Zhang et al. (2025) Assessing the Dominant Impact of Climate and Land Use Change on Runoff Through Multi-Model Simulation in the Karst Headwater Region of the Wujiang River

Identification

• Journal: Water
• Year: 2025
• Date: 2025-11-29
• Authors: Qian Zhang, Yilin Zhou, Yaoming Ma, Xiaohua Dong
• DOI: 10.3390/w17233412

Research Groups

• College of Ecological Engineering, Guizhou University of Engineering Science, Bijie, China
• College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang, China
• Land-Atmosphere Interaction and Its Climatic Effects Group, State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
• College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
• College of Atmospheric Science, Lanzhou University, Lanzhou, China
• National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri, China
• Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing, China
• China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, Islamabad, Pakistan

Short Summary

This study utilized multi-model simulations (SWAT, CA-Markov, CMIP6) to assess the impacts of climate and land use change on runoff in the karst headwater region of the Wujiang River, concluding that climate change is the dominant factor driving future runoff reduction.

Objective

• To systematically investigate the mechanisms by which land use and climate change affect watershed runoff in the Wujiang River source area, with particular attention to the hydrological peculiarities of karst terrain.
• To project future runoff trends under various land use and climate scenarios to support sustainable water resources management.

Study Configuration

• Spatial Scale: Wujiang River headwaters basin, located between 26°38′–27°29′ N and 104°51′–105°56′ E, covering a total drainage area of approximately 8086 km².
• Temporal Scale:
  • Historical data: 1990–2018 (meteorological, runoff). Land use maps for 2000, 2005, 2010, 2015, 2020.
  • Model warm-up: 1988–1989.
  • Calibration: 1990–2013.
  • Validation: 2014–2018.
  • Future projections: 2041–2050 (climate), 2050 (land use).

Methodology and Data

• Models used:
  • Soil and Water Assessment Tool (SWAT) for hydrological simulation.
  • CA-Markov model for land use projection.
  • CMIP6 (Coupled Model Intercomparison Project Phase 6) climate data under SSP245 (medium emissions) and SSP585 (high emissions) scenarios.
• Data sources:
  • Digital Elevation Model (DEM): Geospatial Data Cloud (30 m resolution).
  • Land Use Data: Resource and Environmental Science and Data Center of the Chinese Academy of Sciences (30 m resolution, for 2000, 2005, 2010, 2015, 2020).
  • Soil Type Data: Harmonized World Soil Database (HWSD) (1 km resolution).
  • Meteorological Data (daily precipitation, maximum/minimum temperature, average wind speed, relative humidity, solar radiation): China Meteorological Assimilation Driving Datasets for Soil and Water Assessment Tool (CMADS) (1990–2018).
  • Runoff Observations (monthly): Chinese Natural Runoff Grid Point Dataset CNRD v1.0 (1990–2018).
  • Future Climate Data (daily precipitation, maximum/minimum temperature, wind speed): Downscaled CMIP6 dataset for China (0.25° resolution, 2041–2050, SSP245 and SSP585 scenarios).

Main Results

• The SWAT model demonstrated satisfactory performance in simulating hydrological processes in the karst basin, achieving R² and Nash-Sutcliffe Efficiency (NSE) values of at least 0.75 and 0.7, respectively, and absolute Percent Bias (PBIAS) values below 10% during both calibration and validation.
• Historical land use changes (2000–2015) showed limited impact on runoff, with variations of -0.11% to -0.32% compared to the 2020 baseline.
• Extreme land use scenarios revealed that converting land to cropland resulted in a 0.97% runoff decrease, converting to forest led to a 2.34% runoff increase, and converting to grassland caused a 3.51% runoff decrease. Runoff was most sensitive to changes in grassland cover.
• Future land use projections for 2050 indicate a 236.15% expansion of built-up land, leading to a projected 1.98% increase in mean annual runoff compared to the 2020 baseline, as increased impervious surfaces outweigh other land cover changes.
• Future climate scenarios (SSP245 and SSP585) consistently project a decreasing trend in runoff despite an overall increase in annual precipitation (SSP245: 1003.05 mm; SSP585: 1016.18 mm, compared to baseline 719.79 mm). Runoff is projected to decrease by 14.61% under SSP245 and 12.85% under SSP585, primarily due to rising temperatures and increased evapotranspiration.
• Combined scenario analyses project a total runoff decrease of 12.95% to 14.42% by 2050, confirming that climate change is the dominant factor driving runoff reduction in the karst basin, significantly outweighing the influence of land use alteration.

Contributions

• Provides a comprehensive assessment of runoff response to land use and climate change in the Wujiang River Source Region Basin, a critical karst-dominated area.
• Enhances the mechanistic understanding of karst hydrological processes under global environmental change.
• Establishes a robust methodology integrating the SWAT model with CA-Markov land use projections and CMIP6 climate scenarios, which holds potential for extension to other karst regions.
• Offers a valuable scientific foundation for regional water resource management and planning, supporting adaptive strategies for the conservation of the Wujiang River source area.
• Quantitatively demonstrates the overwhelming role of climate forcing as the primary driver of future runoff reduction in karst basins, even with secondary influences from land use changes.

Funding

• Bijie Science and Technology Joint Fund Project (bike-lianhe[2025]29)
• Programs for Joint Funds of Bijie Science and Technology (bike-lianhe[2025]29)

Citation

@article{Zhang2025Assessing,
  author = {Zhang, Qian and Zhou, Yilin and Ma, Yaoming and Dong, Xiaohua},
  title = {Assessing the Dominant Impact of Climate and Land Use Change on Runoff Through Multi-Model Simulation in the Karst Headwater Region of the Wujiang River},
  journal = {Water},
  year = {2025},
  doi = {10.3390/w17233412},
  url = {https://doi.org/10.3390/w17233412}
}