Trend analysis of hydro-meteorological variables using Mann-Kendall and Sen's Slope with Standardization (SSS): Case study of the Kızılırmak catchment, Türkiye
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In recent times, trend analysis has become a focal point and an essential tool across various disciplines, particularly in reaction to the impacts of climate change. As classical methods and regarding the literature, the Mann-Kendall test (MK) and Sen's Slope (SS) are the most widely-used trend methods and hold paramount significance in trend analysis, particularly when studying hydro-meteorological variables over time. MK determines the trend direction, whereas the trend slope is computed with SS. However, they are used without assessing their compatibility and agreement in detail. This research applies Sen's Slope to the Standardized data (SSS) to evaluate the compatibility and agreement between MK and SS methods. Also, this research aims to analyze the temperature and precipitation trends over the K & imath;z & imath;l & imath;rmak catchment in T & uuml;rkiye from 1970 to 2023 using MK, SS, and SSS, as well as presenting the trend maps, including the actual trend maps. The results showed that the SSS approach is closer and compatible with MK than the results obtained by the classical SS. For the whole time period, the most significant temperature increases are observed in the southern part of the catchment, particularly in Kayseri and Develi stations (2.5 degrees C/54 years). Based on a specified confidence level, 15 out of 20 stations across the K & imath;z & imath;l & imath;rmak catchment showed an increasing trend in temperature. For precipitation data, 2 out of 8 stations (K & imath;rs,ehir and K & imath;r & imath;kkale) showed a negative, insignificant slope of approximately 1.1 mm/54 years, while the remaining stations showed a positive, significant, and insignificant slope reaching up to 5.2 mm/54 years. Finally, the practical implications, future recommendations, and different adaptation strategies were proposed based on the obtained results.










