Chunli Su , Weili Ge , Xianjun Xie , Zhihao Guo , Zhaohui Luo , Yiqun Gan , Ziyi Xiao , Yanhui Gao , Yanmei Yang
{"title":"Prediction and controlling factors of high-fluoride groundwater in the Yellow River Basin based on machine learning model","authors":"Chunli Su , Weili Ge , Xianjun Xie , Zhihao Guo , Zhaohui Luo , Yiqun Gan , Ziyi Xiao , Yanhui Gao , Yanmei Yang","doi":"10.1016/j.gsd.2025.101458","DOIUrl":null,"url":null,"abstract":"<div><div>Long-term consumption of high-fluoride water (F > 1.5 mg/L) has significant negative effects on human health. In the Yellow River Basin of northern China, fluorosis resulting from geogenic groundwater fluoride contamination has been observed in several basins. In this study, the machine learning algorithm regression modeling was employed to predict the distribution of high-fluoride groundwater and potential population at risk using 30337 groundwater samples and 40 relevant environmental factors, with random forest (RF) was identified as the optimal algorithm. The model incorporated various environmental factors, including hydrogeology, climate, soil, topography, and human activities and the model performed well, with the value of AUC of 0.86. The climatic variables were identified as the primary factors influencing the model based on the ranking of their importance. The probability distribution map with a resolution of 250 m drawn from the modelling results shows that high-fluoride groundwater is mainly distributed within the basins, Loess Plateau, the front edge and the southern part of the Yellow-Huai-Hai River Plain (also known as North China Plain). The climate plays a vital role in regulating the distribution patterns of high-fluoride groundwater. Based on different probability cut-off values, it is estimated that approximately 7.307 and 8.899 million people in the study area may be at risk of direct consumption of fluoride-contaminated groundwater. High-fluoride groundwater primarily occurs in shallow pore aquifers of alluvial plains. Fine-grained sediments with high clay content and high levels of cations with exchangeable sites favor the enrichment of fluoride in groundwater. Alluvial and alkaline soils exhibit significant impacts on the enrichment of fluoride. Significant temperature differences and uneven precipitation are the main climatic factors affecting fluoride enrichment in groundwater. This study helps to enhance the understanding of the spatial differentiation and driving mechanism of high-fluoride groundwater, and provides a scientific basis for preventing endemic fluorosis and ensuring water supply security.</div></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":"30 ","pages":"Article 101458"},"PeriodicalIF":4.9000,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Groundwater for Sustainable Development","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352801X25000554","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Long-term consumption of high-fluoride water (F > 1.5 mg/L) has significant negative effects on human health. In the Yellow River Basin of northern China, fluorosis resulting from geogenic groundwater fluoride contamination has been observed in several basins. In this study, the machine learning algorithm regression modeling was employed to predict the distribution of high-fluoride groundwater and potential population at risk using 30337 groundwater samples and 40 relevant environmental factors, with random forest (RF) was identified as the optimal algorithm. The model incorporated various environmental factors, including hydrogeology, climate, soil, topography, and human activities and the model performed well, with the value of AUC of 0.86. The climatic variables were identified as the primary factors influencing the model based on the ranking of their importance. The probability distribution map with a resolution of 250 m drawn from the modelling results shows that high-fluoride groundwater is mainly distributed within the basins, Loess Plateau, the front edge and the southern part of the Yellow-Huai-Hai River Plain (also known as North China Plain). The climate plays a vital role in regulating the distribution patterns of high-fluoride groundwater. Based on different probability cut-off values, it is estimated that approximately 7.307 and 8.899 million people in the study area may be at risk of direct consumption of fluoride-contaminated groundwater. High-fluoride groundwater primarily occurs in shallow pore aquifers of alluvial plains. Fine-grained sediments with high clay content and high levels of cations with exchangeable sites favor the enrichment of fluoride in groundwater. Alluvial and alkaline soils exhibit significant impacts on the enrichment of fluoride. Significant temperature differences and uneven precipitation are the main climatic factors affecting fluoride enrichment in groundwater. This study helps to enhance the understanding of the spatial differentiation and driving mechanism of high-fluoride groundwater, and provides a scientific basis for preventing endemic fluorosis and ensuring water supply security.
期刊介绍:
Groundwater for Sustainable Development is directed to different stakeholders and professionals, including government and non-governmental organizations, international funding agencies, universities, public water institutions, public health and other public/private sector professionals, and other relevant institutions. It is aimed at professionals, academics and students in the fields of disciplines such as: groundwater and its connection to surface hydrology and environment, soil sciences, engineering, ecology, microbiology, atmospheric sciences, analytical chemistry, hydro-engineering, water technology, environmental ethics, economics, public health, policy, as well as social sciences, legal disciplines, or any other area connected with water issues. The objectives of this journal are to facilitate: • The improvement of effective and sustainable management of water resources across the globe. • The improvement of human access to groundwater resources in adequate quantity and good quality. • The meeting of the increasing demand for drinking and irrigation water needed for food security to contribute to a social and economically sound human development. • The creation of a global inter- and multidisciplinary platform and forum to improve our understanding of groundwater resources and to advocate their effective and sustainable management and protection against contamination. • Interdisciplinary information exchange and to stimulate scientific research in the fields of groundwater related sciences and social and health sciences required to achieve the United Nations Millennium Development Goals for sustainable development.