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Analysis of the spatiotemporal characteristics of water and cultivated land resources balance in Northern China
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Chun DONG1, 2, Yuhan ZHAO1, 2, Yan YANG2, *, Chaoying HE3, Rong ZHAO2, Wei ZHAO3, Fengguang KANG2, Xiaochen KANG2, Xinglong QIAN2
Transactions of the Chinese Society of Agricultural Engineering | 2026, 42(12) : 155 - 166
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Transactions of the Chinese Society of Agricultural Engineering | 2026, 42(12): 155-166
Soil and Water Engineering
Analysis of the spatiotemporal characteristics of water and cultivated land resources balance in Northern China
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Chun DONG1, 2, Yuhan ZHAO1, 2, Yan YANG2, *, Chaoying HE3, Rong ZHAO2, Wei ZHAO3, Fengguang KANG2, Xiaochen KANG2, Xinglong QIAN2
Affiliations
  • 1School of Mapping and Geographical Science, Liaoning Technical University, Fuxin 123000, China
  • 2Chinese Academy of Surveying and Mapping, Beijing 100036, China
  • 3Department of Natural Resources Survey and Monitoring, Ministry of Natural Resources, Beijing 100812, China
Published: 2026-06-30 doi: 10.11975/j.issn.1002-6819.202507115
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Cropland water–land balance relationship can be regulated to maintain the cropland productivity, ecological stability, and sustainable land use. It is often required to optimize cropland spatial layout and crop planting structure in sustainable water and land resources, according to “Determining Land Use by Water Availability”. In this study, an integrated analytical framework was developed to explore the spatiotemporal characteristics of the balance between water and cultivated land resources. There was also a close relationship between crop water requirement, water deficit and surplus, drought events, and productivity loss. The research area was taken as the five major agricultural regions in northern China. Meteorological, crop planting structure, and gross primary productivity (GPP) were monthly collected from 2001 to 2022. The full-growing-season crop water requirements of winter wheat, spring maize, and summer maize were estimated using the FAO-56 crop coefficient. A decadal Crop Water Deficit and Surplus Index (CWDI) and its standardized form, the Standardized Crop Water Deficit and Surplus Index (SCWDI), were then constructed to integrate run theory. Empirical orthogonal function (EOF) analysis, correlation analysis, and a Copula–Bayesian conditional probability model were used to systematically identify the Spatiotemporal evolution of cropland water–land balance relationships, crop critical water-demand periods, and productivity loss risks under drought stress. The results showed that (1) multi-year mean full-growing-season water requirements of winter wheat and maize were 500 and 594 mm, respectively, particularly with 627 and 536 mm for spring and summer maize, respectively. Crop water requirements shared significant regional differences. In winter wheat, the water requirement followed the descending order of Huang–Huai–Hai Plain (521 mm) > Loess Plateau (514 mm) > Gansu–Xinjiang Region (467 mm), while spring maize shared the highest water requirement in the Gansu–Xinjiang Region (662 mm). (2) Average drought-event frequency ranged from 0.4 to 2.0 events per year. The Gansu–Xinjiang Region was characterized by a high proportion of extreme drought events, long duration, and high intensity, indicating a cumulative drought pattern, whereas the Huang–Huai–Hai Plain was dominated by high-frequency but short-duration drought events. (3) EOF decomposition showed that the first five modes cumulatively explained 73.7% of the total variance, with EOF1 and EOF2 accounting for 28.6% and 20.0%, respectively, indicating region-wide consistency and regional heterogeneity in interannual dry–wet variations of cropland. (4) Correlation analysis between SCWDI and standardized GPP (SGPP) showed that the key months were identified as July for spring and summer maize, while May for winter wheat. According to the cumulative effect, the water-demand stages of spring maize, summer maize, and winter wheat corresponded to May–June, June, and March–April, respectively. (5) SCWDI–SGPP dependence structures of spring maize and summer maize were best fitted by the Gaussian Copula, while the Frank Copula performed best for winter wheat. The average probabilities of productivity loss were 63%, 80%, and 44%, respectively, for spring maize, summer maize, and winter wheat under extreme drought conditions. The north-central Huang–Huai–Hai Plain and the Loess Plateau were identified as the drought stress conversion into productivity loss. The finding can provide a scientific basis for the optimal cropland layout and crop structure during drought risk prevention in northern China.

water-cultivated land balance  /  crop water requirement  /  SCWDI  /  drought event  /  run theory  /  Copula–Bayesian  /  GPP loss risk
Chun DONG, Yuhan ZHAO, Yan YANG, Chaoying HE, Rong ZHAO, Wei ZHAO, Fengguang KANG, Xiaochen KANG, Xinglong QIAN. Analysis of the spatiotemporal characteristics of water and cultivated land resources balance in Northern China[J]. Transactions of the Chinese Society of Agricultural Engineering, 2026 , 42 (12) : 155 -166 . DOI: 10.11975/j.issn.1002-6819.202507115
Year 2026 volume 42 Issue 12
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doi: 10.11975/j.issn.1002-6819.202507115
  • Receive Date:2025-07-14
  • Online Date:2026-08-20
  • Published:2026-06-30
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  • Received:2025-07-14
  • Revised:2026-03-18
Affiliations
    1School of Mapping and Geographical Science, Liaoning Technical University, Fuxin 123000, China
    2Chinese Academy of Surveying and Mapping, Beijing 100036, China
    3Department of Natural Resources Survey and Monitoring, Ministry of Natural Resources, Beijing 100812, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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