Quansah et al. (2025) Evaluating the Performance of the National Water Model: A Spatiotemporal Analysis of Streamflow Forecasting

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Water
• Year: 2025
• Date: 2025-10-13
• Authors: Joseph E. Quansah, Rubén Doria, Souleymane Fall
• DOI: 10.3390/w17202950

Research Groups

Not explicitly stated in the provided text, but likely involves institutions related to the National Water Model (NWM) development and the U.S. Geological Survey (USGS).

Short Summary

This study evaluates the performance of the National Water Model (NWM) v2.1 in simulating streamflow across the Alabama Black Belt Region, finding that its accuracy significantly improves with longer forecast terms, achieving good performance at the monthly scale despite a consistent negative bias across all time scales.

Objective

• To evaluate the performance of the National Water Model (NWM) v2.1 in simulating streamflow across the Alabama Black Belt Region (ABBR) in the southeastern United States.

Study Configuration

• Spatial Scale: Alabama Black Belt Region (ABBR), southeastern United States.
• Temporal Scale: Hourly, daily, weekly, and monthly.

Methodology and Data

• Models used: National Water Model (NWM) v2.1.
• Data sources: Retrospective NWM streamflow data and U.S. Geological Survey (USGS) observed streamflow data.
• Metrics used: Nash-Sutcliffe Efficiency (NSE), Root Mean Square Error Ratio (RSR), and Percent Bias (PBIAS).

Main Results

• NWM accuracy significantly improves with longer-term forecasts.
• At the monthly scale, 89% of evaluated stations achieved a "Good" classification based on NSE (>0.75), and 85% based on RSR (<0.5).
• A consistent negative bias was observed across all time scales, particularly in underestimating flows.
• Environmental factors such as land use, topography, and soil characteristics influence model performance.
• The NWM's ability to capture flow variability improves at aggregated scales, suggesting its suitability for long-term planning applications despite not incorporating regulated protocols.

Contributions

• Provides a regional evaluation of NWM v2.1 performance in the Alabama Black Belt Region, highlighting its scale-dependent accuracy.
• Identifies systematic biases and the influence of environmental factors on NWM performance.
• Underscores the need for further model structure refinement and regional calibration to enhance predictive reliability for water management.

Funding

Not explicitly stated in the provided text.

Citation

@article{Quansah2025Evaluating,
  author = {Quansah, Joseph E. and Doria, Rubén and Fall, Souleymane},
  title = {Evaluating the Performance of the National Water Model: A Spatiotemporal Analysis of Streamflow Forecasting},
  journal = {Water},
  year = {2025},
  doi = {10.3390/w17202950},
  url = {https://doi.org/10.3390/w17202950}
}