A support vector regression model to predict nitrate-nitrogen isotopic composition using hydro-chemical variables

Yue Yang; Xu Shang; Zheng Chen; Kun Mei; Zhenfeng Wang; Randy A Dahlgren; Minghua Zhang; Xiaoliang Ji

doi:10.1016/j.jenvman.2021.112674

A support vector regression model to predict nitrate-nitrogen isotopic composition using hydro-chemical variables

J Environ Manage. 2021 Jul 15:290:112674. doi: 10.1016/j.jenvman.2021.112674. Epub 2021 Apr 23.

Authors

Yue Yang¹, Xu Shang², Zheng Chen², Kun Mei³, Zhenfeng Wang³, Randy A Dahlgren⁴, Minghua Zhang⁵, Xiaoliang Ji⁶

Affiliations

¹ Zhejiang Provincial Key Laboratory for Water Environment and Marine Biological Resources Protection, College of Life and Environmental Science, Wenzhou University, Wenzhou, 325035, China.
² Key Laboratory of Watershed Science and Health of Zhejiang Province, School of Public Health and Management, Wenzhou Medical University, Wenzhou, 325035, China; Southern Zhejiang Water Research Institute (iWATER), Wenzhou, 325035, China.
³ Key Laboratory of Watershed Science and Health of Zhejiang Province, School of Public Health and Management, Wenzhou Medical University, Wenzhou, 325035, China.
⁴ Department of Land, Air and Water Resources, University of California, Davis, CA, 95616, USA.
⁵ Key Laboratory of Watershed Science and Health of Zhejiang Province, School of Public Health and Management, Wenzhou Medical University, Wenzhou, 325035, China; Southern Zhejiang Water Research Institute (iWATER), Wenzhou, 325035, China; Department of Land, Air and Water Resources, University of California, Davis, CA, 95616, USA.
⁶ Key Laboratory of Watershed Science and Health of Zhejiang Province, School of Public Health and Management, Wenzhou Medical University, Wenzhou, 325035, China; Southern Zhejiang Water Research Institute (iWATER), Wenzhou, 325035, China. Electronic address: jixiao556677@wmu.edu.cn.

PMID: 33901819
DOI: 10.1016/j.jenvman.2021.112674

Abstract

Nitrate is a prominent pollutant in surface and groundwater bodies worldwide. Isotopes in nitrate provide a powerful approach for tracing nitrate sources and transformations in waters. Given that analytical techniques for determining isotopic compositions are generally time-consuming, laborious and expensive, alternative methods are warranted to supplement and enhance existing approaches. Hence, we developed a support vector regression (SVR) model and explored its feasibility to predict nitrogen isotopic composition of nitrate (δ¹⁵N-NO₃^-) in a rural-urban river system in Southeastern China. A total of 16 easily obtained hydro-chemical variables were measured in the wet season (September 2019) and dry season (January 2020) and used to develop the SVR prediction model. The grading method utilized ~75% (35) of the samples for model building while the remaining 11 samples assessed model performance. Principal component analysis (PCA) extracted 7 principal components for SVR model inputs as PCA reduces superfluous variables. We optimized tuning parameters in the SVR model using a grid search technique coupled with V-fold cross-validation. The optimized SVR model provided accurate δ¹⁵N-NO₃^- predictions with a determination coefficient (R²) of 0.88, Nash-Sutcliffe (NS) of 0.87, and mean square error (MSE) of 0.53‰ in the testing step, and performed much better than the corresponding multivariate linear regression model (R² = 0.60, NS = 0.58 and MSE = 1.76‰) and general regression neural network model (R² = 0.66, NS = 0.65 and MSE = 1.45‰). Overall, the SVR model provides a potential indirect method to predict environmental isotope values for water quality management that will complement and enhance the interpretation of direct measurements of δ¹⁵N-NO₃^-.

Keywords: Machine learning model; Nitrate pollution; Nitrate-nitrogen isotopic composition (δ(15)N–NO(3)(−)); Prediction; Principal component analysis (PCA); Support vector regression (SVR).

MeSH terms

China
Environmental Monitoring
Nitrates* / analysis
Nitrogen Isotopes / analysis
Water Pollutants, Chemical* / analysis

Substances

Nitrates
Nitrogen Isotopes
Water Pollutants, Chemical