4.7 Article

Characterizing the impacts of land use on nitrate load and water yield in an agricultural watershed in Atlantic Canada

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 729, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.scitotenv.2020.138793

关键词

Land use; Nitrate load; Water yield; SWAT; Random Forest

资金

  1. Agriculture and Agri-Food Canada project Reducing sediment, Nand P loading fromarable cropping systems to receivingwaters in eastern Canada [J-001270]
  2. Agriculture and Agri-Food Canada project Using Living Laboratory approach to develop and transfer innovative soil and water quality BMPS in Prince Edward Island [J-002269]
  3. Chinese Scholarship Council

向作者/读者索取更多资源

Excessive nitrate loading from agricultural non-point source is threatening the health of receiving water bodies at the global scale. Quantifying the drivers/sources of water and nitrate flux in watersheds and relating them to spatial and temporal land uses is essential for developing effective mitigation strategies. This study investigated the impact of land use on water yield and nitrate loading to surface water in a typical agricultural watershed in Prince Edward Island (PEI), Canada. We used historical streamflow and water quality records to calibrate the comprehensive hydrological model Soil and Water Assessment Tool (SWAT), which was setup with detailed annual land use records. The SWAT model performed well in predicting both daily streamflow and nitrate load. Land use demonstrated little impact on water yield but affected nitrate load significantly. Annual nitrate load ranged from 5.6 to 44.4 kg N ha(-1) yr(-1) for forest and soybean, respectively. Potato rotated land contributed 84.5% of annual nitrate load to the watershed. Source of water yield demonstrated high variability between the growing season and non-growing season. About 90% of water yield was contributed by groundwater during growing season, while runoff contributed over 60% of water yield during the non-growing season. Groundwater was the dominant source of nitrate loading for both seasons. The watershed estuary faced the highest threats from subbasins in the south western area due to the high nitrate load and proximity to the watershed outlet. Results by the machine learning algorithm random Forest analysis indicated that the climatic variables of temperature and precipitation were the top two factors affecting water yield, with a combined relative importance of 61%. Land use was the dominant factor affecting nitrate load, the relative importance of land use alone was similar to 50%. The results of this study provided critical insights for watershed management in Atlantic Canada. (C) 2020 Elsevier B.V. All rights reserved.

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