Effects of Different Nitrogen Rates on Open-Field Vegetable Growth and Nitrogen Utilization in the North China Plain

2004 ◽  
Vol 35 (11-12) ◽  
pp. 1725-1740 ◽  
Author(s):  
Qing Chen ◽  
Xiaolin Li ◽  
Dieter Horlacher ◽  
Hans-Peter Liebig
Keyword(s):  
Open Field ◽  
North China Plain ◽  
North China ◽  
Nitrogen Utilization ◽  
Vegetable Growth ◽  
The North ◽  
The North China Plain ◽  
Nitrogen Rates

scholarly journals Open Field Simulating Nocturnal Warming on Summer Maize Performance in the North China Plain

Agronomy ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 992
Author(s):  
Junfang Niu ◽  
Junxia Feng ◽  
Xiying Zhang ◽  
Suying Chen ◽  
Liwei Shao
Keyword(s):  
Open Field ◽  
North China Plain ◽  
North China ◽  
Carbon Allocation ◽  
Soil Surface ◽  
Grain Filling ◽  
Maize Yield ◽  
Negative Effects ◽  
The North ◽  
The North China Plain

Climate changes show asymmetrical warming, and warming is typically greater at night than during the day. To understand how nocturnal warming (NW) affects the performance of maize (Zea mays L.), an open-field experiment with a free air temperature increase (FATI) facility was conducted for three seasons during 2014 to 2016 at Luancheng eco-agro-experimental station on the North China Plain (NCP). Three nocturnal warming scenarios were set up: the entire growing period (T1, from V4 to maturity), only the vegetative stages (T2, from V4 to a week presilking) and the reproductive stages (T3, from a week presilking to R6). The treatment without NW was the control. Maize lodged seriously in 2015 due to heavy rainfall combined with strong winds, and the experiment failed. The results from 2014 and 2016 were analyzed in this study. During the experimental duration, the average nocturnal temperature was increased by approximately 3.6 and 3.3 °C at 150 cm height and 2.0 and 1.7 °C at the soil surface during the vegetative stages. The corresponding increases were 2.1 and 2.5 °C and 0.7 and 1.2 °C at the soil surface during the reproductive stages in 2014 and 2016, respectively, as compared with that of the CK treatment. NW during the whole growth period significantly decreased maize yield for the two seasons. Treatment T2 had a smaller impact on maize yield than T1 and T3. The silking stage was delayed by 2 days in 2014 and 2016 under T1. As a result, presilking duration and VT-R1 interval were prolonged by 1–2 days; and the postsilking duration were shortened by 1–3 days under T1. The soil moisture in the warmed plots was slightly lower than that in the control plots in the 2014 and during the stages before the earlier grain-filling stages in 2016, but NW decreased soil water content greatly at the later grain-filling stages in 2016, which caused the fast green leaf senescence and exacerbated the negative effects of NW on maize yield. NW for the whole growth duration (T1) significantly decreased seed weight and harvest index. NW increased leaf nighttime respiration rate in both seasons. No significant effects of NW on ear leaf net photosynthesis, leaf area, and specific leaf weight at early grain-filling stage were observed, irrespective of the warming stage and season. The results suggested that reproductive stages were more sensitive to NW compared to vegetative stages under the growing conditions of NCP. The negative effects of NW were worsened in dry seasons. The reduction in maize yield with nocturnal warming was driven by the reduction in the aboveground carbon allocation from shoot to grain during postanthesis stage.

ROx Budgets and O3 Formation during Summertime at Xianghe Suburban Site in the North China Plain

2021 ◽  
Author(s):  
Min Xue ◽  
Jianzhong Ma ◽  
Guiqian Tang ◽  
Shengrui Tong ◽  
Bo Hu ◽  
...  
Keyword(s):  
North China Plain ◽  
North China ◽  
The North ◽  
The North China Plain ◽  
Suburban Site

scholarly journals Improving the Resolution and Accuracy of Groundwater Level Anomalies Using the Machine Learning-Based Fusion Model in the North China Plain

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 46
Author(s):  
Gangqiang Zhang ◽  
Wei Zheng ◽  
Wenjie Yin ◽  
Weiwei Lei
Keyword(s):  
Machine Learning ◽  
Data Fusion ◽  
Groundwater Level ◽  
North China Plain ◽  
North China ◽  
Gradient Boosting ◽  
Fusion Model ◽  
The North ◽  
The North China Plain ◽  
Prediction Module

The launch of GRACE satellites has provided a new avenue for studying the terrestrial water storage anomalies (TWSA) with unprecedented accuracy. However, the coarse spatial resolution greatly limits its application in hydrology researches on local scales. To overcome this limitation, this study develops a machine learning-based fusion model to obtain high-resolution (0.25°) groundwater level anomalies (GWLA) by integrating GRACE observations in the North China Plain. Specifically, the fusion model consists of three modules, namely the downscaling module, the data fusion module, and the prediction module, respectively. In terms of the downscaling module, the GRACE-Noah model outperforms traditional data-driven models (multiple linear regression and gradient boosting decision tree (GBDT)) with the correlation coefficient (CC) values from 0.24 to 0.78. With respect to the data fusion module, the groundwater level from 12 monitoring wells is incorporated with climate variables (precipitation, runoff, and evapotranspiration) using the GBDT algorithm, achieving satisfactory performance (mean values: CC: 0.97, RMSE: 1.10 m, and MAE: 0.87 m). By merging the downscaled TWSA and fused groundwater level based on the GBDT algorithm, the prediction module can predict the water level in specified pixels. The predicted groundwater level is validated against 6 in-situ groundwater level data sets in the study area. Compare to the downscaling module, there is a significant improvement in terms of CC metrics, on average, from 0.43 to 0.71. This study provides a feasible and accurate fusion model for downscaling GRACE observations and predicting groundwater level with improved accuracy.

scholarly journals The water-saving potential of using micro-sprinkling irrigation for winter wheat production on the North China Plain

2021 ◽  
Vol 20 (6) ◽  
pp. 1687-1700
Author(s):  
Li-chao ZHAI ◽  
Li-hua LÜ ◽  
Zhi-qiang DONG ◽  
Li-hua ZHANG ◽  
Jing-ting ZHANG ◽  
...  
Keyword(s):  
Winter Wheat ◽  
North China Plain ◽  
North China ◽  
Water Saving ◽  
Wheat Production ◽  
The North ◽  
The North China Plain
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