This site requires Cookies enabled in your browser for login.
Updating ...
WaterNet Home
WaterNet
for
pour le
Canada
Menu
WaterNet
Home
GWFO
Home
Catalogue
Master Index
Data
Centre
Collections
X
Defaults
Select All
Websites
X
Global Water Futures Observatories (GWFO) Global Water Futures (GWF) Global Institute for Water Security (GIWS) International Network of Alpine Research Catchment Hydrology
Legacy Research Programs
X
Changing Cold Regions Network (CCRN) Drought Research Initiative (DRI) International Network of Alpine Research Catchment Hydrology (Legacy Site) Improving Processes & Parameterization for Prediction in Cold Regions Hydrology (IP3) The Mackenzie Global Energy and Water Cycle Experiment (GEWEX) Study (MAGS)
Legacy sites
Map
Utilities
X
Account Settings Metadata Editor Record List Alias List Editor
Data Centre
Data Type Editor
. . .
X
Clear
Select All
Advanced Search
Go to Top⇡
Related items loading ...
Fetching Chart ...
Publication Additional Information
Publication Type
Journal Article
Authorship
Xiong, Wentao, Tang, Guoqiang, Shen, Yan
Title
Cross-Evaluation of Soil Moisture Based on the Triple Collocation Method and a Preliminary Application of Quality Control for Station Observations in China
Year
2022
Publication Outlet
Water 14, no. 7: 1054
DOI
https://doi.org/10.3390/w14071054
Citation
Xiong, Wentao, Tang, Guoqiang, Shen, Yan (2022) Cross-Evaluation of Soil Moisture Based on the Triple Collocation Method and a Preliminary Application of Quality Control for Station Observations in China, Water 14, no. 7: 1054
Abstract
Soil moisture (SM) measurements from ground stations are often after quality control (QC) in the operational system, but the QC flags may not be reliable in some cases when precipitation events or manual watering happen. This study applies the triple collocation (TC) method to conduct a cross-evaluation of SM data from ERA5 reanalysis estimates, ESA-CCI estimates, and ~2000 ground stations across the China domain. The results show that all datasets can capture the spatial pattern of SM in China. TC-based correlation coefficient (CC) and root mean square error (RMSE) show that the station data have worse performance in western and central China. For most stations, TC-based CC is between 0.6~0.9, and TC-based RMSE is between 0.01~0.06 m3/m3. In addition, TC-based metrics show good agreement with the CC between precipitation and SM, indicating that these metrics can reflect the quality of station data. We further selected typical stations (e.g., CC ? 0.2, RMSE ? 0.06 m3/m3) to check the quality of the QC procedure. The comparison shows that TC-based metrics can better represent the actual quality for these stations compared to raw QC flags. This study indicates that TC has the potential to detect problematic stations and could be a supplement to traditional QC of station observations.
Program Affiliations
GWF: Global Water Futures
Publication Stage
Published
© 2026 - WaterNet Version 2026-07-02
Global Water Futures Observatories
Powered by
G W F Net
T-2024-10-30-d1aB8mRWy3UiXLAHVLVfEd2w Publication 1.0