فصلنامه پژوهش های فرسایش محیطی
سال نهم شماره 3 (پیاپی 35، پاییز 1398)

Dust storms are natural hazards that effect on weather conditions, human health and ecosystem. Atmospheric processes are directly affected by the absorption and diffusion of radiation by dust, and dust in the cloud acts as a nucleus of congestion. The main dust areas in the world are flat topographically dry areas with erosion-sensitive soil and poor vegetation that is easily eroded by wind. Atmospheric processes are directly affected by the absorption and scattering of radiation by dust, and the dust in the clouds acts as a condensation nucleus. Iran is exposed to numerous local and trans-regional dust systems due to being in the arid and semi-arid belt of the world. Recent observations indicate that this phenomenon is increasing in the country and region under study. Khorasan Razavi province has arid and semi-arid climates with numerous dust storms occurring annually. In some years, more than 50 dust events have been recorded in the province. The large amount of dust in this area indicates large harvesting areas across the province, indicating the importance of research in this area. The purpose of this study was to evaluate the factors affecting the occurrence of dust and to prepare its susceptibility map in Khorasan Razavi province using logistic regression and random forest regression models.

Khorasan Razavi Province with an area of 143864.118 square kilometers and with a population of 5.999529 is the fourth largest province in the country. The highest point of the province is in the highlands of Binalood, north of Neyshabur, at an altitude of 3211 meters above sea level, and the lowest point of the province is 300 meters above sea level, on the border of Iran and Turkmenistan. Dust indices include BTD2931, D, NDDI and BTD3132, which were calculated for all satellite images of these indices. Then there are four false color combination methods including 1- R: NDDI, G: B4, B: B3, 2- R: D, G: BTD2931, B: NDDI, 3- R: D, G: BTD3132, B: NDDI and 4- R: BTD2931, G: B4, B: B3, were used to determine the best method for identifying dust source. Initially, 65 dust sources were identified in the study area and for the period 2005-2016. Of the identified focal points, 70% (46 dust source) were used for modeling and 30% (19 dust source) were used for evaluation. Then, 7 factors including soil, lithology, slope, vegetation index (NDVI), distance from the river, geomorphic units and land use as an independent and effective variable on dust were prepared. Then using logistic regression and random forest regression models, the weight of each of the factors in R software was calculated, finally, the dust hazard sensitivity maps were prepared.

Four different false color combinations were used to detect dust areas in all images. Each of these methods revealed a dusty mass. The second method (R: D, G: BTD2931, B: NDDI) is the best method for detecting dust and determining dust collection zones. Finally, by employing these techniques and creating false color combinations and applying them to existing images and their visual interpretation, 65 dust collection points were identified throughout the area. Based on the results, slope had the greatest impact on creating dust source zones. Geomorphology, lithology, vegetation index, soil and land use are the next influential categories of dust source area. Negative coefficients indicate the inverse relationship of the dependent variable (dust source) with the independent variables; in fact, negative coefficients do not indicate a lack of correlation, but mean a weaker correlation than other factors. The distance factor from the river has the least impact on the formation of these dust source. The OOB results show a predicted error rate of about 35.16%. In other words, the accuracy of the model can be considered 64.84%. The results of logistic regression algorithm showed that 24.5% of Khorasan Razavi province was in low sensitivity area, 28.2% in medium sensitivity area, 29.4% in high sensitivity area and 17.9% in high sensitivity area. It is very sensitive. The results show that the highest dust source points (57.9%) are located in high sensitivity area. The results indicate that about 84.2% of the dust collection points are located in the area of high and high sensitivity. Surveying the area of dust susceptibility map using random forest algorithm showed that the area with the highest sensitivity had the lowest area (16.7) and the areas of high, medium and low were 23.5, 31 and 8.8, respectively. 28 estimated. About 63.2% of source are located in the area of high sensitivity and there is no source for the area of low sensitivity.

The results of both models show that slope and land use with the significant coefficients of 0.852 and 0.673 had the most effect on the creation of dust source area. The results also indicate that most dust removal sites (57.9%) are located in high sensitivity area. The results indicate that about 84.2% of the dust collection points are located in the area of high and high sensitivity. The evaluation of models using the ROC curve showed that in terms of success rate, logistic regression models and random forest had a precision of 781 and 907 respectively. Each of the two high correlation models between the sensitivity maps and the distribution of dust source areas can be observed. But in general, the random forest model has a higher accuracy than the other logistic regression models.

Today, geotourism phenomena and geological heritage are at risk of being destroyed by the changing lifestyles and industrialization of most countries. These changes are based on high rates of resource consumption, such as energy, materials, soil, as well as increased production of tailings and waste (Gray, 2004). In recent years, as the number of tourist’s increases in geotourism sites, the risk of damage and destruction by visitors increases, given the fact that “geoheritage is considered as non-renewable resources of nature (Xun and Milly, 2002). Accordingly, World Heritage Committee has related three criteria out of ten criteria of cultural and natural heritage register to geological phenomenon especially to inanimate nature which indicates the importance of such natural phenomenon (UNESCO, 2019). Therefore, given the abundance of unique geological phenomena in Iran and their application for tourism development, the importance of conservation of such a valuable phenomenon against human and natural threats presents serious challenges to geoheritage in Iran. In this regard, awareness of the vulnerability of geotourism phenomena and geological heritage is a prerequisite for the conservation of these phenomena; Providing conservational guidelines to deal with threats relies on analyzing the vulnerability of geotourism phenomena. As a result, this research was done with the aim of developing a model of the vulnerability of geotourism attractions. Therefore, this research seeks to develop a model of the vulnerability of geotourism attractions which explains the causal conditions, process, and consequences of the vulnerability of geotourism attractions. The findings of this research provide the necessary tools for policy-making and decision-making for related managers and officials to conservation management of geotourism attractions.

Due to the nature and purpose of this study which is analyzing the vulnerability of geotourism attractions in tourism destinations, the type of research is fundamental-applied and its approach is qualitative. The strategy used in this research is logical reasoning in order to define a proposed model for data analysis. The strategy of logical reasoning is more comprehensive than other research strategies as each model requires logical integrity. Moreover, the strategy of logical reasoning can help to codify extensive theoretic literature into a theoretical framework. Documents, theories and, scripts related to the subject are reviewed and investigated in order to answer the research question regarding the quality of a model of the vulnerability of geotourism attractions. An/The archival method is used to collect initial data. With respect to the nature of data in the present study, the theoretical texts are analyzed qualitatively. Finally, according to the experts’ opinion, the model of research has validated.

 Results :

 What is inferred by literature is that conservation of geotourism attractions gains importance with respect to their significance. In fact, significance is a fundamental concept to geoconservation” (Dixon, 1991). Conservation of geotourism attractions must be based on features leading to significance of that phenomenon. Consistent with literature, features indicating the significance of a phenomenon are introduced under the concept of “value”. “Value is a representation of significance with is attributed to quality of places by people” (English Heritage, 2008). Conservation of geotourism attractions should be based on conserving their values so that finally it can lead to conservation of their significance. The set of values attributed to geotourism attractions can be defined in two groups of intrinsic and instrumental values. “Instrumental values are human-based values and intrinsic values are independent of human” (Alexander, 2013). Scientific values of a geotourism attraction are considered as its intrinsic values; other values such as ecological, aesthetic, cultural, educational and financial values are expressed as instrumental values as well. In legal framework, World Cultural and Natural Heritage Convention have considered geological valuable phenomena as natural heritage providing that they qualify as being “integrated”. “Integrity is the scale of perfection of heritage” (Basiri et al. 2014). Integration influences how values of a phenomenon are expressed by the audience and secure the sustainability of its values. As the integrity of geotourism attraction is undermined, its values are threatened; integrity is undermined by human and natural threats which finally lead to a/the decline of geotourism attraction values; Declining values lead to a/the reduction of attractions’ significance and make them the vulnerable following reduction of their significance. In the following, for confirming the validity of a proper model, it was done receiqving experts’ attitudes regarding this issue. In this regard, statistical mean for all questions is higher than the theoretical mean (3).The statistical mean for questions is as follows: model comprehensiveness 4.11, the cohesion of components in each dimension 3.98, uniqueness 3.88, briefness and related naming 4.21, timeliness 3.74, adaptability with environmental changes 4.02, fitting with model’s title 4.44, fitting and clarity of graphic pattern 4.13. According to the results of the one-sample t-test, given the error level of 0.05 and significance level of 0.000, obtained value for t is higher than 1.96 for all questions which indicates the statement that “the model is acceptable” is confirmed by experts.

Generally, conservation of geoheritage is essential because geosites are exposed to several kinds of threats such as an/the illegal collection of minerals and fossils from geosites, destruction by visitors, wrongful application, incorrect mining, and legislation. It should be noted that developing geotourism activities without conservation measures can lead to the gradual destruction of attractions and setting the ground for erosive factors, degradation of soil texture due to traffic and hence susceptibility to erosion which can create a critical condition in geotourism regions and threaten the environmental sustainability of the region. Considering that awareness of the vulnerability of geotourism phenomena and geological heritage is a prerequisite for the conservation of these phenomena, this research was done with the aim of developing a model of the vulnerability of geotourism attractions. According to the research proposed model, the significance of attraction is indicated by intrinsic and instrumental values; meanwhile, the integrity of geotourism attractions is itself an effective factor in attributing instrumental and essential values to attractions. If the integrity of geotourism attractions is weakened by natural and human threats, naturally it leads to reduced values; Declining values lead to the reduction of attractions’ significance and make them the vulnerable following the reduction of their significance.

Evaluation is a process of assessing the degree of achievement to determined goals. In the meantime, choosing the right method for evaluating the effects will have a significant role on the results and management strategies. Therefore, considering the importance of check dams in watershed management programs in Iran, in this study, performance of check dams in Kond watershed in Tehran province is evaluated with a new economic approach named Cost-Effectiveness Analysis.

At first, the cost associated with check dams is Actualized based on 2019. Then, their effectiveness in controlling sediment load is determined by calculating the volume of stored sediment in their reservoir by Nakhjavani method. Next, Economic evaluation of check dams done using Cost-Effectiveness approach and their spatial distribution is obtained. Finally, the most cost-effectiveness and optimal type and height of check dams in the Kond watershed is determined.

Obtained results showed that the effectiveness of check dams in the Kond watershed was equal to the control of 131782 t of sediment load, which is a high value. Overall cost-effectiveness of these check dams is equal to 317180 IRR per each ton of controlled sediment load. Their effectiveness-cost is also equal to 0.00000315 ton of controlled sediment load per each IRR, which is a small amount. The results show that the cost-effectiveness criterion increases as the height of check dams up to 4.5 m in the study area. After height of 4.5 m, the cost effectiveness decreases due to the change of the type of check dams from gabion to Masonry. In fact, the cost of sediment load control in check dams with a height of 4.5 meters is about nine times less than that of the check dams with a height of one meter. Accordingly, it is found that sediment load control in this case study has been done with high cost. One of the main reasons of high cost-effectiveness is the large number of check dams in the height range of 1 to 1.5 m (43%) where the cost of sediment load control with them is very high. Obtained results by considering the type of check dams also showed that Gabion check dams with 4.5 m height and cost-effectiveness equal to 134615 IRR per each ton of sediment load have the lowest cost-effectiveness and are the most economical and optimal types of check dams for sediment load control. In contrast, masonry and gabion check dams with heights of 1 and1.5 m also have highest cost-effectiveness and the cost of sediment load control in this type of dams is very high.

This result indicates that the choice of right type of check dams in the management plans will have a significant impact on the efficiency of cost of sediment load control. Also these results show that watershed management approach in Iran needs to change its attitude. In fact, if it is necessary to control the sediment load on the stream, the choice of a less number of check dams with optimal height and type, will load better results than choosing a large number of small check dams.

Geotourism is defined as a form of tourism, in which the geographical features of a place increase the environment, culture, cultural heritage and well-being of its inhabitants (Quartz et al. 2008, 106). Over the past years, the creation of geoparks and the development of geotourism have made geomorphosites a major feature of this type of tourism (Reynard et al. 2007, 150), Because geomorphological features are easily recognizable and are the most attractive non-living natural elements in the landscape (ARTUGYAN ؛ 2014, 92). The combination of geological features with different geographical conditions has led to the formation of glacial and proximal glacial evidence/pieces of evidence, types of karstic landforms and landforms caused by mass movements, water erosion, and sedimentation in Guilan city. Therefore, the city has a rich geomorphological heritage and some of these landforms have tourism potential due to their attractiveness and scientific importance and so far no study has been conducted to identify and evaluate the geomorphosites in this city. Understanding the capabilities of geotourism and identifying the geomorphosites of this city can play an important role in the economic prosperity of this deprived and border city. Therefore, the purpose of this study is to evaluate and identify the geomorphosites of Gilan Gharb city.

This study used descriptive-analytical methods to study the geological, geographical ,and geomorphological status of the study area and based on the criteria of scientific value, added value and value of use (Table 1), suitable landforms were selected as geomorphosites. During extensive field surveys in Gilan-e-Gharb township, 14 landforms with karstic, erosional, evidence/peices of evidence, domain and tectonic motions were selected to evaluate and identify the geomorphosites (Figure 2). Then based on quantitative parametric (QG) and scientific (Q) quality of selected landforms quantitative and numerical are evaluated and their ability to be introduced as geomorphosites is investigated. Finally, the results of the two models are evaluated based on Spearman correlation and the geomorphosites of Gilan-e-Gharb are evaluated.

In the present study, the Gilan-e Gharab, Zardarmar cave, ghalageh Poulet of karstic origin, the Guilin Canyon landforms, the G-shaped Govaver valley, the U-shaped Darvan ghala valley have the karstic origin and water erosion. Balaleh Comb, Mieh Khash gap, Tang Gaul waterfall, and Vijenan badlands are the result of the erosion of current waters cascades and landforms landslides are the result of mass movement activity. The Ghalejeh fault wall and the Gilan Gharb fault faults are of tectonic origin and the Ghaleh circus is the result of ice activity during the last cold period. According to the quantitative parametric method, the selected geomorphosites of Guilanbarg city had scores between 0.554 to 0.736 and the Guilin Canyon, Sarab Gilanbar and Tang Golem cascades had the highest scores respectively. In this study, 14 different landforms were selected for evaluation as geomorphosites. In both methods, the Guilin Canyon and the Sarab Gilan West have the first and second most valuable geomorphosites, respectively. And the Tang Gaulm Waterfall geomorphosite is both highly rated in both models. In both methods, high-rank and high-rank geomorphosites were similar but less overlapping in middle and lower rank geomorphosites (Table 9). To compare the results and determine the reliability of the methods used, the results of the two methods were compared. The similarity of the results of the two models based on the Spearman correlation coefficient was 0.54 and indicates a moderate and positive correlation between the two methods. The high geomorphosites of Guilin Canyon and Sarab Gillan West have the karstic origin, the narrow Golem cascade is the result of the activity of the current waters and the landslide is the result of mass movements.

 Based on the results of both models, the karstic geomorphosites of Guilin Canyon and Sarab Gilan Gharb are the most valuable geomorphosites. According to the quantitative parametric method, all geomorphosites score more than 0.50 and are capable of being presented as geomorphosites.But according to the semi-quantitative (scientific quality) method of Balaleh Camb , the Visjenan badlands, Ghalajeh Pole, and  Zardehmar Vertical Cave have a score of less than 0.50 and are not capable of being presented as geomorphosites. A comparison of the results of the two models based on Spearman's correlation coefficient has moderate overlap, which confirms the significant difference between the results of the two models. This is due to various reasons such as the diversity of genes in the selected landforms and the multiplicity of criteria in the quantitative method. Therefore, it can be said that the quantitative method has better performance than the semi-quantitative method (scientific quality) due to the variety of criteria and coverage of different aspects for evaluation of geomorphocytes and also lack of expert opinion. The results also show that the quantitative method can be used in different geomorphological environments. Finally, it can be said that the selected geomorphic sites of Gilan Gharb city are based on a quantitative method model with high to medium power in geotourism.

    The desert area, the world's widest ecosystem, covers more than one-third of its surface, and much of Iran is affected by climatic conditions. Wind erosion due to the persistence and extent of erosion in time and space, especially in arid areas with high damage potential. In fact, the morphodynamic boundaries affected by climate change have changed from past to present, leading to the expansion of the territory of wind erosion, and in recent years the dust hazard has also become an environmental issue in these areas. One of the natural occurrences and challenges for sustainable development and management in arid and semiarid areas is wind erosion. Also, wind erosion is one of the causes of soil loss and due to its wide range of activities it usually has less destructive performance than other erosions. This study was in Damghan basin. Haj Ali Gholi Playa is affected by wind erosion.

    The data used are library data, meteorological statistics, maps, satellite imagery, field and laboratory data. Initially based on geomorphological, geological, soil, vegetation, slope, land use information, geomorphologic facies of the identified area and using 9 effective erosion potential determination models. This process was studied and the erosion class of each facies (sedimentation rate) was determined. Also, the wind as a motiving factor for wind erosion was studied using the hourly data of synoptic stations over the period (2003-2019) of the Meteorological Organization of the four stations in the basin and the annual windrose was plotted to determine its direction and velocity. After partial understanding of the wind process status to determine its rotational and local pattern system, the features of the evidence of wind erosion landforms (orientation and dispersion distribution) such as barchan, Erg, sand arrows, etc. used in field visits. Then, to determine the influence of particle size on wind erosion and dust erosion performance in this hole, 38 samples from Playa marginal areas were taken from Quaternary sediments for sedimentary experiments.

According to the results of implementation of the Erifer model for determining wind erosion potential in Damghan basin, seasonal lake bed facies, lakes and sand masses in high erosion class and seasonal mud facies and alluvial plain in middle erosion class and the coniferous facies and rough mountain slopes are in a low erosion class. This indicates that the lakeside facies have the highest potential for wind erosion due to the sediment type and the environment. This indicates that the lakeside facies have the highest potential for wind erosion due to the sediment type and the environment. In the study of wind erosion potential, it is the motiving factor of wind erosion that was intercepted and analyzed. The existence of a convective cyclone corresponding to the lowest and hottest point of the plain in the region was found to be counterclockwise in the cyclone, with converging motion toward the center. The wind cyclonic swirl pattern to the ground screw and removal of sediments in the west and southwest prevail hole. This moves eastward from the surface of the Earth, causing sand to be deposited in the southeastern half of the hole as we observe the wells of the Damghan Basin in the southeast of Playa, and in the eastern part of the wind deposits. We don't have. In fact, the movement of wind particles is a function of wind strength and erosion, surface resistance to erosion and erosion.  The analysis of 38 sediment samples showed that sediments above 63 microns in the southwestern range of 66.18%, southeast of 76.33%, northwest of 93.62% and north of 97.85%.

Discussion & Conclusions

The major causes of erosion on the surface, especially in arid and semi-arid wind erosion, to prevent damage is necessary to study their properties. As the Quaternary lakes declined in volume and volume and groundwater levels declined, large areas of the older lakes, including Playa Damghan, were exposed to wind and wind erosion. The results show that a thermal cyclonic system causes the distribution of wind sands along the playa border. Also based on wind data and particle size the sediment movement in the region was then mutated and suspended in creep and wind erosion has led to the creation of landforms, and the dust hazard in the area is poorer than that. The results show that in the Damghan Playa area, due to studies of wind erosion and various forms over time, more dust has been created than the landform evidence we see today in the Playa border.

Soil saturated hydraulic conductivity (Ks) is an important factor in the estimation of water, solute transport models and erosion processes. Direct measurement of soil saturated hydraulic conductivity (Ks) in field and laboratory is time-consuming, laborious and expensive because of high temporal and spatial variability; especially in salt-affected soils around Urmia Lake, Ks measurement is difficult because of high sodium concentration and consequently poor stability of soil aggregates. Therefore, many different regressions, artificial neural network (ANN) and the neuro-fuzzy pedotransfer functions (PTF) have been developed to estimate Ks from readily available soil variables such as sand, silt, clay, bulk density (BD), particle density (PD), electrical conductivity (EC), pH, and organic carbon (OC). The objectives of this study were to derive pedotransfer functions by using regression, artificial neural network, and neuro-fuzzy methods to estimate Ks from some soil variables in the salt-affected soils selected from the northwest of Urmia Lake and to compare the performance of the neuro-fuzzy, artificial neural network and regression models.

Disturbed and undisturbed (steel cylinders with 5 cm diameter and height) soil samples (n= 100) were systematically taken from 0-10 cm soil depth of bare and agricultural lands of Shend Abad region located at the 15 km of Shabestar city, northwest of Urmia Lake, Iran (45° 36ʹ 34ʺ E and 38° 6ʹ 37ʺ N). The values of sand, silt, and clay (hydrometer method), CaCO3 (titration method), bulk density (cylinder method), particle density (pycnometer method), organic carbon (wet oxidation method), and total porosity (calculating from BD and PD) were measured in the laboratory. The mean geometric diameter (dg) of soil particles was computed using the percentages of sand, silt, and clay. The EC and sodium adsorption ratio (SAR) were measured in 1:2.5 (soil: distilled water) extra. The pHe was determined in a/the saturated paste. The soil saturated hydraulic conductivity (Ks) was measured by constant (agricultural lands) and falling (bare lands) head method using steel cylinders in the laboratory. The data were divided into two series as 80 data for training and 20 data for testing. The SPSS 18 software with a/the stepwise method to derive the regression PTFs and MATLAB software to derive the artificial neural network and neuro-fuzzy PTFs were used. A three-layer perceptron network and the tangent sigmoid transfer function were used for the artificial neural network modeling. In estimating soil saturated hydraulic conductivity, the accuracy of neuro-fuzzy, artificial neural network and regression pedotransfer functions were evaluated by the coefficient of determination (R2), root mean square error (RMSE) and mean error (ME) criteria.

Results & Discussion:

Most of the studied soil variables had good distribution for developing and evaluating regression, ANN, and neuro-fuzzy PTFs. The high values of the coefficient of variation (CV) were found for SAR (167.86%), Ks (130.36%), EC (117.05%), dg (88.44%), clay (73.23%), OC (58.46%) and sand (51.47%) in the studied area. The textural classes of studied soils were loamy sand (n= 3), sandy loam (n= 39), loam (n= 20), silt loam (n= 22), silty clay loam (n= 7), silty clay (n= 7) and clay (n= 2). There were found significant correlations between soil saturated hydraulic conductivity (Ks) and sand (r= 0.60**), silt (r= -0.60**), clay (r= -0.43**), organic carbon (r= 0.36**), bulk density (r= -0.52**), particle density (r= -0.53**), total porosity (r= 0.31**), CaCO3 (r= -0.58**), mean geometric diameter (r= 0.57**), SAR (r= -0.35**), EC (r= -0.22*) and pHe (r= -0.44**). These results are in line with the findings of the former studies that reported direct relation of Ks with OC, sand, and inverse relation of Ks with silt, clay, BD, and SAR. Generally, 8 regression, artificial neural network, and neuro-fuzzy pedotransfer functions were constructed to estimate soil saturated hydraulic conductivity (Ks) from measured readily available soil variables. The results of the best regression, artificial neural network and neuro-fuzzy pedotransfer functions indicated that the most suitable input variables to estimate soil saturated hydraulic conductivity (Ks) were bulk density and silt in the studied region. The values of R2, RMSE and ME were obtained equal to 0.65, 0.119 cm min-1, 0.059 cm min-1 and 0.73, 0.087 cm min-1, 0.006 cm min-1 and 0.69, 0.127 cm min-1, -0.051 cm min-1 for the best regression, artificial neural network, and neuro-fuzzy Ks pedotransfer functions, respectively. According to these results, the ANN PTF was the best in estimating Ks because of having high R2 and low RMSE compared with regression and neuro-fuzzy PTFs. The former researchers also obtained bulk density and silt as the best input variables for estimating soil saturated hydraulic conductivity (Ks) in different soils and regions.

The results showed that bulk density and silt are the most suitable readily available soil variables to estimate soil saturated hydraulic conductivity (Ks) in the studied salt-affected soils. According to the RMSE criterion, the precision of an/the artificial neural networks in estimating Ks was more than regression and neuro-fuzzy pedotransfer functions in this research. Also, regression and neuro-fuzzy PTFs have not an/the observable difference in estimating Ks.