تحلیل روند پارامترهای اقلیمی استان خوزستان با استفاده از آزمون من کندال(TFPW-MK)

Nowadays, climate change causes abundant worries in different spots in the world. For this reason, a study was conducted to find the trace of this global phenomenon in Khuzestan province. Therefore, we used meteorology data including temperature parameters, rainfall, evapotranspiration and relative humidity for 15 weather stations in a period of 21 years (1996-2016) and Mann Kendal graph to determine the trend. The result illustrates that there is a meaningful downward trend for rainfall parameter in SafiAbad, Hendijan, Masjedsoleiman and Bandar-E-Mahshar with confidence level of 95% and Omidiyeh with confidence level of 99%. Moreover, there is a meaningful upward trend with confidence level of 95% in tempe-rature parameters in most stations, while this level is 99% in Bostan, Hendijan and Izeh. In addition, a meaningful upward trend in evapotranspiration in two station of Bostan and SafiAbad with confidence level of 95% and 99% and a meaningful downward trend with confidence level of 99% for Shushtar, Izeh, Abadan, Masjedsoleiman and Ahwaz as well, is visible. There is a meaningful downward trend in relative humidity in Bostan, SafiAbad, Izeh, Omidiyeh and Masjedsoleiman, which all present the climate change effect in region.
Climate change is one of the most important challenges in the 21st century. Global warming has caused very unstable changes in climate parameters such as: changes in rainfall patterns and frequency and intensity of climate changes. The issue of climate change has become one of the main concerns of scientists related to atmospheric sciences due to its impact on various dimensions of human life and the dependence of human activities on it, and many researchers are trying to understand the various dimensions of this important phenomenon. The change in climatic elements, especially temperature and precipitation, is one of the most important signs of this phenomenon. Changes in temperature and precipitation in different parts of the earth do not follow the same trend, and climate change does not necessarily mean simultaneous changes in precipitation and temperature.
The amount, distribution and temporal and spatial changes of precipitation and temperature are essential factors for decision-making, management, planning and design, especially in areas such as Iran, which is geographically located in the 28 to 48 degree north latitude and It has a dry and semi-arid climate. In order to detect the trend in the time series of water and meteorological variables, various tests are used, and these tests can be divided into two categories, parametric and non-parametric. Parametric tests are more powerful in detecting trends than non-parametric tests, and when using them, the data should be random and have a normal distribution. On the other hand, non-parametric tests can be used if the data is random and are not sensitive to the normality of the data. Mann-Kendall's test is a non-parametric test that is used in researches to investigate the trends of water and meteorological variables.
To carry out this research, climatic data (average rainfall, average evaporation and transpiration, average humidity and temperature parameters) prepared by the meteorological organization of Tehran province for a statistical period of 21 years from 1996 to 2016 have been used. Mann-Kendall test was used to analyze the trend of climatic parameters, which will be explained in detail below.
• Mann-Kendall non-parametric test
This test was first presented in 1945 by "Mann" and then developed by "Kendall" in 1966. This test does not require a normal frequency distribution or linear behavior of the data, and it works very strongly compared to the data that deviates from the linear behavior and is used to evaluate the trend (Darabi et al., 2015). In this test, the null hypothesis (H0) and the opposite hypothesis (H1) are respectively equivalent to no trend and the presence of a trend in the time series of observational data.
Mann-Kendall diagram test:
The steps of the test are briefly as follows:
We rank the data and calculate the ti statistic, which is defined as the ratio of rank I to its previous ranks, and then we obtain the cumulative frequency of the statistic ( ). Mathematical expectation, variance and Mann-Kendall index are calculated based on the following formulas (Zahedi et al., 2016):
In these relationships, ni is the time order of the data. To check the changes, the index Ui' should also be calculated: rank the data and determine the statistic t'i, which is defined as the ratio of rank I to its next ranks, and then calculate the cumulative frequency of t'i we do The mathematical expectation, variance and index Ui' are as follows:
In the above relationships, N is the statistical sample size under study. The intersection of the index Ui and Ui' is a sign of a sudden change in the time behavior of a statistical series. The non-intersection of the curve or their placement within the 95% confidence range does not indicate significant changes in the data, but if the mentioned lines intersect within the critical range of 1.96 and 2.58 and then leave the critical range, it is a sign of a sudden change and a significant trend at the 95% and 99% confidence levels, respectively. If the U curve moves to the positive side, it has a positive trend, otherwise it has a negative trend. Crossings outside the critical range indicate a sudden change in the behavior of the series (Alijani et al., 2009).
In general, the results showed that during the studied statistical period, rainfall in all stations had a decreasing trend. Also, the minimum and maximum temperature parameters have been increasing in most of the stations. The parameters of evaporation and transpiration and relative humidity in most of the stations had a non-significant decreasing trend. Based on the results of Mann-Kandall charts, it was found that Safi Abad, Omidiyeh and Handijan stations were more affected by these changes than other stations. It is obvious that dealing with the effects of climate change and its consequences, such as the increase in the temperature of the earth's surface or the decrease in rainfall, requires a detailed investigation of the causes of this phenomenon and the provision of appropriate solutions in order to prevent endangering food security, increasing soil erosion, desertification and other problems.