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Title: A Modeling Study of Direct and Indirect N 2O Emissions From a Representative Catchment in the U.S. Corn Belt

Abstract

Indirect nitrous oxide (N 2O) emissions from drainage ditches and headwater streams are poorly constrained. Few studies have monitored stream N 2O emissions and fewer modeling studies have been conducted to simulate stream N 2O emissions. Here, we determined direct and indirect N 2O emission modules and a corresponding calibration module for use in the Soil and Water Assessment Tool (SWAT) model, and implemented the expanded SWAT model (termed SWAT-N 2O) to a representative fourth-stream-order catchment (210 km 2) and six first-order stream catchments (0.22–1.83 km 2) in southeastern Minnesota. We simulated the spatial and temporal fluctuations of the indirect emissions from streams, identified emission “hot spots” and “hot moments,” and diagnosed the correlations between direct and indirect emissions. We demonstrated that zero-order streams and first-order streams could contribute 0.034–0.066 and 0.011 nmol N 2O m –2 s –1 (expressed on the basis of unit catchment area) to the total surface emissions, respectively. Emissions from zero-order and first-order streams equal 24–41% of direct emissions from soil, which may explain the emission gap between calculations using top-down and bottom-up methods. Clear spatial patterns were identified for both direct and indirect emissions and their spatial variations were negatively correlated. Our results indicatemore » that the IPCC N 2O emission factor for streams in the Corn Belt should be increased by 3.2–5.7 times. Increasing precipitation and streamflow in the Corn Belt may potentially increase frequencies of soil anoxic conditions and nitrate leaching to streams, and subsequently increase N 2O emissions from both soils and streams.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [4]; ORCiD logo [3]
  1. Nanjing Univ. of Information Science & Technology, Nanjing (China); Chinese Academy of Sciences (CAS), Nanjing (China); Yale Univ., New Haven, CT (United States)
  2. Nanjing Univ. of Information Science & Technology, Nanjing (China); Yale Univ., New Haven, CT (United States)
  3. Univ. of Minnesota, Saint Paul, MN (United States)
  4. Univ. of Minnesota, Saint Paul, MN (United States); US Dept. of Agriculture-Agricultural Research Service (USDA-ARS), Saint Paul, MN (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org.:
USDOE Office of Science (SC); United States Department of Agriculture
OSTI Identifier:
1544286
Grant/Contract Number:  
[USDA‐NIFA 2013‐67019‐21364; AC02-05CH11231]
Resource Type:
Accepted Manuscript
Journal Name:
Water Resources Research
Additional Journal Information:
[ Journal Volume: 54; Journal Issue: 5]; Journal ID: ISSN 0043-1397
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Corn Belt; nitrous oxide; SWAT; hot spots; hot moments; Little Cannon River

Citation Formats

Fu, Congsheng, Lee, Xuhui, Griffis, Timothy J., Baker, John M., and Turner, Peter A. A Modeling Study of Direct and Indirect N2O Emissions From a Representative Catchment in the U.S. Corn Belt. United States: N. p., 2018. Web. doi:10.1029/2017WR022108.
Fu, Congsheng, Lee, Xuhui, Griffis, Timothy J., Baker, John M., & Turner, Peter A. A Modeling Study of Direct and Indirect N2O Emissions From a Representative Catchment in the U.S. Corn Belt. United States. doi:10.1029/2017WR022108.
Fu, Congsheng, Lee, Xuhui, Griffis, Timothy J., Baker, John M., and Turner, Peter A. Tue . "A Modeling Study of Direct and Indirect N2O Emissions From a Representative Catchment in the U.S. Corn Belt". United States. doi:10.1029/2017WR022108. https://www.osti.gov/servlets/purl/1544286.
@article{osti_1544286,
title = {A Modeling Study of Direct and Indirect N2O Emissions From a Representative Catchment in the U.S. Corn Belt},
author = {Fu, Congsheng and Lee, Xuhui and Griffis, Timothy J. and Baker, John M. and Turner, Peter A.},
abstractNote = {Indirect nitrous oxide (N2O) emissions from drainage ditches and headwater streams are poorly constrained. Few studies have monitored stream N2O emissions and fewer modeling studies have been conducted to simulate stream N2O emissions. Here, we determined direct and indirect N2O emission modules and a corresponding calibration module for use in the Soil and Water Assessment Tool (SWAT) model, and implemented the expanded SWAT model (termed SWAT-N2O) to a representative fourth-stream-order catchment (210 km2) and six first-order stream catchments (0.22–1.83 km2) in southeastern Minnesota. We simulated the spatial and temporal fluctuations of the indirect emissions from streams, identified emission “hot spots” and “hot moments,” and diagnosed the correlations between direct and indirect emissions. We demonstrated that zero-order streams and first-order streams could contribute 0.034–0.066 and 0.011 nmol N2O m–2 s–1 (expressed on the basis of unit catchment area) to the total surface emissions, respectively. Emissions from zero-order and first-order streams equal 24–41% of direct emissions from soil, which may explain the emission gap between calculations using top-down and bottom-up methods. Clear spatial patterns were identified for both direct and indirect emissions and their spatial variations were negatively correlated. Our results indicate that the IPCC N2O emission factor for streams in the Corn Belt should be increased by 3.2–5.7 times. Increasing precipitation and streamflow in the Corn Belt may potentially increase frequencies of soil anoxic conditions and nitrate leaching to streams, and subsequently increase N2O emissions from both soils and streams.},
doi = {10.1029/2017WR022108},
journal = {Water Resources Research},
number = [5],
volume = [54],
place = {United States},
year = {2018},
month = {4}
}

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Figures / Tables:

Figure 1 Figure 1: Locations of the (a) U. S. Corn Belt and (b) the studied catchments, (c) land use, (d) soil classes, and (e) modeled direct and indirect N2O emission fluxes of the studied Little Cannon River catchment. Numbers in plot (e) are subbasin’s IDs. CC in plot (b) is onemore » of first-order stream catchments where stream N2O emission fluxes were monitored. WATR: Water; URLD: Residential-Low Density; URMD: Residential-Medium Density; URHD: Residential-High Density; UIDU: Industrial; SWRN: South Western Range; FRSD: Deciduous Forest; FRSE: Evergreen Forest; RNGE: Grasslands/Herbaceous; HAY: Hay; AGRR: Agricultural Land-Row Crops; WETF: Woody Wetlands; WETN: Emergent/Herbaceous Wetlands; MN175: Ostrander; MN218: Seaton; MN229: Estherville; MN230: Maxfield; MN231: Frontenac; MN232: Marlean; MN233: Timula; MN234: Garwin.« less

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