Effects of soil spatial resolution on quantifying CH4 and N 2O emissions from rice fields in the Tai Lake region of China by DNDC model

D. S. Yu, H. Yang, X. Z. Shi, Eric David Warner, L. M. Zhang, Q. G. Zhao

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Fourteen grid data sets of different cell resolutions were generated, from 0.5 × 0.5 km to 64 × 64 km, to estimate CH4 and N 2O emissions from paddy soils in the Tai Lake region of China using the Denitrification-Decomposition (DNDC) model. The grids were derived from a polygon-based data set (1:50,000 digital soil map/database), which was the most detailed soil database for the region. Comparison of simulated CH4 and N2O concentrations from input of the 14 grid data sets with the original polygon data demonstrated (1) no distinct variability (relative errors <5%) of the results when grid data sets of cell size 2 km were used as input for the DNDC model; (2) slight variability (<10%) in the results when grid data sets with cell size in the range of 2 to 8 km were used as input; and (3) distinct variability (>10%) in the results when grid data sets with cell size of >8 km were applied as input. A grid data set with a cell size of 8 km was found to be optimal based on accuracy and computational efficiency of DNDC simulations. The results can be used as a guideline for optimizing field sampling strategies for locations where there is a lack of or insufficient soil data, whereby soil data can be collected through sampling in cell centers of designed grid frames.

Original languageEnglish (US)
Article numberGB2004
JournalGlobal Biogeochemical Cycles
Volume25
Issue number2
DOIs
StatePublished - May 27 2011

Fingerprint

Denitrification
paddy field
Lakes
denitrification
spatial resolution
decomposition
Decomposition
Soils
lake
polygon
soil
Sampling
sampling
Computational efficiency
effect
simulation

All Science Journal Classification (ASJC) codes

  • Global and Planetary Change
  • Environmental Chemistry
  • Environmental Science(all)
  • Atmospheric Science

Cite this

@article{15a395ae850a4f77a3d6b6928ca8c767,
title = "Effects of soil spatial resolution on quantifying CH4 and N 2O emissions from rice fields in the Tai Lake region of China by DNDC model",
abstract = "Fourteen grid data sets of different cell resolutions were generated, from 0.5 × 0.5 km to 64 × 64 km, to estimate CH4 and N 2O emissions from paddy soils in the Tai Lake region of China using the Denitrification-Decomposition (DNDC) model. The grids were derived from a polygon-based data set (1:50,000 digital soil map/database), which was the most detailed soil database for the region. Comparison of simulated CH4 and N2O concentrations from input of the 14 grid data sets with the original polygon data demonstrated (1) no distinct variability (relative errors <5{\%}) of the results when grid data sets of cell size 2 km were used as input for the DNDC model; (2) slight variability (<10{\%}) in the results when grid data sets with cell size in the range of 2 to 8 km were used as input; and (3) distinct variability (>10{\%}) in the results when grid data sets with cell size of >8 km were applied as input. A grid data set with a cell size of 8 km was found to be optimal based on accuracy and computational efficiency of DNDC simulations. The results can be used as a guideline for optimizing field sampling strategies for locations where there is a lack of or insufficient soil data, whereby soil data can be collected through sampling in cell centers of designed grid frames.",
author = "Yu, {D. S.} and H. Yang and Shi, {X. Z.} and Warner, {Eric David} and Zhang, {L. M.} and Zhao, {Q. G.}",
year = "2011",
month = "5",
day = "27",
doi = "10.1029/2010GB003825",
language = "English (US)",
volume = "25",
journal = "Global Biogeochemical Cycles",
issn = "0886-6236",
publisher = "American Geophysical Union",
number = "2",

}

Effects of soil spatial resolution on quantifying CH4 and N 2O emissions from rice fields in the Tai Lake region of China by DNDC model. / Yu, D. S.; Yang, H.; Shi, X. Z.; Warner, Eric David; Zhang, L. M.; Zhao, Q. G.

In: Global Biogeochemical Cycles, Vol. 25, No. 2, GB2004, 27.05.2011.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Effects of soil spatial resolution on quantifying CH4 and N 2O emissions from rice fields in the Tai Lake region of China by DNDC model

AU - Yu, D. S.

AU - Yang, H.

AU - Shi, X. Z.

AU - Warner, Eric David

AU - Zhang, L. M.

AU - Zhao, Q. G.

PY - 2011/5/27

Y1 - 2011/5/27

N2 - Fourteen grid data sets of different cell resolutions were generated, from 0.5 × 0.5 km to 64 × 64 km, to estimate CH4 and N 2O emissions from paddy soils in the Tai Lake region of China using the Denitrification-Decomposition (DNDC) model. The grids were derived from a polygon-based data set (1:50,000 digital soil map/database), which was the most detailed soil database for the region. Comparison of simulated CH4 and N2O concentrations from input of the 14 grid data sets with the original polygon data demonstrated (1) no distinct variability (relative errors <5%) of the results when grid data sets of cell size 2 km were used as input for the DNDC model; (2) slight variability (<10%) in the results when grid data sets with cell size in the range of 2 to 8 km were used as input; and (3) distinct variability (>10%) in the results when grid data sets with cell size of >8 km were applied as input. A grid data set with a cell size of 8 km was found to be optimal based on accuracy and computational efficiency of DNDC simulations. The results can be used as a guideline for optimizing field sampling strategies for locations where there is a lack of or insufficient soil data, whereby soil data can be collected through sampling in cell centers of designed grid frames.

AB - Fourteen grid data sets of different cell resolutions were generated, from 0.5 × 0.5 km to 64 × 64 km, to estimate CH4 and N 2O emissions from paddy soils in the Tai Lake region of China using the Denitrification-Decomposition (DNDC) model. The grids were derived from a polygon-based data set (1:50,000 digital soil map/database), which was the most detailed soil database for the region. Comparison of simulated CH4 and N2O concentrations from input of the 14 grid data sets with the original polygon data demonstrated (1) no distinct variability (relative errors <5%) of the results when grid data sets of cell size 2 km were used as input for the DNDC model; (2) slight variability (<10%) in the results when grid data sets with cell size in the range of 2 to 8 km were used as input; and (3) distinct variability (>10%) in the results when grid data sets with cell size of >8 km were applied as input. A grid data set with a cell size of 8 km was found to be optimal based on accuracy and computational efficiency of DNDC simulations. The results can be used as a guideline for optimizing field sampling strategies for locations where there is a lack of or insufficient soil data, whereby soil data can be collected through sampling in cell centers of designed grid frames.

UR - http://www.scopus.com/inward/record.url?scp=79956365854&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79956365854&partnerID=8YFLogxK

U2 - 10.1029/2010GB003825

DO - 10.1029/2010GB003825

M3 - Article

AN - SCOPUS:79956365854

VL - 25

JO - Global Biogeochemical Cycles

JF - Global Biogeochemical Cycles

SN - 0886-6236

IS - 2

M1 - GB2004

ER -