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宁夏引黄灌区排水沟水环境质量及其影响因素
引用本文:郑灿,杨子超,邱小琮,尹亮,李延林.宁夏引黄灌区排水沟水环境质量及其影响因素[J].水土保持通报,2018,38(6):74-79,87.
作者姓名:郑灿  杨子超  邱小琮  尹亮  李延林
作者单位:宁夏大学 土木与水利工程学院, 宁夏 银川 750021,宁夏大学 土木与水利工程学院, 宁夏 银川 750021,宁夏大学 生命科学学院, 宁夏 银川 750021,宁夏大学 土木与水利工程学院, 宁夏 银川 750021,宁夏大学 土木与水利工程学院, 宁夏 银川 750021
基金项目:宁夏高等学校一流学科建设(水利工程)项目(NXYLXK2017A03)
摘    要:目的]探明宁夏引黄灌区排水沟水环境质量及其影响因素,旨在为排水沟水体污染综合整治提供一定的理论依据。方法]搜集2009—2015年排水沟水环境因子指标和以地级市为单元的社会经济指标数据,选取高锰酸盐指数、化学需氧量、氨氮、总磷、生化需氧量、挥发酚、氟化物、氰化物、硫化物作为水质综合污染指数的评价因子,采用相关分析法和灰关联法分析研究社会经济指标对排水沟水质的影响程度。结果]南干沟水质呈现逐年好转趋势,银新干沟水质和清水沟水质急剧恶化,其他排水沟的综合污染指数变化趋势较平稳,且水质总体状况较好;排水沟水质与社会经济指标的相关性和关联度都较高:中干沟与化肥使用量相关系数高达0.998,南干沟与工业废水排放总量相关系数高达0.983;永二干沟与农业耗水量的关联度高达0.793 41,南干沟与工业废水排放总量的关联度高达0.755 69。结论]排水沟的水质变化趋势受农业面源污染和工业废水的影响较大;以地级市为单位,综合污染指数与社会经济指标的相关性大小依次为吴忠市、银川市、中卫市、石嘴山市;相关分析与灰关联分析结果有较好的一致性,且运用二者结合分析了影响排水沟的最主要影响因子;总体上,农业生产对银川市和石嘴山市排水沟水质影响较大,工业生产对吴忠市和中卫市排水沟的影响较大,且农业生产导致的农业面源污染比工业生产产生的工业废水对排水沟水质状况影响程度大。

关 键 词:综合污染指数  社会经济指标  灰关联度  引黄灌区
收稿时间:2018/5/26 0:00:00
修稿时间:2018/7/11 0:00:00

Water Environmental Quality of Drainage Ditches and Their Controls in Ningxia Irrigation Area
ZHENG Can,YANG Zichao,QIU Xiaocong,YIN Liang and LI Yanlin.Water Environmental Quality of Drainage Ditches and Their Controls in Ningxia Irrigation Area[J].Bulletin of Soil and Water Conservation,2018,38(6):74-79,87.
Authors:ZHENG Can  YANG Zichao  QIU Xiaocong  YIN Liang and LI Yanlin
Institution:School of Civil and Hydraulic Engineering, Ningxia University, Yinchuan, Ningxia 750021, China,School of Civil and Hydraulic Engineering, Ningxia University, Yinchuan, Ningxia 750021, China,College of Life Sciences, Ningxia University, Yinchuan, Ningxia 750021, China,School of Civil and Hydraulic Engineering, Ningxia University, Yinchuan, Ningxia 750021, China and School of Civil and Hydraulic Engineering, Ningxia University, Yinchuan, Ningxia 750021, China
Abstract:Objective] The water environment quality and its controls in drainage ditches from Ningxia Irrigation area were observed in order to provide theoretial reference for the comprehensive control of water pollution of drainage ditches.Methods] We collected water environmental data of drainage ditch during 2009-2015 and prefectural socio-economic data. The permanganate index, chemical oxygen demand, ammonia nitrogen, total phosphorus, biochemical oxygen demand, volatile phenols, fluoride, cyanide, and sulfides were selected to evaluate the comprehensive water pollution. Correlation analysis and grey correlation analysis were used to analyze the impact of socio-economic indexes on the water quality.Results] The water quality of Nangan ditch was gradually improved, while Yinxingan and Qingshui ditchs deteriorated rapidly, and others remained stable and sound. The water quality was highly related to socio-economic indexes. The correlation coefficient(r) was 0.998 for chemical fertilizers utilization with water quality in Zhonggan ditch, and 0.983 for total industrial effluent discharge in Nangan ditch; the correlation between Yongergan ditch and agricultural water consumption was as high as 0.793 41, the correlation degree between Nangan ditch and discharges of total industrial wastewater discharge was as high as 0.75 569, respectively.Conclusion] The water quality of drainage ditches was greatly affected by agricultural non-point source pollution and industrial waste water. On the prefectural level, the order of correlations between the comprehensive pollution and socio-economic indexes was Wuzhong City, Yinchuan City, Zhongwei City and Shizuishan City. There is a good consistency between the results of correlation analysis and grey correlation analysis. The combination of the two analyses was performed to exploring the main controls for water quality. Generally, agricultural production was the dominant driver for water pollution in Yinchuan City and Shizuishan City, while industrial production was dominant in Wuzhong City and Zhongwei City. Moreover, agricultural non-point source pollution caused by agricultural production has a greater adverse effect on water quality than industrial wastewater produced by industrial production.
Keywords:comprehensive pollution index  socio-economic indicators  grey correlation degree  Yellow River irrigation area
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