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Volume 1, Issue 4 (1-2015)
Mountain systems have an important role on meteorological variations. Different components of the mountain affect the atmospheric parameters and have essential role in atmosphereic circulation. Garmesh wind is one of the most well-known phenomena that are related to mountain systems. In this research, mechanism of garmesh wind are identified using database of garmesh wind in the last 29 years and using remote sensing technology from 2005 to 2010.
To survey the Synoptic and dynamic conditions of atmospheric patterns in the Garmesh wind’s events in the region, SCDATA of several synoptic stations in Gilan province, including Rasht, Bandar Anzali, Astara and Jirandeh are used which had continuous long-term data in 1982-2010period After Identification of days with Garmesh wind, daily images of Modis sensor of terra and aqua satellites in visible band and 7-2-1 band are monitored for checking the cloudiness on the both sides (southern and northern slops) of Alborz mountains and data of Jirande station in southern slop of Alborz mountains are used for detecting atmospheric phenomena like precipitation and snowfall. Also for studying the synoptic and dynamic pattern of this phenomena, reanalysis data from NCEP/NCAR were used.
In this research, Based on the presence or absence of the atmospheric phenomenon (like rainfall and snowfall), three categories were identified. In the first category, Garmesh winds were happened in clear sky conditions and without any atmospheric phenomena on both side of mountain’s slope. In the second category, only cloudiness was seen at the time of the Garmesh wind. In the third category, precipitations (in this research, snowfall) were seen in southern slope of Alborz Mountains.
Statistical analysis of Garmesh wind in central plains of Gilan
Totally, Occurrence of Garmesh wind was 479 days in Rasht, during 1982-2010. The frequency of occurrence of this phenomena was in January, February, November and December and rarely, in September and June. Clouds that observed in the time of Garmesh wind were: Altocumulus (type 4), Cirrus, CirroCumulus.
Patterns of Garmesh wind mechanisms on western half of Alborz Mountain:
- B1. Garmesh wind without any phenomena
This category includes11 cases of total 47 studied cases. 29 January 2008 is an example of clear sky condition in the time of Garmesh wind. In this pattern, in the surface zonal extension of Mediterranean dynamical low pressure’s contours from west of Caspian to Gilan plain and at the same time formation of cold high pressure cell on Zagros mountains caused strong pressure gradient on southern coastal zone of Caspian Sea, As it led to the the increase of wind velocity in Rasht airport synoptic station from 11 kilometer per hour in 00 UTC to 36 kilometer per hour in 12 UTC. Dominance of warm core on southern Caspian versus dominance of cold surface air on Iran Plateau indicates adiabatic warming in northern slope of Alborz Mountains.
- B2. Garmesh wind with cloudiness
This category includes 34 cases of total 47 studied cases. Free of air mass’s patterns in the surface and conditions of atmospheric flows in low-troposphere that are similar to previous category, transition of height trough in mid-troposphere and high-troposphere can be name variant component verses previous category.
- B3. Garmesh wind and precipitation (snowfall)
This category includes 2 cases of total 47 studied cases. At the same time, surface high pressure was on Iran Plateau and low pressure system was on Caspian Sea and also Gilan providence that caused the formation of Northerly stream and west-east stream to southern coastal zone of Caspian Sea and backward of Alborz Mountains like other patterns, snowfall occurred on southern slope of Alborz Mountains. Strong southern and south-western stream and strong positive vorticity on southern slope of Alborz Mountains by deep height trough in low-troposphere has an important role on intensification of vertical motions on lee ward of Alborz Mountains.
Garmesh wind is an atmospheric phenomenon that occurs as a result of interaction between atmospheric systems in synoptic scale and topography on back ward of mountain. In the other words, existence of Alborz Mountain’s as a great wall has an important role in the interaction between synoptic systems and formation of Garmesh wind.
Formation of Garmesh wind phenomena in Gilan province, is affected by extension of Siberian high pressure’s counters and sub-tropical high pressure on central of Iran Plateau and also existence of advection of pressure’s counter like sub-polar low pressure and or the Mediterranean Sea on north of Alborz mountains are required. Without any notification to origin of air masses, three categories has been observed based on existence or absence of Phenomena (in this research, sowfall)
In 700 and 500 hPa, Geopotential height patterns and relative vorticity field indicate that in the first category, wide parts of Iran is affected by high height and negative vortisity like low troposphere, during peak hours the wind. But in the second and third category (specially in third category ) existence of upper trough and easterly extension of trough caused to reduction of height and formation of strong positive vorticity in upper level and all over of air column in both south and north slopes of Alborz mountains.
Volume 2, Issue 3 (10-2015)
Forest fire is one of the important problems in Iran which is caused by different factors such as human and natural factors. One of these factors is climate conditions that can be created by heat wave and special circulation of atmospheric phenomena. Occurrence of forest fire in north of Iran have different impacts on environment such as destruction of natural. According to the position of Iran in the dry climate zone provides required conditions for this hazard. Unfortunately,every year thousands of hectares of precious green cover is burned. Forest fires have harmful effects on human life directly,or in directly and lead to environmental destruction and pollution, global warming, loss of vegetation, and dry soil erosion. As a result, research on forest fires will become necessary. The study region is Mazandaran province forests located in north of Iran with area of 23756.4 square Kilometers.The main object of this study is to detect the forest fires using satellite data and associated analysis with synoptic approach based on weather maps.
To detect fire in the study area different satellite data such as synchronized and geostationary satellite data were used. In this study, MODIS satellite imagery and global algorithm detection of fire to detect fire in the forest and meadows of Mazandaran province were used. The climate data including weather station data and weather map were used. Other data include data of LST and vegetation products of MODIS. In order to downscale the global data an appropriate threshold was defined. In the proposed method, After geometric correction and radiometric the cloud mask was removed, And then fire potential was identified with different thresholds and tests. Three fire episodes of Savadkooh 2006, Noor , 2009 , and Behshahr, 2010 were selected for study.
Results showed a threshold value of 310 ° K for MODIS sensor band 22 is good for a global scale. Cold and small fires are not detected, Therefore Local threshold was used. In addition, surface temperature and vegetation mapping , chlorophyll amount of vegetation were used before and after the fire episode.It became apparent that the amount of chlorophyll was reduced and the temperature was increased after the fire.
The synoptic maps of the fire day showed a low pressure over the region and mid level systems indicated the advection of warm air over the area. Surface stations showed the increase of temperature and reduction of moisture during the fire days over the long period mean values.
According to the results of the study the ground level data accompanied the upper level images and pressure patterns.
Universal high performance of fire detection algorithm was used to identify areas of forest fires Using MODIS satellite images and global algorithm modified to suit the characteristics of the study area fire detection. Then three of the fires were identified with this method. The algorithms with MODIS images and weather data together indicated the validity of the study and performance of this algorithm to identify the location of fire in the study region. Therefore the method of this study can be used in other areas to detect forest fires.
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
Volume 4, Issue 4 (1-2018)
The aim of this study is to validate the identified dust generation sources in Alborz province using time series of satellite data and meteorological stations data. In first step, OLI data of Landsat 8 during the years 2013 through 2015 were used to make maps of vegetation cover, soil moisture and land cover sensibility to wind erosion. These maps were combined with geology and roughness indices by multi-criteria evaluation method to obtain a map of sand & dust source potential areas. Also, based on the location of the intersection of the air flow with the surface of the earth and the application of masks of non-wind erodible areas on them, probable sand and dust sources were identified. These regions were integrated with the map of sand & dust source potential areas using the MCE method (WLC) and based on a stratified random sampling plan, susceptible sites of sand & dust sources were identified. Then in this research, the time series of satellite data and weather stations data were used and the trend of vegetation, soil moisture and surface temperature at the location of identified areas during a 15-year period were monitored. Product of LPRM_TMI_DY_SOILM3 from TMI sensor, data of 16-day vegetation, 8-day land surface temperature and data of aerosol optical depth from MODIS sensor were received. Also ground- based data of dust from synoptic and air pollution monitoring stations were received. Changes Trend analysis of soil moisture, temperature and vegetation cover was done during the period. Also aerosol optical depth in dust events with high concentration was evaluated for possible sources. In addition, the areas with higher dust optical depth than other areas were identified during the period. Finally, identified sources was validated using ground- based data of dust.
The result of trend analysis showed a significant decrease in vegetation, soil moisture and land surface temperature at the place of possible dust sources during the studied period. Decreasing temperature in the southern part of Alborz Province and west of Tehran province was associated with higher frequency of dust in the area that shows why dust events has high frequency. Study of time series of aerosol optical depth data showed that concentration of dust is at or near the detected sources and the high concentration in this area is indicating identified areas are accurate. Checking optical depth in the event of high concentration and checking concurrent of air direction showed the detected sources has been correctly identified. Also Integration of dust information of synoptic and air pollution monitoring stations with the wind direction confirmed the high accuracy of identified dust sources.
Overall, findings showed the ability time series of remote sensing data to validate dust storm sources. The results of the analysis of the time series of the satellite remote sensing data showed that the surface temperature as an important climatic parameter can be well used in the identification and validation of sand & dust sources. Based on the results of this analysis in areas where the frequency of sand & dust storm events is high, there is a significant decrease in the surface temperature. This is particularly evident in the annual maximum surface temperature in the southwestern part of Iran, an area that is considered to be the predominant trajectory of sand & dust storm.
Volume 5, Issue 4 (3-2019)
Deforestation or vegetation degradation is one of the main drivers of global earth changes, which has significant consequences in terms of ecosystem performance and biodiversity conservation. One of the ways for studying vegetation changes as the most important indicator of land degradation is remote sensing. In this study, in order to monitor the vegetation degradation trend in Ilam Province.After obtaining and preparing the required data (410 downloaded images) in the ArcGIS and Surfer software, the multiplication, mosaic and georeferencing operations are made. Converting format of images into ASCII is the next stage of the study. By converting this format, the total number of 953552 pixels is studied within the range; after removing the lost and negative values, 328042 pixels are analyzed. Besides, using parametric statistical method of the classical linear regression and programming in R software, the trend of slope variations and significance of slope variations of vegetations are obtained for the 17-year period (2000-2016). Results of this study show that the focus of the highest trend of declining slope variations (trend of negative slop variations) is in the NDVI index across the western half of the studied area and the focus of the highest trend of increasing slope variations (trend of positive slop variations) is in the NDVI index in the center and east. Significance of the trend of slope variations also approves this claim. Thus, the focus of the highest trend of slope variations (negative) in the west and southwest of the studied area along with the highest trend of slope variations (positive) in the center and east is significant at the probable level of 0.05
Volume 7, Issue 1 (5-2020)
Analysis and Comparing Satellite Products and Simulated
Of AOD in West Iran (2000-2018)
Kaveh Mohammadpour, Ph.D. Student in Climatology, Kharazmi University of Tehran
Mohammad Saligheh, Associate Professor in Climatology, Kharazmi University of Tehran
Ali Darvishi Bloorani, Assistant Professor in RS & GIS, Tehran University
Tayeb Raziei, Assistant Professor in Climatology, SCWMRI, Iran
Introduction
Dust are the main type of aerosols that affects directly and indirectly radiation budget. In addition, those affect the temperature change, cloud formation, convection, and precipitation. In recent years, the increase of different sensors and models has made possible to research the dust. The most important studies about dust analysis has been considered of Aerosol Optical Depth (AOD) as the most key parameter, which are based on the use of remote sensing technique and global models for analyzing the behavior and dynamics of dust in recent two decades. To achieve this, it has used of MODIS and MACC to study and identify the behavior of dust in the last two decades over west Iran.
Materials and methods
Areas in this study are Ilam, Kermanshah, Kurdistan, Lorestan and Hamedan provinces. The area has studied of two data series such as: first is MACC data with a spatial precision of 14 km2 and a 3-hour time scale; and other one is MODIS sensor production on the Terra satellite with a 10-square-kilometers resolution. In order to analyze the dust in the area in the period 2000 to 2018, statistical methods and simulation has used of the AOD parameter in MACC and MODIS. Before any processing, the data regraded to 0.2 × 0.2 degrees in order to compare the data. Then, the average daily AOD formed in a 22 × 23 matrix with 560 pixels that presented with 3653 × 560 for MACC during 2003 to 2012 and 6489 × 560 for MODIS during 2000-2018. Average of daily AOD obtained of MACC and MODIS calculated using of statistical equations. Then, the spatial distribution of AOD during the dusty months for synoptic stations and total province surface extracted using of R packages during the daily time series of the periods. Finally, the spatial distribution of the obtained AOD interpolated using the kriging function.
Results and Discussion
The average annual AOD obtained from Deep Blue algorithm from MODIS was less than MACC in all of the interested stations, except for Hamedan and Khorramabad stations, and provinces surfaces.
Correlation of AOD between MODIS and MACC shown that the correlations is high between model and sensor data (R2 = 59). In addition, the spatial correlation map shows 0.38 to 0.76 in which indicates a significant relationship between the MACC and MODIS pixels and the relationship is more in the western provinces of the area than the northeast of the region (Hamedan). The monthly comparison of the mean of AOD of the sensor and the model in the whole the area shows a highest correlation between the AOD in February and October.
The interpolation of the spatial distribution in the decade of the study (2003-2012) in MACC showed that the spatial variations of AOD is decreasing from the south of Ilam to the north of Kurdistan and reached the lowest level in the north of Kurdistan province. In general, the findings of annual and seasonal spatial distribution (dry period) of dust showed that MACC overestimated AOD compared to MODIS in the area. Nonetheless, the dust pattern in both of the sensor and the model increased from south to north. Although, the dust pattern is more regular in the sensor than the model. The spatial distribution of dust in Ilam, Kermanshah, and Kurdistan provinces in MODIS and MACC shows that dust in the southern point of the Ilam province has the highest concentration and the lowest is observed in the northeast of Kurdistan province. This spatial distribution of dust showed that dust in western provinces of the area follow latitudinal trend , in which is influenced by the high topography of Kermanshah and Kurdistan provinces and the proximity of Ilam province to dust sources in the distribution of dust intensity.
Conclusion
The results showed that there was a significant correlation between the sensor and the model and the coefficient was more than 0.4 in all months on the area. The findings of the annual amount of dust in MODIS showed that the amount of dust in the years 2000 to 2009 has increased in whole areas and from 2009 onwards, this annual trend has been reduced by 2018. MACC findings also showed that the AOD has been growing up in the period, although AOD amount have had a steep slope by 2010, but since 2010, dust has a steady slope. Therefore, West Iran has experienced two active (before 2010) and inactive (after 2010) periods in dust during an 18-years period on the area. The findings of MODIS and MACC in the study area indicate that the monthly distribution of dust from April to August has the highest concentration. In general, the annual and seasonal spatial distribution (months with the highest AOD) of dust indicates that the intensity of AOD in MACC was higher than MODIS in the area. Although the sensor and model has a roughly similar pattern and increases from south to north, but the trend in MODIS is more regular than MACC.
Keywords: Aerosol Optical Depth (AOD), MACC, MODIS, West Iran
Volume 7, Issue 3 (11-2020)
In this research, two categories of data were used: the first group is data on climatic elements or unstable elements.
The annual climatic layers of the region were used for a 30-year statistical period of 2016- 2016. Measurement data on the temperature of surface temperature was obtained from a MODIS sensor in a 17-year statistical period (2000-2016). The second group of data layers and information on the ground factors or factors were stable. The layers of these variables included:
- The digital elevation layer of the area with a precision spacing of 30 meters from this layer was used as the elevation layer of the area.
2. The slope of the region, in percent, which is the layer derivative of the digital elevation model and derived from the same specifications of the DEM layer.
3. The surface layer of the surface layer that was taken from the MODIS surface coating product
4. Layer of vegetation on the surface of the earth, which was also taken from the 1 kilogram MODIS vegetation cover
5. Soil layer that was prepared by the country's water and soil organization
The rainfall factor is the most important and most important factor in determining the areas susceptible to becoming dusty. The weight of this factor in determining and identifying areas susceptible to dusty cores was equal to 239%. Vegetation factor, which was prepared using the NDVI indicator of the MODIS product, was the second factor in the development of dust-prone areas with a weight of 199.99. Relative humidity factor is the third factor or component that influences the determination of suitable areas to become the local focus of dust. The weight of this factor is equal to 0.15. The wind speed factor is in the fourth place in terms of determining the areas susceptible to dust. The relative weight of this factor is estimated at 116.0. As shown in Table 14, slope and elevation factors are the least important factors that can play a role in the production and development of dusty centers. The weight of these factors in identifying areas susceptible to formation of dusts is 0.024 and 032.2, 0 is detected. The calculated incompatibility index for this weighing is as high as 4.8, as shown in Table 15, which indicates that the contradiction between the offered weights of indices relative to each other is less than the allowed threshold (12).
Neutbay expressed the highest concentration of areas susceptible to dust mites in the eastern region, especially the northeast of the province, which includes the cities of Azna and Aligudarz. There are also parts of this category in the southern regions of the study area, including the cities of Poldokhtar and Rumshagan. In the central regions of the province as well as in the northwest of the province including the Khorramabad, Delfan, Dynasty and Dorood districts this class is not observed. In the southern parts of the city of Kohdasht, small parts of the floor of the potential centers of dust are also observed. This flooring has the most risk of becoming a dusty focus. The power source of many of the province's dusty incidents can also be said to be areas where some of them are currently potential sources of dust. Since they have played a major role in the identification and detection of these areas, rainfall and vegetation cover, these areas are exactly in line with parts of the province, which, firstly, have a mean rainfall of less than 250 mm, and the density of vegetation is less than 2 / 0 (NDVI index), which represents a very poor vegetation and, in fact, a lack of viable vegetation. In terms of land use, these areas, or inferior land, or very rangelands, are very weak.
Volume 8, Issue 1 (5-2021)
Simulation of runoff from Gamasiab basin snowmelt with SRM model
Abstract
Snow cover in a basin affect its water balance and energy balance. So, snow cover variation is a major factor in climate change of a region. Study of temporal variation of snowmelt and snow water equivalent depth is very important in flood forecasting, reservoir management and agricultural activities of an area. In the most of the mountainous basins of the country, information on snow cover were not available. Also, the number of meteorological stations in high altitude areas do not match with information needed for snowmelt simulation. Therefore, indirect methods such as the analysis of satellite images to obtain the needed parameters for simulation is necessary, which is the one of the most effective methods in estimation of runoff originated from snow. Using the NOAA satellite data for zoning the snow cover of area started firstly in the USA since the 1961 and continuous until today (spatial and temporal resolution of satellite images increased by starting the MODIS work).
Gamasiab River is one of the important branches of Karkheh basin. Its basin area is about 11040 km2 between latitude 47 degrees 7 minutes to 49 degrees 10 minutes east and latitude 33 degrees 48 minutes 4 degrees 85 minutes north. The altitude of this basin is 1275 to 3680 meters above sea level. In this study, for simulation of runoff originated from melting snow, firstly snow cover in the basin of Gamasiab in 2014 to 2017 calculated by using the satellite images of MODIS in the google earth engine system. Also, air temperature and precipitation data of synoptic stations in the area of study and daily stream flow discharges of Polechehr hydrometric station, from November of 2014 to July of 2017 was used. Then, weather and snow cover area included as the input of SRM for simulation of snowmelt runoff. To obtain the information needed to the model, physiographic characteristics of the basin including the area and different classes of height obtained from the Arc-Hydro and Hec_GeoHMS in DEM maps of GIS software. Then the snow cover areas obtained from the images of MODIS in daily interval that obtained by google earth engine system.
Using the digital elevation map (DEM) and the accession of the Arc-Hydro and Hec_GeoHMS software of GIS, firstly flow direction map plotted. Secondly flow accumulation and stream flow network maps plotted, and by introducing the basin output to the program (Polechehr hydrometric station) borders of the basin identified and classification of the basin accomplished according to the three distinct height classes. Monitoring the snow surface cover during the daily time interval showed that the area covered with snow in winter season. This area decreases as the air temperature increases. The SRM model simulated the snowmelt of Gamasiab basin with good accurately, in which, the percent of volume error or Vd was lose than 2% and the R2 was above 0.9.
The results of this research showed that the using the images of MODIS yields a reasonable estimation of the snow cover area of Gamasiab with local of data. Also simulation results showed the high capability of the SRM in snowmelt runoff of the area under study. Result showed that the coefficient of determination and volume percent of error of model was 0.93 and %0.3 for 2014-2015 and it was 0.9 and 3.33 for 2015-2016 years, respectively. The results of this study, was in consistent with the previous studies fading in which in addition of model's parameters, physiographic characteristics, basin play a major role in the accuracy of the simulation. According to the calculated and observed runoff diagram, in both years of study, peak temperatures begin in March, as the weather warms and the snow melts, and will continue until April. Considering the snow cover, it can be concluded that the main runoff of March Peak is related to snowmelt, but with the change in the shape of precipitation from snow to rain and the warming of the weather, April peak is related to rain. Regardless of acceptable simulation results of the model, the lack of snow survey station in the study area, (yield the model to face with difficulty) in process. To overcome this shortcoming, we used the presumptions of the model and recommended values of the model.
Keywords: MODIS; Remote sensing; Runoff Snow; SRM; Gamasiab.
Volume 8, Issue 4 (1-2021)
In many areas, snow cover in the mountains is a major source of surface and underground water supply. Due to climate change and its effect on the time of melting ,it is very important for environmental planning to predict the arrival time of water from snow melt to water consumption cycle. The purpose of this study is to investigate the volumetric changes and time distribution of snow flood flows in future by integrating remote sensing , GIS and climatic models.The studied area is the Upper Basin of Amir Kabir Dam, which is located on the southern slopes of Alborz Mountains. In this study, digital elevation maps (DEM) and GIS software were used to estimate parameters such as area, environment, main length, highest and lowest elevation points. In order to complete the snow cover data, MODIS products (MOD10A100) were extracted and the snow cover was extracted in the Upper Basin of Amir Kabir Dam. Next, runoff and snow melting models were simulated using SRM software. Calibration and validation of the model's acceptable performance were estimated. Then, in order to investigate the effects of climate change on the future of snowmelt runoff production in the basin of Amir Kabir Dam, the latest CMIP5 climatic models were used under four scenarios RCP2.6, RCP4.5, RCP6.0 and RCP8.5. A survey on the relationship between snow cover area , temperature and precipitation was used to predict snow cover in the future. The increase in temperature in the autumn and winter season has led to a reduction in the shape of precipitation in the form of snow, and as a result, the amount of snow storm is reduced. The results show that the amount of runoff in the autumn and winter increases due to increased rainfall in the form of rain, and it will be increased late winter and spring due to the increase in the amount of water resulting from snow melting. The results of this study are based on the increase of snow melt as a result of increased runoff volume, reduction of snow reserves and maximum flow transmission to earlier than normal conditions due to early snow melting due to temperature rise. Generally, in the future, the average annual runoff will be decreased about 1.1 cubic meters per second, and the average annual melting share will be about 13.9%
Volume 10, Issue 1 (5-2023)
Abstract
The aim of this study was to analyze the temporal and spatial nature of dust storms during the period 2016 to 2018 in Kermanshah Using the HYSPLIT routing model and the MCD19A2 product, the Modis sensor was performed in the Google Earth web engine.In order to route the origin of dust particles, the Lagrangian method of HYSPLIT model was used in 48 hours before the occurrence of dust phenomenon in Kermanshah at three altitude levels of 200, 1000 and 1500 meters.Findings from HYSPLIT model tracking maps indicate that the general route for dust transfer to the study area is the north-west-southeast route with the origin of the deserts of Iraq and Syria at three altitudes of 200, 1000 and 1500 meters. On June 17, 2016 and October 27, 2018, as well as the southwest-west route originating in Kuwait, Northern Saudi Arabia and part of Iraq on November 2, 2017.The results of the maps obtained from the MCD19A2 product of the Modis sensor, especially the maps of periodicity, cumulative concentration, spatial variation and the highest AOD map, show a high correlation with the routed maps extracted from the HYSPLIT model. In general, based on the findings of the maps extracted from the product MCD19A2, Modis sensor during the period 2016 to 2018 in Kermanshah, the central and eastern regions have always been more affected by dust storms than in other parts of the city. On average, they were more exposed to dust pollution than other parts of the city. In this regard, the final results show a high correlation between the actual PM10 data and the AOD values derived from the MODIS sensor.
Keyword: Dust, AOD, Modis, HYSPLIT, Kermanshah, Google Earth Engine
Volume 10, Issue 3 (9-2023)
Extensive and massive agriculture, along with other agricultural activities such as animal husbandry, industrial activities in the southern half of the province, has created and intensified extensive changes in the environmental resources and natural structure of the province. This extensive change can show its effects and consequences in the destruction of forest lands, the transformation of rich pastures into poor pastures and barren lands, severe soil erosion, and finally the creation and development of internal centers of dust. and intensify the severity of dust incidents in the province. Dust events have profound and significant effects on agriculture and soil fertility, health and hygiene, disruption and destruction of industries and power plants, and negative effects on the environment, including the deterioration of forests. Airborne particles, which are mainly driven to the region by dust storms, are one of the important components of the atmospheric system. They can not only change the albedo of the energy balance by acting as cloud particle nuclei, or ice nuclei.
Materials and Methods
The study location of this research is Khuzestan province, which is one of the most challenging provinces in the country in terms of environmental hazards. This province, with an area of about 6.5 million hectares, occupies about 4% of the country's area. Dust is one of the major and most important challenges of this province. Its destructive effects can be traced in various dimensions, such as the quality of water resources, the quality and performance of agricultural products, industries and energy transmission networks, and the air quality of cities. Three categories of data have been used in this research. The data of the first category is related to the data of widespread dust days in Khuzestan province. These data were obtained from the dust codes of the current air condition (ww parameter of synoptic stations of the province) during the statistical period of 2000, 2020. The second category of data was actually the remote sensing data of MODIS sensor, which included the Aerosol Optical Depth (AOD) product of MODIS sensor (MOD04 product) and Aerosol Exponential Index (AEA). These two indicators are dimensionless but with different directions. In the AOD index, higher numbers represent more aerosols in the atmosphere and in the AEA index, in addition to the presence of dust in the place, it also provides the size of the aerosol particles. Finally, the third category of data is the reanalysis data related to incoming net shortwave radiation (SNSR), which was taken from the reanalysis data of the European ECMWF database version ERA5 with a spatial resolution of 0.5 arc degrees.
Conclusion
In this research, it was tried to investigate the influence of the dust event in the context of fluctuations and daily changes in the amount of net shortwave radiation received on the earth's surface. The results of the investigation of three cases of widespread dust in the province showed that in these three cases of widespread dust, aerosol particles are generally in the central, southern and western parts of the province (plain and lowland areas of the province) from the type of medium to large particles (index angstrom between 0.5 and 1) and in the eastern and northeastern parts, it was of the type of coarse particles (angstrom index less than 0.5). In the context of the impact of dust events on the amount of shortwave radiation received by the earth's surface, it was seen that in the dust event of July 22, 2010, the Angstrom exponential index indicates the presence of coarse particles in the atmosphere near the earth's surface and the AOD index also indicates the presence of dense dust in the entire area of the province. The received net shortwave radiation (at 12 noon or 09 UTC) was about 194 watts per square meter (about 28 percent) lower than the average for the same month. This drop rate was less in the other two dust waves, whose AOD and Angstrom index values indicated finer and less concentrated dust. In the dust wave of June 19, 2012, the amount of net shortwave radiation received was only 5% (25 W/m2 at 12 noon or 09 UTC) less than the long-term average, and this drop in the dust event of May 12, 2018 was equal to 28 W/m square (about 4% drop compared to the average of the same month).
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