فصلنامه پژوهش های فرسایش محیطی
سال هشتم شماره 3 (پیاپی 31، پاییز 1397)

Extended abstract Soil erosion is a major environmental threat worldwide. This three-stage process including detachment, transportation and sedimentation of soil particle by runoff affects natural and agricultural areas of Iran. Soil erosion has many off-site and on-site effects such as sediment deposition in the lake of dam and channels, transportation of nutrients and contaminants including phosphorous, pesticides, heavy metals, pathogens and radionuclides (Horowitz, 2008). Therefore, understanding spatial variations of sediment sources can be useful for managing the supply of sediment and contaminants in river systems. Quantifying sediment sources can be important to target efficient management measures, reducing sediment supply in the catchments. Sediment fingerprinting techniques are therefore increasingly applied to determine sediment sources and pathways in catchments and thus inform management interventions (Walling, 2005). Many scientists applied sediment fingerprinting techniques for quantifying source contribution of fluvial (e.g., Owens et al., 2005; Russell et al., 2001; Walling et al., 1999; Zhang and Liu., 2016; Nosrati et al., 2018; Collin et al., 1997 and 2012) and aeolian sediments (Gholami et al., 2017a,b; Liu et al., 2016). The sediment fingerprinting approach has been used for a variety of different applications including agricultural, forest harvesting, wildfires and urbanization (Koiter et al., 2018).
Fingerprinting techniques have evolved from single-property fingerprints to multi-property composite fingerprints because reliance on a single property of sediment makes it difficult to accurately distinguish sediments from a variety of sources in large fluvial systems, such as catchments (Collins and Walling, 2004). Many different physicochemical properties have been successfully used to discriminate potential sediment sources, including mineralogy (Klages and Hsieh, 1975), geochemical elements (e.g. Martinez-Carreras et al. (2010b); Collins et al. (2013); Pulley et al. (2015); Chen et al. (2016)), elemental composition (e.g. Motha et al. (2003); Devereux et al. (2010)), biomarkers (Chen et al., 2016), and environmental radionuclides (Martínez-Carreras et al. (2010)). Sediment fingerprinting technique is principally based on statistical tests such as Kruskal-Wallis H test and discriminant function analysis; and mathematical mixing models. The main objective of this study is quantifying sub-basins contributions as potential sources for sediments deposited on the back of the dam in the Lavar watershed, Fin, Hormozgan province by fingerprinting technique. 2.1.Sampling and Laboratory analysis
In this study, spatially distributed source samples were taken from 23 sites, of which 9, 6 and 8 samples were taken from northern sub-basin, midlle sub-basin and southern sub-basin potential sources, respectively, and seventeen samples were collected from the deposited sediments in the lakes dam, Lavar watershed, Fin, Iran.Samples were collected from the upper 0–5 cm depth of potential sources and deposited sediments on the lake’s dam.All sediment samples and potential source samples were dry sieved in the laboratory. Concentration of 56 geochemical elements including Al,Ba,Be,Ca,Ce,Co,Cr, Cs,Cu,Dy,Er,Eu,Fe,Ga,Gd,Hf,Ho,K,La,Li,Lu,Mg,Mn,Mo,Na,Nb,Nd,Ni,P,Pb,Pr,Rb,Sb,Sc,Sm,Sn,Sr,Ta,Tb,Te,Th,Ti,Tl,Tm,U,V,W,Y,Yb,Zn,Ag,Zr,As,Bi, Sand Sbwere determined using ICP-OES and also, eight REE ratios (∑REE, Nd/Yb, Eu/Eu* (Europium Anomaly), (La/Lu)n, (La/Sm)n, (Gd/Yb)n, (La/Yb)n and δCe (Cerium Anomaly)) were calculated and assumed as tracers.
2.2. Disrcimination of sources and quantification of their contribution
A stepwise discriminant function analysis (DFA) applied to discriminate sources. A mathematical multivariate mixing model was used in conjunction with the composite fingerprint to quantify the relative contributions of each source type to the sediment samples collected from the back of dam. The results of the stepwise DFA, based on the minimization of Wilk’s lambda, for discriminating the three source types, on the basis of the individual geochemical properties, showed that six tracers includingLa/Yb,Nd/Yb, Th, Bi,Pr and Cr were selected as optimum fingerprints. A total of six properties were selected for the optimum composite fingerprint, which correctly discriminated 100% of the source type samples. The minimum and maximum of GOF were calculated 45 and 94%, respectively. The fact that a majority of the GOF values was well above 80% suggested that the mixing model performed well in assessing the sediment sources in our study area (Zhou et al., 2016; Haddadchi et al., 2013). Among of six optimum fingerprints for discriminating sources of sediment, three optimum fingerprints (La/Yb,Nd/Yb and Pr) were selected from rare earth elements and their indices. This indicates that rare earth elements (REE) and their indices have great potential to identify the provenance of aeolian sediments and their transport pathways, because they are less fractionated during weathering, transport and sedimentation (e.g. Rao et al. (2011); Hu & Yang, (2016)). According to the results, the contribution mean from northern sub-basin, middle sub-basin and southern sub-basin were estimated 18%, 16% and 66%, respectively. Therefore, southern sub-basin was recognized as the main source to supply material for sediments deposited on the back of the dam.

Extended abstract The components of nature interact with each other in the form of an interconnected chain in such a way that the effect of each component cannot be ignored. On the other hand, these components and loops have a kind of autonomy and internal congruence, so that in another perspective, independence and independent identity can be considered for each of these loops. The efforts of researchers in scientific epistemology to regulate events were because of reducing human beings’ tendency to predict events and behaviors. Although these efforts have been successful in many cases, the occurrence of all events and behaviors is not the subject of scientific discipline. Domino is a kind of game made by small rectangular pieces. It is a row of aligned tiles that once the first tile is hit, what happens to the first tile is happened to the last tile. If energy enters dominoes, this energy enters from a pixel to the next pixel and flows to the last pixel so that the energy eventually ends up. But domino's energy in geomorphology is just as defined, but energy vectors and directions need to be taken into account. When energy enters a domino, some of this energy sometimes transmitted to the next pixel in harmony with changes in the environment and two other energies are emitted. The emitted energy sometimes transmitted to other pixels in the direction perpendicular to the pixel and at other times parallel to the pixel. The most important thing in the examining of the domino process of Ghezel Owzan basin is a systematic look at the landforms that was obtained in frequent field observations. In order to obtain the domino process in the Ghezel Owzan basin, 30*30 DEM extracted from the USGS site and topographic 1:50000 map, geology 1:100000 and 1:250000 maps were used. Then ArcGIS and Arc map software were used to digitize layers such as drains, lithology and faults. By using the Global Mapper software and DEM of the study area, several profiles were mapped around the geonorons to estimate the difference between the height and the downslope of the areas. The remaining terraces are obtained by evacuating these geonorons. In order to measure the volume of evacuated material from geonorons, the DEM of geonorons was cut into segments, and the Below option in the metric unit was obtained from Functional Surface and Surface Volume extensions in order to obtain the volume of geonorons. The domino effect in the economy means more probability of tomorrow's occurrence compared to today and this energy is maintained for different types of events (Markwat, 2008). This sentence is used in economics, whose objectivity can be seen in geomorphology. The domino effect in geomorphology, i.e. the transformation in the roughness of a site located along the basin as a result of a change, will be greater than the development of a river or basin mirage. The interpretation of this sentence in geomorphology is that the amount of the transformation of roughness increases toward the coastal area. Of course, if the energy obstacle and transforming material are balanced in the basin and the dispersion of the transforming cells in the basin has a certain order, the amount of material and hence the amount of energy is decreasing or increasing in the hierarchical order from mirage toward coastal area. If a particular order cannot be made for the changes in material and energy, then the process of transformation also crashes. Rivers have wide beds in loose areas, i.e. energy and material evacuation is linearly in the surface. But strict lithology with the notion of tight valleys states that energy and material evacuation occurred linearly and led to tight formation over time. Based on the field documentation and the use of topographic and geological maps, evidence of past topo-geonorons can be traced. Among the evidences that can be mentioned are: 1) existence of a lake terrace at a height of 1561 meters in Bijar geoneron; 2) downslope in the base of the old alluvial fan in Zanjan and Miyaneh geonoron, and as a result, marl outcrop at a certain level; and 3) Lake terraces at a height of 898 meters in Abbar and the interstices of alluvial fans in Tarom, which are caused mainly by the changes in the base level of the basin of Ghezel Owzan River. The domino of Ghezel Owzan emphasizes the changes in the base level. The domino of base level changes has occurred in two types of inside the basins and outside the basins. The energy released by base level changes is transmitted from the highest rank of the watersheds of a basin, such as dynasties and domino vertices, to the first-order streams and drains. An example of such a reaction is the domination of the decline of erosion in the basin. The bondage and divergence of Anguran Chai, Hassanabad Yasukand, Yol Kashti, and Sojas Roud are related to changes in the base level of Bijar geoneron, and in Mehrabad and Qaleh Chai is related to the domino's effect of Zanjan geoneron. The energy transfer condition depends on parameters such as lithology, tectonics, duration and intensity. The study of geonerons of Bijar, Zanjan and Tarom well illustrate that Ghezel Owzan has not allowed the equilibrium of forms by varying the local base level. The spread and frequency of landforms are inversely related to the intensity of base level change. As the number of changes in the area is greater, the more landforms are remained but in a smaller size; larger landforms belong to the places where the number of changes is less. Although less landforms are created in such areas, they will remain larger and wider.

Extended abstract
1- The degradation of natural resources in recent decades has led to increasing the erosion and an increase in the sediment production rates. Many activities are carried out at watershed level in order to control the destruction and decrease its effects. Assessment of watershed management projects is one of the most important issues performed today of implementation plans and natural resources management (Abbasi et al., 2010).Considering one of the most important goals of watershed management projects is the prevention of erosion and sedimentation and flood control, Therefore, using erosion estimation methods can be a good way to evaluate projects that are used in indigenous and regionally compatible methods. One of the methods for estimating the water erosion in Iran is Geomorphology (Ahmadi, 2006).This method has been examined and approved by various researchers including (Maleki, 2008, MohammadKhan, 2009, and Angebini, 2014) in different parts of the country. In this model, the erosion rate map can be prepared by determining the criteria and indicators affecting the erosion and the projects were evaluated by investigating the erosion map. In the present study, the effect of watershed management activities on erosion and sediment reduction in Safaroud watershed in Mazandaran province was evaluated using erosion intensity map through geomorphology model.
2- Safaroud watershed is located in the west of Mazandaran province with a total area of ​​13551 hectares. In the present research, the implemented projects in the region were evaluated by geomorphologic method by providing the erosion intensity map. For this purpose, the erosion intensity map was prepared on two time bases before and after the implementation of the projects, the first time base was in 1994 and after the implementation of the projects, the second time base was in 2014, by Geomorphology method. AHP and GIS techniques were used to quantify the erosion intensity map. The erosion trend map in each homogeneous unit was prepared from the difference between the erosion intensity map at the second time base and the erosion intensity map at the first time base. The statistical analysis of the erosion and sediment data in two time bases studied was carried out by comparing the average values.
3- According to the erosion intensity map, it was determined that out of 39 homogeneous units, the erosion trend was negative in 24 homogeneous ones at the area of 10292 hectares. The erosion trend was positive for 15 homogeneous units at the area of 3259 hectares. The results of statistical analysis of the comparison between the specific erosion in the two time bases studied shows that with 95% accuracy level, that is to say, there is no significant difference between erosion in two bases before and after the implementation of the projects. The statistical analysis of the sediment output from the basin indicates, within the same 95%accuracy level, there was no significant difference between the sediment discharge from Safaroud watershed in the two time bases before and after the implementation of the projects.
4- Discussion & The results of statistical analysis of the erosion indicate that the implementation of the plans has not been able to significantly change the intensity of erosion in the region. This result is obtained in a situation where in the 24 homogeneous units of the total 39 homogeneous units, i.e. at the area of 10292 hectares (75.95% of the total area), the erosion trend is negative and the erosion has increased in 15 units of 39homogeneous units totaled 3259 hectares (24.05% of the total area).By examining the histogram diagram of the erosion trend, it is found that the erosion in the three homogeneous units of No. 14, 16 and 17 were respectively 0.0357, 0.0209 and 0.0352 which were relatively high comparing to other units. Thus, these three units with a total area of ​​234.54 hectares (73.1 percent of the total area) were identified as very sensitive units. If we do not consider these three units in the statistical analysis and average comparison with 36 remaining units, the result of statistical analysis shows that there is a significant difference between the erosion in the two groups and the plans implemented in the region have been effective in reducing erosion. Therefore, these three units must first be investigated in terms of prioritization of homogeneous units for future planning. Homogeneous unit 14 due to road construction and, homogeneous units: No. 16 and 17 due to mass movements are also sensitive areas.

Landslide refers to geomorphologic processes and downward movements of the materials of the slopes, including rock, dirt, or a mixture of them (Moradi et al, 2012).Landslides are affected by various factors, including rainstorms, earthquake shocks, changes in the level of underwater, storms, rapid erosion and a series of factors reducing the strength of materials (Dai et al,2002) . Because of geological, geomorphological, and topographical variations resulted from the active seismic belt of the country, many areas are susceptible to landslides. Therefore, it is very important to detect and anticipate this phenomenon to prevent its occurrence. Due to mountainous conditions, the climate of the study area is prone to the domain instability. The road range is also possible to suffer from the same deficiency. Existence of large joints in masses of rocks and several landslides in the boundaries of the road double the importance of examining the stability of the slopes and the dangers of volatility (Khajevand,2017). Due to the high volume of damage and the direct and indirect costs of destruction that mass movement imposes on human societies and the environment, planning to carry out a systematic investigation of the effective factors of mass movements and providing appropriate management solutions in these sensitive areas seem crucial. Our country, Iran, mostly has a mountainous topography with tectonic activities, and is the subject of high seismicity of various climatic and geological conditions. These major natural conditions have the potential to create a wide range of landslides. The study area is located in Fars Province, Marvdasht, Kamfiroz Division. In the UTM coordinate system,it is placed in X=619240 and Y=3347600. This area is situated one kilometer southwest of the village of Abbad. Access to the area is possible through the asphalt road to Sefid village. Abbad village is located in the outlet of the basin. Landslides are considered to be mass fractures. The mass fractures include those fractures in which a mass of crushed soil or crushed stone is disrupted on a curved slip surface.There are various methods for analyzing the stability of these types of ruptures: the equilibrium, the numerical, and the physical simulation methods. Due to the ease of applications and the relatively good results, these methods tend to be more widely used than other methods of slope stability analysis. In general, in order to study of landslides, an attempt was made to use a process-oriented (center-based) model. It can be concluded that the slope stability analysis model can be used to determine the instability of the slopes affected by natural conditions due to the morphology, hydrology, soil physics, and vegetation cover. However, artificial factors affecting landslides such as road constructions and distance from the river have no place in this model. One of the regions with high frequency of landslide in Fars province is the village of Abbad. The susceptible geological structure of this region, its climate, and the manipulation of its natural system (road construction and digging irrigation channels) have exposed it to slippage. In order to find critical slip surfaces in the range having various geometric characteristics, the Bishop circle method was combined with 2008 Taliban method. In this method, the Fs were calculated to find the rupture level at a circular surface using different depths of the soil, taking into account the domain geometry. To implement the 2008 Talebi and Bishop combined model, the reliability coefficient was calculated using MATLAB software. All formulas and the information layers required for the model were codified in appropriate codes in the MATLAB environment, and the confidence coefficients (FS) were eventually calculated for the scope under investigation. According to the results of the model, the range before the slip (1.08) was in a critical state at the threshold of the slip and was unstable. In the second part of the modelling, when the slippery range was implemented, the results of the model indicated that the slip mass (2.19) had already reached sustainability. Sensitivity analysis was identified as the most important factor leading to slippage occurrence. Among the factors causing slopes, the effect of the sensitivity analysis is the most important; however, the effect of moisture cannot be ignored. The moisture formed during the road and canal construction was another reason for instability in the region.

Soil erosion is one of the most destructive processes of arid and semi-arid areas, which leads to desertification in a large area of the region. In windy areas, the wind in the region increases the probability of wind erosion. Soil moisture and soil temperature are the two effective factors in soil erosion control. Vegetation is also one of the effective factors in maintaining moisture, but in the arid and semi-arid areas where vegetation is distributed and Scattered, biological soil crusts between dispersed vegetation can be effective in maintaining moisture and soil temperature. Currently, the results of the effects of biological soil crusts on the moisture and soil temperature are contradictory, and these opposite results may be due to differences between different types of crusts or different climatic conditions. Rangeland is one of the most important sources of sediment production, so studying the factors affecting the process of reducing soil erosion is very importantt. The aim of this study is to evaluate the effectiveness of lichens in maintaining moisture, soil temperature and wind erosion control.
2- THEORETICAL FRAMEWORK
It is expected from the lichens, due to their unique characteristics and structures, to increase the amount of moisture and reduce the temperature of the soil during warm and dry seasons. So far, the role of lichens in different seasons has not been studied on microhabitat characteristics and wind erosion control, so we need to know how the lichens act in maintaining moisture and modulating the temperature fluctuations. The study area is located in the steppe rangelands of Golestan National Park. The wind speed is relatively high in this region and the dominant vegetation of the region is Artemisia Sieberi which is distributed sporadically in the region, in free space sparse vegetation, lichens are present in the form of a patch. Soil moisture under the lichen and bare soil during 4 time intervals using a moisture meter and also minimum, maximum, mean and diurnal temperature fluctuations (DTF) soil under lichen and bare soil during the three different seasons were measured using the thermometer ibutton. To determine the most important factor affecting soil moisture and temperature including treatments, season and their interactions, GLMM was applied and Tukey test was used to compare the means. According to GLMM results, the season (F= 182.41; P < 0.0001) had the highest significant impact on soil moisture. The mean comparison results indicate that soil moisture content of lichen and bare soil did not differ significantly in winter, but during the spring and summer, the moisture content of the lichen was higher than bare soil. The temperature fluctuations of lichen (4-23° C) in spring and summer are lower than bare soil (3.5-35 ° C) and at the end of winter there is no significant difference between two treatments. The maximum temperatures were observed in the bare soil and the minimum temperatures in both lichen and bare soil treatments were the same. Therefore, the temperature equilibrium created by the lichen is higher than the bare soil. Biological soil crusts are important in maintaining soil moisture, so that high humidity can be effective in reducing temperature and erosion control. Lichens with mucilage secretion, the aggregate stability increases so that soil moisture amount is increased and soil erosion decreases. Also biological soil crusts affect the temperature equilibrium, the temperature equilibrium created by biological soil crusts in the warm and cold seasons, improves the water status, available food, soil structure, decreases erosion and controls desertification. The reason for the decrease in the degree of soil temperature by biological soil crusts is related to the evaporation rate, so when evaporation increases, it causes more water to exit. In addition, most of the dominant lichens in the area have light color, which has a significant role in reducing the degree of soil surface temperature.

Extended abstract
1- Threshold wind velocity is a major influencing variable in transportation of soil particles and dust production. It is considered as an important component in many theoretical equations and numerical models due to its importance in wind erosion studies (Stout & Zobeck, 1996). The wind tunnel method (fixed and portable), empirical relationships and sediment traps are the common methods to estimate the threshold wind velocity (Refahi, 2005). Estimation of this variable can assist researchers to recognize critical points, in addition to providing suitable activities to prevent depletion of limited resources in desert region. This study aimed at comparing the accuracy of geo-statistical techniques (Kriging and Co-kriging) and artificial neural network model, estimating the threshold of wind velocity, selecting more accurate methods to be used in wind erosion combating projects, as well as identifying more important variables in threshold wind velocity in the Sistan region.
2- The study site with an area of 60 km2 lies within 30º 49′ 43′′ to 30º 54′ 49′′ N latitude and 61º 30′ 22′′ to 61 º 37′ 05′′ E between Sistan river and Fourth Chah-Nimeh reservoir which supplies drinking water of Zabol and Zahedan cities. Threshold wind velocity was measured using wind tunnel in 60 points of the topsoil. Soil sampling was done at the same points. Soil dataset was checked for normal distribution, then threshold wind velocity estimation and validation of obtained results, were respectively done by using the Kriging and Co-kriging and cross validation methods. The multi-layered perceptron model was implemented and obtained results were evaluated using root mean squared error statistics and coefficient of determination, after data standardization and determining the model architecture using trial and error method.
3- Based on the results, among the geo-statistic methods, co- kriging interpolation method with spherical variogram model in comparison with kriging method was determined as an optimal model for the estimation of the threshold wind velocity (R2= 0.60 and RMSE= 0.45). Study of the importance of effective variables also indicated that the variables related to soil texture (clay, silt, sand percents), acidity, salinity, organic matter percent, average weight of particles diameter and the percentage of surface soil gravel were the main contributors to the accuracy of predictive models and hence determining the threshold wind velocity in the study area. The overall assessment of the models used showed that the lower error rate and therefore, the more precise estimation of thresholds wind velocity erosion in the present study, were carried out by multi-layer perceptron model with three layers and three neurons per layer which utilizes Gaussian' transfer function and Levenberg- Marquardt training rule.
4- Discussion & According to the results, the Co-kriging method enabled to perform interpolation with high precision because it utilizes an auxiliary variable and uses covariance between two variables for interpolation (Lark et al., 2014). Furthermore, some capabilities such as increasing data processing power, problems related to measuring some variables, as well as, the correlation between measured variables and the availability of various software tools has increased the usage of this estimation method in various environmental studies (Amini et al., 2002). Performance superiority of the Co-kriging method compared to the Kriging method, has also been reported by Behnia et al. (2016). Likewise, a set of soil characteristics has the greatest effect on the threshold wind velocity in the Sistan region. In line with this findings, it has been reported that the soil crust properties affect the threshold wind velocity; as a result, the threshold value varies in soils with different characteristics (Webb et al., 2016). According to the findings of this research, it is stated that due to utilization of the pair of input and output patterns, artificial neural networks are as powerful tool in various studies related to natural resources. In general, it can be said that through the development of vegetation using native species in the southern and western parts of the study area can increase the threshold of wind erosion in these areas in addition to reducing soil erodibility and its consequences.