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20 August 2026, Volume 47 Issue 8

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Spatiotemporal Variation Characteristics and Attribution Analysis of Total Solar Radiation in Xizang from 1981 to 2024

DU Jun, HUANG Yan-li, XIAO Zhuo-jing, DECHENDOLKAR

2026, 47(8):  1171-1185.  doi:10.3969/j.issn.1000−6362.2026.08.001

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This study examined changes in solar radiation in the context of a warming and wetter climate regime in Xizang, with the aim of providing a reference for assessing the potential in the development and conservation of clean energy. Monthly sunshine duration and sunshine percentage, together with grain yield data were collected at 38 meteorological stations in Xizang from 1981 to 2024. Variations in annual and seasonal solar radiation (Q) and their spatiotemporal variation characteristics, as well as the influencing factors and their influence on grain yield, were analyzed in the same period based on the Ångstrom−Prescott empirical model and some statistical methods including linear tendency estimation, Pearson correlation coefficient, R/S analysis and Mann−Kendall test. The results showed that: (1) annual solar radiation exceeded 6300MJ·m⁻² at 81.5% of stations over Xizang from 1991 and 2020, meeting the highest abundance levels specified by meteorological industry standard in China, and making it highly suitable for solar energy development. The highest solar radiation were in summer, followed by that of in spring, with the lowest levels occurring in winter. (2) From 1981 to 2024, annual Q over Xizang decreased at a rate of −15.3MJ·m⁻²·10y⁻¹. Q decreased with 61%−66% of the stations during spring, summer and autumn, with the most notable annual reduction. Conversely, Q showed an increasing trend with 71% of the stations during winter. (3) Compared with the mean value of climate base period from 1991 to 2020, the average annual Q over Xizang was 4.5−114.8MJ·m⁻² higher from the 1980s to 2000s, especially in the 1980s. In the 2010s, it was 17.1MJ·m⁻² lower. (4) There was a high likelihood of continuous decline in Q during spring, summer and throughout the year in the future (2021−2050). However, the probability of a continuous decreased in Q during autumn and a continuous increase in Q during winter was lower. Abrupt changes in Q occurred during summer, winter and throughout the year in the mid to late 1990s. The turning points for Q during spring and autumn were around 2000 and 2012, respectively. (5) A significant negative correlation existed between Q and both total grain yield and yield per unit area during the crop growing season from 1981 to 2024. Specifically, Q in May had the most substantial impact on the grain yield, with a correlation that reached statistical significance at the 0.001 level. Consequently, a decrease in Q was beneficial, as it was associated with an increased grain yield. (6) The decrease in annual Q could be mainly attributed to the increase of the average low cloud cover over the past 44 years. Overall, the annual total solar radiation over Xizang showed a declining trend, and the likelihood of continuing this downward trajectory in the future was high in the 2010s. Nonetheless, the total solar radiation remains at the highest abundance levels, indicating significant potential for solar energy development. 

Influencing Factors and Future Projections of Carbon Emissions from Pig Farming in Liaoning Province

ZHAO Hong-liang, WANG Yuan, XIE Li-yong

2026, 47(8):  1186-1196.  doi:10.3969/j.issn.1000-6362.2026.08.002

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To clarify the characteristics of the carbon emissions from pig farming in Liaoning and their relationship to economic development, influencing factors and future trends, this study used data on pig farming in Liaoning from 2003 to 2022. The total carbon emissions and intensity of pig farming in Liaoning were calculated using the IPCC coefficient method. The Tapio decoupling model was used to analyze the state of decoupling between pig farming carbon emissions and output value. The Kaya identity and LMDI model were applied to examine the influencing factors of pig farming carbon emissions, and the STIRPAT model was used to forecast pig farming carbon emissions from 2023 to 2030. The results showed that: (1) carbon emissions primarily originated from manure management systems, with CH₄ emissions accounting for 28.40% and N₂O emissions accounting for 63.49%. The carbon emission intensity of pig farming in Liaoning province significantly decreased from 2003 to 2009, experienced minor fluctuations and remained relatively stable from 2008 to 2017, and showed notable volatility from 2018 to 2022, following an "upward-downward-upward" trend. (2) From 2003 to 2022, the decoupling state of pig farming carbon emissions in Liaoning province was predominantly characterized by weak decoupling and weak negative decoupling. Pork prices and the size of the farming scale were the main factors that increased carbon emissions from pig farming, while efficiency factors, industrial structure and agricultural population suppressed the increase. (3) Based on pork prices in Liaoning from 2003 to 2022, three scenarios were established, including annual growth rates of 2.0%, 5.3% and 8.0%, predicting that pig farming carbon emissions in Liaoning would follow an upward trend from 2023 to 2030 (P<0.01). Under the low−growth, baseline and high−growth scenarios, emissions would increase by 10.81%, 9.65% and 7.17%, respectively. To achieve a low−carbon transformation in the pig farming industry, it needs to implement policies such as supporting the introduction and breeding of high−quality pig breeds, optimizing manure treatment technologies, regulating farming scale, enhancing efficiency, improving carbon emission reduction policies and regulatory frameworks, and establishing a market supply−demand early warning mechanism for the pig farming sector.

Soil Water Storage Change and Driving Factors of Typical Stands in Loess Area of Ningxia

JIN Xue-ping, DONG Li-guo, ZHENG Ji-yong, LI Zhen-ming, HE Yu, WANG Pei-yao, LI Xin, XU Hao, CAI Jin-jun, WEI Yao-feng

2026, 47(8):  1197-1214.  doi:10.3969/j.issn.1000-6362.2026.08.003

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Based on field survey data of soil volumetric water content, topographic factors and soil physical and chemical properties from typical stands in the Loess hilly region of Ningxia, the 0-300cm soil profile was stratified into surface (0–20cm), shallow (20–80cm), middle (80–180cm) and deep (180–300cm) layers. Using correlation analysis, principal component analysis (PCA) and Random forest model, with natural grassland as the control, the differences and underlying mechanisms of soil water storage across 10 typical stands during the leaf-fall period of 2024 in the Yangwa (Zhongzhuang) watershed, Pengyang county, Guyuan city were analyzed. The stands included pure plantations of Robinia pseudoacacia L., Picea asperata Mast., Prunus sibirica L., Prunus davidiana (Carrière) Franch., Hippophae rhamnoides L. subsp. sinensis Rousi, and Caragana korshinskii Kom., as well as mixed stands of Robinia pseudoacacia×Picea asperata, Prunus sibirica×Hippophae rhamnoides subsp. sinensis, Prunus sibirica×Caragana korshinskii and Prunus davidiana×Caragana korshinskii. The relative importance of environmental factors, including slope, aspect, slope position, elevation, clay content, silt content, sand content, soil organic carbon, soil bulk density, tree height, diameter at breast height and biomass, was quantified on soil water storage and identified the core driving factors, so as to provide a reference for the sustainable utilization of regional soil water resources. The results showed that: (1) in 2024, the average soil volumetric water content in the 0–300cm soil layer was significantly higher in P. asperata pure forest (17.47%) and P. davidiana pure forest (17.40%) than in natural grassland (15.95%). P. davidiana pure forest had the highest soil water storage in the surface (31.59mm), shallow (122.27mm), and middle layers (177.65mm), while natural grassland showed the highest deep-layer soil water storage (227.21mm). Soil water storage across 0–300cm was highest in P. asperata pure forest, reaching 524.22mm. (2) Soil bulk density was the core driving factor of soil water storage. It was significantly positively correlated with water storage in the middle, deep and whole soil layer (r =0.567, 0.471 and 0.527, respectively; all P<0.01). In the Random forest model, the importance values were 26.238%, 9.426% and 23.715% for the middle, deep and total soil layers, respectively. The slope was the key factor affecting surface soil water storage, with an importance of 6.959%. Elevation and vegetation factors were key regulators of shallow soil water storage: elevation was significantly positively correlated with shallow soil water storage (r=0.345, P<0.05), and the importance values of diameter at breast height, tree height and biomass were 13.350%, 9.190% and 9.102%, respectively. (3) The first principal component, PC1 (25.0%), represented the synergistic effects of soil texture and soil organic carbon, while the second principal component, PC2 (21.1%), highlighted the influence of vegetation factors. In conclusion, under the current afforestation pattern in Pengyang county, P. asperata and P. davidiana pure forests exhibited stronger soil water storage capacity. Soil water storage across different depths is affected by distinct environmental factors. To enhance regional soil water conservation, particularly deep-layer water storage, priority should be given to maintaining or improving soil bulk density.

Responses of Soil Organic Carbon to Nitrogen Addition and Altered Precipitation in an Alpine Meadow on the Qinghai−Tibet Plateau

GAO Yan-feng, SONG Cheng-gang, WANG Wen, ZHANG Fa-wei, DU Wei, ZHU Jing-bin

2026, 47(8):  1215-1223.  doi:10.3969/j.issn.1000-6362.2026.08.004

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Enhancing soil organic carbon (SOC) sequestration capacity is a crucial nature−based solution for mitigating climate change. To elucidate the mechanisms underlying depth−resolved SOC responses to elevated atmospheric nitrogen (N) deposition and altered precipitation regimes, this study utilized a full−factorial experiment combining N addition (10g·m^–2·y^–1) and precipitation manipulation(±50% ambient precipitation) initiated in 2017 in a northeastern Qinghai−Tibet plateau alpine meadow. The dynamics of 0–40cm SOC, soil nutrients and plant biomass from 2022 to 2024 were quantified to reveal SOC responses to changes in nitrogen deposition and precipitation regimes. The results showed that aboveground biomass (AGB) increased significantly by approximately 30% under the N addition treatment compared to the control (CK, no N addition or precipitation change). Belowground biomass (BGB) showed depth−dependent variations and was more sensitive to precipitation change, where 30–40cm BGB was reduced by 35% under the decreased precipitation treatment. N addition decreased surface soil (0–10cm) pH by 7% but increased SOC and soil total nitrogen (STN) by 7%–9% in the same layer. Conversely, subsoil (30–40cm) SOC and STN declined by 2%–4%. N addition and precipitation change indirectly regulated 10–40cm STN and SOC through the soil pH pathway, rather than via changes in vegetation biomass. Specifically, precipitation change showed positive effects on 10–40cm SOC with a β of 0.08. These findings demonstrate a response of SOC with a "surface accumulation and subsurface depletion" pattern, which alters the vertical distribution of SOC and indicates a decoupling from plant−derived carbon inputs. This study provides valuable insights for assessing and projecting the soil carbon sink function of alpine meadows under future climate change scenarios. 

Eco−economic Synergistic Development Strategies of the Tea Industry in the Qinling−Daba Mountains

HAN Jin, WANG Yi-long, HAO Jia-lin

2026, 47(8):  1224-1238.  doi:10.3969/j.issn.1000-6362.2026.08.005

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As a key ecological function zone and a distinctive tea−producing area in China, the Qinling−Daba mountains face the dual challenges of ecological protection and economic development. Based on the conditions of ecological resource advantages and economic development performance of the tea industry in the Qinling−Daba mountains, this study analyzed the practical constraints that restrict the regional tea industry from achieving ecological and economic coordination. Guided by the theory of agricultural ecological−economic coordination, corresponding strategies and coordinated development pathways for the tea industry in Qinling−Daba mountains were proposed. The results showed that the tea industry in the Qinling−Daba mountains was confronted with practical problems such as insufficient innovation and application of ecological technologies, incomplete industrial chains, insufficient brand influence and imperfect policy support. The theoretical framework for ecological−economic coordination was constructed, which featured the logic of "ecological technology driven−industrial chain value enhancement−ecological benefit feedback". The strategies for the deep integration of full industrial chain value increment with ecological resources, coordinated benefit sharing and organizational innovation and environment−supported ecological branding needed to be established. Coordinated development pathways were put forward, including ecological technology support, digital empowerment for management and utilization of carbon sinks as well as waste resources. This study advocated advancing the deep processing of tea products, promoting the integrated development of regional public brands, enterprise brands and product brands, and improving sales channels and benefit linkage mechanisms. A tripartite integrated development system for the tea industry in the Qinling-Daba mountains should be established. The path of ecological value feeding back into economic value was expanded by establishing a "quantification− transaction−premium" closed loop, constructing a "compensation−ownership−mitigation" policy toolkit, and forming a "responsibility−allocation−supervision" multi−stakeholder co−governance mechanism. A policy and institutional system characterized by diversified investment, cross−regional collaboration, financial adaptation, technological support and talent cultivation was established. This study demonstrates that the coordination of technology, industry, policy and social elements within the "ecological−economic" system of the tea industry in the Qinling−Daba mountains can provide a reference strategic paradigm for the coordinated development of agricultural ecological economies, and lay a foundation for the high−quality development of the tea industry in the Qinling−Daba mountains.

Assessment of Wind Energy Resources and Evaluation of Localized Utilization of Rural Wind Power in Guangdong

ZOU Jia-nan, CAO Qi-min

2026, 47(8):  1239-1246.  doi:10.3969/j.issn.1000-6362.2026.08.006

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 To facilitate the assessment of the ecological value of wind energy and promote the local and proximate development of wind power in rural areas, this study analyzed the fundamental characteristics and development potential of wind resources in eastern, western and northern Guangdong. The analysis utilized wind resource assessment methodologies based on the latest ECMWF reanalysis V5 (ERA5) average wind speed data from the European Center for Medium−Range Weather Forecasts. The objective was to provide a reference for accelerating the green and low−carbon transition of rural energy systems. The results showed that from 2020 to 2024, the average surface wind speed at 100m height in these regions was 4.0m·s⁻¹, with a corresponding mean wind power density of 74.5W·m⁻². Based on the trading price of green electricity, the annual economic value of wind energy ecological products for a 2.0×10⁷W installed capacity per village was approximately 46.56 million yuan, 55.34 million yuan and 37.20 million yuan in eastern, western and northern Guangdong, respectively. If 20.0×10⁴ yuan was allocated annually to village collectives, this would increase the per−village disposable income by 0.6%, 0.4% and 0.8% in the respective regions. Under the construction targets of the "Nationwide Rural Wind Power Initiative" which aimed to develop six rural onshore wind projects per city, the annual electricity generation from these pilot villages could account for 9.4% of the total rural residential electricity consumption in the three regions, despite these villages representing merely 0.5% of the total villages locally. In conclusion, it is recommended that rural onshore wind power projects adopt land−saving technologies for wind turbine towers. Simultaneously, the efforts should be intensified to construct supporting projects such as ultra−fast charging stations and zero−carbon industrial parks in China's rural areas, thus broadening the pathway for new energy absorption. Pilot initiatives for rural onshore wind power in Guangdong should be prioritized in eastern and western Guangdong, so as to demonstrate good practice.

Effect of Annual Precipitation Pattern on Soil Moisture and Maize Yield under Different Winter Fallow Practices

WANG Tian-shu, FENG Wei, LI Ting-yu, MENG Yi-li, JI Jin-meng, WU Yong, YAO Shui-hong

2026, 47(8):  1247-1261.  doi:10.3969/j.issn.1000-6362.2026.08.007

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To address the water−grain nexus in the groundwater funnel area of the north China plain, this study systematically analyzed the dynamics of soil water and the maize yield response by considering both precipitation (normal and dry years) and winter fallow practices (fallow, oilseed rape and hairy vetch) based on field experiments conducted during the maize growing seasons from 2022 to 2024 in the north China plain. The results showed that: (1) annual precipitation pattern and the distribution of rainfall during the maize season significantly affected the soil water storage of winter fallow practices. In the normal year with evenly distributed maize season rainfall (2022), soil water storage increased significantly, thereby reducing the risk of groundwater funnel development. In contrast, with precipitation occurring mainly in the later part of the maize season (2024), soil water storage at the maturity stage was needed to compensate for deficits earlier in the season. Winter fallow practices, especially fallow and oilseed rape, increased soil water storage. However, in the dry year (2023) with low and concentrated precipitation, winter fallow practices did not improve soil water storage, and the winter wheat treatment exhibited extra water consumption, further increasing potential risks to groundwater. (2) Annual precipitation pattern and fallow practices jointly affected maize growth traits and yield enhancement. In normal years (2022 and 2024), winter fallow practices reduced water consumption during the maize growing season and promoted kernel number development, resulting in yield increases of 0.81%−14.48%. In the dry year (2023), drought accelerated grain filling, leading to shorter but thicker ears and limited kernel number; only rapeseed treatment alleviated water stress through residue mulching and optimized water use, thereby stabilizing maize yield. This study suggests that fallow strategies in the north China plain should be dynamically adjusted in accordance with annual precipitation conditions, and attention should be paid to the cumulative effects of long−term fallow on soil water cycling to enhance the sustainable utilization of agricultural water resources.

Influence of Different Fertilization Measures on the Organic Carbon Components of Paddy Field Soil

ZHANG Jing-yu, LI Ying-chun, MA Fen, CAO Guo-jun, CHEN Guo-hui, CHEN Yan-Fang, PENG Chun-feng, QIN Kang-xi

2026, 47(8):  1262-1271.  doi:10.3969/j.issn.1000-6362.2026.08.008

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A rice field experiment was conducted in Jiujiang city, Jiangxi province, from 2023 to 2024, with the following eight treatments of no nitrogen fertilizer (N0), conventional nitrogen application (N100), 20% nitrogen reduction (N80), 20% nitrogen reduction with different amounts of microalgae biofertilizer (M1N80, M2N80 and M3N80), 20% nitrogen reduction with biochar (BN80) and 40% nitrogen reduction with microalgae biofertilizer (M4N60). This study aimed to assess the impacts of nitrogen reduction combined with microalgae biofertilizer and biochar treatments on soil organic carbon (SOC) and its components in paddy fields to provide a scientific basis for enhancing SOC content and improving soil carbon sequestration potential. The results showed that the mineral−associated organic carbon (MOC) accounted for 60.3%−76.5% of the total soil organic carbon. Compared with the N100 treatment, both M3N80 and BN80 treatments significantly increased MOC content by 45.3%−46.8% (P<0.05), which in turn contributed to a 27.6%−34.3% increase in total SOC content. The 20% nitrogen reduction with microalgae fertilizer and biochar significantly increased soil dissolved organic carbon (DOC) by 9.8%−260.0% and microbial biomass carbon (MBC) by 10.7%−120.0% during key rice growth stages. The results demonstrate that biochar and high−dose microalgae biofertilizer (M3N80) application exhibit optimal performance in enhancing SOC content in paddy fields, confirming that exogenous organic inputs can improve SOC stability, thereby providing a novel component−regulated fertilization strategy to enhance carbon sequestration capacity in rice ecosystems. 

Impacts and Projections of Extreme Agricultural Events on Food Crops Carbon Absorption in Shanghai

BU Lu-lei, ZHOU Yu, YANG Wang-hua, XIN Tiao-er

2026, 47(8):  1272-1283.  doi:10.3969/j.issn.1000-6362.2026.08.009

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Based on meteorological data from 11 stations in Shanghai and food crop carbon absorption data from 2000 to 2020, this study integrated the accumulated hot damage temperature index (AHDT), precipitation intensity index (SDII), continuous rain comprehensive index (Z) and cumulative sunshine to investigate the relationship between agricultural extreme disasters and food crop carbon absorption. Utilizing composite analysis, this study analyzed and quantified the intensity differences of extreme disasters between years with high and low food crops carbon absorption and projected the future impact of agrometeorological disasters on food crops carbon absorption in Shanghai. The results showed that the regional average carbon absorption of food crops in Shanghai was 80.82gC·m⁻² during the 2000−2020 period. Food crops carbon absorption decreased by 10.20gC·m⁻² for every 10.7℃·d increase in AHDT, 2.7mm·d⁻¹ increase in SDII, 0.09 increase in Z index, or 27.1h decrease in cumulative sunshine. Compared to the 2000−2020 baseline, projections under the SSP5−8.5 scenario using the HadGEM3− GC31−LL model for 2031−2050 suggested that fluctuations in AHDT could lead to a reduction in food crops carbon absorption ranging from −5.36 to 139.30gC·m⁻². Fluctuations in SDII were projected to increase food crops carbon absorption by 28.03 to 41.16gC·m⁻², while Z fluctuations might cause food crops carbon absorption to vary between a maximum decrease of 38.97gC·m⁻² and a maximum increase of 66.91gC·m⁻². Furthermore, the impact of future solar radiation changes on food crops carbon absorption exhibited a trend of initial decline followed by an increase. These findings provide a scientific foundation for optimizing disaster management and formulating adaptive policies in Shanghai, offering significant insights for ensuring food security and supporting the realization of "Dual Carbon" goals.

Spatiotemporal Distribution Characteristics of Autumn Frost Damage for Liaoning Peanut from 1961 to 2020

WANG He-ran, HAN Xue, WU Dong-li, LI Ying-chun, CHEN Peng-shi, LIU Cong, WANG An-ting

2026, 47(8):  1284-1298.  doi:10.3969/j.issn.1000-6362.2026.08.010

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Based on the daily minimum temperature data in the 56 national meteorological stations of Liaoning from 1961 to 2020, frost days and the first frost date were identified using a threshold of ≤0.5℃, then the number of autumn frost days during the peanut growing season and the number of frost days during the maturation stage were calculated. This study analyzed the spatiotemporal characteristics of the first frost date and the number of autumn frost days during the peanut growing season, screened the high−frequency periods and susceptible stations of frost during the peanut maturation period, providing references for frost forecasting and prevention in peanut‒producing areas at middle and high latitudes. The results showed that from 1961 to 2020, the first frost date in 56 stations of Liaoning was from September 8 to November 27, and the first frost date with an 80% guarantee rate was concentrated from late September to mid−October in 92.9% of stations. The first frost dates occurred sequentially in the northeast producing region, the eastern mountainous region, the western producing region, the middle producing area and the southern producing region. Provincial first frost date showed a delayed trend from 1961 to 2020 (1.25d·10y⁻¹, P<0.05), whereas a non−significant advancing change during 2011 to 2020 (−2.24d·10y⁻¹, P=0.53). From 1961 to 2020, the number of autumn frost days during the peanut growing season in 56 stations ranged from 0 to 6d·y⁻¹. In 67.9% of the stations, the number of autumn frost days during the peanut growing season showed a decreasing change (−0.84 to −0.01d·10y⁻¹), with 35.7% of the stations passing the significance test. No autumnal frost events were recorded during the peanut growing season at the stations along the southern coast. However, some stations in the western producing region, northeastern producing region, middle producing region and eastern mountainous region experienced frost during the peanut ripening period in early to mid−September. With the exception of the southern production area, other peanut−producing areas and mountainous areas in eastern Liaoning should prioritize frost prevention during the harvest drying phase from late September to October. In addition, some stations in the aforementioned areas needed to take precautions against frost during the maturation stage in early to mid−September. Although the limiting effect of autumn thermal conditions represented by frost on the late growth stage of peanuts in Liaoning had been alleviating, attention should be paid to the risks of autumn frost during the growing season and frost during the maturation period due to the unstable advancement of the first frost date in recent years when conducting peanut cultivation or expanding planting areas. For the meteorological departments, a 7d dynamic forecast of peanut autumn frost could be initiated in early September to provide reference for planters to harvest at a appropriate time.

Construction of Annual Yield Harvest Status Assessment Models of Natural Pasture Grass in Hulun Buir Grassland

WU Nier, TERI Gele, QU Xue-bin, YING Chun, XIE Xiao-li, BAO Yong-bin

2026, 47(8):  1299-1311.  doi:10.3969/j.issn.1000-6362.2026.08.011

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To scientifically assess the impact of meteorological conditions on the growth, development and yield formation of natural forage grasses in the Hulun Buir grassland, this study used daily meteorological data from six meteorological stations and ten−days of natural forage observations data in the Hulun Buir grassland from 1991 to 2024. Methods such as correlation analysis, cluster analysis and principal component analysis were employed to classify the suitability grades of meteorological conditions during each growth period of natural forage grasses, determined their significance in the yield formation process, and thereby constructed annual yield harvest status assessment models for natural forage grasses in typical steppes and meadow steppes. The results showed that: (1) the yield of natural forage grasses during the regreening, jointing−heading, flowering and grain ripening periods were positive correlation with precipitation and the number of days with daily precipitation ≥5mm, while negative correlation with effective accumulated temperature ≥10℃, sunshine duration and daily temperature range in the Hulun Buir grassland. (2) The weights of the meteorological condition suitability grades for the four growth stages on yield formation differed between typical steppe and meadow steppe. For meadow steppe, the order was flowering period (0.49) > jointing−heading period (0.24) > regreening period (0.15) > grain ripening period (0.13). For typical steppe, the order was flowering period (0.39) > jointing−heading period (0.26) > regreening period (0.19) > grain ripening period (0.17). (3) The fitting test using historical samples from 2021 to 2024 for the annual forage yield harvest status assessment model showed that the coefficients of determination (R²) for the meadow steppe and typical steppe assessment models were 0.77 and 0.76, respectively. Root mean square error (RMSE) values were 0.45 and 0.76, respectively. Validation against 24 historical samples showed that the model's predictions were consistent with the observed data in 22 cases, achieving an accuracy of 91.7%. 

Simulation Model of Meteorological Yield of Xinghua Crab Based on Meteorological Factors

WU Fang, GONG Jia, ZHANG Zi-qiang, XIANG Yang, YUAN Chang-hong

2026, 47(8):  1312-1320.  doi:10.3969/j.issn.1000-6362.2026.08.012

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In this study, crab yield and meteorological data from Xinghua were collected for the period 2010−2020, and the corresponding meteorological yield was separated using double exponential smoothing, linear regression, and the Hodrick−Prescott (HP) filter. The key meteorological factors affecting meteorological yield were identified by fitting the relationships between meteorological yield and meteorological factors at three growth stages (the first to third molting stages, the fourth molting stage and the fifth molting stage). Finally, a meteorological yield model based on key meteorological factors was constructed using the multiple linear regression method, and validated with yield data from 2021 to 2023. The results showed that: (1) the HP filter method demonstrated the optimal performance both in extracting the trend yield of Xinghua crab and in stably reflecting its meteorological yield. (2) The key meteorological factors affecting the meteorological yield of Xinghua crab included the number of high−temperature days and precipitation days during the first to third molting stages, the vapor pressure during the fourth molting stage, and the relative humidity, diurnal temperature range and minimum air pressure during the fifth molting stage. (3) The model based on the HP filter method (KMF−H) demonstrated the best simulation performance, with a coefficient of determination (R²) of 0.91, a root mean square error (RMSE) of 50.01kg·ha⁻¹, and the highest validation accuracy (D) of 97.14%. Overall, the model constructed using the HP filter method is suitable for simulating the yield of Xinghua crab.

Spatiotemporal Characteristics of Cold Events and Their Impacts on Agriculture in Zhejiang Province from 1971 to 2022

XIAO Jing-jing, MA Hao, GUO Fen-fen, LI Zheng-quan, ZHANG Yu-hui, WANG Zhi-hai, LIU Zan, MA Shang-qian

2026, 47(8):  1321-1335.  doi:10.3969/j.issn.1000-6362.2026.08.013

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Based on daily minimum temperature of 66 meteorological stations in Zhejiang province from 1971 to 2022 and projected results stem the BCC−CSM2−MR model, a series of cold events for Zhejiang was constructed using the absolute threshold values and standard deviations. Furthermore, spatiotemporal variability of cold events was investigated by diagnostic and statistical methods, and agricultural freezing risk under the SSP245 and SSP585 scenarios during 2023−2100 was quantitatively assessed in order to effectively support regional climate adaptation and disaster risk management. It was found that during 1971−2022, the annual mean number of cold days, frequency of cold events, and frequency of extreme cold events in Zhejiang all exhibited significant decreasing trends (P<0.01), with decreasing rates of 6.1d·10y⁻¹, 0.6times·10y⁻¹ and 0.2times·10y⁻¹, respectively. There displayed distinct spatial differences for cold days, cold events, and extreme cold events, with showing patterns of "more in the north and less in the south, more in the west and less in the east" "more in the northeast and less in the southwest" and "more in the central−north and less in the southwest", respectively. As for the long-term trends, climatic tendency rates of cold events' frequency in spring and autumn were −0.4times·10y⁻¹ and −0.3times·10y⁻¹ (P<0.01) respectively, while no significant trend was observed in winter. Empirical orthogonal function (EOF) analysis of extreme cold events indicated that the first mode was a province-wide consistent pattern with a variance contribution of 79.7%, and the second, third and fourth modes exhibited the northwest−southeast dipole patterns, near−tripl and north−south dipole, respectively. In the projection results of the BCC−CSM2−MR model, under the SSP245 and SSP585 scenario, the annual average frequency of extreme cold events in Zhejiang during 2023−2100 would be 0.9times and 1.0times with climatic tendency rates of −0.1times·10y⁻¹ and −0.2times·10y⁻¹ (P<0.01), respectively. During the same period, spatial distribution of the cumulative frequency of extreme cold events under SSP245 and SSP585 scenario indicated that a south-north gradient (higher in the south and lower in the north) and an inland−coastal gradient (higher inland and lower along the coast), and the high−values would be located in southwestern Zhejiang. Under the SSP245 scenario, cold events could result in an agricultural freezing−affected rate ≥5% in 19y and a freezing-suffering rate >5% in 2y over Zhejiang in the future 78 years. Especially, the agricultural freezing−affected rate would reach 18.1% and 25.9%, and the freezing−suffering rate would be 6.7% and 11.0% in 2030 and 2066, respectively. Under the scenario of SSP585, there might be 17y with an agricultural freezing−affected >5% and 3y with a freezing−suffering rate >5%. In particular, the agricultural freezing−affected rate would be 24.9% and the freezing−suffering rate would be 11.9% in 2079.

Impact of Extreme Temperatures on Farmers' Participation in Agricultural Insurance

LIU Ran, REN Guang-jiao, YU Chao-yi

2026, 47(8):  1336-1355.  doi:10.3969/j.issn.1000-6362.2026.08.014

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The frequent occurrence of extreme weather events has resulted in increased risks to agricultural production. Exploring the response effects of agricultural insurance from the perspective of risk diversification is of great practical importance for promoting sustainable agricultural development. This study selected panel data on agricultural activities from 2001 to 2022 in 220 sample cities in 4 municipalities directly under the central government, 22 provinces and 5 autonomous regions in China. Based on the indicators of extreme low temperature and extreme high temperature, a two-way fixed effects model and mediation mechanism test were used to analyze the impact of extreme high temperature and extreme low temperature events on farmers' willingness to participate in agricultural insurance in 220 sample cities in China from 2001 to 2022. The aim was to provide empirical evidence for expanding the decision−making theory of farmer insurance participation in extreme climate scenarios, for optimizing the design of agricultural insurance climate indicators, for improving differentiated subsidy policies, and for constructing a climate-adaptive agricultural risk protection systems. The results showed that: (1) the regression coefficient of extreme high temperatures on agricultural insurance participation in 220 sample cities in China from 2001 to 2022 was 0.24, but did not reach a significant level. Extreme low temperatures had a promoting effect on farmers' participation in agricultural insurance, with a regression coefficient of 0.63 (P<0.01). For every 1 percentage point in the frequency of extreme low temperature events that year, farmers' participation in agricultural insurance increased by 0.63 percentage point. (2) Extreme low temperatures promoted farmers' willingness to participate in agricultural insurance by affecting agricultural planting losses and increasing their expectations for insurance compensation. Extreme low temperatures had a significant negative impact on total crop yield (P<0.05), a highly significant positive impact on rural residents' disposable income (P<0.01), and a significant positive impact on agricultural insurance compensation expectations (P<0.05). Extreme high temperatures had not yet formed a significant impact pathway on farmers' willingness to participate in agricultural insurance. (3) The impact of extreme temperature events on agricultural insurance participation in inland cities was significantly higher than that in coastal cities. Among them, the significant positive effects of extreme low temperature (P<0.01) and extreme high temperature (P<0.05) on farmers' agricultural insurance participation in inland cities were more prominent than those in coastal cities. (4) From the perspective of grain functional areas, extreme low temperatures had a significant impact on the agricultural insurance demand in the main grain production areas (P<0.01) and main sales areas (P<0.05), but had no significant impact on the production and sales balance areas. Extreme high temperatures had a significant positive impact on the agricultural insurance demand in the production and sales balance areas (P<0.01), but had no significant impact on the main production areas and main sales areas. Overall, this study reveals the mechanism and heterogeneity of impact of extreme temperatures on agricultural insurance participation, providing a reference for improving differentiated agricultural insurance policy design, strengthening climate risk response capabilities, and ensuring national food security. 

Report on Meteorological Condition Impact on Agricultural Production in the Winter of 2025/2026

LI Yi-jun, LIU Wei, LI Xuan, ZHAO Xiu-lan, QIAN Yong-lan, WU Men-xin

2026, 47(8):  1356-1358.  doi:10.3969/j.issn.1000-6362.2026.08.015

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 In the winter of 2025/2026, the national average temperature was −2.1℃, which was the second highest temperature on the same period since 1961. There were 13 cold air events with notable temperature fluctuations of warmer−than−normal conditions. The average winter precipitation was 29.4mm, 25.2% less than the average for the same period from 1991 to 2020. The national average sunshine hours was close to the perennial value, and significantly more sunshine hours had been observed in the Sichuan basin compared to the same period in history. Much of the northern winter wheat region had abundant light and heat conditions, with most of the moisture for safe wintering and greening of the wheat within a wide range of rain and snow weather. Most areas of southern China had warm and sunshine hours for the growth and development of rape, wheat, winter crops and economic forest fruits. However, the phase of drought in southern Sichuan and northern Yunnan and the phase of low temperature in Jianghuai and Jianghan were not good for the steady growth of summer crops.