Multi-scale geospatial agroecosystem modeling: A case study on the influence of soil data resolution on carbon budget estimates

doi:10.1016/j.scitotenv.2014.01.099

CORC > 中国农业科学院 > 农业环境与可持续发展研究所 > 气候变化研究室

	Multi-scale geospatial agroecosystem modeling: A case study on the influence of soil data resolution on carbon budget estimates
	Zhang, Xuesong 1,2; Sahajpal, Ritvik 3; Manowitz, David H.1,2; Zhao, Kaiguang 4; LeDuc, Stephen D.5; Xu, Min 6; Xiong, Wei 7; Zhang, Aiping 7; Izaurralde, Roberto C.1,2,3; Thomson, Allison M.1,2
刊名	SCIENCE OF THE TOTAL ENVIRONMENT
	2014
卷号	479 页码:138-150
关键词	Climate change Net Ecosystem Production EPIC Parallel computing Spatial resolution SSURGO STATSGO
ISSN号	0048-9697
DOI	10.1016/j.scitotenv.2014.01.099
通讯作者	Zhang, Xuesong
英文摘要	The development of effective measures to stabilize atmospheric CO2 concentration and mitigate negative impacts of climate change requires accurate quantification of the spatial variation and magnitude of the terrestrial carbon (C) flux. However, the spatial pattern and strength of terrestrial C sinks and sources remain uncertain. In this study, we designed a spatially-explicit agroecosystem modeling system by integrating the Environmental Policy Integrated Climate (EPIC) model with multiple sources of geospatial and surveyed datasets (including crop type map, elevation, climate forcing, fertilizer application, tillage type and distribution, and crop planting and harvesting date), and applied it to examine the sensitivity of cropland C flux simulations to two widely used soil databases (i.e. State Soil Geographic-STATSGO of a scale of 1:250,000 and Soil Survey Geographic-SSURGO of a scale of 1:24,000) in Iowa, USA. To efficiently execute numerous EPIC runs resulting from the use of high resolution spatial data (56 m), we developed a parallelized version of EPIC. Both STATSGO and SSURGO led to similar simulations of crop yields and Net Ecosystem Production (NEP) estimates at the State level. However, substantial differences were observed at the county and sub-county (grid) levels. In general, the fine resolution SSURGO data outperformed the coarse resolution STATSGO data for county-scale crop-yield simulation, and within STATSGO, the area-weighted approach provided more accurate results. Further analysis showed that spatial distribution and magnitude of simulated NEP were more sensitive to the resolution difference between SSURGO and STATSGO at the county or grid scale. For over 60% of the cropland areas in Iowa, the deviations between STATSGO- and SSURGO-derived NEP were larger than 1 Mg C ha(-1) yr(-1), or about half of the average cropland NEP, highlighting the significant uncertainty in spatial distribution and magnitude of simulated C fluxes resulting from differences in soil data resolution. (C) 2014 Elsevier B.V. All rights reserved.
学科主题	Environmental Sciences ; ENVIRONMENTAL SCIENCES
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000334006700017
内容类型	期刊论文
源URL	[http://111.203.20.206/handle/2HMLN22E/19806]
专题	农业环境与可持续发展研究所_气候变化研究室
作者单位	1.Pacific NW Natl Lab, Joint Global Change Res Inst, College Pk, MD 20740 USA 2.Univ Maryland, College Pk, MD 20740 USA 3.Univ Maryland, Dept Geog Sci, College Pk, MD 20740 USA 4.Ohio State Univ, Sch Environm & Nat Resources, Ohio Agr Res & Dev Ctr, Wooster, OH 44691 USA 5.US EPA, Natl Ctr Environm Assessment, Arlington, VA 22202 USA 6.Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20740 USA 7.Chinese Acad Agr Sci, Inst Environm & Sustainable Dev Agr, Beijing 100081, Peoples R China 8.Oak Ridge Natl Lab, Div Environm Sci, Oak Ridge, TN 37831 USA
推荐引用方式 GB/T 7714	Zhang, Xuesong,Sahajpal, Ritvik,Manowitz, David H.,et al. Multi-scale geospatial agroecosystem modeling: A case study on the influence of soil data resolution on carbon budget estimates[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2014,479:138-150.
APA	Zhang, Xuesong.,Sahajpal, Ritvik.,Manowitz, David H..,Zhao, Kaiguang.,LeDuc, Stephen D..,...&Post, Wilfred M..(2014).Multi-scale geospatial agroecosystem modeling: A case study on the influence of soil data resolution on carbon budget estimates.SCIENCE OF THE TOTAL ENVIRONMENT,479,138-150.
MLA	Zhang, Xuesong,et al."Multi-scale geospatial agroecosystem modeling: A case study on the influence of soil data resolution on carbon budget estimates".SCIENCE OF THE TOTAL ENVIRONMENT 479(2014):138-150.