus, it is necessary to explore the temporal and spatial variations of precipitations in relation to flood control based on the capability of flood discharges at a basin level. The objectives of this study therefore were to (a) quantify the temporal and spatial distribution of extreme precipitations with frequency, amount and intensity in the basin of Qinghe River in north of Beijing city, where is one of four rivers in the capital urban center with a drainage area of 175 km2, a length of 28.7 km, an elevation range from 24.4 m to 500.3 m, and a stream length of 23.7 km; and (b) develop an extreme precipitation threshold (index) for the flood control of Beijing city in relation to the real basin situation, in which the hydraulic structures and embankment of Qinghe River are 20 years of flood recurrence period. Considering natural and social factors, the study would help to design an optimal construction of Sponge Cities and provide scientific support to emergency warning and response activities. © ASCE 2 International Low Impact Development Conference China 2016 3 MATERIALS AND METHODS Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Study sites The study sites are Qinghe (40o01'N, 116o20'E) and Yangfang (40o02'N, 116o24'E) located in north of Beijing city (Fig. 1), where are main regions for rain water collection in Qinghe basin. Ten flood discharge gates are distributed along Qinghe river, i.e. Anhe gate, Xiaojiahe gate, Shucun gate, Jingbao gate, Qinghe gate, Xiaqinghe gate, Yangfang gate, Waihuan gate, Shenjiafen gate and Shaziying gate (Fig. 1). The basin lies in semi-humid continental monsoon climate, affected by the high-pressure Mongolia with prevailing northerly winds in winter, and by the continental thermal low-pressure system with prevailing southerly winds in summer. Qinghe site is located at upstream of Qinghe basin in the front terrain of Jundu mountain, and the climate is characterized as a strong air convection current, which often causes rainstorms. Yangfang site is located at downstream of Qinghe basin and affected by urban heat island effect, by which short and partly rainstorm often occurs. The two sites therefore could well present the precipitation situation of studied basin. Shaziying gate Shenjiafen gate Yangfang gate Waihuan gate Qinghe gate Xiaqinghe gate Shucun gate Jingbao gate Anhe gate Xiaojiahe gate Beijing Figure 1. Locations of studied sites (red color crosses) and water discharge gates (blue filled circles) for controlling flood of Beijing. Data source The precipitation data of studied sites of Qinghe and Yangfang was from local meteorological and hydrological stations. Data was recorded from 1986 to 2014. During 1986 to 2004, the precipitation data was measured by a 0.5 mm resolution manual rain gauge. During 2005 to 2014, the data was measured by a 0.1 mm resolution automatic rain gauge. All data was manually re-checked by local hydraulic station to ensure the accuracy. Data analysis Extreme weather events are rare weather events in specific areas and time (Solomon et al., 2007). Extreme weather event is defined as a weather event of a certain region when it seriously deviates from its average. Since “abnormal weather” is relative meaning that is not same for different regions and seasons, World Meteorological Organization Commission for Climatology (CCI/ WMO) recommends to divide climate extremes index into two categories, one is depended © ASCE 4 on absolute physical boundaries and another is relative extreme index, which extreme events have statistical probability of extreme low or high values, i.e. less than 10 percentile or greater than 90 percentile in accumulative distribution function (Wang and Wang, 2007). Seasonal distribution of precipitations in Beijing is uneven, especially in the studied region where the precipitations during flood season (June to September) account for 64% of the total annual precipitations and most daily precipitations in winter (from November to January) are zero. We therefore only focused the period of flood season (1 June to 30 September). All calculations were done only during this period. The absolute values for categorizing extreme precipitations were used in this study. In order to classify precipitations into categories, i.e. middle rain, heavy rain and rainstorm, we used absolute thresholds which are commonly used in Beijing region. We categorized a precipitation greater than 10 mm as a middle rain, 25 mm as a heavy rain and 50 mm as a rainstorm. The days of each rain category were calculated accordingly. SDII defined as index of precipitation intensity is the total precipitation amount divided by rain days. 300 Occurrence time of highest precipitation (d) Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. International Low Impact Development Conference China 2016 280 260 September 240 August 220 200 July 180 June 160 y = 0.6192x - 1030 R2 = 0.0592 (QH) 140 Qinghe (QH) 120 Yangfang (YF) 100 1985 1990 1995 y = 0.4833x - 761.05 R2 = 0.0187 (YF) 2000 2005 2010 2015 Years Figure 2. Distribution of occurrence time (Calendar days) of maximum precipitation per year from 1986 to 2014 in Qinghe and Yangfang, Beijing. Color filled areas indicate flood season and months. © ASCE International Low Impact Development Conference China 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Ratio of extreme precipitation 1 a June 5 b July 0.8 0.6 0.4 0.2 y = -0.0022x + 4.84 R2 = 0.0203 (QH) y = -0.0026x + 5.6517 R2 = 0.0243 (YF) y = 0.0051x - 9.7404 R2 = 0.0859 (QH) y = 0.0062x - 12.08 R2 = 0.0962 (YF) 0 1 Ratio of extreme precipitation c August d September 0.8 0.6 0.4 0.2 y = 0.0046x - 8.771 R2 = 0.0715 (QH) y = 0.0016x - 2.7767 R2 = 0.0112 (YF) y = 0.0042x - 8.0141 R2 = 0.0426 (QH) y = 0.0046x - 8.7884 R2 = 0.0505(YF) 0 1985 0.5 Ratio of extreme precipitation e Flood period 1990 1995 2000 2005 2010 2015 Years Qinghe (QH) 0.4 Yangfang (YF) 0.3 0.2 0.1 y = 0.0014x - 2.631 R2 = 0.0421 (QH) 0 1985 1990 1995 y = 0.0007x - 1.1573 R2 = 0.0045 (YF) 2000 2005 2010 2015 Years Figure 3. Trends of the ratio of extreme precipitation amount over total precipitation during a period from 1986 to 2014 in Qinghe and Yangfang, Beijing RESULTS Extreme precipitations The time that maximum precipitation occurs in a year was distributed almost all within June to September (flood season), except for an exclusion of 1997 in Yangfang (Fig. 2). The highest frequency of the occurring time was in July, while that rarely distributed in June and September. © ASCE Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. International Low Impact Development Conference China 2016 6 Comparing to a concentrated distribution of occurring times of maximum precipitation events in Qinghe, the occurring times in June and September in Yangfang were much more, where there were also not much maximum precipitations in these two months. The ratios of extreme precipitation over total precipitation in June for both Qinghe and Yangfang were slightly decreased from 1986 to 2014 (Fig. 3a), while that in July, August and September showed increasing trends (Fig. 3b,c,d). In June, the extreme precipitations and their variations before 1991 were much higher, comparing to a stable trend after 1991. However, the variations of the ratio of extreme precipitation over total amount of rainfall in July during 2000 to 2014 were much higher than before 1994. That indicates an increased risk of flood in Beijing in July. Days of extreme precipitations Rain days of middle precipitations (R10 mm) during flood season averaged from 1986 to 2014 were 13.1 d and 16.7% more in 1980s than the average of 1990s and 2000s in Qinghe, while that were 13.8 d and 22.7% more in 1980s. The middle rain events mostly occurred in July and August. Rain days of heavy precipitations (R25 mm) during flood season averaged from 1986 to 2014 were 5.2 d in Qinghe and 5.9 d in Yangfang. The 36-44% heavy rain events concentrated in July in both sites, while it rarely happened in September. Rain days of rainstorm (R50 mm) during flood season on average of 1986 to 2014 were 1.8 d in Qinghe and 1.6 d in Yangfang (Table 1). Events of rainstorms concentrated in July and August with a proportion of 80% over flood season for both sites, which indicated a critical period to control the flood in Beijing city. Table 1 Rain days of threshold precipitation events (d) during flood season (June to September) from 1986 to 2014 in Qinghe and Yangfang, Beijing Indexa R10 mm Period R50 mm Yangfang 1980s 1990s 2000s Average June 1.8 1.9 2.7 July 5.0 5.8 August 6.0 September 2.2 b 1980s 1990s 2000s Average 2.3 3.8 2.7 3.6 3.3 4.7 5.1 5.0 5.5 4.0 4.7 3.6 3.7 4.0 5.0 3.9 3.5 3.8 1.7 1.6 1.7 2.7 1.9 1.8 2.0 15.0 13.0 12.7 13.1 16.5 14.0 12.9 13.8 June 0.8 0.8 0.7 0.7 2.3 1.7 1.7 1.8 July 1.5 3.0 2.1 2.3 2.0 2.9 1.5 2.1 August 2.2 1.6 1.6 1.7 2.0 1.9 1.5 1.7 September 0.5 0.5 0.5 0.5 0.0 0.6 0.3 0.3 Flood season 5.0 5.9 4.9 5.2 6.3 7.1 5.0 5.9 June 0.3 0.5 0.1 0.3 0.3 0.3 0.1 0.2 July 0.2 1.4 0.8 0.9 0.2 1.1 0.5 0.7 August 0.5 0.6 0.5 0.5 1.5 0.7 0.3 0.6 September 0.0 0.0 0.1 0.1 0.0 0.1 0.1 0.1 Flood season R25 mm Qinghe Flood season 1.0 2.5 1.5 1.8 2.0 2.2 1.0 1.6 Index of R10 mm, R25 mm and R50 mm indicates rain days of middle (>10 mm), heavy (>25 mm) and rainstorm (>50 mm) precipitation events, respectively. b Average indicates the data is averaged from 1986 to 2014. a © ASCE International Low Impact Development Conference China 2016 7 From 1986 to 2014, R10 mm greatly decreased in two sites, especially in Yangfang (Fig. 4b). R50 mm showed only a slight decrease in both sites. R25 mm had a similar decreasing trend. The yearly variations of R50 mm were smaller than that of R10 mm and R25 mm (Fig. 4). Days of extreme precipitation (d) Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. 25 20 a Qinghe b Yangfang y = -0.0507x + 114.62 R2 = 0.0178 (R10mm) y = -0.0128x + 27.374 R2 = 0.0058 (R50mm) y = -0.164x + 341.84 R2 = 0.1487 (R10mm) y = -0.0507x + 103.03 R2 = 0.1063 (R50mm) y = -0.0261x + 57.458 R2 = 0.0072 (R25mm) y = -0.0901x + 186.19 R2 = 0.0814 (R25mm) 15 10 5 0 1985 1995 2015 1985 2005 1995 Years R10mm R25mm Years 2005 2015 R50mm Figure. 4 Trends of rain days of threshold precipitation events (d) during flood season (June to September) from 1986 to 2014 in Qinghe (a) and Yangfang (b), Beijing. R10 mm, R25 mm and R50 mm indicate rain days of middle (>10 mm), heavy (>25 mm) and rainstorm (>50 mm) precipitation events, respectively Precipitation intensity SDII index, defined as an averaged precipitation intensity (mm d1) calculated by the ratio of total precipitation amount during a period divided by rain days, was similar in two sites on average from 1986 to 2014 during flood period, i.e. 11.8 mm d1 in Qinghe and 11.5 mm d1 in Yangfang (Table 2). The highest SDII occurred in July with a value of 14.9 mm d1 in Qinghe and 15.2 mm d1 in Yangfang. SDIIs in June and September were low ranged from 7.1 mm d1 to 8.6 mm d1 on average from 1986 to 2014. The highest SDII occurred in July of 1990s ranged from 16.5 mm d1 to 18.1 mm d1 in two sites. Table 2 Monthly averaged precipitation intensity (SDII, mm d1) from 1986 to 2014 and during three decades in Qinghe and Yangfang, Beijing Site Qinghe Yangfang Period Flood season June July August September 1980s 11.7 11.4 9.6 16.6 7.6 1990s 12.1 8.1 16.5 11.8 6.1 2000s 11.6 8.1 15.2 13.5 7.7 1986-2014 11.8 8.6 14.9 13.4 7.1 1980s 12.0 12.0 11.3 16.2 6.7 1990s 12.7 8.4 18.1 12.4 7.4 2000s 10.6 7.8 14.2 11.9 7.6 1986-2014 11.5 8.6 15.2 12.6 7.4 SDII is the total precipitation per month or during flood season divided by rain (wet) days during the period. © ASCE International Low Impact Development Conference China 2016 8 From 1986 to 2014, SDII showed a slight but not significant decreasing trend during flood period in Yangfan, however SDII in Qinghe during flood period increased (Fig. 5). While SDIIs in June and August slightly decreased in two sites, during July, which is the critical flood control period, and September, these trends were increasing especially in Qinghe (Fig. 5b). 40 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. a June y = 0.0062x - 12.08 R2 = 0.0962 (YF) b July 35 SDII index (mm d -1) 30 y = -0.0022x + 4.84 R2 = 0.0203 (QH) 25 20 y = -0.0026x + 5.6517 R2 = 0.0243 (YF) 15 10 5 y = 0.0051x - 9.7404 R2 = 0.0859 (QH) 0 40 c August d September SDII index (mm d -1) 35 30 25 y = 0.0016x - 2.7767 R2 = 0.0112 (YF) y = 0.0046x - 8.771 R2 = 0.0715 (QH) y = 0.0046x - 8.7884 R2 = 0.0505(YF) 20 y = 0.0042x - 8.0141 R2 = 0.0426 (QH) 15 10 5 0 1985 40 35 e Flood period SDII index (mm d -1) 2000 2005 2010 2015 Qinghe (QH) y = 0.0007x - 1.1573 R2 = 0.0045 (YF) 25 1995 Years y = 0.0014x - 2.631 R2 = 0.0421 (QH) 30 1990 Yangfang (YF) 20 15 10 5 0 1985 1990 1995 2000 2005 2010 2015 Years Figure. 5 Trends of precipitation intensity (SDII) during flood period from 1986 to 2014 in Qinghe and Yangfang, Beijing © ASCE International Low Impact Development Conference China 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. CONCLUSIONS AND DISCUSSION The time that highest precipitation occurs in a year differed temporally and spatially and mainly concentrated in July and August. Extreme precipitation amount covered, on average for sites and months, 41.7% of total precipitation in a month during flood season. Extreme precipitation amount in July, August and September in Beijing increased from 1986 to 2014, especially in July, which was consistent with Zhang et al. (2008) and You et al. (2009). That indicates the flood risk in Beijing would increase due to the climate change or probably fast urbanization. Rain days of heavy precipitations during flood season on average were 5.6 d and 40% of them concentrated in July. Rain days of rainstorm, as critical events for flood control, were on average 1.7 d and 80% of them distributed in July and August. However, rainstorm events showed the decreasing trends from 1986 to 2014. Rain days of rainstorms were more in upstream of Qinghe basin than that in downstream, which were probably caused by the mountain effects. The results were consistent with previous studies (Alexander et al., 2006; You et al., 2009; Wang et al., 2012). Precipitation intensity (SDII) during flood season was on average 11.7 mm d1 and highest (15.1 mm d1) in July. The spatial distribution of precipitation intensity was significantly different. SDII during critical flood control period (July) slightly but not significantly decreased in downstream of Qinghe basin (Yangfan site), however, increased in upstream (Qinghe site) during recent 30 years. It implies the flood risk of upstream would increase and discharging pressure of whole basin further increase. In Beijing city, the 5% extreme precipitation covers 30-38% of total amount of precipitation and critical flood control period is from 20 July to 10 August (You et al., 2009). However, our study showed the extreme precipitation proportioned 38-47% of total precipitation during flood season in Qinghe basin, which was 25% higher than the average of total Beijing. The critical flood control period based on the frequency and intensity of precipitation events was from 20 June to 16 August in Qinghe basin, which was 36 d longer than that in total Beijing. The temporal and spatial distribution of extreme precipitation in terms of occurrence time, days and the intensity in Beijing at a basin level would help city authorities designing an optimal flood control constructions, drainage facilities and warning systems. Due to the increasing trend of extreme precipitation in Qinghe basin, the standards of flood prevention and pipe drainage adapted to the sponge city might be necessarily researched. In this study, we only focused on the analysis of climate variation and trends, however, for a better control of flood in a huge city (e.g. Beijing), the studies in relation to the land use changes due to city expansion, vegetation, river flow and discharge areas should be considered to quantitatively clarify the relationship between the rainfall and flood resources, inflow rate of a river and flood detention in outer and inner of city. ACKNOWLEDGEMENTS The study was supported by National Nature Science Fund (NSFC) Project (41271053, 41475104). REFERENCES Alexander, L.V., Zhang, X., Peterson, T.C., Klein Tank, A.M.G., Haylock, M., Collins, D., Trewin, B., Rahimzadeh, F., Tagipour, A., Rupa Kumar, K., Revadekar, J., Griffiths, G., © ASCE 9 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. 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Zou, Y., Yang, X., Sun, X., Tang, J., Fang, J. and Liao, Y. (2009). “Seasonal difference of the spatio-temporal variation of the number of the extreme precipitation processes in China.” Journal of Nanjing University (Natural Sciences), 45(1), 98–109. © ASCE 11 International Low Impact Development Conference China 2016 The Effects of Low Impact Development Practices on Urban Stormwater Management Na Li, Ph.D.1; Qian Yu, Ph.D.2; Jing Wang, Ph.D.3; and Xiaohe Du4 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. 1 State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, People’s Republic of China; Research Center on Flood and Drought Disaster Reduction of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, People’s Republic of China. E-mail: [email protected] 2 State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, People’s Republic of China; Research Center on Flood and Drought Disaster Reduction of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, People’s Republic of China (corresponding author). E-mail: [email protected] 3 State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, People’s Republic of China; Research Center on Flood and Drought Disaster Reduction of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, People’s Republic of China. E-mail: [email protected] 4 State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, People’s Republic of China; Research Center on Flood and Drought Disaster Reduction of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, People’s Republic of China. E-mail: [email protected] ABSTRACT Low impact development (LID), which aims at either infiltrating, evapotranspiring or storing water at the source, plays an important role in managing urban rainwater. This paper summarizes the effects of four individual LIDs (i.e., bioretention, green roof, porous pavement, and grass swales) and several combinations of those LID practices on rainfall-runoff management. The survey shows that both individual and combined LIDs are effective in controlling small and medium rainfalls, and the performances are less obvious with increases of the rainfall depths. Hence, the individual or combined LIDs applied with noticeable effects on low or moderate rainfalls might not be useful for heavy rain events which would probably cause urban floods in cities in China. Cities located in different regions show big differences in rainfall characteristics. Rainfall intensity is an even more important factor than rainfall depth that influences performances of LID practices. In the future, more studies should be directed to the effects of LID measures on large storm runoff managements under different rainfall intensity-durationfrequency (IDF), which would be helpful to select suitable LID practices for cities in China. INTRODUCTION During the last decades, urbanization has almost swept across China. The population growth, urban density changes, and land cover changes accompany with urbanizations and urban developments. The traditional developments leading to land cover changes will raise the high proportions of imperviousness. In addition, traditional developments will also result in increased surface runoff volume, diminished infiltration and decreased baseflow in consequence © ASCE 12