Song et al. (2025) Modelling water and land resources synergy and trade-off in a major grain-producing area, China

Identification

• Journal: Agricultural Water Management
• Year: 2025
• Date: 2025-10-11
• Authors: Hao Song, Bo Li, Zhijun Li, Guangxin Zhang, Xixi Lu, Peng Qi
• DOI: 10.1016/j.agwat.2025.109880

Research Groups

• Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, China
• Institute of Water Conservancy and Electric Power, Heilongjiang University, China
• Department of Geography, National University of Singapore, Singapore

Short Summary

This study develops a novel water-carbon-food-ecology (WCFE) nexus framework to spatially optimize water and land resource allocation in China's Sanjiang Plain. It demonstrates significant water savings, enhanced carbon sequestration, and improved ecological connectivity under both conventional and water-saving irrigation scenarios, albeit with a slight reduction in economic benefits.

Objective

• To coordinate and optimize limited water and land resources in the Sanjiang Plain through a novel water-carbon-food-ecology (WCFE) nexus framework, aiming to improve water resource utilization efficiency, increase food production capacity, protect ecosystems, and enhance carbon sequestration, with a focus on explicit spatial allocation under conventional and water-saving irrigation scenarios.

Study Configuration

• Spatial Scale: Sanjiang Plain, northeastern Heilongjiang Province, China (45°01′5″N to 48°27′56″N, and 129°11′47″E to 135°05′26″E), divided into 12 major sub-basins. Distributed hydrological model (CWatM) uses a spatial resolution of 0.5 degrees.
• Temporal Scale: Meteorological data and simulations for the period 2000–2019, focusing on multi-year average available water resources.

Methodology and Data

• Models used:
  • Community Water Model (CWatM): Distributed hydrological model for daily water cycle simulation.
  • Multi-objective optimization model (WCFE nexus): Integrates water resources, carbon sequestration, net agricultural product value, and ecological benefits.
  • Non-dominated Sorting Genetic Algorithm III (NSGA-III): Algorithm for solving multi-objective optimization problems.
  • Entropy-weighted TOPSIS method: For evaluating and screening optimal solutions.
  • GridLandOpt model: For spatial optimization of land use, considering ecological connectivity and conversion costs.
• Data sources:
  • Meteorological data: ISIMIP (Inter-Sectoral Impact Model Intercomparison Project) for 2000–2019 (daily maximum/minimum temperatures, surface radiation, precipitation).
  • River network and drainage direction data: IIASA (International Institute for Applied Systems Analysis).
  • Global land cover data: USGS (United States Geological Survey), reclassified for maize, rice, soybean, forest, grassland, and wetlands.
  • Statistical data: Heilongjiang Statistical Yearbook and provincial financial reports (crop yields, prices, subsidies, fertilizer usage, agricultural machinery, population).
  • Observed runoff data: Local hydrological stations.
  • Surface and groundwater use data: Water Resources Bulletin.
  • Evapotranspiration data: National Tibetan Plateau Scientific Data Center.

Main Results

• Water Resources Variability (2000–2019): Total water resources in the Sanjiang Plain fluctuated between 15.67 billion m³ and 47.92 billion m³, with a multi-year average of 25.07 billion m³. Average annual precipitation ranged from 438 mm to 930 mm, and actual evapotranspiration from 372 mm to 456 mm.
• Water Resource Optimization:
  • Conventional Irrigation Mode: Achieved total water savings of approximately 2.30 billion m³ (surface water reduced by 1.65 billion m³, groundwater by 0.65 billion m³).
  • Water-Saving Irrigation Mode: Achieved total water savings of approximately 4.50 billion m³ (surface water reduced by 3.27 billion m³, groundwater by 1.23 billion m³).
• Carbon Sequestration Optimization:
  • Conventional Irrigation Mode: Total carbon sequestration increased by 12.53% compared to pre-optimization, with maize becoming the largest contributor to carbon absorption (46.84%).
  • Water-Saving Irrigation Mode: Total carbon sequestration increased by 11.21%.
• Ecological Benefits Optimization:
  • Conventional Irrigation Mode: Total ecological benefits increased by 10.20 billion yuan, with wetland area expanding by approximately 1.61 × 10⁴ ha.
  • Water-Saving Irrigation Mode: Total ecological benefits increased by 2.74 billion yuan, with wetland area expanding by approximately 5.61 × 10³ ha.
• Economic Benefits and Crop Yields Optimization:
  • Conventional Irrigation Mode: Overall economic benefit decreased by 3.47 billion yuan. Rice yield decreased by 8.13 billion kg, while maize and soybean yields increased by 4.16 billion kg and 1.16 billion kg, respectively.
  • Water-Saving Irrigation Mode: Overall economic benefit decreased by 3.00 billion yuan. Rice yield decreased by 6.80 billion kg, while maize and soybean yields increased by 3.77 billion kg and 0.89 billion kg, respectively.
• Land Use Optimization:
  • Conventional Irrigation Mode: Crop area ratios of rice, maize, and soybeans adjusted from 3:2:1 to 2.2:2.4:1.4. Overall ecological connectivity improved by 2.79%, with a total land use conversion cost of 427 million yuan.
  • Water-Saving Irrigation Mode: Crop area ratios adjusted to 2.3:2.4:1.3. Ecological connectivity increased by 2.30%, with a conversion cost of 0.36 billion yuan.

Contributions

• Developed a novel water-carbon-food-ecology (WCFE) nexus system by integrating a distributed hydrological model (CWatM), a multi-objective optimization model (NSGA-III), and a spatial optimization model (GridLandOpt).
• Provided a comprehensive evaluation framework for carbon cycling and ecological benefits, moving beyond purely economic objectives in water and land resource optimization.
• Introduced an optimization scheme with explicit spatial representation, enhancing regional ecological connectivity and providing practical guidance for land use management.
• Addressed the lack of systematic consideration of coordination and trade-offs among water, carbon, food, and ecological objectives in major grain-producing areas.
• Offered scientific and practical references for the sustainable utilization of water and land resources, stable grain production, and improvement of ecosystem service functions in China’s major grain-producing areas.

Funding

• National Key Research and Development Program of China (No. 2022YFF1300902 and 2024YFD1501700)
• The Strategic Priority Research Program of the Chinese Academy of Science (No. XDA28100105)

Citation

@article{Song2025Modelling,
  author = {Song, Hao and Li, Bo and Li, Zhijun and Zhang, Guangxin and Lu, Xixi and Qi, Peng},
  title = {Modelling water and land resources synergy and trade-off in a major grain-producing area, China},
  journal = {Agricultural Water Management},
  year = {2025},
  doi = {10.1016/j.agwat.2025.109880},
  url = {https://doi.org/10.1016/j.agwat.2025.109880}
}