Abstract

Nitrate pollution in groundwater, which is an international problem, threatens human health and the environment. It could take decades for nitrate to transport in the groundwater system. When understanding the impacts of this nitrate legacy on water quality, the nitrate transport velocity (vN) in the unsaturated zone (USZ) is of great significance. Although some local USZ vN data measured or simulated are available, there has been no such a dataset at the global scale. Here, we present a Global-scale unsaturated zone Nitrate transport Velocity dataset (GNV) generated from a Nitrate Time Bomb (NTB) model using global permeability and porosity and global average annual groundwater recharge data. To evaluate GNV, a baseline dataset of USZ vN was created using locally measured data and global lithological data. The results show that 94.50% of GNV match the baseline USZ vN dataset. This dataset will largely contribute to research advancement in the nitrate legacy in the groundwater system, provide evidence for managing nitrate water pollution, and promote international and interdisciplinary collaborations.

Measurement(s)

Nitrate transport velocity in the unsaturated zone

Technology Type(s)

Numericial modelling including calibration using the measued/ data from literature

Factor Type(s)

Nitrate transport speed in the unsaturated zones

Sample Characteristic - Organism

None

Sample Characteristic - Environment

Groundwater pollution

Sample Characteristic - Location

Global unsaturated zones

Details

Title
Nitrate transport velocity data in the global unsaturated zones
Author
Yang, Congyu 1 ; Wang, Lei 2 ; Chen, Shengbo 1 ; Li, Yuanyin 3 ; Huang, Shuang 4 ; Zeng, Qinghong 1 ; Chen, Yanbing 1 

 Jilin University, College of Geo-exploration Science and Technology, Changchun, China (GRID:grid.64924.3d) (ISNI:0000 0004 1760 5735) 
 British Geological Survey, Keyworth, Nottingham, United Kingdom (GRID:grid.474329.f) (ISNI:0000 0001 1956 5915) 
 British Geological Survey, Keyworth, Nottingham, United Kingdom (GRID:grid.474329.f) (ISNI:0000 0001 1956 5915); Durham University, Department of Geography, Durham, United Kingdom (GRID:grid.8250.f) (ISNI:0000 0000 8700 0572) 
 MCC Smart City (Wuhan) Engineering Technology CO., Ltd, Wuhan, China (GRID:grid.8250.f) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2723654904
Copyright
© © British Geological Survey, UKRI 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.