Javadi et al. (2025) Analysis of historical global warming impacts on climatological trends for the partially gauged Hirmand river basin based on multiple data products and bias correction methods

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2025
• Date: 2025-10-30
• Authors: M R Javadi, Mostafa Jalilehvand, Hosein Alizadeh, Nima Zafarmomen
• DOI: 10.1016/j.ejrh.2025.102886

Research Groups

• School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

Short Summary

This study evaluated and bias-corrected global climate datasets (CRU, ERA5, GLDAS) for the Hirmand River Basin (1960-2022) using Quantile Delta Mapping (QDM) and Bidirectional Long Short-Term Memory (Bi-LSTM), revealing no significant trends in precipitation or maximum temperature but a significant 4.3 °C increase in minimum temperature over 63 years.

Objective

• To evaluate and bias-correct global precipitation and temperature datasets (CRU, ERA5, GLDAS) for the Hirmand River Basin (1960-2022) using Quantile Delta Mapping (QDM) and Bidirectional Long Short-Term Memory (Bi-LSTM), and subsequently analyze long-term seasonal and annual trends in these climatic variables.

Study Configuration

• Spatial Scale: Hirmand (Helmand) River Basin (HRB), an international transboundary basin shared by Afghanistan, Iran, and Pakistan, covering approximately 400,000 square kilometers.
• Temporal Scale: Long-term period from 1960 to 2022 (63 years).

Methodology and Data

• Models used:
  • Bias Correction: Quantile Delta Mapping (QDM), Bidirectional Long Short-Term Memory (Bi-LSTM)
  • Interpolation: Inverse Distance Weighting (IDW)
  • Trend Analysis: Mann-Kendall (MK) test, Theil-Sen’s slope estimator
  • Evaluation Metrics: Percent BIAS (PBIAS), Nash-Sutcliffe Efficiency (NSE), Root Mean Squared Error (RMSE), Kling-Gupta Efficiency (KGE)
• Data sources:
  • Observational: Monthly records from 89 climatological stations (80 from Afghanistan via NOAA for 1960-1980, 9 from Iran for 1960-2022).
  • Global Gridded/Reanalysis: Climate Research Unit (CRU v4.02), ECMWF Reanalysis v5 (ERA5), Global Land Data Assimilation System (GLDAS).

Main Results

• Uncorrected Data Performance: CRU demonstrated the best performance for precipitation, while GLDAS showed superior performance for both maximum and minimum temperature data among the raw datasets.
• Bias Correction Effectiveness: Bias correction significantly improved all datasets across evaluation metrics (PBIAS, NSE, RMSE, KGE). Bi-LSTM achieved the highest accuracy for precipitation, while QDM achieved the highest accuracy for temperature (both maximum and minimum).
• Seasonal Trend Analysis:
  • Uncorrected and QDM-corrected precipitation data showed no significant trends in winter, spring, or autumn, but an increasing trend in summer. DL correction was found to alter seasonal precipitation trends.
  • ERA5 maximum temperature showed no significant trend in winter, spring, and autumn, but an increasing trend in summer. GLDAS maximum temperature showed a decreasing trend in most sub-basins across three seasons.
  • Minimum temperature exhibited a strong increasing trend across all seasons for all products (uncorrected and corrected) with a 99% confidence level.
• Annual Trend Analysis (Combined Datasets):
  • Precipitation: No statistically significant increasing or decreasing trend was observed across all sub-basins (ZMK values < 1.96). Theil-Sen’s slope indicated a weak, consistent downward tendency, ranging from -0.03 to -0.53 millimeters per year.
  • Maximum Temperature: No significant trend was found in most parts of HRB, except for a statistically significant decreasing trend in the Farah sub-basin (-0.02 °C per year).
  • Minimum Temperature: A significant and pronounced increasing trend was observed throughout the entire HRB (ZMK > 2.56, 99% confidence level). The average rise was approximately 4.3 °C over the 63-year study period, with an average Theil-Sen’s slope of +0.07 °C per year.

Contributions

• First comprehensive bias correction study of global precipitation and temperature data products in the entire Hirmand River Basin (HRB), integrating observational data from both Afghanistan and Iran.
• Detailed evaluation of CRU, ERA5, and GLDAS products for both precipitation and temperature, addressing data scarcity in a transboundary basin.
• Comparative analysis of advanced bias correction methods (QDM and Bi-LSTM), highlighting their trade-offs between predictive accuracy and trend preservation for different climatic variables.
• Conducted a thorough climatological trend analysis (1960-2022) across the entire HRB using combined ground-based and corrected global data, overcoming limitations of previous studies focused on sub-regions or single data sources.
• Provides crucial insights into the evolving climate of the HRB, particularly the significant warming trend in minimum temperatures, which is vital for developing adaptive transboundary water management strategies.

Funding

• Not explicitly mentioned in the provided text.

Citation

@article{Javadi2025Analysis,
  author = {Javadi, M R and Jalilehvand, Mostafa and Alizadeh, Hosein and Zafarmomen, Nima},
  title = {Analysis of historical global warming impacts on climatological trends for the partially gauged Hirmand river basin based on multiple data products and bias correction methods},
  journal = {Journal of Hydrology Regional Studies},
  year = {2025},
  doi = {10.1016/j.ejrh.2025.102886},
  url = {https://doi.org/10.1016/j.ejrh.2025.102886}
}