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The drought monitoring scale plays a crucial role in the assessment and management of drought vulnerability. The quantification of uncertainty across various monitoring scales can aid in strategic planning for drought risk control within the targeted climate. The objective of this research was to develop Prediction Intervals (PIs) for nonlinear Artificial Neural Networks (ANN) models for the Standardized Precipitation Index (SPI) at different scales. The Urmia station in Iran was selected for study due to its climate, which is susceptible to water stress issues. To construct and evaluate the PIs, Lower–Upper Bound Estimation (LUBE) technique was utilized. The results obtained from the SPI models at the Urmia station indicate that the PIs are narrower in 24 months than in other scales, recommended for monitoring meteorological drought at this station. From the results, the propagation risk of meteorological drought through the hydrological cycle in the Urmia climate is a concern.

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Assessing Uncertainty of Drought Risk in an Arid Climate in Iran

  • 会议论文

  • 发表日期：

    2025年

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  • Mina Sayyah-Fard,
  • Vahid Nourani,
  • Sameh Ahmed Kantoush

摘要

The drought monitoring scale plays a crucial role in the assessment and management of drought vulnerability. The quantification of uncertainty across various monitoring scales can aid in strategic planning for drought risk control within the targeted climate. The objective of this research was to develop Prediction Intervals (PIs) for nonlinear Artificial Neural Networks (ANN) models for the Standardized Precipitation Index (SPI) at different scales. The Urmia station in Iran was selected for study due to its climate, which is susceptible to water stress issues. To construct and evaluate the PIs, Lower–Upper Bound Estimation (LUBE) technique was utilized. The results obtained from the SPI models at the Urmia station indicate that the PIs are narrower in 24 months than in other scales, recommended for monitoring meteorological drought at this station. From the results, the propagation risk of meteorological drought through the hydrological cycle in the Urmia climate is a concern.