فهرست مطالب zahra naserianasl

Soil is one of the most vital issues for the sustainability of the environment, which provides human needs and livelihood on the surface of the earth. Therefore, reducing the phenomenon of land degradation is one of the leading challenges for the sustainable development of the environment and economic activities, which is why comprehensive planning and management against erosion is essential. Today, several methods have been developed for preparing soil erosion maps, which can be mentioned using experimental methods; that these methods include equal weights for all parameters in calculating the average erosion; While each criterion has a point value that is affected by environmental, geomorphological and physical factors related to soil erosion. Among other methods, we can mention machine learning, which is an advanced method that requires high-performance computing systems. However, it is necessary to use statistical methods for fast, understandable and accurate modeling, and there is no requirement for high-performance systems in these methods and Among these methods, Entropy Index, Frequency Ratio, Information Value, Certainty Factor, and Witness Weight methods can be mentioned. Therefore, the aim of the current research is to identify the most important criteria and sub-criteria that are effective in preparing the erosion sensitivity map of the watershed upstream of the Tajen River using the Integration of two data mining models Entropy - Information Value.

The erosion inventory map with 252 erosion points for the upper watershed of Tejn River was identified using Google Earth images, and 70% of these erosion points were classified for training and validation of the model. Then, to evaluate the sensitivity of erosion and also to identify the most important driving factors in the occurrence of erosion, the criteria of elevation, slope direction, soil type, land use, Rainfall Erosivity, distance to stream and Topographic Wetness Index were used and The erosion sensitivity map of the studied area was obtained from the integrated entropy-information value model. In order to evaluate the success rate and predict the model, Receiver Operating Characteristics and Area Under the Curve were used.

The results of the present study showed that the effect of elevation on soil erosion is increasing, so that this effect reaches its maximum value in the elevation class of 2745-3742 meters with an Information Value of 1.65. The influence of the slope directions on soil erosion showed that the south-west slope direction with an Information Value of 1.04 has the greatest effect on the erosion of the region. The results of overlapping the distance to stream layer with the erosion map of the region indicate that the distance layer of 0-456 meters has the highest Information Value of 0.63. The barren land use class with an Information Value of 2.74 has the greatest effect on the erosion potential of the region. The results of the overlap between the Rainfall Erosivity map and the regional erosion map showed that the 302-325 layer of rain erosion has the highest Information Value of 1.28. Examining the relationship between types of soil groups with regional erosion showed that the Inceptisols soil group with an Information Value of 0.66 has the greatest effect on soil erosion in the region. The results of the overlap between the Topographic Wetness Index layer and soil erosion in the region indicated that the 6.2-8.6 layer of the Topographic Wetness Index with an information value of 0.25 has the highest erosion potential. According to the curve (ROC-AUC), the success and prediction rate of the combined model of Entropy Index - Information Value was obtained as 0.831 and 0.837, respectively which indicates the good performance of the model for training and validation courses.

Soil erosion is one of the most important issues of land destruction on a global scale, which causes muddying of waters and lakes, loss of fertile agricultural topsoil and biodiversity; Therefore, it is essential to evaluate the sensitivity of soil erosion. The current research was conducted with the aim of identifying the most important criteria and sub-criteria effective in soil erosion with the integrated model of Entropy - Information Value in the upper watershed of Tajen River. The results of the present study showed that out of the total area of 693.23 square kilometers of the study area, 156.75 and 94.71 square kilometers are in the high and very high categories, respectively. The prepared soil erosion sensitivity map in the studied area can be a useful tool for management and planning in line with soil protection measures.

Flood is one of the natural disasters that can threaten economic, social and environmental sustainability activities. Therefore, identifying flood-prone areas in the basins is essential. The aim of this research was to prioritize and analyze flooding potential in Ghamsar watershed using multi-criteria decision making models and fuzzy logic. For this purpose, first, 14 effective criteria on basin flooding (including precipitation, elevation, land use, soil texture, lithology, distance to river, slope, drainage density, stream order, Topographic Wetness Index, Stream Power Index, flow accumulation, plan curvature, profile curvature) were identified. Rhen, pairwise comparisons were made between the criteria using the AHP method in Expert choice 11 software and the final weight of each criterion was obtained. Moreover, the criteria were fuzzified using linear and large fuzzy functions, and finally, the final weights obtained for each criterion were applied in the respective layers and the final flood risk map of the basin was prepared. The results of prioritizing quantitative and qualitative criteria based on the opinion of watershed management experts using the AHP method showed that among the 14 proposed criteria, the precipitation criterion with a final weight of 0.229 has the most impact on the flood risk of the basin. Moreover, the criteria of heavy to very heavy soil texture (0.499), Plvav stone unit (0.252), water areas and bare lands with final weights of 0.345 and 0.225, respectively, have a stronger role in the flood risk of the basin. The results of the final flood risk map of the basin showed that about 30.841, 27.056 and 12.406 percent of the total area of the basin are in the medium, high and very high flood risk categories, respectively, and these areas are located mostly in the central part and along the southeast of the basin. Therefore, knowing flood potential of the basin can be effective in formulating crisis management plans when faced with floods.

The complete or partial movement of rock or soil caused by gravity is called a landslide. Landslides are considered among natural disasters and account for at least 17% of casualties caused by natural disasters, which sometimes cause the loss of life, property and infrastructure. Therefore, the first step to understand and recognize landslides and then reduce the damages caused by them is to analyze landslides using statistical methods. The frequency ratio method is a statistical analysis model and one of the most popular approaches for the analysis of landslides, which is still widely used by many researchers. Another two-variable statistical model in landslide susceptibility studies is the Shannon entropy model. Entropy is a management approach that estimates dispersion and disorder in natural phenomena and is widely used in environmental sciences. Middle Tajen watershed is one of the sub-basins of Tajen basin in Mazandaran province and due to special environmental conditions, it is prone to mass movements and landslides have occurred in different parts of it during previous periods. Therefore, it seems necessary to prepare a landslide susceptibility map with acceptable accuracy for this area. Based on this, the aim of the current research is to evaluate the comparison of two statistical models of frequency ratio and Shannon entropy to prepare a landslide susceptibility map in the middle Tajen watershed.

In order to prepare a landslide susceptibility map with Shannon's frequency ratio and entropy statistical models, first 68 landslide points were identified for the region. Also, according to the field observations of the conditions of landslides recorded in the region, as well as a review of the sources of ten factors affecting the occurrence of landslides, including slope, aspect, distance to stream, elevation, land use, lithology, Plan Curvature, Profile Curvature, rain and Topographic Wetness Index were identified and modeling was done using these factors. The frequency ratio statistical model is a simple and understandable probabilistic model that shows the correlation between landslides in the region and the factors that cause them in the region. In the statistical model, the frequency ratio of the values of one, less than one and more than one respectively indicates the average, low and high correlation between landslides and their causing factors in the region. Entropy measures abnormal behavior, variability, instability, degree of disorder and uncertainty of a system compared to its possible initial state. In general, the concept of entropy describes the abnormality between causes and consequences or the degree of abnormality; Therefore, the Shannon entropy model is used to show the thermodynamic conditions of a system. In the prepared landslide maps, the most important question that is raised is the discussion of the accuracy and correctness of the prepared model, so the process of validating the built models is important. Therefore, In the present study, Receiver Operating Characteristics (ROC) Area Under the Curve (AUC) were used to train and validate the built model.

The results of the effect of factors affecting the occurrence of landslides in Shannon's entropy model showed that the parameters of topographic humidity, land use and longitudinal curvature with the weight values of Wj equal to 0.73, 0.66 and 0.65 respectively are the most have an effect on the occurrence of landslides in the region. The results of evaluating the success rate and predicting the model according to the ROC curve and the area under the curve (AUC) for the training and validity of the two models, frequency ratio and Shannon's entropy are respectively equal to 0.76, 0.72 and 0.62, 0.59 to It was found that it indicates the relatively good performance of the abundance ratio model and the weak to poor performance of the Shannon entropy model for evaluating and preparing a landslide susceptibility map in the studied basin. Also, the results of landslide susceptibility zoning in the middle Tajen basin using frequency ratio model showed that 30.156, 17.066 and 5.206 percent of the basin area are in the range of medium, high and very high sensitivity, respectively.

Landslides are one of the natural hazards that cause many human and financial losses. The zoning of landslide-prone areas, while identifying sensitive and high-risk areas, can provide the basis for the implementation of proper management plans in the slopes in order to reduce damages. In the present study, frequency ratio and Shannon's entropy models were used to evaluate the susceptibility of landslides in the middle Tajen watershed located in Mazandaran province. The results of the landslide susceptibility zoning map in the basin showed that more than half of the basin's area (52.428%) is in the moderate to very high landslide susceptibility range. According to the results obtained from the ROC curve, the frequency ratio model according to the values of the area under the curve (AUC) with success rate (0.76) and prediction rate (0.72) respectively compared to the Shannon entropy model with success rate and prediction 0.62 and 0.59, respectively, have a relatively good performance for the zoning of the landslide susceptibility map in the study area of the middle Tajen basin. Since in the last few decades, due to the change of use and destruction of natural resources, landslides have become a serious and big danger in many parts of the world, Therefore, the preparation of the landslide susceptibility zoning map plays an important role in the management of high-risk slopes and land preparation.

Ecotourism was defined as the responsible travel to natural areas that conserves the environment, sustains the well-being of the local people, and involves interpretation and education. To achieve sustainable development in the watersheds with a comprehensive management approach, it is important to identify the important key elements and parameters. The main purpose of this study is to present and prioritize the best management strategies to achieve sustainable ecotourism in the Vennaei region. The strengths, weaknesses, opportunities, and threats of the region were identified via descriptive-analytical-developmental method. The SWOT analysis matrix was used to codify the best strategies for the region. Quantitative programming matrix were applied to arrange strategies. Therefore, first internal factors (strengths and weaknesses) and external factors (opportunities and threats) of the region have been identified and evaluated based on the field visits and expert judgments. The results of this study showed that the final score for internal factors and external factors are 2.43 and 2.51, respectively. Accordingly, the strategic position of the study area is conservative type (WO). Based on the results, four strategies were proposed for the study area including using the active and young force of the village to provide tourism services, increasing the information of the tourist attractions of the region through the cooperation and participation of local people, developing case infrastructure of ecotourism with the help of the government and the attraction of public participation, and increasing capital and income by providing accommodation centers for travelers and tourists. The results of prioritizing strategies using quantitative planning matrix revealed that the development of infrastructure required for the development of sustainable ecotourism with government assistance and attracting public participation is the top management priority for the Vennaei Basin with a final attractiveness score of 4.92.

One of the ways of sustainable management of groundwater resources is to model the groundwater level of the plains in order to identify water potentials and long-term planning based on the status of aquifers. In this study, MODFLOW code, which is one of the codes in GMS7.1 software, was used to simulate the groundwater flow of Minab plain aquifer. To investigate the observational and computational level of groundwater in the study area, information about the water table of 16 observation wells in the plain was used. The constructed model was initially calibrated assuming the current was constant and the parameters affecting the model including hydraulic conductivity and feed were optimized. Then, the model was calibrated assuming that the flow is unstable in 12 time steps (October 1991 to September 1992) and the specific discharge parameter was optimized. According to the calculated balance of the aquifer, the total feeding of the aquifer is 1409.443 million cubic meters, and the total discharge from the aquifer is 1640.1011.1 million cubic meters, which is negative due to the higher output of the aquifer than the input, and the balance of the plain is negative. It will cause a sharp drop in the groundwater level in the coming years.