Assessment, Management and investigation of the effects of climate change on drought in western cities of Iran

Drought is a hazardous phenomenon, as a result of climatic parameters abnormalities. The effects of high and low drought occur in different parts of the country, and its effects are more noticeable in arid and semi-arid regions. One of these areas is western Iran, which has been affected by this phenomenon in recent years. The purpose of this study is drought modelling and investigation in western Iran. To do this, climatic parameters were first used, including precipitation, temperature, sunshine, relative humidity and wind speed in 32 years (1987-2018) at 16 stations in western Iran. For modelling the TIBI fuzzy index, at first, four indices (SET, SPI, SEB, MCZI) were been fuzzy in Matlab software, then the indices were compared and finally, by Vikor multivariate decision-making model was used to prioritize areas affected by drought. The results of this study showed that the impact of rainfall on the drought intensity on the 12-months scale is weaker than the 6-months scale. In the six months, from May 1998 to August 2006, the trend was increasing and then followed the steady pattern, but on a 12-month scale, from August 1995 to December 2001, the trend was increasing and after this month it followed the mostly steady pattern. The highest frequency of drought at 6 and 12-month scale occurred in Ilam station and its lowest was in Sarpule-Zahab station. The T.I.B.I index accurately reflects the four indicators of SET, SPI, SEB and MCZI. Based on the modelling, T.I.B.I fuzzy index showed relative superiority to the SPEI fuzzy index. Finally, according to the Vikor multivariate decision-making method, the Ilam station with a score of 0.99 was more prone to drought occurrence

Analysis and prediction of Dust phenomenon in the southwest of Iran

Dust is a phenomenon that has many destructive environmental impacts in different parts of human life, including: agriculture, economics, health and Etc. The country of Iran, especially its western and southwestern regions, is suffering a lot of damage due to its presence in the area affected by the dust phenomenon every year. So pay attention to this issue and reducing the resulting damage, It is a priority. The purpose of this Research is to investigate and predict the dust phenomenon in southwest of Iran. For this Research, 27-year-old dust data were used at 14 synoptic stations in southwest of Iran during the period (1990-2017). In this Research, dust data was first normalized in 14 stations Then, by using the hybrid-panel data model, the ANFIS-compatible neural network in MATLAB software was falsified and predicted. and finally, to prioritize more stations, Dust was exposed to TOPSIS and SAW multivariate decision making models. The findings of the study showed that the reliability of the lira faction models (neural network of the hybrid panel compared to the ANFIS comparative neural network) was higher. Based on prediction models, the maximum probability of occurrence, the maximum dust in the next 23 years in the studied area at two stations, Sarpol Zahab and Abadan are respectively (120.709, 128.917). According to the SAW model, the probability of occurrence of dust in the next 23 years is estimated at Abadan station with 0.99% and Based on the TOPSIS model, Islamabad Gharb station with a value of 0.97%. According to the results of this study, in order to reduce the damage caused by the dust phenomenon in the study area, in addition to domestic measures, such as inter-organizational cooperation, it should be addressed by concluding an international agreement with the neighboring countries

Drought monitoring in Urmia Lake by fuzzy index

Drought is a climate phenomenon with a lack of moisture and rainfall compared to normal conditions.  This phenomenon strongly affects all aspects of human activity. In this Article, were discussed the drought situation in Urmia Lake using MATLAB software and system capabilities combined indicators SEPI on two-time scales 6 and 12 months. Therefore was used climate data of temperature and precipitation for 5 synoptic stations basin of Lake Urmia (Tabriz, Maragheh, Urmia, Saghez, and Mahabad). Results indicated that SEPI index show features of SPI and SEPI index. As well as it enters temperatures as a powerful factor in the drought severity in order to the investigation of the drought conditions; So SEPI drought index is better than the SPI for the study of drought. Drought studies on SEPI index indicated that drought trend in Urmia Lake Basin is increasing. The temperature has an increasing trend with more intensity. The longest duration of drought in the basin of Lake Urmia is in Urmia station on a scale of 6 months from May 2005 to November 2006 for 19 months. The highest percentage of drought observed in Urmia and the lowest percentage in Mahabad stations