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    Chinese Journal of Agrometeorology    2020, 41 (12): 1-.  
    Abstract401)      PDF(pc) (208KB)(54)       Save
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    Temporal and Spatial Characteristics of Drought in China under Climate Change
    ZHAO Hai-yan, ZHANG Wen-qian, ZOU Xu-kai, ZHANG Qiang, SHEN Zi-qi, Mei Ping
    Chinese Journal of Agrometeorology    2021, 42 (01): 69-79.   DOI: 10.3969/j.issn.1000-6362.2021.01.007
    Abstract201)      PDF(pc) (5677KB)(194)       Save
    Droughts are the most frequent natural hazards which have caused the second most economic loss in China. In recent years, the trend of annual air mean temperature has been gradually decreased and precipitation has been increased in China. The research of temporal and spatial characteristics of agricultural drought is focused on under new climate background. In order to adapt to climate change and take actions for government and farmers, the spatial patterns, frequency, long-term trends and stage variability characteristics of agricultural drought were analyzed using provincial drought disaster data from 1951 to 2018. The results showed that: (1) the mean area affected by drought, area of drought disasters, area percentage affected by drought and area percentage of drought disasters were used to represent spatial characteristics. Area affected by drought and area of drought disasters were more serious in Inner Mongolia, Shanxi and Hebei province than those in other regions. (2) Based on Warning Grade of Agricultural Drought GB/T 34817−2017 and the definition of area affected by drought, extreme drought, severe drought and moderate drought were classified. The frequency of agriculture drought was more in Inner Mongolia, Shanxi and Shaanxi province than that in other regions. (3) Annual area affected by drought, area of drought disasters, area percentage affected by drought and area percentage of drought disasters were analyzed by fitting at least squares principle. Regression coefficients were used to analyze long-term trends of those four indices. Area affected by drought and percentage experienced decreasing trends in 16 provinces, while they showed increasing trends in most regions with area of drought disasters in 23 provinces and percentage in 27 provinces. (4)According to climate warming trends in China, nearly 70 years were divided into three stages, 1951−1984(stage I), 1985−1997(stage II) and 1998−2018(stage III). It was found that agriculture drought was comparatively less at stage I in China, and it was increasing apparently at stage II. Area affected by drought, area of drought disasters and area percentage affected by drought decreased widely, but area percentage of drought disasters was continued to increase at stage III. Above all, agricultural drought was severer and more frequent in the north of China than that in the south of China, so more attentions should be paid to defending agriculture drought in the north of China.
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    Chinese Journal of Agrometeorology    2021, 42 (05): 438-440.   DOI: 10.3969/j.issn.1000-6362.2021.05.008
    Abstract124)      PDF(pc) (1111KB)(46)       Save
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    Effects of Shading on the Carbon Emission Intensity of CH4 and N2O from Rice- Wheat Rotated Soil in Southern China
    MA Li , LOU Yun-sheng , YANG Xiao-jun, GOU Shang, LI Jun,  LI Rui , ZHANG Zhen
    Chinese Journal of Agrometeorology    2020, 41 (12): 747-760.   DOI: 10.3969/j.issn.1000-6362.2020.12.001
    Abstract112)      PDF(pc) (959KB)(109)       Save
    The solar radiation weakening is one of the main characteristics of climate change. It is still unclear concerning the impact of the solar radiation weakening on the emissionsof greenhouse gas (CH4 and N2O) and carbon emission intensity in rice-wheat soils. A field simulation experiment was conducted to investigate the emissions of greenhouse gases in rice-winter wheat rotation ecosystem and the changes in carbon emission intensity with field managements under shading conditions. The two-factorial experiment was adopted with 3 levels of shading intensities, i.e. control (CK, no shading), light shading (S1, 61.26% of shading rate) and heavy shading (S2, 83.65% of shading rate). The shading treatment was performed by covering the crop canopy with black sunshade net and periodically adjust the net hight to maintain the distance at 30 cm between the net and crop canopy. Field managements (water management/planting date) were set 2 levels, i.e. traditional flooding irrigation/conventional planting date (F/P; rice F, water depth 5cm; winter wheat P, planting time November 6, 2017) and moistening irrigation/late planting (M/L; rice M, anhydrous layer; winter wheat L, planting time November 13, 2017). The closed chamber method was used to measure the emission fluxes of CH4 and N2O from 8:00 am to 11:00 am at one-week interval. The tested soil was a hydromorphic paddy soil. The tested cultivars of rice and winter wheat were Nanjing 5055 and Sumai 188, respectively. The field experiment was performed at the Station of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing, Jiangsu prov., China. The results showed that, shading (S1, S2) significantly reduced the cumulative CH4 emission in rice-winter wheat rotation ecosystem under traditional flooding irrigation/conventional planting by 68.08% and 42.22%, and slightly increased the CH4 emission under moistening irrigation/late planting. Moistening irrigation /late planting significantly reduced the cumulative CH4 emissions by 15.6% to 86.61%. The shading significantly increased the cumulative N2O emissions from rice-winter wheat rotation ecosystem by 63.59% to 111.40% (P<0.05), and the cumulative N2O emissions were slightly reduced under traditional flooding irrigation/conventional planting. In terms of global warming potential, compared with no shading, shading significantly reduced the contribution of CH4 and N2O to the global warming potential in rice-winter wheat rotation ecosystem under traditional flooding irrigation/conventional planting date by 36.32% to 62.51%, but slightly increased under moistening irrigation/late planting. The global warming potential of CH4 and N2O under the moistening irrigation/late planting was reduced by 12.1% to 83.22%, compared with the traditional flooding/conventional planting. This study indicates that shading significantly increased the carbon emission intensity of CH4 and N2O in rice-winter wheat rotated soil, while moistening irrigation/late planting without shading significantly reduced the carbon emission intensity of CH4 and N2O, which ensured the yield and improved the ecological benefits.
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    Investigation of the Effects of Cold Weather on Fruit Setting Rate of Red Cartridge Kiwifruit in Western Guizhou
    CHI Zai-xiang, LUO Pei-fu, SUN Xiang, ZENG Xiao-shan, HU Qiu-ling, LI Xiu-ya , LONG Ru-yong
    Chinese Journal of Agrometeorology    2020, 41 (12): 807-813.   DOI: 10.3969/j.issn.1000-6362.2020.12.006
    Abstract111)      PDF(pc) (314KB)(105)       Save
    In the first ten days of April 2020, a long-term low temperature weather process occurred in western Guizhou, which led to a large number of flower and fruit drop of red cartridge kiwifruit which was in the period of flowering and fruit setting. In view of this to ascertain the effects of low temperature on fruit setting of red cartridge kiwifruit in early April 2020, we investigated the fruit setting rate of red cartridge kiwifruit in nineteen main planting areas of Western Guizhou from April 10th to 17th. And, combined with the data of the daily average temperature and minimum temperature from April 3th to 9th, the study analyzed the effects of cold weather on flowering and fruit setting of red cartridge kiwifruit in western Guizhou. In order to provide scientific basis for prevention and mitigation of low temperature disaster and take reasonable countermeasures, the low temperature conditions affecting the flower and fruit drop of red cartridge kiwifruit in Guizhou Province were found out. The results showed that the cold weather from April 3th to 8th caused serious flower and fruit drop of red cartridge kiwifruit during their flowering, pollination, fertilization and fruit setting stage. The highest rate of flower and fruit drop was 70% in Shunchang, Xinyao and Pugu, and the second is 64.5% in Shaomi, and the third is 63.3% in Houchang. The lowest rate of flower and fruit drop was 10% in Mugang, and the second is 29.5% in Dayong. Through analysing the first-flowering dates and the time of flowering and pollination, it was found that the earlier first-flowering dates, the longer time of flowering and pollination, the rate of flower and fruit drop was higher. Besides, it was found that the rate of flower and fruit drop of Hongyang varieties was higher than that of Donghong varieties. In the period of flowering, pollination, fertilization and fruit setting stage of red cartridge kiwifruit, it was found that when the daily average temperature<12℃ and the daily minimum temperature<10℃ last 3 days or more, or when the daily average temperature<15℃ and the daily minimum temperature<13℃ last 5 days or more, it would cause flower and fruit to fall. In production, spraying antifreeze, smoking and other measures can prevent low-temperature freezing injury, and reduce the impact of low-temperature weather on the flowering, pollination and fruit setting of red cartridge kiwifruit trees.
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    Risk Analysis of Spring Frost in Main Grape Producing Areas
    YUE Hui-xin, HE Yan-bo, JIANG Jian-fu, FAN Xiu-cai, ZHANG Ying, LIU Chong-huai,
    Chinese Journal of Agrometeorology    2021, 42 (03): 221-229.   DOI: 10.3969/j.issn.1000-6362.2021.03.006
    Abstract110)      PDF(pc) (1604KB)(122)       Save
    In recent years, spring frost occurred frequently in China, which had a serious impact on grape industry and became one of the main meteorological disasters endangering grape production. Based on the daily minimum temperature observation data of 607 meteorological stations in China from 1958 to 2019, the occurrence days, frequency, station number ratio and disaster risk of spring frost disaster in main grape producing areas were analyzed by using statistical and spatial analysis methods. The results showed that the average days and frequency of frost in different grape growing areas were very different in the past 60 years. The frequency and average number of frost occurrence in spring were the highest in northwest and southwest mountain regions, and the lowest in southern regions. The intensity of spring frost was obvious in different regions. The intensity index of light frost tended to be smaller from north to south, while that of medium frost and heavy frost were generally smaller. The spatial distribution characteristics of the disaster causing factor index in the main grape producing areas were generally higher than those in the southern regions. The high-risk areas were mainly distributed in the northwest region and the north-east region, and the risk-free areas were mainly distributed in the southern region. According to the results of risk zoning, it can provide scientific basis for disaster prevention in main grape producing areas.
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    CLDAS Drive Land Surface Model to Simulate Latent Heat Flux in China
    WANG Zhi-hui , SHI Chun-xiang , SHEN Run-ping , SUN Shuai, SHAN Shuai, HAN Shuai
    Chinese Journal of Agrometeorology    2020, 41 (12): 761-773.   DOI: 10.3969/j.issn.1000-6362.2020.12.002
    Abstract101)      PDF(pc) (11111KB)(325)       Save
    The correlation coefficient (R), the average deviation between (ME), root mean square error (RMSE), and coefficient of Nash (NSE) were calculated between the three land surface model from the land data assimilation system of the China Meteorological Administration (CLDAS CLM, CLDAS Noah and CLDAS-Noah-MP) and global land surface assimilation system (GLDAS-Noah) and the flux tower standing observation data, and the accuracy evaluation in terms of different time scales and the different underlying surface were given. The results show that the diurnal variation and annual variation trends and peak time of the single peak can be simulated according to the simulation results of the four models. The peak of diurnal variation generally occurs at 14:00, the annual variation peak occurs in summer, and the numerical simulation effect is slightly worse in irrigated or freezing-thawing farmland and wetland in spring. On the scale of the hour, day, and month, the simulation of models driven by CLDAS is generally better than that of GLDAS. The mean R-value of simulation by models driven by CLDAS is higher than that of GLDAS-NOAH, which is 0.07, 0.08, and 0.02, respectively. The mean value of RMSE is lower than that of GLDAS -NOAH, and the errors are reduced by 6.6, 5.5, and 2.3W·m−2, respectively. The simulation of the model will change along with the time scale and the underlying surface properties. From the hour to the day to the month scale, the simulation goes through a process of first getting worse and then getting better. The simulation on the month scale is the best, in which Noah-MP performs well, with R value of 0.88, RMSE of 20.8 W·m−2, and NSE of 0.58. Four model simulation results under different performance have the same certain commonality that simulation in mixed forest and coniferous forest were overestimated and that in the rest underlying surface are underestimated. Although no models work well for all underlying surfaces, CLM performs best in stations covered by Gobi, mixed forest, and coniferous forest, Noah performs best in desert and cropland, and Noah-MP performs best in meadow, grassland, and wetland.
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    Fuzzy Comprehensive Evaluation and Model Establishment of the Effect of High Temperature in the Seedling Stage on the Nutritional Quality of Strawberry Fruit
    XU Chao, GAO Rui, WANG Ming-tian, YANG Zai-qiang , HAN Wei, ZHENG Sheng-hua
    Chinese Journal of Agrometeorology    2020, 41 (12): 785-793.   DOI: 10.3969/j.issn.1000-6362.2020.12.004
    Abstract100)      PDF(pc) (699KB)(128)       Save
    In order to study the effect of high temperature at seedling stage on the intrinsic quality of strawberry fruits in the greenhouse, and then to conduct comprehensive evaluation of different experimental treatments to establish a comprehensive evaluation model of intrinsic quality of strawberry fruits. In 2018 and 2019, strawberry seedlings were stressed with different high temperature (32, 35, 38 and 41℃) and different stress days (2, 5, 8 and 11d), and then transplanted to Venlo glass greenhouse for normal cultivation experiments, with normal greenhouse cultivation as a control. Based on the differences in fruit intrinsic quality indicators under each treatment, the comprehensive score of each experimental treatment determined by the fuzzy comprehensive evaluation method, and by analyzing the relationship between the comprehensive score and different stress temperatures and stress days, a comprehensive evaluation model of fruit intrinsic quality was constructed. Among them, the data obtained in 2018 were used for model construction, and in 2019 were used for model verification. The results showed that the effects of different stress days on the vitamin C, soluble sugar content, titratable acid content and anthocyanin of strawberry fruits were different under high temperature. The weights of the four intrinsic qualities of strawberries are titratable acid (0.33)> anthocyanin (0.25)> vitamin C (0.23)> soluble sugar (0.19). The score of the fuzzy comprehensive evaluation showed that the comprehensive score of the intrinsic quality of the fruit was highest at 8 days and 11 days at 35℃, and 2 days and 5 days at 38℃ (all greater than 0.8). The comprehensive fruit quality scores were medium (between 0.6 and 0.8) at 2d and 5d at 35℃ and 32℃ treatment, and the lowest comprehensive fruit quality scores (between 0 and 0.6) under 38℃ treatments for 8 days and 11 days and 41℃ treatment. The determination coefficients (R2) of the built-in comprehensive quality model for the simulated and measured values ​​of greenhouse strawberry comprehensive quality were 0.86, the root mean square error (RMSE) was 0.01, and the relative error (RE) was 0.06%. Therefore, a certain degree of high temperature treatment (within 11 days at 35℃ or within 5 days at 38℃) in the greenhouse strawberry seedling stage will help to improve the comprehensive intrinsic quality and the model established can predict the comprehensive intrinsic quality of the greenhouse strawberry under high temperature at the seedling stage, which has a guiding significance for the regulation of the strawberry greenhouse temperature environment.
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    Studies on the Difference of Observed Yield and Statistical Yield of Winter Wheat
    LIU Wei, MENG Cui-li, SONG Ying-bo
    Chinese Journal of Agrometeorology    2021, 42 (02): 123-133.   DOI: 10.3969/j.issn.1000-6362.2021.02.004
    Abstract100)      PDF(pc) (4789KB)(74)       Save
    The difference of interdecadal variations, coefficient of variation and tendency ratio between the observed yield of winter wheat from 123 agrometeorological observation stations and the statistical yield of winter wheat at county level where the observation station was located from 1991 to 2017. The proportion of average winter wheat planting area in each county in five years(2006−2010) was used as the weight factor to integrate the observed yield and statistical yield at province level, at the same time using the announced yield at province level from National Bureau of Statistics. The interdecadal variations and tendency ration of three different yields at provincial level were compared and analyzed. The results showed that:(1) the number of high yield counties increased significantly, and low yield counties decreased significantly in both observed yield and statistical yield counties. The two yield were both high yield years in the 2010s, and the difference between the two reached peak value in the 2000s. (2) The coefficient of variation of observed yield at the county scale was higher than the statistical yield. The coefficient of variation of statistical yield in 49 counties were less than 0.20 and only 8 were greater than 0.40, while 72 statistical yield counties were less than 0.20 and only 9 were greater than 0.30. The coefficient of variation of statistical yield in all counties in Xinjiang and Shandong provinces were less than 0.30. (3) The tendency ratio of 73 observed yield counties showed a significant increase mostly concentrated in the major producing provinces such as Hebei, Henan, Shandong, Jiangsu, and Anhui; and 100 statistical yield counties showed the same significant increase. The tendency ratio of observed and statistical yield in 72 counties passed the significance test at the same time. (4) The 2000s were the high yield years for both observed and statistical yield at provinces level and 1990s were the low yield years. The average of the observed yield in every 10 years was higher than the average of the statistical yield in Shandong, Anhui, Hebei, Jiangsu, Shaanxi and Shanxi province. (5) Eight provinces had passed the significant test on tendency ration of the observed yield at the provincial level except for Xinjiang and Shanxi province. While tendency ration of the statistical yield and the announced yield in all provinces had passed the significant test and the yield growth was positive. In general, the winter wheat yield series based on the observed yield could provide a new data source for yield forecast.
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    Evaluation of Potential Climatic Production of Apple during the Possible Growing Period at Zhaotong, Yunnan across Cool Highland of Southwest China
    LIU Yuan, LIU Bu-chun, MA Jun, CHENG Cun-gang, WANG Ke-yi, MAO Liu-xi, HE Yan-bo,
    Chinese Journal of Agrometeorology    2021, 42 (02): 87-101.   DOI: 10.3969/j.issn.1000-6362.2021.02.001
    Abstract99)      PDF(pc) (1740KB)(109)       Save
    Based on the daily meteorological data (1958−2019), the statistical production data (1978−2018) and the observed planting data of apple (2010−2018) at Zhaotong in Yunnan, the change of agricultural climatic resources and meteorological disaster were analyzed, while the local climatic potential production on apple was estimated using linear trend analysis and step by step correction. The aim of this paper can make more efficient and rational use of agricultural climate resources and scientifically guide to the apple industry layout. The results showed that: (1) during 1958−2019, the duration days of frost-free period and stable passing through 10℃ significantly increased by 3.5 and 4.5 days, respectively. Theoretically, the duration can match the apple needs. However, the starting date of flower bud expansion and mature were more advanced than the last frost date and the ending date of stable passing through 10℃; (2) According to the actual phenology of apple at Zhaotong from 2010 to 2018, we calculated the most possibility phenological from the starting date of stable passing through 3℃ and the ending date of stable passing 13℃.So in this period of 1958−2019, average minimum temperature, average temperature and maximum temperature were 11.8, 16.1 and 22.6℃ respectively, with different increase rate of 0.1, 0.04 and 0.05℃·10y−1. The average daily temperature range was 10.89℃ with decreased rate of 0.2℃·10y−1. The precipitation and sunshine hours decreased with 1.0mm·10y−1 and 6.7h·10y−1, respectively; (3) In the past 62 years, the risk of low temperature during flowering period was less, which was not the main agricultural meteorological disaster at Zhaotong. The risk of continuous rain was higher from June to September, which occur in the key growth period of apple; (4) The maximum theoretical yield of apple was about 100t·ha−1. With the restrictions of temperature and water, the production potential of light temperature and climate accounted for 83.0% and 76.0% of the photosynthetic production potential, respectively. However, the actual apple yield and the statistical yield across the whole county were only 35% and 10% of the photosynthetic production potential. With the development of technology and breeding of varieties, the gap is gradually narrowed. Generally, the meteorological conditions at Zhaotong can fully meet the needs of apple growth and development. Through the application of reasonable and efficient planting techniques and the full excavation of agricultural climate resources, the difference in apple yield can be further reduced and the quality of apple can be improved.
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    Dynamic Modeling and Prediction of Soil Moisture Based on Real-Time Water Content Data
    WANG Tie-ying, WANG Yang-ren, ZHAN Guo-long, NIU Shao-qing, YAO Li
    Chinese Journal of Agrometeorology    2021, 42 (01): 13-23.   DOI: 10.3969/j.issn.1000-6362.2021.01.002
    Abstract96)      PDF(pc) (492KB)(107)       Save
    Real-time and accurate prediction of moisture content is to carry out irrigation forecasts, and to achieve precise management of farmland water, which is an important measure to improve water efficiency. Based on the principle of water balance in the root zone (0−60cm soil layer), the crop transpiration and water flux at the lower interface of the root zone are linearized by using the Taylor series. On this basis, a dynamic soil moisture prediction model was constructed with the real-time average soil moisture content of the root zone as an independent variable. The real-time monitoring data (soil moisture content at 30cm and 60cm below the ground surface) of the wireless soil moisture monitoring system (including three monitoring points) in Xilv Village, Wuqing District, Tianjin City are used, and 5 days, 10 days, 15 days and 20 days are selected as the modeling series length respectively, and regression analysis is performed to determine the model parameters. The prediction accuracy of soil moisture was analyzed, using the two forecast periods of 10 days and 15 days. The results showed that: (1)the real-time prediction model fits well, and the deterministic coefficients under the condition of the three modeling series length can above 0.80 (the number of samples are all greater than 550).(2) The relative error of 15 days modeling series is the smallest.(3) Under the conditions of 15 days modeling series length, 15 days prediction period, and 10% relative error limit value, the moisture prediction pass rates of the three monitoring points reached 98%, 100% and 89%, respectively. It can be seen that the real-time moisture prediction model proposed by the research has high prediction accuracy, which is convenient for modeling and analysis, and provides a new method for soil moisture prediction.
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    Chinese Journal of Agrometeorology    2021, 42 (07): 616-619.   DOI: 10.3969/j.issn.1000-6362.2021.07.008
    Abstract96)      PDF(pc) (1218KB)(34)       Save
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    Evaluation of the Ability of Statistical Downscaling Dataset from the CMIP5 Global Climate Models to Extreme Temperature Indices over Liaoning Province
    PANG Jing-yi, LIU Bu-chun, LIU Yuan, QIU Mei-juan, WANG Ke-yi
    Chinese Journal of Agrometeorology    2021, 42 (05): 351-363.   DOI: 10.3969/j.issn.1000-6362.2021.05.001
    Abstract95)      PDF(pc) (9803KB)(110)       Save
    Liaoning Province is one of the main grape production areas in China. Due to the increasing of temperature and the frequent occurrence of extreme temperature, it has a noticeable impact on the planting and production of grapes in Liaoning. Based on extreme temperature indices, Global Climate Models(GCM) are evaluated and the model with the best simulation effect in the study area are selected. It is helpful to improve the accuracy of future climate resource and disaster risk analysis. In this paper, the observation meteorological daily data during 1971−2010 was used, including 32 stations across Liaoning Province. 31 models in the CMIP5 climate downscaling dataset were assessed the simulation performance about the spatio-temporal variation characteristics of the extreme temperature indices in Liaoning Province (yearly and seasonally). And the locations of the meteorological stations were completely consistent with that of the model stations. After using SS/M2 indices and MR comprehensive rating, the best model was selected. Seven extreme temperature indices, including mean maximum temperature(TXm), mean minimum temperature(TNm), frost days(FD0), summer days (SU25), minimum minimum temperature(TNn), maximum maximum temperature(TXx) and the range of extreme temperatures(ETR), were adopted to investigate the change of extreme temperature. There were the following conclusions: for the indices representing the characteristics of mean temperature, the performance of all models were better and closest to the observed values; For the indices representing continuous extreme temperature events, the simulated results of all models were ordinary; And for indices representing extreme temperature, the simulation results were very different from the observation values. Since there was no consistency in the ranking of extreme temperature indices among the different time and space scales, the three models with the best simulation ability were MPI-ESM-LR, GFDL-ESM2M and MIROC-ESM-Chem introduced by MR index. The three models were the first choice in this paper. Comparing the error, the results of the preferred model ensemble averages were significantly better than that of others. It is helpful to use the selected models to predict the future change of agricultural climate resources and to analyze disaster risks across Liaoning Province. It can help seek advantages and avoid disadvantages and reduce disaster losses.
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    Thought on Statistics Methods of Temperature in the Hottest and Coldest Month-Long Periods
    Erkejan HOYHAZI, JIANG Hui-fei , DAI An-ran
    Chinese Journal of Agrometeorology    2021, 42 (08): 693-702.   DOI: 10.3969/j.issn.1000-6362.2021.08.007
    Abstract94)      PDF(pc) (468KB)(71)       Save
    The hottest and coldest month-long periods' temperatures are common indicators of Agro-climatical division. Commonly the hottest/coldest period is replaced by the full month of July/January directly, but this fixed full month is not an accurate reflection of the actual hottest /coldest period. The hottest/coldest period of the year changes in temperatures and starting to end dates every year. In this paper, the length of the month-long period was set to be 31 days, as the common hottest and coldest months, July and January, are 31 days long. By using the daily temperature data from 1951 to 2018, collected at Changde weather station in Hunan province, the temperature of the hottest/coldest 31-day period was calculated using moving average approaches.  The results showed that, (1)the hottest period spans from late June to early September, and the average hottest 31-day period was from mid-July to mid-August. Comparing the average hottest 31-day period and the full months of July and August with the actual highest 31-day period temperatures, the average temperature error was 0.5℃, 0.9℃, and 1.7℃ colder, respectively. (2) The coldest period spanned from early December to mid-March, and the average coldest 31-day period is from early January to early February. Compared to the actual coldest 31-day period, the temperatures of the average coldest 31-day period and the full months of January and February were 1.0℃, 1.1℃, and 2.9℃ warmer than the temperature of the actual month-long period, respectively. (3) With a temperature error within 1.0℃ considered to be acceptable, the average hottest 31-day period' s average temperature was 90% accurate in calculating the actual hottest 31-day period' s average temperature while using July' s temperature is only 61.2% accurate, which demonstrated that the average hottest 31-day period was more accurate than July. (4) With a temperature error within 2.0℃ and temperature accuracy above 80% considered to be acceptable, the effect during the average coldest 31-day was slightly better than January. In summary, the temperature error of the average 31-day hottest/coldest period was less than these of July/January, and the accuracy is the opposite. Therefore, it is recommended that when estimating the temperature of the hottest/coldest month-long period to not use the fixed full month of July/January but instead use the average hottest/coldest 31-day period while still taking into consideration in the adjustments from the actual temperature.
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    Estimation of Soil Organic Carbon and Total Nitrogen Storages under Conservation Tillage as Influenced by Sampling Depths and Calculation Methods
    GAO Qi-qi, ZHANG Wei, MA Li-xiao, REN Tu-sheng, ZHANG Ai-ping, LI Gui-chun, HU Zheng-jiang, DU Zhang-liu
    Chinese Journal of Agrometeorology    2021, 42 (01): 1-12.   DOI: 10.3969/j.issn.1000-6362.2021.01.001
    Abstract93)      PDF(pc) (470KB)(105)       Save
    The objectives of this study were to investigate the profile distribution and accumulation characteristics of soil organic carbon (SOC) and total nitrogen (TN) under different tillage treatments, and further to compare the effects of sampling depths and calculation methods on the evaluation of SOC and TN storages. Two field experiments were established at the Shandong Huantai (5 years) and Hebei Luancheng (17 years) sites. The experiments included three tillage treatments (with residue): conventional tillage (CT), rotary tillage (RT) and no-tillage (NT). Soil samples were collected down to 60 and 50cm depths at Huantai and Luancheng site respectively. Soil bulk density (b) and the distribution of SOC and TN concentrations were determined. The SOC and TN storages were calculated by the fixed depth (FD) and equivalent soil mass (ESM) methods. The results showed that soil depth significantly affected the soil b, the concentrations and storages of SOC and TN (P<0.001). Compared with CT, NT enhanced SOC and TN storages in the top layer, and increased the stratification ratio (SR) of SOC and TN concentrations, though the SR value of SOC at Luancheng site was not significant. RT (cf. CT) increased the storages of SOC and TN in the top layer and the SR value of TN concentration at the Luancheng site. Specifically, at the Huantai site, the SOC and TN storages under NT were 29% and 30% higher than that of CT in the 0−5cm soil layer (P<0.05), but were 8% and 10% lower in the 0−60cm soil profile. At the Luancheng site, the SOC storage in the NT and RT was higher by 10% and 14% than CT; but there was no significant differences in SOC and TN storages between tillage treatments in the deeper profiles (i.e., ≥20cm). Due to the varied soil b between the treatments in the surface layer, the FD method overestimated the SOC and TN storages in the NT soil at the Huantai site, but underestimated them at the Luancheng site. Therefore, to accurately assess the SOC sequestration induced by tillage conversion, the ESM instead of FD method was recommended to calculate SOC storages together with the "deeper sampling" strategy (≥30cm). Our study implicates that although conservation tillage has positive effect on soil quality, the potential for mitigating climate change through SOC sequestration should not be overestimated.
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    Analysis of the Change of Agricultural Heat and Precipitation Resources Based on Grid Revision of GCM Outputs in Hainan Island
    LI Ning, BAI Rui, LI Wei, CHEN Miao, YANG Gui-sheng, CHEN Xin, FAN Chang-hua, ZHANG Wen
    Chinese Journal of Agrometeorology    2021, 42 (06): 447-462.   DOI: 10.3969/j.issn.1000-6362.2021.06.001
    Abstract92)      PDF(pc) (23709KB)(264)       Save
    Tropics are more fragile to climate change, especially in tropical island. It’s has not been investigated the change of agricultural heat and precipitation resources in future in tropical island like Hainan island, China. Because there are a lot of space biases between the raw CMIP5 data set and the observed values in Hainan island. Daily maximum temperature, minimum temperature and precipitation were obtained from the ground weather stations and the GCMs include FGOALS-g2, GFDL-ESM2G, HadGEM2-ES, MPI-ESM-MR and MRI-CGCM3 in Hainan island and its nearby waters. The observations and the raw GCMs outputs for the historical (1970-1999), RCP2.6, RCP4.5 and RCP8.5 (2020−2099) scenarios were processed and interpolated to a spatial resolution of 0.5°×0.5° as grid cells using the bilinear method. We used both systematic residuals revision methods (corrected value method or ratio method) and multi-mode ensemble averaging methods include the Bayesian model averaging (BMA) method and the equal weight averaging (EW) method in each grid cells to reduce the spatial uncertainty of the raw GCMs in the training and verification period. And then, we used the revised GCMs outputs and the agro-climatic index computing software to analysis the change of agricultural heat and precipitation resources under the scenarios of RCP2.6, RCP4.5 and RCP8.5 in both short-term (2020−2059) and long-term (2060−2099). These sources include annual mean temperature, mean temperature in January, ≥10℃ and ≥20℃ integrated temperature, annual precipitation, precipitation in January and precipitation in ≥20℃ integrated temperature period.The results showed that the correct coefficients of the raw GCMs outputs from both systematic residuals revision and the BMA method all have large spatial differences among the grid cells. The raw GCMs outputs underestimate the daily maximum temperature about 3.55℃, overestimate the daily minimum temperature about 1.19℃ and underestimate the daily precipitation which only 54.35% of the observations. It can effectively reduce the spatial uncertainty of the raw GCMs outputs by the above revision methods. The revised results of the BMA and the EW are similar and both are better than a single GCM for simulate historical climate variables. After comprehensive revision of the BMA in each grid cells, the correlation coefficients of maximum temperature, minimum temperature and precipitation are increased about 0.10, 0.07 and 0.06 respectively, and the root mean square error are reduced about 2.38℃, 1.01℃ and 1.01mm respectively, in the verification period. There are decreased about 3.25℃, 1.13℃ and 25.67mm compared with the average biases of a single GCM and closer to the observed value. In the future, the agricultural heat resources will generally show a gradual increase from the central mountains to the coast in spatial. The high temperature will distribute mainly range from the southern to the western coastal areas. The annual mean temperature will increase evenly in the whole island. The increasing amplitude of mean temperature in January, ≥10℃ and ≥20℃ integrated temperature has different patterns that will decrease from the eastern to the western, from the northern to the southern, and from the central mountains to the coast, respectively. It will increase significantly with the fastest climate trend rate under the RCP8.5, or increase first in short-term and then level off in long-term under the RCP4.5, or relatively flat without increase significantly under the RCP2.6. The precipitation resources are transforming into a pattern of gradually decreasing from the eastern to the western and with no significant trend in temporal. The precipitation variability will increase in the southern and the northern coastal areas, while decrease in the western and the central areas. With climate warming and the changes of precipitation pattern in future, the expansion of suitable crop cultivation areas will face huge challenges to agricultural production. It is necessary to arrange in advance to seek advantages and avoid disadvantages.
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    Response of Main Phenological Periods of Two Typical Leguminosae Plants to Climate Change in Alxa Desert
    CHANG Pei-jing , LI Yong-shan , WU Nan, WANG Hai-mei, LI Zhong
    Chinese Journal of Agrometeorology    2021, 42 (05): 364-376.   DOI: 10.3969/j.issn.1000-6362.2021.05.002
    Abstract91)      PDF(pc) (1132KB)(60)       Save
    To explore the climate driving factors of the phenological changes of legumes in Alxa Desert, the characteristics of climate change and the temporal evolution trend of the main phenological periods of two typical leguminosae plants(Caraganabrachypoda Pojark. and Oxytropis aciphylla Ledeb.) were studied by using linear trend rate and stepwise regression methods. Based on the observation data of climate elements and vegetation phenology at Alxa Desert monitoring points in recent 40 years, that is from 1981 to 2019. The results showed that: (1)the annual average temperature of the monitoring points in the past 40 years was 8.8℃, and increased significantly with a trend of 0.46℃·10y-1(P<0.01). The average annual hours of sunlight was 3136h, decreasing at a rate of about 98h·10y-1(P<0.01). The average annual precipitation was 159mm, with an increasing trend and a precipitation variation tendency rate of 19.08mm·10y-1(P<0.05). (2) In recent 40 years, the turning green period and flowering period of Caragana microphylla and C. maotouci were significantly advanced, the yellow withered period was slightly delayed, and the whole growth season was extended over the past 40 years. The annual average turning green, the flowering and the yellow withered period from Jan.1of Caraganabrachypoda Pojark were 898, 11610 and 30810 respectively. And these three periods in Oxytropis aciphylla Ledeb 308 ± 10 and 315 ± 10, respectively. (3) From the correlation analysis between vegetation phenology and climate factors, it would be found that the phenological changes of Caraganabrachypoda Pojark and Oxytropis aciphylla Ledeb were mainly limited by air temperature. The sunshine hours had a slight effect on the green returning period of the two plants, and the precipitation only effected the yellowing period of the Caraganabrachypoda Pojark.
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    Discussion on the Mechanism of Effects of High Temperature and Humidity on Tomato Flower Bud Differentiation in Seedling Stage
    HUANG Qin-qin, YANG Zai-qiang, LIU Xian-nan, WANG Xue-lin, XU Chao, DING Yu-hui, LI Jia-jia, ZHENG Qian-tong
    Chinese Journal of Agrometeorology    2021, 42 (01): 56-68.   DOI: 10.3969/j.issn.1000-6362.2021.01.006
    Abstract90)      PDF(pc) (3331KB)(76)       Save
    In order to study the mechanism of high temperature and humidity affecting the differentiation of tomato flower buds, the tomato variety "Shouhe Fenguan" was used as the test material. The orthogonal test of air temperature, air relative humidity and treatment days was conducted in the agricultural meteorological experimental station of Nanjing University of information technology from April to July 2020. The air temperature (day temperature / night temperature) was set with four treatment levels: T1 (32℃/22℃), T2 (35℃/25℃), T3 (38℃/28℃), T4 (41℃/31℃); The air humidity was set at three levels: H1 (50%), H2(70%) and H3(90%), error range is ±5 percentage points. The treatment time was 2,4,6 and 8 days. The treatments of day / night temperature 28℃/18℃ and air relative humidity 45% − 55% were used as control (CK). The contents of endogenous hormones, starch and soluble sugar were measured at different stages of tomato flower bud differentiation, and stem diameter, dry weight of single plant, strong seedling index and chlorophyll content were measured at budding stage to study the mechanism of high temperature and high humidity on flower bud differentiation of tomato. The results showed that: (1) with the increase of temperature, the whole process of flower bud differentiation was prolonged with the increase of temperature, while the air relative humidity and treatment days had little effect on the process of tomato flower bud differentiation. (2) Under different treatments, the contents of IAA and GA3 in the top buds of tomato decreased, increased and decreased with the flower bud differentiation, while the contents of ZT and ABA showed the opposite trend with IAA. The contents of IAA, ZT and GA3 decreased with the increase of temperature, relative humidity and treatment days, while ABA content increased with the increase of stress degree. (3) The content of starch and chlorophyll in tomato leaves decreased gradually with the process of flower bud differentiation. Soluble sugar content increased gradually from non differentiation stage to stamen differentiation stage, and decreased gradually during pistil differentiation stage. With the deepening of stress degree, there were significant differences among the treatments. The results showed that the inhibitory effect of high temperature and high humidity on tomato flower bud differentiation might be related to the change of endogenous hormone content and the decrease of nutrients. The environmental temperature should be controlled at the level of CK at the initial stage of flower bud differentiation. The higher the temperature, the more unfavorable it would be. The results can provide some scientific basis for tomato growth environment regulation and disaster warning.
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    SPEI Simulation for Monitoring Drought Based Machine Learning Integrating Multi-Source Remote Sensing Data in Shandong
    YANG Jin-yun, ZHANG Sha, BAI Yun, HUANG An-qi, ZHANG Jia-hua
    Chinese Journal of Agrometeorology    2021, 42 (03): 230-242.   DOI: 10.3969/j.issn.1000-6362.2021.03.007
    Abstract87)      PDF(pc) (7016KB)(84)       Save
    In this study, Shandong province was taken as the research area, and three machine learning methods, namely Bias corrected Random Forest(BRF), Support Vector Regression(SVR) and Cubist model were selected to integrate multiple impact factors to simulate the standardized precipitation evapotranspiration index on a three-month time scale(SPEI-3), so as to provide a method for accurate monitoring of drought in Shandong province. SPEI-3 values of 23 stations from 2001 to 2017 were taken as dependent variables. Multi-source remote sensing data including precipitation, surface temperature, evapotranspiration, potential evapotranspiration, normalized difference vegetation index and soil moisture were taken as independent variables. Independent variables and dependent variables constituted 80% of the data set as training set and 20% as test set. According to the BRF model, the simulated values of each site in the study area and the relative importance of each impact factor were obtained. The spatial distribution diagram of SPEI-3 was drawn and verify them. The results showed that the multiple factor simulation was more effective than the single factor. The R2 of the simulated value and observed value in the BRF model’s test set reached 0.856, and the RMSE of the root mean square error was 0.359. The BRF model can well simulate the SPEI-3’s values of the sites. Simulated and observed values for most sites are consistent with the drought trend, and reflect the number of months of different drought conditions is basically the same. The spatial distribution of SPEI-3 simulated by the BRF model is basically consistent with the drought degree of observed SPEI-3 at the site, and SPEI-3 spatial distribution of raster data outside the sites can also reflect the drought situation more accurately. According to the BRF model, the drought situation in Shandong province can be monitored more accurately at the site and spatial scale.
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    Performances of Remote Sensing Monitoring Indices of Agricultural Drought in Growing Season of Typical Dry Year in Northeast China
    WANG Wei-dan, SUN Li, PEI Zhi-yuan, CHEN Yuan-yuan
    Chinese Journal of Agrometeorology    2021, 42 (04): 307-317.   DOI: 10.3969/j.issn.1000-6362.2021.04.005
    Abstract86)      PDF(pc) (1297KB)(70)       Save
    Quite a few indices for agricultural drought monitoring based on remote sensing technology have been developed, but their sensitivity may be affected by specific environment. Different agricultural drought monitoring indices derived from remote sensing have different temporal and spatial adaptability. For the purpose of assessing the impact of drought timely and accurately, it is very important to select appropriate monitoring indices for specific regions and specific crop growth stages. Referring to previous studies, in this paper, agricultural drought monitoring indices were divided into three types: precipitation-based, soil-based and crop-based indicators. With the relative soil moisture (RSM) as the reference, the performances of 10 drought monitoring indices were analyzed during crop growing season in Northeast China. In the process of quantitative analysis of these drought indices’ applicability, the Pearson correlation analysis was carried out on 8-day scale in the typical drought year 2009. The results showed that: (1) except in the early stage of the growing season, the absolute value of correlation coefficient between the temperature vegetation drought index (TVDI) and RSM was about 0.50 respectively. TVDI was sensitive to soil moisture, and can be used for agricultural drought monitoring in the middle and late stage of the growing season. (2) The accumulative crop water stress index (ACWSI) based on potential evapotranspiration and actual evapotranspiration was one of the indices with good correlation with soil moisture. Especially in the early and late growing season, it performed well: the absolute value of the correlation coefficient between ACWSI with RSM was above 0.47. The time scale of cumulative effect needs to be paid attention to in the application. (3) The apparent thermal inertia (ATI) was more suitable for drought monitoring in early growing season, and the modified energy index (MEI) was appropriate for various vegetation cover conditions, but it had certain instability. (4) Compared with the precipitation condition index (PCI), the accumulative precipitation condition index (APCI), considering the accumulated precipitation, reflected the soil moisture status better, especially in the middle and late stage of the growing season. So, it could be used as a supplement to other monitoring indices. (4) The vegetation conditional index (VCI) and normalized difference water index (NDWI) had low correlation with RSM, indicating low sensitivity to current soil moisture, so they are not suitable for agricultural drought monitoring in Northeast China. This study can provide some reference for the index selection of regional agricultural drought monitoring in short time scale, and construct a feasible framework for the extensive application of agricultural drought indices.
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