Calculation of Drought Index SPI for Hydrological Analysis

The following MATLAB code implements the Standardized Precipitation Index (SPI) calculation for hydrological drought analysis. This implementation supports multiple time scales and features probability distribution fitting using gamma distribution for precipitation data normalization. The algorithm follows the standard SPI methodology: data preprocessing, parameter estimation, cumulative probability calculation, and inverse normal transformation. Key functions include data validation, rolling window aggregation for different time scales, maximum likelihood estimation for gamma distribution parameters, and Z-score transformation. The code structure ensures computational efficiency with vectorized operations and includes error handling for missing data. To utilize this code: 1. Launch MATLAB software 2. Create a new M-file in the MATLAB editor 3. Copy and paste the complete code into the M-file 4. Execute the script with your precipitation dataset as input The implementation includes detailed inline comments explaining each computational step, parameter definitions, and mathematical transformations. For optimal performance, ensure input data follows consistent temporal formatting and contains no irregular gaps. This resource provides hydrological researchers with a robust tool for drought assessment across various temporal resolutions. For technical support or clarification regarding the statistical methods employed, please contact our technical team.