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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 （151）      PDF（pc） （1778KB）（505）       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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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 （263）      PDF（pc） （2053KB）（356）       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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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 （279）      PDF（pc） （343KB）（350）       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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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 （440）      PDF（pc） （285KB）（350）       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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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 （213）      PDF（pc） （21968KB）（348）       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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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 （206）      PDF（pc） （480KB）（332）       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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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 （284）      PDF（pc） （5405KB）（327）       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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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 （290）      PDF（pc） （625KB）（318）       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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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 （278）      PDF（pc） （724KB）（302）       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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High Yield and Water Use Efficiency Synergistical Improvement Irrigation Scheme of Winter Wheat in North China Plain Based on Meta-Analysis ZHOU Li-tao, SUN Shuang, ZHANG Zhen-tao, ZHANG Fang-liang, GUO Shi-bo, SHI Yan-ying, YANG Xiao-guang Chinese Journal of Agrometeorology    2022, 43 (07): 515-526.   DOI: 10.3969/j.issn.1000-6362.2022.07.001 Abstract （260）      PDF（pc） （1251KB）（287）       Knowledge map    Save The effects of irrigation on winter wheat yield and water use efficiency (WUE) were mostly explored based on site-based experiments in North China Plain (NCP) region. However, due to the influences of contrasting environmental factors (e.g. climate and soil properties), these results cannot be accurately cross-compared among different studies, resulting in the difficulty to get the generalizable pattern at regional scale. Here meta-analysis was conducted to comprehensively evaluate the effects of irrigation on winter wheat yield and WUE in NCP region, with the observation data of 1876 pairs from 186 field experimental papers totally. The differences of the irrigation effects in different regions, precipitation year types, soil texture, and nitrogen (N) application levels were explored, and the corresponding optimal irrigation amounts for reaching high yield and WUE were ascertained. Results showed that compared with non-irrigation during the winter wheat growing period, irrigation increased the yield of winter wheat in NCP by 32.0%-38.3%, and reduced the WUE by 27.1%-30.1%. The yield increment due to irrigation in the northwest of NCP (39.6%-53.5%) with total precipitation during the winter wheat growing period below 150mm was higher than that in the southeast of NCP (24.3%-27.1%) with total precipitation during the winter wheat growing period higher than 150mm, while the decrease of WUE due to irrigation in northwest of NCP (32.4%-37.5%) was higher than that in the southeast of NCP (22.0%-24.3%). The optimum irrigation amount for high yield and WUE of winter wheat was 150-180mm in the northwest and 120-150mm in the southeast. Specifically, for different precipitation year types, the optimum irrigation amounts were 120-150mm with 2 times during jointing and flowering stages for dry year, during jointing and heading stages for normal year, and during jointing and booting stages for wet year. For different soil texture, irrigation under loamy soil had the highest increases in yield, while clay soil had the lowest decreases in WUE; the optimum irrigation amounts of winter wheat with four different soil texture of sandy soil, loam, clay loam and clay were 60-90mm, 120-150mm, 180-210mm, and 150-180mm, respectively. For different N application levels, N application of 120-240kg·ha−1 led to the highest yield and WUE under the irrigation amounts of 80-140mm, of which the higher yield was obtained under irrigation amounts of 110-140mm, and the higher WUE was obtained under the irrigation amounts of 80-110mm. Collectively, the NCP region can achieve the goals of high yield and WUE when irrigation amount was 120-150mm with 2 times but at different stages during different precipitation year types (i.e. dry year, normal year and wet year). Meanwhile, the combination of loam conditions with the N application of 120-240kg·ha−1 can synergistically improve the yield and water use efficiency of winter wheat. Related Articles | Metrics | Comments（0）

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Evaluation and Projection of Temperature in Southwestern China by CMIP6 Models JIN Cheng-xiu, JIANG Chao, ZHANG Xi-yue Chinese Journal of Agrometeorology    2022, 43 (08): 597-611.   DOI: 10.3969/j.issn.1000-6362.2022.08.001 Abstract （319）      PDF（pc） （5094KB）（274）       Knowledge map    Save Using on the CN05.1 monthly average temperature observation data set from 1961 to 2014 and the output data from 19 global climate models from Coupled Model Intercomparison Project Phase 6 (CMIP6), the simulation ability of CMIP6 models on the climatology spatial distribution and interannual variability of temperature in Southwestern China was systematically evaluated by means of Taylor diagram, Taylor index and interannual variability skill score. The variation characteristics of future temperature in this area were predicted under SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios. The results showed that: (1) compared with other seasons, most CMIP6 models had the best performance in simulating the spatial distribution of autumn temperature climatology during 1961-2014; and CMIP6 models underestimated the interannual variability of seasonal and annual average temperature. Among the 19 models, the best models simulated the temperature in Southwestern China were ACCESS-CM2, CMCC-CM2-SR5 and CMCC-ESM5. (2) The multi-model ensemble mean(MME) of 3 best-fit models simulated the climatology spatial distribution and interannual variability of average temperature better than the MME of 19 models. (3) Compared with the multi-year average temperature observed in the same period during 1961−2014, the seasonal and annual average temperature in Southwestern China showed an upward trend in the future under the four climatic scenarios, seasonal and annual average temeprature increased by 0.94−3.48℃. Under the four scenarios, the increase of average temperature in summer was the largest(2.17−3.48℃) and the interannual fluctuation range was the smallest, the increase of temperature in winter was the smallest(0.94−2.24℃) and the interannual fluctuation range was the largest. (4) In the early of 21st century, there was little difference in the increase of seasonal and annual average temperature under 4 scenarios. During the middle of the 21st century, the upward trend of seasonal and annual average temperature in high radiation forcing scenarios was gradually larger than that in low radiation forcing scenarios. (5) Under the four scenarios, the anomaly values of multi-year average temperature at the early (2015−2034), middle (2045−2064) and end (2081−2100) period of 21st century and the historical(1961−2014) observed temperature showed the spatial distribution characteristics that the northwest was greater than southeast of this region, and the high latitude and high altitude areas were greater than the low latitude and low altitude areas. With the passage of time, at the end of 21st century, the temperature anomaly in the same region was significantly higher under high forcing scenarios than that in low forcing scenarios. Related Articles | Metrics | Comments（0）

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Yield and Water Use of Maize/Soybean Intercropping Systems in Semi-Arid Western Liaoning CAI Qian, SUN Zhan-xiang, WANG Wen-bin, BAI Wei, DU Gui-juan, ZHANG Yue, ZHANG Zhe, FENG Chen, XIANG Wu-yan, ZHAO Feng-yan Chinese Journal of Agrometeorology    2022, 43 (07): 551-562.   DOI: 10.3969/j.issn.1000-6362.2022.07.004 Abstract （193）      PDF（pc） （1181KB）（263）       Knowledge map    Save To explore the mechanism of overyielding, improvement of land productivity and water use of maize/soybean intercropping, and optimize the configuration of the intercrop in semi-arid western Liaoning, a 2-year (2018-2019) field experiment was conducted at the National Agricultural Environmental Station for Agricultural Environment at Fuxin. The effects of maize-soybean intercropping on yield, land productivity, spatial distribution of soil water content and water use efficiency were studied. Cropping systems were, (1) 2 rows of maize: 2 rows of soybean (M2S2), (2) 4 rows of maize: 4 rows of soybean (M4S4), (3) 6 rows of maize: 6 rows of soybean (M6S6), (4) sole maize (M) and (5) sole soybean (S). The total yields of the 5 cropping systems were M＞M6S6＞M4S4＞M2S2＞S. In intercrops, the contribution of maize for total crop yield was greater than soybean, with 79.0%−87.3% of the contribution rates for intercropped maize, and 12.7%−21.0% for intercropped soybean. The land equivalent ratios (LER) of M6S6 and M4S4 were 1.13−1.19 and 1.06−1.07, respectively, indicating a yield advantage of the intercrop, among which M6S6 showed the highest land productivity. The LER of M2S2 was less than 1, indicating a yield disadvantage. The spatial distribution of soil moisture showed that there was water competition between maize and soybean in 0−50cm soil layer, and was water complementarity between maize and soybean in 60−100cm soil layer in intercrops. On the same land area, all the intercrops improved water use efficiency of maize. M2S2 and M4S4 decreased the water use efficiency of soybean. The water equivalent ratio (WER) of M6S6 and M4S4 were 1.18−1.21 and 1.05−1.06, respectively, indicating the water productivity was increased by 5%−21%. Both of M2S2 and M4S4 had water use advantages, and M6S6 showed the highest water use advantage. The WER of M2S2 was 0.99−1.01, indicating a not significant water use advantage (P>0.05). Overall, M6S6 showed the most significant yield and water use advantage, and would provide opportunity for sustainable agriculture in semi-arid western Liaoning. Related Articles | Metrics | Comments（0）

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Hyperspectral Remote Sensing of Crop Information Based on Machine Learning Algorithm: State of the Art and Beyond ZHAO Jin-long, ZHANG Xue-yi, LI Yang Chinese Journal of Agrometeorology    2023, 44 (11): 1057-1071.   DOI: 10.3969/j.issn.1000-6362.2023.11.007 Abstract （226）      PDF（pc） （403KB）（259）       Knowledge map    Save Machine learning, as a new technique combining statistics and computer science, has been widely used in crop information acquisition tasks in recent years. Traditional methods for obtaining crop information mainly rely on chemical detection methods, which is time-consuming and labor-intensive. Based on machine learning algorithms and hyperspectral remote sensing techniques, crop appearance and internal physical and chemical parameters can be quickly sensed in a non-destructive way, which has obvious application advantages and development prospects. First, the researches related to the hyperspectral remote sensing of crop information were systematically reviewed in this paper. Second, the application, advantages and disadvantages and uncertainties of different machine learning algorithms in hyperspectral sensing crop information were summarized. Finally, it was pointed out that the future development trends of hyperspectral sensing crop information were as follows: (1) complementary crop information acquisition methods could be realized through multi-source remote sensing collaborative observations. (2) The assimilation technologies of hyperspectral remote sensing and crop model as well as the deep integration technologies of hyperspectral remote sensing and artificial intelligence could be developed. (3) The intelligent acquisition of key information oriented to the whole growth period of crops and decision-making could be realized. Related Articles | Metrics | Comments（0）

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Effect Mechanism of High Temperature and High Humidity Stress on Yield Formation of Cucumber YANG Li, YANG Zai-qiang, LU Si-yu, ZHANG Yuan-da, ZHENG Han Chinese Journal of Agrometeorology    2022, 43 (05): 392-407.   DOI: 10.3969/j.issn.1000-6362.2022.05.006 Abstract （221）      PDF（pc） （2044KB）（254）       Knowledge map    Save To investigate the effects of high temperature and high humidity compound disasters on leaf photosynthesis and flower sex differentiation of cucumber plants, the cucumber variety "Jinyou101" was used as the test materials. The three factors orthogonal test of air temperature, air relative humidity and treatment days was conducted in the artificial climate chamber of Nanjing University of Information Science and Technology from May to September 2020. Four levels of day/night temperature were set to 32℃/22℃, 35℃/25℃, 38℃/28℃ and 41℃/31℃. The air relative humidity was set at three levels: 50%, 70% and 90%（±5 percent point）, and the durations of treatment time were designed for 3, 6, 9 and 12 days. The treatments of day temperature 28℃/ night temperature 18℃, air relative humidity 50%±5pp were used as control (CK). The photosynthetic parameters, chlorophyll content and endogenous hormone content of terminal bud were measured systematically, and the floral differentiation of each node and final yield were observed. The results showed that: （1）the total amount of chlorophyll in cucumber leaves decreased with the increase of temperature and the extension of stress time. After 12 days of stress, chlorophyll a, chlorophyll b and carotenoid contents in cucumber leaves reached the lowest value, which decreased by 31.51%, 22.62% and 37.10% compared with CK, respectively. （2）The Pmax (maximum net photosynthetic rate), LSP (light saturation point) and AQE (apparent quantum efficiency) values of cucumber leaves decreased significantly with the deepening of high temperature and humidity stress. The LSP, AQE and Pmax values of cucumber leaves at 41℃ were the lowest, which were 48.78%, 40.00% and 43.04% lower than those of CK, respectively. In the range of 32−41℃, the Pmax values of cucumber leaves under 70% air relative humidity were higher than those under other humidity treatments, and the differences were small compared with CK. （3）In the process of flower bud differentiation, the contents of ZT (anti-zeaxin), ABA (abscisic acid) and GA3 (gibberellin) in cucumber terminal buds increased firstly and then decreased, while the contents of IAA decreased gradually with the growth of cucumber plant. The contents of ZT, IAA and GA3 in cucumber terminal buds decreased gradually with the increase of temperature and days of stress, while the changes of ABA content were on the contrary. At the end of 41℃, the contents of ZT, IAA and GA3 decreased by 47.37%, 26.38% and 83.65%, respectively, compared with CK, while the ABA content increased by 27.27% compared with CK. After 12 days of stress, the contents of ZT, IAA and GA3 reached the lowest values in the same period (0.07µg·g−1, 1.11µg·g−1, 0.75µg·g−1), while the ABA content reached the highest values in the same period (1.89µg·g−1).（4）High temperature and high humidity stress increased the node position of each female flower, but decreased the node rate of female flower and the number of flower buds. When treated with 70% air relative humidity, the nodes of female flowers were decreased, and the proportion of female flower nodes and the number of flower buds were increased. （5）High temperature and high humidity stress significantly reduced cucumber yield, and the yield of cucumber treated at 41℃ was 38.50% lower than that of CK. The study found that high temperature inhibited photosynthesis in cucumber leaves, disrupted the endogenous hormone balance in terminal buds, and reduced the number of female flower differentiation, resulting in lower final yield. Related Articles | Metrics | Comments（0）

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Progresses of Crop Model Application and Its Integration with Remote Sensing Technology PENG Hui-wen, ZHAO Jun-fang, XIE Hong-fei, FANG Shi-bo Chinese Journal of Agrometeorology    2022, 43 (08): 644-656.   DOI: 10.3969/j.issn.1000-6362.2022.08.005 Abstract （269）      PDF（pc） （379KB）（248）       Knowledge map    Save Crop model remote sensing and play important roles in agricultural production monitoring, evaluation, and future prediction with their unique advantages. The integration technologies of crop model and remote sensing information have obvious application advantages and broad development prospects in monitoring, evaluation and prediction of large-scale and high-precision agricultural production. In order to promote the wider applications of these technologies in crop yield prediction, impact assessments of agrometeorological disaster, and agricultural decision-making to deal with climate change on a regional scale, the method of literature review were adopted in this paper. The development and application of crop models in Europe, United States, Australia and China were systematically summarized. The principle, characteristics and shortcomings of the current mainstream data integration methods were concluded. The practical applications of integration technologies of crop model and remote sensing information were summarized. The existing problems in improving the accuracy of data integration were discussed, and the future research direction was prospected. The results showed that the research and application of crop model and its integration with remote sensing data were extensive and intensive at home and abroad. The assimilation method could effectively improve the simulation accuracies of crop model, providing technical support for crop growth and yield evaluation on regional scales, impacts of climate change on yield, farmland management decision-making, etc. The uncertainties from crop model simulation results and remote sensing inversion data, diversities of data assimilation strategies, and scale effects were the limiting factors to further improve the accuracy and efficiency of integrated systems. Therefore, multi-source fusion of remote sensing data, multivariable cooperation in assimilation process, multi-type coupling of crop models, and high-performance parallel computing of data were the development trends of integrating crop models and remote sensing research in the future. Related Articles | Metrics | Comments（0）

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Effects of Short-term High Temperature on Spikelet Opening Dynamics and Yield of Different Rice Varieties during Flowering Period XU Peng, HE Yi-zhe, HUANG Ya-ru, WANG Hui, YOU Cui-cui, HE Hai-bing, KE Jian, WU Li-quan Chinese Journal of Agrometeorology    2023, 44 (01): 25-35.   DOI: 10.3969/j.issn.1000-6362.2023.01.003 Abstract （302）      PDF（pc） （630KB）（248）       Knowledge map    Save Under the background of global warming, high temperature weather occurs frequently in the Yangtze River Basin, which has become the primary problem seriously affecting the safe production of rice in this region. In order to clarify the effects of short-term high temperature on the spikelet opening dynamics and yield of different rice varieties during flowering period, the heat-resistant rice variety N22 and heat-sensitive rice variety YR343 were used as experimental materials and planted in pots. From the day of heading and blooming, the artificial climate chamber was used for temperature treatment, with 32℃/25℃ (day/night) as the control, 38℃/30℃ as the high temperature treatment, and continuous treatment for 7 days. Samples were taken on the 1st, 3rd, 5th, and 7th days of treatment to study the effects of high temperature stress on the opening dynamics, physiological characteristics of spikelets and yield of rice in different days of flowering. The results showed that: (1) the yield and seed setting rate of rice showed a decreasing trend after high temperature stress, and the reduction range was related to the duration of high temperature. After 7 days of high temperature treatment, the yield and seed setting rate of N22 decreased by 49.1% and 37.4%, and that of YR343 decreased by 85.1% and 65.3%, respectively. (2) The anther dehiscence rate and pollen activity of rice decreased to varying degrees after high temperature stress during flowering, and the longer the high temperature lasted, the greater the decrease. (3) The total amount of spikelet opening of rice was significantly reduced under high temperature stress, in N22 and YR343, by 33.3% and 65.5%, respectively. The flowering peak and peak appearance time of rice changed under high temperature stress. Compared with the control, the flowering peak ratio of N22 and YR343 decreased by 0.5% and 2.8%, respectively, and the flowering peak of N22 appeared 1 h earlier, while that of YR343 did not change. And under the high temperature coercion, YR343 has a shortened flowering period. (4) The changes of the physiological indices of rice spikelets under high temperature stress were as follows: the contents of soluble protein, soluble sugar and proline generally decreased; the contents of malondialdehyde and hydrogen peroxide increased; the activity of antioxidant enzymes showed a trend of first increasing and then decreasing. In summary, the low seed setting rate is the main reason for the reduction in rice yield. High temperature stress leads to the reduction of rice yield, mainly by changing the spikelet opening dynamics and its physiological characteristics, reducing the anther dehiscence rate and pollen activity, and thus reducing the seed setting rate. Related Articles | Metrics | Comments（0）

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Phenological Change and Its Climatic Impact Factors of Apple under the Background of Climate Warming in South-Central Tibet DU Jun, PU Gui-juan, Sonamwangdoi, WANG Ting, Pasang Chinese Journal of Agrometeorology    2023, 44 (03): 171-181.   DOI: 10.3969/j.issn.1000-6362.2023.03.001 Abstract （212）      PDF（pc） （635KB）（245）       Knowledge map    Save To reveal the characteristics of apple phenology changes and its response to climate warming on the Tibetan plateau, with a view to providing basic scientific and technological support for local apple cultivation, management, breeding and coping with climate change. Both phenological data and meteorological items measured in the period of apple growth in Tsedang agrometeorological station from 2001 to 2020 were analyzed, which include phenological dates and the daily mean value of several meteorological factors such as mean temperature(Tm), maximum temperature(Tmax), minimum temperature(Tmin), diurnal temperature range(DTR), precipitation(Pr), relative humidity(RH), sunshine duration(S), and accumulated temperature above 0℃(∑T0) et al. Statistical methods, including linear regression, Pearson correlation coefficient and stepwise regression, were used to reveal the trends and identify the leading factors caused the changes in apple phenology in south-central Tibet in the past 20 years. The results indicated that: (1) all of the apple phenological dates were postponed in a range from 2.83 to 7.64d·y−1 in south-central Tibet from 2001 to 2020 except for the fruit maturing date (FMD), which exhibited an advanced rate of 1.28d·y−1. The length of fruit growing period (LFG) and flowering duration (FD) were shortened by 8.92d·y−1 and 5.98d·y−1, respectively, while the length of tree growing season(LTG) was slightly extended at an increasing rate of 0.65d·y−1. These results were different from the main apple producing areas in northern China where the autumn phenophase was delayed and the spring phenophase was advanced, and may be attributed to the reduction of ∑T0 during the growth seasons. (2) For all of apple phenological stages, the Tmax has increased with Tmin decreasing, leading to a significant larger value of DTR. For most of the phenological stages, RH and S have reduced significantly, while Pr increased before FMD and decreased afterwards. (3) In spring, temperature was identified as the dominant factor with negative correlation with the phenophase in south-central Tibet. In contrast, Pr was the leading factor causing changes in autumn phenophases, which was positively correlated with the FMD and negatively correlated with both the end of leaf coloring date (LCD) and the end of leaf fall date (LFD). (4) For most of the phenology, ∑T0 has been revealed as the leading factor influencing the length of phenological period. However, Tm has played the dominant roles influencing the length of the whole period and the period from the FMD to LCD, and S can be viewed as the leading factor influencing the length of the period from the LCD to LFD. It has been identified that the first flowering date was advanced by 2.32 days when Tmax increased by 1°C in early March, and the LFD was advanced by 8.55 days when Pr changed with 10mm in late October in this study region. Related Articles | Metrics | Comments（0）

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GIS-based Risk Zoning and Assessment of Mongo Cold and Freezing Injury in South China SUN Chao-feng, LIN Wen, HUANG Chuan-rong, WU Li, CHEN Jia-jin, WANG Jia-yi, LIN Hui-yang Chinese Journal of Agrometeorology    2022, 43 (07): 563-575.   DOI: 10.3969/j.issn.1000-6362.2022.07.005 Abstract （189）      PDF（pc） （1537KB）（237）       Knowledge map    Save Based on the observation data of 115 weather stations of mango planting areas in South China (Guangdong, Guangxi and Fujian) from 1961 to 2016, combined with mango cold and freezing injury index, the weighted comprehensive evaluation method was used to determine the cold and freezing injury hazard index of each meteorological station in the planting area, and then established a multiple linear regression model between the cold and freezing injury hazard index and geographical factors. Finally, the regionalization of cold and freezing injury to mango in South China was made based on GIS technology. The results showed that there was a close relationship between the risk of cold and freezing injury and geographical factors in South China mango planting areas, and an overall trend was that the risk of mango cold and freezing injury gradually increased from coast to inland. In addition, with the increase of latitude and altitude, the risk of cold and freezing injury gradually increased from south to north. The slight risk areas were mainly distributed in the southern coastal areas and the low altitude areas of some inland cities of South China mango planting areas, accounting for 56.85% of the planting area, which was suitable for large-scale mango planting. The moderate risk areas were mainly distributed in the inland low and middle altitude areas of the mango planting area in South China, and the high latitude coastal areas in the north, accounting for 37.03% of the planting area. Furthermore, the severe and over severe hazard areas were mainly distributed in the inland high altitude areas of mango planting areas in South China, accounting for 6.12% of the planting area. Through the verification of historical disaster and annual production information of each county, the zoning result was consistent well with the actual situation. The results of this study could provide reference for the optimal layout and disaster prevention and mitigation of mango in South China mango planting area. Related Articles | Metrics | Comments（0）

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Spatiotemporal Variation and Risk Zoning of Spring Frost Disaster for Tea Plant in Dabie Mountains CAO Qiang, YANG Xian-gui, DONG Shi-jie, LUO Xiao-dan, LI Hong-fei, CHEN Xi, YUE Wei Chinese Journal of Agrometeorology    2024, 45 (01): 67-78.   DOI: 10.3969/j.issn.1000-6362.2024.01.007 Abstract （171）      PDF（pc） （3420KB）（235）       Knowledge map    Save Based on the daily meteorological data of 35 national meteorological observation stations in Dabie Mountains from 1971 to 2020, the spatiotemporal distribution characteristics of spring frost disaster for tea plant were analyzed with trend surface interpolation and ArcGIS technology. According to the theory of natural disasters risk, the risk of hazard-formation factors, the exposure of hazard-formation environments, the vulnerability of hazard-affected bodies and the capability of hazard prevention and mitigation were taken as the evaluation factors, the weighted comprehensive evaluation method was used to construct the comprehensive risk assessment model of spring frost disaster. The risk zoning had been carried out based by the means of ArcGIS technology. The results showed that: (1) the number of occurrence days of spring frost in different grades decreased significantly from 1971 to 2020, with the average number of occurrence days of total, slight, moderate and severe spring frost being 9.6, 5.2, 3.0 and 1.4d respectively, and the climatic tendency rates being -1.45, −0.61, −0.54 and −0.30d·10y−1. The number of occurrence days was positively correlated with altitude and latitude, and the downward trend of the number of occurrence days in the northern region was much more obvious than that in the southern region. (2) The high risk, medium risk and low risk areas of tea spring frost disaster accounted for 16.67%, 41.88% and 41.45% of the total area in the study region respectively. The high-risk areas were mainly located in the high mountainous regions with an altitude of more than 600m in Jinzhai, Yuexi, Huoshan, Yingshan and Xinyang, as well as scattered shady slopes (northern slopes); the medium-risk areas were mainly located in the mountainous region with an altitude of less than 600m and most of the low-altitude region at the northern foot of Dabie Mountains, and scattered shady slope (north slope) in the low-altitude region at the southern foot of Dabie Mountains; the low-risk region were mainly located in the low-altitude region at the southern foot of Dabie Mountains, and scattered sunny slope (south slope) in the low-altitude areas at the northern foot of Dabie Mountains. The refined assessment of the risk of tea spring frost could provide reference for optimizing the layout of the tea industry and enhancing disaster prevention and mitigation capabilities in Dabie Mountains. Related Articles | Metrics | Comments（0）

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Spatiotemporal Patterns of Seasonal Mean Temperature Variations in China During 2001−2100 FU Da-rong, CHEN Xiao-die, LIU Yi-ting, LIU Li, PENG Shou-zhang Chinese Journal of Agrometeorology    2022, 43 (09): 681-691.   DOI: 10.3969/j.issn.1000-6362.2022.09.001 Abstract （321）      PDF（pc） （5662KB）（229）       Knowledge map    Save Based on the 1-km resolution long time series temperature data set, the spatial and temporal patterns of the magnitude and trend of the four-season mean temperature changes in the historical period (2001−2020), and in the future period (2021−2100) under the low forcing scenario (SSP119), medium forcing scenario (SSP245) and high forcing scenario (SSP585) are analyzed using the distance level method, Mann-Kendall trend test method and Sen's slope estimation method, with a view to providing a basis for developing detailed regional adaptation strategies in the context of climate warming. The results show that: (1) compared with the historical period, the average temperature of the four seasons in the future will increase in general under the three scenarios, and the area with the largest increase in summer is 66.70% under SSP119, 37.37% and 99.06% under SSP245 and SSP585, respectively. At the same time, the overall variation range of seasonal mean temperature under the three SSP scenarios is significantly different, which is moderated under SSP119, followed by SSP245, and the largest increase range under SSP585. (2) In the historical period, compared with other seasons, the significant rise in mean temperature in spring had the fastest rate (0.68±0.24℃∙10y−1) and the largest area share (14.44%), mainly distributed in North China, Yunnan, Guizhou, Jiangsu and Zhejiang provinces. (3) In the future period, the regional seasonal mean temperature in China shows an overall rising trend with significant spatial differences; among them, under the SSP119 scenario, the regions with significantly rising mean temperature in spring and winter are mainly concentrated in southern China and the local area of the Qinghai-Tibet Plateau, accounting for 29.03% and 25.58% of the area, respectively; under the SSP245 and SSP585 scenarios, the seasonal mean temperature in all regions of China shows a significant upward trend; under the SSP585 scenario, the seasonal mean temperature in the north increases at a faster rate than that in the south, and the national region has the fastest significant rate of increase in winter (0.66±0.09℃∙10y−1). Related Articles | Metrics | Comments（0）

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Climatic Suitability and Potential Analysis of Apple Planting in Northern Expansion Area of Shaanxi Province LIANG Yi, QU Zhen-jiang, LU Cheng, ZHANG Li, LIU Lu, WANG Jing-hong Chinese Journal of Agrometeorology    2023, 44 (05): 347-360.   DOI: 10.3969/j.issn.1000-6362.2023.05.001 Abstract （301）      PDF（pc） （5232KB）（226）       Knowledge map    Save The purpose of this study is to clarify the fine distribution of climatic suitable area for apple planting in the northern extension area of Shaanxi province in the new climate period (1991−2020), and reveal the development potential of apple planting in this region. Based on the meteorological observation data, the digital elevation model data and the arable land confirmation data，the requirements for the climatic suitability and mountainous site conditions of apple planting in the northern expansion area of Shaanxi province were comprehensively analyzed. Seven factors, including annual average temperature, annual precipitation, average relative humidity from June to August, average minimum temperature from June to August, average temperature in January, aspect and slope, were selected as zoning indexes to divide the climatic suitability of apple planting in the research area. The multiple regression method was used to simulate and calculate the spatialization of every climatic factor. Then the suitability quantitative evaluation model of each single factor was constructed by fuzzy set linear membership function method. The climatic suitability regionalization of apple planting in the northern extension area of Shaanxi was developed by weighted comprehensive evaluation and set optimization methods. Finally, the distribution of dry land and irrigation area in the suitable planting area for apple of each district was extracted by using the arable land confirmation data. The results showed：(1) the northern boundary of the suitable area for apple planting in Shaanxi was from Wuqi county, the middle and south of Jingbian county to the northeast through the south of Hengshan county, Mizhi county to the middle and southern of Jiaxian county, whose terrain were mainly hilly and gully area along the sunny gentle slope, with a general altitude of 730-1660m. (2) The field investigation showed that the zoning result was about 80% consistent with the field planting distribution of apple orchard. (3) The refined spatial distribution of climatic appropriate areas for apple by county (district) based on the arable land confirmation data showed that the area of climatic suitable level above for apple could be developed in the northern expansion zone was about 276.9kha, accounting for 24.6% of the available arable land, among which the dry land area accounted for 96.3%, with rain-fed agriculture as mainstay. Compared with the statistical data of apple planting status in each county (district), it could be seen that there was still 4.9−28.5kha development space in most counties (districts) except Shenmu county and Fugu county in Yulin city, and Wuqi county in Yan’an city. The potential planting area of climatic suitable for apple in Zhidan county in Yan’an city had tended to be saturated. The results can provide reference for optimizing regional layout of apple industry under the background of climate change. Related Articles | Metrics | Comments（0）

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Detecting Response of Vegetation Photosynthesis to Meteorological Drought Based on Solar-Induced Chlorophyll Fluorescence QI Xiao-wen, MIAO Chen, WANG He-song Chinese Journal of Agrometeorology    2023, 44 (02): 133-143.   DOI: 10.3969/j.issn.1000-6362.2023.02.005 Abstract （220）      PDF（pc） （1473KB）（222）       Knowledge map    Save Drought is the most common and complex meteorological disaster in the world, which weakens the carbon sink function of terrestrial ecosystem. Exploring the response of vegetation to drought and choosing sensitive factors for drought detection will be helpful to obtain the impact of drought on vegetation and to understand the response process and the mechanism of vegetation to drought stress. Based on the Solar-Induced chlorophyll Fluorescence (SIF) and the standardized precipitation evapotranspiration index (SPEI), a maximum correlation coefficient method was used to investigate the response of vegetation photosynthesis to meteorological drought in China during the growing season from 2000 to 2018. Sensitivity and response time scale of vegetation to drought was compared for different drought levels and different vegetation types. The results showed that: (1) about 75.05% of total areas of China had a significant positive correlation between SIF and SPEI. These areas were mainly distributed in the northeast, southwest and Qinghai Tibet Plateau of China. The response time scale of most regions to SPEI was mainly medium and short term. (2) The proportion of SIF to SPEI was the lowest in spring, the highest in summer, and slightly decreased in autumn. The response time scale to drought was mainly short-term in spring, while the region with long response time scale in summer was increased compared with in spring. (3) The semi-arid region was the most sensitive to drought, while the arid region was the weakest. The response time scale of different climatic regions to drought was mainly short-term. (4) The selected vegetation types responded to drought in a short time scale. Grassland was the most sensitive to drought, while woodland and cropland were relatively weak. Besides, broad-leaved forest was more sensitive to drought than coniferous forest. The results showed that under different drought gradients and different vegetation types, SIF could quickly reflect the impact of environmental stress on vegetation photosynthesis. Related Articles | Metrics | Comments（0）

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Study on Frost Risk during Apple Blossom in Northern China under Different Climate Change Scenarios QIU Xing-lin, LIN Ze-quan, LI Can, YU Hai-yang, WANG Ying Chinese Journal of Agrometeorology    2024, 45 (01): 33-44.   DOI: 10.3969/j.issn.1000-6362.2024.01.004 Abstract （170）      PDF（pc） （11528KB）（219）       Knowledge map    Save The main apple-producing areas in northern China are located in the North China plain and the loess Plateau, and the apple blossom frost hazard events have had a severe impact on the income of fruit growers and the economy of the production areas. Future climate change will exacerbate the frequency and intensity of extreme weather and climate events. In this study, based on the climate model data shared by NEX-GDDP, the seven models with the best fitting ability for the minimum temperature during apple blossom were selected using Taylor diagrams, and the annual encounter values of the minimum temperature during apple blossom were calculated and revised using the transfer function correction method of the extreme value distribution, so as to predict the risk of frost disaster and yield reduction of apples in northern China under climate change. Taking the intensity of the apple blossom frost disaster with a 30-year occurring period event across the study area as an example, in the near and distant future under the RCP4.5 scenario, the regions of Henan, Shanxi, northern Shaanxi and, northern Ningxia were the main affected areas, dominated by the minimum temperature of −3 to −2°C, and the highest yield reduction rates were in the northern regions of Henan, Ningxia, Shanxi, and northern Shaanxi provinces, with the yield reduction rate of apples in northern China ranging from 2.47% to 5.22%. Under the RCP8.5 scenario, the frost disaster area with a minimum temperature of −3°C or less expands to the whole of Henan, central Shandong and other places, and the yield reduction rate of apples in northern China is 4.57%−12.39%. In the future, apple cultivation in these areas needs to strengthen the prevention of frost disaster risk. Related Articles | Metrics | Comments（0）

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Review on the Impacts of Climate Change on Highland Barley Production in Tibet Plateau HAO Shuai, SONG Yan-ling, SUN Shuang, WANG Chun-yi Chinese Journal of Agrometeorology    2023, 44 (05): 398-409.   DOI: 10.3969/j.issn.1000-6362.2023.05.005 Abstract （220）      PDF（pc） （444KB）（213）       Knowledge map    Save The Tibet plateau is strongly sensitive to global climate change and the ecosystem is very fragile. Highland barley is a major crop on Tibetan plateau and sensitive to climate change. Authors reviewed the studies on the impact of current and future climate change on barley production over the Tibetan plateau and summarized the changes of agro-meteorological resources and agro-meteorological disasters, as well as the impact of climate change on barley cropping systems, fertility and yield. The results of studies have shown that a significantly warmer trend was observed on the Tibet plateau compared to the trend in other regions, together with increasing precipitation, reduced sunshine hours, and more frequent agro-meteorological disasters such as drought and floods under climate change. The potential planting boundary of highland barely moved to higher latitudes and altitudes under climate change, which led to the potential cultivated region increasing. The climate change shortened the growth period and showed a potentially positive impact on highland barley growth. Cultivar renewal combined with technological advances boosted highland barley yields and the ability to climate change adaption. The future climate change would shorten the growth period of highland barley, which posed a big threat to highland barley production and food security on the Tibet plateau. Existing reports are limited in terms of the study area and there are few studies on climate compounding impacts and integrated risk assessment. Therefore, it is necessary to gain a deeper understanding of the mechanism of climate change impact on barley production, the technology of dynamic assessment of meteorological disaster impact and comprehensive risk, and to develop effective measures to promote the adaptation of highland barley to climate change, which can ensure food security for Tibetans over Tibet plateau. Related Articles | Metrics | Comments（0）

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Assessment Regional Grain Yield Loss- Formulation of Agrometeorological Disaster-Yield Model of Inner Mongolia Autonomous Region ZHU Yong-chang, LIU Bu-chun, LIU Yuan, SHIRAZI Zeeshan-Sana Chinese Journal of Agrometeorology    2023, 44 (01): 36-46.   DOI: 10.3969/j.issn.1000-6362.2023.01.004 Abstract （195）      PDF（pc） （624KB）（212）       Knowledge map    Save The aim of this paper is to assess the loss of grain production caused by agrometeorological disasters in the Inner Mongolia Autonomous Region (IMAR), which is an important grain production base of China. The disaster-yield assessment model was formed and verified using grain production, yield, planting area and agrometeorological disaster conditions data of the IMAR from 1981 to 2020, and the loss of grain yield caused by meteorological disasters was assessed by this model. The results showed that grain production, yield and planting area observed an escalating trend from 1981 to 2020, and the rate of increase was 78.85×104t·y−1, 100.97kg·ha−1·y−1 and 74.48×103ha−1·y−1. The covered and affected area of agrometeorological disasters for the IMAR and National both increased and then decreased during the 1981-2020 period. Drought was the most important agrometeorological disaster in the IMAR, and the covered and affected area was 64.10% and 62.45%, respectively, accounting the total covered and affected area of all kinds of disasters in 1981−2020. The grey correlation analysis showed that drought had the highest correlation with grain yield at the level of disaster covered and affected rate, and hail had the highest correlation with grain yield at the level of disaster destory rate. The disaster-yield assessment model constructed by this study was of high simulation accuracy, and the linear regression coefficients (R2) and the slop between the simulated and measured grain yield was 0.99 and 0.98, respectively (P < 0.01). The average relative simulation yield was 0.20% and relative simulation error of the following year grain yield was 2.49%. Grain yield loss rate due to disaster in the IMAR decreased (R2=0.77，P<0.01) from 1981 to 2020 with a rate of 0.48 percentage points·y−1, and average grain yield loss rate was 14.79% and there were 68.42% of years which grain yield loss rate above 10%. The disaster-yield assessment model of the IMAR formulated in this study can simulate and predict grain yield, and assess the loss of grain yield due to disasters, which can meet the needs of agrometeorological services. Related Articles | Metrics | Comments（0）

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Physiological Characteristics of Soybean Leaves at Different Growth Stages LIU Jiang, LI Ming-qian, CHANG Jun-fei, CHENG Xi-han, WANG Li-wei, LIU Qing, GAO Xi-ning Chinese Journal of Agrometeorology    2022, 43 (08): 622-632.   DOI: 10.3969/j.issn.1000-6362.2022.08.003 Abstract （290）      PDF（pc） （387KB）（211）       Knowledge map    Save The impacts of drought on agricultural production is a hot topic in agrometeorological research field. Soybean is an important economic crop. Clarifying its responses and adaptation characteristics to drought would be helpful to predict the soybean yields and improve agricultural production technology under global climate change. Therefore, authors conduct water control experiments in the scientific observing and experimental station of crop cultivation in northeast China. The soybean cultivar "Liaodou 15" was used and the drought and rewatering control experiments were conducted. At the flowering and full seed stage, the light drought (relative soil moisture 65%±5%), heavy drought (relative soil moisture 50%±5%), and control (relative soil moisture 80%±5%) treatments were set, respectively and the treatments lasted for 7, 14 and 21 days, respectively. After the droughts, the rewatering treatments were conducted to make the relative soil moisture recover to the control level. When the water stress reached the set levels, the indexes including contents of soluble protein, malondialdehyde (MDA) and the activities of superoxide dismutase (SOD) and peroxidase (POD) in the leaves were measured. These indices were also measured on the seventh day after rewatering to clarify the effects of drought and the compensation effects of rewatering. The results showed that the contents of soluble protein, malondialdehyde (MDA) and the activity of peroxidase (POD) increased significantly under light and heavy drought conditions at the flowering stage. The activity of superoxide dismutase (SOD) increased significantly under light drought condition. At the full seed stage, the soluble protein content, MDA content and SOD activity increased, but the POD activity decreased significantly. Rewatering showed compensation effects on soluble protein content, MDA content and SOD activity of soybean leaves, but did not show obvious compensation effect on POD. In conclusion, drought would probably induce peroxidation damage to soybean leaves, represented by the increase of antioxidant enzyme and osmotic regulation substance content. Rewatering can alleviate the peroxidation damage caused by drought, showing different degrees of compensation effect. Related Articles | Metrics | Comments（0）

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Assessment and Re-examination the Disaster-yield Model Based on Regional Grain Yield Loss for Five Provinces across North of China LIU Yuan, LIU Bu-chun, MEI Xu-rong, HE Jin-na, CHEN Di, HAN Rui, ZHU Yong-chang Chinese Journal of Agrometeorology    2023, 44 (11): 1009-1021.   DOI: 10.3969/j.issn.1000-6362.2023.11.003 Abstract （185）      PDF（pc） （1564KB）（211）       Knowledge map    Save Based on statistical data on grain acreage, yields and agricultural disasters from 1961 to 2020, the variability characteristics of grain yields and disasters in China and five northern provinces were compared and analyzed. Disaster yield assessment models for Hebei, Shandong and Henan provinces were used to estimate the loss of grain production due to disasters and grain yields by inputting data on disasters from 2008 to 2020. The sensitivity and stability of the disaster-yield assessment model were examined. Based on the statistical modeling method, the model of grain crop disaster-yield evaluation in Shanxi and Shaanxi was constructed, and the universality of the model construction method was evaluated. The results showed that: (1) the grain planting area and total output of the five northern provinces accounted for 28% and 25% of the national total from 1961 to 2020, respectively. In the five northern provinces, the planting area of summer harvest grain and autumn harvest grain decreased significantly at rates of 3.39ha·a−1 and 106.3ha·y−1(P<0.01) respectively, while the total output increased significantly at rates of 137.3×104t·y−1 and 119.9×104t·y−1(P<0.01), respectively. From 2008 to 2020, the grain planting area and grain yield in the five northern provinces increased significantly at the rates of 209.42ha·y−1 and 258.06×104t·y−1(P<0.01), respectively. (2) From 1961 to 2020, the areas of covered, affected and destroyed disaster in the five northern provinces accounted for 28%, 28% and 23% of the national average, respectively, while the disaster situations in the five northern provinces and the whole country showed a significant trend of first increasing and then decreasing. After reaching historically high values in 2008, 2000 and 2000, the covered disaster, affected disaster and destroyed disaster area had declined year on year. The corresponding disaster situations in the five northern provinces showed a downward turning point in 1990, 1989 and 2004, respectively. Drought and flooding are the main causes of crop disasters in China, with 76 percent of the total area affected by drought and flooding. The disaster in the five northern provinces was mainly caused by drought. The areas affected by drought accounted for 66%, 61% and 58% of the disaster statistics, respectively. From 2008 to 2020, the area affected by drought in Shandong was the largest. The area of drought disaster in Hebei and Shanxi was relatively high. Hebei province has the highest area of flooding and hail. (3) When the data series is extended to 2020, the simulated value of grain yield is significantly correlated with the actual value(R2=0.95, P < 0.01), the simulation accuracy of the model was high. In the past 60 years, the grain loss rates of Hebei, Shandong, Henan, Shanxi and Shaanxi provinces were 8.99%, 18.02%, 9.79%, 12.84% and 20.04%, respectively. In the last 12 years, the grain loss rates of Hebei, Henan, Shanxi and Shaanxi provinces had recorded by 4.4%, 17.4%, 9.65%, 8.14% and 17.9%, respectively, influenced by the reduction of disaster zones and advantage in agricultural science and technology. They all went down. With the verification and construction of the model, the modeling statistical method performs well in evaluating the loss of grain yield due to meteorological disasters, had a promising performance in predicting grain yield, and is feasible for commercial applications. As the five northern provinces account for a high proportion of the country's grain output, it is important to prevent the risk of regional hydrometeorological disasters to ensure the country's food security in the new period. Related Articles | Metrics | Comments（0）

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Analysis of Agroclimatic Characteristics of Wine Grape in Ili Region YANG Fan, LIU Yuan, LIU Bu-chun, YANG Xing-yuan, CUI Cheng, CHEN Yu-bao Chinese Journal of Agrometeorology    2023, 44 (04): 261-273.   DOI: 10.3969/j.issn.1000-6362.2023.04.001 Abstract （302）      PDF（pc） （2707KB）（210）       Knowledge map    Save Based on the daily climate and wine grape growth data of 10 meteorological stations in wine grape cultivable area of Ili Kazak Autonomous Prefecture, Xinjiang Uygur Autonomous Region, spatial distribution and variation of wine grape climate resources and agricultural meteorological disasters in the study area from 1961 to 2020 were analyzed. Those were calculated by M-K test, trend test and other statistical methods, combined with ArcGIS spatial expression. It can be provided a scientific basis for more efficient and reasonable use of local snow resources to alleviate drought and freezing injury and optimize wine grape overwintering methods. The results showed that: (1) the light and heat resources in Ili region were rich except Zhaosu and Nilke, while the spatial distribution of precipitation was uneven and less than 455mm. The precipitation in the whole area increased by 5.1mm·10y−1 from 1961 to 2020, which generally met the climatic requirements for the wine grapes growth and development. The snowfall during the wine grapes overwinter period in the whole region increased by 7.4mm·10y−1, while the probability of snow cover in 0−10cm was greater than 90%. (2) The frequency and intensity of frost damage decreased during the overwintering period in the whole region from 1961 to 2020, while drought was more serious in July and September in the potential growing season. Related Articles | Metrics | Comments（0）

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Drought Risk Assessment of Table Grapes in the Bohai Rim Region Based on Crop Water Deficit Index XIAO Nan-shu, LIU Bu-chun, YIN Hong, LIU Yuan, QIU Mei-juan, ZHANG Yue-ying, WANG Ke-yi Chinese Journal of Agrometeorology    2022, 43 (05): 380-392.   DOI: 10.3969/j.issn.1000-6362.2022.05.005 Abstract （163）      PDF（pc） （5594KB）（207）       Knowledge map    Save The influence of water on the growth and development of grapes cannot be ignored. In order to provide a theoretical reference for drought risk management and loss reduction and quality assurance of table grapes, the Bohai Rim region was taken as a study area. The crop water deficit index, which was calculated using daily meteorological data from 60 meteorological stations in the region from 1981 to 2014, was taken as an index to explore the drought of table grapes. By the crop water deficit index of the table grapes in each growth period in the region, the drought frequency and station ratio of the table grapes in each growth period were obtained. Then we evaluated the risk of drought based on the spatial and temporal distribution of table grapes in the region. The results showed that the matching degree was low in the time dimension between the water requirement of table grapes in the Bohai Rim region and precipitation, and table grapes in the region had a certain risk of drought in each growth stage. The new shoot growth period and fruit ripe period of table grapes were high-risk periods of drought in the region, when droughts were more frequently and more severely to occur. The central and southern part of Hebei province were high-risk area for drought, and where the risk of severe droughts is higher for table grapes. Table grapes in the Bohai Rim region had the most widely range of drought during the ripening period. Related Articles | Metrics | Comments（0）

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Spatial-Temporal Variation and Zoning Review of Soil Wind Erosion in the Three Provinces of Northeast China YANG Wan-rong, LIU Zhi-juan, SU Zheng-e, GAO Wei-da, REN Tu-sheng, YANG Xiao-guang Chinese Journal of Agrometeorology    2022, 43 (05): 327-339.   DOI: 10.3969/j.issn.1000-6362.2022.05.001 Abstract （204）      PDF（pc） （4491KB）（206）       Knowledge map    Save Based on the meteorological data from 1981 to 2017 in the three provinces of Northeast China, the temporal and spatial patterns of daily maximum wind speed at different levels during three study periods (the whole year, the fallow period of the year and one month before sowing date) were analyzed. Then using the starting wind speed index considering the influence of precipitation, the temporal and spatial patterns of the days of soil wind erosion during three study periods in different regions were analyzed. And suggestions on soil conservation tillage measures in different regions were put forward. It will provide scientific basis for the promotion of soil conservation tillage measures in various regions. The results showed that the regional annual average frequencies of wind scaled from calm to gentle breeze, from moderate breeze to strong breeze and moderate gale and above were 48.5%, 50.4% and 1.1%, respectively. During the past 37 years, the frequencies of wind scale from calm to gentle breeze during these three study periods showed increasing trends, while the frequencies of wind scale in moderate breeze and above showed the decreasing trends. The regional annual proportion of the days of wind erosion was 35.0%, but this value is higher during one month before sowing period (57.0%). In most areas, the days of wind erosion in each period showed decreasing trends. In Liaohe plain and Sanjiang plain, the frequencies of wind erosion during fallow period and one month before sowing were serious. Therefore, more attention should be paid to the impacts of wind erosion on soil. In Songnen plain, the frequency of soil wind erosion is lower during the fallow period, but serious during one month before sowing. Therefore, no-tillage technology is advocated in this area to reduce soil wind erosion. Related Articles | Metrics | Comments（0）