regression

The purpose of this research is to investigate the temporal and spatial changes of the low-level cloud cover in Iran. For this purpose, ECMWF ERA5 data with a spatial resolution of 0.25*0.25 was used for the period of 1963-2022. Matlab software was used for statistical and graphical operations. By fitting the linear regression model to the parametric method, the trend of low-level cloud cover in the annual atmosphere was investigated, then the characteristics of the low-level cloud cover of the Iranian atmosphere were investigated using analogs. In the analysis of spatial factors with cloud cover, the role of latitude is more dominant than the influence of other spatial factors The results obtained from the trend analysis showed that about 99.7% of the country has a negative annual trend with a decrease of -0.003% of cloud cover per year. And only 0.2% of the country has positive rainfall and increasing cloud cover per year. The results of the analysis of the cycles, which were not evident in other studies, indicate different cycles during the statistical period, some of these cycles can be attributed to local factors, and others to the influence of macro-scale atmospheric systems and neighbors, and sometimes a combination of the two. It has caused diversity in creating different cycles of cloud cover (low level) in one place

Precipitation is one of the elements and complex climatic processes in time and space and is particularly important due to its vital role. In the present study, the analysis of the 60-year rainfall time groups of Iran was done using trend analysis and coefficients. In this regard, ECMWF-ERA5 data with a spatial resolution of 0.25*0.25 was used from 1963 to 2022. First, the country's 60-year rainfall average and change coefficient were investigated, and then the rainfall trend was checked by fitting a linear regression model using a parametric method. Finally, by using spectral analysis, coefficients related to annual precipitation were extracted. According to the research results, the scope of the significant negative trend of precipitation during the statistical period was wider than that of the significant positive trend. About 69 percent of the country has a negative annual trend with a decrease of -0.6 mm of precipitation per year, and 30 percent of the country has positive precipitation and an increase of 0.2 mm of precipitation per year. The negative trend of precipitation generally corresponds to the northwest, north and east areas of the study area, and the significant positive trend corresponds to the high Zagros. The output of the spectrum analysis, which was not evident in other studies, shows the weak role of significant isomers in the northern coastal areas of the country. Also, the southern half of the country is mainly influenced by 2-7 year cycles and the western regions are generally dominated by long-term 7-20 year cycles. Therefore, the patterns related to these cycles can be attributed to local factors, macro-scale atmospheric systems, neighbors and sometimes the combination of all factors that caused the diversity of cycles in one place.

Knowing the flow behavior in the basin is one of the concerns of the watershed managers. That human knowledge, understanding and knowledge of the physical laws governing it is limited in some respects from the point of view of mathematical formulas. Numerous factors are effective in floods in the region, including topographic features, river morphology, rainfall dynamics and human activities. This research was carried out in Hableh Roud Basin. The purpose of this research is to determine the amount of runoff production of different lithology units by identifying the factors affecting sediment production through the regression model in the scale of the rain simulator. The research method is based on field studies and statistical methods. During the field visit, an experiment was performed (on the formations) with a rain simulator with a rainfall intensity of 4 mm per minute with an average rainfall of 10 minutes in three repetitions on the slope surface with a slope of 20%. For each sub-area, environmental parameters and morphometric parameters as dependent variable and runoff production as independent variables were analyzed by SPSS software using multiple regression (simultaneous and retrograde) methods. This test was applied for 21 sub-basins of Hableh River The results showed that retrograde method was the most suitable method. The adjusted coefficient increased from 58.4 in the first stage to 80.5% at the 10th stage. And the effective factors in flood are slope, environment, vegetation and lithology shows the greatest impact.

Soil erosion is one of the serious environmental threats that can affect the political, social and economic aspects of countries. One of the widely used experimental models for estimating the amount of soil erosion is the modified global soil erosion equation known as the RUSLE model. The purpose of this research is to analyze and zonate the amount of soil erosion and its relationship with hydrogeomorphic indicators and vegetation cover of Khiavchai Meshkinshahr watershed in Ardabil province. RUSLE model factors include rain erosion (R), soil erodibility (K), topography (LS), vegetation (C) and protection operations (P). respectively, by using rainfall data, soil texture layer, digital model of height and land use were prepared in the environment of geographic information system (GIS) and after overlapping the layers, the amount of annual soil erosion between 0 and 150.54 tons per hectare per year in The area level was estimated. In the next step, the hydrogeomorphic and vegetation indices that are effective in soil erosion include topographic moisture index (TWI), waterway capacity index (SPI), domain curvature index (Curvatore), section curvature index (Profil Curvatore), surface curvature index (Plan) Curvatore) and Normalized Vegetation Index (NDVI) were created in ArcMap environment and zoning maps were prepared. The results of this research also showed that the topography factor with a correlation coefficient of 0.92% had the greatest impact on the estimation of annual soil erosion by the RUSLE model. In another study, the relationship between hydrogeomorphic indices and vegetation cover with annual soil erosion rate was conducted, and the results showed that normal vegetation cover indices and cross-sectional curvature were the most and least effective with correlation coefficients of 0.57 and 0.05, respectively, compared to other indices.The results of this research confirm the possibility of combining the effective indicators of hydrogeomorphic and vegetation on erosion, as well as the possibility of using other effective indicators and the capabilities of RS and GIS to quantitatively estimate the amounts of soil erosion.

The quality of the urban environment is the social, cultural, economic, and physical-spatial conditions of the urban environment that indicate the level of satisfaction or dissatisfaction of citizens with the urban environment. In fact, the specific aspects of the environment are known as key elements related to the quality of a person's life. In other words, it can be said that the quality of a city's life is directly related to its quality.In this research, the comparative evaluation of the environmental quality of two neighborhoods is based on the morphological and physical components in the form of two components; 1) the quality of the urban texture, which includes criteria such as permeability, compatibility, scale, and aesthetics, and 2) housing quality is evaluated according to indicators such as building form, building age, and building strength.Tabriz, as a metropolis, is not an exception to this rule and faces many environmental issues. The most critical issue in this field is the fundamental and significant difference in the degree of environmental desirability in different areas of this city. Therefore, one of the components that play a role in measuring the quality of the urban environment of Tabriz city is morphological-anatomical criteria.

The current research is based on the purpose of applied type. Data collection was done by field observation method and survey method using a questionnaire tool. The statistical community is the population of 59,560 people in Manjam neighborhood and the population of 41,433 people in Baghmisheh neighborhood; Cochran's formula with a confidence factor of 95% was used to determine the statistical sample, and a total of 382 questionnaires were randomly distributed among the residents of two neighborhoods, based on the percentage share of neighborhoods, 221 questionnaires related to Manjam neighborhood and 161 questionnaires related to Baghmisheh neighborhood. Using Cronbach's alpha analytical model, the validity and reliability of the questionnaire have been estimated, and its value is 0.72, which shows that the questionnaire has acceptable reliability.In order to compare the satisfaction status of the citizens, two neighborhoods were compared using the two-sample t-test and Lon's test. Finally, the relative contribution of the two neighborhoods' morphological and physical components was determined using the multivariate regression method

Morphological indicators of Manjem and Baghmisheh neighborhoods from two dimensions, the texture quality of the neighborhoods from four dimensions (permeability, compatibility, scale, aesthetics) and the housing quality dimension from three factors (aesthetics, building construction age, building strength level) using The observation method and questionnaire results were investigated, described and evaluated. In the following, in order to describe the research findings, the comparison of the environmental quality criteria in bothneighborhoods was discussed. Then, the relative contribution of each sub-index affecting the environmental quality was stated.The results of the questionnaires collected at the level of Monajem neighborhood show that among the existing indicators, the aesthetic index has a medium to high rank in this neighborhood. The rest of the indicators are evaluated as medium and medium to low, and theaverage satisfaction The neighborhood population is estimated to be 2.53 from the morphological and physical criteria.The questionnaires collected at the level of Baghmisheh neighborhood show that the two indices of compatibility and scale have a good rank, and the rest of the indices are also evaluated as medium to high. Finally, the average satisfaction of residents with the morphological and physical criteria in the neighborhood is 3.9.In a preliminary comparison, the level of satisfaction of the residents of Baghmisheh neighborhood is higher than that of the residents of Monajem neighborhood. This high level of satisfaction is noticeable in the indicators of building age and strength, scale, compatibility, and permeability and less in the indicators of form and aesthetics. Of course, regarding aesthetics, the two neighborhoods have almost the same rank.According to the averages obtained from all morphological and anatomical criteria, it can be said that the satisfaction of the residents of Baghmisheh is about 35% more than that of the residents of Manjem neighborhood.

The research results indicate that in Baghmisheh neighborhood, due to the planned structure and the block-blocked neighborhoods, there is a connection between the neighborhoods by local streets, and most of the buildings in Monajem neighborhood have old facades. Therefore, it does not have the harmony of Hedgewar buildings. However, contrary, in the new neighborhood of Baghmisheh, there is good harmony due to the new constructions.In terms of scale, Monajem neighborhood is due to its old construction and is usually one or two stories, and as a result, it has proportionality and scale. Nevertheless, in Baghmisheh neighborhood, due to the new construction, the apartments are harmonious in terms of scale. From the aesthetic side of Monajem neighborhood, there is no eye-catching design due to its historical age, and wall painting in these old neighborhoods has caused visual pollution in this type of neighborhood. However, in Baghmisheh neighborhood of Nobnayad, has a good view, and the painting on the wall is seen a lot in these neighborhoods.In general, it can be said that Monajem neighborhood faces physical, visual, and functional challenges due to its traditional texture in terms of morphological and physical parameters. However, due to the new urban planning, the Baghmisheh neighborhood has fewer weak points from the morphological aspect; it is relative to the Astronomer neighborhood.

Identifying the teleconnection patterns and analyzing their effects on the horizontal structure of circulation patterns can be useful for better recognition and understanding of anomalous climatic events. Temperature, precipitation, and wind, which are the main factors in weather and climatology classifications, are among the parameters whose abnormal increase or decrease can cause irreparable harm and damage to humans, and predicting the abnormalities of these factors can be useful. The teleconnection is as the name suggests; In fact, it deals with the relationship of different climatic parameters in different parts of the world. A significant part of the damages caused by climatic hazards is related to hot and cold waves, destructive floods and violent storms. The term teleconnection is often used in atmospheric science to describe climate links between geographically separated regions. Climatic signals that express changes in temperature and air pressure in the oceans are considered one of the most influential parameters on a global scale on weather patterns, especially precipitation, considering the effect of large-scale climatic factors on extreme events, by examining the effect of these signals on the accuracy of monitoring and forecasting. Floods increase. Atmospheric circulations are very variable. In general, the occurrence of extreme atmospheric-climatic phenomena such as heavy rains and sudden changes have the largest scope of damage to water resources, agriculture and even people's daily life. Having the necessary knowledge of the extent of these phenomena, changes and their prediction will be of great help for more accurate planning in different watersheds, which will reduce the negative effects caused by the occurrence of these phenomena and benefit from their positive effects. These changes lead to the emergence of weather patterns and forms of atmospheric currents that occur on different time scales. teleconnection patterns represent large-scale changes that occur in the pattern of atmospheric waves and rivers and affect the pattern of temperature, precipitation, the path of showers and especially the performance of remote climates in vast territories. During the El Nino-Frein event, the positive sea surface temperature anomalies are more intense in the tropical eastern Pacific Ocean, which causes a significant reduction in the sea surface temperature gradient and, as a result, the weakening of the easterly winds between the tropical eastern and western Pacific Ocean. The purpose of this research is to investigate the relationship between temperature, precipitation and wind anomalies in Mazandaran with Teleconnection indicators. For this purpose, the data of 4 stations of Ramsar, Nowshahr, Babolsar and Qarakhil Qaimshahr were used in the period of 1984-2020. Teleconnection indicators data were obtained from the National Oceanic and Atmospheric Administration (NOAA).

Using the multivariate regression method, the relationships between Teleconnection indices and weather parameter anomalies were investigated. The method used is the backward type, in which all predictor variables that were selected according to the highest correlation coefficient are first entered into the equation and those with lower confidence coefficients are removed one by one from the model. In this research, four-time steps were used: monthly, simultaneous, one month ahead, two months ahead and three months ahead. In most of the indices, which are less related to the surface temperature of the oceans and are subject to pressure changes, the correlation coefficient was often accompanied by a decrease with the increase of the time period. For each month, temperature, precipitation and wind anomalies were extracted in two stages, first by using the (Z) value greater than 0.5 and less than -0.5, and then by applying the 90th and 10th percentile methods. The efficiency of the relationships obtained was calculated through RMSE.

The lowest RMSE with a value of 0.81 and a standard error of 0.85 is specific to the wind parameter in the time step of the same month and from the first method (0.5<Z<-0.5) whose changes have a negative relationship with the CAR index (Caribbean SST Index) and a positive relationship with the indices It has SOI (Southern Oscillation Index), AMO (Atlantic multidecadal Oscillation) and PWP (Warm Pool Pacific). The average correlation coefficients of different time steps for the output data of the first method (moderate to very severe anomaly) are 0.72 for wind, temperature 0.57 and precipitation 0.49 and in the second method (very severe anomaly) for precipitation 0.97, wind 0.86 and temperature 0.68.

AMO, GLBT.s (Global Mean Lan/Ocean Temperature) and SOI indices are the most important oceanic indices of this research in the cold season of Mazandaran. According to the observed changes, there is a significant relationship between the periodic phase change of the AMO index and the Mazandaran wind parameter; So, the correlation coefficient between these two is 0.7.Keywords: Multivariate regression, Teleconnection, anomaly, temperature, precipitation, wind, Mazandaran

Air pollution as one of the most important factors affecting the environment, especially in large cities has caused many problems for residents. On the other hand, green spaces as one of the emphasized elements in urban ecology, play an important role in reducing air pollution. Therefore, studying the type and intensity of the relationship between urban green space and air pollution can show the extent of the impact of urban greenery on pollutants.

Goal:

The main purpose of this study is to analyze the relationship between green space and changes in air pollutants by regions in the metropolis of Tehran with an emphasis on urban ecology.

This research is descriptive-analytical by nature and applied in terms of results and mixed (quantitative-qualitative) in terms of methodology. In this research, the method of interpolation functions in ArcMap 10.7 software and regression analysis in SPSS 21 software have been used. To integrate the current situation of the variables with regression relationship and determine the priority of action by regions, qualitative coding has been done at four levels from high to low.

Geographical area of research:

A case study of the research is the metropolis of Tehran.

The findings indicate that there is an inverse and significant relationship between green space and CO, SO2 and PM2.5 pollutants. With 95% confidence level, the impact of green space on CO, SO2 and PM2.5 pollutants based on Beta coefficient is -0.500, -0.508 and -0.452, respectively. The results of qualitative coding of the current situation of variables with regression relationship show that regions 9, 10, 18 and 21 due to the low level of green space and high concentrations of these pollutants, are in the first priority category to apply suggestions.

The results showed that the presence of green space does not affect the changes in the concentration of all air pollutants. It only affects CO, SO2 and PM2.5 in Tehran. Finally, despite the need for suggestions aimed at controlling air pollutants, the focus of this study is on green space-based suggestions to reduce air pollutants based on the priority of actions by regions. These suggestions are presented in the form of top-down and bottom-up approaches in two short-term and long-term periods.

People migrates for various reasons in order to improve Living conditions.Although scholars disagree about the causes of migration, but in general, the reasons for migration can be divided into two groups: economic and non-economic. In other words, it can be said that economic and non-economic attractions cause migration. Although international migration has attracted more attention in academia, it must be kept in mind that the volume of domestic migration is much larger than that of foreign migration. In Iran, after the land reform and the tendency of central planning to industrialize the country, with the shaking of the rural production system and the prosperity of the oil economy in the city, the migration of rural to the city began and so far most research are concentrated on rural migration to city and the problems created in this process and intercity migration have not been studied; Therefore, the purpose of this study is to investigate the relationship between the attractiveness of cities and the rate of their immigration in Isfahan province between 2011-2016. For this purpose, the economic and non-economic attraction of the cities in the mentioned years was calculated using the gravity model. Then we created a regression relationship between the logarithm of the rate of migration of cities as a dependent variable and the amount of economic and non-economic attractiveness of cities as independent variables. The model was significant at error level of 5% and the coefficient of determination of model was 0.70, which indicates a good fit of the model. The results show that in Isfahan province in the mentioned years, the most important reason for internal migration is non-economic motivations.

Happiness is a person's judgment and evaluation of satisfaction with their quality of life. Studies have shown that there are spatial differences in the Happiness of people between places and regions. Therefore, this study has investigated the state of Happiness and its spatial dependence in rural areas of Torbat-e Heydarieh. The present research is descriptive-analytical in terms of applied purpose and method.Data collection tools were questionnaires and interviews from selected samples consisting of 380 households from the statistical population of rural households in Torbat-e Heydarieh (N = 23105) using Cochran's formula and quota sampling method. Descriptive statistics, Fordyce Happiness Questionnaire, and multiple regression were used to analyze the data and GIS was used to analyze the vigor status of the studied villages in Torbat-e Heydariyeh. The test results and comparison of the means of Happiness obtained from the Fordyce questionnaire indicate that the Happiness of the villages was classified into three categories: low (average scores 320-355), medium (356-365) and high (366-385). The results of multiple regression also showed that out of 18 independent variables related to Happiness, 4 variables were income with a correlation coefficient of (0.399), social capital (0.383), the distance of 5 km from the nearest city (0.599) and distance of 10 to 15 km. It had the highest correlation with the city with a coefficient of (0.452) with the Happiness of rural households. Also, the study of the Happiness map of the studied villages confirms the spatial dependence of Happiness due to the cluster Happiness of the villages.

The results of the study showed that the correlation headley cell and subtropical jet on the atmosphere Iran at the level 200 hPa has a positive correlation with a value of 0.4-0.7 to 35 ° latitude and also regression analysis showed that in latitudes between 15 35 degrees north of the subtropical jet 1(m/s) is higher than normal, although in 2017 up to latitudes 30 degrees north showed an increase of 2(m/s), which had a negative effect on rainfall.

The relationship between Hadley cell and olr in the southern, southwestern and southeastern regions of Iran with a value of 0.4 and the Zagros and northwestern heights of Iran with a value of 0.7 and regression with a value of (w/m2) 0.01 more than normal.

It acts as a tangible source of heat in the middle Wordspehr and the heat is added directly to the middle Wordspehr and causes heating of the upper half of the Wordspehr.

Regression 2 to 1 is shown. Low relative humidity along with the dried air mass is located below the descending branches of the headley cell, which has ruled the drought conditions (-0/7) showed that it creates conditions for lack of rainfall and drought.

Rural and urban interactions are very important in planning and foresight of urban and rural studies. In such a way that the slightest disturbance in this process leads to disruption of order in the levels of spatial structure. The study area in recent decades, especially after the Islamic Revolution under the influence of various economic and social factors and forces, including forces and currents and rural-urban ties and deep and extensive connections with the city of Ahvaz has undergone physical and spatial changes.

In the study, a questionnaire filled out by rural households was used to measure the independent variable (rural-urban relations) and the dependent variable (physical-spatial changes). The rural-urban relations are formed from different flows that each Which are obtained in the questionnaire with different items. Then we measure their role on the transformation of the physical-spatial pattern using the obtained data and the regression test of the effectiveness.

Most of the flow was related to the flow of population, and the movement of residents from the village to the city. Which can be formed for various reasons. And then there are interactions related to health and medical issues. According to the observations, the lack of medical, pharmaceutical and health services can be a good reason to visit Ahvaz.The lowest flow is food and nutrition services, distribution, technical and construction services.

Due to the formation of different currents between the village and the city, being one-sided towards urban settlements and the lack of rural-urban links, especially in the study area of ​​Ahvaz metropolis and surrounding villages, and subsequent developments have been formed.

The knowledge about spatial relationships of vegetation with sediment yield (S.Y) in watersheds is essential for optimal controlling and managing of water and soil resources. The purpose of this study was to recognize and determine the relationship between vegetation cover and annual S.Y of Sabalan catchments, N.W Iran. In this regard, the possibility of presentation of regional S.Y estimation models based on correlation and regression analysis were considered. Independent variables include average, minimum and maximum NDVI (Normalized Differential Vegetation Index), extracted through the processing of Landsa.t 8 satellite imagery in the ENVI environment. The dependent variable, which was the annual S.Y, was obtained through calculations on sediment load data of 10 sample hydrometric stations. Results of correlation test showed that there was a strong and significant relationship between the average NDVI and the annual S.Y in the catchments (r = -0/758). This inverse relationship emphasizes the importance and apparent role of vegetation in reducing sediment production and transporting in the region. Moreover, the results of regression tests showed that is possible to present the regional estimation models regards to annual S.Y by fitting linear, quadratic and power functions. In this regard, the quadratic model has the highest performance and explain 75% of the annual S.Y variance. The linear relationship was also able to explain 57% of the annual sedimentary variance.

The rapid growth of population in the world, especially in developing countries, has led to many problems. Issues that, more than anything else, have led to the physical expansion of cities, the decline in the quality of the urban environment, and instability.in 2012, UN-Habitat a new approach to urban development. A holistic and integrated approach to promote welfare and play a public role. This new approach helps cities better manage the city's future in the economic, political, social and environmental spheres. This approach, called urban prosperity,A prosperous city is one that provides productivity, infrastructure, quality of life, social inclusion, and environmental sustainability.On the other hand, in many cities, the degree of social stability of citizens and urban areas depends on the indicators of urban prosperity prevailing in those areas.A sustainable city achieves a dynamic balance between economic, environmental and socio-cultural components.Accordingly, in this study, urban prosperity and social sustainability as well as the effect of urban prosperity on social sustainability in Khorramabad are investigated.

The research method is descriptive-analytical in nature and applied in terms of purpose. Research data were collected in two ways: documentary and field.The statistical population of the study is the residents of Khorramabad, which was selected as a sample size using Cochran's formula of 364 people by simple random method.Questionnaires were designed according to the number of population among the residents of 24 districts of Khorramabad.Multivariate t-test was used to measure the variables of urban prosperity and social sustainability and multivariate regression test was used to evaluate the effect of urban prosperity indicators on social sustainability in Khorramabad.

The results showed that the indicators of prosperity in the city of Khorramabad are moderate. The value of the test in the research variables is 3 and the average of the infrastructure and environmental sustainability index variable according to Table 3 is more than 3. In this regard, the average index of productivity, quality of life and social inclusion is less than 3. Therefore, according to the significance level, which is less than 0.05, it can be said that the situation of urban prosperity in terms of infrastructure and environmental sustainability indicators is moderately to high. In terms of productivity, inclusion and social inclusion, the status of urban prosperity is evaluated downwards and the mean of the quality of life index variable is less than 3 because the lower limit is negative and the upper limit is positive, so the average value obtained by the test is (3). And there is no significant difference between them. Therefore, it can be said that the situation of quality of life index in Khorramabad is evaluated as moderate.On the other hand, the results of measuring urban sustainability indicators were also evaluated at an average level. Given that the value of the test in the research variables is 3 and the average of the social stability index variable is dependence coefficient, social interaction, social capital status, honesty in social behaviors and participation in local activities according to Table 4, so It can be said that the social stability of these indicators in the city of Khorramabad is assessed as above average. In this regard, the average of the variables of responsibility and civil or institutional trust according to the table is less than 3 because the lower limit is negative and the upper limit is positive, so the average value obtained by the test is equal to (3) and there is no significant difference between them. Therefore, these variables are evaluated as average. Also, the variables of satisfaction with the level of access to services, sense of belonging, interpersonal trust, hours of volunteering, transparency, insurance, social justice and education and research according to the table are less than 3 because the lower and upper limits are both negative. And the significance level is less than 0.05, so the mean obtained is less than the value of test (3) and there is no significant difference between them. Therefore, the status of social stability of these variables in the city of Khorramabad has a low status.On the other hand, the spatial distribution of urban prosperity scores and social stability at the district level indicates the correlation (r = 0.873) between these two concepts. In other words, the areas that had a higher or lower than average score in terms of prosperity, mainly in the field of social sustainability, had the same procedure. Also, based on the results of linear regression, productivity indices with 0.383, quality of life with 0.352, infrastructure 0.297, environmental sustainability 0.204, and social inclusion with 0.186, respectively, have had the greatest effect on social sustainability.

The results of the tests show that the concept of urban prosperity, which has been mentioned by the international community, has a challenge in the city of Khorramabad. This challenge arises from at least two cases;1. Low level of score of some indicators from the middle level such as productivity and inclusion and social inclusion;2. Imbalance and harmony between the dimensions (wheel blades) of prosperity. The results showed that the indicators of prosperity in the city of Khorramabad are moderate. On the other hand, the results of measuring urban sustainability indicators were also evaluated at an average level. However, changes in the indicators measured at the area level are tangible. On the other hand, the spatial distribution of urban prosperity scores and social stability at the district level indicates the correlation (r = 0.873) between these two concepts. As in the case of areas with higher or lower than average scores in terms of prosperity, mainly in the field of social sustainability have had the same procedure. Also, based on the results of linear regression, productivity indices with 0.383, quality of life with 0.352, infrastructure 0.297, environmental sustainability 0.204, and social inclusion with 0.186 had the most effect on social sustainability, respectively.

The idea of ​​resilience of different social, economic, physical, and managerial orientations has entered urban and regional studies on a large scale. This resilient system can absorb temporary or permanent crises and adapt to rapidly changing conditions without losing its function. Among these, resilience against natural disasters can be explained by how social, economic, institutional, political, and executive capacities of societies affect the increase of resilience and understanding of its dimensions in the society. Environmental crises, such as earthquakes, floods, fires, and climate pollution, have caused environmental vulnerability in cities and consequently created threats to their securities, especially in District 20 of Tehran City. By recognizing the dimensions of vulnerability in District 20 of this city against environmental crises, management strategies can be developed to reduce vulnerability and risks and enhance resilience. For this reason, the main purpose of this study was to evaluate resilience of the neighborhoods in District 20 of Tehran City against environmental crises. To achieve this goal, the Fuzzy Multi-Criteria Decision Model (FMCDM) and K-mean method of classification were used.

To identify and assess the resilience of District 20 of Tehran against environmental crises, a database was created based on the crises and its spatial information was prepared in 4 criteria and 26 sub-criteria. After creating the spatial database of the mentioned district and compiling the criteria and sub-criteria, a layer of information was prepared in ArcGIS software and a distance map was drawn for each sub-criterion through Euclidean distance mapping in order to measure and manage the resilience. Then, fuzzy operators were applied to draw each fuzzy map (subscale) with a value between 0 and 1. Analytic Network Process (ANP) method was utilized to weight and evaluate the research criteria and sub-criteria. Next, the map of each criterion and sub-criterion was drawn by combining the Euclidean distance and fuzzy operators multiplied by their fuzzy weights obtained from the ANP model in ArcGIS software. Thus, the final map was prepared for each criterion and sub-criterion, which showed their values of resilience to the environmental crises. Then, fuzzy superimposing operators were applied to superimpose the fuzzy weighting maps and a superimposed map of 26 sub-criteria (4 criteria) was obtained for each fuzzy operator. To identify the best fuzzy operator by superimposing the research sub-criteria, analysis of spatial relationships between the independent variables and the dependent variable was done through the Ordinary Least Squares (OLS) regression. Finally, the classical K-mean clustering method was employed to classify the neighborhoods from the perspective of resilience to environmental crises.

The results showed that the weights and values of the socio-economic criteria, road infrastructure, land use and accessibility in resilience measures were 0.49, 0.23, 0.16, and 0.11, respectively. In the socio-economic, road infrastructure, land use, and accessibility criteria, the sub-criteria of house strength, pedestrian bridge, access to social places, and access to medical centers with the weights of 0.33, 0.43, 0.32, and 0.29 had the highest values in resilience. Among the fuzzy superposition operators, the algebraic addition operator (SUM) had the highest correlation with the research criteria in identifying the resilience of the neighborhoods. The northeast and southeast neighborhoods, as well as the central neighborhoods of District 20 of Tehran, were the most resilient neighborhoods to environmental crises. In the final step of the current research, the classical K-mean method was used to cluster the existing neighborhoods in District 20 of Tehran City based on their resilience to environmental crises. The results revealed that the neighborhoods were divided into 3 clusters. In the first cluster showing a lot of patience, the neighborhoods of Javanmard Qassab, Mansouria and Mangal, Hamzehabad, Sartakht, Ibn Babavieh and Zahirabad, Taghiabad, and Abbasabad were located. In the second cluster indicating moderate tolerance, Dolatabad and Shahadat, Sadeghieh, Shahid Ghayuri, Deilman, Aqdasiyeh, Estakhr, and Alain neighborhoods were situated. Finally, the neighborhoods of Sizdeh Aban, Shahid Beheshti, Firoozabadi, Valiabad, and Hashemabad were located in the third cluster with poor productivity.

Environmental crises, such as earthquake, flood, drought, air and water pollution, and fire, have the potential to become harmful in areas where there are no crisis management and risk mitigation. In the 21st century, the world has been hit by such environmental crises as Asian tsunamis, Hurricanes Katrina and Rita, successive earthquakes, flash floods, desert dust storms, and widespread fires. Although predictive tools are able to predict some disasters, future crises cannot be forecast based on empirical evidence. Therefore, increasing the ability of a system called resilience is very important for responding to such crises; yet, its resilience must first be measured. In the present study, the resilience of District 20 of Tehran City to environmental crises was evaluated based on socio-economic, road infrastructure, land use, and accessibility criteria. The results of this modeling led to the extraction of 3 clusters for the resilience of the neighborhoods of District 20 of Tehran against environmental crises. The neighborhoods in the west region had the highest resilience compared to the urban areas.

Gully erosion is considered to be one of the most destructive and complex types of water erosion. The gully is a stream with steep slopes and active erosional forehead which has been routinely created by erosion due to the alternating surface flow during intensive rain or after it. Gullies are deep canals that are not destroyed by normal plowing, but temporary gullies in agricultural fields, such as ravines, are so small that their repairing is possible by usual plowing. Formation and expansion of gully erosion are influenced by various factors such as physical properties and distribution of its forming particles and amount of salts in the soil and geological formations. Incorrect using of land and changing land use, excessive grazing, lack of correct management of agricultural lands, plowing in the direction of slope, road construction and mining in basins also lead to dredging. The purpose of this study is to investigate the physical and chemical properties of soil and morphometry of gullies in order to identify and control this type of erosion to proper regional planning and actions of water management to control and reduce the damages caused by soil erosion in line with sustainable development goals in the study area.

 It was used from the library documents, topographic maps with the scales of 1: 25000, 1:50000 and the geological maps of 1:100000 of the area for primary identifying of the natural features of the basin. Then 10 samples were selected from identified gullies with surveys and measured the morphometric characteristics of the gullies including the length, width and depth of them. 10 soil samples were collected, transferred to the soil laboratory for analyzing and measured for the specimens. The Pearson coefficient of correlation and regression analysis were used to investigate the correlation between dependent and independent variables. Regression analysis is a statistical process to estimate the relationship between variables, how the amount of the dependent variable changes with the turn of each independent variables and fixing other independent variables.

The morphometric features include the average depth, width, length and volume of the gully. According to the table data (2), the average length is 67/3 meters, width is 3/43 meters and depth is 2 meters which is from small and little depth of the gullies. The volume of the gully is correlated with other variables, which has the highest correlation with EC with the amount of (./796). The correlation between sodium and electrical conductivity with the growth of the gullies is positive. The reason of this, is the release of sodium in the replacement of calcium or potassium, and the increase of soil propagation and the spread of its particles, and provides the field of the development of gully erosion. Accoding to the obtaied results of creating of regression relations between the volume of gullies with soil features, it is seemed that there is a significant correlation in the surface of 95% with high correlation coefficient, which indicates the high soil propagation property in the location of gullies and the formation of gully erosion .Different factors influence in creating and expanding the gullies that physical and chemical characteristics of the soil are very important among them.

 The obtained results of gullies’ morphometry by regression methods show that the volume of the gully is correlated highly and directly with its depth as among the morphometric parameters, (the width, depth, length and volume of the gully) the depth and length of the gully have more relation with its volume and the amount of wasted soil. The obtained results of the correlation between gully volume and soil properties (PH, electrical conductivity, organic matters, sodium, calcium, magnesium and lime) showed that the volume of gullies is increased by decreasing PH, organic matters, lime and potassium.  This means, these parameters have a significant correlation with the volume of the gullies in the opposite direction. The correlation between the volume of the gully with the sodium parameters and the electrical conductivity is positive, and being high of these parameters causes the soil spreading and expanding of the volume of the gullies. The correlation between the expansion of the gullies is also positive relation with electrical conductivity, as by increasing solutes in the soil, the volume of the gullies is also increased.

Predicting and obtaining information about stream flows is vital for many practical applications such as water allocation, long-term planning, catchment management operation, flood forecasting, optimization of hydropower production, designing hydraulic structures, and so on. On these accounts, experts have always attempted to accurately estimate river flows and provide contributions to the existing methods. It is possible to establish a relationship between discharges of catchments based on sufficient statistics and their geometry characteristics by using regional analysis and multivariate regression in a relatively homogeneous region in order to estimate discharges of the catchments without statistics or with insufficient statistics in that region. Owing to the need for a better modeling of water discharges in terms of seasonal variations, the present study tried to regionally estimate the monthly mean, minimum, and maximum discharges in Kashfarud Watershed based on geomorphometric variables in order to: (1) examine the possibility of scientific and useful generalization of surface water quantity in the whole watershed and (2) identify and determine important geomorphometric factors influencing the water discharge variations of Kashfarud sub-watersheds. Kashfarud as a vital flow in this region, including Mashhad plain, has played an important role in supplying water to the inhabitants of Mashhad metropolis and other surrounding cities such as Chenaran and Torqabeh. Besides, extensive engineering facilities, such as Golestan, Torogh, Kardeh, and Ardak dams, have been built on the tributaries of this river. 

The research was grounded upon statistical analysis, including correlation and regression tests. For this study, we made use of monthly average (low, medium, high) discharge data and resolution of 30-m DEM. The discharge data were measured in 10-gauge stations of 10 sub-watersheds over 20 year (1997-2017). In this regard, we considered the monthly discharge values ​​of 10 stations located in 10 sub-basins during the water years of 1997-2016. The research proceeded as follows: after selecting the common statistical period, we calculated the monthly average flows recorded in the stations over 20 years. Next, 2 months with the highest and lowest flows were selected in each station. Also, we considered the values ​​of the two selected months besides the average monthly discharges in the stations (average of 12 months) as the dependent variables. Afterwards, we embarked upon to calculate the independent geomorphometric variables (16 variables), which were determined by using DEM in the GIS environment. The independent variables included perimeter, area, minimum elevation, average elevation, maximum elevation, elevation range, average slope, maximum slope, main stream slope,  main stream length, total stream length, drainage density, Schumm’s roughness index, Gravilius coefficient, elongation, and concentration time. After calculating the values ​​of the 3 dependent and 16 independent variables for each station, we tested them based on a two-way correlation to find out which variables had a significant relationship by means of the correlation matrix. The significance level of the correlation relationships was ≤0.05. Finally, we  presented an estimate model of the dependent variables via the independent variables. This was done based on the dependent and independent variables that had significant correlation relationships.  

The results of the correlation analysis showed no significant relationships between the minimum monthly discharges and the independent variables.  This was probably due to the dryness condition and small variance in the low monthly discharge rates among the sub-watersheds. In contrast, significant relationships were obtained among the monthly mean and maximum discharges and 6 geomorphometric variables including the average elevation, maximum elevation, elevation range, average slope, drainage density, and roughness ratio. The correlation coefficients of all significant relationships were above 0.6, indicating a close and strong relationship between these variables. The direct correlation of altitude, slope, and roughness with monthly mean and maximum discharges indicated that on the one hand, the monthly discharges of the sub-watersheds were strongly dependent on the altitude variables dominating the other environmental factors while on the other hand, the roughness intensity and active dynamics associated with the variables of altitude played an important role in water flowing and transporting from upstream to downstream of the catchments so that the speed of hydrological responses of the catchments increased by the rise of roughness severity. In contrast, the negative correlation between the drainage density and the dependent variables was unexpected and probably associated with hydroclimatic conditions indicating characteristics of the dry and geologic conditions, permeability of some formations, and presence of joints and fissures in the rocks. The predictive regression models of the monthly mean and maximum discharges had good accuracies and efficiencies and could explain 80 and 90% of variances of the monthly average and maximum discharges, respectively. 

Modeling the spatial variations of discharges in watersheds requires consideration of hydrological limit values both daily and seasonally, along with normal and average values. By adopting such an approach, the present study aimed at modeling monthly water discharges in Kashfarud sub-watersheds based on geomorphometric variables. The multivariate regression analysis among the independent variables including the average and maximum monthly flows and 16 independent geomorphometric variables revealed that the regression models could be obtained through the variables of average elevation, maximum elevation, elevation range, average slope, drainage density, and roughness ratio. These factors could explain the major parts of variance of the independent variables. It is possible to generalize the monthly mean and maximum discharges achieved in this study to other sub-watersheds through the resulting models with respect to the low estimation errors and high accuracies. However, generalization the monthly minimum discharges is not possible due to the lack of a significant correlation between this variable and geomorphometric variables. It is necessary to estimate the monthly minimum discharges in Kashfarud Watershed by reconstructing and converting the data or extending other predictive models. Reliable estimations of low water discharges provide us with information about water supply for the environment and water quality management for sustainability of healthy ecosystems. Also, owing to the role of small mountain catchments in the occurrence of peak flows, prioritization of watershed management measures in such catchments is incumbent to reduce the risk of floods. 

Biogeomorphology, defined as the two-way interaction between geomorphology and ecology in different scales. Every landform is comprised of several micro-scale landform units such as peak, ridge, shoulder, etc. landform units can create various microhabitats and enhance heterogeneity in ecosystems. This information is obtained by extracting patterns from plants, processes, and landforms in the landscape. Differences in landforms are followed by differences in biological factors (type of cover, plenty, pattern, density) and non-biological factors (form, soil, geological, climatic). One of the important factors is the chemical and physical properties of the soil. Because soil not only provides the environment, water, and minerals for the plant but also affects the pattern and distribution, type, and dynamics of the plant. Soil properties in landforms cause changes in pattern, density, and vegetation composition. So, soil properties are influenced by vegetation at smaller spatial scales. Small-scale landform patterns play a major role in determining the plant distribution pattern and are a good tool for evaluating Macro-scale bio geomorphological relationships.

The variables examined in this study include the type of landform element, height, chemical and physical properties of soil, and vegetation characteristics (pattern and density). We tested the hypothesis that landform unit features to determine the spatial distribution of vegetation patterns in the case study. This study was aimed to determine the relationship between vegetation properties (vegetation pattern and density) and landform unit type and soil characterize in Hablehroud. Hablehroud basin, that is located between 35°16' 6"- to 35°57' 22" North latitude and 52°15'43" to 53°-8'-53" East longitude (the area about 3200 square km) Between Semnan and Tehran provinces. Our study is based on remote sensing coupled with field observations and laboratory studies.We prepared geomorphic classification of landform unit, vegetation map, and Eco geomorphology map. Using the Geomorphon method of landforms shows the geomorphon-based maps of landforms. Based on geomorphon technique Classification used DEM 12.5 M resolution in SAGA7.5. Geomorphon map includes most common landform elements. In the next step, the vegetation map of the area was prepared using the vegetation index (SAVI). All calculations were performed in ENVI.5.3 software in the next stage after the matching of these two maps; a new Eco geomorphological map was prepared. Where landform-plant units were identified. A field survey was conducted from Jun to July in 2020. We plotted a total of 40 stands within the four micro-landform units in the study basin According to field surveys, and the percentage of vegetation cover four units were identified. Soil samples were collected from a depth of 20cm for all 40 plots (1×1m) some physio-chemical analyses were conducted on them including (PH, EC, wetness, Organic, Texture). According to google earth, field survey, CAD software four types of vegetation patterns includes (spot-dense, gap-dense, spot-scatter, gap-scatter) were identified for each plot. Statistical analyses were calculated using Minitab18 software. We investigate the significance and correlation, principal component analysis, and stepwise regression.Results and discussion Geomorphon map includes the 10 most common landform elements: peak, ridge, shoulder, spur, slope, hollow, foot slope, valley, pit, and flat obtained from 498 patterns. In the geomorphon map, a pattern of various landscapes has been created. The vegetation index (SAVI) of the area was prepared using Landsat8 – July 2020. The map of eco- geomorphological units includes four types of geomorphon: Slope, Hollow, Foot slope, Spur which are extracted with dense to scattered vegetation. Field studies of soil sampling have been done to measure the physical and chemical properties of the soil, plot and photograph the plots to extract plant characteristics (pattern and density). Four patterns were extracted: dense point, dense gap, scattered point, and scattered gap for 40 plots. After data collection, type of landform, height, soil properties (chemical and physical) and vegetation (pattern extraction and density) for statistical analysis and analysis of biogeomorphology in Minitab18 including correlation, factor analysis, and multivariate and stepwise regression has been.

showed that there is a significant relationship between the type of landform and density and pattern of vegetation. Among four landform unit which includes (hollow, foot slope, slope, spur). Foot slope and Hallow have the highest density and spot-dense pattern. The correlation between pattern and vegetation density with soil moisture and landform unit type is significant with value (p <0.003) and landform type with value (p <0.007). The value of R2 indicates that the predictor variables explain 72.32% of the variance in the vegetation pattern of the sign. The results of regression equations showed that vegetation pattern as a dependent variable is influenced by the four variables, first landform type, and wetness, organic, sand percentage. Regression model 70.50% of the variations in vegetation pattern was related to these four variables. Because landform units have a direct and indirect role in other factors of plant growth and distribution such as moisture absorption, heat, amount of organic matter, erosion, soil texture, and activity of microorganisms. Each of the landform units, according to its shape and characteristics, plays a role in the pattern and density of vegetation. The domain landform generally has four extraction patterns (spot-dense, gap-dense, spot-scatter, gap-scatter) in the study area. The differences in landform-unit area, climate, and topographic features show different patterns of vegetation distribution. The pattern and density of vegetation in the spur are often scattered and in the hollow and the foot slope are spot dense, which is due to the morphometric and topographic features of the units.

The results showed that changes in plant distribution patterns are well related to landform type and soil properties. In this study, four types of landform elements (hollow, foot slope, slope, spur) along with chemical and physical properties of soil about the pattern and density of vegetation were analyzed. So that the type of vegetation pattern has a positive correlation with the amount of sand, PH, EC and has a negative correlation with the rest of the variables. The results of the factor analysis and regression model showed that approximately 69 to 70% of changes in vegetation patterns could be predicted by the variables mentioned in the study. Among the independent variables of landform unit type, Soil moisture, Organic matter, and Height have a significant relationship with the dependent variable and state that different patterns of vegetation in different parts of the Hablehroud basin are related to landform type, height, and different soil characteristics. The effect of landform elements is quite different depending on how much it is affected by soil properties. About vegetation, the most spot-dense pattern at the foot slope, hollow, the slope, and the least occurred in the spur. The spot-scatter pattern had the biggest portion on the slopes, the spur, the hollow, and the foot slope. Gap-scatter pattern, the portion of slopes was higher than other landform elements, and the spot-scatter pattern had the least repetition on the desired landform elements, which is generally observed in the slopes.Therefore, the effects of geomorphic processes of vegetation characteristics are inevitable.

One of the most important events in the tourism industry of each country is the demand for a product or destination of tourism. There will always be distances and deviations between actual and predicted values, but the use of scientific and modern methods of forecasting will cause the results to reach far more than an objective estimate to the truth. In recent years, with the changing pattern of holidays and the formation of short-term holidays, cities have found the opportunity for tourism development. One of the most important types of domestic tourism in Tehran, based on the statistics of the National Center of Statistics and the views of the experts in this area, is business tourism. For this purpose, the present study seeks to propose models for forecasting effective variables on forecasting domestic business tourism demand in Tehran. To do this, information was used between the years 2001 to 2015. Independent variable of this study is the number of domestic Business tourists in Tehran, and dependent variables were selected based on Delphi and Fuzzy DEMATEL techniques. The model framework is a combination of regression, fuzzy neural network, and SVR algorithm, which combines these methods to measure forecast errors and compare the methods. The results of this research show that the proposed hybrid approach of regression and Adaptive Neuro-Fuzzy Inference System (ANFIS) can have better prediction than other methods for forecasting domestic Business tourism.

Flood is a natural phenomenon, which threatens the life and properties of a large number of people all over the world, yearly. Flood discharge, regarding water resource exploitation, flood control, construction of dams, basin management, and hydrologic studies, is of high importance in studies. Therefore, the accuracy of these studies and the safety of waterworks and water structures depend on the methods of studies to a large extent. It is impossible to manage water resources in basins without the accurate determination of the peak flood discharge. The advances in flood estimation techniques have made it possible to use rainfall-runoff models to assess the hydrographic properties of the flood in watersheds and decrease the risks of the flood. In studies on water resources, it is of high importance to determine the flood discharge of different basins. Studies of Dile and Srinivasan (2014) and Hoseini et al. (2017) showed that basin level and rainfall can be the most important factor in runoff flow. Consequently, proper simulation and modeling of flood runoff are the important parameters in flood management in the region. However, it is necessary to use new models to determine flood hydrograph parameters. So, this study aimed to determine the peak flood discharge of the Darrehrood basin using regression mode for return periods of 10, 25, 50, and 100 years.

Darrehrood basin is located in Northwest Iran. The basin is surrounded by mountains and is considered the main basin of Ardabil Province. It lies within 47°30' to 48°55' longitude and 37°45' to 39°42' latitude. Its area is approximately 12900 km2. Discharge data were collected from 16 hydrometric stations with a statistical period of 15 years during 2001-2015. Incomplete data related to stations were completed using statistical methods and considering the best statistical distribution of floods in the studied sub-basins, floods with different return periods were calculated then the physiographic characteristics of sub-basins that affect flood rate include: area, slope, shape factor,height average, concentration-time, and curve number achieved using ArcGIS and WMS (watershed modeling system). To evaluate the model, maximum error (ME), root mean square error (RMSE), relative percentage error (ε), mean absolute error (MAE), coefficient of determination (R2), Coefficient of residual mass (CRM), and model efficiency (EF) were used.

The model calibration results showed that the simulated peak discharge and flow volume are in good correspondence with the observed values, so that, the lowest goodness of fit (R2) value in the return periods of 10, 25, 50, and 100 years were estimated to be 97, 96.6, 95.8 and 94.7 %, respectively. The results showed that the linear regression model with very good accuracy can predict the peak discharge in the sub-basins in Darrehrood using the physiographic parameters of the basin and with increasing the return period, the accuracy of the model is slightly reduced. Model evaluation indicators for the return period of 100 years include root mean square error (RMSE), relative percentage error (ε), mean absolute error (MAE), Coefficient of residual mass (CRM), and model efficiency (EF) were calculated 40.75, 52.12, 0.52, 0.92 and 0.62 respectively. Cross-validation diagrams showed that all models were partially underestimated and the scatter of points around the one by one axis was very suitable for the whole return periods. According to the paired t-test of the difference between predicted and actual values in different return periods in the level confidence of 1% are not significant.

The results of this study show that the model has good accuracy for estimating floods in sub-basins of Ardabil province.

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.