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20 January 2022, Volume 43 Issue 01

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Simulation of Reference Crop Evapotranspiration by BP Neural Network Optimization Model with Limited Meteorological Data: A Case Study in the Beijing-Tianjin-Hebei Region

JIA Yue, SU Yong-jun, ZHANG Ran, LI Peng-cheng, WANG Feng-chun, LU Mei

2022, 43(01):  1-16.  doi:10.3969/j.issn.1000-6362.2022.01.001

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In order to obtain the optimal simplified estimation model for reference crop evapotranspiration(ET0) in areas with a lack of meteorological data, the authors took the Beijing-Tianjin-Hebei region as the research area. Particle Swarm Algorithm(PSO), Genetic Algorithm(GA), Evolutionary Mind Algorithm(MEA), Sparrow Algorithm(SSA), and Artificial Fish Swarm Algorithm(AF) were used to optimize the BP model. Five optimization models: PSO-BP, GA-BP, MEA-BP, SSA-BP, AF-BP were constructed. These models were compared with BP model, random forest model(RF), wavelet neural network model(WNN), Hargreaves model(HS) and Droogrs-Allen model(DA). The results showed that: in different regions, the calculation accuracy of the five optimization models is significantly higher than the other models. SSA-BP model had the highest accuracy in different areas, with RMSE, R2, Ens and MAE of 0.297−0.402mm·d−1, 0.879−0.946, 0.862−0.940 and 0.210−0.300mm·d−1, respectively. The portability analysis results of the SSA-BP model showed that the model had strong generalization ability in the Beijing-Tianjin-Hebei region, and can achieve accurate estimation of ET0 from different stations. Thus, with only temperature data, the SSA-BP model can be used as a standard model for ET0 estimation in the Beijing- Tianjin-Hebei region.

Evaluation and Verification of CLDAS Relative Soil Moisture Products during Growing Season in Liaoning Province

LIU Dong-ming, WU Men-xin, HOU Ying-yu, CHEN Peng-shi, ZHANG Wei-wei, WANG He-ran

2022, 43(01):  17-27.  doi:10.3969/j.issn.1000-6362.2022.01.002

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Based on the daily observation data of automatic soil moisture stations in Liaoning province during growing season (May to October) in 2020, the simulation performance of CLDAS(CMA Land Data Assimilation System) relative soil moisture products at 0−10cm, 0-20cm and 0-50cm levels was evaluated and tested by using statistical evaluation indices and methods including correlation coefficient (r), root mean squared error (RMSE), mean absolute error (MAE) and deviation to comprehend the application of CLDAS fusion relative soil moisture data. The results showed that there are trend consistency and significant positive correlation on time scale between CLDAS relative soil moisture simulation results and observed values in three soil layers. During the growing season, the simulation results of CLDAS average relative soil moisture were generally high. CLDAS had a relatively nice simulation effect when the relative soil moisture was between 60% and 90%, and had a relatively poor simulation effect when the relative soil moisture data were in the state of partial wet (RSM > 90%) and partial dry (RSM < 60%). On the other hand, the spatial variation showed a consistent tendency between CLDAS relative soil moisture simulation results and observed values at three levels, and the overall distribution was relatively low in the west and relatively high in the east. There was a significant positive correlation between CLDAS relative soil moisture simulation results and observed values, and the correlation coefficient was more than 0.8 in 0-20cm and 0-50cm soil layer in most areas of Liaoning province. The distribution trend of error assessment results was coincident in the whole province. The errors in the eastern, southern and western parts of Liaoning were relatively small, while those in the northern and central parts were relatively large. Abnormal high value area of error occurred in the line of Kangping-Zhangwu-Xinmin-Tai 'an. The relative soil moisture simulation results of CLDAS had a fairly strong applicability and stability in Liaoning province, which could reflect the variation of soil water surplus and deficit well.

Changes of Soybean Yield in Various Soil Types Responding to 2℃ Warming

PAN Shi-qiu, MIAO Huan, QIAO Yun-fa, MIAO Shu-jie

2022, 43(01):  28-36.  doi:10.3969/j.issn.1000-6362.2022.01.003

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Agricultural cultivation region in China is sensitive to global climate change. The sensitivity of various soil types to warming plays a key role in the relationship between agricultural production and air warming. To reveal the response of soybean yield to air warming, the present study was to study the effect of 2℃ warming on soybean yield in Black soil, Brown soil, Saline-alkali soil, Aeolian soil, Sierozem, Loess, Yellow-brown soil, Purple soil, Shajiang black soil, Fluvo-aquic soil, Red soil, Latosol soil under mimic 2℃ warming with Infrared radiation heating device compared to normal temperature as control. The results showed that 2℃ warming increased the numbers of one-seed, two-seed, three-seed and total pods by 152.3%, 144.7%, 206.9% and 147.5% compared to control, respectively. However, 2℃ warming increased the number of shrunken pods in Shajiang black soil by 42.8% compared to control. Apart of the increase in the numbers of two-seed in Latosol soil and total pods in Purple soil by 76.4% and 50.5%, 2℃ warming did not significantly impact pod number in other soil types. Moreover, 2℃ warming significantly increased the seed number per plant in Red soil, Shajiang black soil, Purple soil and Saline-alkali soil, and their yields increased by 241.4%, 59.2%, 47.6% and 75.2% accordingly. Taken together, soybean yield and its components in Red soil, Shajiang black soil, Purple soil and Saline-alkali soil were sensitive and positive to 2℃ warming, while other 8 soil types were insensitive to 2℃ warming. All these indicated that soybean yield formation in response to air warming was indirectly regulated by soil types. This result might provide theory evidence for adapting future climate change in different soil type regions.

Review on the Cold Dew Wind Damage of Double-cropping Late Rice in Southern Region

SONG Zhong-hua, GAO Wen-juan, LIU Fu-lai , XIE Na, SANG You-wei, HUANG Wan-hua

2022, 43(01):  37-49.  doi:10.3969/j.issn.1000-6362.2022.01.004

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Cold dew wind is a disastrous weather during the heading and flowering stage of double-cropping late rice, which is blocked by low temperature and increases the empty shell rate. In order to understand the current situation of cold dew wind research, inherit and improve the research results of cold dew wind, and provide reference for making breakthroughs, authors summarizes the main results of the cold dew wind research after analysis and combing of the cold dew wind literature.Abnormal atmospheric circulation is the basic reason of large-scale cold dew wind. Factors such as topography and altitude can cause small-scale cold dew wind.The damage of cold dew wind to late rice is mainly at the heading and flowering stage, followed by the booting stage.Most researches on cold dew wind indicators are based on field experiments, meteorological element simulation experiments, production practices, historical data, and literature analysis.The most widely used indicators are "cold dew wind grade" and "technical specifications for evaluation of rice cold damage".The method of weather science is a common method for forecasting cold dew wind. Mathematical statistics are indispensable in weather forecasting, and the application of new methods such as neural networks is a trend in weather forecasting.In the southern double-cropping rice area, the cold dew wind mainly occurs in mid-to-late September or after. Under the global warming, the first day of the cold dew wind tends to be delayed and the number of days decreases, but there are some cases where the first day advances and the number of days increases.Single point (station) observation and 3S technology are commonly used for cold dew wind monitoring.Reasonable arrangement of late rice sowing date, selection of low temperature resistant varieties and water temperature regulation are effective in preventing cold dew wind. In view of the main problems existing in the study of cold dew wind, such as incomplete index factors, inconsistent index standards, and unable to achieve the required accuracies of prediction, monitoring and evaluation, the main research directions in the future are prospected: Deepening the study of multifactor disaster mechanism and multi meteorological element index of cold dew wind, and constructing the index system; Make use of new technologies such as big data and artificial intelligence to strengthen the research on intelligent and accurate forecasting technology of agrometeorology; Strengthening the research on precision monitoring and evaluation technology integrating meteorological observation, satellite remote sensing and crop model; Paying attention to the research on the new law of cold dew wind under climate change; Carrying out research on disaster prevention and reduction technologies suitable for climate change and agricultural scientific and technological progress.

Spatial-temporal Variation of Delayed/Sterile-type Chilling Injury in Major Growth Periods of rice in Jilin Province

YAO Man, ZHANG Qi, YANG Zai-qiang, HAN Jia-hao, LIU Xin

2022, 43(01):  50-60.  doi:10.3969/j.issn.1000-6362.2022.01.005

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Based on the data of daily average temperature, rice development date, yield and historical disasters from 10 agrometeorological observation stations in Jilin province from 1981 to 2019, two types of chilling injury events of delayed and sterile-type chilling injury in key growth period of rice were identified. The disaster intensity and spatial-temporal changes of different types of chilling injury in key growth period were analyzed. The results showed that: (1) under the background of global warming, there was a significant change trend in the rice development period of each station in Jilin province, in which the transplanting date was mainly in advance and the maturity date was mainly delayed. The climate tendency rate of 80% of the stations interval days during the transplanting maturity period were positive, and the increasing trend of half of the stations passed the significance test at the level of 0.05. (2) The frequency of delayed chilling injury decreased significantly in different years, which was mainly related to the improvement of temperature conditions at transplanting heading period; The disaster intensity of delayed chilling injury at transplanting heading period was greater. (3) The frequency of sterile-type chilling injury in flowering period was significantly higher than that in booting period, but the disaster intensity of sterile-type chilling injury in booting period was greater. (4) In terms of spatial distribution, the occurrence frequency of delayed chilling injury in the whole region was not different, and only the severe delayed chilling injury was slightly higher in the eastern region; The occurrence frequency of sterile-type chilling injury in the eastern region of Jilin province is significantly more serious than that in other regions. In conclusion, under the joint action of global warming, farmers' adjustment of rice transplanting date and variety change, the occurrence of delayed chilling injury in key growth period of rice is significantly reduced, and sterile-type chilling injury mainly occurred in the east of Jilin province.

Development of Farming Weather Forecast Service Platform Based on Mobile Cloud Computing Technology —A Case Study on Forecasting of Wine-Grape Farming Activities

GAO Guo-hong, LIU Yao, MA Li-wen, GOU Xiao-hui, LIU Jian-hong

2022, 43(01):  61-71.  doi:10.3969/j.issn.1000-6362.2022.01.006

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The FTP file transfer method based on traditional TCP/IP protocol and the service mode with one-time production and unified distribution of service products no longer meet the pertinence, diversity, high efficiency requirements of the existing services. In order to reduce redundant farming weather forecast service products, improve the operational efficiency and services pertinence, by adopting internet and cloud computing technology, authors took wine grapes in Ningxia hui autonomous region as an example and developed Ningxia farming weather forecast cloud services platform based on user location and farming activities. Online real time production and distribution of service products were realized in this research. This platform was mainly composed of three parts: data processing software, farming product cloud producing software and agriculture meteorological service APP. The workflow of this platform was as follows: basic data and necessary intermediate data in the Meteorological Service Network were uploaded to the cloud server database, then subroutines such as data acquisition, index comparison and forecast making were used, and finally related farming weather forecast were obtained through the API interface of the established cloud service website. In addition, farming weather forecast products with strong professionalism, time-validity and pertinence based on the user's geographical location were acquired through the developed APP. This platform can greatly improve the objectification, automation level and service product quality of farming weather forecast in Ningxia, as well as can provide references for specialization and fine development in farming weather forecast technology in China.

Analysis Report of Agrometeorological Conditions during Growing Season of Autumn-Harvest Crops in 2021

LIU Wei, ZHAO Xiao-feng

2022, 43(01):  72-76.  doi:10.3969/j.issn.1000-6362.2022.01.007

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According to the observed meteorological data and the historical data from 2346 meteorological stations in major agriculture area in China in 2021, the climate suitable index and agrometeorological disaster index were used to analyze the agrometeorological conditions in the growing season of major autumn harvest crops, such as corn, single rice, later rice, soybean and cotton. The results showed that: accumulated temperature greater than or equal to 10 degrees centigrade was 100 to 250℃·d more than normal value and the thermal conditions were sufficient. The precipitation and soil conditions were suitable for crop growth and development. Temperature, sunshine and water conditions matched well in summer which were favorable to flowering and filling stage of corn, single rice and soybean. Also, the meteorological conditions were favorable to flowering and boll setting of cotton. In general, the impact of drought during the main growth period of autumn harvest crops was light, and the meteorological conditions were favorable for crop growth, development and yield. While rainstorm and flood disasters occurred frequently especially in Henan province which caused the crops heavy losses and some crops were out of harvest. There was a continuous extreme rainy and sunless weather during maturity period for corn and cotton in eastern part of Northwest China, North China and the north of Huanghuai region. It was not conducive to crop filling maturation and harvesting. Additionally, staged low temperature in Northeast China, drought in northeastern part of Northwest China, high temperature in southern China and Xinjiang had a certain adverse effect on local crops.