## 2 Materials and Methods
### Data  
Four major datasets were used in this study, as follows: WOFOST model input data, optical remote sensing data, SAR remote sensing data, and field measured data (soil moisture and winter wheat yield). The WOFOST model input data includes crop parameters, soil parameters, and meteorological data. Some parameters of the crop and soil were calculated from the field measurements (e.g., day of emergence (IDEM), initial total crop dry weight (TDWI), and cumulative temperature from emergence to anthesis and from anthesis to maturity ((TSUM1/TSUM2) et al.). Others were derived from the references or default value in the WOFOST model. [PERSON] et al. and [PERSON] et al. provide details of the sources of the different parameters [30; 31]. The meteorological data were obtained from the China Meteorological Administration, ([[http://www.cma.gov.cn/](http://www.cma.gov.cn/)]([http://www.cma.gov.cn/](http://www.cma.gov.cn/))), which includes daily maximum and minimum temperatures, solar radiation, wind speed, actual vapor pressure, and precipitation. The meteorological parameters were interpolated into raster data at 10 m resolution. Each winter wheat assimilation grid has its own meteorological data files. The optical remote sensing data used in this study is Sentinel-2A MSI data. Sentinel-2 is a constellation with two twin satellites Sentinel-2A and Sentinel-2B, launched by the European Space Agency (ESA) in June 2015 and March 2017, respectively. Sentinel-2 carries the multi-spectral instrument (MSI) with 13 spectral channels, including visible, near infrared (NIR), and shortwave infrared spectral range bands. The revisit time of Sentinel-2A/B is 10 days and the spatial resolution of Sentinel-2 is dependent on the particular spectral band. In this study, we used 10 meters for Band 2 (Blue), Band 3 (Green), Band 4 (Red), and Band 8 (NIR) ([[https://scihub.esa.int](https://scihub.esa.int)]([https://scihub.esa.int](https://scihub.esa.int))). Based on the field experiment dates (Figure 2), three cloud-free Sentinel-2 images were collected for the study area. Data pre-processing, including atmospheric correction and converting top-of-atmosphere reflectance into top-of-canopy reflectance, was accomplished by the Sentinel Application Platform (SNAP) software [32]. Figure 1: Study area. (Every county has 2 measured sites; each site has 5 sample points). Figure 2: Calendar of the field experiment, remote sensing data acquisition dates and general growth stages of winter wheat. Three Sentinel-1A images were acquired during field experiment dates (Figure 2). The two-satellite Sentinel-1 constellation carries a SAR instrument at C-band and has been designed to address medium- and high-resolution applications. The Interferometric Widespread (IW) mode is the pre-defined acquisition mode over land. This mode provides dual-polarization (VV and VH) imagery at a resolution of 10 m, with a swath of 250 km ([[https://scihub.esa.int](https://scihub.esa.int)]([https://scihub.esa.int](https://scihub.esa.int))) [8,21]. In this study, we used Level-1 single look complex (SLC) data. Data pre-processing, which includes thermal noise removal, calibration, multi-look, speckle filter, and terrain correction, was accomplished using SNAP to obtain the \(\sigma^{0}\) backscatter coefficient. For the field experiment data, we selected 2 sites in each county (Figure 1) throughout the study area and monitored the winter wheat growing conditions from March to June in 2017. Each site had five 1 m \(\times\) 1 m sampling points in an area of 100 m \(\times\) 100 m. Field experiment dates (Figure 2) were selected during the three main growing seasons of winter wheat (jointing stage, heading stage, and milk-maturity stage). In the field experiment, winter wheat LAI was measured using an LAI-2000 Plant Canopy Analyzer and the soil moisture was measured using a FieldScout TDR 300 Soil Moisture Meter to collect soil moisture data at a depth of 0-10 cm. Winter wheat yields were measured by on-site sampling.