Articles | Volume 14, issue 12
Data description paper
30 Nov 2022
Data description paper |  | 30 Nov 2022

A 1 km daily soil moisture dataset over China using in situ measurement and machine learning

Qingliang Li, Gaosong Shi, Wei Shangguan, Vahid Nourani, Jianduo Li, Lu Li, Feini Huang, Ye Zhang, Chunyan Wang, Dagang Wang, Jianxiu Qiu, Xingjie Lu, and Yongjiu Dai

Data sets

A 1-km daily soil moisture dataset over China based on in-situ measurement (2000-2020) W. Shangguan, Q. Li, and G. Shi

Short summary
SMCI1.0 is a 1 km resolution dataset of daily soil moisture over China for 2000–2020 derived through machine learning trained with in situ measurements of 1789 stations, meteorological forcings, and land surface variables. It contains 10 soil layers with 10 cm intervals up to 100 cm deep. Evaluated by in situ data, the error (ubRMSE) ranges from 0.045 to 0.051, and the correlation (R) range is 0.866-0.893. Compared with ERA5-Land, SMAP-L4, and, SIMI1.0 has higher accuracy and resolution.