Hydrogeomorphology
Abolfazl Faraji mondared; shahram roostaei; Davoud Mokhtari
Abstract
Due to their geomorphological characteristics, alluvial fans are part of the high flood risk area. Placement of human phenomena in flood zones is a factor that intensifies the instability of currents. For this purpose, in this research, we applied the location of human phenomena in the geographical space ...
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Due to their geomorphological characteristics, alluvial fans are part of the high flood risk area. Placement of human phenomena in flood zones is a factor that intensifies the instability of currents. For this purpose, in this research, we applied the location of human phenomena in the geographical space of Pardisan in the flood zone with an applied-experimental method. To achieve this goal, the HEC-RAS-6 hydraulic model has been used as a working tool. Due to the size of the area, the area was divided into 15 sub-basins. First, the sub-layers of rivers and floodplain network were extracted, then human phenomena in the studied space were extracted and located on the RAS background map. Then the measured data and values were considered and implemented in the model. By locating the phenomena and considering the conditions of the alluvial fan flood, it was determined that the 100-year-old flood in the area of railway and communication lines, stairs in the west of Pardisan, west side of Payamnoor University, upstream of Pardisan town and also agricultural lands, has a high vulnerability rate. In general, despite the newly established Pardisan town, urban design and subsequent study and modification of the route did not match the geographical features of the region and the prospect of instability has prevailed in the geographical space of the area. It is suggested that for the future development of the city, the flood route be improved and monitored upstream to maintain environmental sustainability.
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.
Ahmad, Najafi Eigdir; Shahram Roostaei; Asadollah, Hejazi; Masomeh, Rajabi; nader Jalali
Abstract
1-Introduction 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 ...
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1-Introduction 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. 2-Methodology 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. 3-Results and Discussion 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. 4-Conclusion 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.
Fatemeh khodaei; shahram roostaei; Davoud Mokhtari
Abstract
1-IntroductionThe 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: ...
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1-IntroductionThe 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.2-Methodology1-2- Study areaThe 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 area2-2- 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 criterionN: The number of indicators under investigation for each criterionIn 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) 1.63-Results and DiscussionAfter 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 4-Conclusion(s)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.
shahram roostaei; davood mokhtari; christin jananeh
Abstract
1-IntroductionMass movements of the earth's surficial materials downward the slopes is called slope instability, which is affected by the earth gravity, while the rate of material mobility increases by the presence of water in the sediments. Each year, slope instabilities cause enormous economic damages ...
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1-IntroductionMass movements of the earth's surficial materials downward the slopes is called slope instability, which is affected by the earth gravity, while the rate of material mobility increases by the presence of water in the sediments. Each year, slope instabilities cause enormous economic damages to roads, railways, power transmission and communication lines, irrigation and watering canals, ore extraction, as well as oil and gas refining installations, infrastructures in cities, factories and industrial centers, dams, artificial and natural lakes, forests, pastures and natural resources, farms, residential areas and villages or threaten them. Nowadays, many instabilities are resulted by human intervention and manipulations. One of the human factors effective in the instability occurrence is the construction of roads. Road construction, especially in mountainous areas, increases the probability of occurrence of various types of instabilities, as it changes the natural balance of the slopes and causes deformations in the land. Each year, lots of casualties and financial losses are imposed by the occurrence of various types of instabilities in the slopes overlooking the roads, which also cause the destruction of many natural resources in the country. However, the construction of roads, highways and freeways is necessary and unavoidable in today’s life.The Karaj-Chaloos road and the Tehran-North highway are two routes that connect Tehran as Iran’s capital, with the southern shores of the Caspian Sea, although suffering frequent slope instabilities.2-Methodology This contribution aimed to study slope instabilities along these roads using logistic regression method. In this regard, layers of 14 effective factors were identified, comprised of elevation classes, slope, aspect, geology, land use, precipitation, distance from fault, river and road, normalized difference vegetation index (NDVI), climate, slope length (LS), stream power index (SPI) and topographic wetness index (TWI). Consequently, maps of the factors responsible for instabilities were prepared as separate layers in the GIS environment and transferred into the Idrisi software. The whole procedure included: (1) preparation of digital elevation model (DEM), river and fault layers based on the 1:25,000 topographic map of the area, as well as distance maps from rivers and faults, (2) creating slope and aspect maps from DEM, (3) preparation of land use and NDVI maps of the region based on unmatched classification of Landsat 8 image of OLI sensor, (4) preparation of geological map, (5) preparation of precipitation and climate layers based on the information obtained from the meteorological organization, (6) creating LS, SPI and TWI layers based on the DEM, (7) conversion of the distribution data of the regional instabilities using Landsat satellite and Google Earth images, (8) correlating the information layers with the regional instability map and calculating their density per unit area, and (9) performing the logistic regression model using Idrisi software.3-Results and Discussion Results obtained by applying logistic regression model showed that the most important factors affecting slope instabilities in the Karaj-Gachsar road area were the distance from river, climate and SPI, while those for the Tehran-Soleghan road area were the distance from fault and road and climate. 34.95 percent of the lands in the Karaj road area had medium to high potential for instability occurrence; 54.87 percent of the occurred instabilities corresponded to these areas. Moreover, 4.97% of the Karaj road area had a very high potential for instabilities, which correlated with almost 9% of the occurred instabilities. This was while 27.14% of the Soleghan road area possessed medium to high potential for instabilities, within which 86.26% of the instabilities have occurred. Furthermore, 4.57% of the Soleghan road area showed very high risk in terms of instability occurrence, encompassing 61% of the occurred instabilities. According to the prepared maps, the southern and middle parts of the Karaj-Gachsar road, as well as another part in the northwest of the study area had the highest potential for the occurrence of instabilities, whereas in the Tehran-Soleghan road area, the middle and southern parts and a small section in the north of the area had the highest potential for instability occurrence. By comparing these two areas, it was conceived that areas with medium to high potential of instability in the Soleghan road area were less than those of the Karaj road area (27.24% and 34.95%, respectively). However, the percentage of instabilities occurred in the Soleghan road area was much higher (86.26%) than the Karaj road area (54.87%). The high value of the ROC index and its proximity to the end value of 1 in both areas indicated that instabilities strongly correlated with the probability values derived from the logistic regression model. Additionally, the assessment of the instability potential map by the SCAI index showed that there was a high correlation between the prepared risk maps and the occurred instabilities, which have been confirmed by field surveys. The obtained results were in a good agreement with the general opinion that SCAI decreases especially in high and very high risk classes indicating a high correlation between the prepared risk maps and the occurred instabilities and field surveys in both areas.4-ConclusionThe results of this investigation showed that the logistic regression model was suitable for preparing the zonation of the probability of instability occurrence along the edges of the studied roads. Moreover, in addition to natural factors, the human-made factors and particularly unsystematic road construction can play an important role in the instability occurrences on the slopes overlooking the roads. In order to reduce the relative risks and increase the stability of the slopes, it is necessary to avoid manipulating the ecosystem and changing the current land use as much as possible, in addition to policy making for constructions in accordance with geomorphological and geological features of the area.Keywords:Instability, Logistic Regression, Tehran-North highway, Karaj-Chaloos road, Risk zonation.
Ahmad Najafi Eigdir; shahram roostaei
Abstract
1-Introduction Several factors have contributed to the occurrence of the landslide that could increase the risk of landslide in any area. Identifying these factors and their value can help to appropriate landslide zonation. The aim of the study is to find ways to reduce the damages caused by them, which ...
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1-Introduction Several factors have contributed to the occurrence of the landslide that could increase the risk of landslide in any area. Identifying these factors and their value can help to appropriate landslide zonation. The aim of the study is to find ways to reduce the damages caused by them, which makes it necessary to zoning the susceptible areas that play an undeniable role in watershed management. Therefore, by using statistical models and assessing them, the sensitive areas to the occurrence of landslide are identified. In this research, the landslide hazard zonation was performed based on the data-driven method. Based on this method, the zoning was done based on the use of slope data, aspect, elevation, precipitation, vegetation, geology, land use, distance to fault, distance to river, and distance to road. To validate the model, the ROC curve has been used which is a new and efficient method for verification. The purpose of this research is to investigate various influencing factors that affect the landslide occurrence in the Nazlochai basin. 2-Methodology In the methodology section, the satellite imagery processing (to identify and extract landslides, vegetation extraction, and land use) and logistic regression model have been discussed for landslide hazard zonation. In this study, by reviewing the previous sources (Mir Nazari, et al., 1393, Abedini, et al., 1393, Ayalew, et al., 2004, Ebadinejad, et al., 2007) and by investigating various factors (morphometric, climatic, and human) in Nazlochai basin, ten effective factors (elevation, slope, aspect, distance to river, distance to road, distance to fault, lithology, landuse, precipitation, and vegetation) on the landslide occurrence in the area were considered. The ArcGIS software was used to digitize and provide information layers for landslide hazard zonation, and the ENVI software was used for image processing, vegetation extracting, and land use mapping. Existing landslides were identified and characterized using various tools including aerial photos, satellite imagery (Google Earth), existing information, Global Position System (GPS), and field surveys. 3-Results and Discussion The obtained coefficients indicated that the occurrence of landslide in the studied area had a direct relation with lithology, slope, and aspect factors, and weak relation with landuse, distance to fault, precipitation and distance to river. Lithology investigation of the region indicated that the more landslides have occurred on calcareous and conglomerate stones, which could be due to the development of the slopes and the accumulation of destructive materials on them. Slope is one of the slippery factors due to gravity and decreasing shear strength of soil in slopes of more than 10% to 45% leads to instability which in most researches is considered as an effective factor, too. Also, north slopes are more susceptible to landslide than the southern slopes due to the reduction of normal pressure and shear strength of the soil. By considering the Pseudo R-square index (equal to 0.34), which is greater than the threshold (0.2), this model shows acceptable fit. The area under the ROC curve was equal to 0.958, which shows a strong correlation with predicted landslides by the logistic regression model. Finally, the study area was classified into 5 landslide hazard classes include very low, low, medium, high, and very high. 4-Conclusion In this research, landslide hazard zonation has been done using the logistic regression model in the Nazlochai basin. The coefficients of variables indicated that the occurrence of landslide in the study area had a direct relationship with the lithology, slope, and aspect factors; and weak relationship with landuse and distance to fault. Thus this indicates the probability of landslide occurrence increases by changing in lithology, slope, and aspect
