Drought risk probabilistic models based on extreme value theory.

Area of Science:

• Environmental Science
• Hydrology
• Climatology

Background:

• Drought risk quantification is crucial for water resource management and climate change adaptation.
• Existing methods may lack the probabilistic rigor for accurate risk assessment.
• Generalized distribution functions and the standardized precipitation index offer potential for advanced drought analysis.

Purpose of the Study:

• To develop and present original, probabilistic models for drought risk quantification.
• To apply these models to assess drought risk in specific regions.
• To introduce an innovative methodology for drought risk assessment.

Main Methods:

• Utilized generalized distribution functions for extreme value analysis.
• Employed the standardized precipitation index (SPI) for drought characterization.
• Applied probabilistic modeling to quantify drought risk over defined periods.

Main Results:

• Developed novel probabilistic models for drought risk quantification.
• Calculated probabilistic drought risk levels for three case study regions in Poland.
• Demonstrated the application of the models across four 5-year periods for each region.

Conclusions:

• The presented probabilistic models offer an innovative approach to drought risk quantification.
• The methodology is adaptable for creating drought risk indexes in diverse climatic regions.
• The study provides a robust framework for assessing and managing drought risk.