عنوان مقاله [English]
In Iran, precipitation is one of the key variables for assessing the potential of water resources access. But because the spatial distribution of this variable is very uneven, the distribution of water resources of the country is not uniform. The maintenance and management of water resources, while also being a function of rainfall, depends on the variability of precipitation. The smaller the spatial variation of the rainfall, the greater the homogeneity and consistency of water resources. On the other hand, the less variability of rainfall is, the more water resources will be more stable and water supply will be possible. For this reason, the variability of rainfall time in the assessment of water resources, watersheds and the relative study of local and regional water resources is important.
materials and methods
The data used in this study are available statistics for 60 years of daily precipitation of the synoptic station of Tabriz from 1951 to 2010, which was obtained from the Meteorological Office of East Azarbaijan Province. For accuracy raising the modeling stage, data is considered weekly. The most commonly used model used to show the time series of discrete random variables is known as the Markov chain. Examining these uncertain or random modes and selecting the model is the probability knowledge. In this research, it is attempted to use this knowledge and based on the Markov chain method, the probability of rainfall occurrence in Tabriz city is obtained.
Results and discussion
The distribution of rainfall during the year can have a large impact on water and agriculture planning. Considering the fact that Iran is located in the dry world belt and most of its regions have dry and semi-arid climates, and agriculture in these areas It is also based on this climate. Changes in rainfall can cause irreparable damage to the agriculture and water resources of these areas. Therefore, recognizing its system of changes can be a great help in this regard. The number of rainfall days is an appropriate criterion for assessing the distribution of rainfall. The average rainfall days in Tabriz average 80 days per year. An average of 30 days was observed in the spring, 5 days in the summer, 19 days in the fall and 26 days in winter.
The study of state change matrix shows that during the statistical period (1951-2010), from the total of 21960 days of the studied statistics, 14649 days of change from dry day to the next dry day and 2519 days of change in the rainy day, which after dry day It happened. Also, the transformation matrix from rainy day to dry day is 2520 days and rainy day to rainy is 2272 days. The results of the X2 test indicate that the data are not independent and there is enough confidence to adhere to the daily precipitation data of Tabriz station from the Markov ranking model. The results of the trend test using Spearman correlation method at 95% confidence level indicate that the data are not trendy and validated by the approved chain. The results of the fitted final model showed that the probability of changing the order of the rainy day to the other rainy days has a higher percentage than the change from rainy day to dry, and this state is in the weeks leading to the spring and autumn seasons, More than other weeks.