Mohammad Hossein Rezaei Moghaddam; asadollah hejazi; Mehdi Mezbani
Abstract
In this study, in order to identify the spatial distribution of soil erosion and sediment production in Sarab Sikan basin, the RUSLE model, GIS and remote sensing technology are used. First, using meteorological data, soil and digital elevation model with a size of 10 meters, each of the factors of erosion ...
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In this study, in order to identify the spatial distribution of soil erosion and sediment production in Sarab Sikan basin, the RUSLE model, GIS and remote sensing technology are used. First, using meteorological data, soil and digital elevation model with a size of 10 meters, each of the factors of erosion erosivity (R), erodibility (K), slope and slope length (LS) and soil protection (P) in the Arc GIS was calculated in Arc GIS. Sentine2 satellite sensor was also used to extract and prepare the vegetation factor of the basin (C) in ENVI 5.3 software environment. Finally, by combining these factors, the amount of basin erosion was calculated and the amount of sediment produced in the basin was obtained by different methods of sediment delivery ratio (SDR). The results showed that the amount of erosion in the basin is varies from 0.003 to 248.4 t ha-1y-1 and the average erosion in the basin is 22.3 t ha-1y-1. Among the model factors, LS factor with a correlation coefficient of R2 = 0.92 showed the highest share in soil erosion. Also, the SDR ratio was calculated by different methods between 0.12 and 0.36, which after combining with the erosion map, the sediment yield of the basin was estimated. The average sediment yield by Boise method is 2.8 t ha-1y-1, which is closer to the amount of station sediment with an average of 1.65 t ha-1y-1 compared to other methods.
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.
Mohammad Hossein Rezaei Moghaddam; asadollah hejazi; Khalil Valizadeh kamran; Tohid Rahimpour
Abstract
1- Introduction Floods are one of the major natural hazards that annually cause extensive damage worldwide. There are numerous floods in the northwest of the country with the beginning of spring and the start of spring rains, which in most cases results in heavy damages. Aland chai catchment suffers ...
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1- Introduction Floods are one of the major natural hazards that annually cause extensive damage worldwide. There are numerous floods in the northwest of the country with the beginning of spring and the start of spring rains, which in most cases results in heavy damages. Aland chai catchment suffers from destructive floods every year since the beginning of spring. The purpose of this study was to examine and analyze the role of hydrogeomorphic indices in flood sensitivity in this basin. Hydrogeomorphic parameters of sub-basins were studied from three aspects of drainage network characteristics (including order of stream, number of streams, length of streams, frequency of stream, bifurcation ratio, length of overland flow, drainage density, drainage texture, texture ratio, infiltration number, constant of channel maintenance, and Rho coefficient), shape characteristics (Including basin area, compactness coefficient, circulatory ratio, elongation ratio, form factor, and shape factor) and relief properties (relief, relief ratio, ruggedness number, and gradient). 2- Methodology With an area of 1,147.30 km2, Aland Chai basin is located in the Northwest of Iran and in the Western Azerbaijan province. This basin is located between 38°- 30¢-14² and 38°- 48¢-22² N and between 44°- 15¢- 13² and 45°- 01¢-02² E. The minimum elevation of the area is 1093 meters and the maximum elevation is 3638 meters. This basin is one of the sub-basins of the Aras basin, which flows into the Aras River after joining the grand Qotour River. SWARA multi-criteria decision analysis model was used to weight the parameters. The Step-wise weight assessment ratio analysis (SWARA) model was developed by Keršuliene et al (2010). WASPAS multi-criteria decision-making model was used to prioritize sub-basins in terms of flood sensitivity. The weighted aggregated sum product assessment (WASPAS) method was proposed by Zavadskas et al in 2012. The WASPAS method consists of two aggregated parts, namely (1) The weighted sum model (WSM) and, (2) The weighted product model (WPM). 3- Results and Discussion Hydrogeomorphic analysis is significantly involved in the analysis of hydrological behavior of the basins. In the present study, 22 hydrogeomorphic parameters were analyzed from three aspects of drainage network characteristics, shape parameters and relief properties with the purpose of examining the effect of these parameters on the flood sensitivity of the Aland Chai basin. In the first step, the study area was divided into 15 sub-basins based on topographic and drainage characteristics using a digital elevation model (DEM) with a 12.5m spatial resolution. In the next step, the information of each sub-basin was provided based on 22 hydrogeomorphic parameters using the geomorphological laws of Horton, Schumm, and Strahler in ArcGIS software. According to the comparison among 22 parameters using the SWARA method, drainage texture, texture ratio, and drainage density (weighted as 0.273, 0.273 and 0.156) had the highest impacts on the occurrence of floods in study area respectively. On the contrary, Rho coefficient, constant of channel maintenance, infiltration number, and length of overland flow exhibited the lowest weights respectively. 4-Conclusion The purpose of the current study was to examine and evaluate the role of hydrogeomorphic indices in flood sensitivity of Aland Chai basin, for which SWARA and WASPAS multi-criteria decision-making models were employed. The results of prioritization of sub-basins using WASPAS model indicated that sub-basin 1 with a coefficient of 0.907, sub-basin 3 with a coefficient of 0.858 and sub-basin 2 with a coefficient of 0.818 had respectively the highest sensitivity to flooding. The results also revealed that sub-basins 4, 7, 11 and 15 in are placed in the high level category, sub-basins 8 and 9 are categorized in moderate-level category class, sub-basins 5, 10, 12 and 14 are classified in the low-level class and sub-basins 6 and 13 are situated in the very low level category in terms of flood sensitivity. The total area of sub-basins in the high and very high class of flood sensitivity is 656.72 km2, which comprises 57.24% of the total Aland Chai basin. Therefore, according to the findings of the study, which indicate that the study area has high flooding, it is necessary to adopt protective measures such as watershed planning and dam construction in highly sensitive sub-basins to prevent flooding and mitigate potential damages in cases of severe flooding. Keywords: Flood, Hydrogeomorphic Indices, GIS, WASPAS Model, Aland Chai Basin 5- References Keršuliene, V., Zavadskas, E. K., Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA), Journal of Business Economics and Management, 11(2), 243–258. https://doi.org/10.3846/jbem.2010.12. Zavadskas, E.K., Turskis, Z., Antucheviciene, J., & Zakarevicius, A. (2012). Optimization of weighted aggregated sum product assessment. Electronics and electrical engineering, 122(6), 3-6. http://dx.doi.org/10.5755/j01.eee.122.6.1810
Asad'ollah Hejazi Hejazi; Zahra Zanganeh Tabar; Zahra Zamani
Volume 6, Issue 20 , December 2019, , Pages 121-140
Abstract
1-IntroductionMaterials movement on slope and especially landslides are among the most damaging threats that have been accelerating with human manipulation in natural systems in recent decades (Imami and Ghayumian, 2003). These movements annually cause a lot of financial and psychological damage around ...
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1-IntroductionMaterials movement on slope and especially landslides are among the most damaging threats that have been accelerating with human manipulation in natural systems in recent decades (Imami and Ghayumian, 2003). These movements annually cause a lot of financial and psychological damage around the world in different parts of the country. The rapid population growth, the expansion of cities in mountainous areas, the difficulty of predicting the occurrence of landslide events and the multiple factors affecting this phenomenon reveal the necessity of zoning the risk of landslide. Since prediction of the precise time of mass movements is very difficult, identification of these areas is very important (Mosafaei et al., 2009). Using the zoning of the risk of a landslide event, it is possible to identify vulnerable areas with potential risk, and by providing appropriate management approaches and techniques, to some extent prevent the occurrence of landslides or damage caused by them reduced. Accordingly, the purpose of this study is to identify areas susceptible to landslide in the Sarpolzahab Basin. The Sarpolzahab Basin is one of the mountainous regions of the western part of the country which is prone to various types of slopes due to special geomorphological conditions. In this research, for the potential estimation of areas susceptible to landslide, two models of WLC and OWA for zoning and an analysis of the network (AHP) model for weighting into layers have been used.2-MethodologyThe research methodology is based on software, library and analytical methods. In this research, eight layers of information were used to identify landslide susceptibility. Information layers include: 1 elevation, 2 slopes, 3 slopes, 4 rivers, 5 faults, 6 lithology, 7 communication paths and 8 land use areas. The general trend of the present research is that in order to identify the susceptible landslides, information layers were first provided (the choice of information layers was based on the purpose of the research and according to the experts' opinion), and then these layers were based on the opinion of the experts (5 geomorphologist) and using the network analysis model (AHP). After weighing the information layers, the weight is applied to each of the layers, and then, in order to combine and combine the information layers, three methods of fuzzy logic, WLC and OWA have been used.3- ResultsIn this research, in order to achieve the desired goals, information layers are first provided. After providing information layers to combine information layers, layers are standardized using fuzzy area. Layer standardization is based on expert opinion and research objectives. For layers of elevation and gradient, gradient and high-lying areas of value near 1 and low-gradient and low-lying areas are considered to be close to zero. For layers of slope directions, the northern directions are worth close to 1 and the southern directions are close to zero. Also, areas near the lines of the fault, the river and the communication path are worth close to 1 and the distant areas are close to zero. For the land use, the uncovered areas are close to 1, and areas with dense vegetation are close to zero. For the lithology layer, areas with low resistance to lithology such as marl, lime and alluvium have a value of close to 1, and areas with more resilient lithology (basalt areas) are close to zero. 4- Discussion and conclusionThe results of this study indicate that the studied basin has high potential for slippery slopes movement. In fact, the existence of hurdles and the availability of other parameters have led to a relatively large and large part of the eastern basin. Comparison of potentiometric methods suggests that in all three methods, the eastern regions have the highest and western regions with the least potential for landslide occurrence. In the fuzzy logic method, the potential class has the highest potential of 195 km2, and the average potential class with the 121 km2 has the smallest extent, which mainly includes the western regions and the outlet of the basin. In the OWA method, the relatively large potential floor area has a maximum area of 210 square kilometers, which mainly includes the central and eastern heights of the basin. In this method, the high potentiality class with the area of 116 km has the lowest status, and mostly you are the northern and central areas of the basin. In the WLC method, the relatively high potential class with 180 and a high potential floor area of 120 km2 has the highest and the smallest extent.
