ebrahim omidvar

Vegetation is a universal and effective method for water and soil conservation. The significant implications of soil loss necessitate the adoption of appropriate soil conservation practices and soil management solutions according to the regional climate. Investigation of the effects of soil cover on the soil erosion process can provide the information necessary for the success of soil and water conservation practices. In general, vegetation cover can mitigate runoff by increasing water infiltration, enhancing sediment trapping, reducing the kinetic energy of raindrop impact, increasing surface roughness, decreasing flow velocity, and controlling runoff hydraulic properties. The impact of vegetation cover on runoff generation has been studied at different spatial scales, from experimental to watershed scales, and most studies have shown the effectiveness of vegetation cover in reducing surface runoff. In arid regions, it may be difficult and economically infeasible to cover the entire surface area of a soil conservation project with vegetation. Therefore, the question arises as to how much of the soil surface should be covered to have an optimal impact on runoff generation. The main objective of this study was to evaluate the effects of different ratios of alfalfa coverage on runoff generation under simulated rainfall conditions.

A completely randomized design was used with treatments based on the ratio of alfalfa coverage (0, 35, 65, and 90 %) under artificial rainfall conditions. The texture of the studied soil was sandy loam and collected from the surface horizon of farmlands in Kashan. All experimental plots were 2 m long, 0.55 m wide, and 0.35 meters deep with a metal runoff collector. Alfalfa seeds were planted at a spacing of 15×15 cm in the 35 % plot, 10×10 cm in the 65 % plot, and five in 10 cm in the 90 % plot. All plots were subjected to a simulated rainfall with an intensity of 90 mm hr-1 for 70 min. To achieve uniform antecedent moisture conditions, all plots were subjected to a 10-minute long simulated rainfall at an intensity of 90mm h-1 exactly one hour before the experiment.During the experiment, the runoff and sediment samples were gathered using the metal collector (placed at the plot outlet) at 5-minute intervals. In order to investigate the changes in runoff reduction efficiency in different treatments and different testing periods, statistical criteria of runoff reduction efficiency were used. The Kolmogorov–Smirnov, one-way ANOVA, and Duncan’s tests were used for data analysis.

The results indicated that the plant cover treatments were most effective in reducing runoff during the first 15 minutes of the experiments. However, their effectiveness decreased as the experiments progressed due to the soil's inability to pass water at a higher rate once the infiltration reached its final rate. The coverage ratio treatments (0, 35, 65, and 90 %) showed a significant difference in runoff generation (p <0.01). The bare plots had the highest average runoff generation and were classified into a separate group (a). The plots with 35, 65, and 90 % coverage ratios had average runoff rates of 0.329 mm min-1, 0.222 mm min-1, and 0.112 mm min-1, respectively, and were placed in separate groups as well. In the bare soil treatments, the high amount of rainfall drops on the soil surface without vegetation interception exceeded the infiltration rate and subsequently produced runoff. Additionally, soil sealing and crusting processes due to raindrop impacts could reduce infiltration and generate higher runoff. The effectiveness of runoff reduction was also evaluated at 35, 65, and 90 % alfalfa cover. The results showed that 65 and 90 % cover significantly reduced runoff production, but no significant difference was observed between the 35 and 65 % levels.

In this study, we evaluated the influence of alfalfa coverage ratios on runoff generation in experimental conditions subjected to artificial rainfall. We found that higher coverage of alfalfa was associated with a delay and reduction in runoff generation. While all the examined vegetation cover percentages demonstrated an acceptable performance in reducing runoff and sediment. Furthermore, we were able to determine a practical threshold for coverage ratio, which could result in a significant decrease in surface runoff production. We found that a minimum of 65% alfalfa coverage was necessary to achieve this reduction. This threshold could be considered a beneficial criterion for soil and water conservation practices, especially in arid areas where dense vegetation establishment can be difficult and more expensive. This study is also particularly important for dry and semi-arid regions that face challenges of drought and soil erosion. The use of alfalfa as a vegetative cover can help to conserve soil moisture, reduce erosion, and improve water quality in these areas. In addition, vegetation plays a crucial role in soil and water conservation, and alfalfa, being a perennial plant with a deep root system, is a suitable option for erosion and runoff control in various regions, especially in dry and semi-arid areas.

Measuring the amount of runoff and soil loss per unit area is very important to evaluate the condition of erosion in different areas. The runoff is caused by the condition of the upstream watersheds, which has a different response in different time and space ranges of a watershed. Some hydrological responses may be considerable in the upstream areas of a basin, but the same responses cannot be identified in the downstream. These different responses among different regions are referred to as the scale effect, including the mismatch among runoff responses at different scales. In this context, the role of spatial scale is considered as a factor that directly affects the occurrence of various processes of runoff production. Therefore, assuming the uniformity of discharge changes on different scales leads to the application of a single plan and management strategy for the entire watershed area, which ultimately results in the failure to achieve the desired outcomes. On the other hand, an accurate estimation of the discharge status of watersheds provides a correct understanding of the underlying hydrological processes. Comprehending the accurate influence of spatial scale on runoff is essential for precise streamflow estimation in watersheds and their zoning across various spatial extents. This forms the foundation for optimal water and soil resources planning and management, particularly in basins facing serious soil erosion challenges. Therefore, the objective of the present study was to examine the effect of spatial scale on the specific discharge and zoning of discharge values within the Karkheh basin, based on data of 28 hydrometric stations.

Materials and methods :

In this research, the data used includes the average annual water discharge (Q) and the area of the basin and sub-basins (A). The data used was received from the Iranian Water Resources Management Organization. Subsequently, in order to identify the most suitable stations, any disturbances in the natural process of the basin processes were initially investigated. This process involved the identification and removal of stations that had the potential to alter the process. Finally, a total of 28 stations with an appropriate statistical period length and no upstream basin disturbances were selected. Also, in order to calculate the upstream area of each station, the Karkheh basin was divided into 28 sub-basins based on the location of existing hydrometric stations. This was achieved using the Arc Hydro extension and the digital elevation model. In addition, according to the topographical, Geomorphological and hydrological conditions, the Karkheh basin was divided into five main areas.In the following, according to the values of area (A) and specific discharge (Qs) in the sub-basins, Qs-A relationships were drawn under log-log coordinates to calculate a linear or non-linear regression equation between Q and A, the effect of the scale onthe amount the discharge in the main sub-basins should be specified. Finally, using the method provided by Church et al., the corrected specific discharge values were calculated for each of the main sub-basins and through interpolation, the specific discharge map of the basin was produced.

The results of investigating the effect of scale on specific discharge indicated that there was no proper regression relationship between Qs and A for the entire Karkheh basin as a single basin (R2=0.3). However, the regression relationships with a coefficient of determination ranging from 0.7 to 0.98 were obtained for the sub-basins.Other results showed that in the majority of sub-basins, there is a negative relationship between area and specific discharge. That is, as area increases, specific discharge decreases. However, in the Seimareh basin, the increase in area leads to an increase in specific discharge. The observed increase in discharge can be attributed to the reduction in the basin elevation and the broadness of the riverbed. In contrast to other sub-basins, the discharge in the Qarasu sub-basin exhibits a low initial value, followed by an increase and subsequent decrease. This phenomenon can be attributed to the location of the Qarasu sub-basin in the upstream region of the Karkheh basin, the topographical conditions, and the high slope of the area. In general, the results indicated that the specific discharge varies across sub-basins with different areas and spatial scales. So that, the highest specific discharge was observed in the vicinity of the Karkheh basin outlet. This can be attributed to a number of factors, including the high slope and rainfall intensity in the upstream areas, as well as the difference in climate conditions and vegetation cover between the downstream and upstream areas.

Conclusion :

A comprehensive understanding of river discharge and the impact of spatial scale on it is of paramount importance in various fields. It provides a profound insight into the consequences associated with this phenomenon. To sum up, it is critical to understand river discharge patterns and how spatial scale affects them in a variety of contexts, including water resource management, flood risk reduction, sustainable development, and environmental preservation. It gives us a thorough awareness of the resulting effects. The findings of this study indicate that as the area increases, the specific discharge tends to decrease. Based on these results, it can be inferred that spatial scale and the upstream watershed area can exert an influence on discharge. A substantial body of research has demonstrated that spatial scale and the upstream watershed area play a pivotal role in determining river discharge. However, it is crucial to acknowledge the influence of a multitude of factors, including vegetation cover, climate, topography, slope, soil infiltration, and precipitation intensity, on specific discharge across diverse watersheds. Therefore, when evaluating the hydrological conditions of large-scale watersheds, it is essential to pay particular attention to the impact of spatial scale as a crucial factor. It is noteworthy that recognition this phenomenon necessitates more in-depth and comprehensive investigations across various spatial scale levels.

Analysis of the spatial and temporal trends of precipitation is pertinent for the future sustainable management of water resources. Urbanization and climate change affected local rainfall and intensity. As rainfall characteristics are often used to design urban drainage systems, so watershed modeling, and estimate of the flood properties, updating and reviewing rainfall characteristics is necessary. The Intensity-Duration-Frequency (IDF) curves are a suitable tool to estimate the threshold values of precipitation in different return periods. IDF curves should be prepared based on the long-term rainfall statistics in each region and can change under the influence of climate change. These curves which indicate the frequency and maximum intensity of annual rainfall in the different return periods are suitable tools for planning and managing the water resources. IDF curves are broadly used for different purposes, such as the design of flood control and diversion structures in the cities. The main purpose of this research is to investigate the effect of climate change on temperature, precipitation, and IDF curves in the different return periods in an arid environment.

In this research, the effect of climate change on IDF curves was investigated in Kashan City as a dry region. Kashan city with an area of 9647 km2 is located in the northern part of the Isfahan Province. In this study, RCP8.5, RCP4.5, and RCP2.6 scenarios (which are introduced as optimistic, intermediate, and pessimistic scenarios) reported in the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC), were used to predict the impacts of climate change on temperature and precipitation changes. Then, IDF curves were calculated evaluated, and compared for the basic (1993-2017) and future periods (2011-2070). To examine the impact of climate change on the rainfall intensity patterns, it is necessary to extract IDF curves in different climate conditions. Bell's method is a usual method for extraction of the IDF curves, which was promoted by Gharehman-Abkhezr in Iran. In this study, the latest promoted relationships developed were for the desert and southern regions (e.g;Nizar-Salfachgan, Kuhpayeh, Herat, and Jiroft basins in the central Provinces, Qom, Isfahan, Kerman, and Yazd) have been presented and used to extract IDF curves. To investigate the effects of climate change on IDF curves, first, the base period curves were extracted via rainfall data measured at the Kashan synoptic station. Then, using the new climate scenarios (RCP8.5, RCP4.5, and RCP2.6) and the output data of the LARS exponential microscale model, the IDF curves were extracted for different climate scenarios in the future (2011-2030), (2031-2050), and (2051-2070). Finally, the results of these curves were compared with the base period.

According to the results, for the base period, the precipitation and temperature data were predicated with an acceptable accuracy by the LARS model. The accuracy of the model has been higher in estimating the minimum and maximum temperature. the Nash and explanation coefficients for the maximum and minimum temperatures were 0.99 and 0.99, respectively. While, the explanatory and Nash coefficients for precipitation data were 0.95 and 0.93, respectively. Based on the results, the rainfall intensity will have fewer changes compared to the base period for long-term duration rainfall compared to short-duration rainfall (less than four hr. The maximum changes are related to rainfalls with a duration of less than one hour, whereas the minimum changes are predicted for 24- hr rainfalls. For all studied scenarios, a significant difference (P<0.05) was predicted between the average rainfall intensity of 0.17 to 24 hr in the region. As in the two-year return period and under the 2.6 scenario, rainfall intensity was increased from 10.75 to 30.54 mm hr-1 for the duration time of 0.17 hr.

An increase in air temperature, decrease in rainfall, change in the rainfall pattern, decrease in river discharge, and increase in sudden floods, followed by an increase in soil erosion, and a decrease in the amount of agricultural products are the results of climate change. Therefore, the long-term analysis and monitoring of climatic conditions can be very effective for crisis management caused by climate changes such as floods and droughts. Based on the results, the effect of climate change on the intensity of short-term rainfall is greater than long-term duration rainfall, as the intensity of short-term rainfall will increase more than long-term rainfalls.

Rain water harvesting is an appropriate option for storing surface runoff for subsequent uses during periods with limited access to water. The most important step in the application of rainwater harvesting systems (RWH) is the site selection suitable areas. Therefore, by identifying suitable sites for this purpose, time and cost will be saved . In this research, multivariate regression model and GIS were used to site selection in situ (RWH) in Tajare watershed. For this purpose, layers such as crown cover, litter, rock and stones, soil, curve number, rainfall, slope and depth of field as independent variable and infiltration were considered as the dependent variable. Then, according to the maps, their values were calculated in average for each of the 27 sub-basins. Also, to investigate the relationship between these variables and weighting, each of the effective layers of multi-variable regression was used by the stepwise method The results showed that the linear multivariate regression model with an explanation coefficient of 0.993 was able to estimate the penetration factor values well In terms of grade of importance, the curve number variables with a coefficient of -2.433, depth of soil with a coefficient of 0.3488, and rubble and gravel percent with a coefficient of 0.057, were the most important, and other factors were not significant. Comparison of the map from the site selection of multivariate regression in this research with some recommended criteria of various research studies showed that the predicted classes with good in the central parts of the basin and very good in the upstream areas of the basin which in the eastern and southeastern part of the basin fit have a good overlap with the recommended areas with these criteria.

In the recent years, science and technology in urban green space have largely focused on technologies that facilitate infiltration and reduce runoff (such as rain gardens and permeable sidewalks). Trees in urban green space reduce the net rainfall by interception, and on the other hand, their extensive root systems allow them to store and direct significant amounts of water into the soil. The present study investigates the effect of rainfall amount and tree species on rainfall interception in Hashtgerd city of Alborz province during two seasons of winter 2017 and spring 2018. For this purpose, during seven rainfall events, the amount of throughfall was measured by the number of five rain gauges installed under each tree. In order to record rainfall events, a rain gage container was installed in a location that was sufficiently distant from buildings and trees, and rainfall events ranging from 2.1 to 6.8 mm were recorded. The results showed that the percentages of rainfall interception for spruce, apricot, fig, willow, walnut, and oak species were 44.6, 42.6, 36.4, 35.1, 33.6 and 30.4 percent, respectively. The results of statistical analysis showed that there is a significant difference among the values of rainfall interception in different tree species (P <0.01). Also, there is a significant difference among the rainfall interception in the rainfall classes (low (lower than 4 mm), medium (4-6 mm), and high (higher than 6 mm)) (P <0.01). Among the studied species, sparrow and apricot species have the highest rainfall interception, which it is possible to make more use of these two types in the control of runoff with urban planning.

Soil erosion by water and wind is one of the biggest environmental threats worldwide which it has various negative consequences such as soil degradation, mitigation of soil fertility, depletion of nutrients and micro-elements, degradation of soil structure, dust storms, reservoir siltation, and etc. on the natural and anthropogenic ecosystems. Therefore, accurate information of land susceptibility to soil erosion hazard by water and wind, and production of spatial maps of these hazards are necessary for mitigation of their consequences. Therefore, the goal of this research is application of two machine learning models for the spatial modelling of water and wind erosion in the Bakhtegan basin, Fars province.

In order to generate the spatial maps of soil erosion by water and wind, we have used 20 and 16 effective factors on water and wind erosion, respectively. Before the modelling stage, the multivariate adaptive regression spline (MARS) feature selection algorithm and multicollinearity test were used to identify the most important factors controlling water and wind erosion. In next stage, two random forest and support vector learning machine techniques were applied to model soil erosion. Area under curve (AUC) was applied to assess the model performance.

According to results, land use, slope, lithology, roughness, coarse fragment, clay, vegetation cover, aspect, soil bulk density and topographic wetness index were identified as the most important factors controlling water erosion. The most important factors controlling wind erosion are including elevation, land use, wind speed, slope, vegetation cover, soil nitrogen, cation exchange capacity, lithology, aspect, clay and bulk density. The AUC value for wind erosion map generated by random forest model was 99, and for water erosion map produced by support vector machine is 96. Finally, we integrated two maps and results indicate an area of study area about 18% has very high susceptibility to wind erosion and low susceptibility to water erosion.

Due to study area has several lakes consisting of Bakhtegan, Maharlo and Tashk, and also several dams, it is so important to supply water for different purposes such as drinking, agricultural, industry and environment. In case of not paying attention to this challenge especially wind erosion in the study area, this case study especially dried beds for lakes can play as sources for generating dust particles. Therefore, the findings of this research can use by managers to mitigate negative effects of this phenomena.

In this study, the hydrological processes of Khaveh Watershed located in Markazi province, Iran were simulated and the effect of check dams on floods in this basin was evaluated. To assess the impact of watershed management structures on floods, flood volume and peak discharge with different return periods were calculated. In order to estimate the irrigation rate of Khaveh Watershed, in this study, the method of Justin was studied. Then, flooding situation of Khaveh Watershed was simulated using HEC-HMS model. For this purpose, the flood hydrographs resulting from the design storms with different return periods in the pre- and post-construction states of watershed management structures were compared with each other. The results showed that the constructed dams clearly reduced the peak discharge and flood volume of the region. Based on the results, the construction of corrective structures has reduced the peak flow, increased the base time of the hydrograph and increased the time to the peak of the hydrograph in different return periods. For the 5, 10, 20, 50, and 100-year return periods, the peak is 0.6 to 3.3, 4.9 to 2.7, 9.4 to 1.5, and 6, hours respectively. Discharge decreased to 0.8 and 22.4 to 12.4 cubic meters per second. Also, the base time of the hydrograph for the mentioned return periods increased from 6.8 to 11.2, 9.3 to 0.16, 2/10 to 17.5, 5/10 hours to 18.5 and 10.10 to 29.3 hours. The latency in time-to-peak for hydrographs due to the construction of structures was approximately 3.5 h.

The damming can cause changes in the hydrological regime of the river. There is a crucial need to understand the potential impacts of water structures on river hydrologic regimes in order to set managed environmental flows. In this study, the statistics of Tang Esferjan hydrometric station at the outlet of Hoonejan watershed (Isfahan province) were used to investigate the monthly average discharge and flow duration curve alteration using IHA software (version 7.1). The amount of monthly flow has decreased in the post impact compared to the pre impact period. The flow duration curve is higher in all seasons before the construction of check-dams than after construction. The interpretation of flow duration curves shows the reducing effect of correction clauses in all types of flow. The hydrological indicators of the stream (normal discharge index in the high flow condition, normal discharge index in the low flow condition and normal discharge index) have decreased in the post-impact period compared to the pre-impact period. In all months of the year, except for February, March and April, the rate of decrease of the normal discharge index in the low flow condition (Q75) was higher than the normal discharge index in the high flow condition (Q25). The normal discharge index in the high flow condition has decreased more in the spring season than in other seasons after damming. The normal discharge index in the low flow condition in winter, autumn (91%) and summer (90%) has decreased more than in spring.

Collected from sixty-six meteorological stations, the most recent data concerning the intensity-duration-frequency curve in Iran have been recorded in 1374. While rain gauges are required for physically obtaining such data, the collected data may be fraught with inaccuracies, considering the fact that the meteorological data of the extremely remote areas may be impossible to be gauged. Therefore, intensity-duration-frequency formulas are used to reduce the rate of such inaccuracies. While many formulas have so far been developed to be used for obtaining the required data regarding intensity-duration-frequency curves, they could only be applied to those areas whose regional rates have been estimated. This study sought to identify and optimize such formulas’ rates together with the computational algorithms in the Urmia Lake’s basin. Then, the efficiency of the mass-fine computational algorithm and the genetic algorithm was measured and compared. Finally, the influence of climate change on intensity-duration-frequency diagrams in the basin was investigated using the nearest neighbor algorithm.

Considering the precipitation intensity data collected from Western Azerbaijan Province’s Regional Water Organization, first, the method for selecting the function of the precipitation’s intensity-duration-frequency was determined. Then, the fitting methods for the different return years’ functions of the intensity-duration were presented. As for the extraction of IDF curves, the required data regarding the highest annual precipitation rates in 30-, 45-, and 60-minute durations were obtained from the statistics published by the Iranian Meteorological Organization. Then, the precipitation rate was investigated in twenty-seven meteorological stations of the Urmia Lake, and the intensity-duration-frequency curves were made accordingly. Taking the extracted curves into account, the regional coefficients of Abkhezr’s equation were measured and optimized based on the Genetic and Particles Swarm algorithms. Then, to determine the measurement accuracy, the daily precipitation rates were extracted from five sample meteorological stations in terms of 2-200 return years and millimeters per hour unit using the SMADA software. Finally, the IDF curves were made based on the optimized rates and Abkhezr formulas.

The average rates of optimizing the coefficients of the Abkhezr formula with both algorithms mentioned above were found to be the same, bearing a very close prediction. Taking into account the average intensity and continuity rates of the IDF curves in terms of an integral diagram, the study undertook to compare the measurement of pre- and post-optimization IDF curves in five sample stations. Generally, the findings of this study indicated the accuracy of the Abkhezr Formula’s rates (with an acceptable closeness) in all meteorological stations of the Urmia Lake except for the Mahabad camp. It could therefore be argued that the average optimized regional rate are hundred percent fitted with the obtained rates. Discussion and

The findings of the study suggested a high accuracy of the Abkhezr formula’s coefficients in all Urmia Lake’s meteorological stations (with acceptable closeness) except for the Mahabad camp, with the Siyah-Ceshmeh station having the best fitting rate. In this regard, the fitting rate of the coefficients in the above-mentioned stations differed merely at thousandth and ten-thousandth decimal rates. On the other hand, the pre-and post-optimization IDF curves were found to have slight differences, bearing an acceptable fitting. Moreover, the comparison of the integral curves of the IDF parameters indicates the great consistency between the results of this study and the formulas developed by Abkhezr and Bell. Furthermore, a good correlation was found between the results of this study and the research findings of Aghajani and Kerami, which were based on Sherman and Bernahu's formulas. As t and T in Bell's formula can have a local dependence in each area, such a dependence has been included in Abkheder's formula based on regional coefficients. The results also showed that the PSO algorithm performed more efficiently in terms of optimization and its intended function is closer to zero, as it measures each particle with other neighboring particles, putting it in numerous cycles. However, the sensitivity analysis revealed a very slight difference between the two algorithms used in this study, suggesting that both algorithms could be applied.

Natural resources and the environment are the foundation of life and human activities and other creatures, closely intertwined with them. In recent decades, the Earth has been significantly affected by the impacts of global warming and climate change and the country of Iran has not been exempted from this rule. as this phenomenon directly affects environmental, economic-social activities and human health. General circulation models are suitable tools for monitoring future climate change events, but due to their large spatial scale, they require downscaling. This study examined the status of climate variables such as precipitation and average temperature at five synoptic stations on the southern coasts of the country. The basic statistical periodconsidered from 1985 to 2015, and four climate scenarios from the sixth IPCC report were simulated using the MPI-ESM1.2-HR model for the statistical period2023-2043 through downscaling SDSM modeling. The results show an increase in temperature ranging from 1.64% to 8.9% compared to the base period under all four scenarios at all stations. Meanwhile, precipitation is decreasing at some stations under certain SSP scenarios and increasing at others. An increase of up to 140% in Bushehr station and a decrease of more than 10% in Kish station are expected. Estimating, predicting, and monitoring climate change occurrences in different time frames and according to the updated IPCC reports is essential to assist decision-makers and policymakers in taking action to reduce greenhouse gas emissions and adapt to this leading phenomenon.

Water scarcity in arid areas is a serious crisis. The most important step in using rainwater collection systems is to locate suitable areas. In this research, three methods of multivariate regression model and GIS have been used to locate the on-site and off-site rainwater collection method in Tejreh watershed. In this study, canopy, litter, rock and gravel, bare soil, CN, precipitation, slope and soil depth as independent variables and influence on in situ rainwater collection and maximum instantaneous discharge for non-in situ rainwater collection method The title of the dependent variable was considered. The multivariate regression model uses stepwise method, backward removal method, and forward method. And the standard step-by-step method, regression removal method, step-by-step method in collecting rainwater, non-in situ method have been used. The final results by matching the results of previous research show in step rainwater collection, stepwise method and between layers CN, soil, percentage of rock and gravel, and in non-in situ rainwater collection stepwise regression method Standard and among layers the percentage of litter, percentage of canopy, CN, slope, percentage of rocks and pebbles, amount of rainfall, percentage of bare soil and soil depth are known to be important in the equation. Finally, the importance of rain collection sites was divided into four classes: very good, good, medium and poor.

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

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

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

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

Land subsidence is one of the most important environmental problems that affects agriculture and urban infrastructure. In order to plan for mitigating the damages caused by land subsidence, it is necessary to identify high-risk and prone areas for this phenomenon specially in different plains of Iran. The main purpose of this research was zoning the land subsidence in Kashan aquifer using Dempster-Schafer, Weight of Evidence, Shannon Entropy, and Frequency Ratio. To conduct this research, 14 factors affecting the occurrence of subsidence including elevation, slope, slope direction, surface curvature, distance from stream, distance from fault, distance from road, lithology, land use, longitudinal and transverse curvature, water table changes, distance from mining and well density in aquifer surface were used. Then, determining 108 subsidence positions and 108 non-subsidence positions at the aquifer level, these points were randomly classified as 30% and 70% as validation data and test data, respectively. To evaluate each of the models, the ROC curve was used. The results showed that among the used methods based on the ROC curve and the amount of AUC, the Frequency Ratio method (training: 0.84 and validation: 0.89) performed best and is introduced as the best method for predicting areas with subsidence sensitivity in studied area. Shannon Entropy, Dempster-Schafer and Weight of Evidence were also ranked next, respectively. The results of this study can be used by provincial managers to reduce the damage caused by land subsidence and to determine areas with subsidence sensitivity.

Due to the importance of conservation of natural resources, the development of strategies for the protection and exploitation of these resources is felt as a fundamental necessity more than ever. People's participation in any project guarantees the implementation and sustainability of that project. This issue is more important in the protection of natural resources, because issues related to the environment and natural resources are intertwined with the lives of communities, and the success of any program will require the participation of these communities, so the role of people in decision-making, Planning, implementing, monitoring and evaluating any conservation plan is of critical importance. Therefore, an appropriate management system to protect these areas should be according to the management which is based on the participation of local communities. In other words, the main strategy to implement sustainable development in the field of renewable natural resources is to emphasize the factors that call for the participation of local communities. Studies on the participation of watershed residents in watershed management projects show that if the executive activities are carried out without the presence of the people, they do not take responsibility for the maintenance of the projects and therefore do not make any effort to eliminate their defects. In other words, people greatly increase their efficiency by engaging in such plans and programs (watershed management). In general, the success or failure of watershed management projects should be sought in the presence or absence of people. However, paying attention to determining the factors affecting the participation of watershed residents in watershed management projects and analyzing their relationship is an inevitable necessity. Therefore, the general purpose of the present descriptive-correlational study is to determine the factors affecting the participation of watershed residents in watershed management plans and analyze their relationship in the watershed of the great river of Naein.

Naein Great River Basin with an area of about 130,000 hectares between 32 degrees and 45 minutes and 18 seconds to 33 degrees and 09 minutes and 20 seconds north latitude and 52 degrees and 29 minutes and 18 seconds to 53 degrees and 05 minutes and 41 seconds is east of the Greenwich meridian. The minimum height of this basin is 1552 meters and the maximum height is 3094 meters (Figure 1). This watershed is located in Naein city of Isfahan province in terms of country divisions and includes two villages of Koohestan and Baharestan and 41 inhabited villages with a population of about 2298 people. The questionnaire was the data collection tool of this research, the apparent validity of which was examined by a group of experts including professors of watershed science and engineering and experts of the Jihad-e-Agriculture and Natural Resources Department, after which the necessary corrections were made accordingly. Its reliability coefficient was obtained between SPSS software and Cronbach's alpha method between 0.866 and 0.920. The statistical population of the present study consisted of watershed inhabitants living in the Naein Great River Basin of Isfahan Province (N = 2298). Of these, 476 people were selected as a statistical sample using Cochran's formula by random sampling method. Finally, 476 complete questionnaires were submitted and analyzed.

The results of Pearson correlation test showed that there is a positive and significant relationship between economic factors and the willingness of watershed residents to participate in watershed management projects (direct-strong correlation). It seems that in this watershed, the financial conditions and economic power of watershed residents are somewhat equal and at a moderate level. In such circumstances, providing low-interest facilities and credits can greatly strengthen the incentive for watershed residents to participate in watershed management projects. The results of Spearman correlation test showed that there is a positive and significant relationship (direct-severe correlation) between communication factors and information sources with the desire of watershed residents to participate in watershed management projects. The results of Kendall Tao test of each of the items of communication factors and information sources with the willingness of watershed residents to participate in watershed management projects showed that there is a positive and significant relationship between all indicators with the willingness to participate in watershed management projects. In other words, the more communication factors and information resources such as training classes, local leaders, experts, visiting other projects, radio, television, etc. are used, the more watershed residents will participate in watershed management projects. Therefore, it can be said that by promoting mass and social media, holding training classes, visiting other successful projects, etc. the amount of participation in watershed management projects can be increased. Also, according to the findings of the present study, the most important social factors affecting the participation of watershed residents in the Naein River Basin include the motivation of watershed participants to participate in future projects, the ability of local councils, encouraging friends, acquaintances and experts, the impact of educational and extension services, the awareness of watershed residents, the tendency to work collectively, and the impact of work experience. Also, the most important individual factors influencing the participation of watershed residents in the Naein Great River Basin include gender, age, and education. Therefore, special attention should be paid to these factors in the agenda of natural resource planners and specialists. For example, local councils can be used to involve watershed residents in watershed management projects.

In general, the findings of this study on the effects of social factors, economic factors, communication factors, information resources and variables of individual factors and their characteristics (land size, capacity of local councils, impact of local knowledge use, visiting other projects, experts’ information dissemination, etc.) show that these factors influence the participation of watershed residents in watershed management projects, and since these factors and items have severe effects on the desire of watershed residents to participate in watershed management projects, paying attention to these cases can help us improve watershed management projects, which requires that experts and the government pay special attention to the watershed dwellers living in the basin.

In order to achieve sustainable development and conservation of natural resources, it is necessary to promote the participation of individuals, especially users of natural resources. In fact, people's participation is of paramount importance in the implementation of environmental resource protection programs, and new trends in the global arena are based on strengthening the role of people in the protection of natural resources. Experts believe that the involvement of local individuals and groups in rural communities in watershed management projects can bring many benefits. It is believed that involving local people in the watershed management process can improve the technical and analytical skills of the users. In general, the success or failure of watershed management projects should be sought in the presence or absence of people. However, paying attention to the role of people in these projects and finding ways to encourage their participation is an inevitable necessity. Therefore, the general purpose of the present descriptive-correlational research is to prepare a causal model of the elements that influence the willingness of watershed residents to participate in watershed management projects of the Great Nain River Basin. Watersheds are influential and can promote the participation of watershed residents.

Naein Great River Basin with an area of ​​about 130,000 hectares between 32 degrees; 45 minutes and 18 seconds to 33 degrees, 09 minutes and 20 seconds north latitude,52 degrees and 29 minutes and 18 seconds to 53 degrees, and 05 minutes and 41seconds is located on the east of the Greenwich meridian. The minimum height of this basin is 1552 meters and the maximum height is 3094 meters. This watershed is located in Naein city of Esfahan province in terms of national divisions and includes two villages of Koohestan and Baharestan and 41 inhabited villages with a population of about 2298 people. The statistical population studied in this study includes watershed residents living in Naein river basin of Isfahan province (N = 2298), among whom 476 people were selected as a statistical sample using Cochran's formula. due to the large size of the statistical population, random sampling method was used and information was collected. Finally, 476 questionnaires were collected and analyzed (performing stepwise regression, performing path analysis technique and preparing a causal model of the elements that influence the willingness of watershed residents to participate in watershed management projects).

The results of stepwise regression showed that social factors account for 69.1% of the willingness of watershed residents regardless of other variables. Also, social, economic, and communication factors as well as information resources and education item indicate a total of 74% of the changes in the willingness to participate in watershed management projects. The results obtained from the table of regression coefficients to determine the relative importance of variables and their effect on the willingness to participate showed that social factors have the largest share in the willingness of watershed participants to participate in watershed management projects and education item has the lowest share in their willingness to participate. Also, the causal model of the elements that influence the willingness of watershed residents to participate in watershed management projects showed that the factors mentioned above also have many indirect effects on the willingness of watershed residents. Therefore, according to the stepwise regression and the causal model prepared, planners and natural resource specialists should pay considerable attention to social, communication, and economic factors as well as information resources and education, For example, local councils can be used to foster the participation of local people in watershed management projects. Also, providing low-interest facilities and credits can greatly increase the motivation of local communities to participate in watershed management projects. Relevant organizations and the government can motivate local communities to participate in watershed management projects by creating jobs and improving the economic status of people. It can also be said that by promoting mass and social media, holding training classes, visiting other successful projects, etc., the level of participation in watershed management projects can be increased.

In general, the findings of this study indicate the great effects of three factors (economic, social and communication as well as information resources) and an individual item (education) on watershed participation, which was presented as a causal model of watershed participants' willingness to participate. Therefore, planners and natural resource specialists should pay considerable attention to these factors in order to increase the success of watershed management projects by encouraging more participation of watershed residents.

Due to urban development, it is necessary to provide management solutions to reduce the risk of flooding of urban facilities. Passive defense is a new approach aimed at minimizing and preventing financial and human losses and preventing potential crises based on the civilian methods. Among the various models proposed for strategic planning, the SWOT matrix is the most common. The main purpose of this study is to provide the best management strategies to reduce the risk of existing facilities and also to provide strategies for facilities that will be constructed in the future.

The infrastructure map of Kashan City (urban land use) was prepared via Kashan Municipality. Then, the infrastructures (applications) were divided into 14 general categories. In the next step, by carefully examining the area and field visit and examining each infrastructure, a list of internal factors (strengths, weaknesses) and external factors (opportunities and threats) was prepared and the final score of the weight multiplied by the rank for internal and external factors. Achieved and strategic position for the region was identified and management strategies for the region were developed. Finally, the developed strategies were prioritized using the Quantitative Planning Matrix (QSPM).

The final score of internal and external factors was equal to 1.931 and 2.03, respectively, which indicates the predominance of weaknesses in internal factors and the majority of threats in external factors. The strategic position for the study area is recognized as the defensive strategy (WT) type. three strategies include: 1- providing the necessary budget for strengthening urban infrastructure with a passive defense approach against floods and anti-flood action of urban facilities, 2- interacting with scientific centers for studies in the context of floods and the damages caused by it, and 3- principled constructions with the focus on sustainable development and passive defense were developed. The results showed that the strategy No. 3 with a final attractiveness score of 6.51 is the first management priority for urban infrastructure. The strategies 1 and 2 with the final attractiveness score of 4.59 and 4.15 are proposed as the next managerial priorities for the region.

According to the score of internal and external factors, the strategic position was obtained as defensive type. Passive defence tries to neutralize the weaknesses and threats in the region by relying on the strengths of internal factors and the opportunity of external factors. According to the result of the Quantitative Planning Matrix (QSPM), construction with a focus on sustainable development and passive defense with respect to the river area was selected as the initial strategy for the region.

Floods are natural disaster that can endanger lives and property infrastructures in the urban and rural area. The main aim of this study is to analyze the flood risk elements and prepare a flood risk map in the Suk Cham River basin located in Kashan city, Isfahan province. For this propose, a topographic map was prepared for the study period using Google Earth and Gloobal mapper software. The prepared topographic map then was transferred to AutoCAD Civil 3D software to construct the surface and cross sections. To simulate floods in the return period of 25, 50, 100, 200 years, the cross sections were transferred to HEC RAS software. Kolmogorov–Smirnov test was used to convert the maximum daily flow to the maximum instantaneous according to the P-value. The results of flood frequency analysis showed that the log Pearson type III distribution is the most suitable distribution to estimate flood level in difference return periods. According to the results, the flood surface zones were 0.77, 0.9, 1.15, 1.47 square kilometers for the return periods of 25, 50, 100, 200 years, respectively. The results also shows that 41.5 and 4.5 percent of the two villages surface (Khancheh and Baronagh; villages located next to the river) are at moderate to very high flood risk in the 100-year return. Keywords: Flood Risk Map, Hydraulic Model, AutoCAD Civil 3D, Suk Cham River Watershed Keywords: Flood Risk Map, Hydraulic Model, AutoCAD Civil 3D, Suk Cham River Watershed .

Gypsum, sulfuric acid, and sulfur are used to improve saline and sodic soils. In some cases, animal manures are also used, which varies according to environmental conditions and soil type (Jesus et al., 2019). Industrial gypsum is often used to modify saline and sodic soils due to electrolyte maintenance, physical and hydraulic properties (Keren, 1996), low cost, solubility, and ease of use (Amezketa et al., 2005). Gypsum particle size can also affect gypsum performance. Abdolfattah et al. (2015), using gypsum in three different sizes (<0.5, 1-1.5, and 1-2 mm), found that the use of gypsum with smaller particle size has better performance than large particles. Gypsum can reduce salinity as well as soil sodium. Morete and Hiro (2015) showed that the content of soil gypsum has a significant effect on water retention, as the higher the gypsum content, the holding curve soil water holdings have a steeper range and the soil stores more water. In leaching operations and improvement of saline and sodic soils, a large amount of water is required. Therefore, determining the amount of water required due to the water shortage crisis and the protection of water resources is of particular importance. Therefore, in this study, the effect of gypsum modifiers with different amounts and sizes of particles on the amount of water required for leaching saline and sodic soils with low to medium salinity has been investigated. In general, the main objectives of this research are 1- Determining the optimal size of gypsum particles for leaching with minimum water, 2- Determining the optimal amount of gypsum for leaching with minimum water 3- Determining minimum water required for leaching saline and sodium soils.

After drying, the lumps in the soil samples were pounded using a plastic hammer and a unique rolling pin available in the laboratory to prepare the soil. Finally, the compacted soil sample was passed through a 2 mm sieve. Then, using different amounts of sodium chloride, it was transformed into the soil with low to medium salinity and sodium by trial and error in a laboratory. After applying the treatments mentioned in the text of the article to determine the chemical properties of the soil before washing, five different amounts of gypsum (5, 7.5, 10, 25, 50 g of gypsum per kg of soil) were added to the soil in three repetitions and poured into cylindrical pillars. In the preparation of laboratory columns, polyethylene cylindrical containers with a diameter of 35 and a height of 40 cm were used. To drain the laboratory columns in the bottom of the cylindrical containers, a sand filter with a height of 5 cm was used, and pipes for the water outlet were installed in the same part. After 24 hours of treatments and leaching, soil sampling was performed from two different depths (0-15 and 15-30 cm), and soil chemical properties were measured after six leaching steps. The gypsum is passed through different sieves (4, 2, 0.5, 0.25 mm) to obtain different particle sizes in the next step. The treated soils were then tested with three replications as in the previous step, and their chemical properties were measured. After determining the optimal amount and size of gypsum from the last two stages, the soil was leached in six repetitions in 6 stages. After each leaching, one of the treated soils was removed from the leaching cycle and soil and drainage chemical properties. Its output was measured. Finally, soil and drainage characteristics were compared during the repetition of 6 leaching times to determine which stage the leached soil has the desired optimal conditions. Finally, all the mentioned steps were analyzed using SPSS 19 software.

The results obtained from the application of 10, 25, and 50 g of gypsum per kg of soil showed that if the amount of gypsum used to improve the saline and sodium soils studied is less than 7.5 g of gypsum per kg of soil, the soil retains its salinity and sodium content. If the amount of gypsum used is higher than this amount, the salinity and sodium intensity of the soil will increase. For soil with a depth of 30 cm and a volumetric mass of 1.5 tons per cubic meter, the amount of gypsum required will be about 3.4 tons per hectare. In the continuation of experiments to determine the optimal size of gypsum particles, the tested soil was treated with 7.5 g of gypsum per kg of soil in different particle sizes (0.25, 0.5, 2, and 4 mm). After the significance of the ANOVA test, the average chemical properties of soil in each of the different treatments of gypsum particle size were compared. This finding shows that the optimal gypsum particle size for the study of saline and sodium soils was particle size between 0.25 to 0.5 mm. In the continuation of the research, using the determined optimal amount (7.5 g / kg) and the optimal size of gypsum particle (0.5 mm), the effect of each leaching stage on the soil at two depths (0-15 and 30-15) were examined. According to the results, the lowest amount of ESP is related to saturated flower extract after four washing steps.

This study showed that using 7.5 grams of gypsum per kilogram of soil is the most suitable value for leaching saline and low to medium saline soils (equivalent: 11 tons per hectare to a depth of 10 cm, 16.85 tons per hectare to a depth of 15 cm, and 33.7 tons Per hectare to a depth of 30 cm). The gypsum particle size of 0.5 mm had the best performance in soil remediation. Therefore, it can be stated that adding 7.5 g / kg soil with gypsum particle size (0.5 mm) is the best treatment for soil improvement with low to medium salinity and sodium. This section stated that gypsum treatment with 7.5 g of gypsum per kg of soil and gypsum particle size of 0.5 mm has the best performance after four leaching stages. Finally, in this study, control treatment and gypsum treatment with optimal particle size and size were compared in terms of the effect of different leachates in both surface and deep parts of the soil. Leaching saline and sodium soils without using modifiers causes the soil to become sodic and destroys the soil structure. The results of studies by Noori et al. (2021) have shown that saline and sodium soils that have been partially degraded can be developed for agricultural use by modification with a specific type of treatment and with the best soil management practices.

Various methods developed to convert large-scale data to regional climatic data. In few studies , the results of these methods have been statistically compared. The main purpose of this study was to compare SDSM and LARS-WG models for Downscaling output data of CANE-SM2 and HADGEM2-ES general circulation models under RCP2.6, RCP4.5 and RCP8.5 scenarios. For this study, precipitation, minimum and maximum temperature of Arak synoptic station were used as the base period (1980-2005). The results of the predictions of the SDSM and LARS-WG models were compared for three periods (2021-2040, 2041-2060 and 2061-2080). The RMSE, R2, MAE and NSE criteria were used to evaluate the performance of SDSM and LARS-WG models. Based on the results of the evaluation criteria, both models have an acceptable resuts in simulation of climate variables. Downscaling results of both models showed that minimum and maximum temperatures should increased compare to baseline in all scenarios and periods from January to June, but LARS-WG model had a over estimation compared to the SDSM model. Changes in predicted precipitation by SDSM and LARS-WG models did not have a clear trend. According to the results, the SDSM model shows more changes in precipitation, wherase, the LARS-WG model shows more changes in minimum and maximum temperature compared to the base period. Based on the results of this study, it is not possible to determine the exact superiority of each of the models, But SDSM model had a better prediction for precipitation and maximum temperature, while, LARS model had better results for maximum and minimum temperature.in general it can be said that the prediction results of both models are statistically significant (P<0.01) in most cases.

Runoff is one of the most important components of the hydrologic cycle. Since there are no observational data in basins lacking statistics, the process of calibration and validation of hydrologic models seems impossible in these basins. On the other hand, predicting runoffs in basins lacking statistics is essential for planning and management of the basin (runoff estimation, ecosystem services, flood control) (Beck et al., 2016). However, predicting the runoff in basins lacking statistics has been comprehensively discussed using the calibrated hydrologic model in basins having observational statistics through the zoning approach (Yang et al., 2019:67). The zoning approach has been identified as the cheapest and most prevalent solution for solving the prediction problem of flows in basins lacking statistics (Cislaghi et al., 2020:348). According to the definition of the zoning approach, predicting runoff in basins lacking statistics is done using data transfer from basins having statistics to the basins lacking statistics (Rojas et al., 2016).

To conduct this study, firstly SWAT model was calibrated and validated in the watershed basin having statistics; then, the calibrated parameters were transferred to Sukcham basin which lacked statistics, to simulate and analyze the flow using hydro office-FDC software. To analyze the sensitivity of parameters in the zoning approach and for simplifying the complex structure of hydrologic models like SWAT, minimizing the number of parameters in the modeling phases was a necessity. To this end, firstly, a sensitivity analysis was done for the basin having statistics using 14 sensitivity parameters affecting the flow. According to the global sensitivity analysis, the parameters were ranked in SWAT CUP-SUFI-2 based on the sensitivity level and considering two P-value and T-stat factors. Later, 14 parameters having high sensitivity in the basin having statistics were calibrated and transferred to the basin lacking statistics (Sukcham) using zoning and physical approaches.

According to the obtained results from sensitivity analysis of 14 sensitive parameters in the flow simulation, SLSOIL, HRU-SLP, CH-S1, CANMX, SOL-AWC parameters were recognized as the most sensitive parameters of the region. The performance evaluation criteria of NSE, R2, and PBIAS models, respectively, for the calibration periods, were 0.6, 0.65, and 10.7 and for the validation, periods were 0.47, 0.63, and 11.88, showing the acceptable accuracy of daily discharge simulation in the daily scale. After calibration and validation of SWAT model in the basin having statistics and the basin lacking statistics (Sukcham), the daily time step was applied for the 2008-2015 period, and the calibrated parameters of the basin having statistics were transferred to the basin lacking statistics through zoning approach and using physical characteristics. Considering Table (9), the average daily outlet runoff, as well as the average volume of annual outlet runoff for the basin lacking statistics (Sukcham), were estimated. The estimation of such information from basins lacking statistics can present managerial views toward controlling the flood and preventing the occurrence of devastative floods as well as providing the required water sources for filling the aquifers and agriculture in dry regions. Considering Figure (9), the moisture indexes (Q10-Q20) were respectively 0.12 and 0.16 m2/s (10 and 20 percent of the days in a year (33 and 73 days)), discharges were 0.12 and 0.16 m2/s or more. Considering the average extracted index from the curve, flow duration was obtained, respectively, 0.115 (30% of days in a year (110 days)), 0.111 (40% of days in a year (146 days)), 0.094 (50% of days in a year (183 days)), 0.081(60% of days in a year (219 days)) m2/s. Moreover, the scope of low flow index (Q70 toQ95) for 256 and 347 days of a year was obtained 0.058 and 0.024, respectively. In addition, the flood index (Q5) was 0.28 m2/s (5% of days in a year (18 days)), for which the flood discharge equaled 0.28 or more.

Considering the performance evaluation criteria, the performance of SWAT in dry basins having statistics was good and satisfactory in the daily scale of calibration and validation phase. According to the results of administering the SWAT model in the basin lacking Sukcham statistics, the average daily runoff flow (0.107 m2/s) and the average volume of total annual outlet runoff (million m2) of this basin have been estimated. Then, the flow duration curve was drawn for the Sukcham River in the hydro office-FDC software. Considering the results of the flow duration curve of the Sukcham River, it could be concluded that the scope of moisture, moderate and low flow indexes were respectively, (0.12-0.16), (0.081-0.115), and (0.024-0.058) m2/s. Moreover, the flood index (Q5) was obtained 0.28 m2/s for Sukcham River; which meant that regarding 5 % of the days in a year (18 days), the flood discharge equaled 0.28 m2/s or more. The extraction of these results may help in better recognition of hydrologic behavior of basins lacking statistics for planning and management purposes of water sources such as controlling sudden floods and providing drinkable water and agriculture.

Ephemeral Gully (EG) erosion is one of the most destructive types of water erosion, which contributes significantly to land degradation. EG erosion prediction is necessary to assess the magnitude of soil loss and to implement the appropriate conservation measures. The aim of current study  was to evaluate the efficiency of EGEM model for EG erosion prediction in Ghoorichay Watershed, Ardabil Province, Iran. For this purpose, a number of 17 EG erosion was identified and monitored between the years 2014 to 2016. The morphological characteristics and erosion rate of EGs were measured and recorded after seven effective rainfall events. In order to calculate the EG erosion, EGEM model requires four major categories of input data, including identification information, watershed data, soil data, and rainfall data. The model has two major components: hydrology and erosion. The runoff induced by a rainfall event in each gully catchment was determined by the Natural Recourses Conservation service (NRCS) Curve Number (CN). The result of EGEM model performance evaluation showed that the eroded soil volume and cross-section were predicted with a determination coefficient of 0.96 and 0.89, respectively. Sensitivity analysis revealed that the curve number was the most sensitive parameter, so that, with a 10% increasing and decreasing in CN, the volume of soil loss varied 22.98 and -18.92%, respectively. It can be concluded that EGEM model was suitable for event-based EG erosion prediction in Ghoorichay Watershed and it can be recommended for studying and planning on EGs in similar watersheds.

Landslide susceptibility mapping is considered as the first important step in landslide risk assessment. The main purpose of this study is to compare the performance of a machine learning algorithm (a logistic model tree), and a statistical model (a logistic regression), for landslide susceptibility modeling in the Sarkhoon watershed, Chaharmahal and Bakhtiari province. For this purpose, at first, a landslide inventory map including a total of 98 landslide locations was constructed using historical landslides, and extensive field surveys. In addition, a total of 100 non-landslide locations were also identified to construct a database. The landslide and non-landslide locations were randomly selected and divided into two groups with a 70/30 ratio for modelling and validation processes. Twenty conditioning factors were selected based on literature review and geo-environmental properties in the study area. Subsequently, the logistic model tree (LMT) and the logistic regression (LR) models were applied to identify the influence of conditioning factors on landslide occurrence. Finally, the performance of the models in landslide susceptibility mapping was investigated using the area under the receiver operating characteristics curve (AUC). The results concluded that the LR model (AUC = 0.797) outperformed and outclassed the LMT (AUC = 0.740) model in the study area. Although both models were reliable tools for spatial prediction of landslide susceptibility; however, the LR model was more accurate that it can be proposed as an alternative tool for better management of areas prone to landslide in the study area.

Information about river flow change and subsequent changes in water quality characteristics can help to manage and plan water resources. The environmental and socio-economic impacts of river flow changes are very important in an environmental water management. Climate change is an important challenge that should influence different parts of human life on earth such as rivers and lakes. The Evaluation of the impact of climate change phenomenon on the hydrological processes of rivers can decrease the challenges of managers and planners of water resources in the next period. The selection of suitable models is important for evaluation and prediction of the effects of climate changes on rivers and watershed discharge. Several hydrological models were used to evaluate the effects of climate change on a hydrological cycle. The Soil and Water Assessment Tool (SWAT) has been extensively used, mainly by hydrologists for watershed hydrology related subjects, since 1993. SWAT model should include both a forecasting model and weather generating model. This means that the generated weather data of the future should be presented to SWAT model for forecasting future rainfall and temperature. This is a new possibility for future river and watershed hydrology studies. The main aim of this study was to evaluate the effect of the future climate change on river discharge of the Heruchay River in Ardebil using SWAT model. In this study SWAT2009 model was used to in investigate and predict the quantitative changes of the discharge of the Heruchay River. For the period of 2014-2041, the daily rainfall and temperature data were predicted under three scenarios of A2, B1, and A1B, using LARS_WG climate model. The simulated data was used as the entered information of SWAT model and the model was implemented for 2014-2041 period.
SWAT is a river basin scale model that should work on a daily time-step. It was developed to predict the effect of the management decisions and climate change on the water cycle. In this study, SWAT model was used for its ability to simulate and forecast stream flow and evaluate the effect of climate change on river discharge.
A topographical map (Digital Elevation Model), climate data (daily rainfall, Maximum and minimum temperature), and soil and land use maps were prepared using GIS and measured data. As the precipitation is an important key input that influences flow and mass transport of the rivers, 5 rainfall gauging stations and 2 weather stations located in the study watershed were used.

Result and The results of this study showed that SWAT model had an acceptable performance for discharge simulation during calibration and validation periods with coefficients of variation of 0.81 and 0.8 respectively for calibration and validation. Based on the results of A2 and B1 scenarios, the flow rate of the study river increased, whereas a decrease in the flow rate was predicated based on the results of the A1B scenario. The results of the climatic model indicated that the pattern of the rainfall should change in the prediction periods as the rainfall decreases in the winter and spring, while it increases in the summer. This study offered a methodology for flow simulation and forecasting of future discharge via SWAT model. The effects of future climate change on flow quantity were examined. In this study, SWAT model was used to predict the impact of the future climate changes on river discharge. Model evaluation was done via Nash and Sutcliffe (NS), coefficients of determination (R2), P-factor, and R-factor. After model calibration, the predicted data under several climatic scenario were presented to the model. The results showed that the average of discharge will increase based on the A2 and B1 scenarios, while it will decrease under the A1B scenario. Therefore, it can be concluded that SWAT is a suitable model for discharge simulation in semi-arid areas. The results of this study also indicated that the combination of the results of LARS-WG and SWAT model should lead to an acceptable prediction of hydrological behavior of the rivers. It is important to notice that in this study only the effects of climate change on river discharge was evaluated. For a sustainable management strategy, other aspects of the watershed such as population pattern changes, land use change, and industrial development should be considered. The impact of the climate and land use change on water quality and soil erosion should also be investigated in the future studies.

The modeling can provide a quantitative approach and consistency in the estimationsoil erosion and sediment yield by a wide range of conditions. In this study, the integration method of revised universal soil loss equation model, geographic information system and remote sensing techniques were used in order to identify the spatial distribution of soil erosion and sediment yield in the Talar watershed. Parameters of rainfall erosivity, soil erodibility, slope length and slope gradient and vegetation cover were calculated in order to provision RUSLE map. The amount of soil loss was calculated from 0 to 9201 tons per hectare per year for the total basin and classification of erosion areas showed that erosion class of low, medium, high and very high with value of 33.12, 27.62, 21.13 and 18.13 percent respectivelycovered the total watershed. The linear regression analysis showed that in the between parameters of RUSLE model, the slope length and slope gradient parameter with value of 0.93 have the most correlation with the soil loss map. Also sw3 sub-watershed with value of 5580.33 tons per hectare per year and the sw4 sub-watershed with value of 19.59 percent have the highest and lowest Erosion hazard and Sediment yield respectively in the between sub-watersheds. The results showed that conservation and management measures can be useful to control and also reduce soil erosion and sediment yield in the Talar watershed.