جستجوی مقالات مرتبط با کلیدواژه « شبیه‏سازی » در نشریات گروه « اکولوژی »

The aim of this research is to investigate the effects of cover plants (grass) in improving the microclimate.Data collection methods include field analytical, and quantitative, with a comparative analysis method of proposed design options using simulation in ENVI-met software (4.4.6) and Ray-Man 3.1 in two different patterns at the same site for a period of 8 hours (10:00 to 18:00), which took place on June 30, 2020, as the hottest day of the year; The research was also validated by comparing the model's output parameter values with field measurements. The results indicate the optimal performance of the pattern of green cover(grass) compared to the absence of it in improving thermal comfort and reducing physiological temperature. Because it has caused an increase in relative humidity of 0.06% and a decrease in the environmental comfort index (PMV) by 0.005, as well as a decrease in the physiological equivalent temperature (PET) by 0.23 degrees Celsius, the hours of 11:00, 12:00, and 18:00 contain the best performance of vegetation (grass) in terms of enhancing micro-climate conditions, whereas the hours of 14:00, 15:00, and 16:00 include the worst performance in terms of effective micro-climate alterations. The average change in physiological temperature in the most optimal and worst hours of operation is equal to 4.68 degrees Celsius, and these changes in the relative humidity index are equal to 0.45%.

Groundwater is the main component of sustainable development in Iran. Due to population growth, over-exploitation, reduced precipitation, and inappropriate cultivation practices, water storage has significantly declined. Therefore, it is imperative to model groundwater and predict the future state of the aquifer for effective management. In this study, we have modeled the qualitative and quantitative changes of the Kashan aquifer. Based on the hydrological and hydrogeological conditions of the Kashan plain aquifer, we developed a groundwater quantity and quality model (2009-2015) under stable and unstable conditions using the MODFLOW and SEAWAT models in the GMS software. The models were validated through statistical evaluation, demonstrating their accuracy in modeling. Once the models were validated, we assessed the status and quality of the aquifer for the next period (2016-2023) by considering various practical scenarios. Applying the current trend scenarios revealed a projected decrease in aquifer volume to 1.556 Mm3 and an average increase in salt density of quality wells to 160.33 ppm in the next period. Conversely, when simulating the scenario of shutting off wells for a month, the aquifer volume was projected to increase to 0.0147 Mm3, and the salt density of quality wells would decrease to an average of 42.27 ppm during that one-month period. These results highlight the model's capability to accurately recognize and predict observed and calculated outcomes. The expansion of saline water in the northeastern part of the aquifer has resulted in a decline in both quantity and quality in that region. Finally, implementing multiple management and scientific scenarios concurrently is crucial to prevent further deterioration of the quantitative and qualitative status of water resources in this region.

Natural resources and the environment are the foundation of life and human activities and other creatures, closely intertwined with them. In recent decades, the Earth has been significantly affected by the impacts of global warming and climate change and the country of Iran has not been exempted from this rule. as this phenomenon directly affects environmental, economic-social activities and human health. General circulation models are suitable tools for monitoring future climate change events, but due to their large spatial scale, they require downscaling. This study examined the status of climate variables such as precipitation and average temperature at five synoptic stations on the southern coasts of the country. The basic statistical periodconsidered from 1985 to 2015, and four climate scenarios from the sixth IPCC report were simulated using the MPI-ESM1.2-HR model for the statistical period2023-2043 through downscaling SDSM modeling. The results show an increase in temperature ranging from 1.64% to 8.9% compared to the base period under all four scenarios at all stations. Meanwhile, precipitation is decreasing at some stations under certain SSP scenarios and increasing at others. An increase of up to 140% in Bushehr station and a decrease of more than 10% in Kish station are expected. Estimating, predicting, and monitoring climate change occurrences in different time frames and according to the updated IPCC reports is essential to assist decision-makers and policymakers in taking action to reduce greenhouse gas emissions and adapt to this leading phenomenon.

Flooding and soil erosion are a significant issue in the watershed areas of Iran. The result of this is soil lost, soil fertility decreases, vegetation decreases, run-off increases, and severe floods. There are various watershed operations, including biological and mechanical, which protect water and soil, however, it is necessary to investigate which method and how many structures should be used in an area to be more effective. In this research, SWAT hydrological model and scenario building of watershed structures in waterways were used to investigate the impact of watershed management projects on erosion and sedimentation in Sarbaz River watershed, Sistan and Baluchistan province. After preparing the input parameters, the model was recalibrated for a 17-year period (1999-2016) and then validated over a five-year period (2017-2021). The results of the sensitivity analysis showed that the alpha parameters in the return flow and the initial curve number for medium humidity conditions in the SCS method had the greatest effect on the calibration and validation of the simulation. The results obtained from runoff calibration were 0.76 Nash- Sutcliffe coefficient and 0.86 explanation coefficient, and 0.53 and 0.58 respectively for sediment. The scenario's results have regulated the impact of watershed structures on nearly 15% of the sediment. Watershed measures are capable of reducing and controlling runoff, soil erosion, and sediment transfer in the region, as demonstrated by these results. In the meantime, attention should also be given to the financial issues of the plan when selecting watershed scenarios.

In recent years, the phenomenon of dust storms has become a serious global issue, particularly in the Middle East region. Today, the most widespread and damaging environmental crisis in the country is the occurrence of dust storm events, attributed to land use and climate change effects. This study was conducted in western Iran with the aim of detecting the entry paths of dust storm events into Kermanshah province using the HYSPLIT model. Tracking and monitoring the path of dust storms on a wide scale and using methods that are both accurate and fast, but also cost-effective, is of great importance. Therefore, in this study, GDAS data were used to detect and route the movement of dust storms using the Lagrangian dispersion model in the HYSPLIT environment. For this purpose, the dust storm from the 19th to the 21st of May, 2023, in Kermanshah province was selected. Modeling was performed using the backtracking method to determine the movement path of dust particles 6 hours prior to the desired occurrence in the 500, 1000, 1500 and 2000-meter levels. Finally, maps of the path detection and tracking of weather systems and air particles at pressure levels were obtained in both PDF and KML formats. Detection of the movement path of dust particles showed that often the paths pass through the northern and central regions of neighboring countries such as Iraq, Syria, and Saudi Arabia. Additionally, the results indicated that the source of dust storms in western Iran lies in a region between the border regions of western Iran, northern and central Iraq, Syria, and Saudi Arabia.

One of the new challenges in exploiting groundwater resources is seawater intrusion. Unplanned increase in exploitation reduced the groundwater level, which reduced the hydraulic gradient of the shoreline and in some areas reverses the groundwater flow and leads to groundwater salinization. This study examine the seawater intrusion strategies in the Astana-Kuchesfahan coastal aquifer using numerical simulation. Examination of the current status of this aquifer using SEAWAT package was indicated the intrusion of 740 meters of seawater to the aquifer over a 5 years period showed that in order to manage this pressing matter, 19 management strategies (reduction of groundwater exploitation), structural and subsurface dam) and integrated (managerial and structural) to reduce the seawater intrusion was presented. The simulation results of different treatment strategies were evaluated using the aquifer qualitative stability index, which is based on the amount of saline water regression. The results showed that this index was calculated between 14% and 65% for the defined solutions. The highest relative aquifer improvement is related to S18 solution with 20% reduction in groundwater exploitation, artificial recharge and subsurface dam and the lowest relative aquifer improvement is related to S1 solution with 5% reduction in operation. The results showed that S1 solution was associated with 100 m water retreat and S18 solution was associated with 480 m saline water retreat. The results can be used for groundwater exploitation management in this coastal aquifer.

Due to the location of Iran in arid and semi-arid regions and type of soils common in Iran, the high rate of erosion and sediment is one of our country problems. The amount of sediment produced is the result of complex interactions between climate, soil type, landuse and human activities. Therefore, obtaining appropriate methods in predicting sediment load can be considered as one of the most important challenges. The main purpose of this study is to identify critical areas in terms of erosion and sediment in upstream watershed of Nahand Dam located in East-Azarbaijan province. In this regard, SWAT model was calibrated and validated using SUFI-2 algorithm to predict monthly discharge and sediment load. Nash-Sutcliffe (NS) as the objective function for discharge in the calibration and validation periods were 0.84 and 0.75, respectively. The Nash-Sutcliffe coefficient of sediment load was calculated to be 0.65 in the calibration period and 0.8 in the validation period. Then, using the results of the SWAT model, the average runoff and sediment outflow of the sub-basins were classified by method of Natural Breaks (Jenks) and the critical areas of erosion were determined. Accordingly, 5,200 square kilometers (25%) of the watershed area, which are classified in the class with more sediment production, are critical areas in terms of erosion and sediment. Since erosion causes the destruction and reduction of soil fertility and on the other hand, the produced sediments are deposited in dam reservoir, so it is necessary to perform erosion control operations in these sub-basins.

Water is one of the most essential elements in nature that forms the basis of human life and contributes to the economic growth and development of societies. Healthy water is closely related to environmental health and activities. The life of all animals on Earth depends on water and oxygen. In addition, adequate dissolved oxygen (DO) is essential for the survival of aquatic animals. Therefore, in this study, to simulate the dissolved oxygen of the Cumberland River in the United States from the combined artificial neural network (ANN) model with wavelet and meta-heuristic algorithms of gray wolf (GWO) and bat (BA) on a monthly time scale during the statistical period. Used 2020-2010. The criteria of correlation coefficient (R2), squared mean square error (RMSE), absolute mean error (MAE) and Nash-Sutcliffe productivity coefficient (NSE) were used to evaluate and compare the performance of the models. The results showed that all three hybrid models have better results in hybrid models than the other designated models. Also, according to the evaluation criteria, it was found that among the models used in the simulation of dissolved oxygen in river water, the model of artificial neural network-wavelet with coefficient of determination (R2 = 0.958), the root mean square error (RMSE = 0.651), The mean absolute value of error (MAE = 0.334) and Nash Sutcliffe coefficient (NS = 0.962) in the validation stage showed better performance than other models.

Aboveground net primary production (ANPP) is one of the crucially characteristics of rangeland ecosystems and it is importance in the cycle of materials and energy in these ecosystems. The aim of present study was investigate the ANPP of life forms (grasses, forbs, and shrubs), and total ANPP; then modeling of life forms and total ANPP by using precipitation and temperature in Siahpoush and Ganjgah mountain rangelands of Kowsar County, Ardabil Province. Seven sampling sites were determined at different altitudes and in each site according to the vegetation pattern of the representative regions were considered as three transects (100 m) in each site and 10 plots were considered for ANPP evaluation in each transects. The relationship between climate factors classes (precipitation and temperature), and the ANPP were analyzed using one way Anova and Duncan analysis. The ANPP maps were simulated using linear regression in ArcMap10.0. The results show a significant relationship (p>0.05) between the life forms and total ANPP with precipitation and temperature factors. The accuracy (RMSE) of simulated maps for ANPP of grasses, forbs, shrubs and total ANPP was 0.07, 0.08, 0.14 and 0.06, respectively. The present study results can be used in balance between supply and demand of rangelands production.

The aim of the study was to determine the most important environmental factors (topography, climate, and soil) affecting changes in production and canopy cover of plant variations and to prepare prediction maps, based on the most important factor, in semi-steppe rangelands of Hir-Baghrou, Ardabil province, Iran. First, by detecting the vegetation types and different classes of environmental factors, the production and canopy cover were estimated in 1-m2 plots at full flower stage of dominant species. Then, to determine the most important environmental factors, affecting the production and canopy cover changes, the principal component analysis (PCA) was used. For modeling, first, the correlation between the most effective environmental factors was obtained from the PCA. Then, the highly correlated factors were eliminated and the quadratic polynomial models were obtained. Finally, the obtained models were simulated in GIS. The results of the PCA showed that the first six components with 71.65% had the greatest effect on the production and canopy cover changes. Based on the root mean squared error (RMSE), simulating maps of production (RMSE=0.76) and canopy cover (RMSE=0.48) by effective factor (annual precipitation) showed the highest accuracy. The results of this study can be used to manage the rangelands of Ardabil province to create a balance between supply and demand of production and also to balance carbon.

Quantitative methods to the evaluation of vegetation are the basis for describing and analyzing the plant communities and density as one of the main characteristics plays an important role in evaluating the performance (short and long effects) of rangeland ecosystems and management decisions. Therefore, the efficiency of plotless plant density methods in different density intensities and distribution patterns have been examined using a simulated population based on the real density of Astragalus albispinus (control method) in a semi-arid region of Marjan, Boroujen. Simulation schemes in the three density intensities and three distribution patterns within eight 40×100 m sampling units were designed. The predictive precision and accuracy of seven distance-based methods in various density intensities and distribution patterns were investigated comparing with the control method and the ideal point error index. Overall, angel order method in regular distribution pattern and point centered quarter method in random distribution pattern were the best plotless density methods of plant populations in low density. Third closest individual method was the most accurate and precise method of density among the studied methods in other different density intensities and distribution patterns. Therefore, in selecting the most appropriate distance method for estimating the density, the type of distribution pattern and in some cases the intensity of plant species density should be considered to achieve an unbiased estimation of plant populationʼs density, accordingly, the different habitats of this plant species can be monitored and evaluated in terms of management and utilization.

Introduction

Method include seedling size and planting date. Since field experiments are usually laborious and costly, the simulation models could be used as a useful tool for investigating such factors. Due to climate change affects the outputs of crop models, the crop growth simulation models should be widely evaluated with empirical data to ensure that simulation of crop growth under a different management strategy or future weather conditions is reliable. 

 In the present study, the effect of direct-seeding and four seedling sizes (13, 16, 19 and 22 leaf area cm2plant-1 and at 200, 250, 300 and 350 °C cumulative temperature) for transplanting method at four planting dates (10 June, 25 June, 14 July, and 27 July) was simulated in Gorgan environmental conditions for 16 years (2000-2015) using SSM-iCrop2 model. In this simulation, it was supposed that the corn should be harvested on 22 November to provide sufficient time for cultivating the next crop. Also, the economic evaluation between the two methods of transplanting and direct-seeding was carried out using a questionnaire from farmers and experts in the field to evaluate the costs of these two methods.

 The simulation results showed that at early planting date (10 June), in transplanting method, the crop matured earlier between 16 to 26 days compared to the direct-seeding, depending on seedling size. In addition, the average yield of 1331 g m-2 and average net irrigation requirement of 435 mm ha-1 were obtained. At this planting date, transplanting had no effect on the yield and net irrigation requirement. In the common sowing date (25 June), the crop matured earlier between 19 to 33 days (early harvest) in the transplanting method compared to direct-seeding, however, the planting method had no effect on the yield and net amount of irrigation. At this planting date, the average yield and water requirement were 1329 g m2 and 416 mm ha-1, respectively. In late planting date (14 July), transplanting with large seedlings (leaf area of 19 and 22 cm2 plant-1) were able to complete their growth period before 22 November. Average yield and irrigation requirement were 1273 g m-2 and 381 mm ha-1, respectively. It should be noted that in late planting date, direct-seeding and transplanting with small seedlings (leaf area of 13 and 16 cm2 plant-1) were not able to complete maturity to 22 November, therefore, this planting date is not recommended. At the last planting date (27 July), all types of cultivation are not recommended as crop growth period are not completed before 22 November.
 Conclusion

 In general, it can be concluded that transplanting method would be only recommended for late planting date with using large transplants (leaf area of 19 and 22 cm2 plant-1). However, transplanting did not significantly decrease the amount of net irrigation requirement at any of the planting dates, and also had higher costs and lower profit.

Due to limitation of water and soil resources resulted from geological and climatic conditions of Iran as well as necessity of self-reliance in infrastructural issues, efficient usage of water and soil resources available in Iran is inevitable. Climatic changes, reduced biodiversity in the region and concerns about food security are regarded as important issues; hence, evaluation of conditions to attain improved crop production seems essential. To investigate yield improvement methods, yield potential and yield limiting factors (climate, soil, water, and genetic factors) should be determined and evaluated in the first step. Simulation models may be used as scaled-up designs of field experiments to overcome limitations such as time and costs. Crop  simulation  models  are  mathematical representations  of  plant  growth  processes  as  influenced  by  interactions  among genotype,  environment and crop  management. Using crop simulation models can be an efficient complement to experimental research.  Models are being used to understand the response of crops to possible changes in crop, cultural management, and environmental variables. Crop models use various plant and environmental parameters to simulate crop growth and should be calibrated and evaluated before usage.

 SSM-iCrop model predicts phenological stages as a function of temperature, day length.  Calculation of phenological development in the model is based on the biological day concept. A biological day is a day with optimal temperature, photoperiod, and moisture conditions for plant development. Leaf  area  development  and  senescence  is  a  function  of  temperature,  provide nitrogen  for  leaf  growth,  plant  density  and  nitrogen  remobilization.  To  simulate leaf area expansion, the first step is to determine on each day the  increase in leaf number  on  the  main  stem  using  the  phyllochron  (temperature  unit between emergences of successive leaves) concept. In this model biomass is estimated as a function of the received radiation and temperature.  Daily  increase  of  crop  mass  is  estimated  as  the  product  of  incident photosynthetic  active  radiation  (PAR,  MJ  m-2d-1),  the  fraction  of  that  radiation intercepted  by  the  crop  (FINT)  and  efficiency  with  which  the intercepted  PAR  is used to produce crop dry mass, i.e., radiation use efficiency (RUE, g MJ-1).  Yield formation  in  the  model is simply  simulated  as  total  dry matter  production  during seed  filling  period  plus  a  fraction  of  crop  dry  mass at  BSG  (as  mobilized  dry matter).  Modeling  seed  growth  rate  and  yield  formation  in  the  current  model  is based on a modified linear increase in harvest index concept as described by Soltani and Sinclair (2011).The model needs daily weather data, i.e. maximum and minimum temperatures, rainfall, and solar radiation. The model can be run under multiple scenarios/treatments over many years.

 As a result of the SSM-iCrop model parameterization, three early, medium and late maturing cultivars were determined for canola, which their cumulative degree days (GDD) for growth period completion were estimated as 2000, 2500 and 2700 °C days. After determination of the required parameters, the model was run based on sowing date, management, and meteorological statistics of the region using the data from the papers which were not used for parameterization, so as to validate the model. The average of the simulated data for days to maturity and yield were 222 (days) and 383 (g.m-2), respectively, whereas observed values for this traits were 223 (days) and 359 (g.m-2).

 Based on the 1:1 line and statistics of r=0.87, CV=18% and RMSE=67.04 (g.m-2) for grain yield and r=0.97, CV=5% and RMSE=10.68 (days) for days to maturity, it may be concluded that simulation canola growth using SSM-iCrop model has been satisfactory and indicates accurate estimation of the model parameters, as well as serving as a verification of the model efficiency in prediction of canola yield under climatic conditions of major canola production regions of Iran.

In recent years, global warming and climate change have been associated with dire consequences for human societies. Changes in climate patterns can lead to severe floods, extreme heat and cold, more frequent droughts, and global warming. This increase in global warming has upset the Earthchr('39')s climate balance and caused widespread climate change in most parts of the world, known as climate change. Therefore, identifying temperature patterns in the future can be very useful in meteorological studies and other related sciences. This research work was done in 2019 in Ahvaz. The aim of this study is to simulate the temperature in the period of 36 (2050-2015) using data from the general air circulation model in southwestern Iran. In this study, the EH5OM database was used to simulate daily temperature. After extracting the data, spatial and temporal distribution of temperature patterns using ArcGIS software was performed using common cryogenic zoning statistics (OK) techniques. Using the data of the general air circulation model during the 36-year period, the monthly, seasonal and annual temperature patterns of the region, mediation and relevant maps were drawn. Based on the results of the prevailing temperature patterns in the annual period, it is fully consistent with the topography of the study area, which indicates the strong effect of altitude on temperature. The highest average simulated temperature per year is related to Mahshahr port station with 26.25 C and the lowest temperature belongs to Aligudarzwith 12.56 C. Also, in July, with the standard deviation of 3.9, the highest temperature was obtained in all stations, and in January, with the standard deviation of 4.6, the lowest temperature was obtained.

Land Surface Temperature (LST) affects snowpack spatiotemporal changes as one of crucial components of water balance. . Despite of ease of access to Remote Sensing (RS) data, such as Moderate Resolution Imaging Spectroradiometer (MODIS) products that used for monitoring and evaluating LST effect on snow cover area SCA which are sometimes not available for some reason. In order to overcome limitation, the monthly average values of SCA and LST in each 8 days for 13 years (2003-2016) were evaluated by regression relations.The results showed, minimum and maximum values of annual mean of snow cover area percent occurred in 20009and 2011 equal to 5.86%, 20.32, , respectively. In addition to, the annual mean of minimum and maximum values of LST related to 2004 and 2010 were 17.65 and 21.1 , respectively. The pattern of two variables changes illustrated that the SCA changes to LST are reverse and gradually increasing during the study period. Also, the results revealed that in power regression, the Nash-Sutcliff Efficiency (NSE) coefficient for SCA percent simulation, , RMSE and Bias, are 0.6, 0.64, 9.88 and -2.14, respectively. These coefficients are 0.16%, 47%, 14.37% and 86.32% in linear regression method, respectively. Thus, this study may be helpful to estimate SCA and reconstruct missing data in satellite images.

The nitrogen budget or balance is often evaluated by comparing various nitrogen inputs and outputs in soil–crop systems. Research on nitrogen balance can provide more detailed information on the nitrogen cycle and its losses by integrating soil nitrogen processes with the total nitrogen budgets. There are restricted researches for evaluation of nitrogen balances in the cropping systems. It is clear that accurate measuring of each component of nitrogen budgets in relation to soil processes is difficult. Wheat (Triticum aestivum L.) is the main cereal crop cultivated in Iran. According to published data the average nitrogen application rates in wheat cropping systems of Iran is 120 kg.ha-1 but, the excessive use of fertilizer nitrogen is very common in wheat fields. It is estimated that in Iran, about 2.2 million ha of wheat production areas are under irrigation. Alike, there are limited studies on nitrogen dynamics, budgets and its losses pathways in wheat production systems of Iran. Such studies are essential to understand the nitrogen behavior and balance in wheat cropping systems. This research was carried out with the aim of evaluating nitrogen balance of wheat cropping systems with different climatic conditions over the country by using CENTURY model.

We used CENTURY model (Parton et al., 1994) to evaluate nitrogen dynamics and nitrogen balance in wheat cropping systems. For this purpose 14 wheat cropping system located in diverse climates were selected. Soil data was collected from Soil and Water Research Institute and weather data from 2000 to 2014 were obtained from Iran Meteorological Organization for 14 selected stations. The CENTURY model simulates the long-term dynamics of Carbon (C) and Nitrogen (N), for different Plant-Soil Systems. The model can simulate the dynamics of agricultural crop systems. The crop system of CENTURY have different plant production sub-models which are linked to a common soil organic matter sub-model .The soil organic matter sub-model simulates the flow of C, N through plant litter and the different inorganic and organic pools in the soil. CENTURY model runs in monthly time step with monthly precipitation (cm), monthly mean minimum and maximum temperature (°C), site latitude and longitude, sand, silt and clay (%), soil bulk density (g.cm-3), rooting depth (cm), C and N content of the top 20 cm of soil and management information such as planting date, first and last month of wheat growth, number and amounts of applied fertilizers, amount of irrigation water and its schedules are required. For model validation we used two statistical measures including Normalized Root Mean Squared Error (nRMSE), Willmott (1982) index of agreement (d value) and linear regression coefficients between actual and predicted values.

Results revealed that the highest nitrogen input in wheat cropping systems (9.5 - 12.5 g.m-2) was observed in Northwest, West and Southwest and the lowest (7.3 - 9.4 g.m-2) were in East and Southeast areas of the country. Also, nitrogen output plan in wheat cropping systems was similar to nitrogen input. In addition, stepwise regression analysis indicated that fertilizer application rate with partial coefficient of 97.33% and grain nitrogen with partial coefficient of 92.79%, respectively, were the most important variables in relation to nitrogen input and output in wheat cropping systems of Iran.

According to the results, it seems that in relation to nitrogen input, the role of agronomic management such as fertilizer application, coincidence of fertilizer application time with plant requirement and increasing nitrogen use efficiency (NUE) which is mostly dependent on agricultural management are important issues. But in the case of nitrogen outputs from wheat cropping systems, in addition to agronomic managements, use of improved cultivars with higher nitrogen uptake efficiency is more important.

It is accepted that the global annual average temperature has been increased during recent decades. The climate of Iran is also affected by this global warming. Some studies indicated the increasing of mean annual temperature of Iran between 3.5-4.5○C by 2050. Crop phenology is directly related to temperature, so climate change could significantly change the phenology and yield of crops. Modelling phenology is a way to simulate the timing of phenological stages based on climatic factors. Amongst models, WOFOST is known as a powerful model for simulation of phenological stages and yield of wheat. In this study climate warming of Iran was evidenced. Based on this fact, trends of potential grain yield and time of flowering and maturity of wheat were studied in different climatic zones of Iran during 1992-2012. It is expected that understanding the thermal induced of phenological changes, can lead us to better field management decision making.

Weather data of 18 cities from 4 climatic zones of Iran (northern warm and humid (Zone 1), southern warm and dry (Zone 2), temperate (Zone 3) and cold and high elevation (Zone 4)) were analyzed during 1992-2012 and the long-term trends of air temperature were detected by linear regression. The crop growth simulation model WOFOST, was used to simulate the time of flowering and maturity and also the potential grain yield of winter wheat. Calibration and validation of model was conducted in 4 selected cities from each zone using statistical measures. The consequences of temperature on duration of grain filling period and also yield of wheat were determined.

Results indicated that the mean annual air temperature was significantly increased in all cities during 1992-2012. The highest increasing rate (regression line slope) belonged to Ardabil (0.159○C.y-1) and the lowest rate was observed in Pars Abad Moghan (0.06○C.y-1). Validation of WOFOST in 4 selected cities from each climatic zone, showed the perfect ability of model in simulating the flowering and maturity time of wheat. Regression analysis showed that the grain filling period was increased in accordance with temperature rise in zone 1 and 4 whereas it was shortened in zone 2 and 3. Grain yield showed the same trends predicted for grain filling period in different climates. Slop of linear regression between temperature and yield was significant except in Gorgan (Zone 1). In all cities the relation between grain filling period and yield was direct and positive.

Although temperature has increased in all climatic zones of Iran, flowering and maturity time and grain yield of wheat has showed different responses. There was a nonsignificant slope of regression line in the north humid climate, which means that the humidity of northern part of Iran (south of Caspian Sea) enhanced stability for this area. Annual mean temperature in southern warm and dry zone of Iran ranged between 24.3-27.9 ○C that could be stressful for wheat, and hence resulted in shorter grain filling period and less grain yield. It seems that in temperate zones (such as Mashhad) increasing temperature caused yield reduction due to faster GDD accumulation and lack of time to complete remobilization of photosynthetic materials. On the other hand, in cold areas increasing temperature could reduce the risk of cold stress in flowering time, resulting in longer grain filling period and higher grain yield. According to WOFOST simulation results, during 20 years study (1992-2012), mean potential yield of wheat increased 6.25 and 11.42 percent in northern warm and humid (Zone 1) and cold and high elevation (Zone 4), respectively and decreased 12.17 and 13.11 percent in southern warm and dry (Zone 2) and temperate (Zone 3), respectively. Total mean potential yield of wheat, by consideration of proportion of each zone in total wheat production of Iran, showed reduction of 1.8% and 3.28% during 1992-2001 period (10 years) and 1992-2012 period (20 years), respectively.          

Knowledge of the process of change and the prediction of water quality parameters of the rivers provide the quantitative information needed to calculate the tolerable pollution load in the natural environment of the river, as well as a fuller understanding of the biological processes an environment. The main objective of this paper is to use the QUAL2Kw qualitative simulator model to model water quality in the Dyvandareh River and reduce river pollution by more adapting the amount of inputs of pollutants in different areas of the river with its ability to self-pollute. In this study, the process of changing the important parameters of the water quality of the Diwandreh River, such as dissolved oxygen (D0), biological oxygenation (CBOD), chemical oxygen demand (COD), acidity (pH), electrical conductivity (EC) and temperature, and Calculating the percentage of self-pollination of the river from the beginning of the branch before the connection of the tallar river to the decaying parameters of BOD and COD, and to predict their changes, the QUAL2Kw qualitative simulation model has been used. In order to calibrate the model, data from December 2008 were used. Due to the ability of the model for automatic calibration in this study, calibration was done both manually and effortlessly. In order to evaluate and validate the model results, AME and root mean square error (RMSE) were used.

The purpose of this research is to simulate and optimize the utilization of water resources of Zahedan in the next 20 years under various management scenarios. In order to reach the definitive optimal point in this issue, minimization of non-supply demands and minimization of withdrawal from groundwater resources in a single target was studied using a one-goal PSO algorithm. Five scenarios were defined and the results of these scenarios were compared. The results of the research showed that in the reference scenario with increasing population, in the final years of the simulation period, we will face the water stress. The second scenario, with the allocation of refined effluents to the industry and green spaces, was fully funded. In the third scenario, assuming the second line of water transfer from the well, the demands of drinking, industry and the environment will be fully met. The supply of drinking demands in August, June, and September was 4.9, 3.39, 3.21 and 1.20%, respectively. The results showed that this optimization algorithm has been able to reduce the failures. Finally, the ideal scenario was defined by combining the second and third scenarios based on the optimal amount of harvest from the groundwater source. In this scenario, the demands of drinking, industry, and green space are fully met and agricultural demands of over 95%. Also, the rate of harvesting of groundwater resources in the optimal and ideal scenario was 4.95 and 17 percent, respectively, compared to the reference scenario.

Dust storm and its mitigation require in-depth knowledge of prevailing parameters and their interaction. Accordingly, study of dust storm motion and its deposition have special significance. Among the dust storm studying methods, simulation is important because of its lower cost and independency on experiment or satellite. The goal of this study was to simulate the motion and deposition of clay dust storm particles with size of 0.001 to 200 micron affected by wind speed of 1, 3, 10 and 20 m.s-1 on a smooth land and hypothetic obstacles with a height of 6 and 12 m. Gambit and Fluent are used for creating the simulation environment and solving the continuity and Navier-Stokes equations coupled with turbulence intensities equations. According to the results, wind speed is a negative factor for dust storm particle deposition on earth and obstacle surfaces and it is independent of the obstacle height. Therefore, particles under one micron remain primarily in the air and they deposit lower than 10 percent, so they can transfer to farther distances. The larger the particles, the more efficient the gravitational mechanism in their deposition phenomena; such a way that the deposition calculated more than 30 percent for particles larger than 100 microns. At the same wind speed and particle size, the 12m obstacle postpones the deposition because of the separation of the flow from the surface and turbulence and it also decreases the deposition of particles under micron to lower than 1 percent. The deposition of these particles doesn’t vary with wind speed but the one for particles larger than 10 micron is inversely proportional with wind speed.