https://dx.doi.org/10.1016/j.scitotenv.2018.06.048">
 

Title

Influences of agricultural land use composition and distribution on nitrogen export from a subtropical watershed in China

Abstract

Despite the significant impacts of agricultural land on nonpoint source (NPS) nitrogen (N) pollution, little is known about the influence of the distribution and composition of different agricultural land uses on N export at the watershed scale. We used the Soil and Water Assessment Tool (SWAT) to quantify how agricultural distribution (i.e., the spatial distributions of agricultural land uses) and composition (i.e., the relative percentages of different types of agricultural land uses) influenced N export from a Chinese subtropical watershed, accounting for aquatic N retention by river networks. Nitrogen sources displayed high spatial variability, with 40.7% of the total N (TN) export from the watershed as a whole derived from several subwatersheds that accounted for only 18% of the watershed area. These subwatersheds were all located close to the watershed mouth. Agricultural composition strongly affected inputs to the river network. The percentages of dry agricultural land and rice paddy fields, and the number of cattle together explained 70.5% of the variability of the TN input to the river network among different subwatersheds. Total N loading to the river network was positively correlated with the percentage of dry land in total land areas and the number of cattle within subwatersheds, but negatively with the proportion of paddy fields. Distribution of agricultural land uses also affected N export at the mouth of the watershed. Moreover, N retention in the river network increased with increasing N transport distance from source subwatershed to the watershed mouth. Results provide important information to support improved planning of agricultural land uses at the watershed scale that reduces NPS nutrient pollution.

Publication Date

11-15-2018

Journal Title

Science of The Total Environment

Publisher

Elsevier

Digital Object Identifier (DOI)

https://dx.doi.org/10.1016/j.scitotenv.2018.06.048

Document Type

Article

Rights

© 2018 Elsevier B.V. All rights reserved.

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