Water quality safety risk assessment method for water supply network in mountainous cities

doi:10.16265/j.cnki.issn1003-3033.2023.08.2146

Abstract

Abstract:

In order to deal with the water pollution incidents of the water supply network in a timely and effective manner and reduce the harm caused by water pollution of the water supply network, taking the water quality safety of water supply network as the breakthrough point, the factors affecting the water quality of the water supply network were systematically analyzed, and the comprehensive evaluation system of water quality safety risk of urban water supply network nodes was constructed. FAHP was used to quantitatively calculate the influencing factors of hydraulic, water quality, pipeline and location, and the evaluation weight matrix W was obtained. Combined with the basic data of some water supply networks in a district of Chongqing, the Epanet and 1stOpt models were coupled to realize the quasi-dynamic simulation of the hydraulic and water quality conditions of the water supply network in this area, and then the water quality risk index of each node of the water supply network was obtained. The evaluation results show that the water quality risk indexes of 127 nodes in the water supply network of a district in Chongqing are 0.196, 0.286,…, 0.137 and 0.420, among which the low, medium and high-risk nodes account for 88.2%, 7.9% and 3.9% of the total nodes respectively. This method can consider the influence factors of hydraulic, water quality, pipeline and location at the same time, and quantitatively evaluate the water quality safety risk of each node in the water supply network, which can solve the problem that it is difficult to quantitatively evaluate the water quality safety of the current water supply network.

Key words: mountain city, water supply network, water quality safe, risk assessment, fuzzy analytic hierarchy process (FAHP)

WANG Ying, WANG Pu, WANG Zixuan, WANG Fengqing, WANG Liangchao, ZHANG Jin. Water quality safety risk assessment method for water supply network in mountainous cities[J]. China Safety Science Journal, 2023, 33(8): 205-211.

Figures/Tables 16

Fig.1

Tab.1

Tab.2

Tab.3

Tab.4

Comparison of pipeline influencing factors

管道因素B₁	管材 $B 1 1$	管龄 $B 1 2$	管径 $B 1 3$	W
管材 $B 1 1$	0.500	0.600	0.700	0.367
管龄 $B 1 2$	0.400	0.500	0.700	0.345
管径 $B 1 3$	0.300	0.300	0.500	0.288

Tab.4

Tab.5

Comparison of influencing factors of water quality

水质因素B₂	余氯B₂₁	浊度B₂₂	水龄 $B 2 3$	W
余氯B₂₁	0.500	0.500	0.700	0.356
浊度B₂₂	0.500	0.500	0.700	0.356
水龄B₂₃	0.300	0.300	0.500	0.288

Tab.5

Tab.6

Comparison of location influencing factors

位置因素B₃	分界线点B₃₁	重要节点 $B 3 2$	W
分界线点B₃₁	0.500	0.500	0.500
重要节点 $B 3 2$	0.500	0.500	0.500

Tab.6

Tab.7

Tab.8

Tab.9

Tab.10

Fig.2

Fig.3

Tab.11

Tab.12

Fig.4

References 16

[1]	韩林, 赵旭东, 陈志龙, 等. 地震灾害下城市供水网络韧性评估及优化研究[ J]. 中国安全科学学报, 2021, 31(2):135-142. doi: 10.16265/j.cnki.issn 1003-3033.2021.02.019
	HAN Lin, ZHAO Xudong, CHEN Zhilong. Seismic resilience assessment and optimization of urban water distribution network[J]. China Safety Science Journal, 2021, 31 (2): 135-142. doi: 10.16265/j.cnki.issn 1003-3033.2021.02.019
[2]	黄善钦. 山地城市供水管网常规水质监测点多目标优化选址研究[D]. 重庆: 重庆大学, 2020.
	HUANG Shanqin. Multi-objective optimal location of water quality monitoring stations for conventional water supply networks in mountain city[D]. Chongqing: Chongqing University, 2020.
[3]	LIOU C P, KROON J R. Modeling the propagation of waterborne substances in distribution networks[J]. Journal American Water Works Association, 1987, 79(11):54-58. doi: 10.1002/awwa.1987.79.issue-11
[4]	SADIQ R, KLEINER Y, RAJANI B. Water quality failures in distribution networks-risk analysis using fuzzy logic and evidential reasoning[J]. Risk Analysis, 2007, 27(5):1381-1394. pmid: 18076503
[5]	王丹宁. 城市给水管网水质因子宏观研究[D]. 哈尔滨: 哈尔滨工业大学, 2007.
	WANG Danning. The macroscopical research in water supply networks based on water quality gene[D]. Harbin: Harbin Institute of Technology, 2007.
[6]	杨德军, 张土乔, 郭帅, 等. 供水管网水质健康风险评价模型及实例[J]. 中国给水排水, 2009, 25(5):84-88.
	YANG Dejun, ZHANG Tuqiao, GUO Shuai, et al. Model and case of water quality health risk assessment for water distribution system[J]. China Water & Wastewater, 2009, 25 (5): 84-88.
[7]	CHANG Kui, GAO Jinliang, WU Wenyan, et al. Water quality comprehensive evaluation method for large water distribution network based on clustering analysis[J]. Journal of Hydroinformatics, 2011, 13(3):390-400. doi: 10.2166/hydro.2011.021
[8]	童祯恭, 方菊, 谌贻胜. 供水管网水质评价方法的探讨及其应用[J]. 环境科学与技术, 2011, 34(9):201-204.
	TONG Zhengong, FANG Ju, SHEN Yisheng. Water quality assessment method of water supply pipe[J]. Environmental Science and Technology, 2011, 34 (9): 201-204.
[9]	张珂欣. 济南市供水管网水质变化规律及评价[D]. 哈尔滨: 哈尔滨工业大学, 2018.
	ZHANG Kexin. Study on water quality change and evaluation of Ji'nan water supply network[D]. Harbin: Harbin Institute of Technology, 2018.
[10]	ALI M, CHANDU V, NANDINI V, et al. Evaluation of water quality in the households of Baniyas Region, Abu Dhabi using multivariate statistical approach[J]. Sustainable Water Resources Management, 2019, 5(4):1579-1592. doi: 10.1007/s40899-019-00320-7
[11]	NAYERI D, MOUSAVI S A, DARVISHI P, et al. Evaluation of water quality and stability in the drinking water distribution network: a case study in the Kermanshah city, Iran[J]. Desalination and Water Treatment, 2019, 166:180-185. doi: 10.5004/dwt
[12]	严煦世, 刘遂庆. 给水排水管网系统[M]. 北京: 中国建筑工业出版社, 2014:99-107.
[13]	Medical Research Council, Council for Scientific and Industrial Research.The effect of water supply, handling and usage on water quality in relation to health indices in developing communities[J]. Urbanisation and Health Newsletter, 1997, 32:48-52.
[14]	于志强, 赵新华, 程曙初. 基于EPANET与ArcEngine的供水管网建模软件[J]. 计算机工程与应用, 2009, 45(6):35-37.
	YU Zhiqiang, ZHAO Xinhua, CHENG Shuchu. Water distribution system simulation software based on EPANET and ArcEngine[J]. Computer Engineering and Application, 2009, 45 (6): 35-37.
[15]	ORMSBEE L E, WOOD D J. Explicit pipe network calibration[J]. Journal of WaterResources Planning & Management, 1985, 112(2):166-182.
[16]	唐少虎, 朱伟, 程光, 等. 暴雨内涝下城市道路交通系统安全韧性评估[J]. 中国安全科学学报, 2022, 32(7):143-150. doi: 10.16265/j.cnki.issn1003-3033.2022.07.1391
	TANG Shaohu, ZHU Wei, CHENG Guang. Safety resilience assessment of urban road traffic system under rainstorm waterlogging[J] China Safety Science Journal, 2022, 32 (7): 143-150. doi: 10.16265/j.cnki.issn1003-3033.2022.07.1391

定义	标度
绝对重要	0.9
非常重要	0.8
明显重要	0.7
稍微重要	0.6
同等重要	0.5
进行反比较	0.4、0.3、0.2、0.1

节点水质评分	要素1	要素2	要素3
要素1	0.5	x	y
要素2	1-x	0.5	z
要素3	1-y	1-z	0.5

节点水质风险综合评价	管道因素	水力因素	水质因素	位置因素	权重值
节点水质风险综合评价	0.243	0.268	0.247	0.242	权重值
B₁₁	0.367	—	—	—	0.089
B₁₂	0.345	—	—	—	0.084
B₁₃	0.288	—	—	—	0.070
Q	—	1.000	—	—	0.268
B₂₁	—	—	0.356	—	0.088
B₂₂	—	—	0.356	—	0.088
B₂₃	—	—	0.288	—	0.071
B₃₁	—	—	—	0.500	0.121
B₃₂	—	—	—	0.500	0.121
总计	1.000	1.000	1.000	1.000	1.000

供水片区基本数据	统计
供水片区面积/km²	41
水厂个数/座	2
供水规模/(万m³·d^-1)	10
水泵个数/台	11
供水分区数/个	3
DN200以上管道长度/km	85.5
供水人口数/万	40

节点	标高/m	需水量/(L·s^-1)
1	200.0	5.104
2	206.0	3.556
︙	︙	︙
126	281.0	3.753
127	266.0	6.776