中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 地理科学与资源研究所
  3. 中国科学院地理科学与资源研究所
ChinaCropSM1 km: a fine 1 km daily soil moisture dataset for dryland wheat and maize across China during 1993-2018

文献类型：期刊论文

作者Cheng, Fei5; Zhang, Zhao4,5; Zhuang, Huimin5; Han, Jichong5; Luo, Yuchuan5; Cao, Juan5; Zhang, Liangliang5; Zhang, Jing5; Xu, Jialu4; Tao, Fulu1,2,3
刊名EARTH SYSTEM SCIENCE DATA
出版日期2023-01-23
卷号15期号:1页码:395-409
ISSN号1866-3508
DOI10.5194/essd-15-395-2023
通讯作者Zhang, Zhao(sunny_zhang@bnu.edu.cn)
英文摘要Soil moisture (SM) is a key variable of the regional hydrological cycle and has important applications for water resource and agricultural drought management. Various global soil moisture products have been mostly retrieved from microwave remote sensing data. However, currently there is rarely spatially explicit and time-continuous soil moisture information with a high resolution at the national scale. In this study, we generated a 1 km soil moisture dataset for dryland wheat and maize in China (ChinaCropSM1 km) over 1993-2018 through a random forest (RF) algorithm based on numerous in situ daily observations of soil moisture. We independently used in situ observations (181 327 samples) from the agricultural meteorological stations (AMSs) across China for training (164 202 samples) and others for testing (17 125 samples). An irrigation module was first developed according to crop type (i.e., wheat, maize), soil depth (0-10, 10-20 cm) and phenology. We produced four daily datasets separately by crop type and soil depth, and their accuracies were all satisfactory (wheat r 0.93, ubRMSE 0.033 m(3) m(-3); maize r 0.93, ubRMSE 0.035 m(3) m(-3)). The spatiotemporal resolutions and accuracy of ChinaCropSM1 km were significantly better than those of global soil moisture products (e.g., r increased by 116 %, ubRMSE decreased by 64 %), including the global remote-sensing-based surface soil moisture dataset (RSSSM) and the European Space Agency (ESA) Climate Change Initiative (CCI) SM. The approach developed in our study could be applied to other regions and crops in the world, and our improved datasets are very valuable for many studies and field management, such as agricultural drought monitoring and crop yield forecasting. The data are published in Zenodo at https://doi.org/10.5281/zenodo.6834530 (wheat(0-10)) (Cheng et al., 2022a), https://doi.org/10.5281/zenodo.6822591 (wheat(10-20)) (Cheng et al., 2022b), https://doi/org/10.5281/zenodo.6822581 (maize(10)) (Cheng et al., 2022c) and https://doi.org/10.5281/zenodo.6820166 (maize(10-20)) (Cheng et al., 2022d).
WOS关键词IN-SITU ; CROP YIELD ; IRRIGATION ; RESOLUTION ; WATER ; CLASSIFICATION ; ASSIMILATION ; REGRESSION ; PRODUCTS ; IMPACTS
资助项目National Key Research and Development Program of China[2020YFA0608201] ; National Natural Science Foundation of China[41977405]
WOS研究方向Geology ; Meteorology & Atmospheric Sciences
语种英语
出版者COPERNICUS GESELLSCHAFT MBH
WOS记录号WOS:000921486500001
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/189853]  
专题中国科学院地理科学与资源研究所
通讯作者Zhang, Zhao
作者单位1.Nat Resources Inst Finland Luke, Climate Impacts Grp, Helsinki 00790, Finland
2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
4.Beijing Normal Univ, Sch Natl Safety & Emergency Management, Beijing 100875, Peoples R China
5.Beijing Normal Univ, Acad Disaster Reduct & Emergency Management, Beijing 100875, Peoples R China
推荐引用方式
GB/T 7714		 Cheng, Fei,Zhang, Zhao,Zhuang, Huimin,et al. ChinaCropSM1 km: a fine 1 km daily soil moisture dataset for dryland wheat and maize across China during 1993-2018[J]. EARTH SYSTEM SCIENCE DATA,2023,15(1):395-409.
APA Cheng, Fei.,Zhang, Zhao.,Zhuang, Huimin.,Han, Jichong.,Luo, Yuchuan.,...&Tao, Fulu.(2023).ChinaCropSM1 km: a fine 1 km daily soil moisture dataset for dryland wheat and maize across China during 1993-2018.EARTH SYSTEM SCIENCE DATA,15(1),395-409.
MLA Cheng, Fei,et al."ChinaCropSM1 km: a fine 1 km daily soil moisture dataset for dryland wheat and maize across China during 1993-2018".EARTH SYSTEM SCIENCE DATA 15.1(2023):395-409.

入库方式： OAI收割

来源：地理科学与资源研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。