RISK ASSESSMENT OF EXTRANEOUS WATER IN SEWAGE SYSTEMS BASED ON INTEGRATED MONITORING OF WATER SUPPLY AND DRAINAGE SYSTEMS
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摘要: 为了实现城市污水管网外来水入侵风险监测评估持续化、主动化、低廉化,在现有的外来水定性定量方法的基础上,结合城市已有的供水和排水监测感知系统,提出了1套基于供排水一体化监测的外来水风险评估方法。采用外来水占比R及外来水占比等级频率P 2个指标反应风险等级,表征外来水时空分布特性,并将其应用于南方W城市某片区的外来水风险评估工作中。2022年3-4月污水管网监测数据分析结果表明,4个厂泵和3个关键监测节点将评估区域划分为3个子区域,其中,3月旱天情况下子区域Z1外来水入侵等级为较为严重,自流区整体及子区域Z3外来水入侵程度为严重,而子区域Z2为非常严重,4月除了区域整体风险等级下降为较为严重,子区域评价结果不变。与传统方法进行比较,该方法评估结果具有可行性,对实现以较低成本开展外来水风险评估及对提升污水管网管理效率具有重要意义。Abstract: To realize the continuous and low-cost monitoring and assessment of extraneous water risk in urban sewage networks, this paper proposed a set of risk assessment methods based on integrated monitoring of water supply and drainage systems. The risk level was reflected by two indicators:extraneous water proportion R and grade frequency P, which can capture the spatial and temporal distribution of extraneous water. The methods were applied to the risk assessment of extraneous water in an area of City W in south China. The study area was divided into three sub-catchments by four plant pumps and three key monitoring nodes. The analysis results of data in March 2022 showed that the extraneous water risk level of subcatchment-Z1 was L2 (relatively high), the overall region and subctchment-Z3 was L3 (high), and the subcatchment-Z2 was L4 (very high). In April, the results of sub-catchments remained unchanged except that the overall region was reduced to L2. Compared to traditional methods, this method can output reliable conclusions, realize the risk distribution analysis of extraneous water with low cost, and has practical significance for improving the efficiency of sewage network management.
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Key words:
- sewer systems /
- extraneous water /
- risk assessment /
- online monitoring /
- water consumption
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[1] 中华人民共和国住房和城乡建设部.中国城市建设统计年鉴[M].北京:中国建筑工业出版社, 2020. [2] 周宇, 唐川东, 季久翠, 等.城市污水管网外水入流入渗及有机物损失量化分析[J].给水排水, 2022, 58(7):124-130. [3] 徐祖信, 徐晋, 金伟, 等.我国城市黑臭水体治理面临的挑战与机遇[J].给水排水, 2019, 45(3):1-7. [4] 曹业始, 郑兴灿, 刘智晓, 等.中国城市污水处理的瓶颈、缘由及可能的解决方案[J].北京工业大学学报, 2021, 47(11):1292-1302. [5] 周乙新, 李激, 王燕, 郑凯凯, 等.城镇污水处理厂低浓度进水原因分析及提升措施[J].环境工程, 2021, 39(12):25-30. [6] ROKSTAD M M, UGARELLI R M.Evaluating the role of deterioration models for condition assessment of sewers[J].Journal of Hydroinformatics, 2015, 17(5):789-804. [7] 冯杭华, 陈海涛, 施翔, 等.外来水量诊断法在污水管网预诊断中的应用[J].水利水运工程学报, 2022, 4:62-69. [8] OHLIN S A.Infiltration and inflow to wastewater sewer systems:a literature review on risk management[D].Gothenburg:Chalmers University of Technology, 2021. [9] GUO S, SHI X, LUO X J, et al.River water intrusion as a source of inflow into the sanitary sewer system[J].Water Science and Technology, 2020, 82(11):2472-2481. [10] ZHAO Z C, YIN H L, XU Z X, et al.Pin-pointing groundwater infiltration into urban sewers using chemical tracer in conjunction with physically based optimization model[J].Water Research, 2020, 175:115689. [11] 徐祖信, 王诗婧, 尹海龙, 等.基于节点水质监测的污水管网破损位置判定方法[J].中国环境科学, 2016, 36(12):3678-3685. [12] LUND N S V, KIRSTEIN J K, MADSEN H, et al.Feasibility of using smart meter water consumption data and in-sewer flow observations for sewer system analysis:a case study[J].Journal of Hydroinformatics, 2021, 23(4):795-812. [13] SONG R P, LIU X Y, ZHU B, et al.Modeling of water distribution system based on ten-minute accuracy remote smart demand meters[J].Water, 2022, 14(12):1934. [14] ZHANG Q Z, ZHENG F F, JIA Y Y, et al.Real-time foul sewer hydraulic modelling driven by water consumption data from water distribution systems[J].Water Res, 2021, 188:116544. [15] BEHZADIAN K, KAPELAN Z.Modelling metabolism based performance of an urban water system using WaterMet2[J].Resources, Conservation and Recycling, 2015, 99:84-99. [16] 中华人民共和国住房和城乡建设部.室外排水设计规范:GB 50014-2021[S].北京:中华人民共和国建设部, 2021. [17] 中华人民共和国住房和城乡建设部.城市排水工程规划规范:GB 50318-2017[S].北京:中华人民共和国建设部, 2017. [18] 何人杰, 吴林安, 董鲁燕, 等.污水管网在线流量监测技术在无锡市的应用[J].环境工程, 2011, 29(5):123-126.
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