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Hadi Nazaripooya, Parviz Kardavani, Abdoraze Farajirad,
Volume 2, Issue 2 (7-2015)

The runoff simulation have  particular importance in Civil works, river training, design and planning of ground water resources, flood control and prevention of environmental hazards and reduction of erosion and sedimentation in the watershed. The runoff in each region varies according to climatic conditions, hydrological, soil and vegetation in the basin. Simulate these processes need to provide the necessary information on the spatial variation of these factors.  In this context, given the diversity of hydrological models, to achieve the most appropriate simulation of hydrologic models and choose the appropriate model requires the evaluation of their performance in each area is commensurate with hydrological conditions. So hydrologicl models, need to recognize the capabilities and limitations of basins.  In this study, the performance of the two models of rainfall – runoff including IHACRES and SWAT models was compared and evaluated in runoff simulation for two watersheds Yalfan and Sulan in Hamedan province in West of Iran .  

     The SWAT model uses various information, including;  hydrometry, climate , soil , topography, vegetation and land use . SWAT (Soil & Water Assessment Tool) is a river basin scale model developed to quantify the impact of land management practices in large and complex watersheds. SWAT model is a hydrology model with the following components: weather, surface runoff, return flow, percolation, evapotranspiration, transmission losses, pond and reservoir storage, crop growth and irrigation, groundwater flow, reach routing, nutrient and pesticide loading. SWAT model uses a two-level disaggregation scheme; a preliminary sub-basin identification is carried out based on topographic criteria, followed by further discretization using land use and soil type considerations. Areas with the same soil type and land use form a Hydrologic Response Unit (HRU), a basic computational unit assumed to be homogeneous in hydrologic response to land cover change.

     IHACRES model is a catchment-scale rainfall – stream flow modeling methodology whose purpose is to characterize the dynamic relationship between rainfall and stream flow, using rainfall and temperature (or potential evaporation) data, and to predict stream flow. The model can be applied over a range of spatial and temporal scales - from small experimental catchments to basins; using minute, daily or monthly time steps. It can be used to fill gaps in data, extend stream flow records, as well as explore the impact of climate change and identify effects of land use changes.

    Data used in this study includes temperature, precipitation and runoff in the period of 2010-1983. Rainfall and temperature data were used from weather stations and runoff gauging stations from basin Sulan  and Yalfan hydrometry stations. In this study we select two periods, first period from 1983 to1999 for calibration and the second period from 1999 to 2009 for validation. Some of the required basic information such as soil, vegetation, topography and land-use maps were used to carry out the research were received from the Research Center of Agriculture and Natural Resources of Hamedan province.      Accordingly, after collecting basic data and analysis of the sensitivity parameters, then calibrate and validate the models. To determine the ability of models Nash Sutcliffe (NS) and determination coefficient ( R2) were evaluated .

    The results showed that both models are acceptable in simulating runoff in both basins. According to the results obtained in the simulation by SWAT model in both basins, Nash Sutcliffe on a monthly scale in the Yalfan basin for calibration period is 0.68 and verification period is 0. 74 and for Sulan basin calibration period is 0.69 and verification period 0.76.

    The flow rate during validation periods have high accuracy. In the Yalfan basin observed daily flow 1.17 cubic meters per second and simulated flow is 1.10 cubic meters per second. As well as an overview of the values of the coefficient of determination can be seen in both basins, amount represents the high precision simulation in monthly and daily scales. Based on the results obtained in the two basins, IHACRES model has been good performance on a monthly scale, so that the Nash Sutcliffe in the Yalfan basin for calibration period 0.68 and for verification periodic 0.72 in the Sulan basin for calibration period 0.64 and for verification periodic 0. 65. In general, both models can be seen by comparing the SWAT model was calibrated and validated with the highest Nash Sutcliffe on the monthly and daily scales. Generally it can be concluded that to simulate the daily and monthly runoff, the SWAT model is recommended for evaluation hydrology process in the Yalfan and Sulan basins. It is essential in most similar studies to determine of rainfall-runoff models with respect to variability of rainfall-runoff models in different climate periods of dry and wet years.

Miss Elham Karegar, Javad Bodagh Jamali , Abbas Ranjbar Saadat Abadi , Mazaher Moeenoddini, Hamid Goshtasb ,
Volume 3, Issue 4 (1-2017)

Dust particles are important atmospheric aerosol compounds. The particles are resulting performance of strong winds at the soil surface desert areas. Sources of dust are 2 types: 1- Natural Resources 2- Human Resources. Iran is located in the desert belt which this problem cause increased the frequency of dust storms, especially in South East (Sistan) and South West. China Meteorological Administration Center classifies storms based on particles type, visibility and speed storms to 4 kind: Floating Dust, Blowing Dust, Sand/Dust Storm and Sever Sand/Dust Storm. In general, the effects of dust storms in 7 of Environment (particles into remote areas, the effect of dust particles on the material, climate, oceans and deserts), public health and health (increase of respiratory diseases , cardiovascular problems, digestive, eye, skin, reduced hearing, infections, reduced life expectancy and premature death, etc.), economic (unemployment, road accidents, damage to communication lines, air, land, sea, increase water turbidity in water utilities, creating uncertainty for all economic activities, etc.), Agriculture and Livestock (negative effect on the growth of plants and animals, reduced productivity and diversification, intensification of plant and animal pests and diseases, rising costs maintenance of livestock, etc.), socio-cultural (poverty and the loss of local jobs, destruction of subcultures, rural migration to the cities, closure of educational premises, industrial units, services, etc.) and military-security (disabling weapons, food and beverage contamination, the threat of sensitive electronics and power transmission systems, and reduce the useful life sitting on warehouse equipment, logistics cargo weight gain, etc.) can be evaluated. One way to identify, evaluate and forecast dust storm modeling. Dust cycle consists of 3 parts, dust emissions, dust and subsidence transfer dust that can be simulated by models.

In this study using the WRF_Chem model with FNL[1] input data and GOCART schema, sever dust storm in Sistan region was simulated to date 14 & 15 July 2011. Satellite images of the event was received by the MODIS sensor. Dust concentration data was received from the Department of Environment. The dust storm code, minimum visibility data and maximum wind speed data was received from the, Meteorological Organization.

The results of the simulation for dust concentration which peak amount of dust was for 21Z14July2011 and 03Z15 July 2011. Model output showed maximum wind speed 20 m/s with North to South direction in the study area. The model predicts maximum dust concentration for the latitude 31 degree North and longitude 54 degree East to 66 degree East (Within the study area). MODIS sensor images showed clearly the sever dust storm. Simulated time series in Figure 3-1 Changes in dust concentration during the event show in the Sistan region. As can be seen from the peak of the concentration of dust in 21 hours on 14 July (350 micrograms per cubic meter) and 03 hours on 15 July (425 micrograms per cubic meter) 2011 was created. Model simulation and satellite images indicated which the Sistan region, especially dry bed of Hamoun wetland in East of Iran was main source of sand and dust storm. Also, based on the model output blowing wind direction from North to South on Iran which converging these currents in East Iran caused by strong winds in the lower levels (According to the meteorological data), arise dust, increasing the dust concentration (According to Department of Environment data), increasing the dust and being transferred to the Southern regions, especially  Oman sea. To identify the source of the sand and dust storm, the path of the particle and anticipated this event cant actions and warned to stop and reduce effects its. . Simulation of dust particles in the resolution of 10 and 30 kilometers, the plains of Sistan in Iran's East region as the main source screen. The findings suggest that compliance with the maximum concentration limits on known sources of particles (especially Sistan plain dry bed of plain wetlands) is. Check drawings wear rate showed that the source of dust in the Sistan region, particularly the high potential of our wetlands dry bed of soil erosion in wind activity 120 days during the hot and dry conditions, and silt and clay up to thousands of kilometers away from their source transfers. Vector lines on maps wear rate, indicative of converging flow north-south and severe dust storms in history is this. It is better than models forecast dust events and rapid alert

[1] Final Reanalysis

Saideh Khaksefidi, Saideh Vasigh, Mohsen Taban,
Volume 7, Issue 1 (5-2020)

Proper design of the central courtyard in residential areas against Sadobist-roz-e winds in Zabol using CFD analysis
Saeide Khaksefidi - Ma Student of Architecture, Faculty of Architecture and urban planning, Jundi-shapur University of technology, Dezful, Iran.
Behzad Vasigh* - Faculty of Architecture and Urban planning, Jundi-shapur University of Technology, Dezful, Iran
Mohsen Taban - Assistant Professor, Faculty of Architecture and urban planning, Jundi-shapur University of Technology, Dezful, Iran
Wind erosion occurs in many arid, semiarid and agricultural areas of the world. Sadobist-roz-e winds are common phenomena in arid and semi-arid areas. In recent years, Sadobist-roz-e winds frequencies and intensities have increased significantly in Iran. A research on Sadobist-roz-e winds sources is important for understanding the mechanisms of dust generation and assessing its socio-economic and environmental impacts. Deserts are the main sources of emitted dust, and are highly responsive to wind erosion. Low content of soil moisture and lack of vegetation cover lead to fine particle’s release. The wind in the eastern part of Iran, Sistan, is one of the most important phenomena in the ecological studies. The intensity and velocity of the wind, has caused environmental problems. This population is distributed in more than 1000 cities, villages and nomadic settlements. Sadobist-roz-e winds is the most significant wind in the region which starts every year at the end of the spring and lasts all through the beginning of autumn, with a mean velocity of 100 km/h. Architecture and urbanization of the Sistan region have been built with the focus on reducing the amount of sand. The orientation and placement of buildings can be effective in reducing the damage to these winds. Sadobist-roz-e winds has increased in zabol since 1999. The average annual number of dust Storm events increased from 10 d during 1990–1998 (before the drought) to 54 d during 1999–2004 (after the drought). The frequency of dust storms also increased 5-fold after 1999 in the region. This shift is associated with an increase in wind speed, rainfall reduction, drying of Hamoun Lake and drought occurrence. The purpose of this paper is to determine the type of obstruction, orientation and enclosure level of the central courtyard so that it can be useful in two areas: wind speed reduction and reduction of dust contamination in the building area. Modeling of buildings is done using 3D software; and simulation of airflow using “Flow3D” Fluid Simulation software has been investigated.  Each time the flow of air was tested in different models. First, two main patterns that were expected to be appropriate to the behavior of the wind were selected. Both of them were simulated and it was found that the concave shape has a better performance. Because in addition to reducing the wind speed, it also causes rotational movement. Then, with emphasis on the central courtyard, various shapes of the layout of the builders in the central courtyard were examined. The result showed that due to the high initial wind speed, in addition to the inflow and outflow contours (in the enclosure court), the positioning and orientation of buildings at different angles, it can also be effective in reducing wind speed and decreasing wind movement. By extending this collection to more buildings and creating congestion conditions, the comfort conditions for the pedestrian were examined. In the following, with a constant elevation of 9, and enclosure (H / D ratio) and wind input to a set of 3, this load was simulated with different angles against the wind. Every time the wind speed and the wind velocity decreases. The best location was selected at a 45-degree angle faced to the wind. Further, with regard to the fact that high wind speeds are observed in the best building layout, natural obstacles were used to reduce wind speed. Among the native trees of Sistan, “Gaz” were selected because of their highest adaptability to the region's climate and for research purposes. Physical characteristics were taken and modeling was done. Each simulation was performed; the best model with a natural barrier against the wind region was identified. Although the research on locality could be highly generalized, the best location in the study, which was close to the definitions, was approached. At last, the results show that buildings or obstacles that are concave to the wind direction are more likely to prevent wind entering the shadows area than most other building types. The type of layout and orientation of the buildings against the wind and the amount of enclosure at the two points of “entry and exit of the wind”, along with the use of natural obstacles, can be very effective in reducing the wind speed and reducing the entry of dust to the comfort level.
Keywords: zabol, sadobistroze winds, CFD simulation, Residential complex, central courtyard
- Ali Najafinejad, - Hesam Heravi, - Abdolreza Bahremand, - Hossein Zeinivand,
Volume 7, Issue 1 (5-2020)

Simulation of Climate Change on river hydrograph Using WetSpa Model, Case Study: Taleghan Watershed Alborz Province
Introduction: One of the major issues in hydrology engineering is the prediction of the flood routing or rising and falling limb river hydrograph, in which the importance of the climate is very evident due to the high volatility and is therefore one of the most important factors to be carefully studied. Climate has been changing ever since. Changes refer to the variability of the long term trends in the state of the climate or average changes in temperature and rainfall that persist for extended period. Important regional water resource vulnerabilities to changes in both temperature and precipitation patterns are documented. Recent analysis from the inter-governmental panel for climate change indicates that the earth as a whole has warmed by about 0.6°C ± 0.2°C over the past century with locally and seasonally varying amounts. The changes in pattern and intensity of precipitation, melting of ice, increasing atmospheric water vapor and others has a significant natural variability on inter annual to decadal that masking the long term trend. Increased evaporation, combined with changes in precipitation characteristics, has the potential to affect runoff, frequency and intensity of floods and droughts, soil moisture, and water supply. Warming of climate system and change in its state variables are highly related to the atmosphere-land-ocean system. The climate modeling science integrates these complex systems with the Global Circulation Models (GCMs) to simulate future climate changes and forecast it for decades and centuries. Climate change scenarios developed from General Circulation Models (GCMs) are the initial source of information for estimating plausible future climate changes. In regional and local climate studies usually coarse-resolution outputs of global climate models are downscaled to produce necessary fine scale data. Statistical downscaling methods are widely used for prediction of climatic variables e.g. precipitation because of importance of these factors in environmental planning and management. The main purpose of the research is to investigate the past and future potential of climate change and its impacts on the hydrologic response of the basin.
Data and method of work: In this study, the Taleghan Watershed of the Sefidrood basin was selected as a case study due to its socio-economic significance. Elevation range from 1774 to 4362 m and a mean slope is 40.5%. The mean annual precipitation in the catchment is 591 mm. At first using weather data and meteorological data with a daily step in a 21-year period and three base maps information, including precipitation data from eight stations, temperature and evaporation data from two stations were used as input to the model. Three base maps information i.e. DEM, land use and soil types are prepared in GIS and flow hydrograph was simulated using WetSpa model in Taleghan watershed. For runoff verification, the only river station at the outlet of the catchment was used. Then, for the reference period, daily modeled runoff was compared with observed values at available in the region. In the following Future climate change (precipitation, temperature and evaporation) based on CanESM2 model from the fifth report the Intergovernmental Panel on Climate Change (IPCC) on emission scenario RCP8.5 was used for simulating the flow hydrograph during the next period (2016-2029) and its comparison with the base period (1995-2015). In this study, the performance of Statistical Downscaling Model (SDSM) was investigated to predict precipitation, temperature and evaporation. Modeled precipitation was compared with observations of 8 available stations in the region, Observed temperatures from two stations were also used for modeled temperature and evaporation verification.  
Interpretation of results: Regarding to the outputs and spatially distributed hydrological factors in daily time step the model is capable to analyze topography, soil type, and land use effects on the hydrological behavior of the watershed. Model evaluation results showed that The Nash-Sutcliffe criteria, 76% and accuracy of the simulation show the high performance of the model in this watershed. The results of the research showed that the SDSM model is well advanced to simulate Climate variables. Statistical measures of model performance such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean squared error (MSE) and the analysis of output results from SDSM model shown that this model is able to predict precipitation, temperature and evaporation indexes. According to the results of the CanESM2 model, in the considered scenario (RCP8.5), temperature will increase from 0.5 to 0.6 and Average precipitation in the future 8% will increase. Finally the results showed that in the considered scenario, the average runoff watershed will increase Up to 45% by the climate in the future. Also, the average of runoff will increase in all months of the year (except in October) compared to the base period. This increase is more pronounced for April.            
Keywords: Emission Scenario, Flood, Hydrologic Model, River Hydrograph, Simulation

* Corresponding author:

Leila Ahadi, Hossein Asakereh, Younes Khosravi,
Volume 10, Issue 2 (9-2023)

Simulation of Zanjan temperature trends based on climate scenarios and artificial neural network method

Severe climate changes (and global warming) in recent years have led to changes in weather patterns and the emergence of climate anomalies in most parts of the world. The process of climate change, especially temperature changes, is one of the most important challenges in the field of earth sciences and environmental sciences. Any change in the temperature characteristics, as one of the important climatic elements of any region, causes a change in the climatic structure of that region. The summary of the investigated experimental models on climate change shows that if the concentration of greenhouse gases increases in the same way, the average temperature of the earth will increase dangerously in the near future. More than 70% of the world's CO2 emissions are attributed to cities. It is expected that with the continuation of the urbanization process, the amount of greenhouse gases will increase. According to the fifth report of the International Panel on Climate Change, the average global temperature has increased by 0.85 degrees Celsius during 1880-2012. Therefore, knowing the temperature changes and trends in environmental planning based on the climate knowledge of each point and region seems essential. For this reason, the present study simulates the daily temperature (minimum, maximum and average) of Zanjan until the year 2100.

Research Methods
The method of conducting the research is descriptive-analytical and the method of collecting data is library (documents). To check the temperature of Zanjan city, the minimum, maximum and average daily temperature data from Hamdeed station of Zanjan city during the period of 1961-2021 were used. The data of general atmospheric circulation model was used to simulate climate variables (minimum, average and maximum temperature) using artificial neural network and climate scenarios in future periods. The output variables in this study are minimum, maximum and average daily temperature. Therefore, three neural network models were selected. For model simulation, model inputs (independent variables) need to be selected from among 26 atmospheric variables. Therefore, two methods of progressive and step-by-step elimination were chosen to determine the inputs of the model. In these methods, climate variables that have the highest correlation with minimum, maximum and average daily temperature were selected. By using RCP2.6, RCP4.5 and RCP8.5 scenarios, variables were simulated until the year 2100. Markov chain model was used to check the possibility of occurrence of extreme temperatures of the simulated values.

According to the RCP2.6, RCP4.5 and RCP8.5 scenarios and the simulation made by the neural network model, it is possible that on average the minimum temperature will be 3.6 degrees Celsius, the average temperature will be 3.3 degrees Celsius and the maximum temperature will be 2.7 degrees Celsius. Celsius will rise. The monthly review of the simulated data for all scenarios and the observed data of the studied variables shows that the average minimum, average and maximum temperatures in January and February, which are the coldest months of the year, will increase the most and become warmer. While the average minimum temperature in August, the average temperature in April and the maximum temperature in October will have the least increase. According to the simulated seasonal temperature table based on all scenarios, it was found that the average minimum, average and maximum temperature observed with the maximum simulated conditions were 6.9, 5.5 and 5.4 respectively in the winter season, and 3.3 in the spring season. 4, 2.3 and 3, in the summer season it increases by 3.3, 3.4 and 1.4 and in the autumn season it increases by 4.6, 4.5 and zero degrees. The frequency of extreme temperatures observed in all three variables of minimum, average and maximum temperature for the 25th and 75th quartiles is less than the number of occurrences of extreme temperatures simulated in all three scenarios. Based on this, all three variables will increase and there will be fewer cold periods. An increase in night temperature and average temperature in winter season and maximum temperature in summer season will occur more than other seasons. The difference between day and night temperature will be less in autumn and summer. Also, all seasons, especially the summer season, will be hotter and the occurrence of extreme temperatures is increasing for the coming years.

Keywords: climate scenarios, simulation, extreme temperatures, artificial neural network, Zanjan


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