Northwestern Part Of Iran Research Articles

Assessment of Sustainability in Water Supply-Demand Considering Uncertainties

Water is a vital resource for life on earth; hence its maintenance is very important. Different regions especially in arid and semi-arid areas are facing population growth and subsequent increase in the domestic, industrial and agricultural activities. Planning of water systems in order to be ready for future development conditions needs further studies on the estimation of the sustainable levels of demands based on the sustainable levels of supplies. In this study a threefold approach for estimating sustainability level of supply and demand in Ahachay river basin in northwestern part of Iran as a case study is taken. In the first method, the internal flows and the origins and final uses of the total resources for each subsystem are estimated and planning for sustainability use index is determined by calculating the available water. Second method introduced a simulation model which is utilized to estimate reliability, resiliency, vulnerability and maximum deficit for a river basin to determine a group sustainability index. In the third method, for evaluating the movement toward sustainability, an index is developed. This index includes parameters that are the difference between supply and demand, percentage of the satisfied demand, productivity of water resources and an indicator for evaluating the reduction of aquifer storage. Finally these methods are compared and a hybrid index combining the indices is developed. An uncertainty analysis is also performed to investigate the random nature of variables in estimating water balance and quantifying the water sustainability. This hybrid index can be used for evaluating the planning scenarios and for maintaining and improving the sustainable state of supply-demand for the region.

The impact of organic manure and nano-inorganic fertilizers on the growth, yield and oil content of sunflowers under well-watered conditions

The sunflower is the third most important source of edible oil and accounts for about 14% of world production of seed oils. Although the sunflower is well adapted to semi-arid regions, low soil fertility and nutrients deficiencies are important yield-limiting factors for sunflower production. The current experiment was carried out to study the effects of farmyard manure (zero (M1), 20 (M2) t ha−1) and nanostructured fertilizers (Mn, Fe, Zn ) on the agronomical traits, yield and yield components of the common sunflower (Helianthus annuus L.). The experiment was conducted during 2015–2016 growing seasons at a research field in Maragheh in the north-western part of Iran. Application of farmyard manure significantly improved such agronomic traits as plant height, leaf area, the number of leaves, the internode length, the stem diameter, the diameter of the branch head, the number of branches, the length of branches, achene length and achene width, the main capitulum diameter, 100-achene weight, oil content in an achene compared with non-manure condition. Results revealed that plants grown under M2 showed earlier flowering and possessed a higher chlorophyll concentration in leaves. Moreover, application of nano-chelated Zn and Fe considerably decreased the proportion of empty achenes and increased oil concentration, the achene yield and the harvest index. However, the best performance was obtained by combined application of nano-chelated Zn under manure conditions. The findings pointed to the importance of micronutrient deficiencies and balanced nutrition in this area. The overall results show that the integrated application of organic manure and nano-chelated micronutrients are more effective in improving the yield of sunflowers in semiarid production systems.

Prediction of Water Level using Monthly Lagged Data in Lake Urmia, Iran

Prediction of water level fluctuations in lakes is a necessary task in hydrological and limnological studies. Lake Urmia, a hyper-saline lake in the North Western part of Iran, is dealing with a gradual atrophy. In this study, parametric and nonparametric models are used for predicting monthly water level fluctuations in Lake Urmia. Eleven previous water levels in the form of monthly lagged data are used as the known independent variables of the model while lake water level at the twelfth month is considered as the unknown dependent variable to be predicted. Parametric models used in the modelling are multi-linear regression (MLR), additive and multiplicative non-linear regression (ANLR and MNLR) and decision tree (DT) while feed forward back propagation neural network (FFBP-NN), generalized regression neural network (GR-NN) and radial basis function neural network (RBF-NN) are used to represent the non-parametric approach. Monthly water level data in Lake Urmia observed for 1966–2010 are used for the case study. Four criteria, coefficient of determination, Lin’s concordance correlation coefficient, performance index and root mean square percentage error are used in comparison of the models. The first two are considered for the success of the models while the last two for the failure. Success criteria are given a grade between 0 and 10, failure criteria receive a grade from −10 to 0. The summation of the grades is taken as the total grade of each model. It is found that regression models and FFBP-NN are superior to GR-NN, RBF-NN and DT in predicting monthly lake water level.

West Nile Virus in Mosquitoes of Iranian Wetlands.

The West Nile virus (WNV) transmission cycle includes a wide range of migratory wetland birds as reservoirs, mosquitoes as biological vectors, and equines and humans as dead-end hosts. Despite the presence of potential vector species, there is no information about the existence of WNV in mosquito vectors in Iran. The Iranian West Azerbaijan Province is located in the northwestern part of Iran and has borders with Turkey, Iraq, Armenia, and the Republic of Azerbaijan. The current study was conducted to identify the wetland mosquitoes of the West Azerbaijan Province and their infection with WNV. In this study, 2143 specimens were collected, comprising 1541 adults and 602 larvae. Six species belonging to four genera were collected and identified: Anopheles maculipennis sensu lato (s.l.), Culex (Cx.) hortensis, Cx. pipiens s.l., Cx. theileri, Culiseta longiareolata, and Aedes (Ae.) (Ochlerotatus) caspius. In total, 45 pools of mosquitoes were examined. Two of the adult pools collected from the same location showed the presence of WNV in Ae. (Och.) caspius, from Sangar, Makoo County, as confirmed by PCR and sequencing. Due to the discovery of WNV in the mosquito population of the region, and the presence of wetlands and significant populations of migratory birds, the health sector should carefully monitor the factors involved in the cycle of this disease.

Incorporating seepage losses into a 1D unsteady model of floods in an ephemeral stream

Zangemar River is an ephemeral river located in the northwestern part of Iran. Maku and Poldasht are hydrometric stations located upstream and downstream of Zangemar River, respectively. The measured flood hydrograph indicates that the output hydrograph volume from Poldasht station is significantly less than the input hydrograph for Maku station, though there are no lateral outflow branches and the amount of evaporation and direct removal from the river reach during flood events is negligible. These transmission losses can be caused by infiltration into the streambed and floodplain. Due to transmission losses and lack of initial flow, flood routing in these rivers is impossible to achieve through conventional methods and it is essential to develop new flood routing methods. Therefore, in this study a computer model for natural river cross-sections has been developed in which partial differential equations of non-uniform unsteady flow (Saint-Venant equations) are solved by finite difference methods. These equations have been developed by adding Muskat’s equation in such a way that seepage losses can be calculated simultaneously. The results showed that with consideration of seepage losses the developed model can predict the output hydrograph with good accuracy, compared to the field data. The results of flood routing for 13 input hydrographs showed that the seepage loss volume in the river reach is about 74% of the input hydrograph volume, on average. The model predicts seepage losses with a mean error of about 9.93% and the maximum error is less than 20%.Keywords: flood routing, seepage losses, unsteady flow, Zangemar River

Uncertainty based analysis of the impact of watershed phosphorus load on reservoir phosphorus concentration

Summary In many regions of the world that depend on surface reservoirs as a source of water supply, eutrophication is a major water quality problem. Developing simulation models to evaluate the impact of watershed nutrient loads on the reservoir’s water quality is an essential step in eutrophication management. In this regard, analysis of model uncertainty gives an opportunity to assess the reliability and the margin of safety of the model predictions for Total Maximum Daily Load (TMDL) from the watershed nutrient load. In this study, a computational procedure has been proposed for the analysis of the model uncertainties in simulation of watershed phosphorous load and reservoir phosphorous concentration. Data from the Aharchai watershed which is located upstream of the Satarkhan reservoir in the northwestern part of Iran, is used as the study area to test the effectiveness of the proposed methodology. The Soil and Water Assessment Tools (SWAT) is utilized for assessment of watershed phosphorus load as the main agent resulting in the reservoir eutrophication in the region. The most effective parameters in model performance are identified by a global sensitivity analysis technique named modified Fourier Amplitude Sensitivity Test (FAST) which can incorporate parameter interdependencies. The Generalized Likelihood Uncertainty Estimation (GLUE) technique is also applied to set up behavioral ranges of the parameters that are relevant to the actual observations. Finally, the cumulative weighted-likelihood distribution functions (CWLDF) are derived for outputs of the SWAT. They are used jointly for estimation of results uncertainty limits using the Copula method. To assess the effectiveness of applying Best Management Practices (BMPs) in the watershed, two scenarios of with and without BMPs application are tested. The results showed the effectiveness of the proposed model in uncertainty estimation of watershed phosphorus load and reservoir phosphorus concentration as well as the effectiveness of BMPs in reducing P loads from the watershed.

Environmental modelling of visceral leishmaniasis by susceptibility-mapping using neural networks: a case study in north-western Iran.

Visceral leishmaniasis (VL) is a potentially fatal vector-borne zoonotic disease, which has become an increasing public health problem in the north-western part of Iran. This work presents an environmental health modelling approach to map the potential of VL outbreaks in this part of the country. Radial basis functional link networks is used as a data-driven method for predictive mapping of VL in the study area. The high susceptibility areas for VL outbreaks account for 36.3% of the study area and occur mainly in the north (which may affect the neighbouring countries) and South (which is a warning for other provinces in Iran). These parts of the study area have many nomadic, riverside villages. The overall accuracy of the resultant map was 92% in endemic villages. Such susceptibility maps can be used as reconnaissance guides for planning of effective control strategies and identification of possible new VL endemic areas.

Genetic Variations of Tumor Necrosis Factor -α-308 and Lymphtoxin-α+252 in Non-Hodgkin Lymphoma and Acute Lymphoblastic Leukemia Patients.

Non- Hodgkin lymphoma (NHL) and acute lymphoblastic leukemia (ALL) are two main hematological malignances which have been driven from lymphoid tissue. Genetic polymorphisms in tumor necrosis factor-α (TNF-α) -308 and lymphotoxin-α (LT-α) +252 may affect their transcription and expression which leads to their high plasma level. The frequency of the TNF-α (-308) and LT-α (+ 252) polymorphisms are different for NHL and ALL cases in various populations with different ethnicity. This research is designed to investigate the prevalence and association of TNF-α (-308) and LT-α (+ 252) polymorphisms from NHL and ALL in Azarian patients and healthy individuals from Northwestern part of Iran. Seventy subjects with ALL and 68 NHL, along with another 130 healthy subjects as control group took part in this study. Genomic DNA was extracted, then genetic polymorphisms in TNF-α and LT-α genes were analyzed with the PCR-RFLP and NCOI as restriction enzyme. A statistical analysis was performed by chi-square test using SPSS software. A P-value of <0.05 was considered statistically significant. A statistically significant difference of LT-α polymorphism was in NHL patients and control (P-value= 0.008) but there was not any association of TNF-α polymorphism between NHL patients and control group. A significant association for TNF-a variant was in ALL and control (P-value =0.005), however, there was no relationship about LT variant between ALL and control. The results show that there are significant differences between TNF-α (-308) and LT-α (+252) genetic polymorphisms respectively in ALL and NHL patients with control group from Northwestern part of Iran.

HBsAg Mutants Clustered Mainly Outside of “a” Determinant in Chronic Carriers From Azarbayjan Province, Iran

: Background: Hepatitis B virus (HBV) genetic and protein variations have been observed in chronic patients frequently. However, their role in the pathogenesis of chronicity has not been explored yet. Objectives: The aims of this study were to determine the genotypes as well as the patterns of variations distribution in chronically infected patients from the north western part of Iran. Materials and Methods: The surface genes from 17 chronic carriers were amplified, sequenced and subsequently aligned using international and national Iranian database. Results: All strains belonged to genotype D, subgenotype D1 and subtype ayw2. Of all 56 “mutations” that occurred at 37 nucleotide positions, 25 (44.6%) were missense (amino acid altering) and 31 (55.4%) were silent (no amino acid changing) (S/M ratio: 1.2). At the amino acid level, 21 (91.3%) out of 23 amino acid mutations occurred in different immune epitopes within the surface proteins, of which 3 (14.3%) occurred in B cell, 8 (38%) in T helper and 10 (47.7%) inside CTL epitopes. In general, the association between amino acid mutations and especially, immune epitope substitutions was more significant in terms of HBeAg status than ALT levels in patients. Conclusions: The distribution of amino acid mutations as well as the ratio between missense and silent nucleotide mutations (dN/dS) showed that a narrowly focused immune pressure had already been on the surface protein (especially CTL epitopes) which led to the emergence of escape mutants in these patients who were in tolerance phase of chronicity.

Landsat ETM+ imaging for mineral potential mapping: application to Avaj area, Qazvin, Iran

The Avaj area is located in the northwestern part of Iran, on the boundary between the Orumieh-Dokhtar and Sanandaj-Sirjan geological zones. It corresponds to two different geological sub-zones:Abe-Garm, to the north, which is related to the volcanic belt of Orumieh-Dokhtar; and the Razan sub-zone, to the south, which is related to the Sanandaj-Sirjan zone. Lithological aspects of different rock units indicate the presence of four distinct volcanic groups of andesite, basalt, tuff, and dacite. The present research utilizes various Landsat Enhanced Thematic Mapper Plus (ETM+) image-processing techniques, including false colour composite images, colour composite ratio images, and standard principal component (PC) image analysis on six bands and colour composite selective PC images, filtering and supervised classification. Nonetheless, colour composite selective images may be the most reliable method for enhancement of areas with hydrothermal alteration. All the techniques used clearly show the pervasive alteration of kaolinite-argillite in the area. These alterations are mainly related to the andesite, and tuffs have the same trend as fault directions.

Tephritis azari, a New Fruit Fly (Diptera: Tephritidae) from Iran and Azerbaijan, with a Key to the Tephritis maccus Species Group

Tephritis azari sp. nov., from mountains of the northwestern part of Iran and Azerbaijan is described and illustrated. It is closely related to T. maccus Hering and T. urelliosomima Korneyev &amp; Dirlbek based on characters of the wing pattern and aculeus. In addition a key to the species of the T. maccus species group has been provided.

Influences of rural industries on sustainable social and environmental developments

This article is a case study among the owners of cheese-making industry in Lighvan Village of Tabriz City, located in the northwestern part of Iran in Azerbaijan Province, dealing with the effect of rural industry and socio-cultural indices influencing sustainable environmental development. The results were based on two different studies. The volume of the sample denotes the volume of the statistical population (N = 150). The present survey was conducted by means of some questionnaires and interviews during spring 2011. The results of testing the hypothesis as well as the correlation indicated: (a) significant correlation between the rates of empathy and rural environment sustainable development; (b) significant correlation between the rate of innovation and rural environment sustainable development; (c) significant correlation between the rate of providence and rural environment sustainable development; (d) significant correlation between the rates of social trust and rural environment sustainable development; (e) significant negative correlation between the rate of fatalism and rural environment sustainable development; (f) significant negative correlation between the rate of nepotism and rural sustainable environmental development; (g) significant correlation between rural industry and sustainable environmental development; and (h) significant correlation between rural industry and socio-cultural indices.

P-244 - On the relationship between coping strategies and mental health of diabetic patients

Diabetes Mellitus is one of the common chronic illnesses, which endanger patient's mental health. We think there is a meaningful relationship between Diabetes and occurring the Mental diseases. The present study was planned to assess the relationship between diabetic patients' mental health and coping strategies. In this cross-sectional study 193 patients who were referred to diabetes clinic of Imam Khomeini hospital of Ardabil city in north western part of Iran were selected by available sampling method and assessed by GHQ-28 and Folkman-Lazarus questionnaires. Data were analyze by SPSS version 13 software ,using logistic regression analysis and independent t tests. Results showed that 54% of diabetic patients are suspected to have a mental disorder and need more diagnostic assessments .Escape-avoidance (P < 0.001), confronting (P < 0.001) and plan-full problem solving coping strategies could predict the mental health in diabetic patients. Inappropriate and emotion-based coping strategies against medical illnesses-such as escape-avoidance method as a predictor of diabetic patients' mental health-throw patients in vicious cycle of medical and mental illness.

Development of a Demand Driven Hydro-climatic Model for Drought Planning

In recent years, droughts with increasing severity and frequency have been experienced around the world due to climate change effects. Water planning and management during droughts needs to deal with water demand variability, uncertainties in streamflow prediction, conflicts over water resources allocation, and the absence of necessary emergency schemes in drought situations. Reservoirs could play an important role in drought mitigation; therefore, development of an algorithm for operation of reservoirs in drought periods could help to mitigate the drought impacts by reducing the expected water shortages. For this purpose, the probable drought’s characteristics and their variations in response to factors such as climate change should be incorporated. This study aims at developing a contingency planning scheme for operation of reservoirs in drought periods using hedging rules with the objective of decreasing the maximum water deficit. The case study for evaluation of the performance of the proposed algorithm is the Sattarkhan reservoir in the Aharchay watershed, located in the northwestern part of Iran. The trend evaluations of the hydro-climatic variables show that the climate change has already affected streamflow in the region and has increased water scarcity and drought severity. To incorporate the climate change study in reservoir planning; streamflow should be simulated under climate change impacts. For this purpose, the climatic variables including temperature and precipitation in the future under climate change impacts are simulated using downscaled GCM (General Circulation Model) outputs to derive scenarios for possible future drought events. Then a hydrological model is developed to simulate the river streamflow, based on the downscaled data. The results show that the proposed methodology leads to less water deficit and decreases the drought damages in the study area.

Optimization of Watershed Control Strategies for Reservoir Eutrophication Management

A vital key to the development of a reservoir eutrophication management strategy is to link the watershed-nutrient model to the model of reservoir water quality. To develop a cost-effective optimization model, a coupled watershed-reservoir model with an optimization model has been developed to design control strategies in the watershed in a planning time horizon. This methodology can help reduce the phosphorus concentration of a reservoir to the standard level. In this study, the weather data for the next 10 years was generated using downscaled GCM data to simulate the watershed phosphorus load using the SWAT model. Then an optimal model for selection and placement of best management practices (BMP) at watershed scale is developed by linking the coupled watershed and reservoir models with a genetic algorithm. This model is able to identify the minimum present cost design (type and location) of BMP structural alternatives. The objective of water quality is obtained using a system dynamic model for reservoir phosphorus concentration to determine a permissible phosphorus load as the main agent of eutrophication in a reservoir. Structural BMPs in this study include, filter strips, parallel terraces, grade stabilization structures, and detention ponds. The optimum solution was obtained through a trade-off curve between cost and exceedance magnitude from the standard of reservoir phosphorus concentration. The case study is the Aharchai River Watershed upstream of the Satarkhan Reservoir in the northwestern part of Iran.

The case report on squamous cell carcinoma in Oscar (Astronotus ocellatus)

The presence of squamous cell carcinoma is reported in an Oscar (Astronotus ocellatus) from Urmia (north western part of Iran), Iran. Clinical observations revealed a small pink nodule (1 × 1 mm) on the right-hand side of the fish's lower mandible with a gradual increase in nodule size. After 2 months, the nodule was as large as 1 × 1 cm in size with a white-to-cream colouration. By this time, two similar nodules had formed on the ventral surface of lower mandible. At similar high risk sites around the mouth, another single nodule on the mandible adjacent to the operculum was found. The disorder caused an irregular mouth shape that consequently resulted in the fish unable to close its mouth. All mentioned sites were carefully dissected and processed for histopathological analyses. Observations demonstrated the presence of multiple cell masses under the skin layers, with either picnotic nucleus or without a nucleus and with keratin in the central part of the cell masses. Using specific staining for keratin showed a red-coloured keratin mass (cancer pearl) as a bluish background in the tissue components. The invaded cell masses into dermis showed pleomorphic nuclei.

Robust Methods for Identifying Optimal Reservoir Operation Strategies Using Deterministic and Stochastic Formulations

Water allocation in a competing environment is a major social and economic challenge especially in water stressed semi-arid regions. In developing countries the end users are represented by the water sectors in most parts and conflict over water is resolved at the agency level. In this paper, two reservoir operation optimization models for water allocation to different users are presented. The objective functions of both models are based on the Nash Bargaining Theory which can incorporate the utility functions of the water users and the stakeholders as well as their relative authorities on the water allocation process. The first model is called GA–KNN (Genetic Algorithm–K Nearest Neighborhood) optimization model. In this model, in order to expedite the convergence process of GA, a KNN scheme for estimating initial solutions is used. Also KNN is utilized to develop the operating rules in each month based on the derived optimization results. The second model is called the Bayesian Stochastic GA (BSGA) optimization model. This model considers the joint probability distribution of inflow and its forecast to the reservoir. In this way, the intrinsic and forecast uncertainties of inflow to the reservoir are incorporated. In order to test the proposed models, they are applied to the Satarkhan reservoir system in the north-western part of Iran. The models have unique features in incorporating uncertainties, facilitating the convergence process of GA, and handling finer state variable discretization and utilizing reliability based utility functions for water user sectors. They are compared with the alternative models. Comparisons show the significant value of the proposed models in reservoir operation and supplying the demands of different water users.

Probabilistic reservoir operation using Bayesian stochastic model and support vector machine

Available water resources are often not sufficient or too polluted to satisfy the needs of all water users. Therefore, allocating water to meet water demands with better quality is a major challenge in reservoir operation. In this paper, a methodology to develop operating strategies for water release from a reservoir with acceptable quality and quantity is presented. The proposed model includes a genetic algorithm (GA)-based optimization model linked with a reservoir water quality simulation model. The objective function of the optimization model is based on the Nash bargaining theory to maximize the reliability of supplying the downstream demands with acceptable quality, maintaining a high reservoir storage level, and preventing quality degradation of the reservoir. In order to reduce the run time of the GA-based optimization model, the main optimization model is divided into a stochastic and a deterministic optimization model for reservoir operation considering water quality issues. The operating policies resulted from the reservoir operation model with the water quantity objective are used to determine the released water ranges (permissible lower and upper bounds of release policies) during the planning horizon. Then, certain values of release and the optimal releases from each reservoir outlet are determined utilizing the optimization model with water quality objectives. The support vector machine (SVM) model is used to generate the operating rules for the selective withdrawal from the reservoir for real-time operation. The results show that the SVM model can be effectively used in determining water release from the reservoir. Finally, the copula function was used to estimate the joint probability of supplying the water demand with desirable quality as an evaluation index of the system reliability. The proposed method was applied to the Satarkhan reservoir in the north-western part of Iran. The results of the proposed models are compared with the alternative models. The results show that the proposed models could be used as effective tools in reservoir operation.

The prevalence of musculoskeletal complaints in a rural area in Iran: a WHO-ILAR COPCORD study (stage 1, rural study) in Iran

The objective of this study is to study the prevalence of musculoskeletal complaints and disorders in a rural area in Iran. Interviews were conducted in randomly selected subjects from five villages in Tuyserkan County, northwestern part of Iran. The three phases of stage 1 Community Oriented Program for Control of Rheumatic Diseases were done during the same day. A total of 614 houses was visited, 1,565 persons interviewed, and 1,192 persons examined. Musculoskeletal complaints during the past 7 days were detected in 66.6% (shoulder 22.7%, wrist 17.4%, hands and fingers 14.9%, hip 13.9%, knee 39.2%, ankle 19.6%, toes 12.7%, cervical spine 17.9%, and dorsolumbar spine 41.9%). Degenerative joint diseases were detected in 20.5% (cervical spondylosis 2.2%, knee osteoarthritis [OA] 19.3%, hand OA 2.7%, and hip OA 0.13). Low back pain was detected in 23.4%, soft tissue rheumatism in 2.2%, rheumatoid arthritis in 0.19%, ankylosing spondylitis in 1.1%, systemic lupus erythematosus in 0.06%, and fibromyalgia in 0.06%. The prevalence of rheumatic complaints in rural Iran is very high and needs attention in the curricula of medical schools and in the planning of rural health care by the government.

Estimation of Saturation Percentage of Soil Using Multiple Regression, ANN, and ANFIS Techniques

The saturation percentage (SP) of soils is an important index in hydrological studies. In this paper, arti?cial neural networks (ANNs), multiple regression (MR), and adaptive neural-based fuzzy inference system (ANFIS) were used for estimation of saturation percentage of soils collected from Boukan region in the northwestern part of Iran. Percent clay, silt, sand and organic carbon (OC) were used to develop the applied methods. In additions contributions of each input variable were assessed on estimation of SP index. Two performance functions, namely root mean square errors (RMSE) and determination coefficient (R2), were used to evaluate the adequacy of the models. ANFIS method was found to be superior over the other methods. It is, then, proposed that ANFIS model can be used for reasonable estimation of SP values of soils.