Interpretable data-driven chemometric approach for predicting non-optically active water quality parameters using ultraviolet-visible-near infrared absorption spectroscopy and physical-chemical measurements
文献类型：期刊论文
| 作者 | Zhao, Yubo3,4; Zhang, Zhou2; Hu, Bingliang4; Liu, Jiacheng4; Wang, Xueji4; Zou, Lei1; Yu, Tao4 |
| 刊名 | SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
 |
| 出版日期 | 2025-04-15 |
| 卷号 | 331页码:125768 |
| 关键词 | Non-optically active water quality parameters Ultraviolet-visible-near infrared absorption spectroscopy Physical-chemical measurements Yangtze River Basin eXtreme Gradient Boosting SHapley Additive exPlanations |
| ISSN号 | 1386-1425 |
| DOI | 10.1016/j.saa.2025.125768 |
| 产权排序 | 4 |
| 文献子类 | Article |
| 英文摘要 | Non-optically active water quality parameters (NAWQPs) are essential for surface water quality assessments, although automated monitoring methods are time-consuming, include labor-intensive chemical pretreatment, and pose challenges for high spatiotemporal resolution monitoring. Advancements in spectroscopic techniques and machine learning may address these issues. We integrated ultraviolet-visible-near infrared absorption spectroscopy with physical-chemical measurements to predict total nitrogen (TN), dissolved oxygen (DO), and total phosphorus (TP) in the Yangtze River Basin, China. By combining the eXtreme Gradient Boosting algorithm with OPTUNA hyperparameter optimization and the SHapley Additive exPlanations interpretability framework, we developed an algorithm that yielded Nash-Sutcliffe efficiency values of 0.944, 0.934, and 0.835, and mean absolute percentage errors of 7.8 %, 8.2 %, and 7.7 % for TN, DO, and TP, respectively. The UV spectrum was significant in the NAWQPs prediction tasks. Our study offers a novel approach to water quality monitoring and resource management in complex aquatic environments. |
| URL标识 | 查看原文 |
| WOS关键词 | QUANTIFICATION |
| WOS研究方向 | Spectroscopy |
| 语种 | 英语 |
| WOS记录号 | WOS:001422356400001 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/212277]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 通讯作者 | Yu, Tao |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 2.Univ Wisconsin Madison, Biol Syst Engn, Madison, WI 53706 USA; 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 4.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Key Lab Spectral Imaging Technol, Xian 710119, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Zhao, Yubo,Zhang, Zhou,Hu, Bingliang,et al. Interpretable data-driven chemometric approach for predicting non-optically active water quality parameters using ultraviolet-visible-near infrared absorption spectroscopy and physical-chemical measurements[J]. SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY,2025,331:125768. |
| APA | Zhao, Yubo.,Zhang, Zhou.,Hu, Bingliang.,Liu, Jiacheng.,Wang, Xueji.,...&Yu, Tao.(2025).Interpretable data-driven chemometric approach for predicting non-optically active water quality parameters using ultraviolet-visible-near infrared absorption spectroscopy and physical-chemical measurements.SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY,331,125768. |
| MLA | Zhao, Yubo,et al."Interpretable data-driven chemometric approach for predicting non-optically active water quality parameters using ultraviolet-visible-near infrared absorption spectroscopy and physical-chemical measurements".SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 331(2025):125768. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。