جستجوی مقالات مرتبط با کلیدواژه « khuzestan » در نشریات گروه « محیط زیست »

Remote Sensing Technology is considered one of the most important sources of spatial and thematic data in the developed world of today. The objective of this work is a comparison of two different methods of change detection in forests using Landsat images. Therefore, sensor Landsat TM images of 1990 and 2011 (ETM+) satellite images have been used.

In the classification of images, the maximum likelihood algorithm, and artificial neural network to multilayer perceptron method were used.

Evaluated results showed that the algorithm approach, the maximum likelihood overall accuracy, and kappa coefficient maps classified in TM image, respectively, are 96.72 and 0.96 percent and image ETM+ 98.02 and 0.97 percent, and the method of artificial neural networks, overall accuracy and kappa coefficient map classified, TM image was 98.22 and 0.97% and ETM+ image was 98.34and 0.97 percent respectively. Following TM and ETM+ classification maps to detect the changes were marked and the map changes obtained.

The results of this study showed that using Landsat data along with data from have inventory capabilities of forest change mapping

 climate change can be considered one of the biggest environmental challenges of the recent era, which indicates unusual changes in the internal climate of the earth's atmosphere and its consequences in different parts of the globe, which is a serious threat to the environment. The purpose of this research is to prepare a vulnerability zoning map of infrastructures in the southern regions of Khuzestan in the conditions of climate change.

 for this purpose, using previous sources and interviews with experts, eleven variables of total annual precipitation, average temperature of hot and cold season, the trend of maximum precipitation of more than 5 mm per day, the number of dust codes, the occurrence of heat waves above the 95th percentile, precipitation changes, displacement of coastline, underground water changes, floods and inundation and temperature changes during 2019 to 2019 were investigated. By using two trend analysis tests, i.e. Sence slope estimator trend analysis test and Mann-Kendall trend analysis test, the trend of the 32-year time series of these elements during the basic statistical period (1985-2017) was investigated.

 The southern parts of the studied region of Khuzestan had an average temperature of more than 38 degrees Celsius per year, while the northern and central parts of the studied region had a temperature of more than 38.5 degrees Celsius per year.The southern part of Khuzestan has an annual rainfall equivalent to more than 273 mm per year, while the southern parts of the studied area have less than 200 mm of rainfall per year and in some cases about 156 mm per year.

 The results show that high and very high risk areas cover 80% of the region.

Mandragora is a genus of the Solanaceae family, which includes six species worldwide. M. autumnalis Bertol is the only native species of the genus growing in Iran, reported for the first time in 2013 from Khuzestan province in Shimbar Protected Area? Field observations showed that this species is present in the Shimbar Protected area only in 4 locations, its Area of Occupancy (AOO) is about 0.6 square kilometers in total, and its Extent of Occurrence (EOO) is around 1.5 square kilometers. An average number of 5 to 25 individuals is observed in each population. Due to the presence of this plant in only one habitat in Iran and the Area of Occupancy, less than 10 square kilometers, and the number of adults is less than 50 individuals. The species is classified as Critically Endangered (CR) in Iran. Although the habitat of this species is in a protected area, it is heavily influenced by man-made destructive factors due to factors such as deforestation, fire, overgrazing, the presence of nomadic nomads, the villages on the edge of the wetland, and because many tourists to the area. Therefore, these valuable medicinal species face serious threats in Iran and need special attention from the related executive organizations. An urgent protection plan is needed for the conservation of the limited population of M. autumnalis.

Nowadays, climate change causes abundant worries in different spots in the world. For this reason, a study was conducted to find the trace of this global phenomenon in Khuzestan province. Therefore, we used meteorology data including temperature parameters, rainfall, evapotranspiration and relative humidity for 15 weather stations in a period of 21 years (1996-2016) and Mann Kendal graph to determine the trend. The result illustrates that there is a meaningful downward trend for rainfall parameter in SafiAbad, Hendijan, Masjedsoleiman and Bandar-E-Mahshar with confidence level of 95% and Omidiyeh with confidence level of 99%. Moreover, there is a meaningful upward trend with confidence level of 95% in tempe-rature parameters in most stations, while this level is 99% in Bostan, Hendijan and Izeh. In addition, a meaningful upward trend in evapotranspiration in two station of Bostan and SafiAbad with confidence level of 95% and 99% and a meaningful downward trend with confidence level of 99% for Shushtar, Izeh, Abadan, Masjedsoleiman and Ahwaz as well, is visible. There is a meaningful downward trend in relative humidity in Bostan, SafiAbad, Izeh, Omidiyeh and Masjedsoleiman, which all present the climate change effect in region.Climate change is one of the most important challenges in the 21st century. Global warming has caused very unstable changes in climate parameters such as: changes in rainfall patterns and frequency and intensity of climate changes. The issue of climate change has become one of the main concerns of scientists related to atmospheric sciences due to its impact on various dimensions of human life and the dependence of human activities on it, and many researchers are trying to understand the various dimensions of this important phenomenon. The change in climatic elements, especially temperature and precipitation, is one of the most important signs of this phenomenon. Changes in temperature and precipitation in different parts of the earth do not follow the same trend, and climate change does not necessarily mean simultaneous changes in precipitation and temperature. The amount, distribution and temporal and spatial changes of precipitation and temperature are essential factors for decision-making, management, planning and design, especially in areas such as Iran, which is geographically located in the 28 to 48 degree north latitude and It has a dry and semi-arid climate. In order to detect the trend in the time series of water and meteorological variables, various tests are used, and these tests can be divided into two categories, parametric and non-parametric. Parametric tests are more powerful in detecting trends than non-parametric tests, and when using them, the data should be random and have a normal distribution. On the other hand, non-parametric tests can be used if the data is random and are not sensitive to the normality of the data. Mann-Kendall's test is a non-parametric test that is used in researches to investigate the trends of water and meteorological variables. To carry out this research, climatic data (average rainfall, average evaporation and transpiration, average humidity and temperature parameters) prepared by the meteorological organization of Tehran province for a statistical period of 21 years from 1996 to 2016 have been used. Mann-Kendall test was used to analyze the trend of climatic parameters, which will be explained in detail below.• Mann-Kendall non-parametric testThis test was first presented in 1945 by "Mann" and then developed by "Kendall" in 1966. This test does not require a normal frequency distribution or linear behavior of the data, and it works very strongly compared to the data that deviates from the linear behavior and is used to evaluate the trend (Darabi et al., 2015). In this test, the null hypothesis (H0) and the opposite hypothesis (H1) are respectively equivalent to no trend and the presence of a trend in the time series of observational data. Mann-Kendall diagram test:The steps of the test are briefly as follows:We rank the data and calculate the ti statistic, which is defined as the ratio of rank I to its previous ranks, and then we obtain the cumulative frequency of the statistic ( ). Mathematical expectation, variance and Mann-Kendall index are calculated based on the following formulas (Zahedi et al., 2016):In these relationships, ni is the time order of the data. To check the changes, the index Ui' should also be calculated: rank the data and determine the statistic t'i, which is defined as the ratio of rank I to its next ranks, and then calculate the cumulative frequency of t'i we do The mathematical expectation, variance and index Ui' are as follows:In the above relationships, N is the statistical sample size under study. The intersection of the index Ui and Ui' is a sign of a sudden change in the time behavior of a statistical series. The non-intersection of the curve or their placement within the 95% confidence range does not indicate significant changes in the data, but if the mentioned lines intersect within the critical range of 1.96 and 2.58 and then leave the critical range, it is a sign of a sudden change and a significant trend at the 95% and 99% confidence levels, respectively. If the U curve moves to the positive side, it has a positive trend, otherwise it has a negative trend. Crossings outside the critical range indicate a sudden change in the behavior of the series (Alijani et al., 2009).In general, the results showed that during the studied statistical period, rainfall in all stations had a decreasing trend. Also, the minimum and maximum temperature parameters have been increasing in most of the stations. The parameters of evaporation and transpiration and relative humidity in most of the stations had a non-significant decreasing trend. Based on the results of Mann-Kandall charts, it was found that Safi Abad, Omidiyeh and Handijan stations were more affected by these changes than other stations. It is obvious that dealing with the effects of climate change and its consequences, such as the increase in the temperature of the earth's surface or the decrease in rainfall, requires a detailed investigation of the causes of this phenomenon and the provision of appropriate solutions in order to prevent endangering food security, increasing soil erosion, desertification and other problems.

Methane (CH4), nitrous oxide (N2O) and nitric oxide (NO) are considered to be the most important greenhouse gases. Present study is a practical-analytical study conducted with help of DAYCENT software to study flux of methane, nitrous oxide and nitric oxide emissions in citrus orchards of Dezful and Abadan groves in Khuzestan province. DAYCENT model program is written in FORTRAN and C programming languages ​​and runs with Unix / Linux platform. Results of methane flux simulation at Dezful station show release of 0.448 tons of methane per square meter per year, 0.111 tons of nitrous oxide per square meter per year and 0.152 tons of nitric oxide per square meter per year. Results of simulation of methane flux in Abadan station indicate release of 0.398 tons of methane per square meter per year, 0.014 tons of nitrous oxide per square meter per year and 0.129 tons of nitric oxide per square meter per year. Potential for global warming was then calculated for both study areas. Also, in order to evaluate accuracy of the model were used, statistical characteristics of maximum error, root of mean error squares, determination coefficient, model efficiency and remaining mass coefficient. According to statistics, DAYCENT provides acceptable results and has a good accuracy range in all three gases. Results showed that trend of increasing flux of methane, nitrous oxide and nitric oxide gases in Abadan groves is slower than Dezful citrus orchards.

Habitat destruction is one of the most important threats to amphibians. In this regard, considering the national and international importance of Neurergus kaiseri species, it is very necessary to study the vulnerability of its habitat; Therefore, the present study aimed to investigate the vulnerability of Neurergus kaiseri habitat on the boundary of Lorestan and Khuzestan provinces in order to increase the level of conservation of this endemic species . To achieve this purpose, various topographic, hydrogeomorphological, geological, climatic, Land cover and human data have been collected through library, image-based and field methods and analyzed using various tools, especially Arc GIS software and FAHP model. The results of modeling the intensity of vulnerability of Neurergus kaiseri habitat showed that among the 21 indicators, indices of distance from spring and waterfall, distance from drainage, distance from road and land use with normalized weight of 0.117, 0.113, respectively. 0.107 And 0.102 gained the highest level of importance in determining the intensity of the final vulnerability. The results also showed that out of 48 Neurergus kaiseri stations in the study area, 23.5% had very high vulnerability, 33.3% high, 29.2% moderate, 16.7% low and 8.3% intensity vulnerable. They are very few; therefore, it is necessary to protect the areas with the highest density of Neurergus kaiseri and with periodic monitoring and tracking, the necessary planning be done to protect and prevent the extinction of this species.

Convolvulus L. (Convolvulaceae) is represented with 57 species in the Iranian plateau. Convolvulus koieanus Bornm. is an endemic species of Iran, distributed in the Khuzestan and Lorestan provinces.  Based on the research method of the national research project, entitled defining the conservation status of the plant species in Iran and the IUCN guidelines, three criteria related to the extent of occurrence, area of occupancy, and the number of mature individuals in the populations were considered to evaluate the conservation status of C. koieanus. GeoCAT software calculated its Extent of Occurrence (EOO), 24377.917, recognized as the Near Threat (NT), and the Area of Occupancy (AOO) was calculated to be 24 square kilometers, recognized as endangered (EN). Based on field observations, the Area of Occupancy (AOO) of this species was calculated to be 0.19 Km2 for Khuzestan and Lorestan Provinces. According to the IUCN classification, it is in the group of Critically Endangered (CR); however, it does not qualify for this status, considering the number of habitats, sub-populations, and the number of individuals in each subpopulation. Based on the current data, we determine it as endangered (EN). This species is affected by human activities. The field observation indicated that road construction and grazing are the main threats for this species. The conservation of this valuable species as a natural genetic reserve is necessary. We suggest one habitat in each of the Khuzestan and Lorestan provinces be defined as protected by the Forests, Rangelands, and Watershed Organization. The ex-situ conservation needs to be planned. This species is easily propagated by seeds, and if its habitat is protected, it will regenerate and expand in the area.

The present study is to evaluate the surface currents of Khuzestan province and its forecast for the period 2019 to 2021 using time series models.

The present study was conducted in 9 selected stations from Khuzestan province in order to compare the accuracy of the time series model and predict the amount of surface currents. For this purpose, the monthly flow data of the hydrometric station for 22 years (1391-2014) has been used. The multiplicative seasonal time series model of surface currents was investigated and the best model was fitted.

The results of these studies show that the best models fitted in SARIMA (1,1,1) (1,0,1), SARIMA, SARIMA (0,1,1) (1,0,1), telephoto SARIMA, Primate (1,0,1) (1,1,1) SARIMA, Dezful (1,0,2) (1,1,1) SARIMA, Plain SARIMA, Dokehe (0,2,2) (1,1,1) SARIMA, Gotvand (1,1,2) (1,0,1) SARIMA (1,1,1) And SARAB (1.1.2) (2.1.1), which had good accuracy to predict surface currents.

Surveying the annual prediction of surface currents for 2019 to 2029 showed that surface currents in all selected stations decreased and this decrease in Ahwaz station to the highest and the two-hill station to the lowest values reaches to 9.78 and 0/58 respectively; also, the monthly forecast showed that in December, with 6/98 and 1/67, the highest and lowest decreases would occur.

According toincreased Concern about the long-term effects of heavy metals as environmental pollutants, studing showed that the bio monitoring could be desirable and satisfactory method to measure heavy metals. Feathers can play the role of both storing and eliminating metals. In this study, accumulation of heavy metals cadmium and lead in birds with emphasis on impact type of habitat (water and drought) were studied in birds in South West of Iran. Tail feathers of 29 birds belonging to 8 species (4 species of aquatic and terrestrial species 4) were collected. In this study heavy metals were measured by using Fillips PU 9400 Atomic Absorbtion Spectrophotometer. Mean Pb concentration in feather of birds was obtained between 18.23± 1.03 (Aythya nyroca) and 3.33± 1.31(μg/g) ( Merops orientalis). Alse mean of Cd in birds was obtaine between 1.71± 0.06 (Anas platyrhyncho) and 0.06± 0.03(μg/g) (Merops orientalis). For evaluation of effects of habitat type on level of lead and cadmium on feather, the birds studied in two groups (aquatic and terrestrial birds).The mean of Pb in aquatic and terrestrial birds were 11.94±4.95 (μg/g) and 6.81±1.03 (μg/g) respectively. A significant difference was in feather Pb concentration across aquatic and terrestrial birds.The concentration of Pb in feathers of aquatic birds was higher than terrestrial birds. The mean of Cd concentrations in aquatic and terrestrial birds was obtained 1.08±0.73 (μg/g) and 0.25±0.19 (μg/g) respectively. However Cd concentration in aquatic birds were higher than terrestrial birds, but there was no significant difference between Cd concentrations in aquatic and terrestrial birds.

The Shaloo and Mongasht protected area with an area about 12553 ha is located in Irano-Turanian region (Zagros region) between the longitudes 50° 15´ to 50° 40´ E and latitudes 31° 35´ to 31° 45′ N. So far, about 300 species belonging to 50 families have been collected and identified in this region. The forest cover of the region, dominated by Quercus brantii along with Crataegus aronia, Pistacia atlantica, Acer monspessulanum, and Cotoneaster nummularius form the physiognomy of Shaloo and Mongasht protected area. Nine endemic species were found in this area. Overexploitation of natural resources, specially grazing, change in land use, hunting of birds, extension of gardening and agriculture, and construction of villas and residential houses on the margin of protected area can pose a serious threat to the region in the long run. There are many medicinal and edible plants in the Shaloo and Mongasht protected area. Unfortunately, the population of species such as Ferulago angulata, Prangosspp., Myrtus communis, and Allium spp. is declining.

At present, global circulation models are only instrument that simulates global climate change effects for atmospheric elements in large spatial networks. Most famous of these models is SDSM. In this study, using mean data, minimum and maximum daily temperatures of Omidieh and Dezful stations in Khuzestan province were compared with SDSM software until 2099. Results obtained from data of Omidieh include annual observation data of mean temperature of 17.393 and annualized model data average of 15.255, annual observation data of maximum temperature of 35.400 and annualized model data maximum temperature of 45.700, annual observation data of minimum temperature is -2.400 and annualized model is minimum temperature of -6.400, annual standard deviation is 0.098 and annual standard deviation is 1.819 and annual standard deviation of minimum temperature is 0.917. Results obtained from data of Dezful city included annual observational data of 15.300 and average annual data of average temperature of 14.442, annual observation data of maximum temperature of 40.000 and annualized model data, maximum temperature of 39.350, annual observation data of minimum temperature is -13.000, and nnualized model is minimum temperature of -9.850, annual standard deviation is 0.091 and annual standard deviation is 1.459 and annual standard deviation of minimum temperature is 1.682. The simulation of temperature index with HadCM3A2 and B2 models by 2099 was carried out for two stations. The results showed that station's height factor is directly related to model error.

Aim of this study was to investigate the phenomenon of dust in the Khuzestan province and the correlation between these phenomena with elements of precipitation, speed wind and temperature is between 2010-1990. Statistical method library and using monthly data, eight selected stations (Masjed Soleiman, Ahvaz, Ramhormoz, Behbahan, Dezful, Aghajari, Abadan and Omidiyeh) of Khuzestan province using the softwares Minitab 17, spss 19 and Microsoft Excel 2013. For this purpose, using test homogeneity was examined data. From decision models was used to test, including automatic discovery classification method CHAID and regression trees CRT and test multiple interaction linear regression. Test Anderson-Darling and Kolmogorov-Smirnov showed that dust phenomenon data in Khuzestan province is normal. Using two methods CHAID and CRT was determined that wind is the best predictor for classifying dust in Khuzestan. Wind floors more than 2,100 in the CRT method and floor winds more than 6,500 in the CHAID method as a predictor of significant effect on the classification dust synoptic stations. Correlation between temperatur with dust is 0.425 percent, dust with wind speed 0.452 percent and between dust with rainfall -0.311 percent. With increase precipitation in the Khuzestan province reduced the number of days of dust but the temperature and wind speed are correlated to some extent with dust province and variables such as wind speed, rainfall and temperature have significant impact in the dust Khuzestan province.

Farm experiments are useful in knowing the drainage systems but they have considerable limitations including the inability to use them as prediction tools. Application of simulation models can cover these deficiencies but it is necessary to use the field data to evaluate the accuracy of the model. In this study, Artificial Neural Networks (ANN) and model DRAINMOD are used to predict water table.
For this purpose, field R9-11 of the Debal Khazaei sugarcane plantation is selectedand Input parameters of the models, including fluctuations in water table, the volume of irrigation water, drainage flow, Climatic data, Soil physical properties and Drainage system parameters were measured from November 2013 to October 2014. The results have showed that the artificial neural network method has a highest accuracy in predicting water table. So that the average RMSE between measured and simulation with Artificial Neural Networks and DRAINMOD obtained 0.02 and 16.8 respectively.

Nowadays, climate change causes abundant worries in different spots in the world. For this reason, a study was conducted to find the trace of this global phenomenon in Khuzestan province. Therefore, we used meteorology data including temperature parameters, rainfall, evapotranspiration and relative humidity for 15 weather stations in a period of 21 years (1996-2016) and Mann Kendal graph to determine the trend. The result illustrates that there is a meaningful downward trend for rainfall parameter in SafiAbad, Hendijan, Masjedsoleiman and Bandar-E-Mahshar with confidence level of 95% and Omidiyeh with confidence level of 99%. Moreover, there is a meaningful upward trend with confidence level of 95% in tempe-rature parameters in most stations, while this level is 99% in Bostan, Hendijan and Izeh. In addition, a meaningful upward trend in evapotranspiration in two station of Bostan and SafiAbad with confidence level of 95% and 99% and a meaningful downward trend with confidence level of 99% for Shushtar, Izeh, Abadan, Masjedsoleiman and Ahwaz as well, is visible. There is a meaningful downward trend in relative humidity in Bostan, SafiAbad, Izeh, Omidiyeh and Masjedsoleiman, which all present the climate change effect in region.

Lethrinus nebulosus, which belongs to the Lethrinidae family, is widely distributed along the coasts of Iran. Determining the maturity index is essential in studies of biology, fishery management and aquaculture. In the present study, monthly sampling was conducted on northwestern coasts of the Persian Gulf in Khuzestan from July, 2014 to June, 2015. After biometry and sex determination during monthly sampling, gonadosomatic and hepatosomatic indices, length at 50% maturity, monthly sex ratio and absolute and relative fecundity were calculated for this fish. The gonadosomatic index started increasing from February on and its peak was recorded in April (1.7993). A single peak in gonadosomatic graph indicates one spawning a year. Maximum changes in hepatosomatic index were observed among males in March (0.7449) and among females in April (0.7812).  The length of 50 percent of female adults amounted to 37.2 cm. Absolute fecundity and relative fecundity were calculated as 312415 and 8.24 respectively. The females outnumbered the males in most months of the year. The sex ratio of females to males was 1.99 to 1. This fish reaches maturity in shorter length in the middle coasts of the Persian Gulf than in the eastern and western coasts.

The purpose of this study is to investigate the dust and predict the best time series models for the cities of Khuzestan province during the years 2019-2023. The statistical method of the library and using the annual data, eight cities selected from Khuzestan province to identify and predict the best time series models using the software Minitab17, spss19 Excel 2013. For this purpose, annual dust data from eight meteorological stations of Khuzestan province during the period of 1990-2010 were collected and analyzed using the ridge test of homogeneity of dust data. Using time series models of dust walnuts and the best model for identifying fitted dust, the accuracy and accuracy of the models were based on absolute error (MAE), absolute error (MAPE), root mean square error (RMSE average), and The BIAS standard has been approved. The results of the most suitable models of Dust Time Series for the cities of Masjed Soleyman and Behbahan are Halt Winters forecast model, Dezful city alone in the model of Arima (1.0.1) and Ahwaz, Ramhormoz, Aghajari, Abadan and Omidieh models Nemo is smoothly achieved. Also, the results of the dust show that the city of Omidieh with the highest difference of dust increases to 79 days and the city of Dezful reaches the lowest number with 9 days. And the rest of the cities are Abadan, Aghajari, Ramhormoz, Ahvaz, Masjed Soleyman and Behbahan, respectively, 75, 45, 45, 41, 36 and 25 days a year.

Identification of climatic potentials as a context of human activities, constitutes a bedrock for majority of environmental plannings and land use plannings. In this regard, climatic features and their dominant elements play an important role in spatial distribution and development of environmental behavior of human societies, so that weather cognition and the use of its various potencies are comsidered as a base for urban development planning, construction, habitat, architectural and tourism expansion.
Methodes: In this study, the human comfort or discomfort at Arvand Free Zone was evaluated based on bio-climatic indices, Terjung, Neurotic strain, Baker, effective temperature, (TCI), (PET) and (PMV) using data from 60 years (1951-2010). Moreover, using the climatological parameters obtained from synoptic station of Abadan, the best time for environmental activities in this city was determined.
The results showed that the used bioclimatic indices are able to reveal comfortable and uncomfortable periods in Abadan and despite trivial differences, all indices present the same aspects of climatical comfort of this city.
The analysis showed that Abadan mostly had a wide range of variety during the year and changes from hot to very cool weather. During spring and summer, it is excluded from the limits of bioclimatic comfort. In the late fall and throughout winter, Abadan climate with its unique conditions for human comfort, is the best season for environmental and tourism activities.

Ecological capability evaluation is for identity to ability potential land for executable usage and expected.
Meydavood region is located in Baghmalek town in Khuzestan province and include various features such as: mountain, plains, low land, forest land and pastures. The most part of the study area is belong to pastures, and the researching has been trying to potential capability land for using of pasture with using of two models FAO and makhdoom with helping GIS application. Finally potential pastures unit has been recognized based on pastures ecological model in Iran and using searching language in geographical information.
Findings: Based on FAO model 5 unit has been recognized suitable for pasture from 8 unit land, and remainder is unsuitable. Based on Makhdoom model 238 unit has been located in third floor and 71 unit has been located in fourth floor of pasture.
Discussion and Counclusion: comparison between 2 models has been shown that environmental units are more in number and lower in area than FAO model; In the other hand FAO model with present using has been shown high proportion. With due attention to shortage of suitable pasture land in Iran, Makhdoom model is not suitable with performance and management plans of country in Meydavood and FAO model is preference.