Loading...

Table of Content

    20 July 2019, Volume 40 Issue 07
    Correspondence and Shifting Analysis for the Winter Wheat Growing Period before Winter and Solar Terms in the North China Plain under Climate Change Background
    ZHANG Yue, HU Qi, HE Hua-yun, PAN Xue-biao, MA Xue-qing, HUANG Bin-xiang, WANG Jing
    2019, 40(07):  411-421.  doi:10.3969/j.issn.1000-6362.2019.07.001
    Asbtract ( 834 )   PDF (11146KB) ( 829 )  
    References | Related Articles | Metrics
    Based on the 1961-2017 surface data from 55 meteorological stations in the winter wheat planting area of North China Plain, the accumulated temperature required for winter wheat wintering period was selected as the index to analyze the spatial and temporal distribution and variation characteristics of the solar terms of wintering period and sowing period. This study have used the longevity formula and the method of climatic tendency rate. The correspondence and deviation between winter wheat related agricultural activities and solar terms were also discussed. The wintering period of winter wheat in North China showed a trend of significant delay (P<0.05) in recent 57 years. It was delayed by about 3.7 days. The solar term of the sowing time for winter wheat in North China Plain is gradually postponed from north to south. Compared with P1 period (1961-1990), the boundary of sowing period of winter wheat in P2 period (1991-2017) moved northward significantly. Under the background of climate change, there is a certain deviation between winter wheat farming activities and 24 solar terms in North China Plain. The proverbs used to guide farming activities in some areas are no longer fully applicable. For example, the termination day of optimal sowing date of winter wheat in central Shandong Province was postponed from the third pentad of the Autumn Equinox to the first pentad of the Cold Dews. The latest sowing date of winter wheat in northern Henan Province was postponed from the third pentad of the Cold Dews to the first pentad of Hoar-frost Falls.In this paper, agricultural activities were adjusted by studying the corresponding relationship between 24 solar terms and sowing date of winter wheat. In the future, we need to consider the effects of natural factors such as light, water and agronomic measures during the growth period of winter wheat, and scientifically guide agricultural production to adapt to climate change.
    Spatiotemporal Variations of Extreme Temperature Indices in Different Climatic Zones of China over the Past 60 Years
    ZHANG Da-ren, ZHENG Jing, FAN Jun-liang, FANG Zhi-chao, JI Qing-yuan, YUAN Ye-zi, LIU Wen-fei
    2019, 40(07):  422-434.  doi:10.3969/j.issn.1000-6362.2019.07.002
    Asbtract ( 459 )   PDF (7719KB) ( 1130 )  
    References | Related Articles | Metrics
    Based on daily maximum and minimum temperature data during 1956-2015 obtained from 200 weather stations, ten extreme temperature indices recommended by ETCCDI were used to study the temporal trends of extreme temperature indices and their spatial distribution in four climatic zones of China, with the help of Mann-Kendall test, Sen’s slope estimator and Pettitt test. The results showed that, (1) warm nights (TN90p) and warm days (TX90p) tended to increase significantly in China over the past 60 years, with a rate of 2.12 and 1.00d10y-1 (P<0.01), but cold nights (TN10p) and cold days (TX10p) tended to decrease significantly, with a rate of 1.44 and 0.70d10y-1 (P<0.01), respectively. For threshold indices, the change rate of frost days (FD0) was -2.84d10y-1 (P<0.01), but the change rates of summer days (SU25) and tropical nights (TR20) were 1.77 and 1.44d10y-1 (P<0.01), respectively. For duration indices, warm spell duration index (WSPI) and growing season length (GSL) significantly increased, but cold spell duration index (CSDI) showed no significant trend during the period of 1956-2015. (2) The increasing rates of cold extremes were greater than those of warm extremes. Further, faster increases were observed for nightly indices related to the minimum temperature (e.g. TN10p, TN90p and FD0), compared with the daytime indices related to the maximum temperature (e.g. TX10p, TX90p and WSDI). (3) The abrupt change years of temperature extremes mainly occurred in the 1980s and 1990s. The change rates of most temrepature extreme indices were more significant after the mid-1980s than those before the mid-1980s. (4) The change rates of extreme temperature indices varied greatly among different climatic zones, with the greatest decreases in cold extreme indices in the mountain plateau zone and the greatest increases in warm extreme indices such as SU25, TR20 and WSDI in the subtropical monsoon zone.
    Temporal and Spatial Evolution of Climate Dry and Wet Conditions in Ganzi in the Past 57 Years
    WANG Qing-li, HAN Yu-jiang, GUO Bin, WANG Ming-tian, RAN Wang-qun, CHEN Juan
    2019, 40(07):  435-443.  doi:10.3969/j.issn.1000-6362.2019.07.003
    Asbtract ( 336 )   PDF (2640KB) ( 605 )  
    References | Related Articles | Metrics
    Based on measured data from 1961 to 2017 in 18 national weather stations in Ganzi Tibetan Autonomous Prefecture, the monthly, seasonal and annual wetness index for Ganzi and its affiliated counties were counted according to the method described in Ecological quality Assessment Criteria of Meteorology.The spatial and temporal evolution characteristics of climate dry and wet were also analyzed in this study, which will provide scientific basis for drought prevention and mitigation and rational utilization of climate resources. The results showed: (1) the average wetness index of Ganzi in the past 57 years was between 0.67?1.33, the highest value was in 1965, and the lowest was in 1973. The seasonal average wetness index was between 0.07?1.86, the highest value occurred in summer, the second highest value occurred in autumn, and the lowest value occurred in winter; (2) The average wetness index of counties (cities) in Ganzi was between 0.23 and 1.73, which presented a large difference between the various regions.It seemed that the southeast and north was relatively humid and the southwest was relatively dry; (3) The annual climate change rate in Ganzi was 13.4mm·10y-1, the climatic tendency rate of the wetness index was -0.003·10y-1, and the climate tends to be weakly warm and dry. (4) The average wetness index of 2/3 counties (cities) in Ganzi was less than 1, which indicated that the seasonal drought characteristics was significant, and the ecological environment was fragile. Production practices should follow the principle of the combination of exploitation and protection. The drought prevention and mitigation, farmland water conservancy construction, and ecological restoration also should be strengthened during the production process.
    Research Progress in Application of Crop Growth Models
    SUN Yang-yue, SHEN Shuang-he
    2019, 40(07):  444-459.  doi:10.3969/j.issn.1000-6362.2019.07.004
    Asbtract ( 1288 )   PDF (792KB) ( 2347 )  
    References | Related Articles | Metrics
    The crop growth model can not only simulate the dynamic growth of crops on a single point scale, but also evaluate the relationship between crop growth status and environmental factors from a systematic perspective. This paper reviews latest works related to crop growth model, with particular focuses on the research of climate change to agricultural production and application of crop growth model at regional scale. In addition, this paper summarizes the current research on the development of agricultural decision support systems(DSS) with crop growth models as the core. The research is intended to promote crop growth models to be more widely used in researches on ecology, agriculture, regional climate resources and climate change filed. Research results show that the crop growth model is widely and deeply used in China and abroad. Under the background of climate change, the application research of crop growth model to the impact of historical period climatic conditions and agrometeorological disasters on crop production status and yield has been extensive and relatively mature. Using global climate models (GCMs) or regional climate models (RCMs) to construct future climate change scenarios, coupled with crop growth models, has evolved into an important tool for assessing the impact of future climate change on agricultural production. By integrating and consolidating multi-crop growth model, multi-climate model ensemble simulation and optimizing climate simulation data correction methods, the uncertainty of climate change impact assessment on agricultural production can be effectively reduced. The remote sensing data assimilation technology can apply the site model to the regional scale to evaluate the impact of different meteorological factors on agricultural production, broaden the application scale range of the crop growth model and effectively improve the accuracy of crop yield estimation. The research and application of agricultural decision support system with crop growth model as the core is more and more diversified, and it is an important tool to assist agricultural production management and decision-making. However, due to the complexity of crop ecosystems, there are still great uncertainties in crop growth model simulation results. In the future, the exploration of crop growth and process coupling mechanism needs to be strengthened in order to improve the model and promote it more widely used.
    Effect of Waterlogging on Photosynthetic Characteristics of Wheat Flag Leaves during Grain Filling and Recovery Effect of Water Stress Relief
    WANG Hong-jie, LI Wen-yang, SHAO Qing-qin, XU Feng, ZHANG Cong-yu, YAN Su-hui
    2019, 40(07):  460-466.  doi:10.3969/j.issn.1000-6362.2019.07.005
    Asbtract ( 285 )   PDF (429KB) ( 583 )  
    References | Related Articles | Metrics
    In this study, the effects on photosynthetic characteristic of flag leaf under the treatments at 6 days and 9 days during waterlogging and 3 days after relief of water stress were investigated using wheat cultivar Yannong 19 in pot culture both in 2015 and in 2016, respectively. The results showed that the net photosynthetic rate of wheat leaves at the filling stage was significantly reduced by waterlogging with differences in the extent of decline among all the treatments. The net photosynthetic rates (NPRs) of flag leaf after 6 days waterlogging (WL6) and 9 days waterlogging (WL9) were 82.0% and 71.5% of those of control treatment (CK), respectively. The NPRs of flag leaf under WL6 treatment were recovered after the water stress relieved for three days with the consistent performance of CK, while the NPR of flag leaf under WL9 treatment was recovered to 86.3% compared to that of CK with a significant difference. The SPAD values of wheat flag leaf showed a consistent trend with that of the NPR under waterlogging treatment after the water stress was relieved for three days. After the water stress was relieved, the photosynthetic characteristics of WL6 could be recovered better than those of WL9. During waterlogging, the intercellular CO2 concentration of WL6 was significantly higher than that of the control, indicating that the NPR decrease of flag leaf after 6 days of waterlogging was due to non-stomatal factors. While the stomatal conductanceon leave under WL9 treatment decreased significantly, there was no significant change in intercellular CO2 concentration. The results suggested that the low photosynthesis of wheat leaves after waterlogging for 9 days was mainly affected by non-stomatal factors regardless of the stomatal opening.
    Improvement and Prediction of Cold Freezing Injury Index of Korla Fragrant Pear Trees in Winter
    ZHANG Shi-ming,GU Jun-ming
    2019, 40(07):  467-473.  doi:10.3969/j.issn.1000-6362.2019.07.006
    Asbtract ( 452 )   PDF (694KB) ( 713 )  
    References | Related Articles | Metrics
    Using the daily weather observation data and atmospheric circulation data from Korla weather station from 1981 to 2017, four meteorological factors(including extreme minimum temperature in winter, negative accumulated temperature of daily average temperature ≤-10℃, the minimum temperature days ≤-15℃, number of days with snow depth ≥5cm)with significant effects on winter freezing injury of pear trees were synthesized into a comprehensive freezing injury index by Principal Component Analysis(PCA). Then, using the index as the prediction object, the Pearson correlation analysis and stepwise regression method were used to select the atmospheric circulation factor which was significantly correlated with the comprehensive frost damage index as the independent variable, and the comprehensive frost damage index prediction model was established. Finally, the model effect was tested by using data from 1981 to 2017. The results showed that the comprehensive freezing injury index reflected the freezing injury of Korla pear trees over these years, and the smaller the index value, the more serious the degree of freezing injury. Combined with historical disaster records, definition of comprehensive freezing injury index >-0.42 was no freezing injury, -0.91 to -0.42 was slight freezing injury, -1.8 to -0.92 was moderate freezing injury, and comprehensive freezing injury index