کاظم نصرتی

Dolines as karst landforms play an important role in soil formation. In this study, the morphometry of dolines and their relationship with the physicochemical characteristics of soil in Noakoh Anticline in Kermanshah province were evaluated. Chemical and physical characteristics of 36 soil samples of dolines were collected and measured in the laboratory. Also, digital elevation model (DEM; 13 cm) obtaining from UAV images, was used to measure the morphometric parameters of dolines. Pearson’s correlation and T-tests were performed on data using SPSS software. Results showed that large dolines have higher slope, depth and roundness, as well as sandy soils, and higher EC, pH, potassium, phosphorus, water holding capacity and soil organic carbon. Also, low- elevation dolines have higher values of area, slope, depth, roundness, and host soils wih higher EC, PH, potassium, water holding capacity, organic carbon, and saturation percentage than high elevation dolines. The dolines located in the plunge of the anticline have higher values of area, slope, depth, roundness and cntain soils with higher values of clay%, EC, PH, potassium, water holding capacity, organic carbon and saturation percentage than the dolines in the central part. The mean of the most morphometric parameters and physicochemical characteristics of the soil in steeper-slope dolines is higher than in low-slope dolines. Therefore, the morphometric and pedological differences of dolines show that their formation and evolution are more at lower altitudes, plunged areas and steeper slopes. In general, vegetation, elevation, slope and type of precipitation play an important role in morphometric differences and soils in dolines.

Soil erosion is a natural geomorphic process. An increasing number of studies show that changes in the rate of erosion and sediment yield in watershed are often strongly correlated with seismicity. Peak ground acceleration is equal to the maximum acceleration of the ground that occurred during the shaking of the earthquake in a place. Therefore, the purpose of this study is to investigate the relationship between soil erosion and seismic activities and erosion control factors, how high erosion zones are related to the Peak ground acceleration and other factors, and to compare the efficiency of two fuzzy logic and entropy models in erosion zoning.

Talar drainage basin is located on both sides of Qaimshahr-Tehran axis. In terms of geographic coordinates, it is located between ˚52 '35 "22 to˚53 '23 "34 east longitude and ˚35 '44 "23 to ˚36 '19 "1 north latitude. For this purpose, important indices such as erosivity, erodibility, slope-length, cover management have been calculated in the RUSLE equation. Then, the zoning map of the peak ground acceleration has been used as the erosion control factor using the seismic hazard analysis method obtained in the study (Ashtari et al., 2023).

Fuzzy logic and entropy:

For the purpose of zoning, all the layers produced in the previous step were placed as base layers in fuzzy logic and entropy models. Linear function was used to quantify all layers in fuzzy logic. In order to combine the layers, the fuzzy gamma operator was used. In the entropy model, based on the map of erosion levels from specialized studies of the Talar drainage basin, the number of sample sites in each of the erosion zones is as follows: The areas of surface erosion are (16), lateral stream erosion (10), groove erosion (9), gully erosion (8), rock and rock mass erosion (6) and badland erosion (1). The steps of the entropy method are as follows: forming the decision matrix, Ej function and determining the value of entropy, calculating the degree of deviation of criteria dj, determining the weight of each criterion Wij, regional erosion risk model Hi.

Rainfall erosivity factor: This factor expresses the kinetic energy of rain when the drops hit the soil particles, and in other words, it is the intensity of precipitation and erosion resulting from the impact of rain drops on the ground during rainfall. The highest and lowest amount of this factor is respectively in the northern side of the sub-basin 3 with (369-457-8) and in the southern side of the sub-basin 1 with (13.9-102).Erodibility factor: It is in accordance with the average sensitivity factor of formations to erosion of sub-basin 1 (6.09), sub-basin 2 (6.39), sub-basin 3 (7.6). Due to the extent and variety of geological formations, there is a high potential for erosion in all 3sub-basins.length - slope: which is also known as the topography factor, is a function of the height in the basin. The lowest amount of this factor is in the areas of valleys and river streams (>6) and the highest amount corresponds to slopes and heights (>23).cover management: Vegetation factor represents the amount of vegetation waste in different uses. The lower the amount of c, the more vegetation in the area. The highest coefficient c (0.5-0.6) is in sub-basin 1, which indicates the decrease of vegetationand the potential for erosion, and the lowest c (0.2-0.3) in sub-basin 3, which indicates the richness of land uses from forest vegetation.Peak ground acceleration factor: The highest amount of ground acceleration is near the active faults in the region. Due to the structure of the faults, which have an east-west trend, in all 3 sub-basins there are areas of maximum ground acceleration during each event. The highest areas of ground acceleration levels (0.5-0.6) are sub-basin 1 and the lowest are sub-basin 3, which is due to the structure of active faults such as Firuzukuh fault, IRQ112 and IRQ357.

The highest area is in the very low class (839 km2 and 39.9 %) and the lowest area is in the low class (162.9 km2 and 7.7 %). The largest expansion of the mentioned areas is located in sub-basin 1. The distribution of high and very high-risk areas especially in sub-basin 2 and the low coverage of these areas in sub-basin 1 do not match with the relative contribution of high sediment production in sub-basin 1 based on studies.Erosion zonation map by entropy methodThe results of the entropy model showed that the erodibility factor was 20.62%, the peak ground acceleration factor was 20.20%, the cover management was 20%, the erosivity factor was 19.60%, and the slope-length factor was 19.58% in the occurrence of erosion in the region. The area of very high risk with 13.5% of the area of the basin includes erosional facies containing surface, groove, gully and lateral stream. In general, it can be said that the highest erosion risk zones are not related to the highest weighting of the layers, but the placement of a set of factors influencing the occurrence of erosion, which shows the highest amount of erosion.

The peak ground acceleration has a direct impact on the control of sediment yield and erosion processes. The placement of a small part of the IRQ112 fault has caused the extent of ground acceleration levels (0.5-0.6) to be less in sub-basin 3 and more in sub-basin 1 due to the placement of 3 faults, Firuzukuh, IRQ112 and IRQ357. The placement of erodible formations in the ranges of peak ground acceleration has caused the process of sediment production and erosion to accelerate. The coordination of the erosion occurrence zones with the ground acceleration levels is due to the regionality of the entropy model in contrast to the fuzzy model.

Soil erosion is a serious environmental issue. This issue is especially significant when it comes the use and management of land. It is a complex and dynamic phenomenon that has detrimental effects on the physical, chemical, and biological properties—or the quality—of soil and, water while being strongly influenced by soil characteristics, land use, and land management practices. Sediments originate from different parts of the watershed, and the spatial-temporal variability in the contribution of sources (land use, geology, and topography) to sediment yield is related to the localized and dynamic nature of erosion processes. The purpose of sediment transfer studies is often to identify the sediment source, its ultimate fate, and the sediment transport process within the watershed. However, many variables, such as climate, vegetation cover, topography, soil type, and human interventions, can affect the dynamics of source distribution, the fate of suspended sediment, and the sediment transport process in rivers. Therefore, modeling and predicting sediment sources is complex and uncertain due to the variability of environmental factors. Quantifying and identifying sediment sources and associated pollutants is a critical step in soil and water management. Consequently, quantifying soil erosion and sediment production using conventional techniques is challenging, time-consuming, and costly.In recent decades, sediment fingerprinting has been developed to address this problem and has been successfully employed as a powerful tool in sediment and pollutant source tracing studies. Over the past 20 years, sediment fingerprinting has emerged as an essential approach to quantifying the relative contributions of different land use sources to organic matter loads in waterways. Using multiple source group classifications (e.g., agricultural land, pasture, forest, wetlands) can lead to better spatial differentiation of sediment sources, with each source needing to be robustly distinguished by at least one tracer. Currently, examining soil erosion mechanisms and weathering processes is essential to help prevent soil degradation in the region. The weathering process is one of the primary mechanisms controlling the cycling of materials on the Earth’s surface and involves a combination of physical processes and chemical reactions that transform primary minerals into more stable forms. Weathering indices are based on the elemental composition of rocks and soils. Most of these indices are molecular ratios and weight percentages among different groups of major oxides. Therefore, weathering indices have the potential to provide useful tracers for identifying and allocating sediment sources, as they reflect the susceptibility of potential source areas to erosion driven by interactions among climate, geology, soil science, tectonic processes, vegetation cover, and human activities. Accordingly, the main aim of this study is to examine the role of different land uses in sediment production in the Alvand watershed, using geochemical properties and weathering indices as tracers and  applying the Bayesian mixing model MixSIR.

The study area in this research includes the Alvand watershed, located in the southwest of Kermanshah province. The study area ranges between latitudes 33 degrees 57 minutes to 34 degrees 34 minutes and longitudes 45 degrees 32 minutes to 46 degrees 28 minutes, situated between the Tigris and Iran Plateau. The four main sub-catchments of the Alvand watershed include Chelh-Gilan Gharb, Koferavor-Sagan, Sar Pol Zohab, and Qasr-e Shirin. Due to the vastness of the Alvand watershed, this study focused on the Sar Pol Zohab sub-catchment, which includes three sub-catchments: Qale Shahin, Reijab, and Patagh. This watershed, with an area of 1671.93 square kilometers, follows the general direction of the Zagros, running from northwest to southeast. Its maximum elevation is 2474 meters, and its minimum elevation is 486 meters at the watershed outlet. The study area has a Mediterranean climate with a rainy season corresponding to the cold season. The average annual precipitation in the watershed is about 600 millimeters, with an average annual temperature of 13 degrees Celsius. Generally, in the eastern mountainous regions of the watershed, there is more precipitation and lower temperatures, while in the lower western regions, precipitation is less and temperatures are higher.Sampling is done in two ways, one based on sediment sources and the other based on the target sediment or basin output. In other words, in sediment provenance, samples should be taken from sediment sources and sediment outputs. All sediment and source samples were dried at 60 degrees for 24 hours. They were sieved using a sieve smaller than 125 micrometers. XRF analysis was performed on 36 sediment samples. 20 grams of each sample were taken for this purpose, and the concentrations of important geochemical elements, including Al, Ca, Fe, K, Na, Mg, Si, Ti, P, and LOI, were measured using X-ray fluorescence (XRF) equipment. In order to assess the efficiency of weathering indices computable using the measured geochemical elements, 42 air pollution indices (Table 1) were calculated to provide useful tracers for inclusion in sediment provenance. All elements were converted to oxide percentages, and then the molecular weights of the oxide forms were calculated using molar mass.For investigating the proportion of each source of sediment in a tributary, three main steps were used. First, the non-conservative behavior of tracers and a mass conservation test were performed. Second, a two-stage statistical procedure identified the optimum set of source material properties to use as composite fingerprints. The abilities of individual properties to discriminate among sources were tested via the Kruskal-Wallis rank sum test, and those properties that return a P value >0.05 were excluded. Then, a stepwise discriminant function analysis (DFA) was performed to determine the proportion of samples that were accurately classified into the correct source groups. Third, the mixture sampling-Importance-Resampling (Mix SIR) Bayesian model was used to estimate source proportion.Modeling source proportions using statistically validated composite tracers was assessed through virtual sediment samples with known source contributions (Haddadchi et al., 2014). Specifically, model predictions were evaluated for land-use sediment source proportions using 14 sets of virtual sediment mixtures. To generate these virtual sediment samples, known source proportions (details of the source proportions used in the virtual samples are provided in Table 5) were multiplied by selected tracer values, which serve as composite tracer components. The resulting values were then used as inputs for the un-mixing model. The predicted source proportions were subsequently compared with the actual proportions to evaluate the accuracy of the Bayesian model’s predictions. The results from the virtual sediment sample tests were assessed using root mean square error (RMSE), mean absolute error (MAE), and the index of agreement (d).

The results of the standard Bracket test indicated that 10 tracers (WIP, ALK, MWPI, IR, WI-1, Chittleborough, ST, SF, CIW, LOI) were non-conservative and were thus excluded from further analysis in different erosional land-use units. To select tracers, the Kruskal-Wallis test was initially applied. Out of 9 geochemical elements and 42 weathering indices used as tracers, the element sodium (Na) and the weathering index (FENG) were found effective in differentiating sediment units.Comparing the known contributions of sediment sources to the estimated contributions across different land uses (rainfed cultivation, irrigated cultivation, and pasture) using virtual sediment mixtures demonstrated that the root mean square error (RMSE) ranged from 4.2% to 35.5%, the mean absolute error (MAE) ranged from 3.9% to 30.7%, and the index of agreement (d) ranged from 0.060 to 0.907. The overall mean RMSE, MAE, and d for spatial predictions generated using virtual mixtures were 19.6%, 17.5%, and 0.711, respectively.

In this study, land use was considered as sediment sources, the samples collected from various land uses can serve as indicators of different geomorphological processes (erosion and sedimentation), geological changes, and more. This may explain why the optimal combination of tracers aligns with findings from other studies. It is important to remember that source estimates are scale-dependent, as they may vary across sampling sites along a channel network. Regarding land use in the studied watershed, irrigated agriculture is more prevalent than other cultivation methods. However, rainfed cultivation, due to improper land use practices and poor agricultural methods (such as plowing along the slope), contributes the most to erosion and sediment production. This research comprehensively examines weathering indices in various land uses as sediment sources within the Alvand watershed, assessing 42 indices as new tracers, in contrast to previous studies (Derakhshan et al., 2024; Mohammadi Rayegani et al., 2019) that evaluated only a limited number of weathering indices. Geochemical properties of soil generally differentiate the surface soil based on weathering differences, which are also influenced by land use and management practices. With the high erosion rates (Derakhshan Babaei et al., 2020), approximately three-quarters of the nine geochemical elements and 42 weathering indices initially listed passed the two range-based bracket tests.This study investigates the contributions of sediment sources from various land uses based on sediment fingerprinting techniques, using weathering indices along with geochemical elements as tracers to identify and quantify the contribution of each source to sediment yield in the Alvand watershed. A total of 28 soil samples were collected from different land uses (irrigated cultivation, rainfed cultivation, and pasture) to quantify each land use’s contribution using sediment fingerprinting. The results indicate that although rainfed lands cover the smallest area, they appear to produce the highest sediment yield at 53.7%, likely due to poor agricultural practices. Among the 9 geochemical elements and 42 weathering indices analyzed, the chemical element Na and the weathering index FENG were identified as the best tracers, with the strongest differentiation power for sediment sources. These findings suggest that poor land management practices, such as slope-based plowing, cultivation on steep slopes, and improper methods of preparing the land for re-cultivation, are influential factors in erosion and sediment production, which was also observed during field surveys in the study area.

ABSTRACT
Soil erosion is one of the basic problems of watersheds. Soil erodibility is related to factors such as physical and chemical properties of soil. Talar watershed is one of the tectonically active basins in Mazandaran province. The study aims to conduct a detailed analysis of the relationship between ground acceleration and soil properties. In order to compare the effect of acceleration on the soil, the ranges of high acceleration (0.5-0.6) g and low (0.3-0.4) g were determined in sub-basins 1 and 2 of Talar basin. Then, 40 soil samples were collected from different sub-basins, soil texture, organic carbon, and liquid limit tests were conducted, and the relationship between ground acceleration and soil physical properties was investigated using linear regression analysis. The results showed that the highest correlation coefficients in the high acceleration of sub-basin 1 and 2 for the sand variables were -0.97 and -0.95, and the silt variables were -0.97, 0.81, and 0.77, respectively. At low acceleration, sub-basin 1 sand is -0.93, silt 0.84, clay 0.78, organic carbon 0.72, liquid limit 0.74, and sub-basin 2 sand is -0.94. The relationship between the acceleration factor and the physical and chemical properties of the soil is not always linear and is highly dependent on the natural characteristics of the watershed. The analysis of the variables in the acceleration ranges showed that in the high acceleration areas (0.5-0.6) g, the peak acceleration factor has a direct effect on the transfer and displacement of soil particles (sand and silt). These results will benefit environmental managers and decision-makers by creating a scientific basis for planning to reduce erosion.
Extended Abstract
Soil erosion is widely regarded as a primary cause of soil degradation, primarily due to its removal of topsoil and essential organic matter, which are vital for plant growth. One significant factor influencing erosion is peak ground acceleration (PGA), a measure of the potential ground acceleration resulting from an earthquake. Here, the peak ground acceleration accurately measures an area's seismicity status since it depends strongly on the frequency of large and small earthquakes. PGA serves as a direct indicator of tectonic activity. Various physical and chemical properties, including soil texture, organic matter content, pH, and permeability, influence soil erodibility. Given that the Talar drainage basin is a seismically active area with notable erosion and sedimentation, this study aims to examine changes in the selected soil physical and chemical properties at varying levels of PGA to understand its impact on sediment transport and erosion within the Talar drainage basin.
 
The probabilistic seismic hazard assessment (PSHA) method was used to determine the level of ground motion at a given place. To analyze and assess seismic hazards and determine the response of each basin area, it is necessary to study the seismicity trend in the basin in question. This study used the zoning map of peak ground acceleration (PGA), obtained through seismic hazard analysis, as an erosion control factor. To assess physical soil properties, such as soil texture, soil organic carbon, and liquid limit, 40 soil samples were collected from the Talar drainage basin as 20 from sub-basin 1 and 20 from sub-basin 2. Sampling was conducted in areas with high (0.5–0.6 g) and low (0.3–0.4 g) PGA, with 10 samples collected at each acceleration range from 0–20 cm depth in each sub-basin. Soil texture was analyzed using the hydrometer method to determine sand, silt, and clay content. Soil organic carbon was measured via the loss-on-ignition (LOI) method, as described by Nelson and Sommer (1982). The liquid limit, which is relevant for fine-grained soils, was tested using the Casagrande cup. In this analysis, PGA served as the independent variable. At the same time, soil properties such as sand, silt, clay, organic carbon, and liquid limit were treated as dependent variables in sub-basins 1 and 2 across high and low acceleration zones.
The Talar drainage basin is situated along the Qaimshahr-Tehran axis, spanning geographic coordinates from 52˚ 35' 22'' to 53˚ 23' 34'' east longitude and 35˚ 44' 23'' to 36˚ 19' 01'' north latitude.  The main channel is 100 km long.  The main and active faults in the Talar watershed, are IRQ112 and IRQ 357. the main formations in the study area are Shemshak, Elika, Karaj, Lar with sandstone, conglomerate, dolomitic limestone, marl and shale lithologies. The main land use types comprise cultivated lands and orchards (80.8 km2, 3.9%), rangelands (730.9 km2, 34.7%), forests (1280.5 km2, 60.8%), and residential areas (12.8 km2, 0.6%). Important cities and villages in the basin can be mentioned as Pol Sefid, Alasht, Doab, Zirab.
 
In sub-basin 1, soil textures include sandy loam, loam, and occasionally clay-sandy loam, while in sub-basin 2, the texture is predominantly sandy loam. In high-acceleration zones, the correlation coefficients of sand, silt, clay, organic carbon, and liquid limit with peak ground acceleration (PGA) in sub-basin 1 are -0.97, 0.77, 0.55, 0.33, and 0.46, respectively. Sub-basin 2 coefficients are -0.95, 0.81, 0.64, 0.31, and 0.68, respectively. For low-acceleration zones in sub-basin 1, the correlations of PGA with sand, silt, clay, organic carbon, and liquid limit are -0.93, 0.84, 0.78, 0.72, and 0.74, respectively, while in sub-basin 2, the values are -0.94, 0.30, 0.46, 0.43, and 0.46, respectively. In sub-basin 1, when sand and silt were entered as dependent variables, the PGA showed significant correlations (p=0.01), with correlation coefficients of r=0.97 and r=0.77, respectively. The resulting regression models are:Sand = 134.5 - 144.8 * PGA                  Silt = -21.8 + 88 * PGA
In low-acceleration areas of sub-basin 1, PGA was significantly correlated (p<0.05) with sand (p=0.01), silt (p=0.002), clay (p=0.008), organic carbon (p=0.019), and liquid limit (p=0.015), with correlation coefficients of 0.93, 0.84, 0.78, 0.72, and 0.74, respectively. The regression equations for these variables are:  Sand = 140.3-222.6 * PGA    Silt = -13.9 +110.5 * PGA    
 Clay = -26.4 + 112.1 * PGA Organic carbon = -28.6+124.4 * PGA      Liquid limit = -6.2 +20.7 * PGA
In high-acceleration areas of sub-basin 2, the correlation coefficients for sand, silt, and liquid limit with PGA are 0.95, 0.81, and 0.68, respectively, with regression equations as follows:Sand = 175.6-209.1 * PGA       Silt = -45.2 +127.3 * PGA     Liquid limit = -41 +105.6 * PGA;
For low-acceleration areas in sub-basin 2, the PGA’s correlation with sand was 0.94 (p=0.01), with the regression model:  Sand = 95.31-92.1 * PGA.
Overall, a non-linear correlation exists between PGA and soil erosion, influenced by the basin's unique characteristics. Key factors include the minimum PGA threshold required to initiate soil particle displacement, increased erosion with higher PGA, and the effects of earthquake frequency, magnitude, and duration. Extended shaking destabilizes particles, particularly in soils with low cohesion and high moisture content. PGA influences soil cohesion, pore pressure, and displacement, particularly on steep slopes where gravitational forces amplify erosion. The findings indicate that high-acceleration areas significantly impact soil particle transport (e.g., sand and silt) in both sub-basins, underscoring the role of PGA in erosion processes.
 
The values of PGA vary in the Talar drainage basin. Due to several active faults in the region, the highest value of PGA (0.6 g) exists in sub-basins 1 and 2. The placement of erosion-prone formations in peak ground acceleration zones accelerates sediment yield and erosion. High-acceleration areas strongly influence PGA on soil erosion, particle movement, and sediment yield. Analysis of soil properties of sand, silt, clay, organic carbon, and liquid limit in high- and low-acceleration sub-basins 1 and 2 highlights PGA's direct impact on soil particle displacement and movement.
 
Funding
We acknowledge the support of Grant number 600.871 funded by the research council of Shahid Beheshti University, Tehran, Iran.
 
Authors’ Contribution
All of the authors approved thecontent of the manuscript and agreed on all aspects of the work.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgment
We are grateful to all the scientific consultants of this paper.

One of the main issues in drainage watersheds is erosion and sediment yield. Lack of proper management in this field can be environmental hazards and even a threat to human life. The purpose of this study is fingerprinting the sources of sediment yield in sub-basins 1 and 2 of Talar drainage basin in Mazandaran province.140 soil samples in first approach and 80 samples in second approach collected respectively sub-basin 1 (77) and (47), sub-basin 2 (63) and (33) of lithological units and range of peak ground acceleration and 20 drape sediment samples at the outlet sub-basins and 28 geochemical elements measured as tracers in the samples. Using the Kruskal-Wallis test and discriminant function analysis, the composite fingerprints was determined. The largest relative contribution of sediment yield based on the Bayesian un-mixing model is in the first approach (sub-basin 1 unit sandstone and conglomerate with 59.1%, sub-basin 2 unit marl and shale with 47.2%), in the second approach (sub-basin 1 unit the range of peak ground acceleration at the level (0.51-0.6) g with 50.3%, and sub basin 2 units channel bank with 64.6%). The results of this study showed that the range of peak ground acceleration have a direct effect on control of sediment yield and erosion processes. Also, division of lithological groups as sources sediment yield based on range of peak ground acceleration, which have a great impact on sediment yield, as a new approach, can be of great help in understanding sediment yield processes.

The geomorphic characteristics of the watersheds are interrelated and the temporal and spatial scale in the form of season and sub-basins affect the concentration of suspended sediment. One of the objectives of this study was to investigate the relationship between suspended sediment concentration and watershed characteristics of Kan River using principal components regression and to recognize the effect of seasons and sub-basins on sediment concentration. The concentration of suspended sediment during four rainfall-runoff events in three seasons and in sub-basins was measured and calculated. The sixteen physiographic and land use characteristics were determined in the sub-basins and the main factors were identified and the scores of each factor for each feature were calculated using principal component analysis (PCA). The results of variance analysis showed that the concentration of suspended sediment was significant in terms of time scale and spring had the highest rate of sedimentation. Redundancy analysis and canonical analysis on the properties that participate in the first factor (PC1) showed the characteristics of the percentage of erodible formation, relatively erodible formation, and percentage of free construction activity, respectively. Road (slope leveling) and stream length are the most essential attributes of sub-basins in the production and concentration of suspended sediment in the study area.

An important and significant issue in applied research for the management of watersheds is to know integrated drainage sediment yield process to recognize hill slopes and fluvial system. In erosion and sediment study, investigation of form and land form evolution was the earth science study core in the long time. So determination of landform contribution in sediment and erosion yield can utilize for erosion and sediment process in watershed. In recently two decades, sediment fingerprinting method was proven as a key method for contribution of sediment proportion. The purpose of this study was to determine the geomorphic landforms in sediment yield in Chehel-Chaye catchment in Golestan province. By using Topography Position Index, four landforms including concave and convex slope, narrow valleys and slope between concave and convex slope were recognized. In eight flood events suspended sediment sampling was done in March to April 2020. By using XRF instrument, 23 geochemical traces was analysis. After bracket, kruskal-wallis and discernment function analysis, Ba، Ni،Pb، V، Mgo، Mno and Cao had the most discernment percentage in all of tracers. Based of Bayesian mixing model, in first concave slopes 60/9 and in second 28/5 percentage of sediment yield. Result of virtual sediment modeling show that root mean squared error are in 0.6 and 8/4 and mean absolute error 1/7 and 23 evaluated.

Soil erosion is considered as an important factor in reducing soil quality and degradation. One of the important and influential parameters in soil erosion is the types of land use. Each of the land uses directly and indirectly affects the erodibility of the soil and as a result the quality of the soil. Heshtian Catchment area needs monitoring of soil quality and erodibility due to natural conditions, human interventions and diversity of land use. Therefore, the purpose of this research is to investigate the effect of land use on erodibility and soil quality in Hashtian Catchment. In this research, 21, 18 and 14 samples of agriculture, pasture, and garden land use were taken from the basin by systematic-random method, respectively. By performing statistical analyses, the physical and chemical characteristics of the samples, including sodium, potassium, total phosphorus, organic carbon, electrical conductivity, pH, calcium, saturated percentage, bulk density, particle density, and soil texture were determined. Using variance analysis, the relationship between the measured parameters and land uses was determined. The results showed that most physical and chemical parameters of soil with P value less than 0.05 have a significant relationship with land use. Also, the results showed that soil quality index with P value (0.17) has no significant relationship with land use, and soil erodibility with P value less than 0.001 has a significant relationship with land use. Also, using Post-hoc test and Tukey's method, it was determined that agricultural use with better quality soil due to aeration and remaining straw and stubble during plowing and vegetation is suitable, and pasture use is suitable due to excessive livestock grazing and the reduction of soil nutrients has a high erodibility compared to agricultural and garden use.

The annual loss of soil in the world is about 75 billion tons. In Iran, soil erosion is one of the most important environmental problems, and in Iran's catchments, soil erosion increased by 800% between 1951 and 2002. The significant decrease in the performance of Iran's catchments due to a large amount of erosion indicates the increasing necessity of monitoring and following up on this destructive phenomenon. Dendrogeomorphology is a technique that has been very successful in describing and determining geomorphological processes. Dendrogeomorphology is a very flexible method to assess soil erosion and can be used as a data source to determine the reliability of data obtained from direct estimation techniques. The purpose of this research is to investigate the state of sheet erosion in the Nachi watershed using the dendrogeomorphology technique on the oak tree's protruding roots as the region's dominant species. Considering the limited nature of such studies in Iran and the very fragile situation of the studied area, and the risk of filling up the reservoir of Zrebar Lake, which is very important from the point of view of the environment, it is necessary to study the situation of sheet erosion and soil wastage and sediment trans.

In order to achieve the research objectives, after collecting and preparing the primary information, including written information, statistical data, maps, and pictures, a preliminary area survey was carried out, and sampling sites were selected. The samples were prepared according to the program, based on the status of the catchment (according to the land use of the catchment and the direction of the range, the desired work units were selected in places with exposed roots). Based on this, different samples were taken in two different forests, agriculture uses, and western, eastern, and southern directions. All the samples were prepared from the oak tree species, which is the absolute majority in the study area. Finally, 64 samples were selected from the collected samples that could analyze the growth rings' anatomy. Discs harvested from the roots were used to reveal the vegetative rings of the discs by polishing and cutting the surfaces. Using a sanding machine, it was gradually polished with different grades to clear the growth ring border. Then, the disks were measured in the laboratory to determine the first year of root emergence and to determine the width of vegetative rings using a Lin-Tab 5 device equipped with a binocular microscope and specialized T-Sap chronology software with an accuracy of 0.01 mm.

This research showed that in the Nachi catchment, surface soil erosion in agricultural use (average erosion rate 2.43 mm per year) compared to forest use (average erosion rate 0.6 mm per year) is about 4 times. The results of the statistical tests also showed that the type of land use affects the average annual surface erosion rate in the studied basin. Also, this study found that different geographical directions do not affect the average annual surface erosion rate of the Nachi catchment. Comparing erosion values in agricultural and forest use shows the importance of natural covers' protective and important role in preserving the soil and preventing its erosion and wastage. Various studies in the world and Iran have shown that in recent decades, there has been an increasing increase in land use changes, that these changes have the basis of increasing runoff and affecting the amount of soil loss, comparing erosion in the agricultural area with the forest area, showing the protective and important role of the covers. Natural and forests have a valuable role in preserving the soil and preventing erosion and wastage of soil.

The results of this research reveal the necessity of paying more attention to studies on the possibility of modification and change of land use in these areas. The change in land use and the negative effects caused by human interference are not only in the basin itself but also in places outside the occurrence of erosion in the form of accumulation on high-quality agricultural lands, pastures, water storage sources, and irrigated canals. Also, the creation of pollution by sediments and heavy metals and accompanying chemicals, especially the threat to the very fragile ecosystem of Zrebar Lake, is more evident today than ever before. It is suggested to use another method parallel to this method in future works to validate the obtained erosion rate. In future studies, sampling should also be done from the northern slopes for a more detailed investigation of the effect of the slope directions on soil erosion.

Controlling soil erosion and maintaining soil quality is essential for agricultural and environmental sustainability. Degradation of soil quality is caused by a combination of issues including land use change, desertification, soil erosion, chemical pollution, and total loss of soil fertility. Among these factors, soil erosion is considered an important factor in reducing soil quality and degradation. Slopes and their different components of them are one of the important and effective parameters in soil erosion, especially in mountainous areas. Different components of the slope (summit, shoulder, back slope, foot slope, and toe slope) directly and indirectly affect soil erodibility and consequently the soil quality and the development of slopes. Therefore, the purpose of this study is to investigate the effect of geomorphic hillslope components on erodibility and soil quality in the Hashtian catchment.

Hashtian catchment is located in West Azarbaijan province, Urmia city. Hashtian catchment area is 21222 hectares, maximum and minimum heights are 2759 and 1639 meters, respectively. There are three types of land use including agricultural lands (irrigated farming, rainfed farming), rangeland, and garden in Hashtian catchment.In this study, 53 soil samples were gathered from the main hillslope components (summit, shoulder, back slope, foot slope, toe slope), and the physical and chemical properties of the samples including sodium (Na), potassium (K), phosphorus (P), organic carbon (OM), electrical conductivity (EC), pH, calcium (Ca), saturated percentage (SP), bulk density (BD), particle density (PD) and soil texture were determined. Then the analysis of variance was used for investigating the relationship between the measured parameters and the geomorphic hillslope components. Also, the soil quality index was estimated using the following equation:SQI=(∑_(i=1)^n▒〖W_i S_i 〗)/n*10Where Wi represents the weights of the soil indicators, Si denotes the scoring function ranks of each soil property, indexed as i, and n reflects the number of variables selected for the MDS. Soil erodibility is also calculated from the Wischmeier equation as following formula:K = ((2.1 * 10 ^ (-4) M ^ (1.14) (12-a)) + (3.25 (b-2)) + (2.5 (c-3) / 759)M = (V.F.Sand + sand) * (100-Ac)Where K is the soil erodibility, Ac is clay, a is organic matter, b is soil structure and c is the permeability code, which is obtained based on soil characteristics. Finally, the soil quality and soil erodibility index in the geomorphic hillslope components were compared using analysis of variance, and the relationship between different slopes was analyzed by Post-hoc test and Tukey method.

The results showed that only the potassium parameter had a significant relationship with the hillslope components. Some soil properties such as saturated soil percent, potassium, and silt, are affected by the slope of the area. It is always expected that the back slope will have high erosion, but the high amount of clay in the back slope indicates the transfer of particles and nutrients from the shoulder to the back slope. On the other hand, due to the high amount of clay and sufficient amount of organic matter and phosphorus, the back slope has an acceptable soil quality. This has also affected the soil erodibility in this area. The summit has better soil quality due to the presence of suitable clay and organic matter as well as more sodium and phosphorus. The foot slope has better soil quality due to the presence of high phosphorus and potassium and also the amount of suitable organic matter.The results of using PCA to determine the MDS showed that four components were calculated to have an eigenvalue >1 and can thereby be used in the MDS. The cumulative variance was 80.56%. The highest PCs loadings were considered as a condition for selecting the final MDS comprised of Na, Clay, P, PD, and SP. The indicators were transformed into a dimensionless combinable score (0–1). In this study, a 'more is better' scoring function was applied to P and SP, and a 'less is better' scoring function was employed for Na and PD. The sand content followed an 'optimal range' function. The final results revealed that Na, Clay, PD, P, and SP had the highest to lowest weights, respectively.SQI = 0.29 S Na% + 0. 27 S Clay% + 0.27 S PD% + 0.27 S P % + 0.16 S SP%The results showed that different hillslope components do not affect soil quality and the mean values of soil quality at the summit are better than other hillslope components.Finally, different hillslope components do not affect the degree of soil erodibility and have no significant relationship with the results of soil erodibility so these results are not similar to the results of Ayoubi et al. (2014) who examined the soil quality of the slopes of Chaharmahal and Bakhtiari province. However, the results are similar to the results of Nosrati (2017) and Nosrati et al. (2015) in terms of the soil erodibility in the shoulder is higher than the other hillslope components. Also, the mean values of soil erodibility in the hillslope components are not significantly related.

The potassium parameter has a significant relationship with the hillslope components, which means that different hillslope components affect this parameter and there is no significant relationship between other parameters and hillslope components. There is no significant relationship between the geomorphic hillslope components and soil erodibility. Also, the summit and foot slope has better quality than other hillslope components due to the decay of vegetation and its effect on carbon dioxide and carbonic acid production. As a result, it increases the ability to absorb organic and nutrient substances, especially phosphorus in the soil. Accumulation of selected minimum data sets on soil quality at the foot slope and the summit has also increased soil quality. The steep slope in the shoulder has caused the washing of soil organic and nutrient materials and lowered the pH, and as a result, reduced the ability to absorb nutrients and increase erodibility.Keywords: Soil quality, Soil erosion, Geomorphic hillslope components, Hashtian Catchment.

Rivers provide water and energy for nature and humans. Thus, water supply is the most important economic role of rivers. Process of erosion sediment transportation is one of the most important hydrodynamic processes which affect a lot of hydraulic systems such as basins, rivers, coasts and harbors, dams, bridges, farms, and construction facilities. Taleghan River is a major river located in the south hillside of Alborz. The river has dynamic behavior affected by various factors including geology, gradient, land use, hydraulic flow condition, and morphological behavior. Analyzing the stability of Taleghan river bank using mathematical and statistical models and comparing its results with field observations is the aim of this research. Therefore, to achieve this aim BEHI model and statistical one-way analysis of variance (ANOVA) is used and then compared with field and visual observations. The results concerning scoring show moderate to high danger of riverbank erosion in upstream sections and high to very high danger of riverbank erosion in downstream sections. According to the results of one-way analysis of variance (ANOVA), the effects of gradient and discharge have been more than the other parameters. In this analysis, the meaningful parameters consist of mean depth; bank full, riverbank high, discharge, and gradient. According to the results, erodible edges were identified.

The Soil and Water Assessment Tool – SWAT (Arnold et al. 1998; Arnold et al., 2012) is a well-established physically based, semi-distributed hydrological model for river basin scale application (Brighenti et al., 2019). is a hydrological model to assess sediment (Yesuf et al., 2015; Vigiak et al., 2017; Abdelwahab et al., 2018), impact of land use (Zeiger and Hubbart, 2016; Choto and Fetene, 2019; stream flow generation (Hallouz et al., 2018; in-stream water quality, climate change and, water quality and quantity variation (Jiao et al., 2014; Francesconi et al., 2016; Yang et al., 2018 ). A number of studies used laboratory, field scales and modeling studies to understand soil erosion and sediment dynamics in various regions. Several worldwide studies have been done using the SWAT model. The objective of this study is to apply the Soil and Water Assessment Tool (SWAT) model to predict surface runoff generation patterns and soil erosion hazard in Badavar catchment and to prioritize most degraded sub-catchment in order to adopt the appropriate management intervention. The specific objective of the study is validation of the SWAT model to assess its capability in predicting sediment yield transport in Badavar catchment.

Study area The study area is Badavar catchment (58311 ha) in the west of Iran and the northern part of Lorestan Province. Badavar catchment is one of the sub-catchments of of the Karkheh River. The average height of the catchment is 1941 m. The annual average precipitation is 527 mm, and the annual average temperature is about 10.5 °C. The climate of study area is in the category of sub-humid, characterized by cold winters and temperate summers. Most of the study area has slope 0-5 degree. Rain farming and week rangeland are the dominate land use in this area.The soil erosion is critical in the Badavar catchment. soil erosion in addition to damages to the land, it will reduce the capacity of the downstream dam of this catchment (the Karkheh dam). So in this study, SWAT model is used to identify the risk of erosion in Badavar catchment and various factors affecting of the erosion.SWAT Model: Model parameters: For preparation of input data, the GIS "version10.3"and ArcMap "ArcSWAT2012" was used. The following basic data were selected as SWAT model inputs:1) Digital Elevation Model (DEM): it is extracted from 1:50000 topography map with a spatial resolution of 30 m. 2) Landuse: it was obtained by Forests, Range and Watershed Management Organization of Iran. 3) Slope: it is extracted from DEM. Slope map shows that the Badavar catchment consists mainly of the plain with low slope (0-5 degree). 4) Hydro-meteorological data: The data required includes rainfall, river discharge, and climate data such as temperatures, solar radiations, humidity, and wind speed. These hydrological and meteorological data are collected from two organizations; the Iran Meteorological Organization and the Ministry of Energy.5) Soil data: SWAT model requires different soil textural and physico-chemical properties. These include soil texture, available water content, hydraulic conductivity, bulk density, and organic carbon content for different layers of each soil type. All of these soil characteristics and the soil map of the catchment were prepared by field survey and 39 systematic random samples of soil and laboratory works. Also the soil texture data was used to extract hydrological soil groups that were linked with FAO’s texture classification. This was then linked with the SWAT database using the soil layers and soil type. 6) Delineation of sub-catchments and HRUs:SWAT uses two types of functional units: the subbasin and the Hydrologic Response Unit (HRU) (Neitsch et al., 2011). The sub-basin is a spatially defined region that comprises a main reach and its contributing area, which is composed by one or more HRUs (Vigiak et al., 2017). On the other hand, analysis the catchment is allowed by SWAT as a whole or by subdividing it into sub-basins containing the same portions called Hydrological Response Units (HRU) (Briak et al., 2016). The HRU is a land unit of homogeneous environmental properties (soil, land use/cover, management, and topography) and hydrologic behavior (Vigiak et al., 2017). 33 sub-catchments and 53 Hydrological Response Units (HRU) have been generated for Badavar catchment.After simulation, factor analysis was used to determine the most important factors in sediment production. Factor analysis attempts to explain the correlations between the observations in terms of the underlying factors, which are not directly observable. The purpose of factor analysis is to reduce the complexity within the similarity matrix of a multivariate data collection, transforming it into a simpler and more easily interpreted factor matrix.Finally, for comparisons between observed and simulated sediment loads, four model evaluation statistics were selected; Correlation coefficient (R2), Root Mean Squared Error (RMSE), Index of Agreement (D) and Correlation determination (r).

The most important inputs of the model are: soil information, land use, slope, elevation, geology, weather information (rainfall, background and temperature, relative humidity, dew point, solar radiation and wind speed). Also factor analysis was used to determine the most important factors in sediment production. The simulation results showed that amount of sediment output from the basin is 7170 tons per year. After implementation of the model, the amount of sediment simulated and observation sediment was compared. Correlation coefficient (R2), Root Mean Squared Error (RMSE), Index of Agreement (D) and Correlation determination (r ) were validated with 95%, 03%, 97% and 97%, respectively which indicated the high accuracy of the results. Also the results of factor analysis showed that the role of land use in sedimentation of the study area is more than other factors.

The comparisons between observed and simulated sediment loads showed that the model has fairly acceptable accuracy for Badavar catchment. A more accurate estimation of erosion and sediment yield can be made by providing accurate data and the best management practice is highly recommended for the dam sustainability, because of the proximity of Badavar cahchment erosion to the Karkheh dam.
Key word: Erosion, Sediment, Factor Analysis, SWAT, Badavar.

 Geomorphologists have always considered geomorphological processes such as weathering, erosion, and sedimentation, and tectonic processes as the main factor creatingdifferent landforms in the ecosystem. Moreover, a large part of the earth’s surface is affected by the presence and existence of organisms, thus these biological species play a major role in environmental changes and consequently in the creation of landforms. In fact, geomorphology is one of the important factors affecting vegetation heterogeneity in the scope of landscape. Alluvial fans are among the important and majorgeomorphologicalforms in which two natural parameters of landform and vegetation coexist. Various methods are used to study vegetation density. Vegetation variables are commonly estimated using land surveying, but satellite images have made more accurate methods of rangeland management and alsoestimationof plant quantities in inaccessible areas possible. However, usingdata obtained from satellite imageries for partial measurements has some limitations due to unavailabilityof high spatial resolution images such as QuickBird satellite images or high expenses of retrieving such imagery.In the present study, plant variables were investigated using large-scale aerial imagery and field sampling. Plant density and percent canopy cover were also determined in the study area using the same methods.

Study area The area under study is located in the northeastern regions of Semnan province, northernShahroud city. The study area includes three alluvial fans including Saran, Moghatelan and Hot-Sokhteh.

Based on field observations, Google Earth images, and drainage pattern, alluvial fans were divided into active (young surfaces) and inactive (old surfaces) parts. Six sites (P1 to P6) including upstream, downstream, active and inactive parts of the alluvial fans under study were selected in order to determine the density and percent of canopy cover in channels, interfluves (in old surfaces), bars and swales  (in young surfaces). The aerial image was acquired using a Dji Phantom 4 Pro Drone with a relative flying height of 100 m, and a 20 megapixel, FC6210 digital camerain December 2018 (Table 1 and Fig. 3). The canopy covers in alluvial fan landforms (including channels, interfluves, bars and swales) were measured using large-scale images (1: 500) acquiredby drone. In the next stage, 50 rectangle and squareshaped plots were selected to determine the density and percent canopy cover of the aforementioned landforms in the upstream and downstream of the three alluvial fans; 5 squareshaped plots with a dimension of 10*10 m were selected from the interfluves, 45 rectangularshaped plots with a dimension of 3*10 m were selected from the channels, swales and bars. Then, percent canopy cover was calculated in each plot and the average percent canopy cover was finally calculated for the 50 plots of each site.

 Experimental studies:

In order to investigate physical and chemical characteristics of soil and its effects on the density and vegetation type across alluvial fans, 48 soil samples were collected from a depth of 0-20 cm in the three alluvial fanseach including active and inactive parts, bars, swales, channels, and interfluves. PH, EC, phosphorus (P), absorbable potassium (K) and sodium (Na), calcium carbonate (CaCO3), Saturation percentage (Sp), water retention capacity of soil (WHC), soil texture, and total organic carbon (OCT) were also measured in the samples. Sampling vegetation and identifying plant species In order to identify plant species, field work was carried out in June 2019. Plant species of the study area were identified and a sample was collected, dried and pressed.Systematic random sampling was used in the specified types. In fact, a 200-meter transect was selected in each site, and 8 plots with a dimension of 8 * 8 m were identified along each transect including channels, interfluves, swales, and bars of the upstream and downstream alluvial fans. Therefore, 43 vegetation sampling plots were selected along the 200-meter transect.

In the active surfaces of both upstream and downstream alluvial fans, density and percent canopy cover of bars arehigher than those of swales, because of the higher amount of silt and clay in bars. Larger plant species such as shrubs and sub-shrubs requiringfine-textured soil grow in these bars. On the other hand, swales have a higher amount of organic materials and calcium carbonate. EC and PH are lower in the bars as compared to the swales. Water-holding capacity (WHC) and Saturation percentage (Sp) of the soil are higher in the swales as compared to the bars. There are more absorbable potassium and phosphorus in the bars. However, vegetation density and percent canopy cover in swales are lower than those of bars despite their high soil fertility and moisture. This is probably due to the lower stability of the swales whichresults in their higher exposure to unstable currents during occasional storms and floods.Overall, plant species adapted to the specific environmental conditions are settled in each landform. PerovskiaAbrotanoides is the dominant plant species in active surfaces ofbars. The vegetation type is more limited in the swales of active surfaces including species likePoabulbosa and Bromusdanthoniae.In inactive surfaces of alluvial fans, elementsrequired for soil fertility (organic materials, calcium carbonate, absorbable potassium and sodium, phosphorus, pH, saturated moisture of the soil, and soil retention) are higher in the interfluves as compared to channels. The relative higher fertility of interfluves can be attributed to their gentle slopes, higher stability and hence higher possibility of soil formation. Long-term exposure of sediments or alluviums to weathering elements on relatively flat surfaces of interfluves has resulted in the formation of more clay and silt, and thereby denser vegetation in interfluves compared to channels. Herbaceous and shrub species, which require fine-textured soils, settle in interfluves. On the other hand, vegetation density of channels with higher amounts of sand and pebbles is lower likely due to their steep slopes as well as their higher level of erosion. However, percent of canopy cover is higher in channels as compared to interfluves. Channels have a relatively higher level of moisturesince they are in the shade and in vicinity of groundwater. Hence, shrubsare settled in these landforms. These species havea denser canopy cover, and deeper roots and require coarser soil texture.Artemisia sieberi is the dominant plant species in inactive surfacesofinterfluves.This species is a sun-loving plant requiring lots ofsunshine to grow.Apart from Artemisia sieberi, other plants such as Astragalus sp., Acanthophyllum sp., Peganumharmala, AmygdalusScoparia and convolvulus acanthocladus have also settled in the interfluves.

Analyzing vegetation density and percent canopy cover of alluvial fans and their related landforms indicated that bushes are more frequent in the interfluves of old surfaces as compared to other parts of these fans. Despitelower vegetation densityin bars of young fans and channels of old fans, they have a larger type of vegetation (mainly shrubs) and thus, a higherpercent canopy cover. Generally, this study has revealed that bushes are more frequent in the old alluvial fans, especially upstream parts of the fans as compared to other areas. Overall, the results indicate that geomorphological processes such as aggradation and degradation affect the texture and fertility of soil as well as type and density of vegetation.

Quantitative evaluation of the relationship between vegetation and environmental factors is an essential tool in the modern researches on vegetation ecology. The establishment of a plant community, changes in canopy cover percentage and plant density are influenced by soil, climatic, geomorphological and biological factors. Studying the above factors causes the distribution, density and variations of vegetation cover and habitat potential. Much of Iran has the arid, semi-arid or extremely arid climate. In most of these areas, vegetation is little and establishment of vegetation in these areas are associated with numerous restrictions. In addition, the distribution and density of vegetation on the land surface was not accidental, but rather the presence of different plant species in one habitat due to environmental factors (climate, soil, topography, etc.), ecological needs of each plant and tolerance range of each species. Relative to the environmental factors important in each habitat. In fact, by studying environmental characteristics using different statistical methods, the causes of plant community distribution are identified, the most important environmental factors affecting community distribution and the habitat's ability to adapt to other communities. Classification techniques are one of the multivariate statistical methods used in ecological knowledge in the last three decades. Ordering reveals the hidden in the collected data and also reduces the volume. Methodology Study area The area under study has been located in the northeast of Semnan province, north of Shahroud city. The study area includes three alluvial fans including Saran, Moghatelan and Hot-Sokhteh.

Impact alluvial fans are always one of the most prominent geomorphologic landforms with new, old, and even fossilized surfaces. Separation of old and new alluvial fans can be done based on indicators such as weathering, morphology, surface of alluvial fans, drainage patterns, color tone in satellite images. Vegetation sampling Field operations were carried out in early June 2019 with the aim of familiarizing with the area, collecting and identifying plants. In fact, at each site (P1 to P6) 1 transect of 200 m and along each transect 8 plots of 8 * 8 m were deployed on Interfluves, Swales, channels, Bar on toe and apex of all three alluvial fans. Therefore, 43 vegetation sampling plots were laid. Then, within each plot, plants were identified and list of plant species, percentage and canopy density of each species were recorded in the plot. Soil sampling In order to investigate physical and chemical characteristics of soil and their effects on the density and type of vegetation on alluvial fans; 48 soil samples from soil depths of 0-20 cm were collected from different landforms of old and young surfaces of alluvial fans, including bars, swales, channels, and interfluves. Also the amount of PH, EC, phosphorus (P), absorbable potassium (K) and sodium (Na), calcium carbonate (CaCO3), Saturation percentage (Sp), water retention capacity in the soil (WHC), soil texture, and total organic carbon (OCT) were measured. Vegetation analysis In this study, based on 13 physical and chemical properties of 44 quadrates, cluster analysis was performed and vegetation classification was performed by using PAST software. Classification of environmental factors and vegetation Multivariate analysis of principal components (PCA) was performed using by PAST software. Principal components analysis was performed on 13 environmental factors including soil texture (sand, silt and clay content), acidity (pH), electrical conductivity (EC), organic matter content, saturation moisture content, soil water retention capacity in the soil, calcium carbonate, phosphorus, Potassium, sodium and percent of gravel or pebbles were determined.

Plant species of study area Overall, 32 families, 44 genuses, and 46 species were identified by field works in study area. classification of Area vegetation Using cluster analysis with Wards method and Euclidean distance index in PAST software showed that 44 plots in the study area belonged to 4 plant communities. Results of Principal Component Analysis (PCA) In order to determine the most important factors affecting the distribution of plant species, Principal Component Analysis (PCA) was performed on the data. Principal component analysis on 13 variables (soil properties) in 44 habitat (landforms) showed that the first, second, third, fourth and fifth axes were 47.66, 38.91, 7.72, 2.33 and 1.4 percentage of variance justifies the vegetation changes.

In the vegetation data analysis of the study area, using cluster analysis, four ecological groups of vegetation were separated which each ecological group represents a unique homogeneous unit of vegetation. Therefore, identification of plant groups and their location is very important in describing the variability of environmental conditions and can be an appropriate model in fitness management. Most of the active and inactive parts of the alluvial fan are located and in the parts where the amount of fine sediment is higher. In fact, soil saturation moisture and soil water retention capacity are the most important environmental limiting factors affecting plant residues in arid and semiarid regions. In the Miami due to chattels grazing, tractor movement to change land use and heavy machinery due to the presence of several factories in the study area, as well as unnecessary harvesting of medicinal and medicinal plants, in some parts of alluvial fans, especially alluvial fans of soil texture. It is being degraded and these are a serious threat to valuable and rare plant species in the region. Keywords: Cluster analysis, Environmental factors, Ordination, Alluvial fan, Landform, Miami.

Accelerated soil erosion poses a serious threat to land management sustainability and water resource utilization in many areas of the world. The objective of this study was to apportion surface (cropland and rangeland) and subsurface (channel bank) sources relative contributions to the supply of suspended sediment during the storm event in Kamish mountainous catchment, using a geochemical fingerprinting approach and Bayesian un-mixing model. To this end, thirty-four geochemical tracers were measured as potential tracers to evaluate surface and subsurface sediment sources (69 samples), including 10 target suspended sediments samples collected across the hydrographs of a flood event at the overall catchment outlet. In total, two statistical methods Kruskal–Wallis H test and discriminant function analysis (DFA) were used to select the optimum tracer composition. The results of Bayesian un-mixing model indicated that mean (uncertainty range) relative contribution of cropland and rangeland (surface land-use) and channel bank (subsurface) sources are 31.8 (12.7-50.3), 33.2 (17.5-49), 35.2 (25.6- 44.6) percent, respectively. These results indicate surface and subsurface sediment sources have the same contribution to the supply of suspended sediments during the basin flood event. Although sediment sources contribution in during the flood event change intermittently between subsurface and surface soils. As a result, targeted management practices should focus through erosion and land use control of these sources for minimizing their effects on fine sediment deposition.

Erosion and sediment transport are the important hydrodynamic processes in drainage basins that can affect many hydraulic and hydrologic systems such as rivers, beaches, ports, dams, bridges, roads, and farms. One of the most important sediment sources in Iran drainage basin is bank channel erosion that causes on-site and off-site effects. Therefore, investigating of channel/river band instability is necessary for engineering activities to stabilize the riverbank against bank erosion. Thus, the main objectives of this study were to investigate the instability coefficient of the Taleghan River and to find the engineering solution for its stabilization by using the Lin model. In view of this, all required parameters comprising slope, shear stress, slope angle, and satiability coefficient of grain are measured using filed study and Google earth imagery. Finally, bank satiability coefficient and effective rock size for revetment besides the riverbank is obtained in the study area. According to the results, the highest amount of bank erosion and consequently, the lowest stability coefficient and the largest stone at the threshold and effective on revetment are related to the 4th section. The lowest amount of erosion, as a result, the highest range of stability coefficient and smallest stone at the threshold and effective on revetment is related to the 1st section. The main reason could be the size of the grain size on the side, the slope of the basin, slope aside and bank full discharge width.

Mallard city has two aquifers comprising Tehran-Karaj and Ghate-Chahar that providing most of drinking water for villages of this City. Accordingly, there is a dire need to investigate quality and quantity of groundwater in this area. The aim of this study is to survey the impact of soil physical and chemical properties on quality and quantity of Mallard groundwater. in view of this data from thirty-one drinking water wells during a 6-year period were used. the soil physical e.g. soil texture, uniformity coefficient, curvature factor, permeability coefficient, saturation percentage, effective porosity percentage and chemical including electrical conductivity level, sodium, potassium, calcium carbonate, total dissolved solids, pH and dissolved salt percentage properties were measured in seventeen soil samples. the results showed that in eastern areas due to loamy-clay texture of the soil and suitability of permeability coefficient and saturation percent rate the discharge of the wells is better in comparison to other areas. Qualitative parameters of the soil such as Calcium Carbonate, Electrical Conductivity, Total dissolved solids, Sodium, Potassium have strong Positive correlation with Qualitative parameters of groundwater in alluvial Terraces. In agricultural and residential areas, the of nitrate concentration in drinking water have relatively strong positive correlation with soil EC, TDS and dissolved Salt.

One of the most elements in river geomorphology, engineering and management is the channel issue. Rivers are natural and complex systems that their classification offers a better knowledge regarding their processes and forms. Based on dynamic and channel forms, rivers are varied and find natural changes over the years. However, nowadays anthropogenic effects comprising building structures such as bridges, and roads accelerate the destructive process. River classification is a suitable way to increase our knowledge about rivers. One important aspect of river is hydrogeomorphological understanding. Therefore the objectives of this study were to assess and analyze the Taleghan river hydrogeomorphological conditions using the geomorphological quality index method (MQI) in upstream of the Taleghan dam and to validate MQI in this river.

Six reaches in upstream of the Taleghan River have been selected and MQI for each reach determined using satellite images and field survey. In order to determine SQI for each reach, three aspects have considered including river processes continuity (longitudinal and crosswise), channel morphological condition, cross-section form, sediment bed loads and vegetation. These aspects investigated in the form of three  components consists of geomorphological functions, processes and river forms (F), artificial (A) and channel adjustments (CA).

After measurement and field observation of the Taleghan River, effective variables on morphological quality index were obtained in reach. MAI and MQI values for each reach were calculated and classification was done based on the range of each class. The condition of each reach based on MQI was explained as follows:The first reach: took place in a mountain area and upstream of the river that on both sides connected to the river and is limited.Based on the NBS model erosion of bank steam is in a minor amount and the average bed slope in this reach is 0.028 with gravel bed.Channel width is variable between 10 to 18 m and has a single channel pattern. The obtained MQI values in this reach is 0.714 that grouped in a good class. Reaches comprising four reaches (two, three, five and six) have the same condition that in the point of human interfering, morphological condition and values of bed and bank erosion have a normal array and grouped in moderate class.In reach 4 the river is fairly limited and flood plain is present discontinuously on one side and the other side is attached to the hillside. The river has a sinuouse pattern and bed load sediment formed by fine and coarse sand. Furthermore, forth reach strongly influenced by human changes consists of gravel and sand quarring, the existence of bridge structure on the river, presence of built-up area and destruction of vegetation along the river.

Discussion and conclusion

The results showed that reach one with score value of 0.714 due to low human interference and locating in upstream of the river categorized in a good class. Otherwise, reaches two, three, five and six have values of 0.58, 0.54, 0.59 and 0.61, respectively and they are categorized in moderate class; in these reaches in comparison to reach one the values of human interference have been increased. The reach four with MQI score value of 0.49, is categorized in a weak class because of human interference including gravel and sand exploitation and structures such as bridges on the river. The results reveal that the MQI model is approperiate for the classification of rivers in the Taleghan River in southern of Alborz Chain Mountain.

The purpose of this study was to determine the relative contribution of sub-basin resources to sediment production by using magnetic susceptibility data as the tracer in Chehelgazi catchment, Sanandaj. For this purpose, 20 samples of the output 5 sub-basins were measured by harvesting and magnetic susceptibility. Kruskal-Wallis test results showed that in all three trackings, frequency high, low and dependent, at least two sources had the ability to differentiate. In the second step, the three tracers were tested on the discriminant analysis by the sub-basin source and two tracers with different power splitters showed the high frequency of 88% and the frequency dependence of 12%; power splitters both tracers together in the sub-basin splitters was 90%, so they were selected as the optimal combination; therefore, they have the capability to determine the relative contribution model of sediment. The results of Bayesian uncertainty model also indicated Todarsamadi sub-basin with 44.4% of the largest contribution and Doveyseh, Chatan and Cherendo sub-basins with 35.5, 7.9 and 4.5, respectively, and Madian Dol sub-basin with 4/4 percent had the lowest contribution to sediment production. Based on the available results, Todarsamadi and Doveyseh sub-basins had the highest amount of sediment production; so these results could be used in soil conservation and management planning.

Sediment yield is the most important environmental issues in watershed basins which greatly affects human and animal life. Therefore, soil conservation and sediment control is one of the most important measures that should be paid attention. As various factors such as land use change can affect sediment yield,  this study was performed to investigate the effect of land use change on sediment yield of Kouhdasht basin, located in the west of Lorestan province. For this purpose firstly, land use changes were investigated using satellite imagery and then sediment discharge was estimated using discharge and sediment concentration data of Kashkan Afrine station located at the basin outlet. Finally, the contribution of land use in sediment yield was estimated using the fingerprinting technique based on the Bayesian uncertainty model. The results showed that the change in land use from grazing land and forest to agriculture was significant. So that during 1361-1395, 49 and 24.8% of the grazing and forest lands were reduced, respectively and agricultural lands increased by 47.5%. Also the results obtained from Kashkan Afrine station data showed that the average sediment discharge increased from 5.954 ton/day in 1361 to 7.079 ton/day in 1395. The results of fingerprinting sediment model indicated that the agricultural lands have the most contribution in sediment yield. The contribution (uncertainty of 5 to 95%) of agriculture, grazing land and forest in sediment yield were calculated to be 95 (86-99), 3.1 (0-12) and 0.9 (0-3) percent, respectively and the relative importance of each resources was calculated to be 1.5, 0.28 and 0.03, respectively. These results indicated that the most important factor increasing sediment discharge is the land use change from forest and rangeland to agriculture.

Accelerated soil erosion is a serious problem in Iran, leading to degradation of soil and water resources, reduction of soil fertility, destruction of range and agricultural lands, desertification, recurring floods, sedimentation of reservoirs, and pollution of fishery habitats. Hence, understanding of the potential soil erosion process and opposition to this erosion are necessary environmental. To this end, uptake and refinement of sediment source tracing or fingerprinting techniques has expanded dramatically as an alternative approach to traditional methods of identifying key sediment sources. Sediment source fingerprinting involves discriminating potential sediment sources on the basis of differences in source material properties or tracers and determining the relative contributions of these sources to sampled target sediment. different kinds of sediment sources have been used so far in sediment fingerprinting techniques (e. g., land use, geology, sub-basins, surface and subsurface erosion) but, there is a little attention paid to the selecting the soil erodibility groups as sediment sources. Therefore, the main objective of this study are the Kouhdasht watershed dividing into different erodible units based on soil erodibility index and determination of the contribution of each unit in sediment yield using an un-mixing Bayesian uncertainty model and to find its relationship with soil organic carbon stock.

Kouhdasht basin with 1138 km2 area located in  33°  17´ to 33° 41´ north latitude and 47°  20´ to 47°  50´ eastern longitude in western of Lorestan province. samples were collected in two stages; first, 81 samples in order to estimate erodibility, second, in order to determine the contribution of each source to sediment yield, 70 soil samples were collected form sources and 12 sediment samples collected at  the basin outlet.  The soil erodibility was calculated based on the soil texture and based on the geometric mean of the soil particle diameter. Based on the amount of soil erodibility, the area was divided into three different erosion units as sediment sources. To determine the contribution of sediment sources to sediment yield used fingerprinting technique is based on estimation of uncertainty.

The erodibility of the study area varied from 0.0386 to 0.0663. Erodible units were identified as sediment sources based on the values obtained from the erosion parameter and according to the results of selecting the optimal combination of tracers. The results showed that the first erosion unit 2%, the second erodible unit 5%, and the third erosion unit 93% contributed in the region's sediment yield. The relative importance of erodible units in sediment yield was obtained by dividing the share of each resource in the production of sediment into the percentage covered by each source. The relative importance of the first, second and third erosion units is 0.08, 0.28, and 1.57, respectively. Regarding the role of organic carbon in erosion, the amount of organic carbon storage in different erosion units of the area was also measured. The amount of organic carbon storage in each erosion unit is first, second and third ones were 70.5, 64.3 and 54.6 mg / ha respectively.

The third unit with 93% has the largest contribution in sediment yield and with 54.6 mg / ha, it has the lowest amount of organic carbon storage in the area. Considering that this unit is most used in agriculture and geologically under quaternary sediments, showed that the parts that are under cultivation and quaternary sediments have both high erodibility and the highest contribution to sediment yield. Measurements of organic carbon storage also showed, there is the least amount of organic carbon storage in this unit and this suggests that in the third unit, the damage caused by the loss of fine sediments such as clay is higher. Given that the third unit is under agricultural use this can be attributed to the type of land use and exploitation. Therefore recommended more attention to the type of use of land and soil management and conservation programs implemented in the region.

Deficiency of water with suitable quality is a vital challenge in urban and specially in arid and semiarid regions. The aim of this study is to assess temporal and spatial variation of drinking groundwater quality and quantity in County of Mallard in Tehran province. Mallard is a County at margin of Central Iran Plateau. The data used in this research comprises of 14 parameters in 31 drinking water wells that obtained during a 6-year interval. Spatiotemporal variation in these wells were analyzed by applying Parametric and nonparametric statistical techniques including one-way ANOVA, Kruskal-Wallis, independent-samples T-test, Mann-Whitney. The results reveals that concentration of sulfate, chlorine, bicarbonate, electrical conductivity, TDS, sodium and fluorine in dry and wet periods have significant difference. Effects of space on quality of groundwater in Mallard suggest that boring wells in pyroclastic, tuff and sandy lime (E2) Formations meaningfully and at level of Percent 95 have the most impact on mineral concentration of water quality parameters. Furthermore, concentration of nitrate has increased in cultivation and urban-rural land use and the level of pH in cultivating and urban-rural use has decreased significant and at level of Percent 95 in comparison to other lands.

Sediment tracing method has been proven as a successful and effective method to determining sediment sources contribution in sediment yield in recent two decades. Ziarat drainage basin in Golestan province is one of the water supply resources in Gorgan city. The main lithological formations in the study area are Gorgan Schists, Quaternary alluvial deposits, Shemshak and Khosh yeylagh Formation which could have an important role in erosion and sediment yield. For tracing sediment, 14 samples of suspended sediment from catchment outlet during precipitation events and 43 representative samples of geologic formations (as sediment sources) from the soil surface (depth of 0-5 cm) were collected and geochemical elements, 137Cs and organic carbon were measured in the samples as tracers. The optimum set of tracers was selected by using Kruskal-Wallis test and discriminate function analysis. The results of this study indicate that the tracers including OC, 137Cs and Cu have the most potential to discriminate the sediment sources. The result of the sediment fingerprinting mixing model showed that Shemshak formation, fluvial deposition, Khosh yeylagh and Shist formation have 42, 31/9 and 23/7, 1.6% of the sediment contributions in sediment yield, respectively.

Soil erosion is one of the hazards with on-site and off-site effects that gradually cause decreasing soil quality, land degradation, surface water contaminations, reduction of dam’s reservoirs capacity and threating of human food security. The soil loss due to crop harvesting (SLCH) has been considered less comparing the soil erosion types by researches. The objective of this study is therefore to estimate the Potato soil loss due to crop harvesting in the Ghorveh-Dehgolan plain, Kurdestan province. In view of this, 20 samples of potato with weight of 5 kg were collected from dry land and irrigated cultivated lands in the study area. In the laboratory, after washing the samples, the suspensions were filtrated and the remained soils on filter paper were dried and the SLCH determined. The results showed that the SLCH ranged 13.4 to 40.4 g kg-1. The results of one-way ANOVA showed that there is significance difference between SLCH from dry land farming and irrigating cultivation with the confidence level of 95%. The results of cluster analysis also indicated the weak relationships between samples collected from both land use types. The soil loss due to potato harvesting from 80490.4 ha in ten last years was 72374.52 Mg with annual average of 7237 Mg yr-1. Also, the mean soil erosion due to potato harvesting ranged from 0.66 to 1.14 Mg ha-1 harvest-1. The results of this study demonstrated that the soil losses caused by crop harvesting can be of the same order of magnitude as soil losses caused by water erosion processes that should be considered by researchers and planners in soil erosion control and conservation fields.

Snow avalanche is one of the snowy and mountenous areas phenomenons that may result in ‎hazzards and irreparable problems. The objective of this study is to determine the most ‎important effective factors in avalanche events in Meigoun-Shemshak road. Meigoun- ‎Shemshak road has been located in Shemshak drainage basin with area of 37.75 Km2 in ‎Roodbar Ghasran district, Shemiranat County, Northeast Tehran. To assest avalanche ‎corridors, effective enviromental parameters on avalanche including length of valley, width of ‎valley, azimuth, slope percentage, valley curvature coefficient, elevation, clay, silt, sand, ‎roughness coefficient, vegetation and rock cover percentage, precipitation, temperature and ‎snow were determined. In the studied area, three types of valley were identified: ephemeral ‎avalanche valley, permanent avalanche valley, without avalanche valley. The enviromental ‎parameters comparison between ephemeral avalanche valley and permanent avalanche valley ‎showed that slope percentage, roughness coefficient, clay, silt, sand, vegetation and rock ‎cover percentage are significant in the valleys and also in comparison between the sections of ‎them only valley curvature coefficient was significant. In comparison between three types of ‎valleys, parameters: Azimuth, valley curvature coefficient, slope percentage, surface ‎roughness, vegetation and rock cover percentage were significant. The results of comparison ‎between sections of the three types showed valley curvature coefficient was the significant ‎parameter. The most important parameters affecting the avalanche are Azimuth and surface ‎roughness coefficient.‎