Geomorphology
Shahnaz Alizadeh; Mojtaba Yamani; Mohammad Reza sarvati; Manijeh Ghahroudi Tali
Abstract
Neglecting coastal erosion can lead to environmental hazards that are among the main factors affecting human communities and facilities. Paleontology researches demonstrate tens of meters fluctuation in water level of the Caspian Sea. The shores of the Caspian Sea have variable topography and land use ...
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Neglecting coastal erosion can lead to environmental hazards that are among the main factors affecting human communities and facilities. Paleontology researches demonstrate tens of meters fluctuation in water level of the Caspian Sea. The shores of the Caspian Sea have variable topography and land use including lowlands (estuaries of rivers, gulfs and progradation) and sandy uplands. In this study, spatiotemporal analysis was used to analyze the changes in sandy coasts in relation to land use changes and the adaptation of the coastal line in the study area within the framework of coastal cells. Land use data for the years 1975 and 2020 were extracted using SAGA and ENVI software, and land use changes were analyzed using IDRISI software. The results showed that 68 kilometers of the coast have been unstable, with the majority of these areas experiencing erosion due to human activities (land use changes), including cells 10 and 3. Also, the erosion of unstable cells 5, 6, and 1 is of natural erosion type (sea level changes), and the erosion of unstable cells 9 and 2 is of natural-human erosion type. The remaining 24 kilometers of the studied coastline have been stable coasts, with the majority of coastal areas experiencing natural erosion (sea level changes), including cells 7 and 8. Cell 4 has had sustainable coasts with erosion of a natural-human type.
Geomorphology
sayyad Asghari Saraskanrood; abozar sadeghi; elham molanouro
Abstract
Snow-covered (SC) surfaces influence the land surface energy balance through albedo feedback, and also have a major impact on climate processes, human activities, and the hydrological cycle. Land surface temperature is one of the main elements in knowing the climate of a region, whose changes and fluctuations ...
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Snow-covered (SC) surfaces influence the land surface energy balance through albedo feedback, and also have a major impact on climate processes, human activities, and the hydrological cycle. Land surface temperature is one of the main elements in knowing the climate of a region, whose changes and fluctuations in different altitude classes are very useful for hydrological studies. The purpose of this study is to evaluate and investigate the relationship between ground surface temperature and snow cover level with the topographical component of height in Urmia lake basin. In this research, due to the ease of access to remote sensing data and the appropriate temporal and spatial separation of Terra satellite images, monthly, seasonal and annual MODIS sensor images have been used in the period of 1379-1399. The obtained results show that there is an inverse relationship between LST and SC, also the examination of SC maps and elevation classes shows that there is a direct relationship between these two variables, in fact, with the increase in altitude, the stability of snow in the region increases so that at altitudes higher than 3000 m, the amount of snow cover is more than 98% compared to the region. The changes in the temperature of the earth's surface at different altitudes are the reverse of the changes in the snow cover, so at altitudes less than 2000 meters, the annual average temperature is 21-35 Celsius, but at altitudes higher than 3500 meters, the average temperature is about 7-13 Degree.
Geomorphology
Ali Bigham; S.Asedolah Hejazi; Mohammad Hossein Rezaei Moghaddam; Jamshid Yarahmadi; Fariba Karami
Abstract
Changes in erosion and sedimentation of the basin are one of the most important factors that affect different parts of human life and natural life. it is very necessary to receive these changes quantitatively, which mainly take place under temperature fluctuations and climate changes in different regions, ...
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Changes in erosion and sedimentation of the basin are one of the most important factors that affect different parts of human life and natural life. it is very necessary to receive these changes quantitatively, which mainly take place under temperature fluctuations and climate changes in different regions, in order to be more prepared to deal with its negative consequences. In this research, erosion and sedimentation changes in Hajiler watershed were investigated and predicted using GeoWEPP and SWAT models. Based on this, first, by using the data of the current situation of the Ahar synoptic station and using the SDSM model, the changes of the statistical period2020-2040 in three scenarios RCP2.6-RCP4.5-RCP8.5 were investigated, then simulation and prediction of erosion changes was carried out. and sedimentation was done under the influence of climate change by using popular models. The output of the SDSM model indicates an increase in temperature and a decrease in rainfall for the basin until 2040.And the analysis of the simulation results of the sedimentation rate of the models showed that in the studied basin, the GeoWEPP with the selection of the domain method has a suitable level in estimating the sedimentation rate compared to observational statistics. The final model was chosen to predict the amount of sediment in the mentioned period of the basin. Using the downscaled results of the atmospheric general circulation model, the sediment changes in the statistical period of 2020-2040 under the above mentioned three scenarios were estimated as -1.97, 4.45, and 2.98, respectively.
Geomorphology
roya panahi; Mitra moshashaie; Meysam moshashaee
Abstract
First, to extract the morphological variables of the channel, such as the Entrenchment Ratio (ER) index, Width/Depth ratio (W/D), curvature coefficient, channel slope, in the software environment. HEC-RAS (version 5.0.7) was extracted and the bed materials obtained from field investigations were collected. ...
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First, to extract the morphological variables of the channel, such as the Entrenchment Ratio (ER) index, Width/Depth ratio (W/D), curvature coefficient, channel slope, in the software environment. HEC-RAS (version 5.0.7) was extracted and the bed materials obtained from field investigations were collected. And according to the difference of the slope of the river of Mereg River was divided into four reaches and the curvature coefficient and radius of curvature were calculated in the GIS environment (version 10.5) for each section. 44 cross sections were used to calculate the river in level II Rasgen. The results of this study show that Mereg River is in the first reach in the F6 class. in the second and third reaches of the river in the C6 class, and in the fourth reach of the river in the B6 class. The characteristics of cross sections in category F6 are high bed slope, low subsidence index and less developed flood plain, and the potential of side erosion is very high. In the cross sections of category C6, the amount of slope has decreased, in addition, the Entrenchment Ratio (ER) index has increased and the floodplain has expanded, and the controlling effect of vegetation on the stability of the range is very high. cross sections in category B6, the slope is lower than other intervals, the Entrenchment Ratio (ER) index is average and finally the erosion potential of the side is low.
Geomorphology
Reza Abbasian valandar; shahram roostaei; Davoud Mokhtari
Abstract
The Tamtaman area is located between 37◦38/00//-37◦44/00//north and 44◦40/30//-44◦59/30// east in northwestern Iran, approximately 15 km northwest of Urmia. This study aims to identify and zoning the potential development of karst in the area of Tamtaman cave in west Azerbaijan province using ...
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The Tamtaman area is located between 37◦38/00//-37◦44/00//north and 44◦40/30//-44◦59/30// east in northwestern Iran, approximately 15 km northwest of Urmia. This study aims to identify and zoning the potential development of karst in the area of Tamtaman cave in west Azerbaijan province using the AHP method. In this study, the information layers of lithology, tectonics, topography, slope, aspect, hydrology, land use, and climate have been considered as factor maps. The above layers have been called to extract the karst potential model in the GIS environment. Different information layers were classified as Criterion maps by applying expert judgment and assigning the weight of each layer in Expert Choice software and field visits. Finally, according to the obtained weight, the karst development zoning map in the Tamtaman area was obtained. The results obtained in this region exhibited a total area, of 6.68% within the very poorly developed class, 15.64% in the less developed class, 42.50% in the normal developed class, and 35.18% in the developed floor are located. The results show that in the Tamtaman region, the lithological and tectonic factors have the highest weight and are the most important factors controlling potential karst growth, while the land-use factor has the least impact on karst formation.
Geomorphology
heeva elmizadeh; Hadi Mahdipour
Abstract
The purpose of this research is the automatic recognition of morphic patterns of drainage network in the center of Qeshm Island using High Resolution Panchromatic Remotely Sensed (HR-PRS) and fuzzy clustering algorithms. It also investigates the efficiency of these methods in the GeoEye-1 satellite imagery ...
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The purpose of this research is the automatic recognition of morphic patterns of drainage network in the center of Qeshm Island using High Resolution Panchromatic Remotely Sensed (HR-PRS) and fuzzy clustering algorithms. It also investigates the efficiency of these methods in the GeoEye-1 satellite imagery segmentation of the study area in order to detect geomorphic features in areas with cloud and shadow coverage. In this regard, fuzzy segmentation of HR-PRS panchromatic images of the study area, after radiometric and geometric preprocessing using FWS, MSA, IDF and CFM algorithms, was performed in MATLAB software. Finally, the studied fuzzy clustering algorithms with fuzzy parameters are applied to the input HR-PRS images and the results are discussed. The results show that the Classical Fusion Method and FCM (CFM) clustering algorithm has the best performance in the field of fuzzy segmentation and detection of the studied indices. . As a result, the image borders are well defined. The reason for this is the use of fuzzy numbers as well as efficient clustering methods in this method. These results also show that remote sensing technology, by providing multi-time images, can be a very good basis for monitoring and detecting environmental changes, detecting effects and accurately extracting information from images. Also, the use of clustering algorithms and fuzzy features is a suitable and optimal method for integrating HR-PRS satellite image information from a geographical area with the aim of segmentation.
Geomorphology
vahid rahmatinia; Bakhtiar Feizizadeh
Abstract
In this study, 5 main DEM derivatives of 12.5 m ALOS satellite (slope layer, slope direction layer, curvature layer, cumulative flow layer and altitude layer) as well as Sentinel-2 satellite images and NDVI vegetation index were used as auxiliary layers. Segmentation in this area was performed using ...
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In this study, 5 main DEM derivatives of 12.5 m ALOS satellite (slope layer, slope direction layer, curvature layer, cumulative flow layer and altitude layer) as well as Sentinel-2 satellite images and NDVI vegetation index were used as auxiliary layers. Segmentation in this area was performed using segmentation multi resolation method. In this segmentation, the height layer was given a value of 3, the curvature layer was given a value of 2, and the other layers were given a value of 1. Then, using Layer Values and Geometry algorithms and assign class commands, landforms located in the western and southwestern slopes of Zagros (Aligudarz city area) have been classified. The results showed that the use of Layer Values and Geometry algorithms and assign class commands have a good ability to isolate and classify landforms, so that 8 types of landforms (slopes, ridges, water areas, precipices, peaks, ridges, lowlands and lowlands) Kappa coefficient was 0.87 and overall accuracy was 91.71%. The ridge landforms form the largest part of the region and are the dominant landforms of the region and have a good distribution in different parts, but the peak landforms with the minimum area have formed only a limited part of the study area.
Geomorphology
fariba esfandiyari darabadi; hadi rafiei mahmoodjagh; roya farzaneh
Abstract
Today, the preparation of land use maps using remote sensing data is one of the most important methods for producing land use maps and land use assessment together.
Lack of proper infrastructure, non-observance of land development capability in selecting land uses and its unprincipled management leads ...
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Today, the preparation of land use maps using remote sensing data is one of the most important methods for producing land use maps and land use assessment together.
Lack of proper infrastructure, non-observance of land development capability in selecting land uses and its unprincipled management leads to the phenomenon of soil erosion.
The purpose of this study is to prepare land use maps using object-oriented method and to prepare soil zoning maps of Zarrineh Rud catchment for 2000 and 2018 Landsat satellite using WLC method. The results showed the detection of changes from object-oriented classification
The highest rate of change in rainfed and irrigated agricultural land uses has been faced with the largest increase in area in the region.
The trend of changes in barren land uses, rich and medium rangeland, has been decreasing over time, so that the area has decreased by 14.04, 10.66 and 5.73 percent, respectively.
Man-made use has been increasing almost uniformly over time, which has grown by 2.47% over 18 years.
The results obtained from the erosion zoning maps produced in 2000 and 2018 showed that there are two very high-risk and high-risk classes, each covering 15.29 and 27.51 percent of the area. These classes are mostly located in rainfed, irrigated, barren and medium range agricultural uses.
Geomorphology
hojatolah younesi; ahmad godarzi; Masoud Shakarami
Abstract
Today, hybrid models of artificial intelligence are considered as a suitable method for simulating hydrological phenomena, including quantitative estimation of river flow. For this purpose, there are various approaches in hydrology to estimate the flow rate of rivers, of which artificial intelligence ...
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Today, hybrid models of artificial intelligence are considered as a suitable method for simulating hydrological phenomena, including quantitative estimation of river flow. For this purpose, there are various approaches in hydrology to estimate the flow rate of rivers, of which artificial intelligence models are the most important. Therefore, in this study, the performance of support vector-wavelet regression, backup vector-gray wolf regression and bat-support vector regression models to simulate the flow of Kashkan river located in Lorestan province during the statistical period of 2010-2011 in the daily time scale were analyzed. The criteria of correlation coefficient, root mean square error and mean absolute value of error and bias were selected for evaluation and performance of the models. The results showed that the hybrid models have acceptable results in simulating the river discharge. Comparison of models also showed that the support-wavelet vector regression model in the validation stage showed values of R2 = 0.960, RMSE = 0.045, MAE = 0.024, NS = 0.968 and BIAS = 0.001 in predicting daily river flow. . Overall, the results showed that the use of hybrid support-wavelet regression model can be useful in predicting daily discharge.
Geomorphology
shamsolah Asgari; samad shadfar; MohamadReza Jafari; Kourosh Shirani
Abstract
Sedimentation is one of the most important issues in the watershed. Due to the problems caused by sediment, it is necessary to investigate the relationship between hydrogeomorphic variables affecting sediment production and suspended sediment load in the watershed. The purpose of this study is to model ...
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Sedimentation is one of the most important issues in the watershed. Due to the problems caused by sediment, it is necessary to investigate the relationship between hydrogeomorphic variables affecting sediment production and suspended sediment load in the watershed. The purpose of this study is to model the relationship between suspended sediment loads with hydrogeomorphic variables of the basin and to extract geomorphic features and their relationship with sedimentation in the watershed. By simple random method, two cows and conifers, which include 8 specific sub-basins and are equipped with hydrometric stations, were selected. Statistical multivariate regression method was used to analyze the relationship between geomorphic variables with sedimentation of each sub-basin. The results of the study of the relationship between geomorphic characteristics and sedimentation of sub-basins showed that the amount of sediment produced was positively correlated with slope index, roundness, drainage texture, rainfall, unevenness and basin area and was significant at the level of 0.001. In order to influence the variables on the sedimentation rate of the sub-basins, the principal component analysis and cluster analysis methods were used. The results showed that the three factors of roundness coefficient, slope coefficient and drainage texture coefficient of the basin explain 44.62, 25.22 and 16.74% of the variance of all research variables, respectively. In total, the three final extracted factors were able to explain 87% of the variance of all research variables.
Geomorphology
Saeid Roustami; Babak Shahinejad; Hojatolah Younesi; Hassan Torabipoudeh; Reza Dehghani
Abstract
Flood is one of the natural phenomena that causes a lot of human and financial losses in the world every year and creates many problems for the economic and social development of countries. Therefore, in order to reduce the damage, control and guidance of this phenomenon, estimating flood discharge and ...
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Flood is one of the natural phenomena that causes a lot of human and financial losses in the world every year and creates many problems for the economic and social development of countries. Therefore, in order to reduce the damage, control and guidance of this phenomenon, estimating flood discharge and identifying the factors affecting it is very important. In this study, in order to estimate the flood discharge of Kashkan catchment located in Lorestan province, new hybrid artificial intelligence models including artificial neural network - innovative gunner, artificial neural network - black widow spider and artificial neural network - chicken crowding during the period 1300-1400 were used. To evaluate the simulation performance, statistical indices of determination coefficient (R2), absolute mean error (MAE), Nash-Sutcliffe productivity coefficient (NSE), bias percentage (PBIAS) were used. The results showed that hybrid artificial intelligence models improve the performance of the single model. The results showed that the artificial neural network- innovative gunner model has more accuracy and less error than other models. Overall, the results showed that the use of hybrid artificial intelligence models is effective in estimating flood discharge and can be considered as a suitable and rapid solution in water resources management.
Geomorphology
Mousa Abedini; Ehsan Ghale
Abstract
1-IntroductionDue 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 ...
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1-IntroductionDue 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.2-MethodologyMordagh 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. 3-Results and DiscussionAccording 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.4-Conclusions 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.
