فصلنامه پژوهش های جغرافیای طبیعی
پیاپی 121 (پاییز 1401)

The wind has always been considered an energy source from two perspectives: pattern and behavior in urban contexts and potential in suburban environments. There are usually two major strategies for this

one based on observational data and the other providing simulation data with the creation of climate models at various numerical scales (Han et al., 2014: 17). Numerical models are used in most studies to evaluate regional winds nowadays (Haman et al., 2010: 954; Shimada et al., 2011: 21). Simulated weather research and forecasting (WRF) has been used to conduct studies on this topic (Liu et al., 582: 2018; Salvaso et al., 276: 2018; Matar et al., 22: 2016; Charabi et al., 1: 2019; Tokhtenhagen et al., 119: 2020). The sensitivity and performance of the WRF model to initial and boundary conditions, as well as its impact on wind simulation, are investigated in this study. A planetary boundary layer scheme is also chosen to simulate the wind field in the city of Tehran.

The Meteorological Organization provided observational data on wind direction and speed for Mehrabad, Chitgar, Geophysical, and North Tehran (Shemiran) synoptic stations from 2018 on a three-hour time scale (Table 2). Data analysis time series from two databases, the National Environmental Forecasting Center (NCEP-FNL) and the European Center for Medium-Term Weather Forecasting (ECMWF-) ERA5), were used as the initial and boundary conditions to achieve the frequency and distribution of wind direction and velocity for January, May, July, and October. The WRF model, version 4.1.2, was used to simulate the components of wind speed and direction using boundary condition data in this investigation. The RRTM longwave radiation model, the Goddard shortwave radiation design, the Noah surface model, the WSM6 microphysical schema, the two-dimensional Cumulus Betts-Miller-Janjic schema, and the three-dimensional Grell-Freitas schema were all employed in the study. The MRF Medium-Range Prediction Model, the Younesi University YSU Scheme, the MYJ Scheme, the second ACM2 Asymmetric Convection Scheme, the QNSE Normal Gaussian Scale, and the second and third MYNN Turbulence Scale are all used to test the performance sensitivity of the planetary boundary layer schemas.

By checking the characteristics of the observation stations according to table 9, all the selected stations have an average height difference of at least 110 meters, and the difference between the lowest (Mehrabad) and the highest (Shimiran) station is 360 meters. According to the results from the selected stations, this feature can be effective in the accuracy of the simulations by the weather prediction research model. It can be stated that the model cannot correctly simulate the topography due to the low horizontal resolution in the inner domain (7 km) and static data (such as DEM and land cover (by default, these data in the model have a horizontal resolution of approximately 1 km)) to do Therefore, it is not possible to establish a meaningful relationship between the height difference of the stations and the output of the model. Still, the lack of proper introduction of the elevations of the land to the model causes the performance of the model to be weak so that it can simulate the surface currents resulting from local factors correctly.

According to the analyzes done with wind and statistics, it seems that the weather research and forecasting model is more weak in estimating the wind direction in the months when the average monthly wind speed is lower, and it can be said that in the months of July and October, the wind is generally controlled by local factors with Low speed is formed, on the other hand, due to static data with low spatial resolution, the morphology and morphology of the model is weak and due to the dependence of surface currents on topography, it causes a large error in the estimation of the wind direction by the model in the mentioned months, but this weakness in The cold months decrease with the passage of dynamic systems and the increase of the monthly average wind speed, but contrary to the wind direction, the wind speed estimation outputs by the model show that the increase of the monthly average wind speed causes a decrease in the accuracy of the model in the estimation of the wind speed variable, that is why in all the statistics, July has the best simulation in wind speed variable. From the results of these studies, the selected configuration for the direction may not necessarily be associated with the desired results for the speed. It may even be possible to achieve the best output in the months of the year with different configurations. According to the selected boundary configurations and data, the results of this study seem to be consistent with the research of Santos et al. (2013), Gholami et al., Ghafarian et al. (2018), and Laighi et al. (2015) are confirmed.

River terraces represent a history of river stratigraphy and provide valuable information for understanding the interactions of tectonics, erosion, and climate change. The high altitude of the Jajrood basin has resulted in extensive glacial remnants, especially the accumulation of moraines upstream of the basin. The extent of moraine depositions under the upstream basins of the Jajrood River is not evident in the structure of river terraces and they do not have a uniform elevation. Moreover, the relations of old glacial conditions in the sedimentary interference of terraces cannot be easily reconstructed and discriminated, and there is no regular order in the stratigraphic sequence and sedimentological conditions of the river terraces. The moraine deposition seemingly has had a major role in the differences in river terrace sequences from upstream to downstream of the study area, which calls for further investigation and is also addressed in this study. Many studies have delved into the analysis of the evolution of the river terraces. Other important areas of study include paleontology and sedimentology and their effects on the canal sustainability against flow dynamics. This study aimed to explore the climatic and neo-tectonic developments of the Jajrood River Basin and the role they have played in creating terrace sequences.

This pure research investigated the role of neo-tectonic developments and climate change on the formation and evolution of terraces in the Jajrood River Basin. The research was based on analytical calculations and reports prepared through surveys as well as remote sensing methods to examine the effects of tectonics in the area. In addition, sedimentological evidence was studied to see how climate change has affected the formation and evolution of these terraces. The primary research tools were topographic and geological maps alongside aerial photographs and satellite images. Other fieldworks such as terrace morphometry using GPS measurements and sedimentological analysis helped to add insight to the findings. Then, the data was analyzed in ArcGIS. Here, the Jajrood Canyon was divided into three sections to better examine the morphogenesis of the terraces. Next, the transverse profiles and stratigraphic sections were drawn up to investigate the sedimentary strata in each section through morphometry, and then the evolution of the terraces was analyzed and reconstructed. The tectonics were studied using radar images to determine vertical displacement through the small baseline subset (SBAS) time series. Here, 27 Sentinel-1 images were used for the period from Oct. 14, 2014, to Oct. 27, 2016. which was performed using Generic Mapping Tools (GMT) in Linux OS. After preparing the interferogram maps, a map of the displacement in the study area was generated using the SBAS method (Zhao, 2013). Moreover, changes in the climate were studied using sedimentological and stratigraphic evidence.

The research findings can be classified into two parts. First, neo-tectonics was investigated through remote sensing methods and the analysis of vertical displacement across the region. Then, the effects of these neo-tectonic processes on the genesis and evolution of terraces were examined. In the second part, the effect of climate change on terrace developments was explored using sedimentological and stratigraphic evidence. In the first part, the region's tectonics was analyzed using radar imagery. In doing so, the vertical displacement was measured using SBAS time series and 27 Sentinel-1 imagery during the period from Oct. 14, 2014, to Oct. 27, 2016. The specifications of the research images are presented in Table 1. The images were selected based on the research purpose and the baseline of the images relative to each other. The VV polarization was used for all images since co-polarizations exhibit a stronger backscatter. Some sensors have different polarizations, and images with different polarizations can inform interpretations to a great extent.After preparing the images, for measuring displacement using the SBAS method, first, the temporal and spatial baseline of the images was examined and image pairs were selected for interferogram generation (Table 2 and Figure 3), which was performed using GenericMapping Tools (GMT) in Linux OS. After preparing the interferogram maps, a map of the displacement in the study area was generated using the SBAS method. In the end, the role of morphotectonic relations in the morphogenesis (i.e., origin and development) of the terraces were examined.

These findings suggest that terraces in the Jajrood Canyon are highly heterogeneous in terms of sedimentological structures, stratigraphy, and altitude. For instance, the T3 to T1 terraces, respectively, were located 130, 90, and 80 m above the river. These terraces have also experienced three intermittent processes. These three river terraces were created through the combined effects of climate change, tectonic uplifts, and the formation of dam lakes. The results of SAR interferometry (InSAR) and fieldworks also confirm the effect of active tectonic uplift differences along the main canal. These differences reflect the differences in their morphogenetic processes. The altitude of the terraces at the Oushan River tributary (Section 1) is nearly 130 meters. However, this section's altitude downstream (near Hajiabad Village) is estimated at 90 m. This difference cannot be merely due to baseline discrepancies. Evidence indicates that a sedimentary interference originating in the lake due to a past landslide downstream of the study area (Hajiabad landslide) is the cause of the higher altitude of the terraces in this section. The terrace sequences were not the same in any of the three sections. To be more precise, there are three identifiable terrace levels in Section 1, two in Section 2, and one in Section 3. In addition to the differences in the tectonic baseline, three factors—namely climate change, moraine, and the formation of a landslide-dam lake downstream—were identified for the genetic diversity, sequence differences, and terrace sequences throughout the three sections. In addition to morphometric differences, there were great differences in the genesis of the terrace sediments. The river has contributed the most to the formation and structure of terraces and their genesis. Nevertheless, the interference of landslide-dam lake deposits, moraines, and alluvial deposits, consecutively or simultaneously, have affected particularly sections 1 and 2 through differences in flow dynamics. Meanwhile, greater uniformity can be seen upstream, particularly in the Garmābdar basin (Section 3), such that upstream terraces in this section are predominantly glacial.

Human beings have faced one of the most important problems in recent years: the water crisis and the occurrence of drought. Due to this, it is important to study the drought situation when managing water resources. In any climate, drought is caused by a lack of rainfall. However, unfortunately, defining drought and how it relates to hydrological phenomena is very difficult. First of all, drought may not affect all components of the hydrological system simultaneously. The second point is that drought does not refer to an absolute lack of moisture, but to a relative one. As a result of climate change and reduced rainfall and increased evapotranspiration in recent years, drought has become a major problem in the world, in general in arid and semi-arid regions such as Iran. Therefore, drought monitoring and management are essential. Most traditional methods rely on observations from meteorological stations and emphasize droughts. However, researchers and experts have considered the use of remote sensing techniques and satellite images as a useful tool for spatial and temporal monitoring of agricultural drought. A variety of meteorological and remote sensing indicators influence the study of droughts. Standard Index-Evapotranspiration Index (SPEI) and RDI Drought Index  are two such methods.Due to the importance of the topic of this study, the study examined drought status in the study area using remote sensing indicators (EVI, NDVI), drought prediction using Markov and Kumarkov chains, and the connection between them and drought conditions.

EVI index Hewitt and Liu introduced the EVI in 1994. As defined below, improved vegetation indices minimize atmospheric effects and differences in blue and red reflections. NIR, RED, Blue are amount of reflections in the blue, red and infrared bands.   L is the aerosol penetration coefficient and soil separation parameter which was considered equal to 1 in this equation. The coefficients C1, C2, G were considered equal to 6, 7.5, 2.5, respectively.NDVI index Normalized difference vegetation index (NDVI) is an indirect measure of photosynthetic activity. The range of this index is -1 for the minimum and +1 for the maximum amount of photosynthetic activity. NDVI is defined as follows (Tucker et al., 2010):  (2)Pnear and Pred are the reflectance values of the near infrared and red wavelengths, respectively, for pixel i during the months j and year k, respectively.

According to the results, southern regions have lower values for all vegetation indices, which indicates a lack of vegetation in these regions and the existence of drought. There is no drought in the northern areas and parts of the east of the region. Also, the results show that the region often falls into the middle class of drought based on EVI and NDVI indices. The results indicate that in 2000, 96% and 78% of the region were in the middle classes of drought, and in 2020, 98% and 93% of the region were in the middle classes of drought.
The results for the EVI index showed that 47% class 1 to class 3, 20% class 2 to class 4, 12% class 4 to class 5, 29% class 5 to class 6, 27% class 6 to class 7, 21% class 7 to Class 8, 14% to Class 8 to Class 9, and about 8% to Class 9 to Class 10, indicating an increase in drought in the area. NDVI index 49% Class 1 to Class 7, 32% Class 4 to Class 5, 19, Class 5 to Class 6, 14, Class 6 to Class 7, 11% Class 7 to Class 8 and 27% Class 8 to Class 9 has done.

Then, in order to extract the landform map of the study area, the topographic position index (TPI) was used. The results showed that high areas such as ridges and hills, near zero codes indicate flat areas or areas with low slope changes and negative codes indicate low areas such as valleys and waterways. The results showed that the highest landform in the middle drainage and plain area (about 14) percent and the lowest area is related to narrow valleys (about 1 percent). The results showed that the NDVI and EVI index in low altitude areas is lower (dry condition) and the index in high altitude areas is the highest (wet condition). Thus, the topographic situation can be used to predict the drought situation.

Among climatic elements, temperature measurement is essential. Analysis of temperature changes can reveal the climatic realities of any region. Due to Iran's location in the subtropical region, severe temperature changes are its inherent features, so it is necessary to predict and monitor air temperature. Temperature fluctuations on a global scale are somewhat affected by Tele-connections. Tele-connections are intermittent anomalies that affect atmospheric patterns on a planetary scale and have an extended return period. Southern Oscillation is one of the leading indicators of global climate variability on an annual time scale and affects the Iranian climate by changing pressure patterns. The North Atlantic Oscillation (NAO) is the most prominent pattern of Tele-connections in the Northern Hemisphere, indicating the pressure difference between the northern latitudes (Iceland region) and the temperate latitudes (Azores region). Arctic Oscillation is the first active Tele-connection pattern in the subtropical region mid-winter. The Earth's climate is not constant and environmental changes can result from changing climate systems. The behavior of a climatic pattern in each region is associated with Tele-connection patterns. The main purpose of this study was to determine the role of simultaneous occurrence between NAO and AO Tele-connections with SOI on winter temperature in Iran.

In this study, the average monthly temperature data of 100 selected stations in Iran from the Islamic Republic of Iran Meteorological Organization (IRIMO), and Tele-connection indices including MEI, NAO and AO from the National-Oceanic and Atmospheric Administration (NOAA) for the thirty-year statistical period (2019-1988) were received and used as baseline data. First, all data were sorted by climatic seasons (December-January and February). Monthly normalized data were entered into STATISTICA software as the dependent variable, and Tele-connection data were entered as the independent variable to determine Pearson correlation coefficients. Since the main purpose of this study was to investigate the simultaneous effect of North Atlantic Oscillation and Arctic Oscillation with Enso Tele-connection, the positive and negative phases of the mentioned Tele-connection were identified. Thus, numbers smaller than -0.5 negative phase, between -0.5 to 0.5 neutral phase, and greater than 0.5 positive phase were considered. In the next step, the monthly temperature anomalies for the mentioned months were calculated, and the distribution of its anomalous changes in GIS software was zoned by the Inverse distance weighting (IDW) method. According to the results of correlation coefficients and the results observed in temperature anomaly maps, diagrams of the trend of changes in Tele-connection indices compared with the anomalies of changes in the average temperature of the studied stations were drawn. The results indicated that the simultaneous occurrence of the La-Nina phenomenon with the positive phases of the northern hemispheres provides the conditions for the intensification and development of cold in Iran, especially during January and February, and it is almost unlikely to expect a warm winter in this case. Comparing the trend of changes in Iran's average winter temperature with the trend of changes in North Atlantic Oscillation, Arctic Oscillation and Enso multivariate index in December, January, and February showed that in recent years, the average temperature change in December remained constant, but in January and February has been increasing for a variety of reasons, including climate change, climate change patterns, and teleportation. The gradual decrease of the North Atlantic oscillation indices, especially the Arctic oscillation, during January and February coincided with the increase in temperature, so the average temperature of Iran was normal and more than expected during the simultaneous occurrence of the negative phases of the North Atlantic oscillation indices.

This study's results showed a significant inverse relationship between NAO and AO Tele-connections with temperature in the northern and western parts of Iran, especially in February and January. The highest correlation between temperature and AO index was observed in Tabriz station (up to -0.66). However, no significant relationship was observed between the MEI index and temperature in most regions of Iran (except the southern strip). The critical result of this study is to reveal the role of separate phases of northern Tele-connections on winter temperature changes in Iran. The results showed that the positive phases of AO and NAO reduce the temperature of the northern and western parts of Iran. During severe positive phases of AO and NAO, the temperature anomalies of most parts of Iran change below normal. The results also showed that warm winters are associated with negative phases of northern indices in the under-study period. Also, the simultaneous occurrence of La-Nina and El-Nino phenomena with positive and negative phases of NAO and AO causes temperatures below or above normal in most central and southern regions of Iran. The simultaneous occurrence of El-Nino and La-Nina phenomena with neutral phases of North Atlantic oscillation and Arctic oscillation moderates the temperature of Iran and reduces the possibility of widespread and severe positive and negative anomalies. The occurrence of El-Nino phenomenon with neutral phases of NAO and AO has caused the occurrence of normal and higher-than-normal temperatures in the eastern and southeastern half of Iran. The results also showed that the La-Nina phenomenon with neutral phases of NAO and AO causes normal and higher than normal temperatures in the western half, especially in the northwestern regions.

The results showed that El-Nino and La-Nina phenomena do not have a direct and definite effect on winter temperatures in Iran. The simultaneous occurrence of La-Nina phenomenon with positive phases of North Atlantic oscillation and Arctic oscillation provides the conditions for a sharp decrease in winter temperature. It causes normal and below-normal temperatures in most parts of Iran. In contrast, the El-Nino phenomenon with negative phases of NAO and AO causes normal and higher-than-normal temperatures in Iran's central and southern regions. Contrary to these conditions, the simultaneous occurrence of El-Nino and La-Nina phenomena with the neutral phases of NAO and AO causes a normal temperature in winter in Iran, and the possibility of a below-normal temperature, in this case, is improbable.

Worries about how to plan and exploit water resources in confronting new conditions have increased as evidence of climate change becomes more apparent. This issue has led a significant portion of recent meteorological research to examine climate change's consequences on water resources. One of the most important developments is the change in the inflows to the dam's reservoirs. The Dez Dam was built over the Dez river and is located in southwestern Iran, within 23 kilometers of distance from Andimeshk. Its maximum capacity is 3.3 billion m3. As one of the most important water supply sources in the agricultural and electric energy sector of Khuzestan province, this dam has faced severe droughts in recent years, and the flow to the reservoir has been decreasing. The purpose of this study is to evaluate the amount of inflow and reservoir volume of the dam under the conditions of climate change.

To simulate basin temperature and precipitation, the accuracy of 17 Regional Climate Models of the CORDEX - WAS project (South Asia) was evaluated based on the skill score (SS). Then, a combination of ten with the lowest skill score was used to simulate the climatic parameters of temperature and precipitation for future periods. Also, the bias correction of simulated monthly precipitation and temperature data in the historical period and then the future period was done in each station and for each parameter using the change factor method. Simulations of these parameters were conducted for three 20-year periods 2020s (2020-2039), 2050s (2050-2069), and 2080s (2080-2099) under the RCP4.5 and RCP8.5 scenarios for selected stations. In this research, the SWAT semi-distributed hydrological and MODSIM models was used to simulate the inflow and reservoir volume, respectively.

The results of the downscale of the selected models and climatic scenarios indicate an increase in minimum and maximum temperatures in all months of the year and decreased average rainfall in the future. Predictions considered the range of minimum and maximum temperature increase under selected models in the RCP4.5 scenario from 1.5 - 4.2 ° C and 1.5 - 3 ° C, respectively, and in the RCP8.5 scenario from 2.7 - 5.3 ° C, and 1.6 - 5.8 ° C probable. The models also predicted the range of precipitation change to be 11 up 17% under the RCP4.5 scenario and 8 to 18% under the RCP8.5 scenario. After ensuring the hydrological model's accuracy and the general circulation models (RCM) output, the SWAT model was implemented under different scenarios. The outflows indicate a significant reduction in the flow of the Dez River in the future. The reduction rate can be between 49 and 52% in the RCP4.5 scenario and the RCP8.5 scenario was more, especially in the last decade of the 21st century, about 44 to 64%. The highest decrease will occur in the colder months of the year. In other words, the inflow decreases in December and even further decreases in April and March. One of the main reasons for the decrease in the volume of flow in the region in these months (March, April, and May) is changes in the precipitation pattern, in addition to the decrease in precipitation. In other words, in these months, the water of snow melting is associated with an increase in the river's discharge in the current climate, but such conditions will change in the future. The decrease in the flow rate entering the dam has caused a decrease in the reservoir volume of the dam, and its volume has decreased under RCP4.5 and RCP8.5 release scenarios. In the RCP4.5 scenario, the average annual volume of the reservoir will reach 1184.4, 1179.8, and 1138.8 billion m3 for the three decades of 2020-2039, 2050-2069, and 2080-2099, respectively. In the RCP8.5 scenario, this average value equals 1293.8, 1070.4, and 1008.9 billion m3, respectively. Therefore, under the two selected scenarios, the reservoir volume was reduced between 47 to 50% for the future decades. This significant decrease in volume in the future decades, which has affected the volume of water discharge of the dam, that is indicate Dez Dam will face significant challenges in come cross  with downstream needs (environmental needs, agriculture, drinking, industry, and electric energy).

This study evaluated the effect of climate change on the amount of inflow and the reservoir volume of Dez Dam under two climate scenarios. Using the semi-distributed SWAT model, the water flow simulation to the dam is done. After evaluating the model and calibrating and validating the parameters of the hydrological model, by entering the future precipitation and temperature data into the calibrated SWAT model, the flow was simulated for the three future periods under the above scenarios. The results of the climate models illustrated that the average minimum and maximum annual temperature would have increased by 3 and 3.5 degrees Celsius, respectively, for the future decades. The average annual precipitation for the study area will have decreased by 14%. The prediction of the inflow to the dam by the SWAT model under two scenarios indicate a significant decrease in the discharge of the Dez River in the future; The amount of this decrease in the RCP4.5 scenario will be between 49 to 52%, and in the RCP8.5 scenario and especially in the last decade of the 21st century, it will be more and around 44 to 64%. The decrease in the flow rate entering the dam has caused a decrease in the volume of the reservoir of the dam, and its volume will have decreased between 47 and 54 percent under the two selected scenarios for the future decades. In general, the results obtained from this study indicate that this region will move towards a climate with lower humidity and higher temperature in the future decades. This situation will increase the shortage of water resources in the basin and will intensify the water crisis in the downstream areas. Therefore, it seems that the water resources management in this basin requires a review for its sustainable development and exploitation. Since, the flow rate of Dez in the future decades will significantly decrease due to, the expected of the climate changes, the Dez dam's primary goals to meet the needs of agriculture, electricity, drinking, etc. will have face significant shortages. It is recommended to implement the policy of reducing demand, changing the cultivation pattern, recommending and developing the cultivation of low water-demanding plants, using new irrigation methods, and using unconventional waters.

Drought as a long-term stage of water scarcity is a challenging issue in water resources management and a very widespread natural disaster. Being aware of the drought situation can significantly reduce the risk of losses caused by this phenomenon through predicting and zoning the severity of the drought. One method of determining drought is the Standardized Precipitation Index (SPI), which was proposed by (McKay et al., 1993), for drought monitoring in the Colorado area. The SPI index is one of the appropriate indices to be used due to its advantages in the regional analysis of drought and the temporal relationship between events.

First, TWSI data were downloaded from GRACE-CSR satellite. The TWSI data obtained from GRACE satellite were received using coding in Google Earth engine in EXCEL format and were provided for the entire province of Khuzestan. Since the TSDI index provides a comprehensive picture of drought, TSDI values had to be calculated after reviewing the TWSA data from Google Earth Engine. To calculate this index, TSD and cumulative TSD values were calculated first. Then, the total water shortage was calculated cumulatively. In addition, the 15-year SPI index (2002-2006) was used to study drought in Khuzestan province in this study. To do this, from the stations that had better conditions in terms of data, 11 stations were selected and SPI-6-12-24 was obtained through DIP software for each of the selected stations on a monthly and annual basis.

Drought study of SPI-12-24 in Khuzestan province showed that the onset of drought in this province started in 2008 or 2009 and continued until 2013 or 2016. Among all the stations, 2009 and 2012 were the most severe years in terms of drought and in most of the stations in SPI-12-24 these two years were the driest years in the drought periods, and they were in drought conditions in all these stations during these two years. In terms of drought severity, Safi Abad, Omidiyeh, Ahvaz and Abadan stations were all ranked first to fourth with very severe drought. With regard to time, November and January in SPI-12 with frequency of 4 and May, July, August and September in SPI-24 were the most affected by standard precipitation drought. The TWSA values for Khuzestan province from 2002 to 2016 showed that according to this figure, the value of TWSA in this area found a negative trend from April 2008 to December 2016. in Khuzestan province from 2008 to 2016, three dry periods were observed, which are from April 2008 to January 2010, April 2010 to January 2014 and May 2014 to December 2016. The lowest TWSI values in each period were -11.27, -13.03, and -10.58 mm.

In this study, spatial-temporal changes of TSDI water deficit index in Khuzestan province were investigated. To do this, first the monthly index SPI-12-24 was calculated using the monthly rainfall values of 11 meteorological stations for the whole region in the period 2002 to 2016 using the DIP software. Then, to calculate the TSDI index, the data of total water storage anomalies obtained from GRACE-CSR satellite were used. Drought survey of SPI-12-24 in Khuzestan province showed that drought in this province started in 2008 or 2009 and continued until 2013 or 2016. Among all the stations, 2009 and 2012 were the most severe years in terms of drought, and in most stations in SPI-12-24 were the driest years in the drought periods. In terms of severe drought, Safiabad, Omidieh, Ahvaz and Abadan stations all ranked first to fourth with very severe drought. November and January in SPI-12 and August and September in SPI-24 were mostly affected by standard rainfall drought, with 2% of the area in normal condition, 27% in moderate drought condition, 68% in severe drought condition and 3% in a very severe drought situation, meaning that most of Khuzestan province was covered by severe and very severe drought. The study of water shortage in Khuzestan province showed that in Khuzestan province, August, January, and April were the most affected by water shortage and August with -6/89, the driest month in the whole statistical period was studied, which according to the classification The TSDI index is in a very strong category. In terms of seasonality in winter, due to the fact that the amount of groundwater was strengthened in this season, its amount changes sinusoidally and sometimes it was in a moderate position and sometimes in a very severe category. Among the seasons, autumn had the least changes compared to the other seasons and was located in the middle to upper class.

Sand and dust storms are the focus of much attention by governments and the international community because they affect health, agricultural land, infrastructure, and, generally, biological and economic resources. In this paper, critical sources of wind erosion, sand, and dust storms in Ilam province are identified, and environmental factors affecting their activating are determined. Also, the pattern of spatial and temporal changes in wind erosion, sand, and dust storms in this province has been studied according to national and international guidelines. Finally, the priority of critical sources of wind erosion, sand, and dust storm in Ilam province has been classified and determined.

Observed data from the synoptic station of Ilam province were used from 2002 to 2017 to investigate active dust sources in Ilam province. Optical Thickness Aerosol (AOD) At 550 nm, the MODIS sensor product, as a dimensionless parameter, is directly related to the concentration of airborne particles and is considered as an important criterion for detecting aerosols in the atmosphere. In addition, re-analyzed Era5 data are used to examine meteorological patterns. Dust Storm Index (DSI), wind Index, and drought index (SPEI) are calculated during the mentioned period. Then, using the GOCART model, the vertical dust flux was investigated monthly and annually, and the amount of dust emission was obtained from different sources in Ilam province. The HYSPLIT Lagrangian model also is used to determine the transmission path of dust particles through a case study that occurred on March 14 and 15, 2012.

A study of the monthly and seasonal pattern of AOD in Ilam province showed that in the warm season, dust formation is strengthened by north, and northwest winds and canalization of wind fields due to geological forcing, especially in the Mesopotamian region. Also, using observation data from synoptic stations in Ilam province dust storm index (DSI) and wind index were calculated and investigated. The results indicate that the trend of dust event changes in Ilam province has decreased over time. The highest wind index in this province was observed in the class of 0-5 m / s. In addition, in the wind class of 5-10 m / s, the maximum values are observed in the northern and western half of the province. The decrease in horizontal visibility due to dust events in the southern and southeastern of the province reaches between 1500-5000 meters. In spring and summer, the number of dusty days with the mentioned decreased visibility in these areas is more than in the other seasons. By calculating the drought index (SPEI) for Ilam province, it was observed that the drought situation had gradually intensified since 2008 when it was in a normal state so that in 2013, moderate drought prevailed in the province, and then with the continuation of this trend moderate to severe drought has been observed in this province from 2015 to 2017. Then, using the GOCART model, the vertical dust flux was investigated monthly and annually, and the amount of dust emission was obtained from different sources in Ilam province. The results showed that the highest amount of vertical dust flux occurs from Dehloran city in spring and Mehran city in summer, while the lowest amount of dust emission occurs in winter. In general, dust flux is observed in Ilam province in the southern half of Dehloran city and a small area located in the center of Mehran city. A comparison of friction velocity and dust flux quantities also showed that in the southern half of Dehloran city, dust flux values are very high despite very low friction velocity values.Finally, a case study of a dust storm on March 14 and 15, 2012, showed that during these days, the horizontal visibility at Abdanan station had reached less than 1000 meters, and at Darhshahr and Dehloran stations had reached less than 2500 meters. Establishment of the front in the southwestern regions of the country on March 14, 2012, at 12:00 UTC and in the western and southwestern regions on March 15, 2012, at 12:00 UTC, which was well observed with the change of direction and speed of the wind field in these areas, provided the conditions for dust emission in these areas so that a significant reduction in horizontal visibility occurred in many synoptic stations in the country and Ilam province on March 14 and 15, 2012. On the land surface, the establishment of a low-pressure center on the southwestern borders of the country and a high-pressure center on the southern half of the country provide the conditions for creating a strong pressure gradient in the southwestern regions of the country and strengthening the winds that finally, has caused the dust emission. The RGB image of the MSG satellite also shows the presence of dust mass on both days in the central regions of Iran.

Therefore, in Ilam province, two high and very high-intensity sources are located in the south (Mosian city) and southwest (Dehloran city) of this province. The prevailing wind direction in each season indicates the regions affected by each dust source. The dust source located in the south of Ilam, which has the highest intensity, is very active in all seasons. Due to the prevailing wind in spring, which is in the west, southwest, northeast, and northwest, Ilam and Khuzestan provinces are affected by this dust source. In summer, the prevailing wind is in the west, southwest, and northeast; this season, some areas of Ilam and Khuzestan provinces will be affected. Dominant northeasterly, westerly and easterly in autumn, and southwesterly winds in winter in this region cause Ilam and Khuzestan provinces to be affected by dust from this dust source. The second center, which is located in the southwest of Ilam province, is very active in spring, summer, and autumn. Due to the prevailing wind in spring and summer that blows from the west, southwest, northwest, and north, the provinces of Ilam, Khuzestan, and Lorestan are affected by this center. In autumn, northerly, northwesterly, northeasterly, easterly, and southwesterly prevail, and Ilam and Khuzestan provinces are affected by this center. Also, the annual review of the sources' activities showed that both had more intensity in 2013 than the other years.

Experts monitor and value the flow of goods and services produced by wetlands, some of which are traded in markets. Many other goods and services are not marketed, but economists have developed techniques to estimate the economic value of goods and services, which have complex economic and biological relationships. Market goods and services provide personal benefits, while nonmarket goods and services primarily benefit society. To estimate these values, economists have developed methods for valuing nonmarket goods. However, differences in methods, physical characteristics, and location of wetlands in the socio-economic landscape and background contribute to further differences in wetland value. This study aims to identify the type of wetland and the functions of the Qarah Qeshlaq wetland index to enable sustainable development and operation of the wetland through zoning and to determine the value and supply of ecosystem services through planning and management of the wetland. This indicates that ecological resources of this region should be allocated to intrinsic functions with a total net benefit measured by assessing the economic benefits of each usage minus the costs. Ultimately, these services and benefits are assigned to the community.

The study area of the Qarah Qeshlaq wetland (22,000 ha) is located between the provinces of East and West Azerbaijan and on the edge of Bonab and Miandoab cities (37° 13' 25" N, 45° 51' 38" E). On the other hand, it is situated on the southern shore of Lake Urmia at an elevation of 1270 m above sea level (Fig. 1). This wetland includes part of the estuary of the Zarrineh Rud, Sufi Chai, Mordagh Chai, Lilan Chay, and Haji Mosayeb Chai rivers, as well as Neor Chai, which varies in proportion to the peak discharge of the above-mentioned rivers.InVEST3.7.0 is free software available under open source license. Updated versions of the tool are released approximately every three months, which include updated science or new models. First, the main InVEST models were created in ArcGIS. But now almost all models are executable in an independent form and there is no dependence on other software.This model was developed to study the fish production and their economic value in an area. Water temperature and aquaculture conditions are the main factors considered. This model provides the most accurate results using on-site temperature parameters and aquaculture operations as inputs. The model was implemented in four steps:1) Modeling from growth stage to exploitation of aquatic species;2) Calculating the total weight of fish produced by multiplying the number by the weight of the fish, thus eliminating the fish with lower weight and those eliminated due to natural mortality;3) Harvesting all fish on the farm at the same time and restarting the farm after a user-defined downturn; and4) Assessing the processed harvest as an optional and final step of the model.This study has used a conditional valuation method to value the indirect services of the Qarah Qeshlaq wetland. A questionnaire was used to determine people's willingness to pay under hypothetical market scenarios. We used a logit regression model to examine the effects of different explanatory variables on willingness to pay.Conditional Valuation Method is the only method used to estimate unused values. The amount that people were willing to pay for environmental protection was directly asked using a questionnaire. According to Venkatachalam (2004), willingness to pay is the lowest value individuals place on environmental goods. This method seeks to predict people's willingness to pay considering hypothetical market scenarios.The results of Aquaculture service modeling 1) Depending on the scale and capacity of rearing in each farm, juvenile fish up to 0.06 kg were released, leading to the production of larger fish up to 1.4 kg as fishery product. Table 1 shows the numbers and pieces of fish. The release period in each farm ranged from 20 to 70 days per year.2) The amount of fish produced is estimated to be 280 tons per year or one breeding period after calculating the total weight of fish produced by multiplying the number of fish by their weight and eliminating lower weight fish and fish with natural mortality. Finally, all fish in the farm were harvested at the same time. 3) Reducing the inflow of the above two rivers into the Qarah Qeshlaq wetland will not only affect the water quality of the wetland, but also the volume of water in the wetland, which will also negatively affect the performance of fish farming during this period. In other words, the number of farms is reduced from 14 to 13 plots, and water quality affects the performance of the Qarah Qeshlaq and Neor Chay wetlands, reducing from 200,000 to 167934 plots over a year.4) In terms of crop production, fish farming currently produces the most, followed by the Qarah Qeshlaq wetland, while Neor River and water supply canals are in the last place. Fig. 3 depicts the mean and standard deviation of each farm, with farms 3 and 8 having relatively high production compared to the others. The river is less productive due to the lack of human intervention and the releasing of juvenile fish into the river.

The study area is the Qarah Qeshlaq wetland, with an area of 22 thousand hectares. About 60% of this wetland is in East Azerbaijan province, and 40% of it is located in West Azerbaijan. There are 13 types of land use in the area of the Qarah Qeshlaq wetland, which shows the diversity of land use and the active presence of human factors over nearly 22,000 hectares. Around 46% of the area is used for agricultural purposes, and about 28% of the land contains saline and infertile soil. The level of land use, its importance, and the geometric form have been effective in threatening the Qarah Qeshlaq wetland ecosystem. In this regard, residential centers, as the center of threat, and the access road, as the development of the threat, have contributed the most to the change in land use. Among 14 land uses in the study area, 8 land uses are considered as habitats, of which agricultural lands are habitats for ewe and chicken, barren lands, pastures, salt marshes, and floodplains are habitats for waterfowls, and river, water supply channel, and Qarah Qeshlaq wetland are habitats for aquatics. Considering the average income of each household, the willingness to pay was 50000000 Rials for the villages of Qarah Qeshlaq, Ahmadabad, Salarabad, and Majidabad, with 307 native households, leading to a total amount of 6975418531 Rials for one month. The willingness to pay was 259781500 Rials for 500 non-native people, leading to a total value of 7235200031 Rials. However, based on international calculations, the economic value of the Qarah Qeshlaq wetland was estimated at 227773688 dollars per year, whose significant difference shows less attention to ecosystem services during the lifetime of this wetland.