فهرست مطالب mohammad kamangar

The natural abundance of phytoplankton in the Persian Gulf has changed, creating a constant threat to biodiversity. Monitoring and predicting the spatial-temporal behavior of this phenomenon is crucial to prevent negative social-economic consequences and environmental planning. On this basis, the current research aims to assess the spatial-temporal changes of chlorophyll and analyze its relationship with the sea surface temperature in the Persian Gulf. To this end, we estimated and analyzed changes in the concentration of chlorophyll as an organic compound produced by algae and plants using MODIS sensor images from 2000 to 2021 (monthly and seasonally). Spatial indices of the barycenter were also calculated in addition to accuracy assessment using error evaluation criteria. Global Moran and G-star (G*) statistics were used to identify the degree of spatial autocorrelation and the magnitude of spatial patterns. The results showed that the intensity of this phenomenon on average varies between 0.05 and 16.38 mg m-2. The northwest and southwest have the maximum values and the central parts of the Persian Gulf have the minimum values. The northern coast of the Persian Gulf is located in Iran, and the northern parts, i.e., areas with less population and industries, have a low amount of this phenomenon. The ellipse line shows three standard deviations in the northwest and southeast directions following the cities and industries. The time series of changes showed that as the temperature decreases in the cold season, especially in January, the concentration increases, and as the temperature of the water surface increases in the hot season the amount of chlorophyll in the water decrease. Statistical analysis of the spatial distribution also indicates a significant cluster spatial pattern. Slope changes verified that the southern regions of the Persian Gulf, especially in the countries of Bahrain, UAE, and Saudi Arabia, have the most positive slope of changes. In the main part of the area, including the northern part of the Persian Gulf, whose coastline is entirely owned by Iran, except for the northwest, which includes the Mahshahr port and Asaluyeh, the slope of changes has been very low or decreasing. This research could identify areas exposed to adverse changes in phytoplankton concentrations and can be used in environmental planning.

Soil moisture is an important variable in climatic, hydrological, and ecological systems that link atmospheric processes to the earth's surface. The rainfall systems of the water year 2017-2018 abnormally caused more than normal rainfall in Fars province and caused major changes in the surface moisture of the soil. The purpose of this research is to analyze the spatial changes of soil moisture before and after heavy spring rains in Fars province using Downscale RADAR images. Using the backscatter bands of VV and VH polarizations as well as the incident angle band (𝜃) extracted from Sentinel 1 radar images and land use extracted from the MODIS sensor, a training layer was created. Furthermore, using the support vector machine algorithm, the downscaling soil moisture map was obtained. The results showed that the volumetric soil moisture with high resolution is between 0.18 and 0.38 in the rainy year and between 0.12 and 0.24 in the long term. An anomaly map showed that between 0.14 and 0.18 m3 increased soil moisture. The positive anomaly is more in the east and south of the province, and less humid areas have experienced a greater share of positive anomaly. Moran's index statistic with a value of 0.99 has also confirmed the spatial autocorrelation of soil moisture anomaly and clustering of moisture increase. In general, it can be concluded that by using the results of this method, it is possible to monitor areas with low or high soil moisture anomalies after different rainfalls and to improve the decision-making process.

In recent decades, a growing interest has been observed among pharmaceutical companies in producing and selling 80 FDA-approved therapeutic peptides. However, there are many drawbacks to peptide synthesis at the academic and industrial scales, involving the use of large amounts of highly hazardous coupling reagents and solvents. This review focuses on hideous and observant wastes produced before, during, and after peptide synthesis and proposes some solutions to reduce them.

Mapping and spatial analysis of wheat fields are very important in studying macroeconomic and social issues, including agricultural management. Highly variable crop pattern maps and its preparation using terrestrial data are associated with many problems. The purpose of this study is to implement a practical method for extracting wheat fields by using changes in vegetation index and spatial analysis of wheat fields in western of Iran. Investigation of the changes curve of vegetation index of wheat typic farms showed that the highest amount of reflection index of wheat farms is in June and early July and after harvest the reflectance index decreases extremely. In this regard, Sentile sensor data was processed in the Earth Engine system and the 12-month vegetation index of 1398 was extracted as a data set. By introducing training data to the data set created by the support vector machine classification method, the land use of the study area was obtained in five classes. By applying altitude filter and removing the extracted fields above 3,000 meters, the distribution map of wheat fields was verified with the remaining 48 ground data. The total accuracy and the kappa coefficient were obtained 0.86 and 0.79, respectively. Since in the proposed method, more training data are given to the algorithm, the overall accuracy of the classification is increased. The spatial pattern of wheat fields with the mean function of the nearest neighbor and P_value <0.05 indicating the cluster dispersion of the fields and the Caripley function indicating the non-random scattering of wheat fields up to distances of 21,000 meters. The results of this research and its output maps can be used to obtain information for agricultural planning as well as the allocation and spatial distribution of resources and facilities.

Plant transpiration is a process through which part of the water in the plant is transfered out of the pores. The amount of plant transpiration data is useful in developing strategies for water sustainability. Field measurement of plant transpiration is pointwise and discontinious and has some difficulties. The purpose of this study is to provide a plant transpiration map using satellite images and spatial modeling to identify the impact of environmental variables on transpiration in western Iran. First, by using the algorithm written in Google Earth cloud system, the plant vegetation translocation map was extracted as a dependent variable, and then the layers of solar radiation, water vapor pressure, wind speed and maximum temperature, vegetation index were selected as independent variables for modeling. The results showed that the prevalence of plant transpiration in the studied area range from 0 to 2.6 mm per day. Field data collected from 16 typical farms of Agricultural Research Center of Kermanshah and Kurdistan Provinces were used for validation and by comparing the map pixels and the ground data, the root mean square error and the Nash Sutcliffe coefficient were obtained to be 0.71 and 0.63, respectively. After implementing general regression and spatial regression models based on evaluation criteria, the spatial regression showed better explanatory and estimation power than the general regression. Based on this model, the coefficients of each variable were estimated spatially, making it possible to determine the spatial variation of the relationships between the variables. Also, the results of both models showed that the vegetation indices and water vapor pressure deficiency in western of Iran have the most positive effect on vegetation transpiration. Using the results of this study, areas prone to severe plant transpiration can be identified for improving the management of irrigation systems and providing intelligent agricultural services.

Soil salinity is an important environmental issue that reduces soil productivity. For optimal management of soil resources, quantitative monitoring of soil salinity, temporal changes and spatial analysis of the factors affecting it are necessary. The purpose of this study is to extract the soil salinity distribution map and its spatial analysis after more than normal rainfall in the rainy year of 1997-98 in western Iran. Using Landsat satellite imagery and GDVI index and algorithm written in Google Engine system, soil electrical conductivity map was extracted and classified into five salinity classes. The results showed that in general, soil salinity has decreased in the study area. Areas with high salinity that are in the low altitude class have not changed. If the precipitation factor in this study period is the most important factor in changes in salinity distribution, this factor could not have a great effect on the salinity class, but the medium salinity class had the most changes. Move the soil surface of this class down. For the ellipse, three times the standard spatial deviation of the northwest to the southeast was obtained, which shows that more than 99% of the salinity dispersion follows the spatial arrangement of altitudes, precipitation and dispersion of soil categories in this direction. Statistics of 0.4566 of Moran index and P_Value showed 0.00 spatial salinity of soil salinity in the west of the country. The hot-spot map also showed that the surface salinity of the soil is clustered in the northwest and southeast directions at altitudes of less than 1200 meters. Hot-spot analysis also showed that soil salinity to the east and inland has found more clustering pattern. The results and methods of this research can easily and quickly identify areas that are exposed to soil salinity and could be used in environmental planning to implement preventive measures. The results of this research are also used and its outputs are also utilized to identify soil salinity centers in agricultural planning and allocation of facilities.

In recent years, groundwater level has been descending due to climate change as well as method and use of them, especially in arid and semi - arid regions. According to the United Nations studies, Iran is considered one of the countries facing a shortage of water. In terms of climatic conditions, much of the country is but arid and semiarid regions. Water Table level control using observation wells are the main source of information to investigate the hydrological changes in these areas. Due to the recent drought and water shortages on a wide area of the country, the importance and sensitivity of groundwater management is increasing. Predicting the Water Table level using mathematical and statistical models can contribute significantly to proper planning and decisions to provide long - term water supply. In this study, the level of underground water using the gradient network and the transfer function of Tangent has been tried. Because of recent decades, neural network model studies show the high capability of this model in exploring the relationship between data and the recognition of patterns. Coppola and al (2003) investigated the possibility of predicting the level of 12 observation wells in different climatic situations, using artificial neural networks, in an area near the Temba Bay of Florida. Their results showed that, in modeling of the waters of the limestone and karstic areas, neural networks performed appropriate performance. diacplous et al. (2005)conducted an investigation to predict 18 months of groundwater level to predict an underground water level in the Mesrar Valley in Crete, Greece. The results indicate that the lonenberg algorithm is the most appropriate model.

The recent multi - year drought in the province of hormozgan has resulted in the aggravation of drought conditions and the imposition of many problems on water resources in particular in the underground reservoirs in particular. Sarkhoon Plain plain is one of the areas close to the provincial capital of hormozgan. In this paper, prediction of the spatial model of the Water Table plain of Sarkhoon Plain plain using artificial neural network method and Hyperbolic rule is used to investigate the fault level of this model. in this study, the data of ten observation wells during the 25 - year period of 1990 - 1387 to 1392 - 1392 of the regional water organization of hormozgan province have been used. Artificial neural networks are one of the computational methods that utilize the learning process using called Nero, by adjusting the weights, using the input - output samples that are available. This model is subsequently used to estimate the output value for the new data. The weight of the hidden layer and the output layer are changed so that the error rate is min. This error is represented as follows.
(1) E = 1 / 2 [(y - O) ^ 2]The following algorithm is illustrated in order to train the neural network.η > 0 and E > 0After implementation of neural network algorithms with different neurons in matlab software, the results of predicting the water height of Sarkhoon Plain with Hyperbolic transformation functions were obtained to determine the best spatial model of different levels of groundwater depth, the soil water models were used. in order to choose the best extrapolation method in this study, eight methods were used and finally the model that had the lowest fault was considered as optimal model.

In this study, neural network model was implemented with different neurons to predict the level of groundwater level. After reviewing the evaluation criteria, the neural network model was selected as the top model with 40 neurons in the latent layer and with its extension to observation wells a spatial prediction model was obtained from groundwater level. The very low error and the high correlation of this model, from the results of the test data, shows its efficiency in predicting the level of groundwater level. Using this algorithm for data of ten wells, water height was predicted for twelve months of 1400 year. The results of this research have proved the superiority of neural networks to numerical models, This spatial model can be used to control the rate of water harvesting in different locations for sustainable water resources management, to determine the structure of input parameters of the neural network, the effects of drought periods and the effects of parameters such as rainfall, temperature and evapotranspiration in predicting groundwater levels.

In this study, neural network model was implemented with different neurons to predict the level of groundwater level. After reviewing the evaluation criteria, the neural network model was selected as the top model with 40 neurons in the latent layer and with its extension to observation wells, a spatial prediction model was obtained from groundwater level. The results of diacplous et al. (2005) showed the superiority of lonenberg neural network over other models that have sufficient layers of latent layers, while it seems that the use of multiple latent layers with multiple neurons in different models leads to error reduction and the choice of superior model selection. Toarimino, Chua
  and Sethi (2012) emphasize the short - term forecasts of groundwater fluctuations. They have used the parameters of precipitation, evaporation - evapotranspiration and water level in the neural network model. Despite the higher parameters, the absolute mean of their superior model error has been higher than the average model error of the present research. It is probably due to the low intensity of the hidden layer neurons as well as their short time ranges. The results of the study indicate that the use of a neural network algorithm with the number of static neurons cannot be a measure of the performance evaluation of a model. This spatial model can be used to control the rate of water Picked up in different locations for sustainable water resources management, to determine the structure of input parameters of the neural network, the effects of drought periods and the effects of parameters such as rainfall, temperature and evatranspiration in predicting groundwater levels.

Background and Importance: 

Alkaptonuria is a rare genetic disorder due to deficiency of the enzyme homogentisic acid Oxidase which results in the accumulation of homogentisic acid in various body tissues; it produces a multisystemic disorder with a characteristic bluish-black discoloration of the skin and cartilage, termed ochronosis.

Herein, we reported A 45-year-old female patient presented to our outpatient clinic with chronic low back and left leg radiated pain that aggravated gradually in the previous six months. She also suffered from progressive muscle weakness in her left lower extremity. The patient was operated for prolapsed disc herniation. Macroscopically, no abnormality of the skin, muscles or ligaments was observed during surgery. After the annulus was incised, surprisingly it was seen that the nucleus pulposus removed from the L3-L4 disc space was black. The alkaptonuria was diagnosed after histopathological examination of the black disc material and also was confirmed by urinalysis.

The postoperative course was uneventful and the patient was free from low back and leg pain after surgery. In patients with no other signs of alkaptonuria or ochronosis such as our case, early detection of this rare disease is important to asses and treat the involvement of other systems (e.g., cardiovascular and urinary).

Increasing the earth temperature causes anomalies in the planet climate, which affects all aspects of human life. In this study, the determination of temperature changes and the most appropriate model for estimating temperature changes was carried out using the SARIMA time series model in Isfahan. For this purpose, the long-term monthly average temperature of Isfahan during the years 1951-2017 were used in MINITAB software medium. Then, using the time series, an initial guessing pattern was extracted as follows: SARIMA (0, 0, 4) (0, 1, 1) 12 and SARIMA (4, 0, 0) (5, 1, 0) 12 trail and error. The method of the goodness of fit these two patterns resulted in a final pattern SARIMA (1, 0, 1) (0, 1, 1). In the next stage, accuracy and preciseness of this model were confirmed by AIC statistics and analysis of self-correlation charts, the histogram of residual patterns, and other parameters. Finally, based on fitted models, the forecast was made for the next 10 years. The results of this study indicate that these models had almost good accuracy for predicting temperature changes over the coming years. In addition, the assumption of the independency of the residuals was confirmed by the correlation between the model and the remainder of the model due to the inclusion of all self-correlations in their standard limits, and then the histogram of the residual parts of the M1 pattern showed normalilty of the data.

This study aimed to compare the effect of three method of open discectomy, and nucleoplasty with and without ozone injection on the healing, complications, and postoperative pain in patients with lumbar disc herniation.
In this clinical trial study, 180 patients with intervertebral disc herniation were divided into three groups of 60 patients. The first group was operated using open diskectomy method, and the second and third groups were operated with nucleoplasty with and without ozone injection. The severity of pain, relapse symptoms, and postoperative complications were followed up to 24 months later, and compared between the three groups.
Findings: The severity of back pain at preoperative, 14 days, and 1 and 3 months after operation was not significantly different between the three groups; but 24 months after surgery, patients with open discectomy had lower pain severity (P = 0.029). Up to 24 months later, 12 patients needed re-operation, 2 (3.3%) of nucleoplasty with ozone injection group and 10 (16.7%) of the nucleoplasty without ozone injection group, and the difference between the three groups was significant (P = 0.001).
It seems that the use of open discectomy method, in comparison with nucleoplasty with or without gas injection, is associated with a higher rate of cure and a less recurrence rate; although open discectomy is not accompanied by a getting rid of bed quickly, but had less therapeutic costs and less need for reoperation.

Although operation is the most appropriate treatment for Cauda Equina Syndrome, the effectiveness of operation on clinical symptoms is still under discussion. This study aimed to determine the prognosis of Cauda Equina Syndrome in patients with lumbar disk surgery in Al-Zahra Hospital of Isfahan City, Iran, from 2013 to 2015. Methods and Materials/ Patients: In This prospective study, patients diagnosed with Cauda Equina Syndrome who underwent operation in Al-Zahra Hospital of Isfahan from 2013 to 2015 were followed up for two years and the effect of the surgery on the improvement of their clinical symptoms was investigated. In this study, 33 patients with Cauda Equina Syndrome were evaluated. About 24-month follow-up of patients showed muscle weakness improvement in 26(78.8%) of them. Of all 19 patients with urinary dysfunction, 18(94.7%) recovered. Six (33.3%) cases improved the day after surgery, 6(33.3%) cases in one month, 4(22.2%) cases in six months, and 2(11.1%) cases within 24 months after the surgery. All 4(100%) patients with bowl disorder also recovered during the study. One (25%) of them improved the day after operation, 1(25%) one month after the operation and 2(50%) within 24 months following the operation. According to the results of this study, operation of the lumbar disks leads to improvement of Cauda Equina Syndrome, including recovery of sphincter disorders and muscle weakness, but considering the limitations of our investigation (including a small sample size), further studies are recommended in this area.

Surgical Site Infection (SSI) is one of the most important complications after spine surgeries. Different methods have been proposed to prevent this type of infection. The present study was performed to evaluate the effect of applying topical vancomycin powder on prevention of SSI in patients undergoing spinal surgery using implants in Al-Zahra Hospital, Isfahan, Iran from February 2015 to June 2016.
Methods and Materials/Patients: In this clinical trial, 100 patients candidate for spinal surgery with implants were divided into two groups using randomization technique including 50 patients in each group. Vancomycin powder solved in 20cc N/S serum was flushed over all layers of the surgical wound in the case group and in the control group sterile normal saline solution was used. Patients were examined at discharge and three months after surgery for ruling out surgical site infection. SSIs following spine surgery can be superficial, characterized by obvious wound drainage and erythema or it can be deep infections disseminating under the fascia which may lead to discitis, epidural abscess, and spondylitis.
One case of SSI was observed in the control group who was 83 years old. The mean age of all patients was 51.9±14.5 years old. The duration of surgery in this patient was 5 hours. The mean duration of surgery was 3.41±0.73 hours. The length of implant, BMI, sex, underlying diseases and other risk factors (diabetes and hypertension) did not affect the rate of infection.
Even though topical antibiotics seem to be effective on controlling SSI but our finding did not support this hypothesis. The authors would like to suggest that keeping routine strict sterility strategies during spine operations is effective enough in preventing surgical site infection.

Determining the status of distribution of wildlife species, habitats under their occupation and habitats which have conditions for the presence of species is of great importance in the wildlife management. In order to model the habitat suitability of Persian gazelle (Gazella subgutturosa subgutturosa) presence/absent method by using Multi-Layer perceptron (MLP) neural network was used. In order to modelling in Qaraviz No Hunting Area (autumn and winter seasons) and potential dispersion in Kermanshah province the presence points of the species and 14 and 12 environment variables were used, respectively. Model validation was performed by ROC statistic which was 0.87, 0.84 and 0.78 for autumn, winter and entire province and it was confirmer of MLP model. The results of sensitivity analysis showed that distance from road, spring and trough and military areas in autumn and variables of Altitude, distance from tribal areas and vegetation types in winter have the most influence on the specie distribution and variables of height, temperature and vegetarian type were the most effective factors on the specie distribution in large scale. Pearson correlation coefficient indicated significant correlation of 0.83 between habitat suitability of autumn and winter (P

Assessing pollution of coastal sediments is environmentally and ecologically important. Therefore, the aim of this study was to determine environmental pollution and to prepare the geochemical distribution map of elements in the coastal sediments of Hormoz Island at the north of Hormoz Strait. For this purpose, 27 sediment samples were taken to a depth of 10 cm from the surface sediments. These samples were analyzed for the elemental composition using X-ray fluorescence method (XRF). The elemental spatial distribution was mapped using linear Kriging method in GIS environment. The sediments mineralogical analysis using XRF showed that the sediment is mainly consisted of a collection of minerals such as hematite, calcite, quartz, feldspar, plagioclase, dolomite, aragonite, clay minerals and heavy minerals. Calculating the Muller environmental indices (Igeo) and enrichment factor (EF) showed that the sediments of the coastal strip of the Hormuz Island are contaminated with Cr, As, and Pb. Based on the sedimentology and sedimentary geochemistry on one hand and refereeing to interpreting the distribution maps on the other hand, it became clear that alteration and erosion of rock units exposed in the center of the Hormuz Island series under hot and humid weather conditions are the source of these elements. Source of chromium is caused by anthropogenic activities.

Artificial recharge of groundwater plays a pivotal role in the sustainable management of these resources. Sarkhoon plain in Hormozgan was carried out using geographic information system and combining it with the Shannon entropy and a pair-wise comparison test. For this purpose, 9 affecting elements of, water quality, water depth, permeability coefficient, thickness of alluvium, land use, transfer capability, land morphology and drainage density were selected and prepared. Then using entropy method and pair-wise comparisons, the weight of each standard and the classes of each layer were calculated. Next, the areas with constraint for flood spreading are removed and finally the entire area was divided and zoned into four classes using GIS analytical functions and Jencks algorithm. Results showed that drainage density factor weighing 0.211 is the most important factor for locating flood spreading in Sorkhun plain. Areas suited for flood spreading are frequently located at the morphological units of alluvial fan in the north part of the plain, with slopes of less than three percent, and allocated approximately 17.70% of the plain. Evaluate the results by comparing the successful implementation projects in the region was 78 percent overlap model can lead to weight each criterion in considering the impact of the uncertainty, Which can enhance the accuracy of the model output.

As special depositional environments which are adjacent to the seas, deltas have provided a field for human habitat establishment. Geomorphic features of deltas are in constant transformation due to their dynamic features. Constructing dams on rivers can intensify these changes and cause either negative or positive consequences. Minab delta in Hormozgan Province of Iran is a round or crescent-shaped delta which has Esteghlal Dam constructed on its creating river. Minab Dam is constructed upstream of Minab Delta in Hormozgan Province. The research aimed to derive landscape metrics of delta and assess their changes before and after the construction of dams. Landsat Satellite images of 1983 and 2013 provided the four classes as abandoned delta, active delta, subaqueous deltaic plain and aquatic environment, using maximum likelihood method, with a Kappa Coefficient accuracy of 86.55 and 88.42 for revealing changes quantitatively. To quantify landscape metrics, percentage of landscape (PLAND), Number of Patch (NP) and Mean Patch Size (MPS) metrics were computed. As indicated by the results, the NP metric increased in all the classes except active delta, and all classes showed a reduction in MPS metric. The amount of NP, Mean Nearest Neighbor (MNN) and Largest Patch Index (LPI) increased to the 22, 19 m and 1.43 percent, respectively, which clearly reveals landscape fragmentation, along with growing NP metric and a reduction in MPS.

Environmental pollution, and the price fluctuations of fossil energy sources are used in power plants would have to turn to alternative energy sources. Use of sustainable energy, especially solar energy can be the best option for energy in plants. The first step is to expand the use of solar energy is to locate areas where solar power and other desirable plants meet the requirements, it has. Province to exploit the potential of solar energy. Criteria used in locating suitable areas in the province of sunshine, slope, away from the crowds, away from roads, away from power lines, land use and limitations layer was considered. Extract the required information from various sources and a layer of intelligence to the software environment ACGIS10 were introduced. Criteria weights are derived using Analytical Hierarchy Process and Fuzzy model was used to combine the layers. The area of 22524.115 square kilometers of the province in very good class for solar thermal power plants were constructed.

Increase inwater demand will likely be followed by increased pressure on groundwater resources in the short term and long term. At this time, spreading floods on the aquifers is one of the appropriate methods tocontrol and optimal use of floods and artificial recharge of groundwater resources in arid and semi-arid regions. Sarkhoon plain is one of the plains close to the center of HormozganProvince whereits groundwater has been supplyingthe regional needs for water, so far. A look atthe hydrologic statistics of recent years indicates negative water balance in the plain.Thisreveals the importance of sustainable management of water in the region. The purpose of this study was to determine the importance of factors effective in identifying the areas prone to artificial recharge in Sarkhoon plain by using network process analysis and determining appropriate areas for operations of artificial recharge using GIS in combination with the network process analysis. Thus, byidentifying the areas prone to spreading floods and proposal for constructing structures, the wasting of water resources in the region will be prevented. Thus,some progress can be made in planning for sustainable development of water resources.
Sarkhoon study area is located at almost 25 km from Bandar Abbas, HormozganProvince, with an area about 11,400 ha. The estimated average annual rainfall valuesin theplains were234 mm and 219 mm, respectively. The groundwater level changes in Sarkhoon plain during a period of 25 yearsfrom1990-1991 to 2013-2014 accounted for 0.5 m of the annual drop.( pic1)
Materials and In this study, 9 influencing factors of slope, water quality, water depth, permeability rate, alluvium thickness, land use, transferability, geomorphology and the drainage density were selected and analyzed. Then, the paired comparison method to determine the weight of classes of each layer and the ANP method were used todeterminethe final weight of the criteria. The Super Decision software was also used to determine the weights. After omission of the areas with limitation, the areas prone to flood spreading operation were determined.The appropriate criteria for flood spreading operation in SarkhoonPlain are:Slope: To prepare the slope layer, the digital elevation model (DEM) with a pixel size of 30m is extracted from ASTER data.(pic 2)
Geomorphology: From the morphological map of the province, the study area was separated and divided into four classifications.(pic 2)
Water depth: Water depth map was obtained with minimum error using the 10-year average water levels data related to observation wells and generalizationto the whole plain using interpolation algorithm by Kriging spherical model.(pic 2)
Alluvium thickness: The mentioned layer was re-classified into four classes. (pic 2)
Alluvium transferability: The water transferability map of Sarkhoon plain water was prepared according to the existing pumping test results of 10 Piezometers in the plain (Hormozgan Regional Water) with interpolation by Kriging spherical model in the ARCGIS 10 platform.(pic 2)
Land use: The land-use layer for the study area was obtained from 1:25000 maps and updated by using ASTER satellite images combined with bands 1, 2, 3 as well as Google Earth images, and were classified into four categories.(pic 2)
Water quality: In this study, the data of observation wells wereused to provide the electrical conductivity layer of Sarkhoon plain area.(pic 2)
Drainage density: The cumulative flow layer was extracted from regional DEM, and then, the channel density layer was obtained. It was classified into six classes.(pic 2)
Permeability coefficient: To determine the permeability of the study area, the tests results provided by the Agricultural Research Center of Hormozgan province in 2009 were used, and the permeability layer was produced by interpolation.Itwas also re-classified into 5 categories.
Identifying the areas with limitation: In the present study, according to research in this field and the region local conditions, three layers of slope, geomorphology and land use were identified as layers with limitations.
Analytic network process (ANP): This model is one of the multi-criteria decision-making techniques classified in compensatory models series. The most important distinction between this method and the hierarchical approach is in the influenceand effectiveness of criteria on one another. Inthis hierarchical structure model, a target or a node is initially located that finally ends to a destination node or cluster. Therefore, there is a linear structure from top to bottom and without returning from lower or higher levels. But in the network structure, the network and its clusters are not distributed on a regular basis. In addition, there should be the possibility of a cluster being influenced by itself (interdependence) or affectinganother cluster (external dependency).Direct returning from the second cluster or passing through the middle cluster is possible.
Results and Examination ofthe weights of criteria in this study indicatedthat the drainage density factor with a weight equal to 0.274 is the most important factor in locating of flood spreading in SarkhoonPlain. After integration, the value of each cell was determined. To attain better results, using the natural breaks method, the whole land was divided into five final categories based on the zoning map. From the total area of Sarkhoon plain, about14.2576 square kilometers and 45.0283 square kilometers were determined as very suitable and suitable areas,respectively, for flood spreading operation. The results indicatethat most of the perfectly suitable and suitable areas occur in the category of 0-3% and 3-5% regarding the slope. Regarding the measure of depth, the perfectly suitable and suitable areas are located at depths greater than 68 meters. Also, these areas are in accordance with the ranges with higher transmissibility rates. Regarding thickness measure, the alluvium is located in a range greater than 60m. Also, the zones are located in the areas with higher permeability coefficients (18-24 and 24> m per day). Regarding electrical conductivity layer, the suitable and perfectly suitable areas are located within the scope with EC less than 2000 micromhos /cm. In terms of land use layer, the lands are located in the areas with pasture usage and drainage density less than 3.8 km per square kilometers.
Planning to use floods, meanwhile to reduce their destructive effects, will provide a new water source for the consumers. In the studies with similar research subject, the AHP method was used to determine the weights of criteria in such method.The criteria relations and their coefficient of impact are not considered to reduce the accuracy and quality of the work. Since the ANP method deals with the dependencies systematically, i.e., it considers all internal and external dependencies between the elements and clusters for analysis, but other methods consider these relationships. Thus, withthe interdependence of environmental issues (including this study subject), the use of ANP method can provide the necessary supports for decision-makers and planners tosolvewater management issues to gain a deeper understanding of environmental issues.

Wolf (Canis lupus) is the largest of the canidae in Iran, is considered opportunistic species with high compatibility and one of the main predator of ungulates in their habitats. It seems wolves prefer habitats which have a decent population of ungulates. Persian Gazelle (Gazella subgutturosa) is the largest herbivore in Iran's steppe plains. Habitats of Persian Gazelle in the west of Iran and in Qaraviz no hunting area adjacent to country of Iraqproportional to the dispersion mounds. In this investigation area boundary were considered equal to ultimate limit of distribution of gazelles During the summer and autumn seasons of 2013. Data of wolf attacks points was collected and it is divided into two sets, training data and test data. Then entered the model (Maxent) as geographic information system along with summer and autumn habitat suitability maps, Gazelles density and other 8 variables. The results of the score matrix and Jackknife analysis have characterize that distance from water sources and springs is the most important factor in habitat suitability of the summer and autumn and also possibility of the wolf spatial attacks. The results of the receiver operating characteristic (ROC) analysis and the area under the ROC curve (AUC) in the average runs, characterized which model has been successful in the prediction of attacks (AUC=0/949). Results show that areas with high-gradient, the high density of gazelles, near to the springs and watering places and north directions, have high-risk of Wolf attacks.

The purpose of this study was investigate the overwintering Scolopacidae population in the two regions Hara Protected Area (HPA) and Haray Tiab and Minab (Kolahy, Hasan langhi and tiab Estuaries) in the Hormozgan Provence between 2007 and 2012, respectively. According to the results of a 6-year period, A total of 22 species from Scolopacidae have overwintering in the study Areas Which the number of species observed in the HPA and Kolahy, Hasan langhi, and tiab Estuaries was 20,20,17,19 species. Among the species identified from the Scolopacidae In the period that was studied, Two species Dunlin(Calidris alpina) and Eurasian Curlew(Numenius arquata) Respectively 41/08 and 17/26 percent of total observations, were The most abundant species. According to the findings of this study the most observed population was related to HPA(37054 Bird) And the lowest was in the kolahy eustary (5949Bird). Evaluation of biodiversity index and diversity graph sorting by Renyi method showed Hassan langhi estuary with species diversity indices Shannon-Wiener’s(2/18) and Simpson’d(7/14), And The values for Species Abundance(17) and indexes of the evenness Pielou J (0/69)and McIntosh E(0/82)compared to Other areas the has higher biodiversity (P<0/05) And been able to provide the suitable habitat for Scolopacidae. On the other, Analysis of Similarity Percentages(SIMPER) for Hara protected area and Kolahy, Hasan langhi and tiab Estuaries in Ordering was %61/11, %55/89, %46/20 and%63/75. Analysis of Similarity(ANOSIM) Indicated that between HPA and and Kolahy, Hasan langhi and tiab Estuaries And Also Between Hasan langhi estuary And Kolahi estuary There is significant difference between the relative similarity of the total observations (P<0/05). Distribution of the of species in the HPA and tow estuary of Kolahi and tiab from Logarithmic series distribution model and in Hasan langhi estuary from Broken stick model were subordination.