نشریه هیدروژیومورفولوژی
پیاپی 27 (تابستان 1400)

Landslides are influential factors in human life that are not well-known. Several factors have contributed to the occurrence of landslide that could increase the risk of landslide in any area. Identifying these factors and their value can help to appropriate landslide zonation. The classification of areas susceptible to sliding and hazard zoning is an important step in assessing environmental hazards and plays an indelible role in the management of catchment areas (Sakar, 1995). Therefore, knowing the most important factors affecting slip instability and slipping will help us to make developmental plans using appropriate methods. Therefore, by using statistical models, their vulnerability to landslide is identified and zoned by assessing and validating them. Landslide inventory map is the best method for designing a landslide hazard map based on aerial photo interpretation, field surveys, and historic landslides. Then, the spatial distribution of mass movements is presented as a point or polygon on the map. The purpose of this research is to investigate various and effective factors in the occurrence of landslides, as well as to evaluate and compare the effectiveness of statistical models in landslide hazard zonation in Nazlochai basin and introducing the most appropriate methods.

In order to investigate the landslide susceptibility zonation, the provision of a landslide inventory map is the most important part of the work, which can be done by using of geographic information systems with high accuracy. The accuracy of landslide zonation is largely dependent on this stage. So, at first, the existing landslides were identified by using various tools including aerial photos, satellite imagery (Google Earth), existing information, GPS, and in particular field surveys. In the present study, ten factors affecting the occurrence of landslides were considered: elevation, slope, gradient direction, distance from the waterway, distance from the road, distance from the faults,   lithology, land use, rainfall and vegetation index .For landslide zonation, bivariate statistical models, including Gupta-Joshi model with its correction method, information value method, and surface density method have been used.

For landslide hazard zonation using the Bivariate Statistical Models, various factors including elevation, slope, gradient direction, distance from the waterway, distance from the road, distance from fault, lithology, landuse, rainfall and vegetation index were studied. Existence and density of landslides in the western slopes show the role of geological formations, the distance from the waterway and precipitation in the occurrence of landslide. To evaluate the accuracy of the Bivariate Statistical Models, the density ratio index and the quality sum index were used. The more distinction between risk classes is, the model is more capable, and the quality sum index is used to compare the performance of different models. Finally, with respect to the resulting values, the zoning with the information value and surface density models were found to be desirable for the studied area.

According to the results of zoning (using the Bivariate Statistical Models), lithology, distance from the waterways and precipitation are the most important factors controlling the landslide occurrence in the studied area. Particularly lithologic factors are of great importance. Most of the landslides in the study area occurred on limestone and conglomerate, which are similar to the results of the research Amir Ahmadi who worked for Iran, while these formations do not have enough area in the basin. Limestone and a small amount of dolomitic limestone with an occupancy level of 15.5% of the basin, contain more than 30% of landslides. More importantly, limestone is coinciding with north orientation that confirms the role of gradient direction in occurrence of landslides. Although some scholars ignore the role of gradient direction (A. Gemitzi, 2011), other researchers (Carrara et al., 1991; Roostaei et al., 2017) have taken it into account in their research. The impact of the human factor mainly depends on changing environmental conditions, such as road construction, inappropriate plowing, excessive grazing and water diversion for agricultural use. Therefore, by studying the researches in Iran and in different parts of the world, the slipping factors in different basins and regions are not the same and in fact, different slip conditions are present in different regions.

One of the most important wealth of a nation is the water that is flowing in the rivers of that country, and because of its impact on the settlement, site selection and development of villages, cities, communication networks and agriculture, it is of great importance since the past. Because of this, human attention has been given to river systems as one of the most vital constituents of the earth's surface in a variety of respects. River morphology is a multifaceted branch of earth science that may be considered as a specific geomorphological subject. One of the most important purposes of investigating river morphology is the geometric description of river bed parameters and interpretation of its main causes with the help of the theoretical knowledge base of water flow, solids and sediment transport. Changes in river morphology can cause many problems, including river diversion, flooding of surrounding areas, damage to hydraulic structures, as well as some environmental impacts. Short-term river variability may be gradual and continuous, but the long-term variability or under certain conditions, it is inconsistent and abrupt. One of the factors that can severely impair the stability of rivers is the construction of dams. Flow changes by the dam can affect the amount, timing, and duration of upstream and downstream currents. The purpose of this study was to investigate the morphological changes (patterns and dynamics) of the Gharasu River (from Samian Bridge to Sabalan Dam) over a period of 19-years (2000–2019).

The study area of the Gharasu River is approximately 51 km 2 in geographical coordinates of 48 ° 2 min to 48 ° 18 min east longitude and 38 ° 22 min to 38 ° 30 min north latitude in the political-administrative boundary of the city of Ardabil. The highlands of the region are mainly composed of Eocene volcanic rocks. There are also two Quaternary units of Qsc and Qst related to Sabalan volcanic activity. The study area is located in the geological division of Iran in the Alborz-Azerbaijan zone. In most of Iran's construction divisions, the Azerbaijan region has been considered the continuation of central Iran. Topographic maps, geological maps, Landsat, Sentinel and Google Earth satellite imagery, digital elevation model (DEM) images, and climatic and hydrometric data were used in the study. In order to quantify the meandering development of alluvial rivers and determine the behavioral pattern and its changes over time, the geometrical characteristics of rivers such as central angle, meander radius, wavelength, valley length and bending coefficient ( Sinusitis), were measured and analyzed to determine changes in the course of the river channel from the past up to the  present.

The mean radius of meanders for the entire Gharasu River channel during the study periods of 2000, 2010, and 2019 were 11.02, 100.90, and 99.40 meters; respectively, indicating a decreasing trend. The average length of arches during these years was 254.29, 250.24 and 251.74 meters; respectively. For this reason, over the years under the study, the mean central angle has an increasing trend from 138/50 in 2000 to 153/15 in 2010 and 157/41 in 2019. The mean curvature coefficients for the entire study period from the Gharasu River for the periods 2000, 2010 and 2019 were 1.58, 1.61 and 1.63;respectively. The values of this index during the years 2000, 2010 and 2019 were about 2.40, 2.52 and 2.58; respectively, which is of a severe meander type. The average rate of migration (Rm) of the study period from the Gharasu River during the years 2000 to 2010 was about 0.5 m / year. The value of this indicator for the period 2010 to 2019 has decreased to about 0.3 meters per year. According to calculations, the index has grown to about 0.4 m / year over the past 19 years (from 2000 to 2019). Another method called transect method was used to evaluate lateral variations of the study through the Gharasu River channel. According to calculations using the transect method over the past 19 years, a total of approximately 22.45 hectares of the Gharasu River margin lands have been lost due to erosion processes during the study period. This amount was about 13.75 ha during the period 2000 to 2010 and about 10.22 ha during the period 2010 to 2019.

In this study, the morphology and lateral variations of the ditch of Gharasu River in Ardabil province were evaluated. Based on geomorphological conditions, slope and width of the flood plain as well as other factors (such as river discharge variations), the river was divided into three sub-intervals and 30 transects in the study area. In addition to the visual interpretation, in order to evaluate and analyse the morphology of the Gharasu River, quantitative indicators were required. The present study used four indices of curvature, central angle of the cornice, channel migration rate and transect method to detect and identify the river pattern as well as lateral channel changes. These  indices were calculated over the time periods of 2000- 2010, and 2010-2019 for the study river channel. The results showed that the Gharasu River has had a developed meander pattern in most of the studies. The results of the two channel migration rate indices and the transect method also confirmed that, overall, the transverse changes of the Gharasu River channel have been low. Also, these two indices, similar to the Cornis curve coefficient and the central angle, showed that transverse dynamics have declined sharply in the last decade.

At present, it is important to accurately predict the hydraulic parameters of flow and sediment for better operation and management of rivers.Today, quasi-two-dimensional mathematical models have been widely used as an optimal and efficient solution in the hydraulics of river flow and sedimentation Zahiri et al. (2018). Mathematical models are one of the most important and accurate tools for predicting the amount of sedimentation in riverbeds and dam reservoirs, which are based on the equations governing the phenomena affecting the transfer, sediment accumulation. Gholami,et al. (2017).  Raeisi et al. (2019), in examining the temporal phenomena of the sediment measurement curve and comparing it with several statistical methods to estimate the suspended sediment load of Gamasiab watershed, showed that the time series model of the transfer function compared to other models used has higher performance.  Lai et al. (2019) in a study of the capacity of current and sediment transfer with 3D model for open surface channels showed that the model of good simulation between flow and sediment for forecasting is presented and is well matched with experimental data.In the present study, an attempt has been made to examine and determine the most appropriate models for estimating the suspended sediment load of the watershed of Hamedan River by using different models.

Abshineh basin is located in the southeast of Hamedan city and its river regime is under the semi-humid cold mountainous snow-rainy and permanent climate.In this study, the amount of sediment yield of Hamedan Abashineh dam watershed using USBR models, the middle curve of the categories Seasonal measurement curve and FAO method were estimated and while direct sampling of suspended load, the selected model by   logarithmic conversion error correction method (CF1, CF2) and GS + model were statistically analyzed and evaluated.

Examination of CF1 and CF2 correction coefficients shows that the FAO method has evaluated the amount of suspended sediment over time better than the two linear USBR methods and the intermediate method with the least amount of error.In the model without data segmentation, the FAO method with the lowest relative error percentage and the mean power of the second error was selected as the optimal method, and the similar hydrological period method was selected as the most inappropriate method for estimating suspended sediment in the basin. The results show that the USBR method follows the normal distribution to some extent and the FAO method follows the perfectly normal distribution.The results of data analysis in Kriging method show that the regression line fitted in USBR method is not well adapted and could not provide a complete analysis of sediment observation data. However, in the FAO method, it is observed that the computational data have a high and good agreement with the fitted regression line. The results showed that FAO method, due to considering more parameters in boundary conditions and the lowest amount of correction coefficients of CF1 and CF2, estimates the amount of suspended sediment with the least amount of error compared to other methods over time with more acceptable accuracy and efficiency.Also, the results of the Gs + model show that the FAO method calculates suspended sediments more accurately in terms of tons per day and has more fit and consistency with the observed sediment values, and the USBR method has the least fit.

The output results of Gs + model and comparison of suspended load estimation in models show that FAO method due to more compatibility and accuracy, more accurate sedimentary fit with observational data and with least error, as the best model and USBR method with matching and fitting Less with observational data in the next degree and similar hydrological period with the highest relative error percentage of 100.34 and low correlation coefficient were selected as the most inappropriate method for estimating suspended sediment in the basin.Reviews show that hydrological models had different results than each other. So that in the model without data segmentation, FAO method compared to other methods with the lowest percentage of relative error and the average power of the second error as the optimal and appropriate method of more accuracy and efficiency for estimating suspended sediment in a modified form in the Abshineh basin Hamedan.

The phenomenon of desertification refers to the process of destruction and devastation of natural ecosystems in arid, semi-arid and semi-humid arid regions, which leads to a decrease in biomass production and the emergence of soil destruction effects or erosion (Ekhtesasi et al., 2011: 14). Desertification occurs due to natural factors such as climatic variables and human activities (Binal et al., 2018: 10), (Collado et al., 2002: 121) and its impact on ecological processes is very high and complex, such as negative effect on plant characteristics (such as biomass, lands density and area covered by vegetation), soil biodiversity loss and reduction soil fertility, change in landscape patterns of arid areas at various geographical scales (Xu et al., 2009: 1738). Therefore, combating desertification is essential to ensure long-term soil and land exploitation in arid regions of the world. Destruction of water resources, both quantitatively and qualitatively, can lead to biomass depletion and eventually desertification. Groundwater quality is the result of all the processes and reactions that operate on water from the moment of condensation in the atmosphere until it is discharged from a well or spring.

1-2- Study area The study area included part of the Urmia catchment located in the northwest of Iran with a longitude of 44”0’ to 47”0’E and latitude of 37”0’ to 38”20’N, with an area of 14.395km2. The intersection of the mountain and the plain indicates the boundaries of the study area. (figure 1).     Fig (1): The study area 2-2- Method of Preparing a map of desertification sensitive areas in a project entitled “MEDALUS” It was carried out by the European Commission, and the ESAS model was presented in 1999. In the Medalus method, four key criteria are evaluated: soil quality, climate quality, vegetation quality and management quality. Each criterion also has indicators that, in fact, form the layers of that criterion. In Iran, by calibrating the mentioned model, at first, the most important criteria affecting the desertification process are identified and scored based on descriptive-quantitative indicators. The score 1 is considered for the best conditions and the score 2 is considered for the worst conditions and for the average conditions the score between 1-2 is considered. In the next stage, the score of the indicators is investigated and using the geometric mean based on equation 1, the status map is calculated for each main criterion:(1)   Ix = [(L1) × (L2) × (L3)…… .. (Ln)]1 / n   Ix: The status related to each main criterion includes: soil status, climate status, vegetation status, erosion status, management status and groundwater status.   L1, 2, …… n:  Indicators under investigation for each criterion N: The number of indicators under investigation for each criterion In the Medallus model, the desertification risk map is obtained by emphasizing the groundwater criterion according to the following equation:(2)   Criterion of water resources destruction= (groundwater drop × electrical  conductivity ratio × groundwater chlorine ratio × sodium absorption ratio) 1.6 .

After preparing the weighted layers, the groundwater quality map was prepared using ArcGIs software environment. According to the obtained results in the southern half and southeastern of the case study area, groundwater has low quality because the four indicators of water electrical conductivity, chlorine ratio, sodium adsorption ratio, and water table level drop ratio have the highest ratio. So that the electrical conductivity ratio in these areas is in the high class and is about (2400-4600 dS / m), the chlorine ratio is in the middle class and is equal to (500-1033 mg / l), the sodium absorption ratio is in the very high class and is about (27-92 mg /l). In these areas, the groundwater table level has decreased about 50 cm per year (figure 2).   Fig (2): Desertification intensity map with emphasis on groundwater criteria based on Medalus model.

The present research has been conducted with the aim of zoning the risk of desertification based on groundwater resources in the surrounding area of Lake Urmia in the time period from 2000 to 2018 using Medalus desertification model. According to the obtained results, 212 square kilometers of the total area of ​​the case study are in the very severe desertification class, 338 square kilometers are in the severe desertification class, 1,708 square kilometers are in the moderate desertification class, 4,723 square kilometers are in the poor desertification class, and 7,414 square kilometers are in the no desertification class. The parts located in the south and southeast of the case study area have been affected more than other areas by the destruction of groundwater resources and subsequently the occurrence of desertification phenomenon. Because the four indicators of the water electrical conductivity ratio, the chlorine ratio, the sodium absorption ratio, and the water table drop ratio have the highest ratio.  Alluvial aquifers adjacent to the lake have been exploited beyond their allowable capacity limit in recent decades, which along with the drought of the last decade has disturbed the balance of groundwater reserves and also the balance between saline and fresh water in alluvial aquifers. As a result, in some parts of alluvial aquifers near the lake, saline groundwater has infiltrated fresh water and affected its quality. On the other hand, with the increase of irregular abstraction of groundwater, the water level has risen in some areas and has caused desertification by reducing the ratio of soil ventilation. The high ratio of chlorine existing in groundwater is among the factors of soil salinity and a factor that limits the growth of vegetation in the case study area. The ratio of electrical conductivity of groundwater in the case study area is also significant due to reduced rainfall and increased evaporation ratio. This point has led to the destruction of soil structure and the creation of problems in lands drainage and has reduced and decreased the vegetation of the area quantitatively. The investigation of factors affecting the destruction of water resources showed that the geological factor and the presence of geological formations of the third period and quaternary alluvium, and agricultural and garden land use with the highest ratio of table level drop have had an important role in reducing groundwater quality and as a result, the desertification in the case study area.

Debris flows are mass movements that always threaten human activities and cause a lot of damage. The aim of this study was to zoning the risk of debris flow in the Leilan Chai catchment located in East Azerbaijan province and the impact of this hazard on the Leylan alluvial fan. For this purpose, 10 effective criteria in the occurrence of this hazard, including slope, aspect, elevation classes, land use, lithology, precipitation, distance to fault, river density, distance to river and distance to road were used to prepare a zoning map for debris flow hazard. Identifying areas with high risk sensitivity helps regional managers and planners to manage and control this risk in the basin.

Leilan Chai catchment as one of the tributaries of Zarrineh Rood River is one of the important rivers in the eastern part of Lake Urmia (Movahed danesh, 1999:45). This basin is located in East Azerbaijan province in terms of political divisions. The area of this basin is 723 Km2 and is located in the geographical coordinates of 37° 00′ 31″ to 37° 38′ 20″ north latitude and 46° 14′ 26″ to 46° 38′ 37″ east longitude. The minimum elevation of the basin is 1356 meters and the maximum elevation in the heights of Sahand Mountain is 3554 meters. This basin forms an alluvial fan at the exit of the mountain that called Leilan. In the present study, the SAW decision-making method has been used to weight the criteria. Layer fuzzy was also performed due to their importance in the occurrence of debris flow in ArcGIS and Idrisi software.

Mass movements such as debris flows have always been a threat to the development of human activities. The results of weighting the criteria using SAW method showed that lithology, slope and precipitation criteria with a weight of 0.260, 0.211 and 0.190, respectively, are of more importance in the occurrence of this hazard in the study area. After determining the weight of the criteria and sub-criteria, the layers were overlapped in the GIS environment and a potential map of the risk of debris flow in 5 classes was prepared. The results of the final map show that upstream of the basin area due to having high altitude and receiving more rainfall during the year and also having a high slope are highly sensitive to the occurrence of debris flow. The downstream areas of the basin, despite the high density of river and the presence of numerous faults, but due to the very low slope, show low sensitivity to the occurrence of debris flow.

In this study, an attempt was made to prepare a map of the risk of debris flow occurrence in the Leilan Chai basin using effective criteria in the occurrence of this risk. The final debris flow hazard map was prepared by overlaying and multiplying the final weight of the criteria in fuzzy layers in GIS environment. The results showed that about 117 Km2 (16% of the area) of the study area is in the high and very high risk classes in terms of sensitivity to debris flow. In contrast, 49% of the total area is low and very low sensitivity to this risk. Areas located in high and very high classes mainly include the upper parts of the basin, which have the potential for this risk in terms of slope, precipitation (more than 400 mm) and lithology (presence of volcanic ash). Also, according to the research results, it can be said that this hazard cannot have much effect on the Leilan alluvial fan. Due to the occurrence of this hazard in the upper parts of the basin, the possibility of transferring these materials to the downstream areas and even the surface of the alluvial fan is very low due to the very long distance.

Soil infiltration situation indicates soil behavior against water reaching the soil surface. This phenomenon determines the amount of both the water reaching the soil surface and rainfall losses. Soil infiltration of a basin has unique parameters based on its climate, soil conditions, and buildings. Soils are a set of discontinuous particles among which pores exist so that water can move from a point with more energy to a point with less energy; this property is called the passage of water through continuous pores. Gachsaran marl formation has a thickness of about 1600 m and consists of salt, anhydrite, colorful lime marl, and some shale from a lithology point of view. The age of this formation is lower Miocene (Ahmadi, 1999: 714). Estimation of soil infiltration using various erosion components can be a useful method to determine soil infiltration in the shortest time and at the lowest cost.

In this study, soil infiltration was estimated using erosion different components in different land uses in deposits of Gachsaran formation by selecting a part of the Kuhe Gach watershed of Izeh city with an area of 1202 hectares. The relationship between soil infiltration and erosion different components, such as sediment rate, runoff rate, and runoff and erosion threshold, in different land uses of Gachsaran formation was determined by the multivariate regression. Then, different erosion components were sampled at six points with three replicates and different rainfall intensities of 0.75, 1, and 1.25 mm/min in three land uses of rangeland, residential area, and agricultural land using a rainfall simulator. SPSS and Excel software was used for statistical analysis. A portable Kamphorst rainfall simulator used in this study has a plot size of 625 cm2, which determines the characteristics of soil, erosion, and water infiltration, and is suitable for soil research. It is used as a standard method to determine the soil infiltration of surface deposits in the field. The experimental plot area was selected 625 cm2 with a smooth gradient. The preparation of the testing area was followed by installing and setting the rainfall simulator and then starting a chronometer upon observing the precipitation on the screen. The amount of plot infiltration was determined at 10-min intervals (Kamphorst, 1987: 407).

The estimation of soil infiltration was acceptable and appropriate in some models in this study, which have a lower regression coefficient. Therefore, it is not possible to make appropriate comments about the estimation of the models only using regression coefficients and other statistical coefficients nor the significance levels of observational and estimated data as well as the minimum square mean of errors (MMSEs); in some cases, the MMSEs are not sufficient and require more studies (Jain and Kumar, 2006: 272). Despite scientific advances and improvement of measuring equipment, regression models are still used by researchers in different fields due to simplicity.

The results showed that the most positive and negative effects of different erosion components on estimating soil infiltration were related to sediment rate, runoff, and erosion threshold in all three mentioned land uses in three precipitation intensities (0.75, 1, and 1.25 mm min). Meanwhile, the role of sediment rate in estimating soil infiltration was slightly higher than runoff, and erosion threshold and runoff rate had no role in estimating soil infiltration in this method due to a high correlation of data.

Watersheds are physical boundaries that include natural ecosystems and all human interactions. Land-use change in watersheds has been one of the major challenges in the 21st century. According to the findings of some researchers, the effects of land use on water resources are more severe than climate change. The estimation of streamflow in watersheds with different land uses is one of the important issues in hydrological studies. In recent years, one of the most widely used methods to facilitate computation has been the use of computer models that represent the watershed response with high accuracy. Restrictions on access to sufficient hydrological data make the role of watershed simulation models more important. This study aimed at modeling monthly runoff using the SWAT model and assessing the effects of different land-use change scenarios on runoff components.

The Ahl-e-Iman watershed with 7770.86 ha area is located in Ardabil province, which was selected to predict the effects of land-use change on hydrologic response. The SWAT model has been developed to simulate different parameters of the daily, monthly, and annual hydrologic responses. The curve number method in the SWAT model was used to estimate monthly surface runoff and output runoff yield. The main inputs of the SWAT model, including daily precipitation, minimum and maximum temperature, relative humidity, and wind speed, were obtained from available data centers to prepare a digital elevation map (DEM), land use map, and soil map. The SWAT CUP program was used to calibrate the model. The input of this program is observational flow data and the output file is the SWAT model. The statistical indices of   Nash-Sutcliffe coefficient (NS), correlation coefficient (R2), and mean square error (MSE) were used to evaluate the simulation results of the model.

Sensitivity analysis and the model calibration were performed in 2003-2010. The validation of the SWAT model showed that this model had a high performance for predicting the hydrologic effects of management scenarios in the Ahl Iman watershed.  The results showed that the model had high performance in both periods. The obtained land-use map was given to the model to simulate the effect of land use change. The results of runoff simulation with both land uses of the study scenarios compared with the base flow are given in Figure 1.   Figure (1): Comparing base flow with streamflow in the first and second land-use change scenarios.

The performance of the SWAT model was evaluated in both the calibration and validation periods; therefore, this model was used to investigate different land use management scenarios. The results of the first management scenario showed that the average streamflow discharge was equal to 0.3 cms, which showed 17% decrease in discharge compared to the base land use discharge (0.6 m3). The streamflow discharge increased 36% compared to the base flow in the second scenario. Therefore, this scenario will reduce the water resources of the region in a long time.

Submarine Groundwater Discharge (SGD), any flow or all water flows on the continental banks of the sea bed, is defined regardless of the liquid composition and the driving force of its agent (Barnett et al., 2003). This occurs in a calm and continuous flow of SGD wherever its table has a positive relative hydraulic gradient with the sea level, which is attached to the surface runoff. The outflow of the flow into the sea will cause a temperature anomaly on the surface. The depletion of the underground submarine currents plays a remarkable role in the water cycle, which can be considered as an important part of water balance. Therefore, it is important to identify the range of anomalies caused by the probable depletion of SGD into the sea.

Remote sensing systems are used to determine the site of SGD depletion into the sea or lake, including aerial images with high resolution (Lewandowski et al., 2013). The aerial manual infrared imaging (Duarte et al., 2006) or ground thermal imaging (Schuetz and Weiler, 2011) are highly expensive and are certainly not suitable to assess the regional scale or continuous monitoring of SGD depletion in large blue bodies (Wilson and Rocha, 2016). Hence, free data and images of the Landset 8 satellite for 2017 and 2018 were used to determine sea surface temperature maps. For this purpose, corrections were first applied to thermal bands in the ENVI 5.3 software environment. Then, to investigate the existence of geometrical and non-geometrical errors, the quality of the data was examined on satellite images. Analyses and extraction of sea surface temperature maps were carried out using GIS 10.3.1 software. After preparing a suitable temperature map, the least surface roughness level was determined by applying different classifications in the GIS environment. Then, the distribution of each anomaly was finally prepared to prepare the distribution map of thermal anomalies. In this study, a digital elevation model (DEM) was used in GIS software to provide geomorphometryindices and maps related to environmental variables (slope, Topographic Position Index, profile curvature, general curvature, plan curvature, and height) and statistical modeling. Finally, the layers were prepared and the required adjustments were made in the software settings. Maxent Version 3.3.3 software was then used to perform statistical modeling.

Some anomalies were observed by examining the rainfall of existing pluviometry stations (n = 14) in the study area and investigating the rainfall amount (the same month, the month before, six months before, the same year, and the preceding year). The regression relationship between levels of anomalies and rainfall values determined at different times revealed a strong relationship between the anomaly levels and the amount of rainfall in the previous month. Finally, the seasons studied in 2017 and 2018, the results obtained from the study of SST, STA, and the least common level defined, along with rainfall investigations, all indicated that that the highest temperature anomalies with iterations in two different histories belonged to January 2017 and 2018, which were used for subsequent analyses. The depth studies in the range of anomalies included in January 2017 and 2018, as well as the common level of anomalies from the two dates, show that anomalies obtained in the deep-sea regions are not located and the depth of these anomalies is low within the range, which increases the probable presence of the underground spring. It can be stated that the results obtained are related to the depth of temperature anomalies because they are in the shallow depth of the sea and less than 30 meters, which is the reason to increase the likelihood of the presence of the submarine springs in these areas. According to McBride and Pfannkuch et al. (1975), Shaban et al. (2005), Thomas et al. (2002), Lewandowski et al. (2013), Wilson and Rocha (2016), and Farzin et al. (2017), SGD presence rate decreases with the distance from the shore, and the presence of submarine springs would be expected at a water level close to the shore in the disorders created at the surface of the sea, which corresponds to our results. All temperature anomalies, particularly the repeated anomalies in January 2017 and 2018 are located 3 km away from the coast, which increases the probable presence of SGD. According to the results of the jackknife test, the most important indices are in the presence of temperature anomalies and the presence of SGD (depth) and slope, which indicates that the presence of SGD spring is up to a depth of 4 meters and the appropriate slope for the presence of SGD depletion region is 5%.Figure (1): The classification map of the presence of SGD based on temperature level anomalies and environmental variables.Figure (2): The Jackknife test for model sensitivity analysis

The environmental factors play a role in the creation of temporal and spatial changes of SST and STA. Based on the results obtained from geomorphometrystudies and inequalities, as well as those of maxent modeling based on the common level of temperature anomalies in January 2017 and 2018, it can be concluded that anomalies occurred in the Bandar Magham, Bandar Nakhiloo, and coasts of  Bandar Divan, Bandar Shenas, Bandar lengeh, and Bandar kong indicate that these areas have a very high probability of underground aquifers. These submarine currents seem to have a substantial amount of evacuation that could have significant effects on the coastal ecosystem and the regional water balance. If the quality of the evacuated water is not intrinsically salty and is desirable to be used, it can be utilized as a water supply source in the area.

Due to increasing land-use changes, mainly for human activities, it is necessary to monitor vegetation changes, evaluate their trends and their environmental impacts for future planning and resource management. With the increase in population and the development of technologies, human beings are, currently, considered the most important and powerful tool of environmental change in the biosphere. Land use is the type of land use in the current situation, which includes all land uses in various sectors of agriculture, natural resources, and industry. Due to the provision of a wide and integrated view of an area, reproducibility, easy access, high accuracy of information obtained, and high speed of analysis, using satellite data is a good way to prepare a land-use map, especially in large geographical areas. One of the most widely used methods of extracting information from satellite images is classification, which allows users to generate different information. According to the type of classification method of the study area, the characteristics of the educational points get different results to separate the thematic phenomena and extract information more accurately.

Mordagh River, which is known as Mordi Chai in the region, originates from the southern slope of Sahand Mountain located in East Azerbaijan and flows south. By connecting the sub-branches, it continues its way to the city of Maragheh, passes through the city of Malekan, and enters Lake Urmia. In the present study, Landsat satellite images, TM, and OLI sensors from 2000 and 2020 were used to identify the area and prepare a land-use map. To prepare for classification and processing on them, the necessary pre-processing was first done on the images. Images were pre-processed in ENVI5.3 software using the FLAASH method. Finally, ENVI5.3 software was used to classify the base pixel and eCognition Developer 64 software was used for object-oriented classification. To evaluate the classification results, the Kappa coefficient and overall accuracy were used to evaluate the classification accuracy of the maps.

According to the obtained results, it is observed that the most area in the study area in 2000 with the method of minimum distance belongs to the use of medium and dense rangeland. The lowest area for the year 2000 is the use of residential areas. In 2020, the highest area of land use is 173.875 square kilometers. The lowest area is related to the use of snow with a rate of 0.199 square kilometers and the use of residential areas, which compared to 2000, has an increase of up to 5.54 square kilometers. In the maximum likelihood method in 2000 and 2020, the highest areas are related to medium rangeland and soil uses, respectively. The lowest area for 2000 is related to vegetation and for 2020 is snow use. In addition, in the support vector machine method, the highest and lowest areas for 2000 are related to medium rangeland and vegetation uses, respectively, and for 2020, medium rangeland and snow uses have the highest and lowest areas, respectively. According to the maps obtained from the object-oriented method, the highest area in 2000 is related to medium rangeland with 156.406 square kilometers and then dense rangeland with 96.514 square kilometers. The lowest area is related to the use of residential areas with 11.141 square kilometers. In 2020, the highest area is related to the use of dense rangeland (126.907 square kilometers). In addition, the lowest area is snow use with an amount of 5.199 square kilometers.

According to the results of this study and other studies, it can be suggested that the object-oriented classification method for land-use change studies is a more appropriate and accurate method than the pixel-based method. One of the most important reasons for achieving high accuracy in the object-oriented classification method is that in this method, in addition to spectral information, information related to texture, shape, position, and content is also used in the classification process. The study of pixel-based classification showed that in selecting educational examples, the more uniform the user is and free of mixed pixels, the more accurate the classification process is. So that the land use classification and vegetation in the pixel-based method had the highest accuracy, which due to the uniform surface of both land use and homogeneous texture, the selection of training samples in these uses with the highest accuracy and have played an important role in improving overall accuracy and kappa coefficient. Based on the results of the extent of different classes related to the land use of the basin studied in 2000 and 2020, we see a decreasing trend of dense rangeland, medium rangeland, and vegetation and increasing land use of residential areas and soil. What is very clear in these maps is the excessive reduction of pastures and their conversion to other uses.

Given the growing population and the need for food and economic issues, this transformation is obvious and it cannot be said that this change can be prevented.

Determining the temporal change of snowmelt or agriculture water equivalent of snow, predicting flood, and managing the reservoirs of a region is of utmost importance. Some major parts of the western sections of the country are located in the mountainous region and most of the precipitations of this region occur in the form of snow in winter. The runoff resulting from snowmelt has an important role in feeding the rivers of this region and it has a significant share in developing agriculture and the economy. Scientific studies have shown that climate change phenomena have significant effects on precipitations, evaporation, perspiration, runoff, and finally water supply. As the demand increases, climate changes, greatness, frequency, and the damage resulting from extreme weather events, as well as the costs of having access to water increase, as well. Therefore, evaluating the runoff resulting from snowmelt and the effect of climate change seems necessary for managing water resources.

Gamasiab basin is located in the northeast part of the Karkheh basin originating from the springs in the vicinity of Nahavand. Its basin has an area almost equal to 11040 square kilometers that have been located in the east part having 47 degrees and 7 minutes to 49 degrees and 10 minutes geographical longitude and from the north part, it has 33 degrees and 48 minutes to 34 degrees and 54 minutes geographical latitude. This basin has an altitude between 1275 to 3680 meters. In this study, snow-related data required for simulation were derived from the daily images of the MODIS sensor. To this end, first, the snow-covered area of the Gamasiab basin was measured during the 2016-2017 water years using the process of satellite images obtained from the MODIS sensor in the google earth engine system. Allgeometric justifications and calibration processes of images were applied precisely in the mentioned system. In the next step, the output of the GCM model scenarios was utilized for calculating temperature and precipitation changes in future periods. These CMIP5 kind models were under the control of two RCP45 and RCP85 scenarios and were downscaled with LARS-WG statistical model. Moreover, to investigate the uncertainty of models and scenarios, the best models and scenarios were selected for producing temperature and precipitation data of future periods; accordingly, the outputs of the models for future periods (2021-2040) having the basis period of (1980-2010) were compared using statistical indexes of coefficient of determination (R2) and Root Mean Square Error (RMSE). The results were entered into the SRM model as the inputs. In addition, temperature and precipitation data of meteorological station of the studied region as well as the daily discharge of the river flow of hydrometric station of Chehr Bridge (as located in the output part of Gamasiab basin) were used during the statistical period of October 2016 to May 2018.  

Using Digital Elevation Model (DEM) of the region and the appendage of Hec-GeoHMS in GIS software, firstly, flow direction map, flow accumulation map, and stream maps were drawn and the output point (hydrometric station of Chehr Bridge) was introduced to the border program of the identified basin and the basin was classified based on the three elevation regions. Producing temperature and precipitation data of future periods requires a long-term statistical period; accordingly, the meteorological station of Kermanshahd was selected since it was in the vicinity of the studied region. To be confident in the ability of the model in producing data in future periods, the calculated data had to be compared with the observed model and data in the studied stations. The capabilities of the LARS-WG model in modeling the mentioned parameters of this station confirmed the observed data. Moreover, the ability of the model in modeling precipitation was very good and acceptable; however, the most modeling error was related to the precipitation in Mars.
In the next phase and compared to the basic periods, the mean of changes in average precipitation and temperature was measured in the studied stations during January and Juan of 2015 to 2017(for which simulation had occurred); as an index of changing the climate, this was entered into the SRM model under climate change conditions. During the simulation period (January to Juan), it had been predicted that the precipitation parameter would decrease and the temperature parameter would increase.

The results of this study indicated that using the MODIS sensor could provide an acceptable estimation of the snow cover level of the Gamasiab basin, which lacked snow gauge data. Moreover, the results of simulation with the SRM model showed that the model could simulate the snow runoff in the studied region. As the main purpose of the study, the effect of temperature and precipitation in future periods was well stated considering the uncertainty of CMP15 series models and scenarios. The results of temperature changes indicated an average increase of 1.8 C. the results of precipitation also indicated an average decrease of more than 5%. However, decreasing precipitation in the cold months of the years had been predicted severely so that the reduction of precipitation in February was of utmost importance for feeding the snow cover and rivers, which had been estimated to be 20%. This happened while increasing precipitation was mainly related to the hot months of the year whose amount was insignificant and didn`t have that much effect on the runoff. Accordingly, due to the increases in temperature and decreases in precipitation in cold seasons, the results of runoff simulation have indicated a 24% reduction for 2016-2017 and a 29% reduction for 2017-2018 water years.