基于多种评价法的磨盘山水库水质评价  

Water Quality Assessment of Mopanshan Reservoir Based on Multiple Evaluation Methods

作　　者：陈振宙 杨旭[1] 杨鹏辉 许文博 张弛 Chen Zhenzhou;Yang Xu;Yang Penghui;Xu Wenbo;Zhang Chi(School of Water Conservancy and Electric Power,Heilongjiang University,Harbin 150080,Heilongjiang;Harbin Mopanshan Reservoir Management and Protection Center,Harbin 150080,Heilongjiang)

机构地区：[1]黑龙江大学水利电力学院,黑龙江哈尔滨150080 [2]哈尔滨市磨盘山水库管护中心,黑龙江哈尔滨150080

出　　处：《陕西水利》2024年第3期101-103,107,共4页Shaanxi Water Resources

基　　金：黑龙江省省属高等学校基本科研业务费(2020-KYYWF-1020)。

摘　　要：磨盘山水库作为哈尔滨市的主要水源,对其进行的水质评价对于保障居民饮用水安全具有重大意义。选取2022年12个月的溶解氧(DO)、氨氮(NH_(3)-N)、化学需氧量(COD)、总磷(TP)、总氮(TN)5个指标,分别采用主成分分析法和RBF神经网络评价法对磨盘山水库水质进行评价。结果表明:磨盘山水库水质为Ⅱ级,符合当地检测结果。主成分分析法可以真实客观地分析当地水库水质,为水库改进完善提供一定参考。RBF神经网络只需要按照水质的各个分级标准传造出所需的训练样本,用训练完善的计算模型进行水质评价比较容易。该方法简单,具有很好的实用性。此研究可用作其他地区参考。As the main water source of Harbin City,Mopanshan Reservoir's water quality evaluation is of great significance to ensure the safety of residents'drinking water.Five indicators of dissolved oxygen(DO),ammonia nitrogen(NH_(3)-N),chemical oxygen demand(COD),total phosphorus(TP),and total nitrogen(TN)were selected for 12 months in 2022,and the principal component analysis method and The RBF neural network evaluation method was used to evaluate the water quality of Mopanshan Reservoir.The results show that the water quality of Mopanshan Reservoir is Grade Il,which is in line with local testing results.The principal component analysis method can truly and objectively analyze the water quality of local reservoirs and provide certain reference for reservoir improvement and improvement.The RBF neural network only needs to generate the required training samples according to each water quality classification standard,and it is easier to use a well-trained computing model to evaluate water quality.The method is simple and has good practicability.This study can be used as a reference for other regions.

关 键 词：水质评价 主成分分析 RBF神经网络 磨盘山水库 

分 类 号：X824[环境科学与工程—环境工程]