Investigating drought trends with new and traditional drought indices using innovative trend analysis (ITA): A case of Seyhan, Ceyhan, and Asi River Basins, T�rkiye

Accurate monitoring of drought conditions requires the use of quantitative indices that capture the variability of precipitation and other climatic parameters. The development and comparison of such indices provide valuable insights for both scientific understanding and practical applications in drought management. This study investigated historical drought trends in T & uuml;rkiye's Seyhan, Ceyhan, and Asi River basins by employing indices such as Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Discrepancy Precipitation Index (DPI), and New Drought Index (NDI). Given the growing importance of understanding drought dynamics, these indices were selected to ensure a comprehensive evaluation by incorporating distinct climatic parameters such as precipitation, evapotranspiration, and temperature. 13 meteorological stations were examined to ensure data reliability and accuracy for the years 1970 to 2021. The drought indices were calculated, and their temporal trends were analyzed using the Innovative Trend Analysis (ITA) method. The 52-year dataset was divided into three distinct periods for detailed trend evaluation. Partitioning the 52-year record for ITA revealed widespread negative NDI trends in the third period (nearly all stations) with a persistent wetting signal at Karata & scedil;, while RDI declines were pronounced at Karaisal & imath; and Kahramanmara & scedil;. Correlation analyses revealed that SPI and RDI showed strong alignment due to their common reliance on precipitation data. In contrast, NDI, which includes temperature as a parameter, exhibited broader sensitivity, indicating its ability to detect extreme wet and drought periods more effectively. Findings highlighted significant spatial and temporal variability in drought conditions. Across 13 stations (1970-2021), all four indices converged on the same extreme years, six wet (1976, 1981, 1987, 1988, 1997, 2009) and six dry (1989, 1990, 1993, 2013, 2017, 2020), demonstrating cross-index consistency in event detection. Overall, the study underscores the critical need for employing multiple drought indices to capture complex climatic dynamics accurately. It also emphasizes the utility of integrating newly developed indices like DPI and NDI into drought monitoring frameworks. The findings suggest that future drought management strategies should consider index-specific sensitivities and regional climatic characteristics for precise drought assessments.