Root Zone Soil Moisture Retrieval Based On Surface Soil Moisture

As an essential component of soil moisture（SM）,root zone soil moisture（RZSM）is an important environmental variable that affects many natural processes and plays an important role in agriculture,hydrology,meteorology.In addition,as a major driver of agricultural productivity and an indicator of crop water stress,accurate estimation of RZSM is also of great value for predicting agricultural productivity and monitoring drought.In order to develop and strengthen agriculture in China,a country with not only water shortage but also uneven distribution of water resources,it is crucial to understand the changes of SM,especially the spatial-temporal distribution and dynamic changes of RZSM.In this study,daily/0.05°resolution RZSM covering the major land areas of China was estimated from the synergistic use of soil moisture analytical relationship（SMAR）model and satellite-derived surface SM（SSM）estimates.First,based on the fifth generation of atmospheric reanalysis（ERA5-Land）,the Monte Carlo Markov Chain（MCMC）algorithm was applied to optimize the SMAR model to determine four essential parameters(S_csuf,S_wroot,α,β)pixel-to-pixel over the study area.In addition,the optimized SMAR parameters were integrated with satellite-derived daily/0.05°SSM to predict the daily/0.05°RZSM in China.Finally,due to the lack of in situ RZSM data and other RZSM truth at a spatial resolution of 0.05°,the Soil Moisture Active Passive（SMAP）L4（SPL4SMAU）RZSM product resampled to 0.05°was taken as a reference to preliminarily assess the estimated RZSM.The results show that:（1）Among the optimized SMAR model parameters in the study area,the root mean square error（RMSE）of more than 90%pixels was lower than 0.04cm³/cm³,and the correlation coefficient（R）of more than 85%pixels was higher than 0.8,indicating that the optimized SMAR model parameters have high accuracy,which can ensure the retrieval accuracy of RZSM.（2）The accuracy of RZSM estimation was the best in croplands,with an unbiased RMSE（ub RMSE）of 0.064 cm³/cm³,followed by woodlands and grasslands,with an ub RMSE of 0.071 cm³/cm³and 0.081 cm³/cm³,respectively.Overall,the R and ub RMSE between the estimated RZSM and the resampled SPL4SMAU RZSM product were～0.611 and～0.080 cm³/cm³,respectively.