simulation

Climate is one of the most fundamental factors in the structure of the planet Earth. Undoubtedly, the biological (including human) and non-biological fields are deeply and widely affected by climatic conditions. Climate change can have many feedbacks and consequences. During the last 30 years, the frequency of some Frein accidents has increased, and it is expected that more hazards related to weather will occur in the future. Due to the increase in climatic extremes and natural hazards in Iran, which is characterized by ecological sensitivity, these events have a significant impact on the state of water resources, agriculture, energy, tourism, and bio-climatic conditions; Therefore, studying this field is an inevitable necessity. The main goal of the current research is to investigate the simulation of average values and minimum, maximum and average daily temperatures of Zanjan based on climate scenarios and using the SDSM model.

The method of carrying out descriptive-analytical research and the method of collecting data is library (documents). SDSM model and climate scenarios (RCP2.6, RCP4.5 and RCP8.5) have been used to simulate temperature variables. The data used includes the average, minimum and maximum daily temperature recorded at the Hamdid Zanjan station during the period of 1961-2021 and the data of the general atmospheric circulation model to simulate climate variables in future periods. In order to obtain the most suitable atmospheric variables for estimating triple temperature profiles, the relationship between dependent variables (minimum, average and maximum daily temperature) with independent atmospheric variables (NCEP) was examined to select independent variables and recalibrate the model for dependent variables. Also, the Markov chain model has been used to investigate the probabilities of Frein events. In order to recalibrate the SDSM model, the observational data of Zanjan station and the data of NCEP National Center for Prediction of Environmental Variables were divided into two periods: 1961-1990 and 1991-2005. The first period was used to calibrate the model.

The simulation results of the three studied temperature variables showed that in all scenarios, they will increase the most in the period of 2082-2100 compared to the values of these variables in the base period (1961-2021). The monthly review of the simulated data and the observed data of the studied variables showed that based on the studied scenarios and the SDSM model, it was determined that from 2022-2100 the minimum temperature will increase by 2 degrees, the maximum and average temperature by 3 degrees. The average minimum and average temperature will increase the most in January and February and the least in October. While the average maximum temperature will increase the most in August and the least in April.

Result shows that all seasons of the year will become warmer, especially the cold seasons of the year. In other words, the cold seasons will be shorter. The number of extreme frequencies observed in all three temperature parameters for the 25th and 75th quartiles is less than the number of simulated extreme temperature events in all three scenarios. The highest number of extreme low frequencies is expected in January and the highest number of extreme high frequencies is expected in July.

Very Long Baseline Interferometry (VLBI) is one of the essential approaches in geodesy. Significant capabilities of this technique are creation of International Celestial Reference Frame (ICRF), determination of Earth orientation parameters (EOPs), coordinates of station with high accuracy and light deflection. Many attempts could be done to increase accuracy of VLBI data, including technical improvement of equipment, physical models improvement, using optimal data processing methods and increasing number of stations. In this study, in order to reduce the error of EOPs in CONT17 campaign, the appropriate position for a VLBI station in the Middle East is investigated. The results showed that mean error of EOPs in the Legacy-1and Legacy-2 reduced approximately 6.64% and 13.86% by adding two stations in Oman and Egypt countries, respectively.

Droughts caused by precipitation deficits and increasing water consumption are intensifying worldwide, with negative economic and environmental consequences. The negative impacts can be mitigated by using optimized reservoir operation patterns and implementing rationing rules during droughts. These approaches involve meeting only a portion of total demand, allowing for water storage and accepting a small current deficit to mitigate severe future shortages. This research presents a case study to determine the operational command curves for Jareh Dam and to investigate the impact of reservoir operation under two management policies, Standard Operating Procedure (SOP) and rationing, on downstream drought indices, an aspect not previously studied. To achieve this, an optimization model coupled with a genetic algorithm was linked to a simulation model to determine the optimal values of command curves and rationing coefficients based on historical inflow data to the reservoir. The performance of the model was evaluated in the Allah River water resources system. In addition, the drought severity index (SDI), SOP performance, and rationing model performance during the base period were evaluated by calculating the objective function value or modified shortage index (MSI) and the resilience, vulnerability, and reversibility indices. The results showed that under the rationing model during the study period, the MSI value improved by 41% compared to the SOP method. In addition, the implementation of the rationing policy significantly improved the vulnerability of the system compared to the SOP method, reducing it from 64% to 26%.

Hamoun wetland includes Hamoun Pozak, Saberi and Helmand as the largest freshwater lake in Iran and one of the most important wetlands of international importance. This wetland is located in the southeast of Iran in Sistan and Baluchestan province. Due to the increase in rainfall in Afghanistan and eastern Iran in 2018-2020, there is a possibility of flooding of the gas transmission pipeline from Dashtak Launcher Station to Zabol city in a part of Helmand wetland. Based on the Projection of the General Circulation models (GCMs), in the future there is a possibility of increasing temperature and decreasing rainfall in Sistan erea. Therefore, based on 5 models and two scenarios, RCP4.5 and RCP8.5, first the precipitation and temperature values in the period (2020-2040) were calculated and then the hydrological variables were predicted. In order to simulate water level changes in Hamoun Wetland, various scenario of the floods with different return periods in unstable flow mode was performed using HEC-RAS software and flood zoning was calculated as the maximum water depth at any point in Hamoun Wetland. Examination of rainfall and water discharge of Sistan and Helmand rivers showed that most river floods and flooding of wetlands occur annually in the period from February to May. The actual monthly hydrograph flood of the Helmand River (October 2002 to October 2012) showed that the peak of this flood has a return period of about 130 years. Simulation showed that the flooding of the gas pipeline will occur in places located at 20, 30, 68, 80 and 104 km of Dashtak crossroads and especially in the location of Shila waterway and the water depth varies between 1.5 to 5 meters. Therefore, in the above-mentioned places, the necessary measures should be taken to prevent the gas pipe from floating.

Groundwater plays a vital role in supplying water demands for different consumptions in dry and semi-dry regions of earth. Iran is considered as an arid and semi-arid region and its groundwater resources have recently shown some significant changes. Owing to the reduction of groundwater resources and recent droughts, simulation of groundwater level variations has significant importance. In some areas of the country of Iran, groundwater levels have been dropped significantly. Therefore, the prediction and simulation of the groundwater level variation are crucially important. In this study, the Gene Expression Programming (GEP) model was combined with Wavelet Transform (WT) to estimate long-term variations of groundwater level (GWL) in the Sarab-Ghanbar observation well over a 13-years period. Firstly, observation data were divided into two sub-samples, 9 years for training and 4 years for testing. Then, the most effective input lags were identified using the autocorrelation function. Next, four different models for each GEP and WGEP method were developed using the lags. The superior model was identified by analyzing all GEP and WGEP models. The superior GEP model simulated the GWL with acceptable accuracy. For instance, the correlation coefficient and Nash-Sutcliffe efficiency coefficient for the model were calculated at 0.938 and 0.851, respectively. A comparison between the GEP and WGEP models showed that the wavelet transforms enhanced the performance of simulation significantly. For example, Variance Accounted For (VAF) index for the best WGEP model was 14 times more than the best GEP model. In addition, the sensitivity analysis indicated that (t-1), (t-2), (t-3) and (t-4) lags were the most influenced input lags.

Thunderstorms often appear with a strong, energetic and short-term air flow. These types of storm are caused by the ascent of hot and humid air in an unstable atmosphere and can lead to heavy rainfall if there is sufficient moisture, and otherwise they will lead to a dust storm. The purpose of this study was to investigate the storms in Khuzestan province, which usually experiences gusty winds, and convective storm events during spring and early summer. With regard to the frequent occurrence of dust storms in Khuzestan in recent years, it has become ever more important to study the convective storms. In order to identify the storm events in Khuzestan, Ahvaz station was selected due to much longer record of data and more accurate information than other stations in the province. A statistical analysis has been carried out on the long-term data of Ahvaz synoptic station between 1981 and 2016. After a thorough analysis of the long-term data, five cases of severe convective storms were selected. The cases include the 16th of October 1981 (case 1), the 27th of August 1985 (case 2), the 18th of December 1985 (case 3), the 24th of April 1992 (case 4) and the 8th of May 2000 (case 5). Finally, the characteristics of the cases were determined by numerical simulations using the Weather Research and Forecasting (WRF) model. The simulations were performed using four nested domains D1 to D4 with horizontal resolutions of 81, 27, 9 and 3km, respectively. The NCEP/NCAR reanalysis data were used for the boundary and initial conditions.Statistical analysis shows a decrease in the intensity and frequency of occurrences of the convective storms with maximum wind speed of greater than 12m/s during the 36-year period. Monthly analysis reveals that the most (least) frequent severe convective storms occur in April (October). Another important finding is that the severe convective storms occur mainly in spring and in the interval between 12UTC and 15UTC. From the early hours of the day until 13:00 UTC, the percentage of events increases, and then until the end hours of the day, the percentage of events decreases as the surface heating is maximized in the afternoon. The low frequency of occurrence in autumn and winter is due to reduced surface heating as a result of reduced solar energy received from the sun. The results of numerical simulations demonstrate that the position of the maximum wind speed is different in the considered cases. The comparison of the results of simulation of the selected cases with observational data shows that the model of simulated storm has a time delay of about 1 to 3 hours with respect to the actual storm occurred in the area. Tracking the storms from 30 min before to 30 min after the occurrence of the maximum wind speed along the path in the fourth domain of the model points out that the cases 1 to 3 evolve in the northeast and the cases 4 and 5 evolve in the northwest of Ahvaz station.

In countries such as Iran that are facing a shortage of water resources, paying attention to all water resources is of the utmost importance. Until recently, drainage management had received less attention and more drainage research focused on design issues. Following the 1992 World Summits, the International Committee on Irrigation and Drainage focused its attention on drainage management and emphasized the conservation and use of fresh-water resources in the context of comprehensive water management. Many studies have been conducted about the effects of high water levels in different aquifers. The study of the role and seasonal contribution of the drain in the hydrology of the region (King et al., 2014.) is among these studies. Nowadays, the underground drain is used to lower the water level. Among the studies in this regard, the effect of drainage system on lowering of groundwater level of Shiraz plain using groundwater model by Karimipour et al can be mentioned. (2012).

Farrokhabad plain in Dehloran is classified as folded Zagros based on the division of Iranian building units (Nabavi, 1977). Shallow water levels in the village of Farrokhabad (five kilometers southwest of Dehloran) have caused problems for the inhabitants of the village, demanding the village to move to other areas. In this study, the use of drainage system for lowering groundwater level of Farrokhabad plain is evaluated. In this regard, the hydraulic behavior of the aquifer of Farrokhabad plain was modeled using Visual MODFLOW code. After calibration and validation, the model of impact of drainage system on groundwater status of Dehloran plain was simulated under three different scenarios. Scenario One: Lowering the plain water level by underground drainage in dry, wet and normal hydrological conditions for a five-year period. Scenario 2: Lowering the plain water level by using pumping wells in dry, wet and normal hydrological conditions for a five-year period. Scenario 3: Water table drop in different hydrological periods without drainage.

The drainage system used in the first scenario includes a combination of the main collection drains with the gradient at the point of the Meymah River, where drainage discharges. Due to the curves of the water table level in the drainage range, the water level drop over five years in dry climatic conditions is about two to four meters, in wet hydrological conditions four to five meters, and in normal hydrological conditions. There are four to five meters of drainage area available. Then, a series of pumping wells were used to lower the water level, considering the potential curves in the range of pumping wells in arid climatic conditions, with a water level of about three to five meters during the normal five years. In five-year period with wet hydrological conditions, three to five and a half meters drop and in dry hydrological conditions a drop of three to five meters in the range of pumping wells were observed.

The results of the potential curves show better performance of wells than in the drain. However considering that the wells should be made to remove the water collected in them as well as transporting the water to other places, it requires more expenditures to drop the water level in this area. But with the proper design of the underground drain network, water can be transferred with gravity force to the Meymah river, and only the initial expenditure of the drainage is required. Though, with the proper design of the underground drainages, and the use of a layer of sand and coarse aggregate particles over the main branches of the drain can be used for several years. So with regard to the mentioned cases, it is more suitable to study the design of underground drainage wells. To lower the groundwater level to the desired depth, sub-drainage networks should be implemented in the direction of the land slope.

Excessive population growth over the past three decades, limited surface water resources, agricultural, industrial, urban activities and excessive exploitation of aquifers have caused irreparable damage to Iran''s water resources regarding quality and quantity. To prevent the continuation of quantitative and qualitative decline, management of exploitation and protection of groundwater should be the basis of planning in the country. Groundwater management requires an adequate understanding of the aquifer system and the use of a tool that can simulate the response to the various quantitative and qualitative stresses of the aquifer in the current and future conditions. In this regard, by using the model, real conditions in nature can be simulated with good accuracy and achieved to acceptable results. The study area of Gamasiab is located in Sahne-Bisotun plain in the northeast of Kermanshah province. In this area, only one case investigated in a small part of the aquifer. In this study, the status of the aquifer and the relationship between surface and groundwater in the entire aquifer zone of Sahneh-Bistoon plain simulated with the use of the MODFLOW 2000 code, the GMS v10 software. The results of the model show that the water budget of Sahneh-Bisotun plain is negative in the year 88-87 and is 22.81 million cubic meters per year. The river is the main factor that recharges the aquifer, which is 248.8 million cubic meters per year, and pumping from water wells is the most crucial factor in the drainage of aquifers, which is 36.4 million cubic meters per year. The results of the model show that the Gamasiab River recharges the aquifer in two reaches and drains the aquifer in other reaches. The river drains 15.55 million cubic meters of water per year from the aquifer.

Estimation of discharge flow in basin due to impact on water resource management can have an important economic role.In this research several computationals intelligence techniques suchas:ANN,SVR and ANFIS have been used to prediction the runoff dez basin.correlation between stations was investigated and stations of kamandan,zoorabad and daretakht were eliminated due to small correlation with around stations.then due to lack of human intervention with using xlstat software were evaluated  trend of stations and were selected stations without trend.Inorder to evaluate the performance of  models were used correlation,RMSE and NSE.Results of this research showed that ANFISwith clustering approach gives better estimation than grid partitioning approach.ANN, ANFIS and SVR have agood ability to simulate the flow of dez basin.

The simulation and prediction of pollutants dispersion entering into the atmosphere (such as material releases from the chimneys of industries and power plants) are important in different views, long-term environmental monitoring and dose calculations as well as issuing an appropriate warning in the event of an accident. To this end, a system of coupled meteorology-dispersion model can be used. In fact, a numerical weather prediction model is coupled to a dispersion model. In the present work, the weather research and forecasting (WRF) model is used to provide the meteorological data for the HYSPLIT (HYbrid Single Particle Lagrangian Integrated Trajectory) dispersion model.
Sensitivity and validation of the WRF model are conducted by utilizing different combinations of physical parameterization schemes (microphysics, longwave radiation, shortwave radiation, surface layer, land surface, boundary layer and cumulus convection) for the prediction of meteorological parameters in an area containing the Bushehr power plant. For this purpose, eight different configurations are used. Then, for several dates, sensitivity, and validation of the model results is carried out to find the proper configuration of the model. Assessment of the predictions of the WRF model is carried out by computing the statistical parameters including correlation coefficient (CC), root mean square error (RMSE), and comparing with the collected observational data (on-site the meteorological tower and Sodar system in Bushehr power plant and synoptic meteorological stations nearby).
After determining the proper configuration of the WRF model, dispersion simulations and annual effective dose for the adult age group are carried out by WRF-HYSPLIT coupled model under normal conditions for Bushehr power plant. The predicted annual effective dose for the adult age group by the coupled model for the years 2014, 2015 and 2016, provided 5.8×10-8 (Sv), 6.7×10-8 (Sv) and 1.1×10-7 (Sv) respectively, in return value 7.7×10-8 (Sv) for Bushehr power plant final safety analysis report (FSAR report). Comparing these results show that the simulation and prediction of dose by the coupled WRF-HYSPLIT model are in good agreement with observations and indicates the validity of the simulations. The ratio of predicted annual effective dose to dose limit for normal operation is obtained less than 0.2 percent (The results of the present work showed that the coupled WRF-HYSPLIT model can be used as a promising tool for the prediction of dispersion and dose calculations for Bushehr power plant under normal operation. In addition, the results of this coupled model can provide the required information for emergency management to forecast the movement and direction of radioactive plume and exposure dose calculations.

Topography of Tehran, density and height of buildings, traffic, width and direction of the passages with the climate, play a major role in the accumulation of pollutants. One of atmospheric parameters in the dispersion of air pollutants in Tehran decisive is the wind. In this research, the behavior of the wind in the current situation has been investigated using descriptive-analytical and cross-comparison and simulation techniques by software Matt ENVI, which is a software to analyse the climate. Collecting data was through library and field studies. The results show that in the north-south streets (parallel to the prevailing wind direction), the majority of septic streets has increased wind speed. This results in the emission of these streets. In streets that are perpendicular to the prevailing wind direction (east-west streets), the effect of altitude and the proximity of buildings to each other, in addition to the change of direction and wind speed, will causes the published accumulation of pollutants on the street. Based on the results obtained from this study, north-south streets, especially Besat Street in the neighborhood of Saadat Abad, has the highest wind speed. One of the main reasons for the increase of wind speed on this street can be channeled and its width. High wind speeds on this street has an inverse relationship to the amount of carbon dioxide released. So that the least amount of carbon monoxide was found in the street.

In this paper, the proper modeling of the wettability modification mechanism in the process of water injection with low salinity was investigated using the eclyps simulator. Most reservoirs are in their late stages of production, and still a high percentage of oil is available in reservoirs; hence the need to find a way to increase oil production from these reservoirs is more and more felt. Hence, the methods of harvesting should be used. One of the ways of treating withdrawal can be low intake of water with salinity. In this project, the method of water injection with low salinity is investigated with the aim of increasing the recycling of oil. To achieve this goal, the Ellips simulator is used. The heavy oil fluid model is modeled for oil reservoir; then water injection is simulated with different salinity (low salinity). Salines are considered to be high salinity with a concentration of 45000 PPM and low salinity, with concentrations of 24000 PPM, 8000, respectively. Water injection with different salinity increases the recovery rate of oil. The results show that water injection with salinity of PPM is 8000, with an oil recovery rate of 38% to 50%.

In arid and semi-arid areas with limited water availability such as Iran, groundwater resources are a very important source of freshwater for domestic, agricultural, and industrial use. Regarding, the most of the plains have been salinized due to the consistent groundwater over-extraction. Since these reservoirs are located underground, monitoring of them is not easy as well as it is time-consuming and expensive.
Finney et al. (1992) developed an optimization model to control the saline water infiltration in the Jakarta Basin, Indonesia. Western and Peralta (1994) introduced an optimization model for quantitative and qualitative management of complex and nonlinear aquifers in Salt Lake Valley in Utah, USA.
Shabestar plain aquifer at north-east of the Urmia Lake is one of the fertile plains of Iran. Agriculture activities use the significant amount of groundwater in the area. Surface waters can only provide a small portion of the waters used for agricultural and industrial activities. Therefore, the life of local people is severely dependent on the groundwater whereas annually a huge amount of groundwater pumped by the farmers for irrigation peruses. Over the recent years, some parts of the aquifer located in the adjacent of the Urmia Lake is influenced by the progressive incursion of saltwater as a result of over-extraction of the groundwater. The main source of the salinity is the salt solutions which entrapped within fine-grained matrix at the southwest-end part of the plain (Immobile zone). In this research, we conducted a mathematical model to explore the qualitative and quantitative characteristics of the Shabestar aquifer using GMS (Groundwater Modeling System) processor.
Material and methods GMS is a complete program for building and simulating groundwater models (Ref). Therefore, in this research, the GMS model was applied to simulate the groundwater flow in the area. This model was originally developed by the University of Brigham Young in the late 1980s. In addition, the MT3DMS (mass-transport 3D multi-species) numerical code, as a tool that simulates solute transport in ground water, was used to evaluate the saltwater intrusion in the aquifer.
Results and Discussion To qualitatively and quantitatively investigate the Shabestar aquifer, the water-level data measured in twenty-four observation wells in 2012 were imported into GMS 7.1. The model covers the most of the Shabestar basin with 624 km2 in area. Each grid cell covered an area of 1 km2.
The optimal parameter values of the aquifer were determined after model calibration settings and verification. Simulation results show that in two parts, located in the southern and the northwest of the plain, the water table consistently declines due to the over-extraction from the groundwater. Subsequently, the MT3DMS (mass-transport 3D multi-species) numerical code that simulates solute transport in ground water was used to evaluate the saltwater intrusion. The results of the model indicate that saltwater encroachment has occurred in the southern part of the plain where the groundwater depletion is primarily caused by sustained groundwater pumping.
Conclusions To safely manage the groundwater of the area, the GMS model was conducted to quantitatively and qualitatively explore the Shabestar aquifer. The results indicated that the storage depletion is occurred in the two parts of the plain: one in the central part of the plain where the water samples were taken from the production wells show high values of electrical conductivity, and another in the northwestern part. In fact, salty solutions entrapped in the immobile zone migrate toward the production wells due to the over-extraction of groundwater. In the area, salt water intrusion can occur by two mechanisms including molecular diffusion and mechanical dispersion. The distribution of the contaminated (salinized) zone can be explored by drilling of exploration wells.
In order to prevent the progressive incursion of salt solution into the aquifer, we suggest to determine the annual safe pumping rate in the aquifer.

One of the most important effects of the Manjil earthquake (M=7/7, 20/6/1990) has been triggering of the numerous landslides in the area affected by the earthquake. To predict landslides locations during the future earthquakes, it is essential to analyze the distribution of landslides triggered by the Manjil earthquake. In this paper, by employing the Monte Carlo Simulation, an area with 309 km2 including Chahar – Mahal and Chalkasar rectangles (near the Manjil Epicentre) was investigated in order to achieve a probabilistic model to predict earthquake-induced landslides. There is a good correlation between the provided map and the inventory map of landslides occurred during the Manjil earthquake.

In this paper, the Artificial Neural Network (ANN) approach is applied for forecasting groundwater level fluctuation in Aghili plain, southwest Iran. An optimal design is completed for the two hidden layers with four different algorithms: gradient descent with momentum (GDM), levenberg marquardt (LM), resilient back propagation (RP), and scaled conjugate gradient (SCG). Rain, evaporation, relative humidity, temperature (maximum and minimum), discharge of irrigation canal, and groundwater recharge from the plain boundary were used in input layer while future groundwater level was used as output layer. Before training, the available data were divided into three groups, according to hydrogeological characteristics of different parts of the plain surrounding, each piezometer. Therefore, FFN-LM algorithm has shown best result in the present study for all three hydrogeological groups. At last, to evaluate applied division, a unit network with all data and using LM algorithm was trained. Validation of the network shows that dividing the piezometers into different groups of data and designing distinct networks gives more focus on simulating groundwater level in the plain. The degree of accuracy of the ANN model in prediction is acceptable. Thus, it can be determined that ANN provides a feasible method in predicting groundwater level in Aghili plain.