Nitrate removal mechanism in riparian groundwater in an intensified agricultural catchment-Reference-Cited by-同舟云学术

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Nitrate removal mechanism in riparian groundwater in an intensified agricultural catchment

Published:2023-04 Issue: Volume:280 Page:108223
ISSN:0378-3774
Container-title:Agricultural Water Management
language:en
Short-container-title:Agricultural Water Management

Author:

Xie Zheyu,Zhang Yujing,Zhang Zhenyu,Huang Jinliang

Funder

China Scholarship Council

Xiamen University

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Earth-Surface Processes,Soil Science,Water Science and Technology,Agronomy and Crop Science

Reference49 articles.

1. Analysis of Kansas water well policies and proposal of nonpublic household water well recommendations;Ablah;Environ. Health Perspect.,2020

2. Nitrous oxide emission from denitrification in stream and river networks;Beaulieu;Proc. Natl. Acad. Sci. USA,2011

3. Meiofauna increases bacterial denitrification in marine sediments;Bonaglia;Nat. Commun.,2014

4. Nitrate reduction in groundwater and isotopic investigation of denitrification in integrated tree-grass riparian buffers in Taihu Lake watershed, eastern China;Bu;J. Soil Water Conserv.,2017

5. Identifying the main crops and key factors determining the carbon footprint of crop production in China, 2001–2018;Chen;Resour., Conserv. Recycl.,2021

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1. How much nutrient reaches a stream: Insights from a hybrid model and implications for watershed nitrogen export and removal;Journal of Environmental Management;2024-06

2. Seasonal nitrate variations, risks, and sources in groundwater under different land use types in a thousand-year-cultivated region, northwestern China;Environmental Research;2024-06

3. Surface Water (SW) and Shallow Groundwater (SGW) Nutrient Concentrations in Riparian Wetlands of a Mixed Land-Use Catchment;Land;2024-03-23

4. Nutrient removal performance from agricultural drainage by strengthening ecological ditches in hilly areas;Agricultural Water Management;2024-02

5. A spatially explicit interpretable machine-learning method to track dissolved inorganic nitrogen pollution in a coastal watershed;Ecological Indicators;2024-01

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