Arra et al. (2025) Evaluating Droughts and Trends in Data-Scarce Regions: A Case Study of Palestine Using ERA5, Standardized Precipitation Index, Bias Correction, Classical and Innovative Trend Approaches

Identification

• Journal: Water
• Year: 2025
• Date: 2025-09-20
• Authors: Ahmad Abu Arra, Eyüp Şişman
• DOI: 10.3390/w17182780

Research Groups

• Department of Civil Engineering, Yildiz Technical University, Istanbul, Türkiye
• Department of Civil and Architectural Engineering, An-Najah National University, Nablus, Palestine

Short Summary

This study evaluates temporal and spatial drought characteristics and trends in data-scarce Palestine using bias-corrected ERA5 precipitation data and various trend analysis methods. The research found that bias correction significantly improves ERA5 data accuracy, and while short- and medium-term droughts show no significant trends, long-term droughts (SPI-12) exhibit a significant intensifying trend across the region.

Objective

• To evaluate the performance of ERA5 monthly precipitation data, both raw and bias-corrected, against observational data using statistical metrics and in terms of drought evaluation in data-scarce regions like Palestine.
• To assess drought conditions and characteristics using the Standardized Precipitation Index (SPI) at multiple timescales (1-month, 6-month, and 12-month).
• To apply and compare classical trend analysis methods (Mann–Kendall, Spearman’s Rho, Sen’s Slope) and the Frequency-Innovative Trend Analysis (F-ITA) method to SPI for Palestine using alternative data sources.
• To provide insights for drought management, water policy planning, and climate adaptation in Palestine.

Study Configuration

• Spatial Scale: West Bank, Palestine, covering five meteorological stations (Al-Khalil, Jenin, Jericho, Nablus, Ramallah) and corresponding ERA5 grid points.
• Temporal Scale: ERA5 data from 1940 to 2025; ground-based observations from 2005 to 2021. Drought analysis conducted at 1-month, 6-month, and 12-month timescales.

Methodology and Data

• Models used:
  • Standardized Precipitation Index (SPI) for drought assessment.
  • Linear Scaling (LS) for bias correction.
  • Mann–Kendall (MK) test, Spearman’s Rho, and Sen’s Slope (SS) for classical trend analysis.
  • Frequency-Innovative Trend Analysis (F-ITA) for innovative trend detection and drought classification.
  • Inverse Distance Weighting (IDW) for spatial interpolation.
  • Statistical metrics: Pearson’s Correlation Coefficient (CC), coefficient of determination (R²), Root Mean Squared Error (RMSE), Mean Bias Error (MBE), and Percent Bias (PB) for data evaluation.
• Data sources:
  • ERA5 global atmospheric reanalysis monthly precipitation data (European Centre for Medium-Range Weather Forecasts - ECMWF).
  • Ground-based monthly precipitation observations from the Palestine Meteorological Department (5 stations).

Main Results

• Bias correction significantly improved the accuracy of ERA5 precipitation data, reducing RMSE (e.g., from 57.41 mm to 32.05 mm at Al-Khalil) and eliminating bias (MBE and PB became 0.0%) when compared to observed data.
• Drought durations for short-term (SPI-1) and medium-term (SPI-6) events typically ranged from 4 to 5 months.
• The average drought duration for long-term (SPI-12) events ranged between 14 and 16 months.
• Spatially, eastern regions (Jericho) experienced the longest short-term droughts (up to 4.92 months), while central regions (Ramallah) showed the highest medium-term drought intensity (up to -1.13). Long-term droughts most severely affected northern (Jenin) and central (Ramallah, Jerusalem) regions, with durations up to 15.8 months.
• Classical trend analyses (MK, Spearman, SS) showed no significant trends for short (SPI-1) and medium (SPI-6) timescales.
• All stations exhibited a significant decreasing trend in SPI values at the long timescale (SPI-12), indicating intensifying drought conditions (e.g., Jenin MK Z-statistic = -5.611 at 99% confidence level).
• F-ITA results for SPI-12 confirmed an increasing trend in drought events and a decreasing trend in wet events, with extreme drought classifications increasing (e.g., at Jenin, EXD frequency increased from 0.2% to 0.4%, and ED from 0.4% to 2.18% between the two periods).

Contributions

• First application of bias-corrected ERA5 precipitation data combined with ground-based observations for comprehensive drought assessment in Palestine.
• Development and application of a novel framework integrating ERA5 data, multi-timescale SPI analysis, bias correction, and both classical and innovative trend analysis (F-ITA) for drought evaluation.
• Addresses the critical challenge of data scarcity in developing regions by validating and utilizing reanalysis data for robust drought monitoring.
• Provides detailed insights into the temporal and spatial variability of drought characteristics and trends in Palestine, offering crucial information for water resource management, policy planning, and climate change adaptation strategies.

Funding

This research received no external funding.

Citation

@article{Arra2025Evaluating,
  author = {Arra, Ahmad Abu and Şişman, Eyüp},
  title = {Evaluating Droughts and Trends in Data-Scarce Regions: A Case Study of Palestine Using ERA5, Standardized Precipitation Index, Bias Correction, Classical and Innovative Trend Approaches},
  journal = {Water},
  year = {2025},
  doi = {10.3390/w17182780},
  url = {https://doi.org/10.3390/w17182780}
}