EVALUATING GRID-POINT SELECTION PROCESS FOR ACCURATE STANDARDIZED PRECIPITATION INDEX (SPI) CALCULATION

II. International BRITISH Congress on Interdisciplinary Scientific Research & Practices, London, İngiltere, 24 - 26 Ocak 2025, ss.462, (Özet Bildiri)

The accuracy of gridded precipitation datasets, which can be satellite and reanalysis data, is crucial for

hydrological and meteorological applications. These datasets are used to estimate drought indices such

as the Standardized Precipitation Index (SPI), especially for data scarcity regions. This study

investigates the impact of different grid-point selection methods on the accuracy of SPI calculations by

comparing gridded precipitation data with station-based observations. Three scenarios for grid-point

selection were examined: (1) the nearest grid point to the station, (2) the average of the nearest four grid

points, and (3) the average of the nearest six grid points. Precipitation data were extracted for each

scenario and used to calculate SPI values using the ERA5-LAND data source for Kocaeli province.

These values were then compared to the SPI calculated directly from station observations to evaluate

the performance and suitability of each method. Statistical metrics were used to quantify the differences,

including correlation coefficient (CC), root mean square error (RMSE), and bias. The results provide

insights into the optimal grid-point selection strategy for gridded precipitation datasets to enhance the

reliability of SPI calculations, offering practical recommendations for their use in drought monitoring

and water resource management.