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基于随机森林的引江济太入湖磷通量计算

陈年浩 陆昊 饶文昕 刘彤 钱新

四川环境2023,Vol.42Issue(6):1-7,7.
四川环境2023,Vol.42Issue(6):1-7,7.DOI:10.14034/j.cnki.schj.2023.06.001

基于随机森林的引江济太入湖磷通量计算

Phosphorus Flux Calculation of Yangtze River-Lake Taihu Water Diversion Based on Random Forest

陈年浩 1陆昊 1饶文昕 1刘彤 1钱新1

作者信息

  • 1. 南京大学环境学院污染控制与资源化研究国家重点实验室,南京 210023
  • 折叠

摘要

Abstract

Under the background that the risk of algal blooms is still high in Lake Taihu and the planned water diversion volume increases in the future,it is of great significance to identify the phosphorus flux of different forms of Yangtze River-Lake Taihu water diversion.Based on field environmental monitoring data from 17 sampling sites along Wangyu River and Lake Taihu in 2021,the random forest(RF)method was used to build a simulation model of dissolved total phosphorus(DTP)concentration and estimate the dissolved and particulate phosphorus flux into Lake Taihu.The results showed that the R2,RMSE and NSE of RF model were 0.690,0.0110 and 0.651,respectively,which had good fitting and generalization performance and could be applied to retrieve historical DTP concentration.Total phosphorus,wind direction,turbidity,water temperature,pH and dissolved oxygen were important predictors of the RF model.From 2010 to 2021,the DTP flux of Wangyu River into Lake Taihu was 6.7-83.7 t,with an average annual flux of 34.6 t,accounting for 42.2 to 66.6%of TP flux.Therefore,the influence of dissolved phosphorus input caused by Yangtze River-Lake Taihu water diversion on phosphorus cycle and water environment of Gonghu Bay needs to be paid more attention.This study results can provide key data for the analysis of the influence,and provide technical support for the optimization of water diversion scheme.

关键词

引江济太/望虞河/磷形态/磷通量/随机森林

Key words

Yangtze River-Lake Taihu water diversion/Wangyu river/phosphorus form/phosphorus flux/random forest

分类

资源环境

引用本文复制引用

陈年浩,陆昊,饶文昕,刘彤,钱新..基于随机森林的引江济太入湖磷通量计算[J].四川环境,2023,42(6):1-7,7.

基金项目

江苏省自然科学基金项目(BK20211155) (BK20211155)

国家自然科学基金项目(41907388). (41907388)

四川环境

OACSTPCD

1001-3644

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