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.
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
Mohsen Armin; Hadis Valinejad; Vajihe Ghorbannia Kheybari
Abstract
1-Introduction On a national scale, soil erosion in Iran, has an important effect on agricultural production, sedimentation in dam reservoirs, soil degradation and so on. Severe soil erosions and the subsequent high deposition of sediments in dam reservoirs and reduced soil fertility are serious environmental ...
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1-Introduction On a national scale, soil erosion in Iran, has an important effect on agricultural production, sedimentation in dam reservoirs, soil degradation and so on. Severe soil erosions and the subsequent high deposition of sediments in dam reservoirs and reduced soil fertility are serious environmental problems with dangerous economic consequences for the country. The situation of sedimentation in Iranian dams indicate that their design have often focused on civil engineering and structural aspects and no attention has been paid to the issue of erosion and sediment yield in the basin of dams, which makes a large amount of sediment be deposited in many of these dams for many years; this causes a lot of sediment after many years to be deposited in many of these dams` reservoir, as a result of which, the useful life of the dam is greatly reduced. The present study aimed at estimating soil erosion in the Tang-e-Sorkh dam watershed with a total area of 39,000 hectares in the east and south-east of Boyer Ahmad County in Kohgiluyeh and Boyerahmad province using the RUSLE model and the remote sensing (RS) and Geographic Information System (GIS) capabilities in order to plan protective measures in the dam watershed. 2-Methodology Digital altitude, precipitation, physico-chemical properties of soil and satellite imagery data were used to estimate soil losses using RUSLE model in the Tang-e-Sorkh basin. First, the boundary of Tang-e-Sorkh watershed was drawn on a topographic map with a scale of 1: 50,000 in the geographic information system environment. The meteorological stations in and around the watershed were then identified and marked on the map. RUSLE has calculated the average annual soil erosion expected on a sloping land using Equation (1). A=R.K.L.S.C.P (1) Where A is calculated as the average spatial loss of soil and the average time of soil loss per unit area is expressed in terms of units selected for K and the time period selected for R. In practice, these units are usually selected so that A is expressed in tons, per hectare, per year (t ha-1 year-1). R Runoff-rain erosivity factor is expressed in MJ mm ha-1 h-1 year-1, K Soil erodibility factor which is the amount of soil loss per unit area of erosion index for a given soil- is obtained by measuring in a standard plot with a length of 22.1 meters, a slope of 9% and a permanent fallow and is expressed in t ha h ha−1 MJ−1 mm−1. L is the slope length, S is the slope, C is the plant cover management factor and P is the protective measures factor. The parameters L, S, C and P are without units. The layer of parameters of the RUSLE model includes rainfall erosivity (R), soil erodibility (K), slope and length of the hill (LS), vegetation management (C), and soil conservation operations (P) have been prepared in geographic information system environment and after overlayering, the amount of erosion was estimated locally. 3-Results and Discussion The amount of rainfall erosivity was from 179.62 to 327.77 MJ mm ha-1 h-1 year-1. Erodibility factor was from 0.08 to 46.0 t ha h ha−1 MJ−1 mm−1. The minimum and maximum values of slope and hill length were 0.08 and 12.42, respectively. The minimum and maximum values of vegetation management were 0.33 and 0.54, respectively. The minimum and maximum values of soil conservation operations were 0.5 and 1, respectively. The amount of soil erosion in the studied area varied between 0.0033 and more than 100 tons per hectare per year at the pixel level. About 80% of the studied area had an erosion rate of 35 tons per hectare per year, with the highest amount in the western and northeastern parts of the country, which was due to high rainfall erosivity and soil erodibility in the area. 4- Conclusions It can be said that in the current situation of Tang-e-Sorkh watershed, due to the lack of real sediment statistics, the best model for estimating erosion and sediment yield with the aim of introducing soil protection measures at the basin level was RUSLE model. The proposed method and the results of this research can be used as a dam maintenance planning system. The RUSLE model could predict the potential of soil erosion as a cell-by-cell, which was very useful when trying to identify the spatial pattern of current soil losses within a large area. Spatial information systems can be used to separate and inquiry these locations to assess the role of effective variables in the amount of soil erosion potential observed. Regarding the results, decision makers need to manage the risk of soil erosion in the most effective way; and management scenarios can adopt the best ways to improve and rehabilitate the basin based on the priority of different areas of the basin.
