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Showing 10 results for Erosion

Hamid Alipour, Sayedenegar Hasheminasab Hasheminasab, Amir Hossein Hatefi, Azam Gholamnia, Yasser Shahnavaz,
Volume 1, Issue 2 (7-2014)
Abstract

Wind erosion is important in areas with less than 150 mm of rainfall Measuring the extent and severity of wind erosion in many countries, including Iran, there is no station to measure wind erosion sediments and so the deposition estimation methods rely on empirical models so that in many cases there are measurement errors. With estimates wind and water erosion and deposition potential compared using IRIFR EA and MPSIAC models in semi-arid Nematabad Bijar watershed concluded that the IRIFR model quantitatively and qualitatively accuracy and, due to a 22.6% wind erosion and 77.4 percent water erosion effective in reducing the fertility of soil (Ahmadi et al, 2006). This study estimates deposition and wind erosion potential using IRIFR method in esfarayen Miandasht region.

In this study, the data collection and basic research in the area uses of maps such as topography, geology, geomorphology, land capability, vegetation, and include information and meteorological studies, field visits, and the prevailing wind direction in the form of desert and question naires were completed and work units to people in another way - specific preparation, IRIFR experimental model of wind erosion in each of the work units were defined the land to wind erosion susceptibility map was prepared using IRIFR and deposition potential temperature using the relationship between precipitation and sediment yield were obtained. After scoring each of the factors affecting wind erosion facies geomorphology (erosion) and the sum of given annual sediment production rates, the rate of erosion severity maps were produced in ArcGIS environment. Soil erosion severity and sedimentation of the area, were obtained nine factors affecting wind erosion scores are considered in five classes.

The results showed erosion class I (very little) with an area of ​​about 11287.21 acres more land erosion. This erosion class is includes geomorphological facies 1-1-2 (water erosion on the erosion piedmont) and 1-2-2 (water erosion on the apandajz piedmont). and class IV (erosion) with an area of ​​6682.45 acres, is the second largest in the area. This erosional class also includes geomorphological facies detachement region - farm lands – fine desert pavement and the stream. Among stream geomorphologic facies (5-3-2) and arable land (2.3.2) have the most the highest amounts of precipitation.

Wind erosion in the miandasht region,  include 8 erosional form and severity of erosion stream facies, etachement region, farm lands and fine desert pavement have high erosion rates. Topography is flat and low-slope land in the north eastern parts of the area where directly affected by the prevailing winds, led to the destructive power of wind improve. One of the best ways to combat wind erosion in the area around the farm and out carminative Miandasht construction area of agricultural land around the study area and the direction of the prevailing winds in parts of the east, the north east is. The study area of wind erosion control perspective is a set of constraints and capabilities. Fine tissue silt abundant salts in the soil and reduces adhesion of soil particle aggregate structure fragmentation and reduce the threshold velocity of wind erosion in the region and the area are prone to erosion. Existence drought resistant species such as Haloxylon prsicum Artimisia sp. in the region can be developed that will help to control wind erosion.


Khalil Rezaei,
Volume 3, Issue 3 (10-2016)
Abstract

Erosion is one of the most destructive and continuous phenomena that cannot be prevented and only could be controlled by studying the chemical and physical properties of soil. Marls are one of the most important sedimentary units in Iran which have high rate in sediment production and erodibility because of their Physico-chemical characteristics. These properties caused large environmental and civil damages and so, the study of erosion and erodibility of the marl units is essential. One of the most important points about marls is grain size nature and elements in them and their effects on amount of erosion. The physical and chemical proprieties of soil are very important in the development of badlands. This study deals with Physico-chemical properties of Marl and its impact on various land forms of erosion in Lotshur-Pakdasht region. Badlands are a typical landform of greatly dissected fine-grained materials in arid or semi-arid environments like Lotshour, although they are also found in different climatic conditions. Climate and geology are several factors determining the tendency to badland formation. Runoff, rain splash, marl and loose formations together with massive wasting processes such as creep, sliding and flow, become the dominant factors determining landform genesis, resulting in the formation of badlands in Clayey-silt slopes.

In this research, in addition to sampling the soil and sediments, rain simulated (using rain simulators) in two marl, two conglomerates and two alluvium  units, in area with different forms of erosion and runoff and produced sediment amounts in each point were measured in laboratory. Also, at the same time, soil samples were taken from adjacent plot and the amount of runoff and sediment produced in the laboratory, separated and measured in the lab for all points. parameters such as Ph, electrical conductivity, content of sodium, potassium, calcium, magnesium, gypsum, chlore, carbonate, solfate, nitrate, organic carbon, CEC was measured. In analyzing the data, analysis of correlations and Pearson and Spearman comparison of means method were used in SPSS software. Also, grain size and Aterberg limits for all samples were determined in lab.

Mineralogical, geochemical and grain-size composition of soil and pore-water chemistry parameters was characterized on both eroded (south-facing) and non-eroded (north-facing). Only a few grain-size parameters and mineralogy discriminate eroded from non-eroded slope substrates. Erosion occurs where the fine fraction is abundant. This may be due to reduced permeability in the eroded soil, whereas the non-eroded one is more stable with respect to weathering, as it is more permeable. The abundance of clay minerals is affected by pedogenetic processes in the non-eroded slope, which increases in mixed layers and indirectly reduces the amounts of other minerals, making clay mineralogy a discriminating parameter in the two different types. Chemical data enable discrimination between eroded and non-eroded slopes. pH, SAR (sodium adsorption ratio), TDS (total dissolved salts), mineralogy and PS (percentage of sodium) are distinctive parameters for both eroded and non-eroded slopes. TDS increases in depth in the non-eroded slope, whereas the maximum TDS is just below the crust in the eroded one. On average, eroded substrates are higher in pH, SAR and PS than non-eroded ones. The ESP (exchangeable sodium percentage) of the eroded slope has a higher value than the non-eroded one. Crusts are less dispersive than eroded substrates, and non-eroded substrates behave as crusts. This suggests that the portion of the slope most severely exposed to weathering tends to stabilize, due to strong decreases in SAR, PS and ESP. Several diagrams reported in the literature show similarly anomalous crust samples on eroded slopes, compared with other samples coming from greater depths on eroded slopes. In the present case study, the exchangeable form of Na characterizes crusts more than the soluble form. The meaning of maximum SAR and TDS (and covariant parameters) is interpreted as the effect of decreased permeability, as suggested by a local increase in the fine-grained fraction, which coincides with maximum TDS. Variations in SAR values are of primary importance for soil erosion, because many authors have used solution chemistry (i.e., SAR, PS, TDS, EC) as a descriptor of dispersity.

            Based on results of analysis of variance in various forms of erosion are significantly different in the sodium ion, sodium absorption ratio and the percentage of clay. The average amount of sodium ion and sodium absorption ratio in marl samples of region, increase from sheet to gully erosion forms while average clay percentage decreases in this trend. Finally, three variables of sodium ions, sodium absorption ratio and clay percentage of marl samples can be significant factors in erosion and related forms in this region. This study describes the erosional mechanism, which involves morphological and geographic exposure and climatic elements, as well as grain size, mineralogy, chemistry and exchangeable processes of soils.

In analyzing the data, correlation analysis and comparison of averages by the SPSS software has been used. As well as a brief comparison between north and south facing slopes that are different in terms of erosion, was also performed. Based on statistical analysis of in various land forms of erosion are significantly different in the sodium ion, sodium absorption ratio and the percentage of silt and clay. The average of sodium ion value and sodium absorption ratio increase from surface to gully erosion form and average silt percent reduced from surface to Gully erosion in marls outcrops in this area. Also, three variables of sodium ions, sodium absorption ratio and clay percent factors can be seen in the erosion of marl and create various land forms of erosion in the region.


Norollsh Nikpour, Samad Fotohi, Hossien Negaresh, Masod Sistani,
Volume 4, Issue 1 (4-2017)
Abstract

Has been stated in various sources, soil as one of the most important natural resources has a major, role on the lives of humans. Today soil erosion and sediment production, a problem that is increasing day to day process and loss of surface soils and sediment accumulation in dam reservoirs, canals and also sedimentation damage to the country's economy. One of the most important types of water erosion, gully erosion or (Galli formation). This type of erosion and loss of soil due to sediment production and enormous damages to land, roads and infrastructures, is of great importance. Soil erosion is one of the most important factors that threatens large areas of Iran annually and decreases or eliminates the quality of agricultural lands and rangelands. Due to highlands of Iran in comparison with the grounds and surrounding plains (mean elevation of 1250 m), it has been affected by water erosion. So it is very important to study erosion and present management strategies to reduce the impacts of erosion in basins of Iran. This study to Target morphometry gullies and the influencing factors on gully erosion in the South West sub-basin of ILAM (Cham Fusel).

The average height in the area between 50 and 1,200 meters above sea level and has a dry climate with an average annual rainfall of less than 200 mm and the average annual temperature is above 25 degrees C°. In terms of the main geological formation of this area is affected by gully erosion, Aghajari formation (red mudstone, siltstone and sandstone) are related to Miocene period. Basin area of over 150 hectares affected by gully erosion and slope threshold for gully erosion in the area between 8-2 percent.

The research method in this study is field research, library study and morphometric measurements of gully erosion forms. Besides, on the basis of the geological maps of 1/100000 and topographic 1/50000 and DEM 30 meter area, the software of GIS Arc has been used to make the required maps. Furthermore, the GPS device and a camera has been used in the field to harvest. o

The average height in the area between 50 and 1,200 meters above sea level and has a dry climate with an average annual rainfall of less than 200 mm and the average annual temperature is above 25 degrees C°. In terms of the main geological formation of this area is affected by gully erosion, Aghajari formation (red mudstone, siltstone and sandstone) are related to Miocene period. Basin area of over 150 hectares affected by gully erosion and slope threshold for gully erosion in the area between 8-2 percent. The study, which the sub basin in Cham Fusel ILAM province is located in the South West, with the aim of gully morphometric including deep, height, length, height from sea level, and geographical location as well as classification criteria in three sample gully gully of area, In order to identify factors affecting the development of erosion in the basin plain Cham Fusel was evaluated. The results of morphometric and field visits to the region, factors such as climate factors, slope and aspect, geology (Land genus), tectonic activity and faulting, land use, overgrazing of amount plants, including the most important factors recognized were identified in the development of gully. Which layers to extract some of these factors in Arc GIS software designed and based on creation of maps and data to analyze each of these parameters and their impact on Gully Erosion percent has been paid.

According to the morphometric data, it can be concluded that the gullies basin largely toothed and clawed, permanent, of medium to large gullies, which have expanded continuously. Below you can see images of morphometric gullies sample was collected during the field visit of the area. The results show that due to the widespread earthquake in the region in recent years and local faults can be concluded that one of the most important factors in the formation Galli uplift of the Earth. Also overgrazing by cattle ranchers in the area Tuesday Abdanan city, murmury, Dahlgren and ranchers outside the province of Hamedan and Kermanshah provinces such as ranchers who use the area as Qishlaq, Another important factor in the development of gully erosion in the area. Due to the climatic amount of rain, sleet, snow, ice, temperature and wind could be the climate factors in the rise of water erosion. As the geographical location and local climatological data suggests, the study area is influenced by the Mediterranean winter rains. Which are imported to Country from the West in winter and more in the form of showers and hail rainstorm conditions caused severe erosion gully in the area easy. Lack of growth of vegetation and bare Land is another contributing factor is considered in the development of gully erosion in the area. That is because the rainy season in the winter when the soil in the area is almost devoid of vegetation. The lack of vegetation in the region as one of the important factors, has caused soil erosion, its most destructive erosion of the gullies show. Also according to the map slope and aspect of the region was marked within the range of between 2-8 percent and Create Gully and aspect with the West and the South West and North West are more affected by gully erosion. Finally, all factors except factors of land use, all other factors were named among the important factors affecting the development of gully erosion are the region. It was also found other factors in the evolution of land use contrary to gully erosion region. That is because of the lack of culture in this area and dropping land by farmers as wasteland, and also because of the recent drought in the region has caused more and more extend of gully erosion and land with the ability crop damage and destroy all. The results obtained showed that the study area in terms of of gully erosion in critical condition.


Amir Saffari, Amir Saffari, Jalal Karami,
Volume 5, Issue 1 (6-2018)
Abstract

Investigation about the influence of land-cover and land use changes on soil erodibility potential, case study: Gharesou, Gorganrood
Land use and land cover (LUC) change associated with climatic and geomorphologic conditions of the area have an accelerating impact on the land degradation. Natural as well as human-induced land use land cover change (LUCC) has significant impacts on regional soil degradation, including soil erosion, soil acidification, nutrient leaching, and organic matter depletion. Since the last century, soil erosion accelerated by human activities has become a serious environmental problem. It has a manifold environmental impact by negatively affecting water supply, reservoir storage capacity, agricultural productivity, and freshwater ecology of the region. In recent years, many researchers have highlighted the environmental consequences of soil erosion.
Soil erosion estimation at a regional scale is influenced by the complexity of the soil erosion process and the availability of data describing the soil erosion factors. In the last decade, regional and national level assessments of soil erosion were carried out using different approaches, ranging from indicator or factor-based approaches to process-based models. However, the revised universal soil loss (RUSLE) and its modifications are still widely used because of its simplicity and a greater availability of input parameters.
Gharesou basin is one of the sub-basins of Gharesou, it suffered from severe erosion in some areas over the past years. This erosion has occurred for different reasons and one of them is land use change and weak management of water and soil resources. The purpose of this research is to investigate the effects of land-cover changes on the potential of soil erosion in Gharesou Basin, a sub-basin of Gorganrood, in Golestan province. For this, we have employed RUSLE Model and used landsat satellite images from the sensors of TM, ETM, and OLI for 1985, 2000, and 2015. The potential soil erosion in this study was estimated using RUSLE model, which can be described using following equation:
A = R × K × LS × C × P
where A is amount of soil erosion calculated in tons per hectare per year, R is rainfall factor , K is soil erodibility factor , L is slope length factor, S is slope steepness factor, C is cover and management factor, and P is erosion control practice factor. To run the RUSLE model in GIS, first, rainfall raster layer, soil, slope, Digital Elevation Model, and also layers of soil protection range were created. Each of the involved factors was calculated in separate units in the basin level. In this research, Gharesou basin was analyzed based on raster network data with 30 meters cell size, because, from one hand it's small
enough to show heterogeneity of the basin and on the other hand, it matches pixel dimensions of landsat satellite images.
The results of land-cover changes have revealed a decrease in dense forest areas, low forest areas and the mixture of orchard, forest and pastures in a thirty years period. According to the results of RUSLE, changes of the classes indicate a general trend to the soil loss in the basin. Therefore, Gharesou basin is a basin with increasing soil erosion potential. In the plain and coastal plain areas of the basin, that is the mainly cultivated area, the amount of erosion is different from the other areas, and soil loss process is decreasing. It's due to the changes of cultivation method from traditional to modern, increase of irrigated farming area, choosing more environmentally friendly plants, and also, increase in the area of cities and villages from 7.14 percent to 29.04 percent during 30 years. In the study classes, for output of RUSLE model, in every 3 years of study, the maximum area relates to the classes of 100 to 200 Ton per year that is more seen in the mountainous regions. In these regions, all factors except vegetation are toward soil loss. Also, during 30 years, the amount of dense vegetation decreased from 34.56 to 31.55. In fact the only factor in protecting soil in (prone to erosion) areas has given its place to less effective vegetation, so, the area of this region has increased and Gharesou basin is in danger of soil loss in mountainous and forest parts. Also, areas with more than 200 Ton in hectare, with the lowest amount, have had a tangible increase during 30 year of study and its amount has increased from 11.74 to 12.50. These areas are usually located in mountainous parts with no vegetation. Also, the average of soil erosion potential estimated in Gharesou basin for 1985, 2000 and 2015 is 102.02, 103.11, and 103.76 (ton per hectare per year). This amount was found in the sub-basins too and except the sub-basin 4 located in coastal plain areas of the basin, with farming use, the amount of other sub-basins is increasing. According to the results of study, mountainous parts of Gharesou basin, has the most damage due to the accumulation of involved factors in the potential increase of soil loss. So, the necessity of watershed management is observed. Also modification of cultivation pattern and soil conservation training in farming lands of foothills and hillsides are required.
Keywords: RUSLE Model, soil erosion, Gharesou, Remote Sensing, land-cover changes

Reza Bayat, Mahmood Arabkhedri, Najmeh Behnam, Zahra Gerami,
Volume 7, Issue 3 (11-2020)
Abstract

Soil erosion is one of the most important environmental issues in developing countries, including Iran that there is inaccurate information about its amount and distribution. For this purpose, the accuracy and distribution of erosion classes obtained from EPM and MPSIAC models as compared to BLM as ground truth values were evaluated in Shahriari watershed. First, the required data and information for MPSIAC, EPM and BLM models for basin erosion status was stored in a database. Then, using ARC/GIS9.3 software, erosion class maps were prepared based on each model formula and they have been intersected with the ground-truth map. Also a point map containing 1400 random points was also prepared for sampling the maps obtained from the models. Then, based on random sampling points map, each of the statistical indices of RMSE, RRMSE, MAE, MBE, NSE, CD, CRM and MSE were calculated. Also, to verify the spatial accuracy of the erosion class maps derived from the error matrix models and the Kappa coefficient of agreement, overall accuracy, producer accuracy and user accuracy. The results of the erosion of the models showed that the mean erosion intensity in MPSIAC model was 589 and in EPM model 287 m3/ km2.year that the basin erosion status is estimated to be moderate for the basin with the help of MPSIAC model and EPM model. The analysis of the above statistical indices shows that the RSME, MAE, MBE and MSE statistics in MPSIAC model have lower values. As a result, the MPSIAC model has less error than the EPM model. Overall, the results of the statistical indices showed that the MPSIAC model's erosion classes were more in line with the BLM output (as a ground truth map) than the EPM model. Also the kappa coefficient in MPSIAC is higher than in EPM model. Overall, the results show that the MPSIAC model erosion class maps overlap with the BLM model and in fact with the actual conditions of the area.

Mohammad Ali Zanganeh Asadi, Mahnaz Naemi Tabar,
Volume 8, Issue 1 (5-2021)
Abstract


 Relationship between hydrogeomorphic features and suspended sediment load under Kashfarud basins
 
Introduction
As a stressful stimulus, river sediment is the most significant threat to aquatic ecosystems. To prevent or minimize the damage, three stages of the erosion process should be investigated (Naseri et al., 2019: 83). Determining the amount of sediment transported by rivers is important from different aspects. Sediment carried by water flows is considered a factor effective in shaping the geometric structure and geomorphic characteristics of rivers (Tashekabood et al., 2019: 282).
Data and methodology
To estimate the amount of annual suspended sediments, the flow and sediment statistics of hydrometric stations (8 stations) and meteorological stations (13 stations) were employed (Figure 2). The research statistical period is 25 years (1993-2017). The altitude, area, and perimeter of the basins were obtained from topographic maps with a scale of 1.25000. To investigate the correlation between independent and dependent variables, the normality tests of Shapiro-Wilk and Kolmogorov-Smirnov were performed in SPSS16 software. To extract the geomorphic features of the basins, the digital elevation model was used. Then, ground surface corrections and pretreatments such as removal of hydrological pits were performed and ground drainage pattern was determined.
Stepwise multivariate regression
In the present study, stepwise multivariate regression was used to reduce the number of independent variables and determine the effective factors in the sedimentation of the basin. This method investigates the effect of several independent variables on a dependent variable (Zare Chahuki: 2010). In stepwise multivariate regression, the independent variable that has no more significant effect on the dependent variable is removed from the analysis, hence excluded from the equation. The general form of the stepwise regression equation is:
Equation 1                                                                            Y= a + B1X1 + B2X2 + …… + BnXn + e
Data description and interpretation
The principal component analysis method was used to determine the most effective characteristics of sediments as well as their grouping. In principal component analysis, variables that have a high correlation and are distributed in a multidimensional space are reduced to a set of non-correlated components, each of which is a linear combination of the main variables. The obtained non-correlated components are called principal components (PCs). Prior to component analysis, the KMO coefficient was used to ensure the appropriateness of the data for principal component analysis. This coefficient fluctuates in the range of zero and one and if its value is less than 0.5, the data will not be suitable for principal component analysis and if the values of this coefficient are between 0.5-0.69, The proportionality of the data is moderate and if the value of this coefficient is more than 0.7, the data will be quite suitable for performing principal component analysis.
Regression analysis results
In this study, the sediment weight of the basin was considered as a dependent variable and other parameters as independent variables. The variables of slope, precipitation, basin length, Elongation Ratio (R), circularity coefficient, and unevenness of the basin have a higher correlation with the amount of sediment production in the basin than other variables.
An eigenvalue was used to determine the number of factors. The minimum eigenvalue for the selection of final factors is 1, and factors with an eigenvalue bigger than 1 are considered final factors. The results showed that the three factors of circularity coefficient, compactness coefficient, and basin form coefficient have an eigenvalue bigger than 1.
Conclusion
The results showed that geomorphic parameters have a high correlation with the amount of annual sediment. The results showed that seven factors of slope, precipitation, basin length, elongation ratio, circularity coefficient, unevenness coefficient, and form ratio of the basin were the most important in estimating the amount of suspended sediment based on the principal components analysis method. The average of special sediment varies from 134 tons per year in Dehbar basin to 16 tons per year in Kardeh basin and also the average annual sediment varies from 261.6 tons per year in Golmakan basin to 156.7 tons per year in Shandiz basin. Evaluation of Bartlett's test of sphericity tests and KMO values is 0.9. Therefore, the data is suitable for factor analysis. The percentage of variance explained by each factor indicates that the circularity coefficient with 50.71% of the variance explains all the research variables. In total, three factors of circularity coefficient, compactness coefficient, and form ratio of the basin could explain 82.6% of the variance of all research variables. Therefore, the results are consistent with Lu et al. (1991), Sarangi et al. (2005), Tamene et al. (2006), Zhang et al. (2015), Salim (2014), and Ares et al. (2016).
Khorram Dareh sub-basin with heavy rainfall (504 mm) has the lowest specific sediment, which is due to the geological structure of the region. Based on the calculated indicators, most of the studied sub-basins are elongated. The form ratio of the basin is less indicative of the elongation of the basin. The highest branching ratio of the basins is in the vicinity of faults. Also, high circularity values indicate points prone to sedimentation. River sections up to degree 3 are located in more subdued areas and have a steeper slope. Golmakan, Khorram Darreh, Zashk, and Dehbar sub-basins have a high potential for sedimentation. Regression equations of sediment measurement curves are usually used in sediment load estimates. The most important reason is the ease of application of these equations. According to the research results, it can be concluded that the integrated use of principal component analysis, cluster analysis, and multivariate stepwise regression has a suitable and acceptable efficiency in estimating suspended sediments. Testing the regression model concerning different climatic and hydrological regimes of Iran’s watersheds to achieve an efficient pattern of using these equations can be fruitful in estimating sediment load in different regions.
 
Keywords: Hydrogeomorphic, Sediment erosion, Kashfarud basin, Stepwise multivariate regression
Somaiyeh Khaleghi, Mohammad Mahdi Hosseinzadeh, Payam Fatolah Atikandi,
Volume 8, Issue 2 (9-2021)
Abstract

River channel changes, bank erosion and sedimentation are the natural processes of the alluvial rivers that destroy the agricultural land and damage to human installations around the river. In the present study, the CAESAR model was used to assess the changes of the Kaleibar Chai River in order to measure the variation of 3 km of its main channel.CAESAR is a cellular automata model for river system evolution. CAESAR  is a cellular model  that uses a regular mesh of grid cells to represent the river catchment studied. Every cell has properties of elevation, water discharge and depth, vegetation cover, depth to bedrock and grain  size.  It  is  based  upon  the  cellular  automaton  concept,  whereby  the repeated  iteration of a series of  rules on each of  these cells determines  the behaviour of the whole system. CAESAR has a set of rules for a hydrological model, hydraulic model (flow routing), fluvial erosion and deposition and slope erosion  and  deposition.  For  every  model  iteration,  cell  properties  (e.g. elevation) are updated according to the rules, and the interaction between an individual cell and its neighbours. For example, the amount of fluvial erosion in a cell may depend upon the depth of water in the cell and the slope between that cell and its neighbours.
For modeling, the input data such as topography (DEM), daily discharge (year 2012) and sediment grain size were prepared and then channel modifications were simulated. Channel changes were identified before and after the simulation by plotting profiles of each cross-sections and were analyzed sensitive to erosion and sedimentation.Six cross-sections were selected before and after simulation. Results showed that the channel geometry has changed. The width and depth and form of the channel have changed. And only the mean depth of the channels was changed in sections 1, 2, 6 and 4. The erosion was dominated in the cross- sections 1, 2, and 3 (the initial part of the main channel). Then the sedimentation was dominated in the cross- sections 4, 5 and 6.


 
Reza Esmaili, Fatemeh Abedini Zadeh,
Volume 8, Issue 4 (3-2022)
Abstract

Streambank erosion hazard analysis by BEHI method, case study: Sajadroud stream, Mazandaran province
Extended Abstract
Introduction
River bank erosion is a complex natural process and plays an important role in the dynamic equilibrium of the river. The amount of river bank erosion affects the river plan, cross section and dimensions of the river and is the main factor controlling channel migration and the evolution of the river planform. This research was conducted with two main objectives, which are: 1. River bank erosion susceptibility analysis in incised rivers in mountainous areas, 2. Comparison of river bank erodibility with two methods original BEHI and modified BEHI.
Method
In this study, Bank Erosion Hazard Index (BEHI) and the modified BEHI method along a part of Sajadrood Stream in Mazandaran province have been investigated. The original BEHI (Rosgen, 1996, 2001) evaluates the river bank erosion field measurements. In this method, several parameters are measured, including bank height, Bankfull height, bank angle, root depth, root density, surface protection, bank material structure and stratification. From this parameters, the bank angle and height, root depth can be measured, but indicators such as plant root density and surface protection are visually estimated as a percentage. The score of each index varies from 1 to 10. The total scores of all indicators are classified into 6 groups: very low, low, medium, high, very high and extreme.
Newton and Drenten (2015) Based on the modified BEHI proposed a protocol for estimating the river bank erosion. In this protocol, the lengths of similar riverbanks are first defined as a uniform section of bank. These uniform sections can be identified due to differences in bank slope, differences in bank material and a break in vegetation. The characteristics of uniform sections are then evaluated in a pre-screening questionnaire consisting of six questions. If the answer to two or more questions is "yes", there is a high probability of erosion and the BEHI evaluation will be performed. Otherwise, the measurement will not be taken because the erosion is low or very low.
Result and discussion
The study area was divided into four reaches and 36 sites were surveyed. These river reaches have a deep bed (incised), high slope, low sinuosity, low width to depth ratio and predominant cobble sediments in the bed. They are in type A3 according to the Rosgen River classification. The height of the banks of the stream is high and its average is 2.6 meters with a minimum and a maximum of 0.4 to 9.7 meters. The average height of bankfull was 0.44 meters and varied from 0.15 to 0.85 meters. Hence, the ratio of bank height to bankfull height has been high. The root depth of plants was low and their average was 0.34 meters. Root density of plants was also low and averaged 5.7% The stream bank angle is measured from 31 to 90 degrees and an average of 51degree. The percentage of surface protection varied between 25 and 65% and averaged 42%. From a total of 36 sites, 8% are in the medium group, 39% in the high erosion category, 45% in the very high erosion group and 8% in the extreme erosion category.
Among the various variables, the β coefficients of the surface protection index and the ratio of bank height to bankfull height were -0.62 and 0.51, respectively. To evaluate the modified BEHI method, all reaches were first examined according to the pre-screening table and more than two "yes" answers were confirmed for each reach. In the modified BEHI method, 26 out of 36 sites were in the erosion group. But in the original BEHI method, 16 sites are in a very high class. The total score of the studied sites was evaluated by two BEHI methods with Pearson correlation coefficients, which obtained a coefficient of 0.21 and shows a relatively low correlation.
Conclusion
Sajadrood stream has high and steep banks due to the incision created in the channel bed. The deposition of large boulders at the toe of the streambank has caused its protection and the flood currents of bankfull are not able to carry this piece of rock. Under these conditions, calculating the ratio of bank height to bankfull height cannot indicate the erodibility of the streambank in the bankfull stage. Nevertheless, the erodible potential of the bank for larger flood currents is confirmed. Comparison of the original BEHI with the modified BEHI showed that the modified method has an overestimate than the original BEHI.

Key word: river bank erosion, BEHI, Sajadroud, Mazandaran
 
Dr Fariba Esfandiari Darabad, Dr Raoof Mostafazadeh, Eng. Amir Hesam Pasban, Eng. Behrouz Behruoz Nezafat Takleh,
Volume 9, Issue 1 (5-2022)
Abstract

Soil erosion is one of the environmental problems that is a threat to natural resources, agriculture and the environment, and in this regard, assessing the temporal and spatial amount of soil erosion has an effective role in management, erosion control and watershed management. The main aim of this study was to estimate soil erosion in Amoqin watershed and its relationship with well-known vegetation-based and topographic-related indices. The meteorological data has been used to determine the rainfall erosivity. The rainfall erosivity index was calculated using the modified Fournier index during the 10-year available recorded rainfall data. The value of LS factor has been calculate using digital elevation model. Meanwhile, C and P factors were determined based on the utilization scheme and condition of the study area. Data were analyzed and processed using ArcMap 10.1, ENVI 5.3, and Excel software. In this study, RUSLE model was used to estimate soil erosion, in GIS environment. According to the results, the amount of factor R in Amoqin watershed varies from 12.32 to 50.52 MJ/ha/h per year. The variation of soil erodibility index (K) over the study area is between 0.25 to 0.42. The amount of LS factor varies between 0.19 and 0.38, which is more in high slopes, especially around the waterways and uplands of the study area. The variation of C factor was estimated to be around -0.18 to 0.4. In general, it can be said that the central part of Amoqin watershed has less C value due to the greater area of agricultural activities and the highest amount is related to western areas, especially southwest areas because existing the rangeland areas. Due to the lack of protective measures in the study area, the amount of factor P was considered as unity for the whole region. The base layers of RUSLE factors were obtained and overlayed in GIS to calculate the soil loss in tons per hectare per year. The map of annual soil loss indicate that the erosion amounts varies between 1.21 to 5.53 tons per hectare per year in different parts of the study area. According to the results, the vegetation factor with a coefficient of determination 0.47% had a significant correlation with soil loss. The stream power index with the coefficient of determination of % 0.07% had the lowest correlation with soil erosion values.
Dr Javad Mozaffari, Mohamad Pooranvari, Dr Seyed Asadolah Mohseni Movahed,
Volume 10, Issue 1 (5-2023)
Abstract

Introduction
Soil erosion is the process by which soil particles and components are separated from their main bed by an erosive agent and transported to another location. In the soil erosion process, there are three distinct phases: 1- separation of soil particles, 2- particle transfer and 3- sedimentation of transported materials. In water erosion, the erosive factors are rainfall and runoff. Erosion and the consequent reduction of soil fertility are among the issues that make it difficult to achieve sustainable agricultural development and environmental protection. It is important to study the quantity and quality of erosion in the country's watersheds and to prevent the loss of one of the richest and most valuable natural resources of the country, namely soil, and to fight against this process. (Tabatabai, 1392). Therefore, to calculate the rate of erosion and sediment production in most watersheds of the country that lack statistics or lack of statistics, the use of experimental models to estimate erosion and sediment is required. According to what has been said, the present study was conducted based on the following two main objectives: 1- Estimation of erosion and sediment in Adineh Masjed watershed, which is one of the main sub-basins of Kamal Saleh Dam, using EPM and MPSIAC experimental models and 2- Investigation and comparing two models and choosing a better model for similar regions and climates.

Materials and methods
Adineh Masjid watershed is one of the sub-basins of Dez and the main sub-basin of Kamal Saleh dam. Temperature, isotherm, geology of the area, slope and available information were performed and finally, by interpreting the photos, types, land units, current land use were determined and updated with field control. For a more detailed study, first, according to the condition of the main waterway and changes in the appearance of the land and vegetation and new land material, the ridges separating the basin were divided into 15 sub-basins. In EPM model, four watershed erosion coefficient (Ψ), land use coefficient (Xa), rock and soil susceptibility coefficient to erosion (Y) and average basin slope (I) and in MPSIAC model, nine geological, soil, climate factor (Climate), runoff, slope, vegetation, land use, current erosion status and waterway erosion are examined. Each model was scored according to data analysis and digital images and then placed in the relevant formula. Finally, the amount of erosion and sediment in the basin was estimated and the sedimentation class of the area was determined.
Results
To determine the score of nine factors affecting soil erosion using MPSIAC method and the four factors of EPM model, each of the factors affecting erosion in units were analyzed. Finally, by weighting, the points of each factor in the models were calculated. The degree of R deposition from the sum of the nine factors of MPSIAC model and the degree of Z erosion was obtained by combining the four EPM factors. Then, the amount of sediment production and erosion in the field of relationships related to each model was calculated and compared and analyzed. In MPSIAC model, the amount of specific sediment (M3 / Km2 / year) was calculated as 112.713 and the specific erosion (M3 / Km2 / year) was calculated as 375.71. In the EPM model, the amount of specific sediment (M3 / Km2 / year) was calculated as 213.95 and Specific erosion (M3 / Km2 / year) was calculated to be 395.86.

Discussion and conclusion
The results of sediment and erosion estimation were estimated separately for each sub-area using two models and it was found that the two models are somewhat relatively compatible with each other. The results of MPSIAC model, have more accuracy and reliability, and therefore the results of the MPSIAC model can be used to estimate the amount of sediment entering the Kamal Saleh Dam. However, due to the small distance between the results of the two models, if we do not have access to MPSIAC model data in similar areas, the EPM model can be used with less data and more easily accessible. It was also observed that in the upper and entrance parts of the basin, where the slope is higher and the vegetation is less, the amount of sediment production and erosion is higher in these areas. So that the upper parts of the basin are in the medium erosion class and the rest of the basin is in the low erosion class.

Keywords: watershed, erosion and sediment, modeling


 

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