大运河扬州段水质评价及预测OA
Water quality assessment and prediction of the Yangzhou Reach of the Grand Canal:a case of the Baoying Ship Lock Section
基于大运河扬州段宝应船闸断面水质监测数据,联合运用单因子指数法和综合水质标识指数法进行水质评价,构建高锰酸盐指数(CODMn)、氨氮(NH3-N)、总氮(TN)和总磷(TP)的综合水质标识指数(WQI)时间序列的ARIMA-LSTM模型,预测水质变化趋势.结果表明:断面水质TN长期偏高;WQI 相对平稳,以Ⅲ类水为主;ARIMA-LSTM模型对WQI 时间序列预测结果的NSE达0.88.研究结果以期为大运河沿程不同河段及不同尺度河流水质评价与预测提供基础数据.
Based on the water quality monitoring data of the Baoying Ship Lock Section of the Yangzhou Reach of the Grand Canal,the single factor index method and the comprehensive water quality identification index method were jointly used to evaluate the water quality.The ARIMA-LSTM model was developed for the comprehensive water quality identification index(WQI)time series of the four water quality factors—Permanganate Index(CODMn),Ammonia Nitrogen(NH3-N),Total Nitrogen(TN),and Total Phosphorus(TP)—to predict the temporal trend of water quality changes.The results indicate that the TN concentration in the section remains relatively high over the long term;WQI remained relatively stable,and the water is mainly Class III water.The NSE of WQI time series predicted by the ARIMA-LSTM model reached 0.88.The results of this study are intended to provide basic data for water quality assessment and prediction of different reaches and rivers at different scales along the Grand Canal.
赵洲雅;黄金柏;翁智浩
扬州大学 水利科学与工程学院,江苏 扬州 225009扬州大学 水利科学与工程学院,江苏 扬州 225009扬州大学 水利科学与工程学院,江苏 扬州 225009
资源环境
大运河单因子指数综合水质标识指数ARIMA-LSTM水质预测
The Grand Canalsingle-factor indexcomprehensive water quality identification indexARIMA-LSTMwater quality prediction
《江苏水利》 2026 (10)
9-13,5
中国水利水电科学研究院流域水循环模拟与调控国家重点实验室开放研究基金项目(IWHR-SKL-KF202309)
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