Prediction of ammonium nitrogen pollution in surface water in small watersheds of Yinhai,Beihai City based on machine learning models
The issue of eutrophication in surface water of small watersheds(Fengjiajiang River,Sanhekou River,and Fucheng River)in Yinhai,Beihai City,is of grave concern.However,there has been limited re-search on the prediction of surface water ammonium nitrogen(NH4+-N)levels.In this study,three machine learning models,namely multiple linear regression,support vector machine and random forest,were em-ployed to predict the spatial distribution of NH4+-N in small watersheds of Yinhai,Beihai City,using com-prehensive water quality analysis data.The results indicate that in multiple experiments,the random forest model consistently exhibited the lowest median root mean square error and the best fitting performance,showing a high degree of consistency with observed NH4+-N distribution in surface water.Based on the re-sults,areas with NH4+-N concentrations exceeding the Class V water quality standard limit of 2 mg/Lare mainly in Fengjiajiang River.Furthermore,PO43-,HCO3-,and total alkalinity are identified as the most sig-nificant indicator factors contributing to the enrichment of NH4+-N in surface water,highlighting the unde-niable influence of human activities on surface water pollution.
surface waterammonium nitrogen(NH4-N)pollutionmachine learning modelBeihai City