Nasrinalsadat Bazmi, Zahra Hejazizadeh, Parviz Zeaiea Firoabadi, Qholamreza Janbazghobadi,
Volume 23, Issue 70 (9-2023)
Abstract
This article was written with the aim of revealing land use changes in Urmia city using remote sensing of Landsat satellite images for 4 periods of 8 years between 1990 and 2019. For this purpose, two categories of data will be used in this research. The first category includes data obtained from satellite images and the second category includes ground data taken from Urmia ground station, which includes temperature and other parameters used in this research. The results showed that urban land use in Urmia city has faced significant changes during the statistical period of 30 years. This user has had an increasing trend during all the studied periods, so that during the study period, it has faced a 5-fold increase. Swampy areas and sludge fields east of Lake Urmia have undergone a significant decline during 1990-2019 and has reached less than 6,000 hectares. The citychr('39')s barren lands, which cover a small percentage of the citychr('39')s area, have been declining over the 30-year period under review. The use of gardens has increased during all periods, so that in 2019, its area has reached more than 20,000 hectares. The use of irrigated agriculture has increased during all the studied periods and its area has reached more than 80,000 hectares by 2019. The area of rainfed agricultural lands, after the rangelands, is the widest land use in Urmia, but with a relatively gentle slope has a decreasing trend. Water areas have also been declining, so that in 2019, it has decreased by about 26% compared to 2012. Rangelands, which is the largest land cover in Urmia city, has gone through three different processes during the study period. From 1990 to 1998, these lands did not change significantly, but from 1998 to 2005, the increasing trend and in 2019, with a 10% decrease compared to 2012, reached its lowest area during the statistical period under study, ie less than 20,000 hectares.
Fahimeh Shakeri, Gholamabbas Fallah Ghalhari, Hashem Akbari, Zahra Hejazizadeh,
Volume 24, Issue 72 (3-2024)
Abstract
In this research, the sensitivity of the meteorological elements (such as mean temperature, relative humidity and wind speed) to different physical parameterizations in the numerical forecast model (WRF) was evaluated to simulate the climate of the city and adjust the Urban Heat Island of the study area.To study urban environmental issues, the Urban Canopy Model (UCM) was coupled to the WRF model. Several experiments were performed to achieve optimal configuration for simulation in the period from 18-21 August 2016 in the stable atmospheric conditions in summer. Selection of the most appropriate configuration with the least error is proposed as an appropriate setting for urban climate simulations and the study of Urban Heat Island (UHI). Increasing surface reflections to reduce UHI in the range was applied. Two indices of Root Mean Square Error (RMSE), and Mean Bias Error (MBE) were used to evaluate the predictive performance of the model and its corresponding observational values. The results showed that in the province of Tehran, in general, all configurations estimate the air temperature and wind speed less than real and relative humidity more than the actual value. In Alborz province, all configurations estimate the air temperature and wind speed more than real and relative humidity less than real value. By increasing the reflection of urban levels, the mean temperature of Tehran and Alborz provinces decreases 0.6 and 0.2 ° C, respectively. Wind speed, especially in urban areas, increases somewhat. We also see an increase in relative humidity (especially in urban areas) in the studied areas.
Dr Zahra Hejazizadeh, Dr Mehry Akbary, Zarin Jamshidiyini,
Volume 24, Issue 74 (9-2024)
Abstract
The present study investigated the impacts of NAO and ENSO on the precipitation in the southern shores of Caspian Sea. The accumulated monthly and annual rainfalls from 5 synoptic stations during the years (1956-2017) were taken through Islamic Republic of Iran Meteorology Organization (IRIMO) and the Multivariate Enso Indices (MEI) and NAO activity years are obtained from National Oceanic Atmospheric Administration. Pearson correlation was used to investigate the relationship between indices and precipitation amounts of selected stations. The results showed that there was a significant relationship between precipitation and NAO index in some months in all stations but this correlation was not following a particular pattern in all the stations. The maximum correlations were observed at Babolsar and Anzali station and the least correlation was found at Gorgan stations. The correlation between precipitation and different phases of NAO showed that there was a positive correlation between precipitation and negative phase of the index in Ramsar station and a negative correlation between precipitation and positive phase in the Gorgan station.The results of the Pearson correlation show a significant correlation between the MEI and rainfall amounts in the autumn in some stations in the early winter. In Review drought and wet periods with both Indicator it was observed that the behavior of the stations in the El Niño period, which was with different phases of the NAO was not entirely harmonious but the coefficient of 89% of rainfall in normal and more than normal during the period of El Niño showed that Elnino is better fitted to normal and more than normal rainfall in these stations also coefficient of 60% of weak to severe droughts in the Lanina period in the selected stations Indicates that the LaNina phase was more related with severe droughts in the under studied period.
Mr Mohammad Reza Salimi Sobhan,, Mrs Zahra Beygom Hejazizadeh , Mrs Fariba Sayadi, Mrs Fatemeh Qaderi,
Volume 24, Issue 75 (12-2024)
Abstract
In examining natural hazards, such as hail, statistical analyzes can play a significant role. Due to the great importance of economic and side losses of hail in the northern part of Zagros with maximum frequency and damage, the necessity of studying its temporal and spatial location is felt very distinctly. Therefore, in order to estimate and estimate the probability of occurrence of this phenomenon, 10 hail data data of 10 synoptic stations of the region were used during the statistical period of 2014- 1992. In choosing the best method for calculating the distribution of precipitation probabilities, different types of probability distributions of discrete random variables were tested by means of both Kolmogorov and Anderson-Darling testsThe results showed that the good Poisson distribution test had a good fit for hail occurrence at a high level of 90.99%. Baneh station with the maximum frequency of hail precipitation has the lowest probability (0.023%) and Pearnshahr station has the most probable days without hail (0.39%). Therefore, the probability of occurrence of hail in Baneh has a higher percentage. In the next round, the negative binomial model satisfies the observations of this type of precipitation well. The calculation of probabilistic distributions by these two methods showed that the probability of occurrence of hail with the frequency of 1 to 6 times and more in the region and the highest probability is related to the frequency of 3 occurrences of 0.20%. At a frequency of 1 to 6 times, the probability of occurrence of this phenomenon is 5 times more than the probability that it will not occur, which indicates the region's high vulnerability to this type of climate risk.
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Mr Milad Khayat, Ms Atefeh Bosak, Dr Zahra Hejazizadeh,
Volume 25, Issue 76 (3-2025)
Abstract
Using urban growth and development modeling, it is possible to draw a development trend appropriate to the city's position according to environmental and natural factors and population attraction. The purpose of this study is to represent a model of urban development in Shushtar that can be used as a felicitous tool to analyze the complex processes of urban development. To achieve this goal, two databases consist of urban land use maps for educational, medical, habitation, etc and Landsat satellite images for major land uses such as rivers, barren areas, forests, etc were used by GIS and MATLAB software environment in three time periods 1991, 2004 and 2014. Existing urban land use maps were updated by using Landsat satellite imagery after digitization. Then the effective parameters in urban development were entered as inputs with the adaptive neuro-fuzzy inference algorithm (ANFIS). in order to evaluate the performance of the proposed method, training for 1991 and 2004 was performed. the result of urban development forecasting using the algorithm was compared with the current situation in 2014. The results are very close to reality and with an accuracy of 93.7%. The land use change map, which is the result of the change detection process, can be prepared based on multi-time remote sensing images and combined with urban user maps, and the relevant consequences examined. The use of intelligent algorithms in this research has allowed us to execute modeling with high accuracy. The results are satisfactory and this development was predicted for the coming years.
