Modeling Soil Water Content and Crop-Growth Metrics in a Wheat Field in the North China Plain Using RZWQM2

Abstract

Soil water content (SWC) is an important factor restricting crop growth and yield in cropland ecosystems. The observation and simulation of soil moisture contribute greatly to improving water-use efficiency and crop yield. This study was conducted at the Shandong Yucheng Agro-ecosystem National Observation and Research Station in the North China Plain. The study period was across the winter wheat (Triticum aestivum L.) growth stages from 2017 to 2019. A cosmic-ray neutron probe was used to monitor the continuous daily SWC. Furthermore, the crop leaf area index (LAI), yield, and aboveground biomass of winter wheat were determined. The root zone quality model 2 (RZWQM2) was used to simulate and validate the SWC, crop LAI, yield, and aboveground biomass. The results showed that the simulation errors of SWC were minute across the wheat growth stages and mature stages in 2017–2019. The root mean square error (RMSE) and relative root mean square error (RRMSE) of the SWC simulation at the jointing stage of winter wheat were 0.0296 and 0.1605 in 2017–2018, and 0.0265 and 0.1480 in 2018–2019, respectively. During the rain-affected days, the RMSE (0.0253) and RRMSE (0.0980) for 2017–2018 were significantly lower than those of 2018–2019 (0.0301 and 0.1458, respectively), indicating that rain events decreased the model accuracy in the dry years compared to the wet years. The simulated LAIs were significantly higher than the measured values. The simulated yield value of winter wheat was 5.61% lower and 3.92% higher than the measured yield in 2017–2018 and in 2018–2019, respectively. The simulated value of aboveground biomass was significantly (45.48%) lower than the measured value in 2017–2018. This study showed that, compared with the dry and cold wheat growth period of 2018–2019, the higher precipitation and temperature in 2017–2018 led to a poorer simulation of SWC and crop-growth components. This study indicated that annual abnormal rainfall and temperature had a significant influence on the simulation of SWC and wheat growth, especially under intensive climate-change stress conditions.

Hydrodynamic Border Irrigation Model: Comparison of Infiltration Equations

“…It is important to determine the crop water requirements and the appropriate moments of their application to cover the irrigation sheet needs of the crops established in the plots, because the variation of the moisture content in the soil is a factor that limits the development and yield of the crops in agriculture [31]. The initial moisture content determines the irrigation time, optimal irrigation flow, and irrigation sheet that should be supplied in the plot to bring the soil to field capacity [25].…”

A New Non-Inserted and Portable FDR Instrument for Measuring Surface Soil Water Content

“…To date, a number of methods at different scales have been proven useful for measuring SWC, including the weighing method [9], neutron instrument method [10,11], capacitance method [12], time domain reflection (TDR) method [13], frequency domain reflection (FDR) method [14], and remote sensing [15]. Among them, monitoring SWC at a point scale (less than 0.01 cm 2 ) has advanced with various in-situ sensors, and the FDR method has been widely used [16].…”