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Showing 2 results for khorshiddoust

Alimohammad Khorshiddoust, Behrooz Sarraf, Bagher Ghermez Cheshmeh, Mrs Fatemeh Jafarzadeh,
Volume 17, Issue 47 (12-2017)
Abstract

In recent years, the severe fluctuations in precipitation have affected various parts of the country. On the southern coasts of the Caspian Sea, precipitation as one of the important climatic parameters has undergone changes due to global climate change. In the present study, we tried to evaluate the effect of climate change on rainfall in this region by applying a suitable model. In this study, observational period rainfall (1961-2001) was analyzed. the output of the HadCM3 model was used. At first, seven synoptic stations were selected and their data were analyzed in terms of accuracy, and length of statistical period, and lost data was restored. The AOGCM data were simulated using the SDSM model and the rainfall values were simulated for the observation period. After confirming the matching of the simulated data with observational data, the values of the Future (2039-2011) is estimated. The estimation errors of the SDSM model were calculated monthly by MBE and MAE criteria, and then compared. The output of the SDSM model was used to study the total annual precipitation in days with rainfall of more than 1 mm in the observation period and the upcoming period (2011-2039) by the R-Climdex model and the values of the PRCPTOT index Became zoning in the Future. The results showed that the model error in season with high rainfall is more than seasons with low rainfall. On a monthly scale, the maximum error occurred in the months of September, October, November and December. The maximum error in the fall and the minimum error was calculated in the spring and April and May months. According to the results, the total annual rainfall in the period of 2039-2011 will decrease in Anzali, Babolsar, Gorgan and Noshahr stations and rainfall will increase in stations of Astara, Ramsar and Rasht. Geographical distribution of selected were 5 sites in the Khuzestan, 20 sites in Bushehr, 24 sites in Hormozghan and 12 sites in Sistan and Baluchistan provinces. In total, 9000 sites were selected with a 2 km2 were suitable for large scale microalgae cultivation. The total area of these sites were estimated to be 18000 km2. The highest number of proper sites were found in Hormozghan province and lowest numbers of sites were found in Khuzestan province. The availability of technical service, carbon dioxide point resources from oil and gas units are an advantages for microalgae related activities in the Bushehr and Khuzestan provinces. The higher quality of water in the Sistan and Baluchistan province is an advantages for development of microalgae biomass production in the area.
 

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Saeed Jahanbakhshasl, Ali Mohammadkhorshiddoust, Fatemeh Abbsighasrik, Zahra Abbasighasrik,
Volume 24, Issue 75 (12-2024)
Abstract

 Assessing and predicting future climate change is of particular importance due to its adverse effects on water resources and the natural environment, as well as its environmental, economic and social effects. Meanwhile, rainfall is also an important climatic element that causes a lot of damage in excess conditions. West Azerbaijan Province is no exception. The aim of this study is to model and predict 30 years of rainfall in West Azerbaijan province. The statistical period studied is 32 years (2019-1987). Selected stations in the province include Urmia, Piranshahr, Takab, Khoy, Sardasht, Mahabad and Mako stations. Average slider time series models, Sarima (seasonal Arima), Health Winters were used for analysis and prediction and also linear regression and Mann-Kendall test were used to determine the data trend. The results show an increasing trend of precipitation in Urmia, Piranshahr, Khoy, Sardasht and Mako stations and a decreasing trend in Takab and Mahabad stations. According to the results of comparing the models used, the Health Winters model with the least error in the absolute mean of deviations, mean squared deviations and the percentage of absolute mean errors was introduced as the best precipitation forecasting model for West Azerbaijan province. province.                                     [A1] 



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