GULLY eroaion is one of the developed forms of water EROSION which redolent of surface soil destruction in the lands. Recognize of the effective factors in happence of GULLY EROSION and it’s zonation is a basic implement to manage and control this phenomenon. This study has been performed with aim of recognizing the effective factors on the GULLY EROSION making and it’s zonation in the watershed of Torood. The most important effective factor in happending GULLY EROSION such as slope, aspect, litology, land use, distance of communications network, land and canopy cover were selected as the most important factors on GULLY development and their layers were provided in GIS environment. All three gullies in the area were selected for the study. For each GULLY, three soil samples were collected from 25, 50 and 75 percent of GULLY length and three from outside of GULLY for comparison. These Samples have examined from the view of Gypsum, Organic Carbon, Salinity, Saturation Percentage, Lime, Sodiun Absorption Ratio and PH. GULLY EROSION zonation map of Torood watershed was prepared using 1:40,000 areal photos of 2001 and field measurements using GPS. The area covered by GULLY EROSION in each class of effective factors, were computed by overlaying GULLY EROSION zonation map with effective factor layers. Effective factors and their classes in related layers were weighted using Multi Class Maps method. Results demonstrated that 88 percent of gullies are located at high to very high classes of vulnerability zones. Soil analysis also indicated that salinity, gypsum and sodium absorption ratio in the gullies are higher and the amount of organic carbon is less than that of surrounded areas. But, there were no significant difference between saturation percentage, lime and pH in the gullies and surrounded areas.

Prediction of occurrence of GULLY EROSION through the use of models and output them to the hazard mapping of GULLY EROSION, most appropriate strategy for land management planning in watersheds prevent the occurrence of EROSION. in this research, the zoning of GULLY EROSION in the Quyjoq watershed Golestan province of Multilayer Perception neural network structure and the use of variables the selected suitable factors are: slope, aspect, elevation, land unit, land use, distance to river, lithology, distance to road. SPSS modeler software and MLP method were used to perform the neural network. The method of using layers in MLP method was 1-8-9. It includes 9 input layers, 8 hidden layers and 1 output or target layer. Results of the study show that 20, 30, 24, 16 and 10 percent of the region form the areas with very high, high, medium, low and very low risk of EROSION. This finding is primarily related to streams, roads and geology. The produced GULLY EROSION susceptibility maps can be helpful to make decisions for soil and water planning and management and finally sustainable development in the Quyjoq watershed.

The purpose of the present research was to study the role of morphometric, vegetation, and rain event factors on GULLY development in different stages.Research method consisted of sampling after every rainfall event of 10mm in 24-hr, during two hydrological years of 2008-09. Graduated rods were installed in different parts of the GULLY and were used to measure the morphometric characteristics and advance of the GULLY after the rain. Soil samples were taken at distances of 0, 25, 50 and 75 meters from the headcut.The results showed that the GULLY development was cavernous (a large hole) and, from its middle parts to lower layers, GULLY development was facilitated by frail and fragile layers and solubility of salts, thereby causing collapse of the GULLY roof. The results of statistical analysis showed that all factors investigated had an important role in GULLY development such that the correlation coefficient was in the confidence range between 87 to 92 percent.Also, GULLY development charts in different distances from the head-cut showed that the GULLY in stages 2 and 3 was more than stage 1.Besides, according to the results of mechanical analysis, clay content in the B and C layers were more than in A layer. Due to the clay swelling properties, it contributed to the formation and development of the GULLY. The results of this study indicated that soil physical and chemical conditions including vegetation and rainfall were effective in soil displacement and GULLY development both in length and width.

Introduction: One of the main problems in the Golestan province watersheds is the high degree of EROSION and soil degradation, so that the equilibrium between the soil process and the soil EROSION is unbalanced, and the EROSION rate increases from west to east. Among these, the GULLY EROSION and piping have the highest role. GULLY is a canal or stream with the headcut with active EROSION, sharpened slope and steep walls that results from the destruction of surface flow (usually during or after the occurrence of precipitation), dissolution movements, and small mass movements. The extent of GULLY in the eastern parts of Golestan province has caused the land degradation of arable land and landscape and has increased the conservation cost and etc. Because of connecting upstream areas of the basin to the downstream areas, GULLY has particular importance, which provides the possibility of sediment and pollutant transport, road destruction and financial losses to agricultural lands. In order to prevent and control the development of GULLY processes from a small scale to large one, it is a versatile utility to identify and extract the areas prone to GULLY EROSION. Due to the high intensity of GULLY EROSION and its increasing growth in the Gharnaveh watershed, the Garnaveh River has an unstable status and severe eroded GULLY, and in some areas it has a great depth and vertical lateral walls, as well. Therefore, in this research, the watershed of Garnaveh was selected to prepare the risk areas of GULLY EROSION. The aim of this research is to determine GULLY EROSION Hazard zoning using Frequency Ratio and Gupta & Joshi methods (GULLY Nominal Risk Factor-GNRF) in the Garnaveh watershed (Golestan province). Ultimately, the accuracy of the model has been evaluated using quality sum method and Kappa coefficient. Material and methods The study area is located in the northern part of Iran, Golestan province. The Garnaveh watershed with an area of about 78430 hectares lies between longitudes 370360 E and 414472 E, and latitudes of 4183819 N and 4155267 N (UTM Zone 40). At first, GULLY EROSION inventory map with the scale of 1: 75, 000 (dependent variable) for the Gharnaveh watershed has been prepared using multiple field surveys and satellite images. From total gullies, 70% have been selected randomly for building GULLY EROSION hazard zoning model and the remaining ones (30%) have been used to validate the provided model. In this research, seven data layers including slope percent, slope aspect, plan curvature, lithology formation, land use types, distance from rivers and distance from roads have been selected as GULLY EROSION controlling factors (covariates/ independent variables) and then they have been digitized in ArcGIS software. The amount of GULLY density of each factor class has been calculated from a combination of independent and dependent variables, and the rating of classes have done based on Frequency Ratio and GULLY Nominal Risk Factor equations. Finally, the GULLY EROSION hazard zoning map has been drawn from the summation of weighting maps in ArcGIS. In this map, the value of each pixel is calculated by summing the weights of all the factors in that pixel. The pixel values are categorized based on the natural breaks classifier into very low, low, medium, high and very high hazard zones. Then, an accuracy of zoning map has been evaluated by quality sum method and Kappa coefficient. Results and discussion The result of affecting factors classification of the gullies shows that loess deposits formation, rangeland, areas with low distance from road and rivers, northwest aspect, low slope amplitude and concave slopes contain the most susceptibility to GULLYing. The results of frequency percent comparison of gullies in hazard classes show that from all GULLY zones in the validation step of the GNRF and frequency ratio models %74. 52 and %78. 11 of zones are located in the high and very high risk classes, respectively. The result of model validation using the quality sum method and a Kappa coefficient show that the frequency ratio model is a more appropriate model for GULLY EROSION hazard zoning (with the quality sum and a Kappa coefficient of 3 and 0. 89, respectively) than the GNRF model (having the quality sum and Kappa coefficient of 1. 27 and 0. 74, respectively). Conclusion In this research, the areas susceptible to GULLY EROSION in the Gharnaveh watershed have been mapped with the frequency ratio and GNRF (for the first time) models. For this purpose, 7 affecting factors (independent variable) and 805 GULLY zones (dependent variable) were provided to measure the hazard maps of GULLY EROSION. The following results are obtained from this study.-The geology factors were identified as the most effective factors in the occurrence of GULLY EROSION in the Gharnaveh watershed.-Based on the GULLY EROSION zoning hazard map of the Gharnaveh watershed, more than 70 percent of gullies are situated in the very high and high hazard classes.-The produced GULLY EROSION hazard map is useful for planners and engineers to reorganize the areas susceptible to GULLY EROSION hazard, and offers appropriate methods for hazard reduction and management, as well.

Surface. The development of gullies causes the loss of a great amount of soil and could be considered as one of the principal causes of geo-environmental degradation. In this research FAZI model introduced for GULLY EROSION zonation in arid and semiarid area considered to calibration and validation in Kahkiloeh and Boyerahmad Province. Therefore, the ABGANDI watershed were selected by consideration of GULLY EROSION distribution in Kahkiloeh and Boyerahmad Province. In this region the maps of lithology, slope, soil, rainfall, land cover and land use were extracted and thus selected the working units. In each of the units, gullies morphometric, soil penetration condition and soil conservation percent characteristics with survey investigated. Also, determinates the quantity value of six maps model input layer include (lithology, percent of slop, soil type, annual average precipitation, land use and percent of soil conservation) was determined. Finally, GULLY EROSION mapping using overlay index, fuzzy algebraic sum, fuzzy algebra product and fuzzy gamma in GIS performed. Obtained result of different regions indicated that the fuzzy gamma model 0. 8 is the proper method to GULLY EROSION zoning in studied watershed.

Introduction Background and objectives GULLY EROSION is one of the destructive forms of soil EROSIONs that may lead to a considerable volume of soil loss. This EROSION type in addition to on-site and off-site effects has an important role in land degradation and forming in some watersheds. In this regard, due to GULLY EROSION in some provinces of Iran such as Hormozgan, Bushehr, Fars, Khorasan, Semnan, and Zanjan vast agricultural areas are under threat of GULLY EROSION. There are biological and mechanical methods that are available for controlling this type of EROSION. One of the most important issues before designing any biological or mechanical practices is knowledge about morphological characteristics of gullies and process of their development. Therefore, this study was planned to assess morphological changes and development of gullies during 1955-2016 years in Idelo watershed in Zanjan Province, Iran. . . .

Extended abstractIntroductionGULLY EROSION is a water EROSION that has a great contribution to land degradation and is known as one of the most important environmental hazards in the world and especially in Iran. In recent years, machine learning techniques and geographic information systems have been highly effective in determining areas sensitive to GULLY EROSION and have increased accuracy and speed in the evaluation and potential of GULLY EROSION and in determining effective factors on GULLY EROSION has also been effective. The loess lands of Golestan Province are more susceptible to water EROSION due to sufficient depth and almost uniform silty graining, excessive use, cultivation on sloping lands, and wrong land management so that all types of EROSION can be observed in these areas. The most common type of EROSION in these sediments is GULLY EROSION. The studied watershed is faced with the increase of dry and abandoned land, land use change, the presence of surplus livestock in the forests, and also the population increase. Therefore, this area is facing an increase in sensitivity to GULLY EROSION, and areas with the potential for GULLY EROSION should be identified and managed. Materials and methodsThe studied watershed with an area of 222,000 ha and an elevation range of 58 to 2168 m is located in the northeast of Golestan Province. The average rainfall of the area is between 224 and 736 mm. In this research, first, the location of the gullies was obtained from the General Directorate of Natural Resources and Watershed Management of Golestan Province. Then, from the total of 1127 gullies position, 70% were randomly classified as training data and 30% as validation data. To determine the effective variables in GULLY EROSION sensitivity, 14 factors were identified and in the next step, the collinearity test between the variables was performed using SPSS software. By using the indices of tolerance coefficient and variance inflation factor, if there is collinearity between the variables, they were removed from the modeling process. Considering the importance of the DEM map and its application in the preparation of various factors of the current research, a DEM was prepared using ALOS satellite images. The layers of slope and aspect are prepared by using a digital elevation model and slope and aspect functions respectively. Slope length index in SAGA GIS software, layers of distance from stream based on the map of stream, and distance from roads based on existing roads, and using the Euclidean distance function in the ArcGIS software was prepared. Stream density and road density layers were obtained based on the map of existing streams and roads in the region and using the line density function in ArcGIS. The lithology layer was extracted from the geological map of the region and the land use layer was obtained from the General Directorate of Natural Resources and Watershed Management of Golestan province. The rainfall map has been prepared using the information from 35 rain gauge stations. First, the average rainfall of 26 years was calculated for each station, and then rainfall zoning was done using the global Kriging Method (due to the lowest RMSE) in ArcGIS. The TPI layer was prepared using the DEM and using the SAGA GIS software. The HAND index is a topographic-hydrological index of the DEM of the nearest drain, representing the hydrological behavior of the watershed. To evaluate the models, the relative performance detection curve (ROC) was used for the predictive power of the models.  Results and discussionThe results showed that there is no co-linearity between the variables and therefore all the variables were used in the modeling process. The relationship between GULLY EROSION and elevation showed that lower elevations are more sensitive than higher elevations and more susceptible to GULLY EROSION near waterways. The results showed that with the increase in drainage density, the sensitivity of GULLY EROSION increases, and the possibility of GULLY EROSION increases. The results showed that the old barracks, shale, and loess have the greatest impact on the sensitivity of GULLY EROSION. The results show a decrease in the sensitivity of GULLY EROSION with a decrease in the HAND index. This result indicates that in the areas where the level of saturation in the watershed level increases, the possibility and sensitivity of GULLY EROSION increases. The results showed that among the types of land use, canals, poor pastures, and agricultural land use have the highest sensitivity to GULLY EROSION. This is even though the forest areas have the lowest sensitivity to this EROSION. The results showed that in the rainfall range of 220 to 420 mm, the possibility of GULLY EROSION has increased, and the range of 420 to 500 mm has shown the highest level of sensitivity, and with the increase of rainfall from 500 mm to above, a reduction in the sensitivity of GULLY EROSION has been encountered. One of the reasons for reducing the sensitivity of GULLY EROSION in higher rainfalls is the increase in vegetation and the creation of suitable conditions for landslides. The results showed that the depth of the valley up to 235 meters have increased the probability of GULLY EROSION, and from 235 meters above, it has decreased the probability of EROSION. The results showed that the sensitivity of GULLY EROSION increases near roads, and this case shows the effects of road construction and the aggravation of conditions for GULLY EROSION. ConclusionThis research was conducted to determine the effective factors on GULLY EROSION and zone its spatial distribution in the northeast of Golestan Province. In this study, by considering 14 important factors and using RF, ANN, and CART models, a sensitivity map of GULLY EROSION was prepared. Because the identification of GULLY EROSION-sensitive areas based on traditional methods and expert opinions do not have acceptable accuracy, it is necessary to use modern machine learning methods. The results showed that the factors of distance from the road and land use are the most important factors affecting the sensitivity of GULLY EROSION, which requires land use management as human activities. The ROC curve showed that the accuracy of the models in estimating areas with GULLY EROSION sensitivity was excellent in the test stage (ANN) and very good in the test and validation stage (RF and CART), which means the excellent performance of the models.

GULLY EROSION in one of the different types of soil EROSION by water that initiation and advancement of it can tend to the great changes on landscape, degrades the lands and deteriorates the environment. Considering the variety and rate of different factors effecting initiation and progress of GULLY EROSION which varies from place to place, recognition of the most important factors contributing in gulling that can lead to identify alternative solution for its prevention and control, Arab Gareh Haji watershed locating in Golestan province-Iran, where vast part of it is covered by loess depositions were selected as study area. In order to conduct the study remote sensing data (i.e. aerial photos data 1956 and 1967 together, with land sat ETM+ images dated 2002) using geographic information techniques were applied for Mapping and determining sequential changes of gullied area size. Characteristic of environmental factors were than analyzed to find out probable relations between them and rate of GULLY initiation and progress on loess depositions using correlation analysis method. Finally based on the results of the study, Alternative solutions were presented that seem to be effective in preventing and/or controlling GULLY EROSION in loess covered areas. Results of the study were shown that initiation and advancement of GULLY EROSION are function of mean annual precipitation, weather temperature, land slope class and aspect, lithology, source of land, soil type and its physical and chemical characteristics, vegetation type, land use and mean annual runoff depth of given area.Accordingly, it was fund out that land slope, and soil characteristics including soil depth, SAR, Ec, Na and TDS of soil are highly correlate to the rate of GULLY initiation as well as its progress (i.e. morphometeric characteristics of the gullies) thus based on the gained results, the best strategic solution for prevention and control of GULLY EROSION in the studied area and the areas with similar environmental conditions can be prevention of surface runoff concentration and land rehabilitation together with vegetal cover management ,particularly controlling over grazing by livestocks, improper road construction and cutting trees and shrubs throughout the watershed.

One of the types of water EROSION and land degradation which causes imbalance, is the GULLY EROSION phenomenon. Land degradation, a broken ecological balance of the land and landscape and risk of falling at biological resources in these areas, the study of the GULLY, is inevitable and necessary especially in the Darrehshahr Township. In this regard, GULLY 36 number were selected in Darrehshahr area in the ilam province. To this end, were identified environmental factors, Physical-Chemical Soil properties, cover and hydrological properties of gullies tested using aerial photography, the digital maps and field operations. To determine the extent effect these factors on each of the GULLY geometry characteristics using fuzzy logic and information theory, the membership function and the weights of the membership function of each of the factors was calculated. Then relationship between the independent and dependent variables was obtained by using multivariate regression. Results of statistical analysis using multiple regression (stepwise method) revealed that length of GULLY with upstream area of the GULLY, top and bottom width and cross section of the GULLY with basin elongation, deep GULLY with basin elongation and slope curvature, high of head GULLY with local slope of the GULLY and steep walls of GULLY with percentage cover have a significant relationship. So could be concluded that characteristics of geometry GULLY in the study area would be a function of the upstream, basin elongation, curvature slope, Local slope of the GULLY head and the percentage of canopy cover catchment area of GULLY.

In this study using Frequency Ratio (FR), Statistical Index (SI), Weights Of Evidence(WOF), Logistic Regression (LR), Random Forest (RF) models the probability of GULLY formation was calculated in Aytamar watershed and susceptibility maps was prepared. First the thematic maps of 13 GULLY conditioning factors including lithological formations, distance to faults, faults density, altitude, slope-length, slope angle, slope aspect, plan curvature, profile curvature, distance to roads, land use, distance to rivers, stream power index and topographic wetness index was prepared. Then landslide inventory map was combined with each GULLY conditioning factor and all models weights and parameters were calculated. Area under curve for test data was calculated as 0. 74, 0. 78, 0. 75, 0. 86 and 0. 96 for Frequency Ratio (FR), Statistical Index (SI), Weights Of Evidence(WOF), Logistic Regression (LR), Random Forest (RF) models, respectively. Random forest, Frequency Ratio and Logistic Regression have the least the area of high susceptibility zone, respectively. With respect three validation criteria multivariate methods including Random Forest and Logistic Regression had the best performance among all models.