Prediction of Root-Zone Soil Moisture Using Aquacrop Model Over Irrigated Farmlands

The root-zone soil moisture (RZSM) is essential to agricultural water management. However, it is still difficult nowadays to obtain spatiotemporal root-zone soil moisture dynamics using remote sensing technology due to several challenges including the limited penetrate capacity of satellite signals and complicated water flux within soils, especially over irrigated farmlands with growing crops. In the present study, the North China Plain (NCP) which is dominated with a summer maize-winter wheat rotation system, is selected as the study region to investigate the feasibility of predicting RZSM using the AquaCrop model. An in-situ measurements based RZSM dataset named Soil moisture of China by in-situ data (SMCI) was used for calibrating the performance of AquaCrop. Results indicated that an unbiased root mean square difference (ubRMSD) of approximately 0.05 m
³
m
^-3
can be found between the AquaCrop RZSM and SMCI RZSM during calibration stage from 2013 to 2017. For the prediction period, ubRMSD of approximate 0.04 m
³
m
^-3
was obtained for both summer maize period and winter wheat period, respectively.