Duan (2026) Dataset for hybrid streamflow simulation in a semi-arid grassland catchment

Identification

• Journal: Mendeley Data
• Year: 2026
• Date: 2026-03-25
• Authors: Limin Duan
• DOI: 10.17632/wfgsnpdpm3.2

Research Groups

Inner Mongolia Agricultural University

Short Summary

This dataset supports a study on hybrid streamflow simulation in a semi-arid grassland catchment, utilizing an enhanced distributed hydrological model and deep learning for residual correction. It provides processed hydro-meteorological forcing data, model input files, parameter-related variables, and simulation outputs for model calibration and validation.

Objective

• To provide a comprehensive dataset supporting hybrid streamflow simulation in a semi-arid grassland catchment using an enhanced distributed hydrological model and deep learning residual correction.

Study Configuration

• Spatial Scale: Semi-arid grassland catchment
• Temporal Scale: Not explicitly stated, but includes time-series hydro-meteorological forcing data.

Methodology and Data

• Models used: Enhanced distributed hydrological model, Deep learning residual correction
• Data sources: Processed hydro-meteorological forcing data, model input files, selected parameter-related variables, simulation outputs.

Main Results

The main results are reported in a separate manuscript which this dataset supports; they are not detailed within this dataset description.

Contributions

This dataset provides a valuable resource for researchers, enabling the reproduction and further investigation of hybrid streamflow simulation in semi-arid grassland catchments using advanced hydrological modeling and deep learning techniques.

Funding

Not specified in the provided text.

Citation

@article{Duan2026Dataset,
  author = {Duan, Limin},
  title = {Dataset for hybrid streamflow simulation in a semi-arid grassland catchment},
  journal = {Mendeley Data},
  year = {2026},
  doi = {10.17632/wfgsnpdpm3.2},
  url = {https://doi.org/10.17632/wfgsnpdpm3.2}
}