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Implementing a Dynamic Root Distribution Scheme Responsive to Soil Environment Into Noah-MP-Crop: Improving Simulations of Soil Water, Crop Growth, and Energy Fluxes in Agro-Ecosystems

文献类型:期刊论文

作者Meng, Huimin4,5; Zhan, Chesheng3; Hu, Shi2; Li, Zhonghe1; Lin, Zhonghui2
刊名JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
出版日期2026-04-08
卷号131期号:4页码:e2025JG009462
关键词dynamic root distribution land surface model soil moisture crop growth latent heat flux agro-ecosystems
ISSN号2169-8953
DOI10.1029/2025JG009462
产权排序1
文献子类Article
英文摘要Reliable simulation of land-atmosphere interactions in land surface models (LSMs) requires realistic root distribution modeling, yet conventional static root parameterizations often fail to capture seasonal root dynamics in cropland ecosystems. In this study, we developed a soil-environment-responsive dynamic root distribution scheme (SE_root) within the Noah-MP-Crop framework that explicitly accounts for soil moisture (SM), temperature, aeration, bulk density, and soil texture. Evaluations against in situ observations in the North China Plain demonstrated that SE_root substantially outperformed the default static (fixed_root) and exponential dynamic (Exp_root) parameterizations. Site-scale simulations exhibited improved accuracy in capturing SM dynamics, leaf area index (LAI), and latent heat flux (LHF), yielding R 2 values consistently above 0.56. The simulated vertical root biomass distribution, with approximately 70% of root biomass concentrated in the upper 40 cm and declining with depth, closely matched field observations. Relative to the fixed_root and Exp_root schemes, the site-scale mean absolute errors were reduced by 10%-12% for SM and 4%-10% for LAI. Regional simulations further revealed that by capturing the dynamic feedback between root growth and local soil constraints, SE_root better represented the spatial heterogeneity of SM and LAI, alongside modest LHF improvements. Overall, incorporating this soil-responsive root parameterization improves the representation of SM dynamics, root allocation, crop growth, and land-atmosphere exchanges. These findings underscore the importance of explicitly representing root-soil interactions in agricultural LSMs, offering a robust pathway for coupling with climate models to capture crop-climate feedbacks and support sustainable management.
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WOS关键词SURFACE MODEL EVALUATION ; COMMON LAND MODEL ; PHYSICAL-PROPERTIES ; WINTER-WHEAT ; EVAPOTRANSPIRATION ; CLIMATE ; DATASET ; CARBON ; DEPTH ; CHINA
WOS研究方向Environmental Sciences & Ecology ; Geology
语种英语
WOS记录号WOS:001734862200001
出版者AMER GEOPHYSICAL UNION
源URL[http://ir.igsnrr.ac.cn/handle/311030/221554]  
专题禹城站农业生态系统研究中心_外文论文
通讯作者Zhan, Chesheng; Hu, Shi
作者单位1.Cent South Acad Inventory & Planning NFGA, Changsha, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China;
3.Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Earth Syst Numer Modeling & Applicat, Beijing, Peoples R China;
4.Univ Chinese Acad Sci, Beijing, Peoples R China;
5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Yucheng Comprehens Expt Stn, Beijing, Peoples R China;
推荐引用方式
GB/T 7714
Meng, Huimin,Zhan, Chesheng,Hu, Shi,et al. Implementing a Dynamic Root Distribution Scheme Responsive to Soil Environment Into Noah-MP-Crop: Improving Simulations of Soil Water, Crop Growth, and Energy Fluxes in Agro-Ecosystems[J]. JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES,2026,131(4):e2025JG009462.
APA Meng, Huimin,Zhan, Chesheng,Hu, Shi,Li, Zhonghe,&Lin, Zhonghui.(2026).Implementing a Dynamic Root Distribution Scheme Responsive to Soil Environment Into Noah-MP-Crop: Improving Simulations of Soil Water, Crop Growth, and Energy Fluxes in Agro-Ecosystems.JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES,131(4),e2025JG009462.
MLA Meng, Huimin,et al."Implementing a Dynamic Root Distribution Scheme Responsive to Soil Environment Into Noah-MP-Crop: Improving Simulations of Soil Water, Crop Growth, and Energy Fluxes in Agro-Ecosystems".JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES 131.4(2026):e2025JG009462.

入库方式: OAI收割

来源:地理科学与资源研究所

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