Electrical conductivity and dissolved oxygen as predictors of nitrate concentrations in shallow groundwater in Erhai Lake region
文献类型： 外文期刊
作者： Zhang, Dan 1 ; Wang, Panlei 1 ; Cui, Rongyang 3 ; Yang, Heng 1 ; Li, Guifang 1 ; Chen, Anqiang 2 ; Wang, Hongyuan 4 ;
作者机构： 1.Yunnan Agr Univ, Coll Resource & Environm, Kunming 650201, Yunnan, Peoples R China
2.Yunnan Acad Agr Sci, Agr Environm & Resources Inst, Kunming 650201, Yunnan, Peoples R China
3.Chinese Acad Sci & Minist Water Resources, Inst Mt Hazards & Environm, Chinese Acad Sci, Key Lab Mt Surface Proc & Ecol Regulat, Chengdu 610041, Peoples R China
4.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Minist Agr & Rural Affairs, Key Lab Nonpoint Source Pollut Control, Beijing 100081, Peoples R China
关键词： Nitrogen concentration; Predictive model; Electrical conductivity; Dissolved oxygen; Shallow groundwater
期刊名称：SCIENCE OF THE TOTAL ENVIRONMENT （ 影响因子：10.753； 五年影响因子：10.237 ）
ISSN： 0048-9697
年卷期： 2022 年 802 卷
页码：
收录情况： SCI
摘要： Elevated nitrogen (N) concentration in shallow groundwater is becoming increasingly problematic, putting water resources under pressure. For more effective management of such a resource, more precise predictors of N level in groundwater using smart monitoring networks are needed. However, external factors such as land use type, rainfall, and N loads from multiple sources (residential and agricultural) make it difficult to accurately predict the spatial and temporal variations of N concentration. In order to identify the key factors affecting spatial and temporal N concentration in shallow groundwater and develop a predictive model, 635 groundwater samples from drinking wells in residential areas and agricultural wells in croplands of a typical agricultural watershed in the Erhai Lake Basin, southwest China, in the period from 2018 to 2020, were collected and analyzed. The results showed that the type of land use and seasonal variations significantly affected the N forms and their concentrations in the shallow groundwater, as the ratios of ON and NO3--N to TN were 30%-39% and 52%-59% for the two land uses and 25%-44% and 46%-66% for seasonal changes. Their variations were reflected by electrical conductivity (EC) and redox environment. EC and dissolved oxygen (DO) had a positive non-linear relationship with the concentrations of total nitrogen (TN) and nitrate (NO3--N). The fitted non-linear quantitative models were established separately to predict TN and NO3--N concentrations in groundwater using easily available indictors (EC and DO). The high accuracy and performance of the models were investigated and approved by rRMSE, MAE, and 1:1 line. These findings can provide technical support for the rapid prediction and evaluation of N pollution in shallow groundwater through easily available indicators. (C) 2021 Elsevier B.V. All rights reserved.
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