Golamabas Falah Qalhar; Rasol Sarvestan
Abstract
The aim of this study is to predict and verify the number of days of dust phenomenon selected stations in Khuzestan Province using Box-Jencks model. Study in eight selected stations of the province to compare the Box-Jenkins model and predict the effect of dust has been done. Using the Minitab 17 software ...
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The aim of this study is to predict and verify the number of days of dust phenomenon selected stations in Khuzestan Province using Box-Jencks model. Study in eight selected stations of the province to compare the Box-Jenkins model and predict the effect of dust has been done. Using the Minitab 17 software Box-Jykyz time series model, number of days of dust monthly was checked and best models were fitted, the accuracy of the model using normal distribution of residuals, assuming constant variance, charts left over time, Mvntv Perth test was confirmed. Finally, Arc-GIS10.4 software was used for output mapping. Results showed that the best monthly pattern for Ramhormoz, Aghajari, Behbahan, Abadan, Dezful, Omidiyeh, Ahwaz and Masjed Soleiman are ARIMA (2,0,1)(1,1,1), ARIMA (2,1,1)(1,1,1), ARIMA (3,0,1)(2,1,1), ARIMA (1,0,1)(2,1,1), ARIMA (2,0,1)(2,1,1), ARIMA (3,1,1)(1,1,1), ARIMA (3,0,1)(1,1, 1) and ARIMA (4,0,3) (1,1,1), respectively. These models have a good accurately for predicting dust and the numbers of dusty days for 2018 to 2027. Also, results showed that Agajari, Abadan and Masjed Soleiman are more exposure with dust phenomena in Khuzestan Province that needs for further attention to city officials and planners in facing with this phenomena.
Mokhtar Karami; Rasol Sarvestan; Reza Sabouri
Abstract
The purpose of this study was to investigate the effect of climate change on the monthly discharge of Karoon Catchment as the largest basin in the country. In this study, five hydrometric stations (Bamdgeh, Telezang, Gharmaleh, Gotvand and Dezful) and three synoptic stations (Ahwaz, Dezful and Masjed ...
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The purpose of this study was to investigate the effect of climate change on the monthly discharge of Karoon Catchment as the largest basin in the country. In this study, five hydrometric stations (Bamdgeh, Telezang, Gharmaleh, Gotvand and Dezful) and three synoptic stations (Ahwaz, Dezful and Masjed Soleiman) were considered. Using the SDSM software, NCEP data and large-scale data from the general circulation model (HadCM3 for temperature and CgCM3 for water discharge) were scaled parameters under two climate scenarios A1B and A2 in the Karun Basin. Then, the climate change data and the output of the microscale model were applied to the SPSS 19 and Minitab 17 to predict the significance of water discharge for future climate courses (2020-2070) be simulated. Results of climate change analysis showed that under different scenarios, monthly air temperature in the scenario A1B increases by 1.60°C and in the scenario A2 1.58°C, but the average annual rate of stations in the scenario A1B is 19.82 m S-1 in size and 16.27 m S-1 in the A2 scenario. The modified Kendall and age tests were used to identify seasonal and semi-annual seasonal time series trends. Results also showed that under climate scenarios of discharge in spring and first half of the year, there was no significant trend at 95% of confidence, but in other seasons of the second half of the year, there was a significant decrease.
