Guo et al. (2026) Wind-water energy characteristics and sediment transport prediction in sandy coarse sand basin

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-03-11
• Authors: Xingyue Guo, Tian Wang, Zhanbin Li, Peng Li, Heng Wu, Xiaoming Zhang, Tiegang Zhang, Ganggang Ke, Yunzhe Zhen
• DOI: 10.1016/j.jhydrol.2026.135289

Research Groups

• State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Xi’an University of Technology
• Key Laboratory of National Forestry Administration on Ecological Hydrology and Disaster Prevention in Arid Regions, Xi’an University of Technology
• State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research
• Inner Mongolia Yin Mountain Northern Foothills Grassland Ecological Hydrology National Field Scientific Observation and Research Station, China Institute of Water Resources and Hydropower Research

Short Summary

This study developed an energy-based wind-water composite watershed erosion and sediment transport model for the sandy coarse sand area of the Yellow River, demonstrating its high accuracy in predicting sediment yield across different soil types and revealing significant spatiotemporal differentiation of erosion energies.

Objective

• To address the issue of erosion mechanism differentiation caused by differences in soil surface properties in the sandy coarse sand area of the middle reaches of the Yellow River.
• To construct an energy-based wind-water composite watershed erosion and sediment transport model to accurately simulate composite erosion sediment yield and provide scientific support for soil and water conservation.

Study Configuration

• Spatial Scale: Sandy coarse sand area in the middle reaches of the Yellow River, specifically analyzing sand-covered bedrock, sand-covered loess, and loess erosion areas.
• Temporal Scale: Annual cycle, with seasonal differentiation analysis (wind erosion concentrated in spring, water erosion concentrated in summer).

Methodology and Data

• Models used: Energy-based wind-water composite watershed erosion and sediment transport model; energy-based wind erosion sediment transport prediction models.
• Data sources: Wind tunnel experiments, hydrometeorological data.

Main Results

• Wind erosion energy-based sediment transport prediction models showed high fitting degrees and reliability for sand-covered bedrock (R² = 0.944, RSR = 0.305), sand-covered loess (R² = 0.979, RSR = 0.188), and loess erosion areas (R² = 0.978, RSR = 0.194).
• Wind erosion energy is concentrated in spring, and water erosion energy is concentrated in summer, indicating significant spatiotemporal differentiation.
• Average annual energy values followed the order: sand-covered loess area > sand-covered bedrock area > loess area.
• The compound erosion sediment yield model exhibited good adaptability across all three soil types, with R² values no less than 0.75 and RSR values all below 0.5 during both calibration and validation.
• The model achieved the highest accuracy in the sand-covered bedrock area, with an R² of 0.989 and an RSR of 0.104.

Contributions

• Developed and validated a novel energy-based wind-water composite watershed erosion and sediment transport model for complex erosion zones.
• Quantified the spatiotemporal differentiation of wind and water erosion energies in the sandy coarse sand area of the Yellow River.
• Provided a scientific basis for precise soil and water conservation management strategies in regions affected by composite erosion.

Funding

• Not specified in the provided text.

Citation

@article{Guo2026Windwater,
  author = {Guo, Xingyue and Wang, Tian and Li, Zhanbin and Li, Peng and Wu, Heng and Zhang, Xiaoming and Zhang, Tiegang and Ke, Ganggang and Zhen, Yunzhe},
  title = {Wind-water energy characteristics and sediment transport prediction in sandy coarse sand basin},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.135289},
  url = {https://doi.org/10.1016/j.jhydrol.2026.135289}
}