The Analysis and Prediction of Short-term Drought by Using of Markov Chain and SPI Method in Golestan Province

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Introduction

Due to the growing trend of climate change in recent years and the occurrence of accident-causing events such as glaciation, storms, hail, drought, etc., the need for more analysis and forecasting of this type of climate-causing hazards is felt.Since Golestan province is one of the agricultural hubs and there are many forests and pastures in it, managers, farmers, and ranchers must anticipate the occurrence of droughts to reduce possible losses during accidents and disasters. Therefore, in this research study, by selecting different stations and distributing the appropriate location in the selection of stations from the data of synoptic stations and rain gauges, evaporators using common annual data 1979-2008 AD and 56-57-85-86 to analyze and predict drought paid.

Materials and Methods

The research place of Golestan province with geographical coordinates is 37.2898 ° N, 55.1376 ° E. In this research, in the first stage, 6 stations from meteorological stations of Golestan province (Gorgan, Gonbad, Bandar-e-Turkmen, Aq Qala, Kalaleh, Aq Togha) were selected with 36-year annual data. Precipitation data lacked independence and homogeneity of data. Thyer (2000) notes in his research that it takes at least 120 years to simulate the annual rainfall of an area using the Markov chain. Thyer et al. (2006)To continue from Hashemabad Semioptic Station of Gorgan and Gonbad with statistical years (1979-2008) 30 years old and Evaporation and Rain Metering stations of Maravatpeh, Tangarah, Tamar, Til Abad, Araz Kuseh, Tarshkoli, Incheh Borun, and Ghaffarhaji with statistical years (2005-2006 to 1977-1978) 30 years selected and quarterly data collected with the calculation of 4 seasons and 30 years of data reaches a total of 120 cases.

Findings

In these stations, in the whole studied period, there were 1200, 566 wet seasons, and 634 dry seasons, which indicates the increase of droughts.According to the probability transfer matrix of the first order of the studied stations, the highest wetting limit is related to Hashemabad Gorgan station with a stability of 64% and the lowest limit is related to Tilabad station with a stability of 39%.probability matrices such as hashem abad gorgan in winter are expected to have p00 means that the probability occrunce of a dry month After a dry month, 56% and the probability of occurrence of p11 means a probability of occurrence of a wet month after a wet month is 53%. P10 means a 47% probability of occurrence of a wet month after a dry month and p01 means a 46% probability of occurrence of a dry mouth after a wet month which is the lowest probability of occurrence.

Results

1- According to the 30 years studied, the dry season occurred 634 times and the wet season 566 times, indicating an increase in drought periods and that its durability has also increased.2- There has been a long period of drought in Gorgan station since 2005. There was only one wet season in winter 2006, i.e. during the last 14 seasons, it was only one wet season. In this period, the most severe drought with SPI 3- index (extremely dry) is unprecedented in the studied stations. Has occurred.3- In Gonbad station, like Gorgan station, a drought trend has been observed since 2005. During the last 14 seasons, only 4 seasons have been wet and the highest level of drought occurred in this period has reached close to SPI 2- (extremely dry).Results of transfer probability matrices1- In all studied stations, P00 (probability of occurrence of a dry season after a dry season) is above 50% except (Til Abad), the highest of which is related to Hashem Abad station in Gorgan with a probability of 66%. This shows. The duration of droughts in the province is long.2- In Maraveh Tappeh, Tangarah, Tamar, Tilabad, Arazkuseh, Tarshkoli, Incheh Borun, Ghaffarhaji, Gorgan, and Gonbad P01 stations (probability of occurrence of a dry season after a wet season) 42, 50, 47, 51, 44, 47, 41, 48, 34, 52, percent, most of which are related to Gonbad station and the least of which is related to Hashemabad station in Gorgan.3- The percentage of drought in Gonbad station is higher than other stations. In Maraveh Tappeh, Tangarah, Tamar, Til Abad, Arazkuseh, Tarshkoli, Incheh Borun, Ghaffarhaji, Gorgan, and Gonbad stations, the probability of P10 occurrence (ie the probability of occurrence of a wet season after a dry season) is 55-51, 60-54.5, respectively. 55-54,61-5,52-47, 55-54, 52-45, 53-52, 51-36, 54-51, the highest percentage is related to Tilabad station with 61% and the lowest is related to Gorgan station with 36%.4- The highest percentage of P11 (probability of occurrence of a wet season after a wet season) is related to Hashemabad station with 64% and the lowest is in Tilabad station with 39%

Conclusion

Because winter has the wettest season and the highest frequency of wet season, but in some years dry season has occurred continuously in most stations in this season, for example in Gorgan station, the most severe continuous drought occurred in winter 2006 with an index of -98-98 It has been found that it is unprecedented during the study period. If winter is the wettest season and the highest frequency of the wet season in the whole province, it seems that this type of change is due to climate change, which needs further investigation.According to the studies and the results of drought analysis in Golestan province, it shows that the length of dry periods has increased, which is in full accordance with the findings of Daneshmand and Mahmoudi (2017). And that the duration of droughts has increased since 2000 and the highest intensity of droughts has occurred in the years 2000-2008 and since 1979-80, so that since 2005 in Gorgan, Gonbad, and Ghaffar Haji stations is more intense and long.Since the minimum drought period is more than one year and the maximum is more than 5 years, the droughts in the province are increasing and changing, and this can pose many risks to the agricultural sector and water resources.

Language:
Persian
Published:
Journal of Climate Research, Volume:12 Issue: 46, 2021
Pages:
73 to 88
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