The variation in climate extremes at different spatial and temporal scales can be conceived as an important indicator of climate change. The focus of this study is to reveal linear trends and observe space-time (ST) variation in extreme climate indices over the Euphrates Basin in Turkey. Extreme climate indices are calculated using daily maximum, minimum, and mean temperatures, including observations of daily precipitation measured from 41 meteorological stations from 1970 to 2017. Three precipitation indices, consecutive dry days (CDD), consecutive wet days (CWD), and precipitation intensity (SDII), together with three temperature indices, number of summer days (SU), number of frost days (FD), and growing season length (GSL), are analysed. Linear trends in these extreme indices are examined using the Mann-Kendall test. The ST distribution and variation in climate indices are examined through prediction maps for this study period. Ordinary kriging (OK), which has proven to be accurate and reliable in many studies, is used to obtain prediction maps on ST framework. Results indicated that there is an evident trend in the temperature-related indices. Regarding SU and GSL, about 66% and 34% of all stations, respectively, show a significant increasing trend. The downward trend (negative Z statistic) for the FD is observed at approximately 83% of all meteorological stations, of which 35% show a significant trend. The ST variation in temperature-related extremes is evident from prediction maps; the trend is not as dominant for precipitation-related indices. In terms of ST prediction maps, the most prominent variation is observed in the south and northeast parts of the basin in CDD and CWD prediction maps from 2013 to 2017.

不同时空尺度上极端气候的变化可以被认为是气候变化的重要指标。这项研究的重点是揭示土耳其幼发拉底河流域的线性趋势并观察极端气候指数的时空变化。极端气候指数是使用每日最高，最低和平均温度计算得出的，包括从1970年到2017年从41个气象站测得的每日降水观测值。三个降水指数，连续的干旱天（CDD），连续的潮湿天（CWD）和降水分析强度（SDII），以及三个温度指数，夏季天数（SU），霜冻天数（FD）和生长季节长度（GSL）。使用Mann-Kendall检验检查了这些极端指数中的线性趋势。通过本研究期的预测图检查了气候指数的ST分布和变化。普通克里金法（OK）已在许多研究中被证明是准确和可靠的，用于获取ST框架上的预测图。结果表明，温度相关指数有明显的趋势。关于SU和GSL，分别占所有台站的66％和34％，显示出明显的增长趋势。下降趋势（负 显示出明显的增长趋势。下降趋势（负 显示出明显的增长趋势。下降趋势（负在所有气象站中约有83％观测到FD的Z统计量，其中35％表现出显着趋势。与温度相关的极端情况下，ST的变化可以从预测图中看出。这种趋势在与降水有关的指数中并不占主导地位。就ST预测图而言，在2013年至2017年的CDD和CWD预测图中，盆地南部和东北部的变化最为明显。