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<p>This study evaluated the performance of three evapotranspiration models, namely, Awhari1, Thornthwaite, and Hargreaves, in assessing drought frequency (DF), using the Penman–Monteith (PM) model as the reference. Fifth Generation European Centre for Medium-Range Weather Forecasts (ERA5-Land) dataset, with a spatial resolution of 0.1° × 0.1°, was used to calculate monthly potential evapotranspiration (PET) for the reference period (1950–2022). The Standardized Precipitation-Evapotranspiration Index (SPEI) was computed at 1-, 3-, 6-, 9-, and 12-month time scales to identify moderate, severe, and extreme drought scenarios for each model. The spatial distribution patterns of DF were analyzed. Results indicate that the Awhari1 model outperforms the Thornthwaite and Hargreaves models across all time scales. The performance metrics of the newly developed model show a Kling-Gupta Efficiency (KGE) of (0.61 to 0.89), Nash–Sutcliffe Efficiency (NSE) (-0.08 to 0.56), percentage bias (PBIAS) (-26 to 19), and Normalized Root Mean Square Error (NRMSE) (69.70 and 103.9) across various SPEI time scales and scenarios. In this study, we demonstrate that the Awhari model successfully replicates the PM using maximum temperature (Tmax) and relative humidity (RH) as input variables. These findings highlight the critical importance of validating PET models before applying them in drought analysis to ensure accuracy and reliability.</p>

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Assessing the efficacy of simplified temperature-based PET models in replicating penman–monteith drought frequency

  • 期刊论文

  • 发表日期：

    2025年5月5日

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  • Dauda Pius Awhari,
  • Mohamad Hidayat Bin Jamal,
  • Mohd Khairul Idlan Bin Muhammad,
  • Mohammed Abdu Nasara,
  • Najeebullah Khan,
  • Zulfaqar Sa’adi,
  • Mohammed Khalid Othman,
  • Shamsuddin Shahid

摘要

This study evaluated the performance of three evapotranspiration models, namely, Awhari1, Thornthwaite, and Hargreaves, in assessing drought frequency (DF), using the Penman–Monteith (PM) model as the reference. Fifth Generation European Centre for Medium-Range Weather Forecasts (ERA5-Land) dataset, with a spatial resolution of 0.1° × 0.1°, was used to calculate monthly potential evapotranspiration (PET) for the reference period (1950–2022). The Standardized Precipitation-Evapotranspiration Index (SPEI) was computed at 1-, 3-, 6-, 9-, and 12-month time scales to identify moderate, severe, and extreme drought scenarios for each model. The spatial distribution patterns of DF were analyzed. Results indicate that the Awhari1 model outperforms the Thornthwaite and Hargreaves models across all time scales. The performance metrics of the newly developed model show a Kling-Gupta Efficiency (KGE) of (0.61 to 0.89), Nash–Sutcliffe Efficiency (NSE) (-0.08 to 0.56), percentage bias (PBIAS) (-26 to 19), and Normalized Root Mean Square Error (NRMSE) (69.70 and 103.9) across various SPEI time scales and scenarios. In this study, we demonstrate that the Awhari model successfully replicates the PM using maximum temperature (Tmax) and relative humidity (RH) as input variables. These findings highlight the critical importance of validating PET models before applying them in drought analysis to ensure accuracy and reliability.