气候变化领域集成服务门户(CCPortal): Joint Modeling of Crop and Irrigation in the central United States Using the Noah-MP Land Surface Model

CCPortal

DOI	10.1029/2020MS002159
	Joint Modeling of Crop and Irrigation in the central United States Using the Noah-MP Land Surface Model
	Zhang Z.; Barlage M.; Chen F.; Li Y.; Helgason W.; Xu X.; Liu X.; Li Z.
发表日期	2020
ISSN	19422466
卷号	12 期号:7
英文摘要	Representing climate-crop interactions is critical to Earth system modeling. Despite recent progress in modeling dynamic crop growth and irrigation in land surface models (LSMs), transitioning these models from field to regional scales is still challenging. This study applies the Noah-MP LSM with dynamic crop-growth and irrigation schemes to jointly simulate the crop yield and irrigation amount for corn and soybean in the central United States. The model performance of crop yield and irrigation amount are evaluated at county-level against the USDA reports and USGS water withdrawal data, respectively. The bulk simulation (with uniform planting/harvesting management and no irrigation) produces significant biases in crop yield estimates for all planting regions, with root-mean-square-errors (RMSEs) being 28.1% and 28.4% for corn and soybean, respectively. Without an irrigation scheme, the crop yields in the irrigated regions are reduced due to water stress with RMSEs of 48.7% and 20.5%. Applying a dynamic irrigation scheme effectively improves crop yields in irrigated regions and reduces RMSEs to 22.3% and 16.8%. In rainfed regions, the model overestimates crop yields. Applying spatially varied planting and harvesting dates at state-level reduces crop yields and irrigation amount for both crops, especially in northern states. A “nitrogen-stressed” simulation is conducted and found that the improvement of irrigation on crop yields is limited when the crops are under nitrogen stress. Several uncertainties in modeling crop growth are identified, including yield-gap, planting date, rubisco capacity, and discrepancies between available data sets, pointing to future efforts to incorporating spatially varying crop parameters to better constrain crop growing seasons. ©2020. The Authors.
英文关键词	crop; Earth system model; irrigation; land surface model; model uncertainties; parameters
语种	英语
scopus关键词	Cultivation; Earth (planet); Irrigation; Mean square error; Nitrogen; Plants (botany); Surface measurement; Uncertainty analysis; Earth system model; Irrigation amounts; Irrigation schemes; Land surface modeling; Land surface models; Model performance; Root mean square errors; Water withdrawal; Crops; crop yield; estimation method; growing season; growth rate; harvesting; irrigation system; land surface; maize; nitrogen; soybean; spatial variation; uncertainty analysis; United States; Glycine max; Zea mays
来源期刊	Journal of Advances in Modeling Earth Systems
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156696
作者单位	Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK, Canada; School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK, Canada; Research Application Laboratory, National Center for Atmospheric Research, Boulder, CO, United States; College of Engineering, University of Saskatchewan, Saskatoon, SK, Canada; College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China; College of Agriculture, Purdue University, Lafayette, IN, United States
推荐引用方式 GB/T 7714	Zhang Z.,Barlage M.,Chen F.,et al. Joint Modeling of Crop and Irrigation in the central United States Using the Noah-MP Land Surface Model[J],2020,12(7).
APA	Zhang Z..,Barlage M..,Chen F..,Li Y..,Helgason W..,...&Li Z..(2020).Joint Modeling of Crop and Irrigation in the central United States Using the Noah-MP Land Surface Model.Journal of Advances in Modeling Earth Systems,12(7).
MLA	Zhang Z.,et al."Joint Modeling of Crop and Irrigation in the central United States Using the Noah-MP Land Surface Model".Journal of Advances in Modeling Earth Systems 12.7(2020).