气候变化背景下城市应对极端降水的适应性方案研究——以西宁海绵城市试点区为例
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摘要
气候变化将导致极端天气事件频率与强度的增加,城市迫切需要对未来的极端天气做出适应性反应.因此,为了找到应对未来暴雨极端天气的最佳适应性方案,明确不同方案对暴雨极端天气的缓解程度,本研究基于西宁市海绵城市试点区50年(1966—2015)的气象资料,利用Pearson-III概率分布和线性趋势估计法预测了该区未来50年的极端降水量,进而利用SWMM模型模拟未来50年极端降水条件下的城市内涝情况,并根据模拟结果提出基于低影响开发(LID)配置和管网改造的城市内涝适应方案.这些方案包括:局部布设LID措施、局部布设LID措施结合局部管网改造、全局布设LID措施、全局布设LID措施结合满流管网改造.再次利用SWMM模型对这些方案进行模拟,并评价它们应对未来极端降水的能力.结果表明,全局布设LID措施和满流管网改造的效果最好,全局布设LID措施的效果和局部布设LID措施结合局部管网改造的效果相近.然而,管网改造无法有效储存和利用雨水资源,因此,全局布设LID措施将成为城市应对极端降雨的重要适应性方案.
Climate change would result in the increase of extreme weather events. Correspondingly, the increase in extreme precipitation and rapid urbanization would cause more serious waterlogging problems. To address these challenges, it is necessary to develop an adaptive solution to tackle the potential problems of extreme weather events in the future. Based on the observed meteorological data(period: 1966—2015) of a sponge city in Xining(Qinghai Province, China), we adopted the Pearson-III probabilistic distributions method and the linear trend estimation method to estimate the daily maximum precipitation, as extreme precipitation, of the year of 2065. Furthermore, the Storm Water Management Model(SWMM) was applied to simulate and analyze the urban waterlogging problems under future extreme precipitation events. To cope with the urban waterlogging problems, we put forward some climate adaptation schemes involving the deployment of Low Impact Development(LID) measures and pipe network transformation(PNT). Specifically, the schemes include local-area LID measures deployment, local-area LID measures deployment with local PNT, whole-area LID measures deployment and whole-area LID measures deployment with full flow PNT. The SWMM model was used to simulate these counter-measures, and the ability of these schemes on coping with the extreme precipitation waterlogging problems was evaluated using the entropy weight method. The evaluation results show that the scheme of whole-area LID measures deployment with full flow PNT would be the most effective measure on handling the city′s waterlogging problems. The effect of the whole-area LID measures would be close to the effect of the scheme of local LID measures deployment with local PNT. However, PNT could not store and utilize the rainwater resources. Hence, the scheme of whole-area LID measures deployment should be adopted for managing the challenges of urban extreme precipitation events in the future.
Climate change would result in the increase of extreme weather events. Correspondingly, the increase in extreme precipitation and rapid urbanization would cause more serious waterlogging problems. To address these challenges, it is necessary to develop an adaptive solution to tackle the potential problems of extreme weather events in the future. Based on the observed meteorological data(period: 1966—2015) of a sponge city in Xining(Qinghai Province, China), we adopted the Pearson-III probabilistic distributions method and the linear trend estimation method to estimate the daily maximum precipitation, as extreme precipitation, of the year of 2065. Furthermore, the Storm Water Management Model(SWMM) was applied to simulate and analyze the urban waterlogging problems under future extreme precipitation events. To cope with the urban waterlogging problems, we put forward some climate adaptation schemes involving the deployment of Low Impact Development(LID) measures and pipe network transformation(PNT). Specifically, the schemes include local-area LID measures deployment, local-area LID measures deployment with local PNT, whole-area LID measures deployment and whole-area LID measures deployment with full flow PNT. The SWMM model was used to simulate these counter-measures, and the ability of these schemes on coping with the extreme precipitation waterlogging problems was evaluated using the entropy weight method. The evaluation results show that the scheme of whole-area LID measures deployment with full flow PNT would be the most effective measure on handling the city′s waterlogging problems. The effect of the whole-area LID measures would be close to the effect of the scheme of local LID measures deployment with local PNT. However, PNT could not store and utilize the rainwater resources. Hence, the scheme of whole-area LID measures deployment should be adopted for managing the challenges of urban extreme precipitation events in the future.
引文
Akinyemi E. 2008. International Experiences with Low Impact Development (LID) [C]. International Low Impact Development Conference
拜亚丽. 2018. 基于熵权的集对分析法在水环境质量评价中的应用[J].地下水, 40(5): 70-72
Campbell C W, Sullivan S M. 2002. Simulating time-varying cave flow and water levels using the Storm Water Management Model [J]. Engineering Geology, 65(2): 133-139
程晓陶, 王静, 夏军, 等. 2008. 气候变化对淮河防洪与排涝管理项目的影响及适应对策研究[J]. 气候变化研究进展, 4(6): 324-329
封威. 2015. 基于SWMM武汉某小区低影响开发设计与模拟评估[D]. 武汉: 华中科技大学
Gilroy K L, Mccuen R H. 2009. Spatio-temporal effects of low impact development practices [J]. Journal of Hydrology, 367(3/4):228-236
郭凤, 陈建刚, 杨军, 等. 2016. SWMM模拟植草沟功能的参数敏感性分析[J]. 中国给水排水, 32(9): 131-134, 139
侯改娟. 2014. 绿色建筑与小区低影响开发雨水系统模型研究[D]. 重庆: 重庆大学
Kahsay G A, Hansen L G. 2016. The effect of climate change and adaptation policy on agricultural production in Eastern Africa [J]. Ecological Economics, 121:54-64
Kim K U, Park S W, Shin S H, et al. 2007. Construction of a real-time urban inundation analysis system based on UIS using SWMM [C]. Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management & Applications. 38-46
Kong F, Ban Y, Yin H, et al. 2017. Modeling stormwater management at the city district level in response to changes in land use and low impact development [J]. Environmental Modelling & Software, 95:132-142
林两位, 王莉萍. 2005. 用Pearson-Ⅲ概率分布推算重现期年最大日雨量[J]. 气象科技, 33(4): 314-317
李娇利. 2018. 基于AHP-熵权法和云模型的绿色建筑可持性评价研究[D].南昌:江西财经大学
李少英,刘小平,黎夏,等. 2017.土地利用变化模拟模型及应用研究进展[J].遥感学报, 21(3): 329-340
Mantyka-Pringle C S, Visconti P, Marco M D, et al. 2015. Climate change modifies risk of global biodiversity loss due to land-cover change [J]. Biological Conservation, 187:103-111
Millennium Ecosystem Assessment. 2005. Ecosystems and Human Well-being: Biodiversity Synthesis [R]. World Resources Institute, Washington, DC
Miller N L, Hayhoe K, Jin J, et al. 2008. Climate, extreme heat, and electricity demand in California [J]. Journal of Applied Meteorology & Climatology, 47(6): 1834-1844
Peterson E W, Wicks C M. 2006. Assessing the importance of conduit geometry and physical parameters in karst systems using the storm water management model (SWMM) [J]. Journal of Hydrology, 329(1/2): 294-305
Pettorelli N, Chauvenet A L M, Duffy J P, et al. 2012. Tracking the effect of climate change on ecosystem functioning using protected areas: Africa as a case study [J]. Ecological Indicators, 20(9): 269-276
Qin H P, Li Z X, Fu G. 2013. The effects of low impact development on urban flooding under different rainfall characteristics [J]. Journal of Environmental Management, 129(18):577-585
任伯帜, 许仕荣, 王涛. 2001. 皮尔逊—Ⅲ型分布统计参数的确定[J]. 中国给水排水, 17(1): 40-42
Rossman L A. 2010. Storm water management model-User′s manual version 5.0[R]. Environmental Protection Agency, EPA/600/R-05/040
She D X, Shao Q X, Xia J, et al. 2015. Investigating the variation and non-stationarity in precipitation extremes based on the concept of event-based extreme precipitation [J]. Journal of Hydrology, 530:785-798
Tripathi R, Sengupta S K, Patra A, et al. 2014. Climate change, urban development, and community perception of an extreme ?ood: A case study of Vernonia, Oregon, USA [J]. Applied Geography, 46:137-146
Tsihrintzis V A, Hamid R. 1998. Runoff quality prediction from small urban catchments using SWMM [J]. Hydrological Processes, 12(2): 311-329
van der Sterren M, Rahman A, Dennis G. 2012. Implications to stormwater management as a result of lot scale rainwater tank systems: A case study in Western Sydney, Australia [J]. Water Science Technology, 65(8):1475-1482
王茜,杨小柳,徐超伟,等. 2018.基于土地利用的城市内涝交通风险评价[J].自然灾害学报, 27(5):197-204
王琼珊, 刘晓梅, 赵冬泉. 2014. 低影响开发措施比选及适建区域分析[J]. 中国给水排水, 30(3): 96-100
魏凤英. 2007. 现代气候统计诊断与预测技术[M]. 北京:气象出版社
邢薇, 赵冬泉, 陈吉宁. 2011. 基于低影响开发(LID)的可持续城市雨水系统[J]. 中国给水排水, 27(20): 13-16
徐慧珺. 2017.基于SWMM模型的南京典型区雨洪模拟研究[D].南京:南京师范大学
Zhai P, Zhang X, Wan H, et al. 2005. Trends in total precipitation and frequency of daily precipitation extremes over China [J]. Journal of Climate, 18(18): 1096-1108
翟盘茂, 任福民, 张强. 1999. 中国降水极值变化趋势检测[J]. 气象学报, 57(2): 81-89
张大伟,赵冬泉,陈吉宁,等. 2008. 芝加哥降雨过程线模型在排水系统模拟中的应用[J].给水排水, 44(S1): 354-357
张磊,王春燕,潘小多. 2018.基于区域气候模式未来气候变化研究综述[J].高原气象, 37(5): 1440-1448
拜亚丽. 2018. 基于熵权的集对分析法在水环境质量评价中的应用[J].地下水, 40(5): 70-72
Campbell C W, Sullivan S M. 2002. Simulating time-varying cave flow and water levels using the Storm Water Management Model [J]. Engineering Geology, 65(2): 133-139
程晓陶, 王静, 夏军, 等. 2008. 气候变化对淮河防洪与排涝管理项目的影响及适应对策研究[J]. 气候变化研究进展, 4(6): 324-329
封威. 2015. 基于SWMM武汉某小区低影响开发设计与模拟评估[D]. 武汉: 华中科技大学
Gilroy K L, Mccuen R H. 2009. Spatio-temporal effects of low impact development practices [J]. Journal of Hydrology, 367(3/4):228-236
郭凤, 陈建刚, 杨军, 等. 2016. SWMM模拟植草沟功能的参数敏感性分析[J]. 中国给水排水, 32(9): 131-134, 139
侯改娟. 2014. 绿色建筑与小区低影响开发雨水系统模型研究[D]. 重庆: 重庆大学
Kahsay G A, Hansen L G. 2016. The effect of climate change and adaptation policy on agricultural production in Eastern Africa [J]. Ecological Economics, 121:54-64
Kim K U, Park S W, Shin S H, et al. 2007. Construction of a real-time urban inundation analysis system based on UIS using SWMM [C]. Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management & Applications. 38-46
Kong F, Ban Y, Yin H, et al. 2017. Modeling stormwater management at the city district level in response to changes in land use and low impact development [J]. Environmental Modelling & Software, 95:132-142
林两位, 王莉萍. 2005. 用Pearson-Ⅲ概率分布推算重现期年最大日雨量[J]. 气象科技, 33(4): 314-317
李娇利. 2018. 基于AHP-熵权法和云模型的绿色建筑可持性评价研究[D].南昌:江西财经大学
李少英,刘小平,黎夏,等. 2017.土地利用变化模拟模型及应用研究进展[J].遥感学报, 21(3): 329-340
Mantyka-Pringle C S, Visconti P, Marco M D, et al. 2015. Climate change modifies risk of global biodiversity loss due to land-cover change [J]. Biological Conservation, 187:103-111
Millennium Ecosystem Assessment. 2005. Ecosystems and Human Well-being: Biodiversity Synthesis [R]. World Resources Institute, Washington, DC
Miller N L, Hayhoe K, Jin J, et al. 2008. Climate, extreme heat, and electricity demand in California [J]. Journal of Applied Meteorology & Climatology, 47(6): 1834-1844
Peterson E W, Wicks C M. 2006. Assessing the importance of conduit geometry and physical parameters in karst systems using the storm water management model (SWMM) [J]. Journal of Hydrology, 329(1/2): 294-305
Pettorelli N, Chauvenet A L M, Duffy J P, et al. 2012. Tracking the effect of climate change on ecosystem functioning using protected areas: Africa as a case study [J]. Ecological Indicators, 20(9): 269-276
Qin H P, Li Z X, Fu G. 2013. The effects of low impact development on urban flooding under different rainfall characteristics [J]. Journal of Environmental Management, 129(18):577-585
任伯帜, 许仕荣, 王涛. 2001. 皮尔逊—Ⅲ型分布统计参数的确定[J]. 中国给水排水, 17(1): 40-42
Rossman L A. 2010. Storm water management model-User′s manual version 5.0[R]. Environmental Protection Agency, EPA/600/R-05/040
She D X, Shao Q X, Xia J, et al. 2015. Investigating the variation and non-stationarity in precipitation extremes based on the concept of event-based extreme precipitation [J]. Journal of Hydrology, 530:785-798
Tripathi R, Sengupta S K, Patra A, et al. 2014. Climate change, urban development, and community perception of an extreme ?ood: A case study of Vernonia, Oregon, USA [J]. Applied Geography, 46:137-146
Tsihrintzis V A, Hamid R. 1998. Runoff quality prediction from small urban catchments using SWMM [J]. Hydrological Processes, 12(2): 311-329
van der Sterren M, Rahman A, Dennis G. 2012. Implications to stormwater management as a result of lot scale rainwater tank systems: A case study in Western Sydney, Australia [J]. Water Science Technology, 65(8):1475-1482
王茜,杨小柳,徐超伟,等. 2018.基于土地利用的城市内涝交通风险评价[J].自然灾害学报, 27(5):197-204
王琼珊, 刘晓梅, 赵冬泉. 2014. 低影响开发措施比选及适建区域分析[J]. 中国给水排水, 30(3): 96-100
魏凤英. 2007. 现代气候统计诊断与预测技术[M]. 北京:气象出版社
邢薇, 赵冬泉, 陈吉宁. 2011. 基于低影响开发(LID)的可持续城市雨水系统[J]. 中国给水排水, 27(20): 13-16
徐慧珺. 2017.基于SWMM模型的南京典型区雨洪模拟研究[D].南京:南京师范大学
Zhai P, Zhang X, Wan H, et al. 2005. Trends in total precipitation and frequency of daily precipitation extremes over China [J]. Journal of Climate, 18(18): 1096-1108
翟盘茂, 任福民, 张强. 1999. 中国降水极值变化趋势检测[J]. 气象学报, 57(2): 81-89
张大伟,赵冬泉,陈吉宁,等. 2008. 芝加哥降雨过程线模型在排水系统模拟中的应用[J].给水排水, 44(S1): 354-357
张磊,王春燕,潘小多. 2018.基于区域气候模式未来气候变化研究综述[J].高原气象, 37(5): 1440-1448