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全文下载次数:39
2018年第3期   DOI:10.22217/upi.2017.425
美国智能雨洪管理途径与发展前景研究
Current Instruments and Future Development of Intelligent Stormwater Management in the US

孟婷

Meng Ting

关键词:智能感测;智能控制;雨洪基础设施

Keywords:Intelligent Sensoring; Intelligent Control; Stormwater Infrastructure

摘要:

随着雨洪管理日益受到关注和智能技术的迅猛发展,智能雨洪管理成为美国各级政府和相关部门对雨洪管理实现有效和实时调控的热点发展方向。通过在基础设施上安装智能传感组件,与管理中心发生交互,完成雨洪信息搜集、分析、处理、控制和调整,智能雨洪管理扩展了基础设施的功能范围,增强了自动化操作和管理的灵活性,降低了长期维护成本和人力投入,有利于提升雨洪管理的效率和成果。本文以智能雨洪管理的发展背景为切入点,辨析智能雨洪管理的相关概念,并结合实际案例分析了美国雨洪管理的应用现状、发展重点、现实阻碍和有效推广途径,以期对我国未来雨洪管理的智能化提供借鉴。

Abstract:

With a broad attention on stormwater management and the rapid development of intelligent technology, intelligent stormwater management provides opportunities to governments at all levels to integrate the real-time control in stormwater management. By installing sensors and controls on stormwater infrastructure with connection to a central management system, intelligent stormwater management fulfills an entire process of collection, analysis, control, operation and adjustment in the system. It improves infrastructure capability, enhances auto-operation and flexibility, saves longrun labor and maintenance cost, and increases the efficiency of stormwater management. Based on the demonstration of background and key concepts, this paper investigates the current status, implementing opportunities, potential barriers, and promotion channels of intelligent stormwater management in the US. It provides insightful experience and lessons on how to use intelligent stormwater management in China.

版权信息:
基金项目:国家自然科学基金项目(41501169)
作者简介:

孟婷,中国农业大学经济管理学院,讲师。tmeng@cau.edu.cn

译者简介:

参考文献:
  • [1] GRIFFIN D, ANCHUKAITIS K J. How unusual is the 2012-2014 California drought?[J]. Geophysical Research Letters, 2014, 41(24): 9017-9023.
    [2] LEE J G. Estimation of urban imperviousness and its impacts on storm water systems[J]. Journal of Water Resources Planning and Management, 2003, 129(5): 419-426.
    [3] THURSTON H. Opportunity costs of residential best management practices for stormwater runoff control [J]. Journal of Water Resources Planning and Management, 2006, 132(2): 89-96. DOI: 10.1061/(ASCE)0733-9496(2006)132:2(89).

    [4] RASEHK A, HASSANZADEH A, MULCHANDANI S, et al. Smart water networks and cyber security[J]. Journal of Water Resources Planning and Management, 2016,142(7): 01816004-1. DOI: 10.1061/(ASCE)WR.1943-5452.0000646.
    [5] RUGGABER T P, TALLEY J W, Montestruque L A. Using embedded sensor networks to monitor, control, and reduce CSO events: a pilot study [J]. Environmental Engineering Science, 2007, 24(2): 172-182.
    [6] ZIA H, HARRIS N R, MERRETT G V. Water quality monitoring, control and management framework using collaborative wireless sensor networks[C/OL]. Conference presented at the 11th International Conference on Hydroinformatics (HIC), 2014. http://eprints.soton.ac.uk/365852/.
    [7] KERKEZ B, GRUDEN C, LEWIS M, et al. Smarter stormwater systems [J]. Environmental Science & Technology, 2016, 50: 7267-7273.
    [8] STEINER F, SIMMONS M, GALLAGHER M, et al. The ecological imperative for environmental design and planning[J]. Frontiers in Ecology and the Environment, 2013, 11(7): 355-361.
    [9] MENG T, HSU D, WADZUK B. Green and smart: perspectives of city and water agency officials in Pennsylvania toward adopting new infrastructure[J]. Journal of Sustainable Water in the Built Environment, 2017, 3(2): 05017001.
    [10] DARSONO S, LABADIE J W. Neural-optimal control algorithm for realtime regulation of in-line storage in combined sewer systems[J]. Environmental Modelling & Software, 2007, 22(9): 1349-1361.
    [11] REIDY P C. Innovation in CSO reduction: implementing intelligent distributed infrastructure[C]. World Environmental and Water Resources Congress 2011: Bearing Knowledge for Sustainability, 2011: 3539-3549.
    [12] Opti. Project[EB/OL]. (2017)[2017-8-18]. http://optirtc.com/projects.
    [13] YU B, BEHERA P K, ROCHAC J F R. Advanced sensor-computer technology for urban runoff monitoring[J]. Proceedings of SPIE, 2011, 79815U. DOI: 10.1117/12.881817.
    [14] MUSCHALLA D, VALLET B, ANCTIL F, et al. Ecohydraulic-driven realtime control of stormwater basins[J]. Journal of Hydrology, 2014, 511(4): 82-91.
    [15] CRAWFORD A. Green technologies and sensor networks for BMP evaluation in stormwater retention ponds and wetlands[D/OL]. (2014)[2017-8-7]. Master thesis. University of Central Florida. http://stars.library.ucf.edu/etd/1209/.
    [16] STARRY O, LEA-COX J, RISTVEY A, et al. Monitoring and modeling green roof performance using sensor networks[J]. Acta Horticulturae, 2014, 1037(1037): 663-669.
    [17] STARRY O S, LEA-COX J D, RISTVEY A G, et al. Utilizing sensor networks to assess evapotranspiration by greenroofs[C]. American Society of Agricultural and Biological Engineers, 2011.
    [18] OCAMPO-MARTINEZ C, PUIG V, CEMBRANO G, et al. Application of predictive control strategies to the management of complex networks in the urban water cycle[J]. IEEE Control Systems, 2013, 33(1): 15-41.DOI:10.1109/MCS.2012.2225919.
    [19] WANG Z, SONG H, WATKINS D W, et al. Cyber-physical systems for water sustainability: challenges and opportunities[J]. IEEE Communications Magazine, 2015, 53(5): 216-222. DOI:10.1109/MCOM.2015.7105668.
    [20] 王岩. 论海绵城市在市政工程设计中的应用[J]. 城市道桥与防洪, 2016, 1: 100-102.
    [21] 张静. 中国科学院院士刘昌明: 海绵城市建设需做足气候变化应对文章[N]. 中国气象报, 2016-2-17(1).
    [22] 潘安君, 张书函, 孟庆义, 等. 北京城市雨洪管理初步构想[J]. 中国给水排水, 2009, 25(22): 9-12.
    [23] 车伍, 张伟, 李俊奇, 等. 中国城市雨洪控制利用模式研究[J]. 中国给水排水, 2010, 26(16): 51-57.

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