摘要
水质检测对水生态污染治理和环境保护有重要意义.以银川市阅海湖湿地为例,基于 Landsat-8 影像数据和取样水质参数实测值,首先建立了输入节点数为 8、卷积层为 2、归一化层、全连接层为 16-1 和 16-8-1、池化层和回归输出层均为 1 的卷积神经网络反演模型,对化学需氧量(COD)、氨氮(NH3-N)、总磷(TP)、总氮(TN)4 项水质参数浓度进行反演.其次,选用不同的卷积核、全连接层和优化器进行对比试验.结果表明,卷积模型 14 适用于COD等浓度值>3 mg/L的水质指标反演,决定系数R2 为 0.91;卷积模型 10 适用于氨氮、总磷、总氮等浓度值范围在 3 mg/L以内的水质指标反演,决定系数R2 分别为 0.95、0.81、0.9;卷积反演模型的反演精度(R2,RRMSE)达到(0.91,4.44),优于BP神经网络和传统的水质反演方法.最后,对水质指标COD进行了数据可视化处理,制作卷积神经网络预测COD浓度值热图,结果表明在空间上阅海湖湿地 COD污染程度中间水域高于南部和北部水域.
Abstract
Water quality testing is of great significance to water ecological pollution control and environmental protec-tion.Taking Yuehai Lake Wetland in Yinchuan City as the research object,based on the Landsat-8 image data and the measured values of sampling water quality parameters,a convolutional neural network inversion model was established which include 8 input nodes,2 convolutional layer,16-1 normalization layer,16-8-1 the fully connected layer,1 pooling layer and 1 regression output layer.The concentrations of four water quality parameters,such as chemical oxygen de-mand(COD),ammonia nitrogen(NH3-N),total phosphorus(TP)and total nitrogen(TN),are inverted.Secondly,different convolution kernels,fully connected layers and optimizers were selected for comparative experiments.The re-sults show that:the convolution model 14 is suitable for the inversion of water quality indexes with COD concentration values>3 mg/L,and the coefficient of determination R2 is 0.91;the convolution model 10 is suitable for the inversion of water quality indicators with concentration values of ammonia nitrogen,total phosphorus and total nitrogen within 3 mg/L,and the coefficients of determination R2 are 0.95,0.81,and 0.9,respectively;The inversion accuracy(R2,RRMSE)of the convolution inversion model reached(0.91,4.44),which was better than the BP neural network and the traditional water quality inversion method.Finally,the data of COD was visualized,and a heat map of COD concentration value predicted by convolutional neural network was produced,and the results show that the middle waters of COD pollu-tion in the wetlands of Yuehai Lake were higher than those in the south and north.
基金项目
国家自然科学基金项目(62365016)
2023年中央引导地方科技发展专项(宁夏)(2023FRD05034)
宁夏大学研究生创新项目(CXXM202221)
NETL
NSTL
万方数据