Determining Future Precipitation Probability for Kahramanmaras City Using Markov Chain Approach
Year: 2017
Type: article
Abstract: Precipitation is unique source meeting water need of all ecosystems in the world. It is the irreplaceable element of the organism life. Turkey, particularly its Mediterranean region, ranks among the regions expected precipitation changes due to climate change. Kahramanmaras is located in Mediterranean region where is expected to experience the effects of the climate change at the very most. Since Kahramanmaras has the largest water reserve in Turkey, it is acknowledged as a rational way that alterations in the area should be watched consistently and future plans should be made in the light of a set of prediction models. In this study, it is aimed to predict future precipitation probability for Kahramanmaras city using Markov chain model. For this purpose, 44 years precipitation data including 1970-2014 period belonging to Kahramanmaras precipitation station has been used. Precipitation data has been classified by taking SPI (Standardized Precipitation Index) criterions into consideration. In order to test the model accuracy, observed value in 2014 has been compared with predictions of the model for 2014. Then the model is run for 2015, 2016, 2017, 2018, 2019 and 2020 years. When results have been examined, negligible differences have been seen among predictions value for these years. Thus the results of these 6 years are submitted as a single vector. According to this, predicted precipitation amounts and their probability of occurrences are 1079 mm and above with 7%, 990-1078 mm with 5%, 545-900 mm with 74%, 456-544 mm with 12% and 367-455 mm with 2% for 2015, 2016, 2017, 2018, 2019 and 2020 respectively. In addition to this, precipitation amounts are not expected to occur 901-989 mm and 366 mm and below for all these years in Kahramanmaras.
Authors: Mahmut REİS, Hurem DUTAL, Zeynep KAYRAK
Institution: Kahramanmaraş Sütçü İmam University
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2897120425