Shi et al. (2025) Spatiotemporal evolution pattern of water yield service of ecosystems in the Shule River Basin, Northwest China, integrating future climate and land use changes

Identification

• Journal: Ecological Indicators
• Year: 2025
• Date: 2025-11-20
• Authors: Peng Shi, Dongmei Zhou, Jing Jiang, Xin Huang, Jun Zhang, Qinghan Dong, Yiyang Jia
• DOI: 10.1016/j.ecolind.2025.114452

Research Groups

• College of Resources and Environmental Science, Gansu Agricultural University, Lanzhou, China
• College of Management, Gansu Agricultural University, Lanzhou, China
• Flemish Institute for Technological Research (VITO), Mol, Belgium
• Lanzhou Meteorological Administration, Lanzhou, China

Short Summary

This study projected future water yield in the Shule River Basin under various climate and land-use scenarios for 2030 and 2050 using InVEST, FLUS, and Geodetector models, finding that water yield generally increases, primarily driven by precipitation and digital elevation model (DEM), with significant spatial heterogeneity.

Objective

• To simulate the future spatiotemporal patterns of ecosystem water yield in the Shule River Basin for 2030 and 2050 under various land-use and climate change scenarios, and to identify the key environmental factors influencing these variations to provide a scientific foundation for water resource allocation and comprehensive watershed management.

Study Configuration

• Spatial Scale: Shule River Basin, Northwest China (38°00′–42°48′ N, 92°11′–98°30′ E), a typical arid inland river basin. All data were resampled to a 1 km spatial resolution.
• Temporal Scale: Base year 2020, with future projections for 2030 and 2050. Historical climate and socioeconomic data from 2000, 2010, and 2020 were used for model calibration.

Methodology and Data

• Models used:
  • Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model (Water Yield module)
  • Future Land Use Simulation (FLUS) model
  • Geodetector model
• Data sources:
  • Population density: WorldPop (http://hub.worldpop.org)
  • Road data: https://www.gisrs.cn/
  • Land use data: https://essd.copernicus.org/articles/13/3907/2021/
  • Elevation (DEM): http://www.gscloud.cn
  • Precipitation (2000, 2010, 2020): https://www.geodata.cn
  • Temperature (2000, 2010, 2020): https://www.geodata.cn
  • Gross Domestic Product (GDP) (2000, 2010, 2020): https://www.gisrs.cn/
  • Evaporation data: https://poles.tpdc.ac.cn/
  • Soil data: https://poles.tpdc.ac.cn/
  • Future climate data (SSP119, SSP245, SSP585): CMIP6 Scenario Model Intercomparison Project (ScenarioMIP) (https://poles.tpdc.ac.cn/) at 30° resolution.

Main Results

• In 2020, desert was the predominant land-use type in the Shule River Basin, covering 78.6% of the total area, followed by grassland (18.4%), farmland (1.53%), water body (0.62%), forest (0.53%), and construction land (0.30%). Deserts are projected to remain the dominant land-use type under all nine future scenarios.
• The spatial distribution of water yield in 2020 showed high values concentrated in the southern part of the basin (e.g., Subei) and lower values in the northern and eastern areas (e.g., Dunhuang), a pattern projected to persist.
• By 2030, under natural development and farmland protection scenarios (SSP119 and SSP245 pathways), significant increases in water yield are projected around Yumen.
• By 2050, the increase in water yield is expected to be more pronounced under the SSP245 and SSP585 pathways across natural development, farmland protection, and ecological protection scenarios, particularly in Subei, Guazhou, and Yumen.
• Under the natural development scenario, water yield is projected to reach approximately 843 Mm³ by 2030 (SSP585) and 1.482 Gm³ by 2050 (SSP245). Under the farmland protection scenario, the highest water yield is projected at 833 Mm³ by 2030 (SSP585) and 1.477 Gm³ by 2050 (SSP245). Under the ecological protection scenario, water yield is projected at 832 Mm³ by 2030 (SSP245) and 1.474 Gm³ by 2050 (SSP245).
• Subei consistently exhibited the highest water yield, while Dunhuang had the lowest across all scenarios. The overall water yield of the Shule River Basin was found to be greater than the sum of the water yields of individual districts and counties.
• Factor detection analysis ranked the influencing factors on water yield by importance (q-value) as: precipitation (0.923) > digital elevation model (DEM) (0.859) > temperature (0.818) > slope (0.395) > GDP (0.147) > land-use type (0.023) > aspect (0.019) > population density (0.009). Natural factors, especially precipitation, are the primary drivers.
• Interaction detection revealed significant synergistic effects, with the interaction between any two factors surpassing their individual explanatory power (nonlinear or dual-factor enhancement). The strongest interaction was observed between precipitation and land-use type (q=0.964).

Contributions

• First-time coupling of FLUS, InVEST, and Geodetector models in an arid inland river basin to quantify the interactive effects of climate and land use under Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathway (RCP) scenarios.
• Demonstrated that basin-wide protection strategies for water resources yield greater benefits than the sum of individual county-level protection efforts, advocating for integrated watershed management.
• Identified a positive feedback mechanism involving "glacier – precipitation – vegetation" that challenges the conventional understanding that warming in arid regions inevitably leads to reduced water yield.

Funding

• Science and Technology Major Project of Gansu Province (25ZYJA032)
• Key R&D Project in Gansu Province (23YFNA0036)
• Innovation Fund of Gansu Education Department (2025A-098, 2025B-096, 2025B-110)
• Natural Science Foundation of Gansu Province (23JRRA1413; 24JRRA774)

Citation

@article{Shi2025Spatiotemporal,
  author = {Shi, Peng and Zhou, Dongmei and Jiang, Jing and Huang, Xin and Zhang, Jun and Dong, Qinghan and Jia, Yiyang},
  title = {Spatiotemporal evolution pattern of water yield service of ecosystems in the Shule River Basin, Northwest China, integrating future climate and land use changes},
  journal = {Ecological Indicators},
  year = {2025},
  doi = {10.1016/j.ecolind.2025.114452},
  url = {https://doi.org/10.1016/j.ecolind.2025.114452}
}