农科机构知识库联盟

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

文献类型：外文期刊

第一作者： Zhang, Xuesong

作者： Zhang, Xuesong;Manowitz, David H.;Izaurralde, Roberto C.;Thomson, Allison M.;West, Tristram O.;Zhang, Xuesong;Manowitz, David H.;Izaurralde, Roberto C.;Thomson, Allison M.;West, Tristram O.;Sahajpal, Ritvik;Izaurralde, Roberto C.;Zhao, Kaiguang;LeDuc, Stephen D.;Xu, Min;Xiong, Wei;Zhang, Aiping;Post, Wilfred M.

作者机构：

关键词： Climate change;Net Ecosystem Production;EPIC;Parallel computing;Spatial resolution;SSURGO;STATSGO

期刊名称：SCIENCE OF THE TOTAL ENVIRONMENT （影响因子：7.963；五年影响因子：7.842 ）

ISSN：

年卷期：

页码：

收录情况： SCI

摘要： The development of effectivemeasures to stabilize atmospheric CO_2 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 EcosystemProduction (NEP) estimates at the State level. However, substantial differenceswere 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.

分类号： X1

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