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Showing 5 results for Standardized Precipitation Index

M. Nouri, M. Homaee, M. Bannayan,
Volume 22, Issue 1 (6-2018)
Abstract

In this study, the trends of changes of the standardized precipitation index in a 12-month timescale (SPI-12) and seasonal and annual precipitation were investigated in 21 humid and semi-arid stations of Iran during the 1976-2014 time period. After removing the serial correlation of some series, the trend of precipitation and SPI-12 was detected using the Mann-Kendall nonparametric trend test. The results revealed that the trends of annual precipitation had been declining in all stations over the past 39 years.  The seasonal precipitation trend in winter, spring, autumn and summer was downward in approximately 90, 95, 47 and 37% of the studied stations, respectively. In addition, the descending trend of wintertime precipitation was significant in Sanandaj, Khoy, Urmia, Hamedan, Mashhad, Torbat-e-heydarieh, Nozheh and Qazvin. Also, the temporal trend of SPI-12 was decreasing in all surveyed stations except Shahrekord. Furthermore, SPI-12 showed a significant downward trend only in Sanandaj and Fasa. Moreover, the most severe meteorological drought occurred in the period 1999-2000, in Ramsar, Urmia and Hamedan, and in the period 2008-2009, in Tabriz, Sanandaj, Shiraz, Fasa, Qazvin, Mashhad, Torbat-e-heydarieh, Shahrekord, Gorgan and Kermanshah stations. Overall, the results of this study indicated that the trend of precipitation in most studied sites, particularly in semi-arid parts of the northeast and southwest of Iran, has changed due to the severe and long metrological drought that has occurred in the recent decade (2005-2015).
 


S. Ekhtiary Khajeh, F. Negahban, Y. Dinpashoh,
Volume 23, Issue 2 (9-2019)
Abstract

In this study, drought characteristics of Arak, Bandar Anzali, Tabriz, Tehran, Rasht, Zahedan, Shiraz and Kerman stations during the statistical period of 1956 to 2015 were studied by Reconnaissance Drought Index (RDI) and Standardized Precipitation Index. Precipitation and temperature data were needed to calculate RDI. Precipitation data was also required to estimate SPI. In this study, Drinc software was used to calculate RDI, SPI and potential evapotranspiration (PET). The software calculated PET by the Thornthwaite method. One of the main challenges in drought monitoring is to determine the indicator that has a high reliability based on its monitoring purpose. Therefore, in this research, two methods used for selecting the appropriate index based on the minimum rainfall and normal distribution were evaluated. The results of the evaluation of the minimum rainfall method for selecting the appropriate index showed that most drought indices with the occurrence of minimum rainfall level indicated severe or very severe drought situations; in most cases, it could not lead to selecting an exact and unique index. Based on the results of the normal distribution method for the stations of Arak, Tabriz, Rasht, Zahedan, Shiraz and Kerman, SPI index, and for the stations of Bandar Anzali and Tehran, RDI index were selected as the most appropriate ones.

E. Soheili, H. Malekinezhad, M. R. Ekhtesasi,
Volume 23, Issue 4 (12-2019)
Abstract

The Kor River in Fars province supplies an important part of water requirement in the Doroodzan dam basin and its surrounding area. In this study, the meteorological and hydrological droughts of this area were investigated in the last four decades. For this purpose, the temporal and spatial trend variability of the stream flow was investigated in monthly, seasonal, and annual time scales in the 6 selected stations. The trends of Standardized Precipitation Index SPI, as the drought index, in the 5 selected stations were also studied by the modified Mann-Kendall method. The results indicated that the trend in the stream flow was decreasing in all time scales. Significant downward trends were observed at 95% confidence level on monthly, annual and monthly time scales, especially in the warm months from May to September. These significant downward trends were located spatially in the stations located near the agriculture area, in the middle part of the basin. The significant upward trend existed only at the Doroodzan dam station, at the outlet in the area and in the warm months of the year. In the case of the SPI index, trends were  decreasing in all time scales and were  significant only at 2 stations in the long-term periods, 9, 12, and 18 months, at 95% confidence level. The results, therefore, indicated the occurrence of severe droughts (SPI<-2) during 1982-83 and 2007-8 periods.

F. Saniesales, S. Soltani, R. Modarres,
Volume 25, Issue 2 (9-2021)
Abstract

Several indices are used for drought identification and quantification. In this paper, the new Standardized Palmer Drought index (SPDI) was introduced and then the drought condition of Chaharmahal-Va-Bakhtiari Province was studied using this index. For this study, 11 synoptic, climatology, and evaporation meteorology stations were selected. Essential information in this investigation includes monthly temperature, monthly precipitation, and soil moisture measurement. To estimate SPDI, moisture departure, was first calculated on a monthly time scale. Then, converted to cumulative moisture departure values in different time scales including 3, 6, 9, 12, and 24 months. The best statistical distribution (GEV) was then fitted to cumulative departure. These values were then standardized to have the SPDI. The results showed that, as soil moisture affects SPDI estimation, it will be more valid for analyzing and monitoring drought conditions, especially for agricultural drought. Also, the results showed that 2000, 2001, and 2008 years were the driest time in this Province from 1988 to 2012. Moreover, drought frequency was found out in the western half of the Province more than in the other parts.

S. Banihashemi , S. S. Eslamian, B. Nazari,
Volume 25, Issue 2 (9-2021)
Abstract

The upcoming climate change has become a serious concern for the human society. These changes, caused and aggravated by the industrial activities of the international community and the increase in the concentration of greenhouse gases in the atmosphere, are seen as a threat to the food security and environment. Temperature change and precipitation are studied in the form of different probabilistic scenarios in order to have an outlook for the future. The present study was conducted to address the effects of climate changes on temperature and precipitation in Qazvin plain in the form of five AOGCMs including Hadcm3, CSIRO-MK3, GFDL, CGCM3 and MICROC3.2, and 3 greenhouse gas emission scenarios of A1B, A2 and B1, based on different possible scenario combinations in the next 30 years, 2021-2050 and 2051-2080 (near and far future). On basis of the study results, all 4 target stations, on average, will have experienced a change between two ratios of 0.5 and 1.4 of  the observed precipitation period  by the end of 2050, and the mean temperature will have had a change  between -0.1 to 1.6 °C, relative to the observed period.  By the end of 2080,  the  precipitation will also have fluctuated between the two proportions of 0.5 and 1.7 times of the observed precipitation period and the mean temperature will touch an increase between 0.6 and 2.6 °C. Both SPI and SPEI indices suggest the increment in the number of dry periods in the near and far future. However, the total number of negative sequences differed considering the 3, 12 and 24-month intervals at the stations level. Given the SPEI index, as compared to the base period, the total negative sequences of drought and number of dry periods will increase at 3 stations of Avaj, Bagh-Kowsar and Shahid-rajaei-powerhouse and decrease at Qazvin station in the future; however, SPI gives different results, such that  for Bagh-Kowsar, there will be an increase in both total negative sequences of drought and number of dry periods, as  compared to the baseline period; three other stations will have more dry periods, specifically, but less total negative sequences. The results reported that the drought events would become severe, and the wet events would become extreme in the future.


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