摘要
以湘中矿区典型重金属镉超标水稻田为研究对象进行原位实验,分析稻田淹水期土壤重金属镉向水相析出特征。基于统计及遗传编程方法的EPR数据挖掘技术,建立镉析出质量浓度与温度影响因子关系方程。结果表明,温度是镉向水相析出质量浓度的重要影响因子,相比传统的统计方法建立的线性及非线性方程,EPR具有一定的预测优势。稻田淹水期水温达到30℃时,溶解态镉质量浓度接近生活饮用水标准的限值,是地表饮用水水质安全的潜在威胁。
Typical Cadmium contaminated paddy field was selected for a case to reveal Cd transportation law from soil to waterlogged paddy field water, in central Hunan mining area. Cd release dynamic characteristics in waterlogged paddy soil under field conditions were analyzed. Evolutionary Polynomial Regression (EPR) was used to build the model between Cd concentration in waterlogged paddy field water and temperature, and EPR combined the power of evolutionary algorithm with traditional numerical regression. Results showed that water temperature of paddy field had the sensitive impact on Cd concentration, and model fitted by EPR was more effective prediction than traditional numerical regression models. Concentration of dissolved Cd was close to the drinking water standard limit value when paddy field water temperature was near 30℃, which was a serious threat to local drinking water safety.
出处
《灌溉排水学报》
CSCD
北大核心
2013年第2期119-121,共3页
Journal of Irrigation and Drainage
基金
湖南农业大学校青年基金项目(62020111031)
国家自然科学基金项目(31100329)
关键词
数据挖掘
湘中矿区
稻田
重金属
data driven teehnique
central mining area Hunan provinee
paddy soil
heavy metal