Geography and Environmental Sustainability
Year:2019 | Volume:8 | Issue:29 |Papers Count:7

The development and creation of new ways to protect water and soil lead to either educing or controlling soil loss which are considered as vital issues. In this study, the effect of vermicompost and straw as a soil organic conditioner on reducing runoff and sediment is investigated in the plots with two square meters area. For this purpose, 400 g of straw and 500 g of vermicompost per square meter were mixed with the topsoil of plots. Besides, the rainfalls with 51 and 65 mm/h intensities were simulated by portable rainfall simulator in field with natural condition. The results showed that straw could decrease runoff volume up to 16. 84 % compared to the control treatment, while suspended sediment load is increased by 9. 06 % at 51 mm/h intensity. Vermicompost, the runoff volume and suspended sediment increase up to 2. 37 and 11. 04 %, respectively. However, statistical criteria showed that none of these results was significant in this intensity. By the rainfall intensity increase from 51 to 65 mm/h, wheat straw treatment reduces the runoff volume at a significant level (p

Climate is considered as one of the most important factors affect the tourism industry. The present study is a field study that aims to investigate the role of climate in tourism and validate the performance of bioclimatic indices. This research has been carried out in Gondman lagoon area in Chahar Mahal and Bakhtiari province on the Nowruz holiday of 1396. The field data are collected through a questionnaire with axial topics including thermal sensation, thermal preference, aesthetics, adaptive behavior, and individual characteristics. Another part of the data is climate parameters such as temperature, relative humidity, cloudiness and wind, which is measured at the same time as completing the questionnaire by the lutron-lm-9000 data logger calibrated to CE standard. Bioclimatic indices (Predicted mean vote and Physiological Equivalent Temperature) are used to measure the thermal comfort conditions. Besides, Pearson correlation and multiple regression model are used to analyze the data. The results show that there is no significant correlation between the actual data obtained from the questionnaire and the data estimates by the indicators. Biochemical indicators show more warming conditions, while actual data often indicate a feeling of thermal cooling. In contrast, the thermal sensation of individuals reveals a significant and meaningful impact on independent climate parameters, the highest for clouds (R =-0. 82) and humidity (R =-0. 88). In other words, the visual conditions of the environment have a significant role in the type of person's sense of warmth. Due to the negative of these coefficients, cloudy sky with high humidity has significantly affected the type of heat feeling stated in the questionnaires. The use of bioclimatic indices in the evaluation of thermal comfort conditions requires the validation of these indicators and, if necessary, corrected. Extended Abstract 1-Introduction Climatology in general investigates the wind, precipitation and other atmospheric elements in a region and in the specialized mode, the details of the relationship between atmospheric elements changes with special activities such as health, agriculture, transportation, architecture, maritime tourism, tourism, and so on. Awareness of climate comfort in human life and its everyday activities can play an important role. In terms of comfort conditions, a set of conditions is suitable for at least 80% of the people in terms of heat. By changing any of the aforesaid elements, the comfort condition is lost, and another element must be changed to compensate it. For example, if the temperature rises, the coating can be lowered, or it can achieve to a new comfort point by increasing air flow. The whole set of these points of comfort is called the Comfort Area, which is a very important debate in biology, climatology, health, tourism climatology, urban climatology, and architectural climates. Many of the bioclimatic indicators have been developed in laboratory or by selection of sample groups in different parts of the world (especially in the first world countries), and in many cases they can be used in a region of the world, such as our country. It is necessary to provide the results that are far from reality. Therefore, it is necessary to evaluate and validate the use of this indicator in different parts of the country. In this way, the best measure can be a survey of people about their feelings of heat. 2-Materials and Methods The present study was carried out based on field studies and data from a questionnaire. The completed questionnaire consists of 12 questions that are designed to fulfill the research objectives. In this questionnaire, the issues such as: thermal sensation, thermal preference, climate aesthetics, behavioral and comparative mechanisms along with individual and physiological characteristics are investigated. As each questionnaire is completed, the quantity of weather parameters (temperature, humidity, cloudiness and wind) is also recorded by the data logger. The Study period in this study was 13 days of the Nowruz holiday of 2017, and a total 167 people participated in the project and completed the questionnaire. Descriptive statistics such as correlation, multiple regression and t-test were used to analyze the information and data of the questionnaire. The bioclimatic indicators (in this study, PMV and PET), which are calculated using weather parameters and individual characteristics, in fact, indicate the conditions of the heat sensation of individuals, and the estimated values for these indicators The actual responses of individuals about their heat feelings were compared and evaluated to validate the level of ability and accuracy of the indicators in the research area. 3-Results and Discussion The results of the statistical surveys showed that there is no significant and significant correlation between the actual data obtained from the questionnaire and the estimated values by the indicators. The correlation coefficient between the output of the indicators and the considerations of the questionnaire for the PMV index, R= 0. 278 and for the PET index, was R = 0. 270, while these correlations were not statistically significant for both indices. Bioclimatic Indicators showed more warming conditions, while the actual data often showed a sense of heat-sensitivity. Investigating the relationship between the data related to weather parameters (temperature, humidity, cloudiness and wind), independent and heat sensation of individuals, showed significant results. Regarding negative coefficients, it seems that cloudy sky with high humidity has been significantly effective in the type of heat feeling stated in the questionnaires. 4-Conclusion Bioclimatic indicators show higher heating conditions, while the actual data often indicate a cooling sensation. On the other hand, the relationship between the data on climate parameters (temperature, humidity, cloudiness and wind), independent and heat sensation of individuals, showed more acceptable results. So that, the presence of cloudy conditions and high humidity along with increasing wind speed has caused the feeling of cooling in people. However, temperature changes alone have not been decisive in this regard. It seems that in the range of the year (April to March) in the study area, more than the temperature changes that control the person's thermal feelings, this change the humidity parameters are cloudy or decisive. The use of various biochemistry indices in many researches, regardless of the environmental and physiological differences that may have outcomes from the reality, is a prerequisite for the application of this indicator to be evaluated and verified in different geographical regions.

The agricultural sector is highly vulnerable to climate change, so that this change is considered a serious threat to the agricultural sector. Considering that the increasing importance of farmers' adaptation to these changes and their adverse effects, the need to study the factors influencing adaptation behavior with climate change is becoming more and more important. The purpose of this study is to investigate the factors influencing the behavior of wheat growers in Kermanshah County toward adaptation to climate change. The study population is all wheat growers' of Kermanshah County (N=30000). A statistical sample is 380 Wheat growers' that are determined by Krejcie and Morgan table. A Multi-Stage Random Sampling is used to select the samples. The data gathering tool is a researcher-made questionnaire, whose face validity is confirmed by two faculty members of Department of Agricultural Extension and Education, Agricultural Sciences and Natural Resources University of Khuzestan and one member of the faculty of Environmental Sciences Research Institute, Shahid Beheshti University. The reliability of the main scales of the questionnaires is examined by Cronbach Alpha coefficients, which ranged from 0. 72 to 0. 89, indicating the tool of study is reliable. The results indicate a significant positive correlation between risk perception, belief in climate change and trust in government institutions with variable growers' adaptation behavior. This means that increasing the variables of perception of risk perception, belief in climate change and trust in government institutions will increase the growers' adaptation behavior. Besides, the results show that the variables of belief in climate change, risk perception, trust in government institutions and trust in experts has effects on adaptation behaviors of climate change. Finally, based on research findings, some suggestions are presented to increase the adaptability of farmers. Extended Abstract 1-Introduction Global climate change is widely viewed as one of the most significant challenges facing society today and is considered to be the main threat to sustainable food security in developing countries. Climate change refers to a variation in temperature and rainfall records, occurring for decades or longer. This phenomenon occurs because of greenhouse gas emissions from fossil fuel combustion, deforestation, urbanization and industrialization. According to the intergovernmental panel on climate change, the evidence suggests that global warming observed for the last 50 years is attributed to human activities. It is estimated that agriculture contributes between 10% and 15% of global anthropogenic ghg emissions including nitrous oxide (n2o), methane (ch4), and carbon dioxide (co2). Given the predictions that the effects of climate change are going to worsen in future vis a vis the need to feed a burgeoning population, there is a need for natural and human systems to adapt across geographical, time and ecological scales to safeguard the already fragile food security situation. One of the ways communities can adjust to climate change is through adaptation. Adaptation to climate change in agricultural production refers to adjustments in farming activities or methods to suit the changes in climatic conditions to lessen the resultant potential damages. In spite of the importance and influence of psychological factors in the formation of perceptions, cognition and behavior of individuals in the context of climate change, there are few studies in Iran regarding farmers' adaptation to climate change and adaptation strategies used by farmers. Therefore, this research aims to investigating the factors influencing the behavior of wheat growers in Kermanshah County toward adaptation to climate change. 2-Materials and Methods In this study, a survey research method was used, and the main tool for data collection was a questionnaire. The study population was all wheat growers' Kermanshah county (n=30000). Statistical sample was 380 wheat growers' determined by Krejcie and Morgan table. A multi-stage random sampling was used to collect data from grower using questionnaire. The data gathering tool was a researcher-made questionnaire, whose face validity was confirmed by two faculty members of department of agricultural extension and education, agricultural sciences and natural resources university of khuzestan and one member of the faculty of environmental sciences research institute, Shahid Beheshti University. Moreover, Cranach alpha reliability coefficients for the pilot study assessment were employed to refine the questions to be prepared for the final questionnaire (0. 72 to 0. 89). To analyze the information, structural equation modeling and statistical analysis methods were used. They were calculated by spss24 and amos22 software. 3-Results and Discussion Regarding demographic variables, the age of the participants is suggested to have a range from 25 to 84 with a mean value of 48. 67 years (s. d. = 12. 47). The sample consisted of 13 female farmers (3. 7%) and 337 male farmers (96. 3%). A Pearson correlation test was used to investigate the relationship between all variables. The results revealed a significant relationship between adaptation behavior and other variables, including risk perception, belief in climate change and trust in government institutions. The trust in experts was not significantly related to adaptation behavior. We analyzed empirical data from the survey with the help of structural equation modeling. Adaptation behaviors was selected as the dependent variable and belief in climate change, risk perception, trust in government institutions and trust in experts as independent variables and entered into the sem. Path relationships revealed that the variables of belief in climate change, risk perception, trust in government institutions and trust in experts has direct effects on the variable positive adaptation behaviors of climate change. Collectively, these variables are capable, 20 percent of the variability adaptation behaviors of climate change. The most effective variable to predict adaptation behavior of farmers in the face of climate change was a belief in climate change that has a direct and significant effect on growers' adaptation behavior. 4-Conclusion The purpose of this study was to investigate the factors influencing the behavior of wheat growers in Kermanshah County toward adaptation to climate change. In this study, the relationship and the effect of five factors influencing the adaptation behavior of wheat farmers under climate change conditions was investigated. The results of this study showed that if farmers in Kermanshah County believe the knowledge and information provided by experts and experts in the agricultural sector as governmental organizations such as agriculture Jihad, their belief in climate change is strengthened. As a result of government organizations, experts can help them to cope with climate change and its effects more easily. On the other hand, the possibility for a better understanding of the dangers of climate change has increased and, overall, the likelihood of pursuing measures that contribute to their adaptation to climate change is rising.

Sustainable management of the forests requires satellite data at a large scale. This research aims to exploit pixel-based image fusion methods including principal component analysis (PCA) transformation, wavelet transformation, PCA/Wavelet transformation to improve the estimation accuracy of the mean height and age of a Pinus radiata plantation using SPOT-5 panchromatic and multi-spectral images at segment level. Therefore, the average height and age of the trees is measured within 61 plots in a Pinus radiata plantation in NSW, Australia. After applying pre-processing on the images, the spectral information including reflectance and vegetation indices along with textural information derived from gray level co-occurrence matrix for four window sizes and orientations are extracted from multispectral and panchromatic images, respectively. The same information is extracted from the fused images. It is shown that the textural information derived from the fused images performs more efficient than the textural information derived from panchromatic images to estimate average height and age. The results indicate that the models derived from PCA/Wavelet-based fused images with estimation error of 16% and 11% for age and height, respectively, perform better than the models derived from the data extracted from the images fused by the other fusion methods. Extended Abstract 1-Introduction Efficient management of the forests, especially those which are commercially important, requires update information about the structural parameters. Having reliable estimation of structural parameters enables estimation of forest productivity, prediction and modeling of the forest tensions, and prediction of environmental problems of the forests. Recently, remote sensing techniques are used as a cost-effective alternative to estimate forest structural parameters. So far, different methods were proposed for image fusion at pixel-level and all these methods are based on transferring the spectral and textural information of the input images to the fused image with the minimum changes. There have been many studies which compared the performance of the pixel-level image fusion methods; however, there are not many studies on the assessment of the fused image for the estimation of forest structural parameters. Therefore, this study aims to assess the capability of SPOT-5 fused images to estimate the average age and average height of Pinus radiata trees at segment level. 2-Materials and Methods The study area is a 5000 ha Pinus radiata plantation in the vicinity of Batlow at New South Wales, Australia. In September 2008, 61 plots were randomly collected at the study area. During this campaign, height and diameter at breast height (DBH) were measured and collected for 978 trees in the plots. The information of the years when the trees were planted was available. Accordingly, the average age of the trees were calculated for each plot and consequently the calculated mean ages were extended to the segments. SPOT-5 panchromatic and multispectral data were used in this study. Dark object subtraction-3 (DOS-3) was applied on multispectral and panchromatic images to reduce the effect of the atmosphere. Then, multispectral and panchromatic data were fused using three pixel-level image fusion methods including principal component analysis (PCA)-based image fusion, wavelet-based image fusion, and wavelet-based PCA image fusion. Afterwards, the spectral and textural attributes were derived from the fused and original images and they were used to fit the models to estimate the average age and average height of the segments. In order to avoid multicollinearity and model overfitting, it was necessary to remove some of the attributes for which the inter-correlation is high. For this purpose, random forest feature selection (RFFS) method was used. After applying RFFS, the attributes which were remained by RFFS were used as input data for multiple-linear regression to develop the models for estimating mean age and mean heights of the trees at segment-level. 3-Results and Discussion According to the results, the attributes derived from the images fused by wavelet-based PCA method performed better than the others fusion methods to estimate average height and age of trees. The main reason for the good performance of the fused image derived from wavelet-based PCA method is that this method improves the spatial information of the multispectral images better than the other image fusion methods. Moreover, it changes spectral information of the fused images less than the other fusion methods, since only the approximation image derived from wavelet-transformed panchromatic data is replaced by the first principal component and the coefficients of this data is preserved. This partial replacement led to the less spectral distortion in the fused image compared to that derived from the other fusion methods. The models derived from textural attributes extracted from the fused images estimated average age and height with higher accuracy compared to the models derived from the textural attributes extracted from the panchromatic image. The type of spectral data used for calculating textural information is very important. The panchromatic data are derived in a wide spectral band and consequently contain less spectral information compared to the fused multi-spectral data with a spatial resolution of 2. 5 m. In the other words, the fused multispectral data inherits spectral data and structural data from multispectral images and panchromatic image, respectively. 4-Conclusion In this research, three pixel-level image fusion methods were compared to identify which result is more appropriate fused image to estimate mean height and age of Pinus radiata plantation. It was shown that the models derived from spectral and textural information of the images fused by wavelet-based PCA method performed better than the other methods to estimate the average height and age. There is not any significant difference among the performances of the models derived from textural information of the images fused by different methods. Moreover, the textural information derived from fused multispectral images, performed better than those derived from panchromatic data to estimate the average age and height of trees.

Part of rural-urban interactions is the flow of people which is considered as a key element. Social life flows into a network of social relations, this network embodies within spatial separation of social groups – the result of accumulation of time, place and social relations. This research investigates the impact of demographic linkages between rural and urban areas on social capital. For achieving this aim, in the first step, the most important indicators of social capital were gathered based on the literature review. Then, according to Cochran formula, 377 questionnaires were responded randomly. The samples of this study were selected radomly from 7 districts and 26 villages located in Damavand, Firuzkoh, and Shemiranat. The main methods to analyze the collected data were network analysis and cross-impact analysis; the results of these methods led to the determination of impacts demographic linkages on creation of social capital. The density index was almost 60% in Damavand, Firuzkoh, and Shemirant. The reciprocity and transferability indices were almost 50% and 60%, respectively. After checking demographic linkage among rural and urban settlements, we analyzed indicators of social capital. We analyzed the results based on the t-test in network analysis framework by UCINET. The results and significance level suggest demographic linkages among the settlements led to social capital at 95% confidence level. Social capital indicator averages (participation and cooperation, compatibility and coexistence, social relations, social identity, trust, and commitment), were higher than average level (almost 3/5 base on Likert Scale) and this result suggests the studied indicators are acceptable. Extended Abstract 1-Introduction Rural-urban interactions can be divided into two categories: linkages across space (such as flows of people, goods, money and information and wastes); and sectoral interactions, which include 'rural' activities taking place in urban areas (such as urban agriculture) or activities often classified as 'urban' (such as manufacturing and services) taking place in rural areas. Rural-urban linkages are important for poverty alleviation and sustainable rural development and urbanization. Strong linkages can improve the living conditions and employment opportunities of both rural and urban populations. Domestic trade and the adequacy and efficiency of infrastructure are the backbone of mutually beneficial rural-urban relationships and the success of the relationship between urban and rural areas. Social life is flowing into a network of social relations, this network embodies within spatial separation of social groups – the result of accumulation of time, place and social relations. Any change in this geometry is required to explore the boundaries of a group and thus it requires serious stimulus to create or exacerbate intergroup competitions or even intergroup conflicts that can make conditions to manage the out-of-control issues. Therefore, social and cultural linkages in regional plans-beyond the logistical and technical importance-have strategic importance and value. 2-Materials and Methods According to Cochran formula, 377 samples responded to the questionnaires. The samples of this study were selected randomly from 7 districts and 26 villages. The main methods to analyze the collected data were network analysis and cross-impact analysis that the results of these methods led to the determination of impacts demographic linkages on creation of social capital. Density (The density of a binary network is the total number of ties divided by the total number of possible ties), reciprocity (A tie is reciprocated if whenever a tie is connected from actor A to actor B then there is a tie from actor B to actor A), transferability, E-I index (E-I index is the number of ties external to the groups minus the number of ties that are internal to the group divided by the total number of ties), centrality (The group degree centrality of a group of actors is the size of the set of actors who are directly connected to group members) and geodesic distance (The length of a path is the number of edges it contains. The distance between two nodes is the length of the shortest path) of population linkages were calculated as the foundations of social linkages based on network analysis. Then, the indicators of social linkages were analyzed by researchers. We used UCINET 6 to analysis data. UCINET 6 for Windows is a software package for the analysis of social network data. It was developed by Lin Freeman, Martin Everett, and Steve Borgatti. It comes with the NetDraw network visualization tool. 3-Results and Discussion Density index was 65/6%, 60%, and 56/6% in Damavand, Firuzkoh, and Shemirant, respectively. The Calculated values show demographic linkages led to strong linkages among urban and rural areas in the study area. This condition has various issues such as employment incentives, leisure like second home tourism or visiting relatives, services and administrative centers. On the other hand, density for the settlements was 22/6% which is due to the weak linkage among rural settlement together. Reciprocity index was 51/28%, 54/29%, and 59/57% in Damavand, Firuzkoh, and Shemirant, respectively. Reciprocity shows that the linkages were beyond of average level in the study area. It suggests a sustainable network of demographic linkages. Reciprocity for the settlements was 52/71% that we must seek its reason in the mutual ties among rural and urban settlements. Calculated transferability was 66/6% for Damavand, 62/3% for Firuzkoh and 61/1% for Shemiranat. These values show weak ties in a group outside that according to Granovetter they can improve social capital. In the study area, transferability was 63% in all, suggesting a sustainable network. In Damavand, E-I index was 17/9%, it was 8/6% in Firuzkoh, and 14/9% in Shemirant. This index was 14/7% in all that suggests internal ties. We can conclude that demographic linkages in urban areas were stronger than rural areas and the population trend is from rural settlements to cities. In the study area, centrality network has 69% output flow and 80% input flow, these values were 38% output flow and 38% input flow in Damavand, 44% output flow and 44% input flow in Firuzkoh and 37% output flow and 47% input flow in Shemiranat. We can conclude that Tehran is Igo in this network. Central nodes can allow people access information and resources. Finally, we settled on Geodesic distance average; this index was 1/34 in Damavand, 1/4 in Firuzkoh, 1/43 in Shemiranst and 1/33 in the study area. It means that nodes were linked by a link, so the distance is very much among the nodes, speed and flow level of demographic linkages is low. It should be noted that the reason for this low level was weak linkage among the rural settlements because other indexes showed dynamic linkages. 4-Conclusion Checking demographic linkage among rural and urban settlements, we analyzed indicators of social ties that are introduced as social capital by social science researches. In this section, the respondents were asked to rank social factors based on the Likert scale. We analyzed the results based on the t-test in network analysis framework. The results and significance level suggest that the demographic linkages among the settlement led to social capital at 95% confidence level. Social capital indicators averages (participation and cooperation, compatibility and coexistence, social relations, social identity, trust, and commitment), were higher than average level which suggests desirability of these indicators.

Evaluation and prediction of sediment transport and associated processes have been one of the main issues of hydraulic and river engineers. There are some variables which affect the amount of bed load of a stream or river which may carry such as hydraulic, hydrological and sediment parameters caused the complexity of sediment transport phenomenon. Furthermore, gravel-bed rivers have features that distinguish them from sand-bed rivers and caused problems and challenges in their analysis. Considering the influential parameters to predict bed load transport rate in 20 gravel-bed rivers, in this study, the accuracy of support vector machine was investigated in different intervals of hydraulic and sediment parameters. The obtained results confirm the superiority of the model with input parameters of Froude number, the ratio of average velocity to shear velocity (), the ratio of hydraulic radius to the median grain diameter () and shields number () with Nash-Sutcliffe efficiency (NSE) of 0. 806. In a second step, the data in different intervals are categorized according to the hydraulic and sediment characteristics using trial and error. Obtained results show that prediction of bed load transport with the median diameters of sediment particles (D50) ranging from 1 to 1. 4 mm led to significant outcomes of NSE= 0. 952, as well as flow condition in the intervals of 0. 65 and 0. 75 of Froude number generate better predictive ability with NSE= 0. 925. Besides, it is found that hydraulic conditions govern the rivers flow in specific intervals of Shear Reynolds number and bed slope of channel led to better predictive ability of bed load transport rate in gravel-bed rivers. Extended Abstract 1-Introduction Evaluation and prediction of sediment transport and associated processes have been one of the main issues of hydraulic and river engineers. Determination of the bed load transport rate in natural rivers is depended on different factors such as hydraulic, hydrological and sediment parameters. Prediction ability of bed load transport is variable due to complexities that governs fluvial sediment transport in different flow conditions. In recent years, intelligent methods have been introduced as a reliable alternative of classic formulas and have been widely used to predict sediment transport rate in rivers. Since intelligent methods are applied for various rivers with different flow conditions, it is necessary to evaluate the accuracy of these methods in quantification of bed load under varied hydraulic conditions. According to this, Support vector machine (SVM) was used as a common kernel based approach to determine influential parameters to predict bed load transport in gravel-bed rivers. In a second step, the applicability of SVM with best input combination is investigated in intervals of different parameters based on hydraulic and sediment properties. 2-Materials and Methods In this study, 966 data points from 20 gravel-bed rivers located in USA were used to predict the bed load transport rate. This dataset covers a diverse set of streams and rivers with different topographic, morphologic, hydraulic and sedimentological characteristics. 75 percent of each river data were selected for training the models and remaining 25 percent of data were used to validate models. The RBF kernel function was used as core tool of support vector machine for all proposed models. After optimization of parameters for kernel function, the bed load transport rate was predicted and obtained results from different models were investigated in terms of correlation coefficient (R), Root mean square error (RMSE) and Nash-Sutcliffe (NSE). in order to assess the capability of SVM in quantification of bed load under varied hydraulic conditions, Froude number (Fr) and bed slope of channel (S0) were selected as a parameters describing the hydraulic conditions and median diameter of the sediment particles (D50) and shear Reynolds number (Re*) were considered as a representative of sediment characteristic. Bed load transport rate was predicted in various intervals of mentioned parameters and obtained results were studied. 3-Results and Discussion The comparison of developed models confirmed the superiority of model (4) in quantification of bed load transport rate. Model including parameters Froude number, ratio of average velocity to shear velocity (V/U*), the ratio of bed hydraulic radius to median diameter (R/D50) and Shields number (θ ) with the highest level of R (0. 898), NSE (0. 806) and lowest value of RMSE (0. 029) for test series showed more precise results. Performing the sensitivity analysis demonstrated the remarkable impact of parameter V/U* in modeling process. Furthermore, obtained results showed that prediction of bed load transport with the median diameters of sediment particles (D50) ranging from 1 to 1. 4 mm led to significant outcomes of NSE= 0. 952, as well as flow condition in the intervals of 0. 65 and 0. 75 of Froude number generated better predictive ability with NSE= 0. 925. According to prediction results of bed load transport in proposed intervals of Froude number, it can be seen that small variations in values of Froude number led to notable effects on accuracy of prediction process. Additionally, stable conditions in transportation of bed loaded with finer particles (median diameter of particles less than 2 mm) caused better predictive capability in compare of transportation of bed load with coarse material. Prediction of bed load with shear Reynolds number between 100-300 yielded better accuracy while changes in river tendency for transportation of bed load with coarser material in shear Reynolds number from 300 to 450 decreased modelling accuracy dramatically. Despite the fact that sediment transport predictions in steep channels are further complicated, the obtained results of SVM approach demonstrated a good performance in prediction of bed load of rivers with relatively high bed slope ranging from 0. 0048 to 0. 0174. 4-Conclusion In this paper, it was attempted to depict the influence of various hydraulic conditions on prediction process of bed load transport rate in gravel-bed rivers. Results revealed that complicated nature of sediment transport under different flow characteristic such as different Froude number and bed slope of channel can even reduce the accuracy of intelligent methods in predicting tasks. Differences between the characteristic of rivers cause different effective parameter in bed load transport at various flow conditions. Therefore, further researches may be carried out to investigate the effective parameters for predicting bed load in different hydraulic conditions using intelligent methods.

Agricultural land use change, agricultural lands abuse and abandonment of farms around the cities are of the most important challenges facing agriculture and rural areas. In recent decades, these changes have resulted different social, economic, and environmental consequenses. Therefore, the purpose of this study is to identify the strategies to prevent agricultural land use change and the optimal use of agricultural abandoned from the viewpoint of farmers. The statistical population of this research was the farmers of Sanandaj city (N=4900). Sample size is determined using Cochran formula (n = 357) and a systematic random method is used for sampling process. The data gathering tool is a questionnaire, which is validated by the experts from Kurdistan's Agricultural-Jihad Organization and its reliability is confirmed during a pretest by Alpha Cronbach test and it is 0. 88. Structural equation modeling is used to identify the strategies to prevent agricultural land use change through confirmatory factor analysis method. The results showed that the strategies for using the abandoned agricultural lands can be divided in four groups: socio-economic, technical-structural, managerial-monitoring, and legal-policy. Based on the results of a confirmatory factor analysis, from farmers' point of view, the most effective solutions are legal-policy and managerial-monitoring respectively. Legal-policy solutions in the research area, Sanandaj, can affect other factors and, in a large extent, prevent the use of agricultural land around the city. Therefore, it is necessary to manage this problem by establishing basic and transparent laws and enforcing binding policies on land uses around the city with serious planning and monitoring. Extended Abstract 1-Introduction City and village, as the foundations of geographic space, have always had mutual or one-sided links and relationships in the form of population flows, goods, capital, ideas and information. The use of rural spaces by urban residents often involves spatial planning and leisure activities, in order to achieve a leisure and psychological burden, which may be the result of tourism activities in rural areas. This phenomenon often prevails in mountainous and bay areas, especially around big cities and metropolitan areas, which has grown significantly over the last few decades. Today, increasing the value of land in rural areas and the formation of new uses, including tourism development, the creation of second homes, industrial development and so on has doubled the importance of attention to the issue of land use and land conservation. For this reason, in Iran, various plans have been developed and implemented, such as land plot planning, urban development, rural land plot planning, and land consolidation in order to organize land use. Agricultural land use change, agricultural lands abuse and abandonment of farms around the cities are of the most important challenges facing agriculture and rural areas. In recent decades, these changes have resulted different social, economic, and environmental consequenses. Therefore, the purpose of this study is to identify the strategies to prevent agricultural land use change and the optimal use of agricultural abandoned from the viewpoint of farmers. 2-Materials and Methods The statistical population of this research was the farmers of Sanandaj city (N=4900). Sample size was determined using Cochran formula (n = 357) and a systematic random method was used for sampling process. In this way, at first, 9 villages were selected systematically out of the 26 villages in central sector of the sanandaj city, then the proportion of farmers was selected considering the population size of each village. The main instrument of the research at the field stage was a researcher-made questionnaire based on theoretical foundations. The questionnaire consisted of two parts: individual or demographic characteristics (including 12 questions), and solutions to prevent land use change (including 39 items). Questions of the second part were in ordinal scale, which were ranked from very low to very high using a Likert's type scale. The validity of the questionnaire was approved by the experts of Kurdistan's Agricultural-Jihad Organization at the state level and the reliability of the questionaire was confirmed by a Cronbach's alpha test during pre-test which was 0. 88. The data processing of 357 questionnaires was performed using descriptive statistics methods such as frequency distribution, percentage and mean, and analytical statistics such as mean compare. Structural equation modeling was used to identify the strategies of preventing agricultural land use change, through confirmatory factor analysis method. 3-Results and Discussion The results showed that the strategies to use the abandoned agricultural lands can be divided in four groups: socio-economic, technical-structural, managerial-monitoring, and legal-policy. Based on the results of a confirmatory factor analysis, from farmers' point of view, the most effective solutions are legal-policy and managerial-monitoring respectively. Legal-policy solutions in the research area, Sanandaj, can affect other factors and, in a large extent, prevent the use of agricultural land around the city. Therefore, it is necessary to manage this problem by establishing basic and transparent laws and enforcing binding policies on land uses around the city with serious planning and monitoring. 4-Conclusion To avoid agricultural land use and the sustainable management of agricultural land, a combination of legal policies and policies should be applied. Among these policies the following can be mentioned: preventing increase the land price along with less burdens for marginal farmers, amending and ratifying new laws to protect and optimize the use of agricultural lands in the margins of cities, unity and integration of management and legislation in the field of agricultural land and natural resources, in particular land abandoned, and the implementation of land surveying. Furthermoreconsidering rural development policies in rural areas face many obstacles and problems such as land consolidation, water supply network, extension training activities and public participation projects, there is a need for more precise planning, monitoring and management in these areas, especially abandoned lands is inevitable.