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2003~2020年黄河内蒙古段干流水质演变趋势
摘要点击 419  全文点击 97  投稿时间:2023-05-08  修订日期:2023-09-30
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中文关键词  黄河流域内蒙古段  水质评价  时空变化  综合水质标识指数(WQI)  水质预测
英文关键词  Inner Mongolia section of the Yellow River Basin  water quality assessment  spatial and temporal variation  water quality identification index(WQI)  water quality prediction
作者单位E-mail
侯元松 内蒙古自治区环境监测总站, 呼和浩特 010011 332476821@qq.com 
谢志磊 内蒙古自治区环境监测总站, 呼和浩特 010011
内蒙古大学生态与环境学院, 呼和浩特 010021 
xiezhilei1987@163.com 
田永莉 内蒙古自治区环境监测总站, 呼和浩特 010011  
姜家伟 内蒙古大学生态与环境学院, 呼和浩特 010021  
梁运青 内蒙古大学生态与环境学院, 呼和浩特 010021  
王倩 内蒙古自治区环境监测总站, 呼和浩特 010011  
房强 内蒙古自治区环境监测总站, 呼和浩特 010011  
许韬 内蒙古环保投资在线监控有限公司, 呼和浩特 010010  
张英芳 内蒙古自治区环境监测总站, 呼和浩特 010011  
李浩 内蒙古自治区环境监测总站, 呼和浩特 010011  
策力汗 锡林郭勒盟苏尼特右旗生态环境监测站, 锡林浩特 011200  
中文摘要
      为全面了解黄河流域内蒙古段近年来的水环境质量状况及其变化趋势,基于流域内5个监测断面2003~2020年的水质数据,使用主成分分析、聚类分析和长短时记忆模型等多源数据分析方法,结合改进的综合水质标识指数,探究了黄河流域水质的时空变化特征. 结果表明,流域水质状况整体向好并稳定. 时间特征方面,汛期和非汛期水质的主要影响因素存在显著差异,主要与农业灌溉用水和汛期水量增大有关;空间特征方面,可将5个监测断面归为3类,汛期的主要影响因素具有时间特征,而非汛期3类监测断面的水质差异主要由其周边城市的用水结构决定. LSTM模型的预测值变化趋势与真实值拟合效果良好,可对黄河内蒙古段的水质指标进行有效的预测评价,可为黄河干流各河段水质达标控制与管理提供科学依据.
英文摘要
      The aim of this study was to comprehensively understand the water environment quality status and its change trend in the Inner Mongolia section of the Yellow River Basin. To analyze the water quality in recent years,the water quality data in the Yellow River basin from 2003 to 2020 were firstly collected from five typical monitoring stations.Various data analysis methods, including principal component analysis, cluster analysis, and a long short-term memory model, were used along with an improved comprehensive water quality identification index to explore the spatiotemporal characteristics of water quality in the Yellow River Basin. The results showed that the overall water quality in the basin has improved and stabilized over time. In terms of temporal variation, there was a distinction between the wet season and dry season, with a better status observed during the wet season due to increased agricultural irrigation and higher water volume. Spatially, the five monitoring sections could be divided into three categories based on strong natural factors that maintained their temporal characteristics during the wet season; however, significant differences were observed during the dry season due to urban water usage patterns. Analysis using LSTM models revealed that ammonia nitrogen will continue to decline and have a decreasing impact on the comprehensive water quality. These findings provide valuable insights for the comprehensive management of water quality in Inner Mongolia's Yellow River Basin.

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