Throughout the geological history of the earth, there have been many climate changes due to natural and external factors. In the past, the changes in climate were caused by natural causes, and today it is primarily caused by human activities. Besides being different climate types, Turkey is among countries that will be affected by climate change induced by global warming. Climate changes in the regions will be affected differently and degrees due to the country’s surroundings by seas, fragmented topography and orographic features. Trend analysis methods are used in many areas such as on various engineering, agriculture, environmental and water resources, especially in climate change impact studies resulting from global warming. When data are analyzed with classical trend analysis methods, forward-looking predictions are generally made as low, medium, high, decreasing and increasing. However, risk classes showing changes between available data sets are not known. Innovative Trend Pivot Analysis Method (ITPAM) determines risk classes by establishing a relationship between data. Furthermore, in this method, increasing and decreasing trend regions are separated into five classes more clearly than classical/traditional trend methods. In this study, Susurluk Basin’s total monthly precipitation data (2006–2017) were analyzed by using ITPAM which the newest trend method. When arithmetic mean analysis results are examined, a significant change is observed between first data set and second data set at two stations (Bandirma and Uludag). When examined at other stations, it is observed that at least one month of almost every station is in 1st degree risk group. When standard deviation analysis results of each station are examined, a significant change is observed between first data set and second data set at many stations. Because while trend class of a point in developed IPTA graph is the medium degree, this point is in 1st risk class in the risk graph.

在地球的整个地质历史中，由于自然和外部因素，已经发生了许多气候变化。过去，气候变化是自然原因引起的，而今天它主要是由人类活动引起的。除了是不同的气候类型，土耳其还是受全球变暖引发的气候变化影响的国家之一。由于该国的周围环境受到海洋，地形分散和地形特征的影响，因此该地区的气候变化将受到不同程度的影响。趋势分析方法用于许多领域，例如各种工程，农业，环境和水资源，尤其是在全球变暖导致的气候变化影响研究中。当使用经典趋势分析方法对数据进行分析时，前瞻性预测通常会比较低，中，高，递减和递增。但是，尚不清楚显示可用数据集之间的变化的风险类别。创新的趋势枢轴分析方法（ITPAM）通过建立数据之间的关系来确定风险类别。此外，在这种方法中，与传统/传统趋势方法相比，将趋势区域的增加和减少趋势更清楚地分为五个类别。在本研究中，使用最新趋势方法ITPAM对苏苏鲁克盆地的月降水总量（2006-2017年）进行了分析。当检查算术平均分析结果时，在两个站点（班迪尔玛和乌鲁达）的第一个数据集和第二个数据集之间观察到了显着变化。在其他站点进行检查时，观察到几乎每个站点中至少有一个月属于1级风险组。当检查每个站点的标准偏差分析结果时，在许多站点的第一数据集和第二数据集之间观察到了显着变化。因为在已开发的IPTA图中某点的趋势类别为中等程度，所以该点在风险图中属于第一风险类别。