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Showing 2 results for Lake Urmia
Analysis of the Spell of Rainy Days in Lake Urmia Basin using Markov Chain Model
Khadijeh Javan,
Volume 16, Issue 43 (12-2016)
Abstract

In this study, the Frequency and the spell of rainy days was analyzed in Lake Uremia Basin using Markov chain model. For this purpose, the daily precipitation data of 7 synoptic stations in Lake Uremia basin were used for the period 1995- 2014. The daily precipitation data at each station were classified into the wet and dry state and the fitness of first order Markov chain on data series was examined using Chi-square test at a significance level of 0.01 and was approved. After computing transition probability matrix, the persistent probability, average spell of dry days and rainy days and weather cycle was calculated. By calculating the frequency of 1-10 rainy, the spell of this periods and 2-5-days return period were calculated. The results show that in this study period the average of rainy days is 25% and the probability of Pdd is more than other states (Pww ، Pdw و Pwd). The average spell of rainy days in the study area was estimated at about two days. Generally, in all stations the persistent probability of wet state is more than rainy state. Estimation of frequency and spell of rainy days and 2-5-days return period show that with increasing duration, the frequency of rainy days decreases. Also with increasing duration of rainy days, their spell is reduces and return period increases.


Investigating the trend of changes in the eastern county's of Lake Urmia and identification of areas capable of cultivating saline plants using remote sensing and GIS
Miss Rahimeh Rostami, Dr. Ali Mohammad Khorshiddust, Dr. Mohammadreza Nikjoo, Dr. Hassan Mahmudzadeh,
Volume 19, Issue 55 (12-2019)
Abstract
The drying of Lake Urmia has had many environmental impacts on the surrounding areas of the lake. In this research, efforts have been made to identify vegetation coverings that are compatible with the study area and then it use of multiplicative decision-making models for identify areas susceptible to cultivation of these products. In the present study, following the study of species in the region of rapeseed, was selected as a suitable halophytes plant. Initially, using Landsat 5 and 8 images, the changes in the land use type and vegetation cover type of the region were investigated from 2000 to 2016, and after calculating the changes, the potential planting of the halophytes plant was sought. The ANP Fuzzy method was used to estimate the ability to cultivate rapeseed. Main criteria used in this research are topography, soil and meteorology. The topographic sub criteria are included: height, slope and tilt direction, soil criteria including soil texture, soil salinity, and soil pH and soil organic matter. Finally, the criteria for meteorological data are total annual precipitation, Relative humidity, average annual temperature, maximum annual temperature and annual minimum temperature. These layers first be changed to fuzzy and then, applying the weight of each of the following criteria, a map of the main criteria of soil, topography and meteorology was prepared and finally, by combining these three main parameters, the potential mapping was obtained. The results indicate a 25.43 percent reduction in water content and an increase of 21.03 percent in saline areas between 2000 and 2016, and the results of identifying areas susceptible to cultivation of halophytes plants have identified 14.28 percent of the study area suitable for rapeseed cultivation.

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