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Study on Accuracy Evaluation of Multi-Source Precipitation Fusion Analysis Products under Complex Terrain in Chongqing KUANG Lan, TIAN Mao-ju, LI Qiang, LI Qi-lin, LIU Feng-xia Chinese Journal of Agrometeorology    2023, 44 (01): 71-81.   DOI: 10.3969/j.issn.1000-6362.2023.01.007 Abstract （155）      PDF（pc） （1778KB）（744）       Knowledge map    Save Two sets of multi-source precipitation fusion analysis products FAST and FRT products from 2020 to 2021, and the hourly precipitation data of 35 national meteorological stations in Chongqing after quality control were used to test the correlation and error of the two sets of products in combination with the topographic factors of each station, so as to provide data support for hydrometeorological research under complex terrain. Some results in this study showed that: (1) FAST and FRT products had good correlation with the observed value, positive correlation and small error. The overall product was lower than the observed value, and there was a slight difference between them. (2) On monthly and seasonal time scales, the accuracy of spring was the best, and the error and dispersion degree of flood season from May to September were the largest. (3) With the increase of precipitation grade, the distribution of product error, correlation and TS grade score became more discrete, the absolute value of error gradually increased, the TS grade score gradually decreased, and the correlation first decreased and then increased, among which the correlation of precipitation grade 0.1-1.9mm and ≥ 20mm was better. (4) In terms of terrain factors, the accuracy of products was slightly different, among which the accuracy of products on the slope was the best, followed by the flat slope, above the steep slope and gentle slope. The accuracy of products with undulation greater than 70m was the best; With the increase of altitude, the product accuracy decreased first. When the altitude was greater than 700m, the product accuracy increased. The accuracy of products with the Southwest and East slope directions was better, and the Southwest slope direction was the best. FAST and FRT precipitation products had high accuracy in Chongqing, which could effectively supplement the precipitation data in areas with few automatic stations. Related Articles | Metrics | Comments（0）

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A Comprehensive Drought Evaluation Model in Beijing-Tianjin-Hebei Region Based on Deep Learning Algorithm HU Xiao-feng, WANG Dong-li, ZHAO An-zhou, LIU Xian-feng, WANG Jin-jie Chinese Journal of Agrometeorology    2021, 42 (09): 775-787.   DOI: 10.3969/j.issn.1000-6362.2021.09.005 Abstract （320）      PDF（pc） （4631KB）（519）       Knowledge map    Save Drought is the most common natural hazard in the Beijing-Tianjin-Hebei region. Timely and accurate drought evaluation is crucial for socio-economic development and agricultural production. Unilateral factors such as vegetation or precipitation are usually only considered in current drought assessment, which have some limitations in actual drought evaluation. In this study, multiple drought-causing factors such as precipitation, temperature, soil and terrain were considered comprehensively. Land surface temperature (LST), normalized difference vegetation index (NDVI), precipitation and other multi-source data from 2007 to 2017 were used to construct a comprehensive drought evaluation model with standardized precipitation evapotranspiration index (SPEI) as the target value under Tensorflow frame in the Beijing-Tianjin-Hebei region, Chinese main grain production base. Determination coefficient (R2) and root mean square error (RMSE) were used to evaluate model accuracy. The station standardized precipitation index (SPI), soil relative moisture data and meteorological disaster data for the Beijing-Tianjin-Hebei region in 2016 were used to validate the accuracy of model in time and space. The results showed that model in training and test sets had different performance in various months, with R2 both greater than 0.5 and RMSE less than 0.55. Comprehensive drought evaluation model had the best performance in November. Comprehensive drought index (CDI) output from the model was close to SPI and SPEI at Miyun station, and the change trend was basically consistent. The correlation coefficients between the CDI of the model and SPI, relative soil moisture at a 10cm depth were greater than 0.7 and 0.4 respectively. Both of them passed 0.01 significance level test. Spatially, compared with SPEI, the results of drought events in Beijing-Tianjin-Hebei region from March to July in 2016 calculated by CDI were more consistent with actual situation, which indicated that the comprehensive evaluation model was applicable for drought monitoring in Beijing-Tianjin-Hebei region.  Related Articles | Metrics | Comments（0）

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Spatiotemporal Variation of Climate Dry-Wet Condition and Its Potential Trend in the Yellow River Basin from 1960 to 2020 GONG Jie, GAO Bing-li, LI Yan, JIN Tian-tian, ZHANG Yun-xia, ZHU Yue-hua Chinese Journal of Agrometeorology    2022, 43 (03): 165-176.   DOI: 10.3969/j.issn.1000-6362.2022.03.001 Abstract （270）      PDF（pc） （12119KB）（519）       Knowledge map    Save Based on the humidity index, using the daily climate data of 113 meteorological stations in and adjacent the Yellow River Basin(YRB) from 1960 to 2020, climate trend rate, Morlet wavelet, simple correlation analysis, and Hurst index were used to analysis the spatiotemporal characteristics of dry-wet condition in the YRB in the latest 61 years and to predict the future trend of dry-wet changes in the YRB, to provide scientific basis for drought prevention and mitigation and rational utilization of climate resources in the YRB. The results showed that: (1) among all the geographic zones, the annual and seasonal humidity index in the YRB was high in the southeastern YRB and low in the northwestern YRB. Spatially, the climate of the annual, spring and autumn in the YRB was mainly dry, the proportions of stations with significant decrease of humidity index of the total stations were 5.31%, 7.96% and 6.19%, respectively. The climate of summer and winter was mainly wet, the proportions of stations with significant increase of humidity index were 10.62% and 13.27%, respectively. (2) As for the interannual change, the annual and seasonal humidity index of the YRB from 1960 to 2020 showed no significant change. Semi-humid, semi-drought, semi-humid, semi-humid, semi-drought were found in entire year, spring, summer, autumn, and winter, respectively. The annual and seasonal humidity index of the YRB had periodic oscillation characteristics at multiple time scales, and the first main period was 3 years, 26 years, 14 years, 3 years and 15 years, respectively. (3) The change of humidity index in the YRB was extremely significantly positively correlated with precipitation and relative humidity. There was a extremely significant negative correlation between sunshine duration and humidity index. Precipitation, relative humidity, and sunshine duration were the main factors affecting the change of humidity index in the YRB. (4) The Hurst index of annual and seasonal humidity index in the YRB were larger than 0.50, indicating that the climate of annual, spring, and autumn of the YRB would continue to be drying, the summer and winter climate would continue to be wetting. Related Articles | Metrics | Comments（0）

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Review on Research of Spatial Pattern and Influencing Mechanisms of Terrestrial Ecosystem Stability CHEN Ji-jing, ZHOU Lei, CHI Yong-gang Chinese Journal of Agrometeorology    2021, 42 (07): 552-560.   DOI: 10.3969/j.issn.1000-6362.2021.07.002 Abstract （260）      PDF（pc） （458KB）（516）       Knowledge map    Save The earth has been experiencing ever-increasing climatic fluctuation and extreme events for decades, and ecosystem structure and function have generally slipped into recession, resulting in significant impacts on economy and ecology. Ecosystem stability refers the ability of ecosystem to maintain or restore to normal structure and function, which is the key to maintain the ecosystem service function. However, due to the complexity of the ecosystem, the results of the research on the stability are still controversial. Here, the dimensionality, spatial patterns and influencing mechanisms of ecosystem stability were summarized from 58 relevant literatures. The multi-dimensional framework of ecosystem stability, definition and interrelationship of various stability indicators were discussed respectively as well as the effects of latitude, altitude, and position on stability. The dominant factors of the variation of stability at different scales and the effects of abiotic factors such as climate, nutrition and biological factors such as biodiversity on stability were also discussed. The results indicated that correlations between different components of ecosystem stability leaded to their generalization into three dimensionalities, including resistance, resilience and temporal stability. In addition, ecosystem stability was regulated by abiotic factors such as climate and nutrition as well as biological factors such as species richness and population variability. Stability and its influencing mechanisms showed strong spatial heterogeneity and scale dependence, which were mainly controlled by biological factors such as biodiversity at the site scale, and abiotic factors such as temperature, precipitation and radiation at the regional and global scales. Data source noise and unstandardized quantification methods were the main problems in stability study. In the future, with the applications of satellite remote sensing and other acquisition methods, the research field will be gradually expanding from local scale such as site to global scale such as region and continent, and a standardized stability assessment method can be formed. The large spatial scale research can effectively elucidate the general relationship between ecosystem stability and its response to various driving forces, providing a theoretical basis for the formulation of sustainable ecological protection policies. Related Articles | Metrics | Comments（0）

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The Scientific Problem and Improvement of the Concepts of Accumulated Temperature and Heat Resource ZHANG Zi-yuan, ZHENG Da-wei, PAN Yu-ying, PAN Zhi-hua Chinese Journal of Agrometeorology    2021, 42 (08): 686-692.   DOI: 10.3969/j.issn.1000-6362.2021.08.006 Abstract （404）      PDF（pc） （438KB）（433）       Knowledge map    Save The concepts of accumulated temperature and heat resources have been widely presented in domestic literature and teaching materials, and accumulated temperature is usually as the main form of representation of heat resource. But its traditional definition obviously violates the principles of physics, and the measurement units also have not been unified. It urgently needs to be given an accurate scientific interpretation and further standardized. Based on the origin and development history of the concepts of accumulated temperature and heat resources, the problems in its practical application are reviewed in this paper, and the application frequency, geographical distribution characteristics of the term of accumulated temperature and its synonyms through Web of Science related literature are statistically analyzed and compared. The results show that, although accumulated temperature is the main indicator of traditional term of agricultural heat resources and is widely used, however, in fact, plants and cold-blooded animals do not need a certain amount of heat energy to complete a certain stage of growth and development, but require suitable temperature conditions and necessary duration. Excessive heat or too high temperature will cause damage to organisms, and some species even require relatively lower temperatures. On the other hand, literature search and statistics show that the term “accumulated temperature” has been rarer and rarer used in the international academic communities now, and the term “heat resource” is also rarely used in authoritative agricultural meteorological literature. In order to promote a more accurate and scientific term, it is recommended to stop use of the term “accumulated temperature” in Chinese Scientific Journals and to change into "integrated temperature" or "thermal time". And the unit should be unified into "℃·d" or “℃·h” and not “℃”. The term of “heat resource” is also changed to “temperature resource” and broadened, i.e. the synthesis of temperature conditions and their duration conducive to growth and development of plants and cold-blood animals. It will give full scientific significance without affecting the large number of applications and achievements of the current accumulated temperature theory, and will promote further development of agricultural meteorology and related disciplines. Related Articles | Metrics | Comments（0）

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Spatiotemporal Changes of Double Cropping Rice Phenology in South China and Relationship with Climatic Conditions LI Wei-guang, HOU Mei-ting, ZHANG Jing-hong, CHE Xiu-fen, CHEN Xiao-min Chinese Journal of Agrometeorology    2021, 42 (12): 1020-1030.   DOI: 10.3969/j.issn.1000-6362.2021.12.004 Abstract （341）      PDF（pc） （1361KB）（389）       Knowledge map    Save In order to explore the sensitivity of rice growth and development to climate change, and to estimate the contribution of climate change and varieties change to the change of rice phenology in South China, the phenological and meteorological observation data of double cropping rice planting in South China from 1981 to 2013 were selected for analysis. Theil-Sen estimation linear tendency rate and Mann-Kendall trend significance test were used to analyze the change trend and spatial distribution characteristics of double cropping rice phenology. Different from other regions, the sowing date of early rice in South China is ahead of schedule and the mature period of late rice is delayed slightly. The vegetative growth period of early and late rice was shortened, while the reproductive growth period was prolonged. The length of vegetative and reproductive growth periods of early rice and late rice increased with the increase of precipitation and sunshine hours, and decreased with the increase of temperature; the length of growth period was shortened by 0.5−4.7 days when the average temperature increased by 1℃. The analysis of the contribution rate of climate change and varieties to the impact of rice phenology showed that the influence of varieties change on the long-term length of early and late rice was greater than that of climate change. In the past 30 years, early rice tended to choose the varieties with long vegetative and reproductive growth period, late rice tends to choose varieties with short vegetative growth period and long reproductive growth period. Related Articles | Metrics | Comments（0）

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Mechanism on the Formation of Climate Change Impact Chain and Its Responses PAN Zhi-hua, HUANG Na, ZHENG Da-wei Chinese Journal of Agrometeorology    2021, 42 (12): 985-997.   DOI: 10.3969/j.issn.1000-6362.2021.12.001 Abstract （316）      PDF（pc） （535KB）（374）       Knowledge map    Save Once climate change brings various stresses and disturbances on the receptor system, the receptor system will transfer these stresses and disturbances to other systems through its connection with them, resulting in the continuous extension of climate change effects in time and space, forming a complex climate change impact chain. At present, studies on the impacts of climate change mostly focus on the direct impacts, while the indirect impacts are rarely considered. The incomplete understanding of the impact transmission of climate change is one of the main constraints in addressing climate change. It is of great significance to explore the formation mechanism of the impact chain of climate change. This research analyzed the characteristics of climate change impacts, explored the formation mechanism of climate change impact chains, defined the connotation and classification of climate change impact chains, clarified the impact levels of climate change, and proposed ways to cope with climate change impact chains. The results showed that the impacts of climate change were extensive, different, persistent, transferable, transformable, and sometime sudden. When climate change acted on the direct receptors, the impacts of climate change would be transmitted along the food chain in the ecosystem, along the industrial chain in the economic system, and along the social relationship chain in the social system. The transmission of impact chain took the form of material flow, energy flow and information flow. The impacts of climate change always rose from low to high levels, along changes in resource endowments to natural production, economic production systems and social systems. It is believed that the effective control or cutting off of the transmission of adverse impacts of climate change can effectively reduce the impact risks and losses of climate change. The impact chain of climate change and its formation mechanism provide ideas and approaches for people to deal with climate change comprehensively. Related Articles | Metrics | Comments（0）

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Predicting Potential Suitable Planting Area of Rice in China under Future Climate Change Scenarios Using the MaxEnt Model LV Tong, GUO Qian, DING Yong-xia, LIU Li, PENG Shou-zhang Chinese Journal of Agrometeorology    2022, 43 (04): 262-275.   DOI: 10.3969/j.issn.1000-6362.2022.04.002 Abstract （375）      PDF（pc） （3631KB）（372）       Knowledge map    Save To provide a scientific basis for reasonably planting rice in China, this study investigated the major climatic factors affecting the rice distribution and predicted the changes of rice suitable areas in the past and future periods, using the distribution data of rice, the high-spatial-resolution historical (1970−2000) and future (2081−2100) climate data, and the MaxEnt model. The results showed: (1) the main climatic factors affecting the distribution of early rice and late rice were precipitation of driest month, mean temperature of warmest quarter, and precipitation of driest quarter, and those of single-season rice were annual mean temperature and precipitation of warmest quarter; (2) In the historical period, the suitable planting areas for early rice and late rice in China were mainly in the middle and lower reaches of the Yangtze River and the south of the Yangtze River, accounting for 14.26% and 13.01%, respectively, where most of the regions were slight suitable areas, accounting for 7.66% and 6.62%, respectively. The area of the suitable planting area for one season rice accounted for 45.46%, and most of the regions were slight suitable areas and suitable areas, accounting for 23.47% and 18.86%, respectively; (3) Compared with the historical period, the future suitable planting areas of early rice under the SSP126, SSP245, and SSP585 scenarios increased by 6.27, 9.26, and 16.66 percentage points, respectively; the future suitable planting areas of late rice increased by 4.26, 5.55, and 10.97 percentage points, respectively; and the suitable planting area of one season rice increased by 11.34, 18.46 and 28.31 percentage points, respectively. To the end of the century, the suitable planting areas for early rice would expand to Sichuan, Chongqing and Huang-Huai area, the suitable planting areas for late rice would expand to Sichuan, Chongqing and a small area of the north of the middle and lower reaches of the Yangtze River, and the optimum suitable areas for one-cropping rice showed spatial expansion to the North China Plain and Northeast China. In general, future climate change will contribute to the expansion of suitable rice planting areas over China. Related Articles | Metrics | Comments（0）

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Application of Deep Learning Technology in Monitoring, Forecasting and Risk Assessment of Agricultural Drought HUANG Rui-xi, ZHAO Jun-fang, HUO Zhi-guo, PENG Hui-wen, XIE Hong-fei Chinese Journal of Agrometeorology    2023, 44 (10): 943-952.   DOI: 10.3969/j.issn.1000-6362.2023.10.007 Abstract （286）      PDF（pc） （343KB）（372）       Knowledge map    Save The development of artificial intelligence technology, especially the emergence of deep learning, has promoted new developments of agriculture, and is regarded as a new direction of modern agricultural production. Deep learning has the advantages of strong learning ability, wide coverage, strong adaptability, and great portability. Considering that its development of simulated datasets can solve real-world problems, it is more and more widely used in monitoring, forecasting and risk assessment of agricultural drought. This paper used the method of literature review to summarize the development and application of monitoring, forecasting and risk assessment of agricultural drought, and summarized the principles, advantages and disadvantages of the deep learning model. The practical applications of depth learning model in monitoring, prediction and risk assessment of agricultural drought were systematically summarized. The existing problems of large dataset requirements, long data preprocessing time, narrow predefined category range, and complex remote sensing images were discussed, and the future research directions were prospected. The results showed that in recent years, the technologies of monitoring, prediction and risk assessment of agricultural drought had made important progress. However, due to the nonlinearity of agricultural system and the complexity of disasters, existing technologies were still difficult to meet the needs of actual agricultural production in the new situation in terms of applicable regions, objects and accuracies. The deep learning technology provided a new means for agricultural drought research. However, the deep learning model could not accurately express the specific process and mechanism of crop growth, so coupling of crop growth model with deep learning model could ensure the interpretability of deep learning model. For correcting the prediction sequence, coupling models based on general circulation model and depth learning model could be established to further improve the prediction ability of deep learning model for medium and long-term agricultural drought. Aiming at the problem of limited disaster sample size, strengthening the research on agricultural drought monitoring and evaluation based on migration learning could further improve the precisions in fine monitoring and evaluation of agricultural drought. In view of the fact that the factors affecting agricultural drought formation was characterized by large amount of data, diverse types and nonlinearity, the method of combining deep learning and information fusion was adopted to further improve the accuracies in regional monitoring, prediction and risk assessment of agricultural drought. Therefore, the coupling of deep learning models and crop growth models, agricultural drought prediction by integrating deep learning models and general circulation models, fine monitoring and evaluation of agricultural drought based on deep learning and migration learning, regional monitoring, prediction and risk assessment of agricultural drought based on deep learning and information fusion were considered as the development trends of applicating deep learning technologies in monitoring, prediction and risk assessment of agricultural drought in the future. Related Articles | Metrics | Comments（0）

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Analysis of Annual Compound Events of Heat and Drought in North China Based on Copula Function YU Xin, ZHANG Qi, YANG Zai-qiang Chinese Journal of Agrometeorology    2023, 44 (08): 695-706.   DOI: 10.3969/j.issn.1000-6362.2023.08.005 Abstract （271）      PDF（pc） （2053KB）（366）       Knowledge map    Save The Copula function was used to analyze the annual compound events of heat and drought in North China, which can provide reference for agricultural water management and disaster prevention and mitigation in North China. Based on the daily maximum temperature and precipitation data of 36 meteorological stations in North China from 1960 to 2019, the year-by-year heat intensity and drought intensity were identified, the Copula function was introduced to construct a two-dimensional joint cumulative probability distribution function of heat intensity and drought intensity, and the return period of compound events of heat and drought in different grades were analyzed to assess the occurrence characteristics of the compound events. The results showed that when fitting the marginal distributions of annual number of heat days and drought intensity, the GEV function worked best at more stations; the most applied Copula function was the Symmetrised Joe-Clayton function when combining annual number of heat days and drought intensity in two dimensions; compared with high temperature intensity, drought intensity had a greater effect on the magnitude of the joint return period of compound events. North China is more prone to compound events with high heat intensity in the southwest and drought intensity in the south-central part of the country. The leading factors of compound events in North China vary from region to region, and different measures need to be taken to mitigate the damage caused by compound events in different regions. Related Articles | Metrics | Comments（0）

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Current Situation and Research Prospect of Agrometeorology in the New Stage PAN Zhi-hua Chinese Journal of Agrometeorology    2023, 44 (04): 327-332.   DOI: 10.3969/j.issn.1000-6362.2023.04.007 Abstract （443）      PDF（pc） （285KB）（364）       Knowledge map    Save At present, China has been entering a new stage of building an agricultural power, and agrometeorology is facing unprecedented challenges and opportunities for development. In view of the new situation of smart agricultural production, food security, green development and climate change, it is urgent for agrometeorology to establish the quantitative relationship between climate factors and agricultural production, make scientific and rational use of climate resources, and improve the utilization rate of climate resources. The major tasks of agrometeorology are to deepen the research content, expand the research field and innovate the theory and method, and the key research directions include agrometeorological basis, climate change adaptation, greenhouse gas emission reduction, efficient utilization of agro-climatic resources, agro-microclimate regulation, and climate-smart agriculture. Agrometeorology needs to accelerate its development and stay ahead of other basic agricultural disciplines. Related Articles | Metrics | Comments（0）

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Characteristics of Drought Distribution for Summer Maize over Whole Growth Period in Huang-Huai-Hai Plain Based on Crop Water Deficit Index ZHANG Xiao-xu, SUN Zhong-fu, ZHENG Fei-xiang, LIU Jiang, LI Chong-rui, WANG Yi-hao Chinese Journal of Agrometeorology    2021, 42 (06): 495-506.   DOI: 10.3969/j.issn.1000-6362.2021.06.005 Abstract （332）      PDF（pc） （3886KB）（359）       Knowledge map    Save The Huang-Huai-Hai plain is the main production area of summer maize in China, which is also one of the worst-hit drought areas. The loss of summer maize yield caused by drought has seriously affected China’s grain production. Therefore, it is of great significance to clarify the law of drought in this area for the formulation of anti-disaster measures and the guarantee of grain production. Base on the meteorological data of 76 stations from 1981 to 2015 in Huang-Huai-Hai plain was used in this study, the crop water deficit index(CWDI) as the drought index was used to analyze the spatial-temporal evolution characteristics of drought for summer maize in this area. The results showed that the overall changing trend of CWDI in the whole summer maize growth period increased first, and then decreased with the highest drought frequency occurring in sowing-seedling stage and tasseling-milk ripe stage. Drought was getting worse in the summer maize growth period during the period of 2011 to 2015, and southern Hebei, northern Henan and Shandong province exhibited the highest CWDI value. The slight drought was the main drought type in this area in the whole summer maize growth period, the moderate light drought ranked second and the severe and extra severe drought was barely. The frequency of drought in the northern area was higher than that in the southern area, as well as the western area was higher than that in the eastern. The ratio of extra severe drought occurring station was the highest in the sowing-seedling stage, and the ratio of slight drought occurring stations was the highest in the other growth periods. Related Articles | Metrics | Comments（0）

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Integrated Risk Evaluation on Multiple Meteorological Disasters of Apple in Eastern Gansu YANG Xiao-li, ZHOU Jia, ZHOU An-ning, ZHANG Wei, WU Ying-juan Chinese Journal of Agrometeorology    2021, 42 (06): 518-529.   DOI: 10.3969/j.issn.1000-6362.2021.06.007 Abstract （284）      PDF（pc） （6314KB）（355）       Knowledge map    Save Eastern Gansu is the most important apple base of Gansu province,but drought, freezing damage, hail and other meteorological disasters occured frequently during growth period of apple,which could lead to loss in yield and quality. Therefore, it was necessary to evaluate the integrated risk of multiple meteorological disasters on the growth of apple.In this paper, the meteorological data of 22 counties (districts/cities) in eastern Gansu from 1965 to 2018, planting area and yield of apple from 1995 to 2018, and other socio-economic statistics data for the latest 5 years were employed.12 indices of 4 kinds were analyzed and selected, and the integrated risk index system was established using disaster risk analysis theory. The weights of risk indices were determined by the compromising method between analytic hierarchy process method and entropy-coefficient method. In addition, the risk value of each evaluated unit was calculated. Therefore,an integrated risk evaluation index model of meteorological disasters was established and the risk was zoned and evaluated with GIS technique. The studied region was divided into four–risk–grade areas according to the integrated risk value, including mild risk area, moderate risk area, severe risk area and severity risk area. The results showed that hazard of the disaster-causing-factors was the most important factor influencing the integrated risk, the vulnerability of the hazard-affected body takes the second place, while the sensitivity of disaster environment and the disaster prevention and mitigation capability play alleviative roles in the risk factors composition. The integrated risk of meteorological disasters on apple growth in eastern Gansu shows a trend of increasing from southeast to northwest. The regions with severe and severity risk were mainly distributed along the mountainous area of Guanshan, the both sides of Liupan Mountain, and the north of Longdong Loess Plateau, with the risk index value of above 0.45; the regions with the moderate risk were mainly distributed in the south-central part of Longdong, and most of the Weihe River Basin, with the value between 0.25 to 0.45; the regions with the mild risk were only scattered in a small part of the Weihe River Basin, and the southeast of Longdong, with the value of below 0.45. Related Articles | Metrics | Comments（0）

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Research Progress on the Mechanism of High Light Use Efficiency in Wheat LI Yi-bo, TAO Fu-lu Chinese Journal of Agrometeorology    2022, 43 (02): 93-111.   DOI: 10.3969/j.issn.1000-6362.2022.02.002 Abstract （336）      PDF（pc） （667KB）（352）       Knowledge map    Save Crop yield is dependent on crop biomass and harvest index. The increases in crop yield in the past benefit mainly from the increase in harvest index, the increase in biomass has been small. Light use efficiency is a bottleneck to further increase crop biomass and yield. Wheat (Triticum aestivum L.) is a widely cultivated cereal crop globally, providing energy to up to 20% of the world's population. It is necessary to reveal the intrinsic mechanism and extrinsic factors affecting the light use efficiency of wheat, which is important for improving the utilization efficiency of crop resources and productivity. Achieving high light efficient production of wheat under limited natural resources has become the focus of study at home and abroad. Here, the definition of light use efficiency, the main processes, the characteristics of light use efficiency in wheat were summarized from relevant references, showing a more significant potential to improve light use efficiency. The effects of external factors such as light, water, nutrient and tillage system on wheat light use efficiency were summarized. The results indicated that light use efficiency was regulated by internal factors such as photosynthesis at the individual plant scale, and by abiotic factors such as temperature, precipitation and tillage practices at the field scale. The current problems and the adaptation mechanism of wheat in the context of climate change were also analyzed, aiming to provide a theoretical reference for the practical research of the high light use efficiency of wheat. Future research on light use efficiency can use high-throughput phenotypic observation techniques combined with molecular markers to design ideotypes in the target environment, providing scientific evidence for crop breeding. Related Articles | Metrics | Comments（0）

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Climate Suitability Analysis of Green Orange Cultivation in Hainan Island under Future Climate Change Scenarios CHEN Yan-xi, LOU Yun-sheng , REN Li-xuan , SU Lei , TANG Li-ling, YANG Jian-zhou Chinese Journal of Agrometeorology    2022, 43 (10): 786-797.   DOI: 10.3969/j.issn.1000-6362.2022.10.002 Abstract （221）      PDF（pc） （21968KB）（351）       Knowledge map    Save Green orange is a characteristic fruit and plays an important role in local agricultural production in Hainan island. However, few researches have been available regarding the climatic suitability of green orange planting in the island. Based on the last 40a (1980-2019) daily meteorological data, topographical and other factors from 19 meteorological stations in the main island of Hainan island, a spatial analysis model is established to comprehensively determine the climate suitability index for green orange planting in the island. With climate suitability model, this study constructed the suitability models of temperature, sunshine and precipitation, as well as comprehensive suitability model for green orange planting. The methods of geographic information system (GIS) and natural point break were used in finely zoning green orange planting climate suitability. With the model simulation data of RCP4.5 climate scenario, this study assessed the trend of green orange planting suitability zone in the next 30y (2020-2049) under future climate change scenario. The results show that, the most suitable area for green orange planting is mainly distributed in the central region, with the subtotal area being 0.87×104km2, and the climate suitability index ranging from 0.9-1.0; the suitable area is mainly distributed in the eastern local region and most of the central and western regions, with the subtotal area being 1.83×104km2, and the climate suitability index being 0.7-0.9; the subsuitable area is mainly located in the western coastal, central and western high altitude regions, with subtotal area being 0.51×104km2, and the climate suitability index varying from 0.4-0.7; the unsuitable area is mainly distributed in the central mountainous region, with the subtotal area being 0.17×104km2, and the climate suitability index ranging from 0-0.4. Under the future climate scenario, the area with suitable temperature and precipitation will have large change, namely, the area with suitable temperature will gradually shrink from the surrounding to the central regions, the area with suitable precipitation will gradually move from the eastern to the central regions. The most climatic suitable area for future green orange planting will mainly distribute in the most parts of Qiongzhong, Tunchang and Baoting counties, western parts of Wanning, central and eastern parts of Baisha county in the island. Related Articles | Metrics | Comments（0）

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Risk Assessment of Spring Frost Damage to Tea Plant in Anhui Province LIU Rui-na, CHEN Jin-hua, CHEN Xi, CAO Wen Chinese Journal of Agrometeorology    2021, 42 (10): 870-879.   DOI: 10.3969/j.issn.1000-6362.2021.10.006 Abstract （256）      PDF（pc） （5042KB）（350）       Knowledge map    Save In order to reduce the spring frost damage to tea plant in Anhui province, based on the daily meteorological observation data from1981 to 2017 of 45 stations, as well as garden area and tea production of 45 counties in tea plantation district from 1998 to 2017, the spring frost risk index was built by weighted index sum method. The index included comprehensive frequency of spring frost, sensitivity index of slope aspect, tea area and variation coefficient of yield reduction. The spring frost risk zoning was analyzed using the ANUSPLIN and geographic information system. The results showed that the areas of high-risk region, medium-risk region and low-risk region were118×104ha, 337×104ha, 353×104ha, and take 14.6%, 41.7% , 43.7% of the gross area of tea plantation district respectively in Anhui province. The high-risk region was mainly distributed in Jinzhai county, Huoshan county, Yuexi county, Qianshan county in Dabieshan tea area and the mountain areas with altitude above 600m in Jiangnan tea area, and scattered in the windward slope regions in Jiangbei tea area. The medium-risk region was mainly distributed in mountain areas with altitude below 600m in Dabieshan tea area and Jiangnan tea area, as well as hilly and low mountains in Jiangbei tea area. The low-risk region was mainly concentrated in the region along the Yangtze river, and scattered in low mountain areas in Jiangnan tea area. The spring frost risk index constructed in this paper can objectively reflect the risk level of spring frost damage to tea plant. This study provides a scientific foundation for tea disaster prevention and disaster management. Related Articles | Metrics | Comments（0）

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Simulation of Influences of Thermal Insulation Quilt Top Roll on the Light Environment in the North-South Greenhouse on Equinox Day FAN Yi-ran, LIU Huan, YAN Zheng-nan, LI Xiao-ye, YANG Yan-jie Chinese Journal of Agrometeorology    2021, 42 (08): 676-685.   DOI: 10.3969/j.issn.1000-6362.2021.08.005 Abstract （223）      PDF（pc） （1883KB）（349）       Knowledge map    Save In order to figure out the influences of thermal insulation quilt on the light environment in different positions in the greenhouse, the light distributions in different positions (from east to west) in the greenhouse were analyzed. The simulation and actual measurement were conducted in the Spring and Autumn Equinox Day in this study. Shading from direct sunlight in greenhouse was studied through converting the three-dimensional solar altitude angle into two-dimensional angle. Moreover, the movement position and distance of the shading zone from east to west were calculated in the Spring and Autumn Equinox Day. The distribution of daily light integral (DLI) was simulated in the greenhouse in different positions. The simulated greenhouse span was 12m, the ridge height was 4.2m, and the length was 60m The steel arch above the ground was 16m long, the radius was 0.35m, and the diameter was 0.7m after the insulation was rolled up. Ethylene vinyl acetate (EVA) film with actual light transmittance at 65% was used in the greenhouse. The light intensity of different positions in the top roll of insulation quilt in greenhouse was measured and the DLI was calculated. The measured value was compared with the simulated value. The distribution of DLI at different positions in the east-west direction and the light distribution in the greenhouse were analyzed. The results based on the model showed that the DLI at the middle point in east-west direction of greenhouse was the smallest, which was 10.91mol·m−2·d−1. The DLI was lower within 1m from the middle point to east/west, which increased by 11.8% from 10.91mol·m−2·d−1 to 12.20mol·m−2·d−1. DLI increased with the increased distance from the middle to the east/west, and the maximum value was 13.70mol·m−2·d−1, which was 6m away from the middle point (the edge of the greenhouse). The measured results showed that the DLI in the greenhouse was also the smallest at the middle point of the east-west direction, which was 7.31mol·m−2·d−1. The DLI was also lower within 1m from the middle point to east/west, which increased by 3.4% from 7.31mol·m−2·d−1 to 7.56mol·m−2·d−1. Similar trends were observed in the measured results, and the maximum value was 12.70mol·m−2·d−1. The variation law of DLI in measured values was consistent with the simulated values, which were the smallest in the middle point of greenhouse, and DLI increased with the increased distance from the middle to the east/west. The DLI changed slightly in different positions from east to west in the greenhouse. However, this does not affect the accuracy of the simulation trend. The simulation values were consistent with the measured values. In conclusion, DLI in the middle region will restrict the growth of photophilic crops in the season with poor light environment, thus leading to light stress on the growth of vegetables and other light-loving crops in the greenhouse. Related Articles | Metrics | Comments（0）

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Review on Drought and Waterlogging Disasters for Apple in China DAI An-ran, HUO Zhi-guo, JIANG Hui-fei Chinese Journal of Agrometeorology    2022, 43 (05): 362-379.   DOI: 10.3969/j.issn.1000-6362.2022.05.004 Abstract （214）      PDF（pc） （480KB）（345）       Knowledge map    Save The cultivation of apples plays an important role in China's fruit production. Climate change has brought about more frequent and severe drought and waterlogging disasters, which have negatively impacted apple yield quantity and quality. Through the summary of previous research studies done on the impact of drought and waterlogging disasters and its effect on apple production, methods for disaster prevention and mitigation can be provided to reduce the impact of these disasters to the industry. In this paper, the methods of classification and systematic analysis combined with studying actual disaster cases were used to review the latest research into the effects of droughts and waterlogging disasters on apple production in China and identify the next steps for future research and development into this subject. The intensity and impacts of droughts and waterlogging disasters on apple production are determined by weather, regional climate, topography, soil composition, and several other factors. Adopting the morphological indicators to study these disasters, most existing research into this area only focuses on meteorological factors and rarely consider agrometeorological factors such as soil composition, current crop conditions, and more. The distribution of apple drought disasters in China decreases from north to south. The prevention measures of apple drought and waterlogging included irrigation, strengthening orchard soil management, implementing the integration of soil and fertilizer, etc. More of the current research done into this subject takes place in the Northern parts of China and often lack the necessary information to be put into use in disaster monitoring and early warning applications. In the future, research into apple droughts and waterlogging disasters should focus on increasing in orchard observation data collection, constructing a disaster risk monitoring and early warning model, and implementing the model into apple growing. Related Articles | Metrics | Comments（0）

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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 Abstract （465）      PDF（pc） （468KB）（341）       Knowledge map    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. Related Articles | Metrics | Comments（0）

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Based on the Phenological Model to Study the Possible Changes of Apple Flowering Dates under Future Climate Scenarios in Shaanxi Province WANG Run-hong , RU Xiao-ya , JIANG Teng-cong , WANG Jin-hong , WANG Zhao , SU Bao-feng , ZHANG Dong, YU Qiang , FENG Hao , HE Jian-qiang Chinese Journal of Agrometeorology    2021, 42 (09): 729-745.   DOI: 10.3969/j.issn.1000-6362.2021.09.002 Abstract （425）      PDF（pc） （1975KB）（339）       Knowledge map    Save Shaanxi has large apple cultivation areas and high apple yields, but its yields are susceptible to late frost. The occurrence of freezing damage is closely related to the apple flowering date and the time of late frost. Therefore, accurate prediction of apple flowering date and research on the temporal and spatial changes of apple flowering date is of great significance to the disaster prevention and mitigation of apple production. In this study, the phenological models (e.g. Spring warming model, Sequential model, Overlap model, and Parallel model) were used to study the variations of apple flowering date (including both first flowering date and end flowering date) in Shaanxi Province under the background of climate change. Firstly, four phenological models were selected to evaluate the results of model simulation on apple flowering date in Shaanxi apple producing areas, and the optimal flowering prediction models in the study area needed to be screened out. Then, based on the selected optimal model, the apple flowering date of each representative station (e.g. Luochuan, Baishui, Fengxiang, and Changwu) during the historical period (1980−2019) was simulated. Finally, based on the future meteorological datasets generated by 33 Global Climate Models (GCMs), the selected model was used to simulate the apple flowering date at each representative station from 2021 to 2100 under the two scenarios of RCP4.5 and RCP8.5, and the temporal and spatial variations of flowering date were analyzed. The results showed that the Sequential model was the optimal model to simulate the apple flowering dates in the Eastern and Western area of Weibei, while the Parallel model was the optimal model for Yan'an and the Western area of Guanzhong. From 1980 to 2019, the first flowering date of representative stations was advanced by 3.4−4.7d·10y−1, and the end flowering date of representative stations was advanced 3.3−4.6d·10y−1. The apple flowering date in the study area was gradually delayed from southeast to northwest, and the average annual flowering duration was about 10−11 days. Under the RCP4.5 scenario, the advanced rate of first and end flowering date was 0.7−0.9d·10y−1 and 0.6−0.8d·10y−1 at representative stations from 2021 to 2100. Compared with 1980−2019, the average first and end flowering date for 2021 to 2060 were advanced 0−4.4 days and 0−5.0 days at representative stations, and the average first and end flowering date for 2061 to 2100 were advanced 3.4−7.6 days and 2.6−8.2 days at representative stations. Under the RCP8.5 scenario, the advanced rate of first and end flowering date were 1.3−1.8d·10y−1 and 1.3−1.6d·10y−1 at representative stations from 2021 to 2100. Compared with 1980−2019, the average first and end flowering date for 2021 to 2060 were advanced 1.3−5.9 days and 1.0−6.1 days at representative stations, and the average first and end flowering date for 2061 to 2100 were advanced 6.7−12.4 days and 6.2−12.3 days at representative stations. Under future climatic conditions, the spatial distribution of apple flowering date was basically the same as the historical period, but the duration of flowering date was slightly shortened. For the first time, this study combined the flowering date prediction model with future climate datasets to study the apple flowering date variations in Shaanxi apple producing areas, and it will provide some theoretical basis for coping with the freezing damage in flowering dates caused by climate change in Shaanxi apple producing area. Related Articles | Metrics | Comments（0）

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Analysis of Spatial-temporal Variation Characteristics of Meteorological Drought in the Hexi Corridor Based on SPEI Index XUE Hua-zhu, LI Yang-yang, DONG Guo-tao Chinese Journal of Agrometeorology    2022, 43 (11): 923-934.   DOI: 10.3969/j.issn.1000-6362.2022.11.006 Abstract （289）      PDF（pc） （5405KB）（339）       Knowledge map    Save Using the daily meteorological data of 21 meteorological stations in the Hexi corridor from 1965 to 2017, SPEI at different time scales was calculated based on the Penman-Monteith evapotranspiration model, and the temporal and spatial variation characteristics of meteorological drought in the Hexi corridor, such as the change trend, occurrence frequency and duration, were analyzed. The results showed that: (1) in the past 53 years, the SPEI of the Hexi corridor showed a significant upward trend on the monthly, seasonal and annual scales, which indicated that the drought had a significant weakening trend, but the drought lasted for a long time at individual stations, and the drought lasted for 11 months in 2013 in Wuwei. (2) The Hexi corridor had a trend of wetting in four seasons, and it was significantly wet in winter. Among them, the in spring, summer and autumn presented unstable drought changes, while the sudden change in winter around 1989 indicated the trend from drought to wet. (3) The spatial distribution of drought in the Hexi corridor had obviously regional characteristics. The arid area was mainly concentrated in the northwest, and the humid area was mainly concentrated in the south. (4) The frequency variety law of different grades drought occurance at different time scales was consistent .The frequency of mild to moderate droughts was much higher than that of severe and extreme droughts, and the spatial distribution characteristics of relatively high frequency areas of severe and extreme droughts on the annual and seasonal scales were opposite to those of mild to moderate droughts. Generally, the drought in the Hexi corridor had weakened in the past 53 years, which was beneficial to the local agricultural production and ecological environment. However, the climate change in this region is complex, and local drought needs to be paid attention to. Related Articles | Metrics | Comments（0）

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Construction of Meteorological Grade Index for Summer Maize Lodging LI Shu-yan, XUE Chang-ying, ZHANG Shou-lin, REN Li-wei, CHEN Dao-pei, WEI Qing-wei Chinese Journal of Agrometeorology    2021, 42 (12): 1042-1056.   DOI: 10.3969/j.issn.1000-6362.2021.12.006 Abstract （294）      PDF（pc） （660KB）（337）       Knowledge map    Save Strong wind and precipitation are the direct external conditions that induce maize lodging. In order to accurately define the lodging degree of summer maize under different wind and rain conditions, the data of maize regional variety tests in Hebi city from 2003 to 2019 was used. The wind speed (extreme max. or max.wind speed) and precipitation were extracted according to the recorded lodging time. The quantitative relationship between lodging percentage and meteorological conditions was analyzed, and the summer maize lodging meteorological grade index was constructed. The validations of the indices were conducted using agricultural meteorological observation data and lodging disaster data in the literatures. Firstly, according to the correlations between the lodging percentage and precipitation at different time scales, the “process rainfall” that had a significant impact on lodging was determined as the total amount of precipitation from 1 day before the occurrence of the lodging to 1 hour during the lodging process. R2 of the regression equation between the determined "process rainfall" and the lodging percentage was 0.924. According to the threshold of "process rainfall" of 15mm, the types of lodging disaster weather were classified into "strong wind type" and "wind and rain type". After classification, the fitness between wind speed and lodging percentage for two weather types was significantly improved. The regression equations between meteorological conditions and lodging percentage for two weather types were established. Then, the meteorological factors thresholds for three lodging grades (slight, moderate and severe) were determined responding to the lodging percentage standards 5%, 10%, and 20%, respectively. For the "strong wind type", the indices of light grade were the extreme maximum wind speed between 14m•s−1 and 25m•s−1or the maximum wind speed between 8m•s−1 and 16m•s−1. The indices of moderate grade were the extreme maximum wind speed higher than 25m•s−1 or the maximum wind speed higher than 16m•s−1. For the "wind and rain type", 15mm≤"process rainfall"＜40mm and the extreme maximum wind speed≥11m•s−1 or the maximum wind speed≥5m•s−1 was moderate grade；The indices of severe grade were the "process rainfall" higher than 40mm and extreme maximum wind speed higher than 15m•s−1 or the maximum wind speed higher than 7m•s−1. The validation results of the meteorological grade indices of maize lodging showed that 73% of the judged grades were consistent with the actual disaster grades, and 27% were different by one grade. The indices could provide a reference for meteorological early warning of lodging and guide agricultural production to prevent and reduce disasters. Related Articles | Metrics | Comments（0）

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Risk Analysis of High Temperature Disaster during Summer Maize Flowering Period in Henan Province XU Yan-hong, LIU Tian-xue, FANG Wen-song, LI Shu-yan Chinese Journal of Agrometeorology    2021, 42 (10): 879-888.   DOI: 10.3969/j.issn.1000-6362.2021.10.007 Abstract （274）      PDF（pc） （3934KB）（335）       Knowledge map    Save In recent years, high temperature disaster occurred frequently in China, which had a serious impact on maize and became one of the main meteorological disasters endangering maize production. Based on daily maximum temperature observation data of 110 meteorological stations in the region from 1970 to 2019 and observational data of the summer maize booting period from 19 agro-meteorological observational stations in Henan province, the occurrence days, frequency and disaster risk of high temperature disaster were analyzed by using statistical and spatial analysis methods. Four key meteorological factors were selected to build integrated climatic indexes. The indices included the occurrence probability of temperature higher than 32℃ and 35℃, and the accumulation of temperature higher than 32℃ and 35℃. The results showed that: (1) the days and occurrence probability of temperature higher than 32℃ and 35℃ decreased from 1970s to 1980s, and increased since 1990s. The days of high temperature in 2010s during the summer maize flowering period was increased by 1.4d (≥32℃) and 1.5d (≥35℃), and the occurrence probability increased by 20.6 percent point (≥32℃) and 20.5 percent point (≥35℃). The days of high temperature during the summer maize flowering period was from 1.8 to 4.5d (≥32℃) and from 0.4 to 1.9d (≥35℃), and occurrence probability of high temperature was from 24.3% to 64.3% (≥32℃) and from 2.5% to 31.1% (≥35℃). The spatial distribution has significant difference, and the frequency in the southeastern was higher than other areas. (2) The accumulation of temperature higher than 32℃and 35℃ showed an increasing trend after decreased in the early stage. Compared with the 1980s, the accumulation of temperature in 2010s increased by 52.8℃·d (≥32℃) and 52.5(≥35℃). The accumulation of temperature higher than 32℃ was from 56.7℃·d to 156.4℃·d during the summer maize flowering period and that of higher than 35℃ was from 15.9 to 79.1℃·d, and accumulation of temperature in south was higher than that in the north, and it in the east was higher than that in the west. (3) Integrated risk indexes showed that high risk was mainly located in southeastern areas, which adjacent to the south part of Nanyang, Luohe, the east part of Xuchang, and Zhoukou, accounting for approximately 28.5% of the main summer maize planting area. The risk was moderate in the central region, accounting for approximately 56.2% of the main summer maize planting area. While the risk of heat stress was relatively low in Sanmenxia, Anyang and in the western part of Luoyang and Jiyuan, accounting for approximately 15.3% of the main summer maize planting area. Related Articles | Metrics | Comments（0）

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Application Effectiveness and Problems of Biodegradable Mulch GUO Bo, YANG Zhen-xing, HE Wen-qing, LIU Jia-lei Chinese Journal of Agrometeorology    2023, 44 (11): 977-994.   DOI: 10.3969/j.issn.1000-6362.2023.11.001 Abstract （299）      PDF（pc） （625KB）（331）       Knowledge map    Save Mulch film mulching cultivation technology not only increases agricultural production and income, but also causes serious pollution problems because of the long-term use of polyolefin mulch film and low recovery rates. In areas with serious mulch film residue, the soil structure is seriously damaged, the quality of cultivated land is reduced, agricultural operations are blocked, and crop emergence, nutrient absorption and root growth and development are restricted. Biodegradable mulch film can be degraded by microorganisms such as bacteria, fungi and actinomycetes in the natural environment, and finally decomposed into CO2 and H2O, which not only has no pollution to soil but also promotes the growth and development of crops, and has become one of the effective ways to solve the problem of white pollution. With the deepening of the research on biodegradable mulch film, people found that biodegradable mulch film has different effects on soil environment and crop yield, and these effects are quite different in different regions and crops. It is not possible to directly draw the conclusion that biodegradable mulch film is better than PE mulch film through one or several experiments. In this paper, the effects of biodegradable mulch film on soil environment, crop growth and yield in recent years were summarized, and the experimental effects of biodegradable mulch film (BM) and mulch mulch film (PE) were compared, and their advantages and disadvantages were analyzed, and suggestions were put forward to improve the performance of biodegradable mulch film, so as to continuously improve the performance of biodegradable mulch film and realize the sustainable development of agricultural science and technology. Summary and analysis show that: (1) Biodegradable mulch film can increase soil temperature and humidity, meet the needs of crops in the early stage of growth, accelerate the emergence of seedlings, shorten the growth cycle, and have beneficial effects on soil organic matter, available nitrogen and soil enzyme activity, and improve soil nutrient content. In terms of microorganisms, biodegradable mulch film can promote the growth of soil microbial content and soil respiration rate. At the same time, biodegradable mulch film has better weed control ability than PE mulch film, among which black biodegradable mulch film has the best effect, which can effectively reduce the number of weeds in the field and ensure the supply of nutrients needed by crops. (2) In terms of crops, biodegradable mulch film can promote corn growth, shorten the growth period and increase the yield in the early and middle stages of corn growth. There was no significant difference between the yield of cotton seed cotton covered with biodegradable mulch film and PE mulch film, and the yield of cotton seed cotton covered with mulch film is significantly higher than that of bare land. The potato treated with biodegradable mulch film germinated faster in the early growth stage because of the increase of soil temperature, which significantly shortened the growth cycle and brought it to market earlier, and significantly increased the yield compared with PE mulch film and bare land, among which the black biodegradable mulch film had the most obvious effect. For millet crops, there was no significant difference in yield between the treatment with biodegradable mulch film and the treatment with PE mulch film, and the yield of the treatment with mulch film was significantly improved compared with the treatment with bare land. For vegetable crops such as tomato, eggplant and beet with short growth cycle, biodegradable mulch film can play the role of heat preservation and moisture increase for a long time, and promote the rapid growth of crops. The final yield is not significantly different from that of PE mulch film mulching treatment, even slightly improved, and significantly improved compared with bare land treatment. (3) Put forward the influence of different components of biodegradable mulch film on soil and crops, controllable degradation and cost problems, such as the difficult control of degradation speed, environmental problems caused by incomplete degradation of biodegradable mulch film, low technical maturity and high price, and put forward suggestions for future research and development, so as to modify and innovate biodegradable raw materials, reduce costs and regulate the degradation mechanism of biodegradable mulch film. Strengthen the research on raw materials, formula and production technology of biodegradable mulch film, and develop new biodegradable mulch film with high performance and multifunction, which can meet the regional applicability and crop applicability at the same time, and lay a theoretical foundation for the popularization and application of biodegradable mulch film to more regions and more crop varieties. Related Articles | Metrics | Comments（0）

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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 Abstract （262）      PDF（pc） （23709KB）（328）       Knowledge map    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. Related Articles | Metrics | Comments（0）

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A Review of the Response Characteristics of Soil Respiration to Temperature and Moisture Changes under Global Climate Change RAN Man-xue, DING Jun-jun, SUN Dong-bao, GU Feng-xue Chinese Journal of Agrometeorology    2024, 45 (01): 1-11.   DOI: 10.3969/j.issn.1000-6362.2024.01.001 Abstract （297）      PDF（pc） （724KB）（326）       Knowledge map    Save Warming of the climate and changes in precipitation patterns are major manifestations of climate change and abiotic factors affecting soil respiration. Authors presents a systematic analysis of recent research advances on the effects and mechanisms of temperature and moisture on soil respiration. The results show that:（1）there is positive feedback between soil respiration and climate warming, but the temperature adaptation weakens this positive feedback. The effect of temperature on soil respiration varies spatially and temporally due to the different duration of warming and soil carbon storage. The main mechanisms of soil respiration adaptation to temperature include soil microbial adaptation, substrate depletion and soil mineral activation.（2）The effect of precipitation on soil respiration depends on the initial soil water content. When soil water content is lower than the wilting factor, precipitation not only increases soil water content but also promotes soil respiration, reaching a maximum when soil water content is close to the field holding capacity, while soil respiration is inhibited when soil water content reaches saturation value. The main mechanisms by which water affects soil respiration are substitution and blocking effects, substrate supply, microbial stress and root response. （3）The coupling of soil respiration with soil temperature and moisture depends on the ratio of soil water and heat factors. When soil temperature becomes a stress factor, the stimulating effect of increasing soil water content induced by precipitation on soil respiration is suppressed by the negative effect of low temperature. When soil moisture becomes a stress factor, the promoting effect of increased soil temperature due to climate warming on soil respiration is counteracted by the negative impact of drought. The interaction between soil temperature and moisture should be fully considered when studying soil respiration. In order to understand the disturbance factors of soil carbon emissions in terrestrial ecosystems, this paper proposes that future research on the relationship between soil respiration and the environment under climate change. Firstly, strengthen the research on the effects of multi-factor interaction on soil respiration and quantify the soil respiration components. Secondly, continue to pay attention to the characteristics of soil respiration in response to initial soil temperature and temperature fluctuations, and to explore the effects of biodiversity or community structure composition on soil respiration. Related Articles | Metrics | Comments（0）

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Effects of Elevated Atmospheric CO2 Concentration and Nitrogen Application on Mass Fractions of Carbon and Nitrogen Assimilates in Functional Leaves of Maize after Flowering LI Ming, LI Ying-chun, HAN Xue, NIU Xiao-guang, MA Fen, WEI Na, HE Yu-tong, GUO Li-ping Chinese Journal of Agrometeorology    2021, 42 (09): 715-728.   DOI: 10.3969/j.issn.1000-6362.2021.09.001 Abstract （284）      PDF（pc） （1623KB）（313）       Knowledge map    Save In order to provide the theoretical support for the change of maize physiological processes under global climate change based on the experimental data and provide the evidence for parameter adjustment for crop models, the effects of elevated atmospheric CO2 concentration (eCO2) and its interaction with nitrogen application on the dynamic of concentrations of carbon and nitrogen assimilates and the yield of maize, one of the C4 crops, were studied based on the free air CO2 enrichment (FACE) system. The summer maize variety ZHENGDAN 958 was planted to conduct the field experiments. Four treatments were set under two atmospheric CO2 concentrations, ambient CO2 concentration (aCO2, 400μmol·mol−1) and elevated CO2 concentration(eCO2, 550μmol·mol−1) at two nitrogen levels including zero nitrogen (ZN) and conventional nitrogen (CN, 180 kg N·ha−1) The maize yield and some other physiological parameters were measured including the concentration and dynamic of carbon assimilates (ie. soluble sugar, starch and total carbon), nitrogen assimilates (ie. nitrate, free amino acid, soluble protein, insoluble nitrogen compounds including cell wall-N and thylakoid-N, and total nitrogen), and C/N ratio since flowering of summer maize in the functional leaves. Results showed that: (1) The above-ground biomass and yield of summer maize did not show significant increase under eCO2 possibly due to unexpected disturbance from insect pests at this study. (2) Under eCO2, the concentration of carbon assimilates, including soluble sugar and starch, showed significantly (P<0.05) increase in the functional leaves after flowering. For the nitrogen assimilates, the concentration of some assimilates with simple components, including nitrate, free amino acids, soluble protein, as well as total N and C/N ratio showed increase to some extent (P>0.05); while the concentration of structural N components, including thylakoid-N and cell wall-N, were decreased significantly at later period after flowing, implying the synthesis of structural N components were impacted under eCO2. (3) Under N application, both the carbon assimilates (ie. soluble sugar and starch at most stages) and major nitrogen assimilates were increased significantly in the functional leaves after flowering, as well as the biomass and yield of summer maize. While the concentration of total C did not show significant change in the functional leaves. (4) N application under eCO2 could promote the concentration of simple fractions of carbon assimilate (ie. soluble sugar and starch at most stages) and initial nitrogen assimilates (ie. Nitrate, free amino acids and soluble protein) in the functional leaves of maize, as well as total C, above-ground biomass and yield. Therefore, under the future climate change characterized by increased atmospheric CO2 concentration, appropriate N management and regulation in physiological processes would be helpful in promoting the carbon and nitrogen assimilation and beneficial to the high yield and good quality of maize. Related Articles | Metrics | Comments（0）

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Prediction of Potential Distribution of Diaphorina citri Kuwayama in China under Future Climate Change Scenarios of CMIP6 YAO Jun-meng, LIU Dan, DUAN Li-cheng, CAI Zhe Chinese Journal of Agrometeorology    2021, 42 (12): 1031-1041.   DOI: 10.3969/j.issn.1000-6362.2021.12.005 Abstract （235）      PDF（pc） （1719KB）（306）       Knowledge map    Save Based on the climate data in 1970−2000 and the distribution data of Diaphorina citri Kuwayama in China, the main climatic indices affecting the distribution of Diaphorina citri Kuwayama were identfied by maximum entropy model (Maxent), including temperature seasonality standard deviation, precipitation of driest month(mm), precipitation of coldest quarter(mm), average maximum temperature in January(℃), average maximum temperature in September (℃), average maximum temperature in October(℃) and average minimum temperature in August (℃). The MaxEnt model was reconstructed by the 7 main climatic indices to estimate the impact of climate change on the potential distribution of Diaphorina citri Kuwayama in China. The results showed that climate prediction mode selection of CMIP6 had significant impacts on prediction of the distribution of Diaphorina citri Kuwayama. The overall prediction distribution of Diaphorina citri Kuwayama was the highest in the CanESM5 mode, and the lowest in the BCC-CSM2-MR mode. It showed that the single mode had a greater uncertainty. Affected by climate change, multi-mode ensemble prediction showed that the potential suitable areas in the 2081−2100 for Diaphorina citri Kuwayama would increase significantly compared with in the 1970−2000, from 18.8% (SSP126 scenario) to 55.7% (SSP585 scenario). In the 2081−2100, the potential high suitable area would increase significantly from 78.3% (SSP126 scenario) to 177% (SSP585 scenario). The northern boundary of the suitable distribution shifted northward to about 32°N (SSP126 scenario) and 37°N (SSP585 scenario), while the actual northern boundary was at 30°N in the 1970−2000.This study indicated that climate change would be very beneficial to the spread of Diaphorina citri Kuwayama and threaten the ecological security of citrus-producing in China. The main citrus producing provinces, especially the areas where Diaphorina citri Kuwayama had not been found, need to be vigilant and strengthen the prevention of Citrus Huanglongbing. Related Articles | Metrics | Comments（0）

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Effect of Subsoil Plowing on Soil Bacterial Diversity in Potato Fields in Mountainous Areas of Southern Ningxia YUE Heng, LI Shan-shan, DUAN Ya-xin, LIU Ji-hu, MA Nan, KANG Jian-hong, LU Xing-li Chinese Journal of Agrometeorology    2021, 42 (12): 998-1008.   DOI: 10.3969/j.issn.1000-6362.2021.12.002 Abstract （201）      PDF（pc） （2680KB）（304）       Knowledge map    Save A field experiment during May 3 and October 8, 2019 using Illumina MiSeq high-throughput sequencing methods systematically was conducted to examine the impact mechanisms of three different farming tillage methods (CT, traditional tillage; STD, subsoiling tillage with 30cm soil depth; and STS, subsoiling tillage with 50cm soil depth) on the composition and diversity of soil bacterial communities in potato fields in the mountainous area of southern Ningxia. The seasonal variation of soil enzyme activities, total nitrogen content, organic carbon content, and soil bacterial community composition and diversity were also analyzed. The results showed that: (1) the activities of soil enzymes showed seasonal changes during the entire growth period of potatoes under different tillage methods. STS could significantly increase the activity of urease by 12.9% as compared with CT. When compared with STD and CT, STS could significantly increase the activity of invertase by 17.1% and 56.1%, respectively. As compared with STD and CT treatment, STS increased the activity of catalase by 27.5% and 16.7%, respectively. Additionally, subsoiling treatment could be benefit for the improvement of soil organic carbon content, and total nitrogen content; (2) Sphingomonas belonged to the dominant genus under different tillage treatments in the potato field. Meanwhile, STD significantly increased the relative abundance of Sphingomonas by 24.3% as compared with CT. As compared with CT, STD increased the Simpson index by 0.72%. When compared to the CT treatment, STS significantly increased Shannon index by 6.4%, and Chao 1 value by 35.1%, respectively; (3) Redundancy analysis showed that Shannon index and richness index (Chao1 value) were significantly positively correlated with the activity of soil urease, and soil total nitrogen content. Stepwise regression analysis showed that soil total nitrogen content was the primary factor influencing soil bacterial richness and diversity under different farming methods in the mountainous area of southern Ningxia. Therefore, STS might be the superior farming method for maintaining the high yield of potatoes due to the improvements of the activities of soil enzymes, soil properties, the richness and diversity of soil bacterial community in the area. Related Articles | Metrics | Comments（0）

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Applicability Evaluation of Global Solar Radiation Models in Different Zones of Sichuan Province ZOU Qing-yao, CUI Ning-bo, GONG Dao-zhi, HU Xiao-tao, JIANG Shou-zheng, WU Zong-jun, HE Zi-ling Chinese Journal of Agrometeorology    2021, 42 (07): 537-551.   DOI: 10.3969/j.issn.1000-6362.2021.07.001 Abstract （241）      PDF（pc） （1134KB）（304）       Knowledge map    Save The global solar radiation(Rs) is of great significance in the fields of agricultural production system, hydrometeorological research and clean energy development. Due to the complicated topography and various climate in Sichuan province, the distribution of global solar radiation is uneven. In order to explore the most suitable Rs estimation models for different zones of Sichuan, Sichuan was divided into three solar radiation zones in this paper (zone I: western Sichuan plateau, zone II: eastern Sichuan basin, and zone III: southwest Sichuan mountain) for research. Zone I(Ganzi and Hongyuan stations) has low temperature, sufficient sunshine and strong solar radiation; zone II(Chengdu, Mianyang and Luzhou stations) has high relative humidity, short sunshine duration and low radiation; zone III(Emeishan and Panzhihua stations) is abundant in solar radiation resources, but the air temperature and humidity vary greatly within the zone. In three solar radiation zones, based on the meteorological data from 1994 to 2016, the applicability of six Rs estimation models were evaluated under three weather types(sunny, partially cloudy and cloudy), and the simulation effect of combined models based on weather types in different zones were analyzed. The results showed that: (1) the empirical models performed well in Sichuan province(the coefficient of determination R2 ranged from 0.554 to 0.934, P<0.001). The most accurate simulation model in zone I was sunshine-based model A−P with mean absolute error (MAE) 2.210±0.714MJ∙m−2∙d−1. The hybrid model Chen was the best in zone II (MAE was 1.510±0.027MJ∙m−2∙d−1) and zone III (MAE was 1.510±0.027MJ∙m−2∙d−1). (2) The statistical performance of the six models under three weather types in Sichuan showed sunny>partially cloudy>cloudy. The sunshine-based models(A−P and Ba models) could better simulate the Rs in sunny days, while the hybrid models(Chen and Ab models) had higher accuracy in simulating partially cloudy and cloudy days. The A−P(the global performance indicator GPI = 0.850), Ab(1.294) and Ba(0.862) models were the best models to simulate Rs of zone I in sunny, partially cloudy and cloudy, respectively. The A−P(GPI = 0.381), Chen(1.358) and Chen(1.742) models were the best models to simulate Rs of zone II under three weather types, respectively. The Chen model was the best model to simulate Rs of zone III in sunny, partially cloudy and cloudy with GPI 0.204, 0.857 and 0.526, respectively. (3) The Rs combined models(Mnew) based on weather types had the best simulation accuracy in each zone(GPI were 0.558, 0.582 and 0.134 in 3 zones, respectively). Therefore, it is recommended to use the Rs combined models based on weather types to estimate Rs in Sichuan province. Related Articles | Metrics | Comments（0）