Statistical Analysis of the Effects of Drought, Prediction and Classification in Salahuddin Province

  • Ali Sab

Abstract

      Statistical methods require the availability of climate data for a long period of not less than 30 years and from that data one can calculate the rate and standard deviation and the coefficient of variation and fluctuation ratios and the probability of recurrence of climate phenomena because of their usefulness in climate prediction. The quantitative method is one of the best scientific methods in geographical studies to know the impact of one or more variables on a specific phenomenon or several phenomena.


     In order to reach the scientific accuracy and to determine the effect of climate variables on the occurrence of drought phenomenon, it will be calculated and measured according to the fluctuation coefficient in the amount of rainfall as it is the key factor in determining the character of drought in the region as well as the use of correlation coefficient (Pearson) to know the relationship between the phenomenon of drought and climatic elements (brightness).  The dry years in which the total rainy months of the rainy months are less than the standard deviation is less than half the standard deviation or less, while the year in which rain exceeds this limit is considered a wet year. Attention to regularity in the spatial distribution of rain and without attention to the impact of evaporation / transpiration and then the application of the law of probability of the possibility of future prediction of the occurrence of years of drought and then carry out drought classification in the stations of the study area

Published
Dec 8, 2019
How to Cite
SAB, Ali. Statistical Analysis of the Effects of Drought, Prediction and Classification in Salahuddin Province. Journal of Tikrit university for humanities - مجلة جامعة تكريت للعلوم الانسانية, [S.l.], v. 26, n. 11, p. 253-226, dec. 2019. ISSN 1817-6798. Available at: <https://jtuh.tu.edu.iq/index.php/hum/article/view/871>. Date accessed: 28 apr. 2024. doi: http://dx.doi.org/10.25130/hum.v26i11.871.