تحلیل بارش های روزانه تبریز جهت بررسی احتمال تواتر و تداوم روزهای خشک و مرطوب

یکی از مهم ترین عوامل موثر در مدیریت صحیح منابع آب، شناخت دقیق احتمالات رخ داد بارش و نحوه توزیع روزهای متوالی خشک و بارانی است. چنین شناختی می تواند زمینه های مناسبی برای برنامه ریزان در جهت مقابله با اثرات مخرب خشکسالی ها و نوسانات شدید بارش ارائه دهد. در این پژوهش با استفاده ازداده های مربوط به بارش های روزانه تبریز در یک دوره آماری 60 ساله(1951 -2010) که از اداره کل هواشناسی استان آذربایجان شرقی دریافت گردید، با استفاده از قوانین احتمال، به صورت فرآیندهای تصادفی و با استفاده از  مدل زنجیره های مارکوف، احتمال تداوم و تواتر روزهای بارش و خشکی، احتمال وقوع بارش و احتمال مقدار بارش، دوره برگشت و احتمال تداوم خشکی های 3، 4، 5، 6 و 7 روزه برای تمام روزهای سال در قالب هفتگی محاسبه و مورد تحلیل قرار گردید. در این بررسی احتمال وقوع بارش هفتگی 22 درصد و احتمال عدم وقوع بارش 78 درصد بدست آمد. نتایج حاصل از محاسبه ماتریس تغییر وضعیت برای روزهای مختلف سال در قالب هفته ای نشان می دهد که در مجموع 17168 روز، روز خشک و4792روز بارندگی وجود داشته است. به عنوان نمونه طی 119 روز آمار موجود از اولین هفته فروردین در این دوره 60 ساله 191 روز، روزهای خشکی است که بعد از روز خشک رخ داده است. بالاترین احتمال وقوع بارش در فصل بهار و هفته با 46 درصد می باشد و خشکی های 7 روزه دارای کمترین احتمال تداوم برای تمام هفته های سال بدست آمد.

Analysis of daily rainfall in Tabriz to study the probability of frequencies and the persistence of dry and wet days

Introduction 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 semiarid 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.   Conclusion The study of state change matrix shows that during the statistical period (19512010), 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.