Yield estimation of winter wheat in North China Plain by using crop growth monitoring system (CGMS)

Author(s):  
Teng Fei ◽  
Wu Wenbin ◽  
Li Dandan ◽  
Chen Zhongxin ◽  
Huang Qing ◽  
...  
Author(s):  
O. A. Kryvobok ◽  
O. O. Kryvoshein ◽  
T. I. Adamenko

The Crop Growth Monitoring System (CGMS) is one of the most advanced systems of monitoring the conditions of crops growth and development and forecasting their yields in agrometeorological practice. The CGMS allows to assess the conditions of growth, development and accumulation of productive biomass of a number of agricultural crops - winter wheat, barley, maize, rice, sunflower, potatoes, soybean etc. For each of the crops the system must be adapted to specific territories taking into account  meteorological, phenological, biological information and soil characteristics. The paper discusses the peculiarities of technological adaptation of the CGMS system (Crop Growth Monitoring System) including creation of a meteorological database for the period of 2000-2017 using standard meteorological observations of the Ukrainian Hydrometeorological Center (UkrHMC) network; creation of a soil characteristics database by finding a correspondences of taxonomy of the soil map of Ukraine (scale:1:2500000) to classification of soils of the WRB; creation of a database of phenological characteristics such as TSUMEM (sum of temperatures within the period from sowing to coming-up), TSUM1 (sum of temperatures within the period from coming-up to blossoming) and TSUM2 (sum of temperatures within the period from blossoming to maturity) calculated according to the data obtained from agrometeorological posts and stations of the UkrHMC network for the period of 2000 - 2015 with regard to five main crops (winter wheat, maize, spring barley, soybean and sunflower); creation of a statistical crop capacity database at the regional and district levels. In addition, the paper considers spatial schematization of calculations and aggregation of agricultural crops productivity indicators obtained as a result of the WOFOST biophysical model application. It also outlines the scheme of crop capacity forecasting based on administrative units and the estimation of forecast accuracy for winter wheat crop capacity in administrative districts of Kiev region. The link to the website containing results of operation of the CGMS-Ukraine system is as follows: http:/entln.uhmi.org.ua/case/CGMS.


Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1245
Author(s):  
Kun Du ◽  
Yunfeng Qiao ◽  
Qiuying Zhang ◽  
Fadong Li ◽  
Qi Li ◽  
...  

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.


2021 ◽  
Vol 20 (6) ◽  
pp. 1687-1700
Author(s):  
Li-chao ZHAI ◽  
Li-hua LÜ ◽  
Zhi-qiang DONG ◽  
Li-hua ZHANG ◽  
Jing-ting ZHANG ◽  
...  

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2416
Author(s):  
Ming Lei ◽  
Yuqian Zhang ◽  
Yuxuan Dang ◽  
Xiangbin Kong ◽  
Jingtao Yao

Agricultural water management is a vital component of realizing the United Nation’s Sustainable Development Goals because of water shortages worldwide leading to a severe threat to ecological environments and global food security. As an agro-intensified irrigation area, the North China Plain (NCP) is the most important grain basket in China, which produces 30%–40% of the maize and 60%–80% of the wheat for China. However, this area has already been one of the largest groundwater funnels in the world due to long-term over-exploitation of groundwater. Due to the low precipitation during the growing period, winter wheat requires a large amount of groundwater to be pumped for irrigation, which consumes 70% of the groundwater irrigation. To alleviate the overexploitation of groundwater, the Chinese government implemented the Winter Wheat Fallow Policy (WWFP) in 2014. The evaluation and summarization of the WWFP will be beneficial for improving the groundwater overexploitation areas under high-intensity irrigation over all the world. So far, there have been few attempts at estimating the effectiveness of this policy. To fill this gap, we assessed the planting area of field crops and calculated the evapotranspiration of crops based on remote-sensed and meteorological data in the key area—Hengshui. We compared the agricultural water consumption before and after the implementation of this policy, and we analyzed the relationship between changes in crop planting structure and groundwater variations based on geographically weighted regression. Our results showed the overall classification accuracies for 2013 and 2015 were 85.56% and 82.22%, respectively. The planting area of winter wheat, as the most reduced crop, decreased from 35.71% (314,053 ha) in 2013 to 32.98% (289,986 ha) in 2015. The actual reduction in area of winter wheat reached 84% of the target (26 thousand ha) of the WWFP. The water consumption of major crops decreased from 2.98 billion m3 of water in 2013 to 2.83 billion m3 in 2015, a total reduction of 146 million m3, and 88.43% of reduced target of the WWFP (166 million m3). The planting changes of winter wheat did not directly affect the change of shallow groundwater level, but ET was positively related to shallow groundwater level and precipitation was negatively related to shallow groundwater levels. This study can provide a basis for the WWFP’s improvement and the development of sustainable agriculture in high-intensity irrigation areas.


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