جستجوی مقالات مرتبط با کلیدواژه « soil erosion » در نشریات گروه « جغرافیا »

Monitoring of land use changes and destruction of vegetation as one of the dominant parameters in soil erosion is one of the important issues for assessment and control in natural resource management. The Hyrcanian forests of Gilan province, over the past years, have deteriorated due to neglect and have taken on a different face. So; The purpose of this research is to reveal the changes in land use and the destruction of forest cover and its effects on soil erosion in the watershed of Ghaleroodkhan Fuman. For this purpose, the changes in land use that took place between 1371 and 1402 were extracted using Landsat images and object-oriented classification techniques and were classified (agriculture, forest, pasture, water, and residential). In the next step, by identifying the effective factors in the erosion of the area and preparing the information layers of each criterion in GIS, the standardization of the layers was done using the fuzzy membership function, the weighting of the criteria using the CRITIC method and the final modeling was done using the MARCOS multi-criteria analysis method. The study of the changes in watershed use shows that the forest cover in 1992, with an area of 222.17 square kilometers, had the largest area among the land uses, and in 2023, its area decreased to 205.03 square kilometers. Also considering the results; Residential use with an increase of 27.17 square kilometers has changed the most during the 30 years of study. According to the erosion zoning map, respectively; The area of the floor with very high and high erosion potential has increased from 18.04 and 31.05 percent in 1992 to 22.52 and 32.34 percent in 2023. According to the obtained results, it is possible to reduce the forest cover and convert it into residential areas, agricultural lands, and pastures, as well; He considered the conversion of agricultural lands to residential areas and the increase of residential and agricultural use in the boundaries and riverbeds as the most important factors involved in increasing the soil erosion potential of the basin.

Desertification in arid and semi-arid areas is an invisible and very dangerous phenomenon, and if it continues, it leads to the destruction of the land and the loss of renewable natural resources. Several factors play an effective role in the occurrence of desertification in a region, among which the phenomenon of land subsidence can be mentioned. Land subsidence is a geological process that occurs in a long-term balance and coordination between human activities and the hydrogeological environment. Today, land subsidence caused by the extraction of underground water has become a global problem, and it can even be the site of other hazards and threaten the society. The challenge of establishing a balance between groundwater consumption and land subsidence control is essential for sustainable development and curbing desertification. In order to meet their needs, including agriculture, industry and drinking, human societies depend on underground water sources and provide the required water through underground water. These conditions have become more severe in Iran due to its location in the arid and semi-arid belt, along with the improper distribution of rainfall with excessive extraction of underground water. In Iran, this phenomenon has extensive ecological, economic, social and environmental consequences due to the multiplicity, extent and complexity of the environmental and human factors that cause desertification. Hence, the precise monitoring and analysis of the intensity of desertification is of great importance for risk assessment and risk assessment. Therefore, it is necessary to know the criteria and indicators effective in the occurrence of desertification in order to achieve a model that can monitor the intensity of desertification in order to manage and plan the desert areas correctly and on principles. For this purpose, the aim of this research is to evaluate the state of desertification by IMDPA model based on two criteria of underground water and subsidence in the Rafsanjan watershed located in the northwest of Kerman province.

In this research, two criteria of underground water and subsidence rate were used as key criteria to prepare the desertification intensity map. According to the available information and the goals of this research, the criteria of underground water were scored based on electrical conductivity indicators, sodium absorption ratio, and groundwater level drop. For the subsidence criterion, the subsidence rate index was used in the year 2014-2015. In the next stage, a weight between 1 and 4 was given to each index based on its effect on desertification. The weighting is linear and equal in proportion; So that value 1 is the best and value 4 is the worst weight. Zoning of the mentioned indicators was also done by geographic information system and interpolation methods. The subsidence criterion was evaluated using the subsidence map prepared from Sentinel 1 satellite images in the year 2014-2015. In the end, the final map of the desertification situation was obtained according to the IMDPA model and based on the geometric mean of the criteria.

The average electrical conductivity measure in Rafsanjan watershed was 9351.4, which with a score of 4, is in a very severe desertification situation. Also, in terms of absorbable sodium, this watershed with an average of 12.28 and a score of 1, put it in a state of low desertification. In addition, according to the results of the groundwater quantity criterion based on the average level drop for the aquifer located in the Rafsanjan watershed, it was determined that the average drop of groundwater is about 54 cm with a score of 4, and is in a severe state of desertification. The subsidence of the aquifer located in the Rafsanjan watershed has varied from seven to less than one centimeter per year. Also, based on the average values, the average subsidence in the water year 1394-1395 in the region was in the low category with an average of -1.25 and a score of 1. Examining the areas with subsidence and the level of the drop in the underground water level showed that the drop in the underground water level can be considered as the main reason for the subsidence in the Rafsanjan aquifer. The overlap of three indicators of groundwater criteria, including: electrical conductivity, sodium absorption ratio and level drop, showed that 2.74, 59.07, 37.15 and 1.02 percent of Rafsanjan watershed are in low, medium, severe and There is a lot of desertification. Also, the overlap of the underground water and land subsidence criteria showed that the intensity of desertification is placed in three levels: low, moderate and severe, and the highest level corresponds to the moderate severity.

Rafsanjan watershed is one of the critical areas of subsidence. For this purpose, it is very important to evaluate land degradation caused by subsidence and drop in the underground water level in the Rafsanjan watershed. The results of this research confirm that according to the underground water criteria, the average electrical conductivity, absorbable sodium, and the drop in the water level of the region are in very severe, low, and severe desertification. In addition, in terms of the intensity of desertification from the point of view of water quality, the region is located in low, medium, severe and very severe classes. Finally, the intensity of desertification according to the two investigated criteria (underground water and subsidence) is placed in three levels: low, medium and severe, and the highest level is related to moderate severity. The results of this research will create a clear horizon for managers and planners of the natural resources sector, which will lead to a precise understanding of the criteria and indicators effective in the occurrence of desertification in the region. In addition, it is suggested to identify other effective factors in the region and introduce them to the desired model for accurate estimation of this phenomenon.

Soil erosion is one of the serious environmental threats that can affect the political, social and economic aspects of countries. One of the widely used experimental models for estimating the amount of soil erosion is the modified global soil erosion equation known as the RUSLE model. The purpose of this research is to analyze and zonate the amount of soil erosion and its relationship with hydrogeomorphic indicators and vegetation cover of Khiavchai Meshkinshahr watershed in Ardabil province. RUSLE model factors include rain erosion (R), soil erodibility (K), topography (LS), vegetation (C) and protection operations (P). respectively, by using rainfall data, soil texture layer, digital model of height and land use were prepared in the environment of geographic information system (GIS) and after overlapping the layers, the amount of annual soil erosion between 0 and 150.54 tons per hectare per year in The area level was estimated. In the next step, the hydrogeomorphic and vegetation indices that are effective in soil erosion include topographic moisture index (TWI), waterway capacity index (SPI), domain curvature index (Curvatore), section curvature index (Profil Curvatore), surface curvature index (Plan) Curvatore) and Normalized Vegetation Index (NDVI) were created in ArcMap environment and zoning maps were prepared. The results of this research also showed that the topography factor with a correlation coefficient of 0.92% had the greatest impact on the estimation of annual soil erosion by the RUSLE model. In another study, the relationship between hydrogeomorphic indices and vegetation cover with annual soil erosion rate was conducted, and the results showed that normal vegetation cover indices and cross-sectional curvature were the most and least effective with correlation coefficients of 0.57 and 0.05, respectively, compared to other indices.The results of this research confirm the possibility of combining the effective indicators of hydrogeomorphic and vegetation on erosion, as well as the possibility of using other effective indicators and the capabilities of RS and GIS to quantitatively estimate the amounts of soil erosion.

Water soil erosion is one of the most common types of soil degradation, which has very destructive effects on the environment and human life. This phenomenon reduces the quality of the soil in the site and may cause sedimentation problems in the downstream or reservoirs. The severity of soil erosion is usually estimated using different models. The Revised Universal Soil Loss Equation (RUSLE) is the most common soil erosion model due to its simplicity, less need for data, and adaptability to different environmental conditions. Studies around the world show that this experimental model is very efficient for estimating annual soil losses at the watershed scale. Sediment Delivery Ratio (SDR) is used to estimate the rate of sediment yield based on the soil erosion rate obtained from RUSLE. Dizgaran watershed, located on the border of Kurdistan and Kermanshah provinces, western Iran, is one of the mountainous areas of the country and has rough topography, vegetation cover, and weather conditions that make it prone to severe soil erosion. This research aims to estimate the annual average rate of soil erosion and sediment yield in the Dizgaran watershed and also to investigate the correlation between different RUSLE factors and the erosion rate to better understand the effect of each factor on the erosion rate. In this research, the rainfall-runoff erosivity (R) factor was created using the WTLS linear regression method based on the Digital Elevation Model (DEM). According to the results of the RUSLE/SDR model, the average rate of soil erosion was 45.09 tons per hectare per year and the average rate of sediment production was 19.42 tons per hectare per year in the watershed. 1.3% and 4.66% of the area of the area were placed in very low and low erosion classes, respectively. 16.18% of the area was in the moderate erosion class, and 36.18% and 41.68% of the area were in the severe and very severe erosion classes, respectively. Also, the results indicate that the two factors of topography (with a correlation coefficient of 79%) and cover and management (with a correlation coefficient of 47%) have the highest correlation with the soil erosion rate, respectively, and therefore play the most important role in changing the erosion rate in the watershed. The results of this research show that this watershed is involved in severe erosion, as can be seen from the presence of different forms of soil erosion in the field investigation. The results of this research can be used to carry out management measures to reduce the rate of soil erosion in the points with a high rate of erosion and to protect and manage the Dizgaran watershed.

In recent years, the mutual impact of land use change and soil erosion has become a major environmental concern. Therefore, this study tried to investigate the changes in different land uses and evaluate the impacts of land use changes on soil erosion in Givi city. To achieve the goals of the research, first, a land use map was prepared using the object-oriented method for the two periods of 2000 and 2021. Then, according to the natural and human conditions of the area, other effective factors for erosion in the area were identified and the information layers of each of the criteria were prepared by the geographic information system. Evaluation and standardization of layers were done using the fuzzy membership function and weighting of the criteria was done using the CRITIC method. The final analysis and modeling were done using the MABAC method as one of the Multi-Criteria Decision-Making (MCDM) methods. The results showed that the largest area in 2000 is related to good and medium pastures, recording 313.172 and 283.144 square kilometers, respectively. In 2021, the biggest areas are related to poor pastures and barren lands, with 335.077 and 329.815 square kilometers, respectively. According to the 2000 erosion zoning map, 16.34% and 20.36% of the city and according to the 2021 erosion zoning, 22.92% and 25.58% of the city’s area are in very high and high erosions, respectively. Decreasing good and average pastures and lands with dense vegetation and turning them into agricultural areas, poor pastures, and man-made and barren lands have had the greatest impact on soil erosion.

Soil is the bedrock of life and economic and social activities, biological and biological diversity. Lack of statistics and information on soil erosion and sediment production in many catchments of the country necessitate the application of appropriate methods and models for estimating the severity of soil erosion and sedimentation. In this study, using the BLM Erosion Estimation Model and ElectRE-1 Multi-Criteria Decision Making Method, the erosion rate in the Romeshgan basin has been investigated and the erosion intensity and zoning map has been prepared. Results of applying ELECTRE-1 model show that topographic factor (slope) with weight of 0.5578 is more effective than other factors in basin erodibility and plays the main role. Also based on this model, sub-basin 1 in the north of the basin had the highest vulnerability to erosion and then sub-basin 2, 4 and 3, respectively. Using the BLM model, it was found that the low erosion class in the Romshgan catchment covers the most extent and then there are high, very high, moderate and minor erosional classes. In general, the area has moderate erodibility. The overlap of the layers indicated that the maximum erosion intensity was in the slopes and mountain units, which included new and old alluvial deposits and cone deposits, marl, lime, siltstone, sandstone, conglomerate and gypsum. Also, rainfed agriculture units have the highest intensity and forest and pasture units have the least amount of erosion. In terms of slope factor, lands with slope of 8 to 30 percent have the highest degree of erosion.

AbstractSoil erosion is one of the most important problems in the watersheds of Iran, which causes the loss of thousands of tons of arable soil every year. The aim of the present study is to zoning the risk of soil erosion in Givi Chay watershed (northwestern Iran). In this study, first, the effective factors for erosion in the region were identified and then the information layers of each criterion were prepared in Geographic Information System (GIS). Valuation and standardization of layers was done using fuzzy membership function and criteria weighting, using critic method. Final analysis and modeling was performed using the Multi-Attributive Border Approximation Area Comparison (MABAC) method as one of the Multi-Criteria Decision Making (MCDM) methods. According to the results of the study, slope, land use, soil and lithology had the highest weight coefficient, respectively. Also, the results of the study showed; 283.89 and 414.93 km-square of the area, respectively, has a very high and high risk potential, and very high-risk and high-risk areas in unstable and erodible formations, agricultural uses and gardens and slopes of 25-40 % are located. It can be said that the results of this study indicate the high potential of the study basin in terms of erosion occurrence and it is necessary to control erosion and conservation measures on the agenda of experts and land managers. In addition, the results of validation of the results showed that the use of MABAC method has a high relative accuracy for studying the risk of erosion.

Soil erosion is one of the main factors of land degradation and desertification in large areas of the earth's surface, which is the result of the interaction of human and natural factors causing the destruction of natural ecosystems such as rangeland, forests, and agricultural ecosystems. Factors such as topographical settings, land use and land cover change, intensity of rainfall, soil properties, and wind can also be accelerated by human activities of intensive agriculture, deforestation, and tillage on steep slopes. Many models have been suggested for estimating water erosion such as USLE, RUSLE, WEEP, and EPM.  According to previous studies, the global model of soil erosion has been used in the zoning of areas with high erosion risk, but very few studies have used the USPED model, which unlike the RUSLE model that only identifies the erosion areas, this model identifies also the amount of sediment. In a study conducted by Zakerinejad and Maerker, 2015, they assessed and zoned water erosion in the Mezayjan watershed in Fars province by combining the USPED model and the Strean Power Index (SPI). The results indicated the high capability of the proposed model. It is also used to identify high erosion risk areas. The Khasuye watershed is one of the sub-watersheds located in the south of the country and in the territory of Fars province, which is affected by the severe types of water erosion leading to the loss of surface fertile soil, filling of reservoirs of dams and the reduction of water quality. Therefore, planners can consider the preparation of the potential map of the rate of erosion and sedimentation in the identification of susceptible areas in order to prioritize the implementation of soil protection and watershed management operations.

The parameters of the USPED model were estimated using different data sources by ArcGIS 10.8. The rainfall erosivity factor (R value) was estimated from the annual rainfall data of six meteorological stations located throughout the study area. The soil erodibility factor (K value) was derived from the soil samples collected from our study area. The topographic factor was calculated by analyzing a digital elevation model (DEM) with a spatial resolution of 12 m from TanDEM-X. The crop factor (C) weas derived from Sentinel-2 satellite images and conservation practice factor (P) was considered 1 because of no special soil practice in the study area. Since the spatial resolution of the applied factor maps is different, it requires resampling of the factor maps. So, in this study, the nearest neighbor re-sample sub-tool of the data management toolbox in the ArcGIS platform was used.

The study used the GIS–USPED interface model for analyzing the spatial distribution of water erosion in Khasoue watershed in Fars province. Also, according to the classification result tables of the erosion and sedimentation model of the Khosoye watershed, about 39% of the studied area is in the low and insignificant erosion class, which is mostly in the central and low slope areas of the basin, and about 24% corresponds to the low and very low sedimentation class.  It is possible that these areas are better next to areas with low erosion and low areas with a higher slope of the basin (Table 2). It should be noted that this interval is due to the change of vegetation and physiographic factors and human activities. The lowest rate of erosion is in the center of the basin, and the highest rate of erosion is in the western and northern steep areas of the studied basin. The final results obtained from the application of the USPED erosion-sedimentation model in the studied basin showed that the amount of erosion and sedimentation varies from 0.1 to more than 30 tons per hectare per year, that signify erosion areas with a negative number and sedimentation areas with a positive number (without sign) area.

Among the several fundamental approaches for calculating soil erosion rate, the USPED model is a critical tool for conducting improved conservation planning. The implementation of this erosion model can help to identify the places that are affected by erosion, especially the inaccessible areas, and by identifying these places, the necessary management can be applied to control and reduce soil erosion in these areas.

Soil erosion is one of the most significant environmental problems in the world; it is a threat to food security, the environment, natural resources and causes socio-economic problems. In this regard, the importance of estimating the amount of erosion to adopt appropriate management methods in different areas has been established. Among the existing models of soil erosion and sedimentation, models that can predict soil erosion and sediment performance can be useful and widely used. In this regard, the IntErO model, which is a graphical computer method based on the EPM erosion potential method embedded in its algorithm, can be applied.

This study aimed to estimate the severity of soil erosion and runoff using the comprehensive, rapid, and effective IntEro model in the Kahouristan watershed. After collecting basic information, 26 input variables were extracted and calculated using topographic maps, geology, geology, land use, and climate data. In this regard, to estimate the inputs of the IntErO model, at first, the physiographic and topographic features of the Kahouristan watershed were extracted using a 1: 25000 digital map and the boundary of the information range. Also, the lowest and highest elevation points, the lowest value of the alignment line, and the equal distance between the alignment lines were determined. Geological and land use characteristics of the region Geological and land use maps were used. The maximum probable precipitation (PMP) method was used to achieve the height of torrential rainfall. Finally, after preparing all the inputs of the IntErO model, the computational data for the Kahouristan watershed were entered into the graphical environment of the software, and the components related to erosion and sediment as well as the maximum outflow from the Kahouristan watershed were estimated using the model.

The results showed that the drainage density was 1.35 in the Kahouristan watershed using the IntEro model, and the infiltration coefficient of the watershed and the vegetation cover coefficient were 0.67 and 0.84, respectively. Also, the coefficient of water retention in the studied area was found to be 0.91 and the potential of water flow during flash floods was found to be 6597.04. On the other hand, the erosion energy coefficient in the study area was found to be 102.12 using the Intro model, and the total erosion in the mentioned area was equal to 3456636.72, and the erosion coefficient of the Kahouristan watershed was 0.918. The amount of real soil erosion and special real soil erosion in the studied watershed is 631152.53 m3/year and 150.14 m3/Km2.year, respectively. The re-sedimentation coefficient of sediments due to erosion was 0.183.   

The results of the current research showed that the permeability coefficient of the study watershed was 0.67, which according to the value of the vegetation coefficient which was 0.84, it can be said that the appropriate cover in the area has caused the permeability. However, the drainage density in the study area was 1.35, which indicates the resistance of the soil in the area against erosion.
Also, examining the results shows that the maximum output flow estimated by the mentioned model for the study watershed is about 1778 m3/s. Examining the maximum outflow with the 21-year statistics of the Kahouristan hydrometric station shows that the maximum outflow from the study watershed is about 1635 m3/s, which indicates the appropriate performance of the model in estimating the maximum outflow from the study watershed. Based on this, it is recommended to use this model in estimating the output flow and other characteristics in the study watershed. Another hand, the results showed the predominance of rill erosion in the area and the transfer of sediments to the outlet of the basin. According to the model results, estimating the amount of erosion in the study area was not accurate enough. However, estimating the maximum output current from the basin based on the available statistics indicated good results; in other words, the use of this model is recommended in estimating the output current and other characteristics, but in areas having similarities with Kahouristan watershed conditions, heavy and short rainfalls for estimating the amount of erosion is not recommended due to its inability to provide appropriate results. Finally, it is suggested that other models of erosion and sediment assessment for the Kahouristan watershed and other watersheds with similar conditions in this respect be studied and compared with the IntEro model as well.

Nowadays, land use change increasingly causes environmental problems and usually, in the first step, affects the soil properties and causes a decrease in the quality and an increase in the destruction, and erosion of the soil. Land use is defined as the sum of management and planning activities and inputs that humans do in a specific type of land cover (Ellis, 2021). The improper use and management of land resources, which has led to soil degradation, can have a great impact on the development of sustainable agriculture and is recognized as a serious global challenge for food security and ecosystem sustainability (Ebabu et al., 2020). Changing the use of forest lands and pastures for agriculture purposes has become one of the significant concerns in the world causing environmental degradation and climate change. Studying the effect of land use on soil properties provides the possibility of identifying sustainable management and preventing future soil degradation. The knowledge about the effect of land use change on soil properties, as one of the most essential components in sustainable agriculture in Jiroft, which is considered one of the important agricultural regions of Iran, is very limited. Therefore, this study was carried out to investigate the effect of different land use on some physical and chemical properties of the soil and to prepare distribution maps of these properties in the Konarsandal region of Jiroft.

In this research, the effect of the type of land use was studied in a part of the lands of Jiroft Plain (around the historical hills of Konarandal). For this purpose, by sampling surface soil in four types of land use, including agricultural land, abandoned agricultural land, date garden, and natural forest, some of the physical and chemical properties of soil including the percentage of sand, silt, and clay, electrical conductivity, pH, absorption ratio of sodium, calcium carbonate, organic carbon, bulk density, liquid limit (LL), plastic limit (PL), specific surface area (SSA), cation exchange capacity (CEC) and hygroscopic water content (HWC) were studied, and the spatial distribution maps of some parameters were obtained. In terms of topography, the studied area has a relatively uniform slope and its physiographic unit is in the form of alluvial plains. The dominant forest land cover in this area mainly includes Prosopis and Tamarix aphylla and the dominant vegetation cover of the abandoned agricultural land includes the Salsola soda. Also wheat and melon are mainly cultivated in the agricultural lands. According to the announcement of the residents and owners in the studied area, the history of agricultural lands (date garden and arable land) is more than 20 years and the irrigation system of these lands is in the form of flooding. 26 samples of the surface soil (0 to 20 cm) were taken from each land use (104 sampling points). For statistical analysis of the data, SAS9.1 was used and averages were compared with Duncan’s test (p<0.05). Correlation between the data was done using SPSS16 and Variowin2.2 was used to calculate and draw the Variogram maps.

The results showed that the type of land use changed all the studied parameters. The highest percentage of clay (46%) was observed in the abandoned agricultural land. Changes in the percentage of sand, silt and clay in different land uses could be caused by the type of management conducted on the process of soil particle loss. With changes in soil textural characteristics (sand, silt, and clay), the SSA, LL, PL, HWC, and CEC had also changed. The kriging maps also showed the uniform distribution of these features well. The soil quality in the abandoned agricultural land was not very suitable compared to other land uses. The amounts of EC and organic carbon in this land use were about 2 times more and about 20% less than agricultural lands, respectively. The coefficient of variation of particle size distribution (sand, silt and clay) and the organic carbon among the studied soil variables in the region were relatively high, which could be attributed to the land use changes, differences in plowing, management operations and surface soil erosions.

Differences in the separation of soil particles in different land uses can cause differences in the distribution size of soil particles and even soil texture (Tallen and Yerima, 2018). The result that was also observed in this study. Other properties of the soil such as LL, PL, SSA, CEC and HWC were also different in the studied land uses which could be related by positive and significant correlation (r>0.7**) with clay content. The abandonment of agricultural lands had caused low quality and fertility of soil in this land use; this issue could be due to high evaporation in this area which can increase salinity, and also because of little vegetation in this area which decreased the amount of organic matter of soil. It is suggested that in order to preserve the soil properties of the abandoned agricultural lands, if the conditions in terms of water supplement are available, this land use should be restored as agricultural land, or according to the amount of seasonal precipitation in this region, these lands be cultivated by drought-resistant plants such as Tamarix aphylla.

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 process of soil erosion and its intensification due to improper management and exploitation causes a lot of damage to the basins of semi-arid and arid regions of Iran every year. Among the various methods of soil erosion studies, morphometric parameter analysis is a cheap, fast and efficient method for soil erosion study.The semi-arid basin of mianrahan is at risk of soil erosion due to the outcrop of different formations, diversity of geomorphological conditions, rugged topography and the prevalence of agricultural and livestock livelihoods.Therefore, zoning of soil erosion potential of this basin is necessary for scientific management and sustainable development.The aim of the present study is to zoning the soil erosion potential in sub-basins, intermediate basins. In this research, WSA and averaging methods are used, which are based on the calculation and ranking of morphometric parameters. The results showed that according to WSA and averaging methods, 47.49% and 65.53% of the area of the mianrahan basin are located in areas with high soil erosion potential and need to implement protection plans.The WSA method is more efficient for soil erosion potential zoning studies due to the use of morphometric, linear and uneven morphometric parameters and the calculation of the correlation coefficient between them.The southern, northern and central sub-basins of the mianrahan basin have low, medium and high potential for soil erosion, respectively. The amount of soil erosion potential in the sub-basins of the mianrahan basin is affected by the roughness and shape of the sub-basins and the parameters related to the shape of the basin and the unevenness of the basin have the greatest impact on the soil erosion potential of the sub-basins.

Soil erosion and production of sediment load in the watershed has become one of the important environmental problems today, and therefore, Preventing its occurrence is one of the most important factors for protecting natural resources. Increasing soil loss in watersheds Watershed is a continuous challenge that is caused by the increase in population and the pressure on natural resources and unsustainable cultivation in soils and lands Slope causes a decrease in production in the land (Ahmad Abadi, 2017). One of the most important factors of soil destruction and fertility reduction is soil erosion, which is increasing nowadays and leads to Loss of good agricultural soil.

which is called the RUSLE relationship and is a function of six factors as follows:A=R*K*L*S*C*P (2) A: average soil loss per surface unit (tons per hectare per year) R: rain erosion factor, K: soil erodibility factor, L: slope length, S: slope degree, C: management factor Vegetation, P: Factor of soil protection measures This model is still the best available erosion prediction model that can be easily applied at the local level area to be used. In this method, using the DEM map of the basin in the GIS environment and having the factors RKLSCP factors, raster maps are prepared and finally, with the correlation of these maps, the soil erosion map is obtained. In the GIS environment, rain erosibility index maps (R), soil erodibility index (K), slope length index (L), Slope degree index (S) is prepared. Also, Landsat satellite bands 1 and 7 are used to prepare the NDVI map, Vegetation index (C) is prepared. - Third step: modified PSIAC

In 1968, the American Water Management Committee presented the Psiak method qualitatively. This model is based on the sum of 9 factors (X1-9) Effective on erosion, it gives the sedimentation of the basin, according to which the erosion class of the basin can be determined. In the year 1982 Johnson and Wegbhart took these factors numerically (Y1-9) so that the model takes on a quantitative state and its accuracy to increase Factors affecting erosion in this model include: lithology, soil, climate, runoff, topography, vegetation, Land use, the current state of erosion and erosion of Khanhai River. - Fourth step: preparing the necessary invoices:As stated, the revised global equation of soil erosion is an empirical model of soil erosion estimation based on the global equation. Soil erosion is designed. This model, in addition to being able to use data such as the physical characteristics of the basin and Meteorological stations can estimate the amount of soil erosion, it also enables the spatial distribution of soil erosion.

In this regard, in order to calculate the average loss of soil per surface unit (tons per hectare per year), the following factors were examined and calculated and prepared:- Slope degree: S=L* H/A S =541781.94*20/144538670=0.074 S=0.074*100=7.4 - Slope length:Basin slope length 16.03 square kilometers were calculated. Then, the erosive factors of precipitation, soil erodibility, slope length, slope degree, vegetation cover and protective measures were calculated and put in relation to the global equation as follows:R=8.86*0.376*0.72*7.17*1 R=17.197 Also, 3 factors involved in the modified Psiak model were calculated as follows and placed in the relevant section as follows:Q = 0253e^(0/036R) Q = 0.253*〖2.718〗^2.641 0.253×14.02=3.54

In this research, by preparing different layers of information, the state of sediment erosion and the amount of sediment production were determined. According Based on the amount of sediment production calculated and comparing this number with the sediment determination table, it can be said that the basin In terms of sedimentation and erosion, Kal Ismail Dara is in Class I and among the areas with very low intensity of sedimentation. The studied basin has a maximum height of 2000 meters and a minimum height of 1320 meters and in terms of topography (82.38) percent of the region includes, as well as the mountainous region with an area of 25.43 square kilometers, 17.61 percent of the basin includes In this research, using the Revised Universal Equation of Soil Erosion (RUSLE) (sediment erosion rate in the basin) 17.197 tons per hectare per year was obtained in Kal Ismail Valley, and other researchers used the same model for basins.They have calculated different figures. So that Artman et al. (2011) in Navroud, the rate of sediment erosionSediment erosion is 0-100 tons per hectare per year, Mousavi (2015) (in Shahroud-Miami, Mohammadi et al.) (2016) Taaler, Mahmoudi and Naqshbandi (2019) (in Gavshan dam, Arman et al.(2015) in TengSarkh dam, Mozbani et al.( 2021) In Sikan, the amount of sediment erosion was calculated as 2.31-68.185, 0-92.01, 35.2 and 62.17 tons per hectare respectively.Other researchers have also provided different figures for different basins using the PSIAC method. Rostaminia and Safarlaki (2017) In the Cham Gardalan basin, Eylamra 9.6, Alipour et al. (2016) in the Iver basin, 2.95 and Divasalari et al. (2013) in Solqan Qom, Nasiri et al. (2021) in Bakhtar, Qochan and Ghafari et al. (2015) in Cannes, the amount of sediment erosion They calculated 19.85, 4.5-84.2, 4.6-4.17 and 72.78 tons per hectare respectively. The basin of Kal Ismail Dara has an elongated shape

Investigating and measuring the amount of rill erosion at ground level is one of the sensitive and time consuming tasks in erosion management. The aim was to measure erosion using image analysis in the southwest of Kermanshah. Images of 12 erosion events were taken on different days. Photos were taken in ten-meter increments, magnified and scaled through software. The width and depth of the rills on the ground were measured with a caliper and on the image with the help of software. In this study, a new method was introduced to calculate the depth of erosion. Erosion events were recorded using a full-frame camera with a 100mm and 125mm macro lens. In addition to the two-dimensional data, the wall shadow of the rills was used to measure the depth of erosion. The dimensions of the rills were calculated by direct and indirect measurements, and the obtained data were analyzed. The results showed that the error between the direct and indirect values of the dimensions of the rills is in the range of 5%. The measured data from the recorded erosive images showed that this method has good accuracy in determining the volume. The accuracy and speed of the rill dimensions were measured. In the process of measuring the dimensions of rills erosion, it is generally assumed that there is a real or accurate value, although this exact value may never be revealed; But based on the least time and resources available, we tried to find this ideal value within the ability of the method and tools. The method used during the measurements may have slightly different results. No real or exact value, how do you now report your findings for the best estimate? The most common way is to provide a range of near-realistic data. The closer the measured data on the image (rills erosion dimensions) to the actual data or the accepted value, the more measurement error it provides. This provides the relative accuracy of the measurement. The degree of consistency among independent measurements is the same quantity (here width, rills depth) that results in reliability and reproducibility; Shows measurement accuracy. An ideal or real value is needed to accurately measure the dimensions of the rills on the images. To do this, the field dimensions of the rills were measured three times simultaneously with imaging (February 6, 2017 and May 2, 2016) with calipers and rulers (direct and real data); The same rills erosion was then imaged. Using the image analysis algorithm in the software, measurements were made on the same rills (indirect data). It was assumed that the ideal or real data is the same as the field data; From it for the correctness of the results obtained; used. Because there is no theoretical data for furrow erosion facies, it is assumed that even if the true value is not revealed, the same available field values can be trusted. In this regard, reference data is not available for either the actual value or the measured value to be compared, with both measured values being equally accurate. Therefore, there is no reason for the former to be superior to the latter and vice versa. Uncertainty is an estimate that was considered for the accuracy and precision of measurements.The accuracy of the data is measured by the proximity of the data extracted from the rills erosion event image to a real value. The distance between the calculated error value and the measured value showed that the method used in this study is reliable. Accordingly, the data of other images of erosive events were analyzed with reference to the small amount of measurement error between the actual data values and the measured data.According to the characteristics of the rills in the other images, the results showed that the width of the rills was between 23.7 to 141.26 mm and their depth was between 19.39 to 58.99 mm and their length varied from 6236 to 91755 mm. The width and depth of the rills are suitable indicators to evaluate the development of the rills. In fact, it was used to evaluate the use of field images to measure the properties of rills, auxiliary data, and the position of the sun and amplitude at the time of shooting. With the arrival of these auxiliary factors in the extraction of rills depth data; The distance between the actual data and the data measured on the image minimized their sharpness. Among the rills erosion characteristics, measuring the width and length of the rills was easier than the depth of the rills. Because two-dimensional sizes can be easily measured on image pixels. More than 2450 transects in the width and length of the rills were drawn to calculate the width, shadow length of the rills wall and the length of the rills, from data that were taken three times at the same time as imaging (February 4, 2017 and May 2, 2016) with calipers and rulers. Were measured (direct and real data) used to control indirect data. By comparing the results of this type of measurement with direct measurement of the same data, the amount of measurement error was determined; The results of direct and indirect measurements show that the extracted data of two-dimensional images are suitable for measuring object erosion.To measure the characteristics of furrow erosion in traditional methods, rulers, chains, filling furrows with soil and other artificial materials are still used, but they do not have the ability to study changes and spatial distribution of furrows, but in this method, which is used in the erosion range It was possible to determine the morphometric parameters of the furrow, which in traditional methods only allows the calculation of the volume of lost soil. In this study, it was found that measuring through ground photographs and analyzing them not only increases the speed and accuracy but also Provides spatial distribution, in addition to estimating the extent of spatial damage of soil erosion.

Soil erosion is one of the environmental problems that pose a threat to natural resources, agriculture and the environment. Quantitative assessment of erosion and sediment using erosion and sediment estimation models is one of the solutions through which erosion and sediment can be controlled to some extent and its amount minimized. In the present study, the aim is to predict the annual soil loss potential and sediment load. To predict these cases, the Revised Universal Soil Loss Equation (RUSLE) has been used in the context of the GIS. The amount of annual rainfall erosivity factor was calculated using 22-year monthly rainfall data at 18 stations around the basin. Its spatial variations were then estimated using conventional kriging. Soil erodibility index was obtained from soil map, which was prepared using field survey and remote sensing data. The topographic factor was extracted from the digital elevation model with a spatial resolution of 30 m. The annual vegetation factor was also estimated from remote sensing data. Since soil protection operations are insignificant in the study basin, the amount of soil protection factor was considered 1 throughout Basin. In this study, the mean values ​​of R, K, LS, C and P factors were equal to 264 MJ mm ha-1h-1y-1, 0.35 Mg ha h ha-1MJ-1mm-1, 2.00, 0.51 and 1. The average annual sediment yield in the study basin was estimated to be 16.137 th-1y-1, which was close to the value obtained from the sediment measuring station of the basin outlet (16.58 tons per hectare per year). The results of the erosion map in this model show that most erosion is located in the western and middle part of the basin. Because this region is composed of unstable formations and prone to erosion. The steep slope of the region, in addition to rainfall and land use change in this area, has faced many areas with soil erosion crisis. According to the results, the largest area of ​​the basin is related to the very low, low and medium erosion class, which is generally distributed throughout the basin, and the lowest basin area is in the high to very high erosion class (20%). Due to the fact that 20% of the study basin is in the high to very high erosion class, the need for protection measures in these areas is mandatory. The results of this study also showed that LS factor with a correlation coefficient of 0.81 had the greatest effect on estimating annual soil erosion by RUSLE model. This study proved the effectiveness of RS and GIS for quantitative estimation of soil erosion amounts, sediment yield and also erosion management.

Evaluation and zoning of soil erosion using models that are more accurate, helps to implement conservation activities and control soil erosion within the watershed and reduce the amount of sediment outside it. The aim of this study was to zoning the soil erosion intensity of Baladeh watershed using RUSLE and ICONA models and toa investigate their accuracy with observations and terrestrial reality values. RUSLE model factors including rainfall erosion (R), soil erodibility (K), topography (LS), vegetation (C) and conservation operations (P) were calculated from rainfall data, soil map, digital elevation model and remote sensing techniques, respectively. In ICONA model, soil erodibility map was obtained by combining two layers of slope and rock surfaces. Then, in order to prepare soil conservation layer, vegetation index and land use layers of the area were overlapped and by combining erosion and soil conservation layers, erosion zoning map was prepared with this model. The accuracy of these models was evaluated using statistical indices and BLM method, all of which were obtained during field observations. For this purpose, a map with 2500 points was prepared as regular networking for sampling the maps obtained from the models and accordingly, RMSE statistics (root mean squares error), MAE (mean absolute error), MSE (mean squares error) and NSEC (Nash-Sutcliffe Model Efficiency Coefficient) were calculated. The results of the mentioned statistical indices and the errors of the models shows that the mentioned models are not sufficient in baladeh watershed, but the efficiency and degree of adaptation of the erosion classes of ICONA model with BLM output as reference map is higher, because the amount of RMSE, MAE and MSE is lower and NSEC is closer to number one.

In this study, in order to identify the spatial distribution of soil erosion and sediment production in Sarab Sikan basin, the RUSLE model, GIS and remote sensing technology are used. First, using meteorological data, soil and digital elevation model with a size of 10 meters, each of the factors of erosion erosivity (R), erodibility (K), slope and slope length (LS) and soil protection (P) in the Arc GIS was calculated in Arc GIS. Sentine2 satellite sensor was also used to extract and prepare the vegetation factor of the basin (C) in ENVI 5.3 software environment. Finally, by combining these factors, the amount of basin erosion was calculated and the amount of sediment produced in the basin was obtained by different methods of sediment delivery ratio (SDR). The results showed that the amount of erosion in the basin is varies from 0.003 to 248.4 t ha-1y-1 and the average erosion in the basin is 22.3 t ha-1y-1. Among the model factors, LS factor with a correlation coefficient of R2 = 0.92 showed the highest share in soil erosion. Also, the SDR ratio was calculated by different methods between 0.12 and 0.36, which after combining with the erosion map, the sediment yield of the basin was estimated. The average sediment yield by Boise method is 2.8 t ha-1y-1, which is closer to the amount of station sediment with an average of 1.65 t ha-1y-1 compared to other methods.

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.

Depth to wet front is generally considered as the amount of water which penetrates into soil and wets the internal soil layer. This is an important variable especially in applications such as runoff generation and sediment yield estimation. This variable in some cases is used as a hydrological science in the form of a proxy for infiltration as an important factor in soil erosion processes. The importance and necessity of this research is estimating the performance of suspended sediment by adding the wetting depth variable to the regional model. The aim of this study was to investigate the effect of wetting depth on runoff and sediment production capacity by using the modified Williams equation.

In this field study, a rain simulator equipped with drip systems installed on a test site on a mountain slope to produce rainfall with intensities of 45 and 60 mm per hour on three slopes of 10, 20 and 30% was used with three replications. Adjacent to the experimental plots, soil surface depth was used to determine the physical and chemical properties of the soil, including soil texture, lime percentage, organic matter, initial moisture and aggregate stability. After setting the artificial sprinkler on the experimental plot, runoff and sediment obtained from each plot were collected in special bottles at 10-minute intervals and transferred to the laboratory. Then the amount of sediment produced at the end of each precipitation was weighed and calculated for each plot. Then, to measure the wetting depth using thin tissue rods, the wetting depth was measured every 10 minutes in diameter with 3 repetitions inside the plot. Explanation coefficient (R2) and Nash-Sutcliffe return (Nse) were used as sediment yield criteria for the model.

According to the results obtained in the study area and the efficiency coefficient, before adding the wetting depth parameter, the effect of precipitation intensity on sediment indicates a significant difference. The Nash coefficients at intensities of 45 and 60 mm/h are 0.84 and 0.63%, respectively, while the Nash coefficient for the combined intensities (total) of 45- and 60 mm/h is 0.55. Due to the low Nash coefficient in the Williams equation, for investigating the wetting depth on the amount of sediment, the Williams equation was modified. Based on the results in the study area, the relationship between wetting depth and the amount of suspended sediment in the mentioned intensities and slopes through the equation of Qs=(qe×qpe)0/32×S0/28×1/17dp×DA2/89 was obtained. Sediment performance has a non-linear and inverse relationship with wetting depth at the desired intensities and slopes, and also with the parameters of slope, runoff volume, runoff peak discharge and area. The results showed that the extent that increasing the slope, runoff, runoff peak and area leads to increasing the amount of sediment, and increasing the wetting depth reduces the amount of suspended sediment. The calibration and validation results of estimating the amount of suspended sediment in the developed model showed the value of Nse= 0.81; R2 = 0.81.

This study investigated the effect of wetting depth on runoff and sediment production capacity in the field at slopes of 10, 20 and 30% with rainfall intensities of 45 and 60 mm/h using the modified Williams equation. In the present case without considering the wetting depth variable, the results showed that at intensities of 45 and 60 mm/h, the amount of sediment and runoff increases by increasing the slope. This is because the shear energy poured on the soil by raindrops has produced runoff and sediment. But by combining rainfall intensities of 45 and 60 mm per hour, the amount of Nash coefficient decreased. One of the reasons for this is the increase in the diameter of raindrops and also the increase in the number of droplets that hit the soil surface. Although increasing the intensity of rainfall in most soils increases sediment by increasing runoff, it can sometimes reduce sediment efficiency by reducing sediment due to the spatial homogeneity of the slope of the soil surface layer. Addition of slope and wetting depth parameter, which is due to the amount of infiltration that moistens the soil around the bottom layers, is one of the factors that affect the production of sediment. The results of evaluating the efficiency of the regional model showed that the equation obtained for the region fits well with the observational data to the extent that the coefficient of explanation of fitted lines on the data increased by adding the wetting depth variable. There is an inverse exponential relationship between the amount of leached sediment and the wetting depth. Performance coefficient indices such as sedimentation coefficient and explanation coefficient, as two of the most widely used indicators to evaluate the results in the simulation of the amount of sediment, showed the value of Nse = 0.88 and R2 = 0.88. The results of estimating the amount of suspended sediment in the calibration (Nse = 0.81; R2 = 0.81) and validation (Nse = 0.81; R2 = 0.81) stages were very suitable for the study area.