Chinese Journal of Agrometeorology ›› 2026, Vol. 47 ›› Issue (2): 169-179.doi: 10.3969/j.issn.1000-6362.2026.02.001

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Regional Verification of CLDAS Relative Soil Moisture Product for Soil Moisture Monitoring in Henan Province

ZHANG Hong, GUO Kang-jun, JI Xing-jie   

  1. Henan Provincial Key Laboratory of Agrometeorological Safeguard and Applied Technique, China Meteorological Administration/ Henan Institute of Meteorological Sciences, Zhengzhou 450003, China
  • Received:2024-12-27 Online:2026-02-20 Published:2026-02-10

Abstract:

To develop highprecision, hightimeliness and highresolution relative soil moisture products, based on the daily relative soil moisture product from the China Meteorological Administration Land Data Assimilation System (CLDAS) and hourly relative soil moisture data from 309 automatic soil moisture observation stations in Henan from March to November during 20222024, the CLDAS relative soil moisture products for the 010cm, 020cm and 050cm layers in six agroecological zones of Henan were evaluated by using correlation coefficient, root mean square errorRMSE, and bias at the site, regional and regional monthly scales. Regional correction models of three layers were developed by regressionbased correction, and the models were validated through a comparative analysis of RMSE and the bias before and after correction. The results showed that the CLDAS simulated values of relative soil moisture in Henan were consistent with the observed values from March to November during 20222024. At the site scale, the CLDAS simulated values of relative soil moisture at depths of 010cm and 020cm were close to the observed values, while the CLDAS simulated values of relative soil moisture at a depth of 050cm were smaller than the observed values. At three depths, the correlation coefficient between the CLDAS simulated and observed values was generally greater than 0.50, with the RMSE below 30pp. At the regional scale, the correlation coefficient between the CLDAS simulated and observed values at a depth of 010cm ranged from 0.83 to 0.91, with the highest values in southwestern and southern Henan; the RMSE ranged from 5.72pp to 9.00pp, with the smallest value in eastern Henan; and the bias ranged from −6.20pp to 5.54pp, with the smallest absolute value of bias in eastern Henan. The correlation coefficient between the CLDAS simulated and observed values at a depth of 020cm ranged from 0.85 to 0.92, with the highest value in eastern Henan; the RMSE ranged from 4.13pp to 9.07pp, with the smallest value in eastern Henan; and the bias ranged from −6.36pp to 4.74pp, with the smallest absolute value of bias in western Henan. The correlation coefficient between the CLDAS simulated and observed values at a depth of 050 cm ranged from 0.80 to 0.91, with the highest value in eastern Henan; the RMSE ranged from 4.68pp to 12.51pp, with the smallest value in northern Henan; and the bias ranged from −11.05pp to 1.39pp, with the smallest absolute value of bias in northern Henan. At the regional monthly scale, the overall monthly correlation between the CLDAS simulated and observed values was good, with correlation coefficient exceeding 0.70 in most areas from May to October. The RMSE was generally less than 15%, with the smallest values in western and eastern Henan at three depths. After regional correction, the RMSE between the CLDAS simulated and observed values decreased to 3.47−7.25pp, with a reduction range of 0.04−7.20pp; and the bias decreased to −0.04−0.02pp, with a reduction range of 0.45−11.42pp. Additionally, the correction models for northern, eastern, and central−southern Henan demonstrated good generalization capabilities. Overall, the CLDAS relative soil moisture product has high simulation accuracy in northern, western, and eastern Henan, with higher simulation accuracy from May to October. After regional correction, the simulation accuracy of CLDAS relative soil moisture was further improved, providing important support for agricultural drought and flood monitoring, assessment, and early warning.

Key words: CLDAS, Relative soil moisture, Automatic soil moisture observation station, Agro?ecological zone, Precision assessment, Spatiotemporal comparison