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    20 July 2025, Volume 46 Issue 7
    Changes and Influence Factors of Carbon Footprint of Rice Agricultural Land Use in Panjin from 2014 to 2022
    SHEN Qi, LI Wei-ran, YU Xiao-peng, LI Hao, WANG Zi, JI Wei-wei, YU Ya-hui
    2025, 46(7):  907-917.  doi:10.3969/j.issn.1000-6362.2025.07.001
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    To calculate the carbon footprint of rice production could help promote coordinated efforts to increase agricultural yield and efficiency, as well as green and low−carbon development. Based on the data of yield, sowing area and agriculture production input of rice in Panjin region (Shuangtaizi district, Xinglongtai district, Dawa district and Panshan county) from 2014 to 2022, carbon footprint of rice agricultural land use and influencing factors were estimated. These results could provide a reference base for achieving energy conservation and emission reduction in rice production and green low−carbon development. The results showed that the carbon sequestration per unit sown area of rice in Panshan from 2014 to 2022 showed a decreasing trend and then an increasing trend (P<0.01), with a large fluctuation from year to year. There was little change in carbon sequestration per unit sown area in Shuangtaizi district, Xinglongtai district, and Dawa district, and the differences were no significant at different regions. During the study, there were no significant in carbon emissions per unit sown area of rice, carbon footprint between Shuangtaizi district, Xinglongtai district, Dawa district and Panshan county from 2014 to 2022, but the differences were significant (P<0.01) at different regions. The average carbon footprint of rice agricultural land use showed that Dawa district (0.50×104ha) and Panshan county (0.53×104ha) were significantly higher than Shuangtaizi district (0.03×104ha) and Xinglongtai district (0.04×104ha). In the carbon footprint structure of rice agricultural land use, nitrogen fertilizers, agricultural machinery and pesticides accounted for 23.20%, 12.05% and 20.82% of the average carbon footprint. With the promotion of low−carbon rice production, various approaches such as reducing nitrogen fertilizer and pesticide fertilizer input and increasing utilization efficiency, mechanized operation efficiency, and policy leverage have combined to reduce carbon emissions from the rice production in Panjin. 

    Future Changes of Precipitation and Temperature over Tailan River Basin Based on CMIP6 GCMs
    CELIGEER, DONG Wen-ming, HAO Zhe, XU Jing-dong, PENG Liang
    2025, 46(7):  918-931.  doi:10.3969/j.issn.1000-6362.2025.07.002
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    Mountainous alpine areas are important water−producing areas in inland river basins that are highly sensitive to climate change. This study explored the projected changes in precipitation, maximum temperature (Tmax) and minimum temperature (Tmin) in the Tailan river basin (TRB) based on 14 Global Climate Models (GCMs) from the coupled model intercomparison project phase 6 (CMIP6) and the multi−model ensemble (MME) of the bias−corrected dataset by Delta method during 2081−2100, with reference to the baseline period 1995−2014, under three integrated scenarios (SSP1−2.6, SSP2−4.5, and SSP5−8.5) of Shared Socioeconomic Pathways (SSPs) in order to understand precipitation and temperature changes over TRB and provide references for local strategies against climate change. The results showed that: (1) the biases between CMIP6 GCMs and observation value could be effectively corrected by DCM. Meanwhile, it was found that the MME was better than all other individual models for each climatic variable. (2) Precipitation,Tmax,Tmin over the TRB from 2025 to 2100 was projected to increase under SSP1−2.6, SSP2−4.5 and SSP5−8.5. Precipitation was projected to increase at the rate of 6.51mm·10y−1, 8.81mm·10y1 and 9.01mm·10y1 under SSP1−2.6, SSP2−4.5, and SSP5−8.5, respectively. Tmax was projected to increase at the rate of 0.09℃·10y1, 0.16℃·10y1 and 0.42℃·10y1 under SSP1−2.6, SSP2−4.5 and SSP5−8.5, respectively. Tmin was projected to increase at the rate of 0.09℃·10y1, 0.17℃·10y1 and 0.43℃·10y1 under SSP1−2.6, SSP2−4.5 and SSP5−8.5, respectively. (3) During 20812100both precipitation and temperature over TRB increased under three integrated scenarios (SSP12.6, SSP24.5 and SSP58.5). The annual precipitation was projected to increase by 7.84−11.45pp, 18.45−21.35pp and 20.20−24.02pp under SSP1−2.6, SSP2−4.5 and SSP5−8.5, respectively. The annual mean Tmax over the TRB was projected to increase by 2.03−2.07℃, 2.95−3.02℃ and 5.07−5.12℃ under SSP1−2.6, SSP2−4.5 and SSP5−8.5. The annual mean Tmin over the TRB was projected to increase by 1.85−1.92℃, 2.99−3.04℃ and 6.09−6.13℃ under SSP1−2.6, SSP2−4.5 and SSP5−8.5.

    Variation Characteristics of Net Ecosystem Carbon Exchange of Farmland in Eastern Qinghai-Tibet Plateau
    LIU Cheng-qi, TALINGEWA, LI Yue-mei, WANG Hong-xia, WANG Qian-bing, SONG Ming-dan
    2025, 46(7):  932-941.  doi:10.3969/j.issn.1000-6362.2025.07.003
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    Based on the National Agricultural Environment Observation and Experiment Station of Xining ( Xining Station), the instantaneous CO2 flux of farmland ecosystem in Qinghai Province was obtained by using eddy covariance technique. The data were processed by Eddypro, Tovi and other software to explore the variation characteristics and influencing factors of instantaneous carbon flux at different scales of farmland ecosystem. The results showed that the daily average values of instantaneous net ecosystem carbon flux NEE during crop growth period (April 1 to August 10) in Xining station of Qinghai-Tibet Plateau in 2022 and 2023 were 2.78µmol·m2·s1 and 3.12µmol·m2·s1, respectively. The cumulative net ecosystem carbon flux during the growth period was 1396.07g·m−2 and 1564.79g·m−2, respectively. The carbon sink in 2022 increased by 150.73g·m−2 compared with that in 2023. The air temperature (TA), wind speed (WS), photosynthetically active radiation (PPFD) and net ecosystem carbon flux (NEE) were significantly correlated during the crop growth period in Xining station of Qinghai-Tibet Plateau from 2022 to 2023, and the correlation coefficients were all above 0.4. The order of correlation coefficients was air temperature (TA)>photosynthetically active radiation (PPFD)>wind speed (WS). Among them, photosynthetically active radiation ( PPFD ) had a promoting effect on carbon absorption; with the increase of temperature ( TA ), the absorption was promoted first and then inhibited. Wind speed (WS) haan inhibitory effect on carbon absorption. In summary, the net ecosystem of farmland in the wheatrape rotation system in Qinghai Province from 2022 to 2023 was a carbon sink. Photosynthetically active radiation, air temperature and wind speed are the main influencing factors of the net ecosystem carbon flux of farmland in the wheatrape rotation system in Qinghai province.

    Evolution Characteristics of Hydrological and Meteorological Elements and Their Influence on Runoff in Danghe River Basin
    WANG Yi-ru, SUN Dong-yuan, WANG Xing-fan, CUI Yan-qiang, SHU He-ping, MA Ya-li, WU Lan-zhen
    2025, 46(7):  942-953.  doi:10.3969/j.issn.1000-6362.2025.07.004
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    Based on meteorological and hydrological data from the Danghe river basin spanning 1966 to 2022, the β−Z−H three-parameter comprehensive indicator method, M−K test, Budyko hydrothermal coupling balance equation and Pearson correlation analysis were employed to analyze the evolution characteristics of hydrological and meteorological elements in the basin, quantify the contribution of climate change and human activities to changes in runoff, as well as the response of runoff to climate change under various scenarios. The results indicated that: (1) from 1966 to 2022, annual precipitation, runoff and average temperature in the Danghe river basin exhibited significant increases, with rates of 10.57mm·10y1, 0.21×108m3·10y1 and 0.39℃·10y1, respectively, while potential evapotranspiration increased at a slower rate of 2.44mm·10y1. (2) The annual runoff at the Dangchengwan station experienced an abrupt change in 1982. Compared to the base period (1966−1982), the average runoff during the change period (1983−2022) increased by 0.73×108m3, with climate change identified as the primary influencing factor, contributing 58.22%. (3) Among the climate change factors, precipitation and average temperature were found to be the main driver of runoff changes. Under a climate scenario projecting an increase of 2.5°C in average annual temperature and a 20% rise in annual precipitation, the annual runoff depth change rate for the Danghe river basin was estimated at 23.66%. These research findings provide a theoretical basis for the integrated management of water resources in the Danghe river basin and for the sustainable development of the Dunhuang oasis.


    Coupling Coordination Relationship between Agricultural Water Resources Utilization Efficiency and Agricultural Modernization across Fenhe River Basin
    DAi Yan-yan, YAO Hang-yu, HAN Jia-qi, LIU Geng, CHAO Jin-long, ZHANG Lei, ZHANG Peng-fei
    2025, 46(7):  954-966.  doi:10.3969/j.issn.1000-6362.2025.07.005
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    Based on panel data encompassing agriculture, water resources, economy, and society from 40 counties (districts, cities) in the Fenhe river basin from 2011 to 2022, this study employed the coupling coordination degree model, Dagum Gini coefficient decomposition, and kernel density estimation to systematically analyze the spatiotemporal evolution characteristics and driving factors of the coupling coordination degree between agricultural water resources utilization efficiency and agricultural modernization. The aim was to provide scientific evidence and policy recommendations for achieving high−quality agricultural development in the Fenhe river basin. The results showed that: (1) from 2011 to 2022, the agricultural water resources utilization efficiency in the Fenhe river basin showed a fluctuating upward trend, with the mean efficiency evaluation score significantly increasing from 0.094 in 2011 to 0.134 in 2022 (P<0.05). Spatially, the efficiency generally followed the pattern of midstream (0.117) > upstream (0.096) > downstream (0.087). (2) The level of agricultural modernization in the Fenhe river basin also exhibited a fluctuating upward trend during the study period, with the mean evaluation score for development level significantly rising (P<0.05) from 0.183 in 2011 to 0.256 in 2022. Spatially, the midstream (0.220) and downstream (0.225) regions were significantly higher than the upstream region (0.168). (3) The coupling coordination degree between agricultural water resources utilization efficiency and agricultural modernization in the Fenhe river basin demonstrated a fluctuating upward trend from 2011 to 2022, with an average annual growth rate of 1.7%. Spatially, the midstream region (0.392) exhibited significantly higher coordination levels than the upstream (0.349) and downstream regions (0.370). (4) The regional disparities in coupling coordination across the upstream, midstream and downstream regions of the Fenhe river basin mainly stemmed from intra−regional and inter−regional differences. Upstream regions suffered from uneven resource allocation due to mountainous terrain and weak infrastructure, while the midstream regions benefited from intensive production models and policy support, demonstrating balanced development. Downstream regions achieved notable progress in ecological management and technological advancement. (5) During the study period, the kernel density curve of the coupling coordination degree in the Fenhe river basin shifted rightward, with peaks gradually rising and bandwidth narrowing, indicating a gradual reduction in disparities among the upstream, midstream and downstream regions and enhanced overall coordination. The study recommends strengthening infrastructure construction in upstream regions, promoting technology diffusion in midstream regions, and optimizing ecological governance policies in downstream regions to foster balanced regional development. 

    A Review of Rice-fishery Co-culture System Effects on Crops and the Environment
    FAN Hai-dan, LV Wei-guang, PEI Ya-nan, MA Meng-qian, BAI Na-ling, ZHANG Juan-qin, ZHANG Hai-yun, LI Shuang-xi, ZHANG Han-lin
    2025, 46(7):  967-976.  doi:10.3969/j.issn.1000-6362.2025.07.006
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    The coculture system of rice and aquatic animals is one of the main models of modern ecologically sustainable agriculture. The ricefishery aquaculture model, which combines rice and aquatic animals, can not only protect the biodiversity of paddy fields, but also maintain soil fertility and stabilize crop yields, with the potential of controlling water pollution, reducing greenhouse gas emissions, and increasing soil microbial activity in paddy fields. However, there are still controversies about the production performance and eco−environmental benefits of the rice−fishery co−culture system. In this paper, based on the latest research results of the impact of rice−fishery co−culture system on crops and the environment durning 2014 to 2023 at home and abroad, authors synthesized the key effects of rice−fishery co−culture system on crop yields, soil quality, water and gas, combined with the actual situation of rice−fishery co−culture system in China, and made outlooks and suggestions on the future research direction, with the aim of providing scientific support for the sustainable development of rice−fishery co−culture system. The results showed that the rice−fishery co−culture system could increase rice yield and quality, significantly improved soil physicochemical properties and soil microbial activity, and enhanced water quality and reduced CH4 emission. However, the mechanism of influence on N2O was not clear, which was mainly due to multiple factors such as water management, fertilizer management and aquatic animal species. 

    Potential Distribution Pattern of the Endemic Species Pomatosace filicula (Primulaceae) on the Qinghai−Tibetan Plateau
    WEI Xu-dong, WANG Sheng-zhen, YE De-li, MA Hong-yuan
    2025, 46(7):  977-987.  doi:10.3969/j.issn.1000-6362.2025.07.007
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    The distribution data of Pomatosace filicula (Primulaceae) , a second−class protected monotypic plant specied endemic to the Qinghai−Tibet Plateau, were investigated using MaxEnt (Maximum Entropy) ecological niche model and ArcGIS 10.7 software. 30 environmental variables, including climate, elevation, soil conditions and human activities were selected based on the species’ growth and distribution characteristics. The species’ potential distribution patterns and its responses to key environmental factors were simulated both with and without human activity impacts. The relationships between potential suitable distribution patterns and environmental factors were examined, and changes in potentially suitable distribution areas under human influence were analyzed. The following results were obtained: (1) the potential suitable areas for Pomatosace filicula in Qinghai province were primarily concentrated in the Three−river source region of southeastern Qinghai and the Qilian mountains in the northeast. Highly suitable areas, accounting for 14.2% of the province's total area, were mainly distributed across Chenduo, Maduo, Maqin, Gande, Dari, Jiuzhi, Henan and Zeku counties. Moderately suitable areas, comprising 15.4% of the provincial area, were predominantly found in Zhiduo, Zaduo, Qumalai, Tianjun, and Qilian counties. (2) When human activities were considered, the potential distribution area was found to be contracted and fragmented, displaying a strip−like pattern along plateau valleys. The total potential suitable area in Qinghai province was reduced by 35.6%, with highly suitable areas decreased by 9.96×104 km2 and moderately suitable areas reduced by 10.97×104 km2. (3) Without considering human influence, the primary environmental variables affecting Pomatosace filicula distribution were determined to be annual precipitation, elevation and precipitation in the driest season, with contribution rates of 27.7%, 14.5%, and 12.4%, respectively. When human activities were included, the main influencing factors were identified as the human footprint index, elevation and annual temperature range, with contribution rates of 57.6%, 11.6%, and 10.1%, respectively.

    Effect of Organic Fertilizers on Photosynthetic Characteristics, Yield and Quality of Flax
    MA Wei-ming, LI Wen-zhen, ZHAO Yong-wei, LI Ying, ZHANG Hai-jie, ZHANG Tong-ke, GAO Yu-hong
    2025, 46(7):  988-998.  doi:10.3969/j.issn.1000-6362.2025.07.008
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     In the arid and semi−arid regions of Northwest China, establishing effective nutrient management measures is crucial to optimize the growth of oilseed flax plants and improve yield and quality. In order to investigate the high−yield green cultivation technology to enhance the yield and quality of dryland oilseed flax, the effects of chemical fertilizer (T2), chicken manure organic fertilizer (T3), mushroom residue organic fertilizer (T4), bio−organic fertilizer (T5) and humic acid organic fertilizer (T6) on the accumulation of dry matter, photosynthetic characteristics and quality of oilseed flax were comparatively analyzed through a randomized block trial in the field, with no fertilizer application (T1) as the control treatment. The results showed that the leaf area under different fertilization treatments was higher than that of the control in different reproductive periods, the total chlorophyll content of T3 treatment at the flowering stage was significantly higher than that of other treatments by 14.09%−31.47%, and the photosynthetic potential of leaves under T3 treatment at the flowering to fruiting stage was significantly higher than that of other treatments by 5.42%−28.36%. Organic fertilizer could promote the dry matter accumulation in each reproductive period of oilseed flax, the dry matter accumulation of T3 treatment was significantly higher than other treatments by 3.80%−17.37% at the green fruit stage, and the organic fertilizer promoted the transport of leaf photosynthesis products to the seed, and the percentage of dry matter in the leaves was reduced in this period. Application of organic fertilizer could significantly increase the number of capsules, thousand grain weight and single plant yield, T3 treatment under the seed yield was significantly higher than other treatments 5.33%−43.64%, and significantly increased the oil content of the seed 1.66%−2.58% and linolenic acid content of 2.62%−6.52%, improving the quality of oilseed flax. In summary, the local organic fertilizer is conducive to optimize the photosynthetic characteristics of oilseed flax, improve seed yield and quality, can be used as suitable for high−yield and high−quality cultivation of oilseed flax in the arid and semi−arid areas of the northwest fertilization management techniques.

    Distribution of Potential Suitable Areas for Flue-cured Tobacco in Hubei Province under the Climate Change Scenario
    XU Hao-yuan, LI Wen-feng, REN Yong-jian, LI Jin-jian
    2025, 46(7):  999-1011.  doi:10.3969/j.issn.1000-6362.2025.07.009
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    Using the Maximum Entropy Model (MaxEnt), 80 flue−cured tobacco planting sites in Hubei province and 11 environmental variables from 1970 to 2000 were selected. Based on the future climate scenario data of CMIP6, the potential suitable area for flue−cured tobacco in the 2030s (2021−2040), 2050s (2041−2060), 2070s (2061−2080) and 2090s (2081−2100) was predicted to provide a scientific reference for the planning and layout of flue−cured tobacco planting in Hubei province. The results showed that the dominant environmental variables affecting flue−cured tobacco were elevation, precipitation of wettest month, slope and temperature seasonality, with a cumulative contribution rate of 86.8%. Under the current climate from 1970 to 2000, the total area of the potential suitable area for flue−cured tobacco was 4.52×104km2, mainly distributed in Enshi, the western and northern parts of Yichang, the southwestern part of Xiangyang and the central and southern parts of Shiyan. The area of high, moderate and low suitable area was 1.02×104km2, 1.45×104km2 and 2.05×104km2 respectively. Under the SSP1−2.6 and SSP2−4.5 climate scenarios, the potential suitable area for flue−cured tobacco in Hubei was projected to decrease in the 2030s, 2050s 2070s and 2090s and compare to the current climate, indicating a decline in overall suitability. Conversely, under the SSP3−7.0 and SSP5−8.5 climate scenarios, the potential suitable area was projected to increase in the 2030s, 2050s and 2090s, but decreased in the 2070s, relative to the current climate. The centroid of the potential suitable area for flue−cured tobacco in Hubei generally exhibited a westward shift from 2030s to 2090s under future climate change scenarios. To adapt to future climate change, it is recommended to promote the cultivation of flue-cured tobacco in Enshi, where the potential suitable area remains relatively stable and experiences some expansion, thereby capitalizing on the region's existing and emerging planting potential.
    Spatial-temporal Variation Characteristics of Spring Maize Drought in Northeast China Based on Dynamic Thresholds of SIF Index
    CHEN Yu-ye, WANG Pei-juan, ZHANG Yuan-da, LI Yang, Wang Qi, AN Xiao-ying
    2025, 46(7):  1012-1025.  doi:10.3969/j.issn.1000-6362.2025.07.010
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    Drought has become a problem faced by terrestrial ecosystems globally, with its development exhibiting distinct regional characteristics. Revealing the temporal and spatial distribution characteristics of regional drought is urgently required to address climate change and ensure the safety of agricultural production. Based on the drought dynamic threshold constructed using the Solar−induced chlorophyll fluorescence (SIF) index during the entire growth period of spring maize in Northeast China, drought frequency and affected areas of spring maize in this region from 2000 to 2020 had been calculated using pixel−by−pixel analysis method. Linear trend estimation and other methods were used to analyze the drought trends and spatial distribution characteristics of spring maize in Northeast China. The research findings were as follows: (1) from 2000 to 2020, the Solar−Induced Chlorophyll Fluorescence (SIF) values of spring maize in Northeast China exhibited a fluctuating upward trend on both the interannual scale and across different developmental stages in time series. Spatially, regions with an increasing trend in SIF values accounted for more than 50%, indicating that the study area had experienced a gradual reduction in drought impacts and a decreased risk of drought over the past 20 years. (2) From 2000 to 2020, the drought−affected areas in the spring maize cultivation regions of Northeast China showed a fluctuating decreasing trend. For different drought levels, the extent of drought−affected areas was ranked as follows: mild drought > moderate drought > severe drought. For different developmental stages of spring maize, the extent of drought−affected areas was ranked with: seedling stage > jointing to booting stage > filling to maturity stage > heading to flowering stage.(3) Most of the spring maize planting areas in northeast China experienced droughts, with a frequency exceeding 40%. The frequency of droughts was higher in the west than in the east. Among different drought severity levels, light drought occurs most frequently, while moderate and severe droughts had lower frequencies. In terms of different growth stages, most of the study area experienced drought frequencies exceeding 25% during the seedling stage. In particular, the central and western parts of Jilin province had frequencies higher than 45%, indicating that the seedling stage remained a period of high drought incidence for spring maize in northeast China.

    Spatiotemporal Variation Characteristics of Meteorological Drought in Xinjiang Based on Pixel−scale SPEI
    YI Ke-fan, LIN Hai-xia, QIN Guo-peng, YAO Ning, GAO Xue-hui, LU Wei-juan, LU Yu-hang, LIU Jian
    2025, 46(7):  1026-1038.  doi:10.3969/j.issn.1000-6362.2025.07.011
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    Based on the 19812018 China meteorological forcing dataset, the standardized precipitation evapotranspiration index (SPEI) was calculated for different time scales. The Mann−kendall (MK) test and Sen's slope method were used to analyze the spatial and temporal characteristics of meteorological drought in Xinjiang, including trends of change, frequency of occurrence and duration. This study endeavored to provide a scientific basis for the formulation of strategies for drought prevention and mitigation in Xinjiang. Results showed that: (1) from 1981 to 2018, the climate of Xinjiang exhibited a nonsignificant trend of aridification, with the proportion of droughtaffected area decreasing at a rate of 0.845 percentage points per decade in a non−significant manner. Both spring and summer climates showed a nonsignificant trend of aridification, while autumn meteorological droughts significantly intensified after 2005 and winter had tended to become wetter after 1997. (2) The spatial distribution of seasonal drought based on the SPEI3 in Xinjiang was regionally distinct. Significant droughtaffected areas were observed in spring, summer and autumn, with the intensified drought concentrated in the Tarim basin and a few eastern regions. During the winter, 57.82% of the area in Xinjiang exhibited a nonsignificant trend of wetting, 29.23% showed a significant trend of wetting, and only 0.03% showed a significant drought trend. The remaining areas showed a nonsignificant drought trend. (3) The spatial distribution of drought frequency at monthly, seasonal, and annual scales was relatively consistent, with the eastern region being a highfrequency drought zone. The average annual frequency of drought was 36.05%, with Turpan reaching 44.97%. Interdecadal differences in drought duration across Xinjiang were minimal, with the longest average drought duration observed in 20002009, which lasted 3.6 months. Generally, trends of aridification have intensified in the southern and eastern regions of Xinjiang over the past 38 years, with a high frequency of droughts, there is an urgent need for measures to mitigate the adverse impacts of drought.

    Spatiotemporal Characteristics of Agricultural Drought in the Tarim River Basin from 2000 to 2022 Based on the Vegetation Condition Index
    PENG Yong, LI Qiao, JIANG Ping-an, TAO Hong-fei, MAHEMUJIANG Aihemaiti
    2025, 46(7):  1039-1049.  doi:10.3969/j.issn.1000-6362.2025.07.012
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    Based on monthly MODIS series NDVI data from NASA between February 2000 and December 2022, the vegetation condition index (VCI) was calculated, and combined with land use type data. Methods such as univariate linear regression, the Theil-Sen Median trend test, and the Mann−Kendall test were used to analyze the trend and abrupt change of VCI, the drought proportion, and the drought frequency. The spatiotemporal characteristics of agricultural drought in the Tarim river basin were explored. The results indicated that: (1) the VCI concentration in the Tarim river basin from 2000 to 2022 was between 0.3−0.6 and showed a significant increase trend. The drought proportion was showing a significant decrease trend, with the highest drought proportion being 98.4%, and the lowest being 38.6%. The most severe seasons, annual, and land use types of drought were spring, 2000 and cultivated land, respectively. The years of agricultural drought abrupt changed in the Tarim river basin and its different land use types (cultivated land, wood land, meadow) were in 2011, 2010, 2014, and 2015, respectively. (2) The proportion of VCI spatial changes showed a highly significant increasing trend during the growing season was the highest, accounting for 63.50%. The frequency of agricultural drought in spring, summer, autumn, and growing season was mainly concentrated in the range of 50%−100%. The regions where VCI spatial changes showed a significant increasing trend, mainly distributed in the central and southeastern parts of Kaidu−Kongque river, the central part of Aksu river, the central and northeastern parts of Kashgar river. The low−frequency areas where agricultural drought occurs were mainly distributed in the southern part of Hotan river, the southern part of the small rivers of Crimea river, and the northern and southwestern parts of the small rivers of Chechen river. Overall, the agricultural drought in the Tarim river basin from 2000 to 2022 is mainly characterized by regional drought and shows a decreasing trend year by year.

    Identification Technology of Rice Development Stages Based on Real Pictures via Deep Learning
    WANG Yang-yang, OU Xiao-feng, HUANG Wan-hua, YUAN Yu-rong, LIU Fan, PANG Xin-wei, SHUAI Zi-ang, SHUAI Xi-qiang
    2025, 46(7):  1050-1062.  doi:10.3969/j.issn.1000-6362.2025.07.013
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    Based on photos of rice collected hourly during the daytime and manually observed developmental stage data from Qiaoshang village, Luyang town, Zhongfang county, Huaihua city, Hunan province in 2023, a picture dataset containing developmental stages of rice which were seeding period, greening period, tillering period, jointing period, booting period, heading period, grain filling period as well as pre-seeding and the harvested period in a total of 10 periods had been established and processed using cuttingpreprocessing and data enhancement techniques. Six representative deep learning network models, namely 18-layers residual networkResNet18, 50-layers residual network variantResNet50_vd, lightweight convolutional networkMobileNetV3_large, lightweight convolutional networkPPLCNet, deep convolutional residual networkXception41, and densely connected convolutional networkDenseNet121were selected, which were used as pre-training models to recognize the developmental stages of rice based on real pictures, the performances of the six models were compared in the training and test sets to evaluate their accuracy and loss rate to verify the feasibility of the deep learning model for the intelligent recognition of rice developmental stage, analyze its differences, and screen out the optimal rice developmental stage recognition model to promote its application in the business service. The results indicated that all models achieved a recognition accuracy of 92% or higher on the test set, among these models, Xception41 exhibited the highest recognition accuracy of 96.19%. The best model for recognition of pre-seeding, seeding, tillering, booting, grain filling and maturity periods of rice was Xception41, the best model for recognition of greening period of rice was ResNet50_vd, the best models for recognition of jointing and heading periods of rice were DenseNet121 and Xception41, and the best model for recognition of harvested period of rice were ResNet50_vd and DenseNet121 for test set. The study provided a new idea for the intelligent recognition of rice developmental stage, demonstrating the feasibility of deep learning models in recognition of rice live pictures and their potential to meet the demand of agricultural meteorological business services

    Evaluation of the Applicability of ESA-CCI Soil Moisture Data in China
    HU Jie, JIANG Zhi-wei, JIANG Tao, WANG Hai-bing, YANG Zhi-bo
    2025, 46(7):  1063-1076.  doi:10.3969/j.issn.1000-6362.2025.07.014
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    To address the issues of extensive missing values and limited applicability of ESA−CCI soil moisture data in China, a three−dimensional spatio-temporal gap−filling method was developed by incorporating the K−Nearest Neighbor (KNN) machine learning algorithm, with full consideration given to spatio−temporal data correlations and structural characteristics. A comparative analysis of regional applicability was conducted utilizing ESA−CCI soil moisture products and ground observation data collected from May to October during 2016−2018 across China. Three main findings were obtained: (1) significant improvement in spatio−temporal continuity was achieved in the gap−filled ESA−CCI soil moisture data, with the original spatio−temporal structural characteristics being well preserved. The processed data demonstrated enhanced capacity in representing China's soil moisture variation patterns, though spatial structure and heterogeneity characterization outperformed temporal fluctuation representation. (2) Statistical distribution consistency was observed between the gap−filled ESA−CCI data and ground measurements. The filled data exhibited satisfactory accuracy and consistency nationwide, with average performance metrics recorded as follows: root mean square error (RMSE) of 0.068 m3·m3, bias of 0.008 m3·m3, correlation coefficient (r) of 0.618, and structure similarity index measure (SSIM) of 0.999. (3) Regional comprehensive applicability was evaluated through combined analysis of data missing rates and spatio−temporal metrics. Optimal performance was identified in the Huang−Huai−Hai plain, Loess Plateau and Northeast plain regions. Intermediate applicability was observed in the Yunnan−Guizhou plateau, middle−lower Yangtze river basin and Northern Arid/Semi−arid regions. Although improved spatio−temporal coverage continuity was noted in the Sichuan Basin and South China regions, relatively poorer evaluation metrics were obtained. The most severe data limitations and poorest comprehensive applicability were found in the Qinghai−Tibet Plateau region.