مجله مهندسی و مدیریت آبخیز
سال دوازدهم شماره 1 (بهار 1399)

Destroying natural resources and environment is one of the most important problems in different regions around the world, especially in arid zones. So that extent areas of these zones are being destroyed in extensive spectrum of these destruction processes. For this reason, evaluating and providing vulnerability map of vegetation degradation in our country can considerably help the management and executive planning. In the present research, the criteria used in a new model called NIDLTS are proposed for evaluating the vegetation degradation. These criteria are natural index(N), human indirect index (I), human direct index (D), livestock pressure (L), trend of degradation (T) and state indicators (S). In order to estimate each criterion, a number of risk index were used. Natural indices studied in this research were climate change, draught, climate and suitability of lands. Human indices which were studied are population density, population growth, governmental expenses from executive works and researches, changing natural resources land to agricultural lands, percentage of unemployment, percentage of illiteracy. The indices of studied status are percentage of crown cover, production of the present biomass and production of the present biomass to the potential. Hazard index related to each destruction group were classified in to five classes of hazard intensity with numerical values in order to be analyzed in GIS. Then, the weight of each index and each main group of NIDLTS framework were calculated by Hierarchy Analysis Process (AHP); so that giving priority was done through investigating their share and effects in the vegetation decline. Finally, the vulnerability map of vegetation risk was generated through overlaying all the layers for each criterion in GIS. Results showed that among the human factors, the changing land use from natural resources to agriculture is the most important factor, whereas among the natural factors, drought is the most important factor in the study area. Also, among all the criteria, natural index has the highest effect and the trend of degradation of natural resources lands has the lowest effect in the vegetation degradation during the time. The final hazard map showed that the most widespread hazard class is moderate, followed by no-hazard in the region. It seems logical that the proposed model of NIDLTS for assessing the hazard of vegetation degradation can provide a more accurate estimation of vegetation degradation in a region with taking into consideration of the ecological, anthropogenic and hazard trend in comparison with some other evaluations that only consider the current state of vegetation degradation.

Water resources scarcity is the negative impact of climate change, which is more severe in arid and semi-arid regions, including Iran. However, harvesting water through micro-catchment is one of the possible issues for combating this problem. This research was conducted in Kaboodeh-Olya Village to compare the effects of three different micro catchment systems on runoff harvesting and increasing soil moisture. The experimental plots were constructed at a 20% hill slope in northern direction. Research was carried out in randomized experimental block with tree replications. Micro catchments were constructed in rhomboid-shape (1.7×1.7 m) and treatments included plastic with pebble pavement (PPP), compacted surface soil with crop residue (CSCR) and control plot (CP) which was a natural surface soil. The harvested runoff from each plot was stored in a container with 100 litter capacity at the downward. The valium of overland flow was measured after each rainfall occurrence. Results demonstrated that harvested runoff rates through PPP, CSCR and CP were 88, 44 and 16 percent, respectively indicating significant effects (p<0.05) of both PPP and CSCR on runoff harvesting. Furthermore, the effective rainfall for triggering runoff at the PPP, CSCR and CP were 0.8, 1.5 and 3.4 mm that significantly was lower in PPP. Consequently, in limited CSCR building, the SSS can be used for maximum runoff harvesting and soil moisture storage.

Understanding the base flow can be useful in river flow analysis, rainfall-runoff modeling, calibration of models, water resource management in low flow conditions and determination of the amount of water storage in watershed. In this research, 22 stations were selected with the appropriate data and common period of the years of 1982-2012. The trend of flow changes during the months of the year was determined for all hydrometric stations in the study area and the driest month was determined. Then, the calibration of six recursive digital algorithms was performed using the long-term data of the driest month of the year and after obtaining optimal parameters of the models, the base flow separation for the whole period was performed. The performance evaluation of the models was done using root mean square error. The results showed that the major part of the river flow in the study area was related to the base flow and the minimum, maximum and average annual base flow index for the whole period was equal to 0.48, 0.62 and 0.56, respectively, representing more than 50% of ground water contribution to stream flow of the studied watersheds. Results of the evaluation of the models using the root mean square error showed that the mean error in the research area for all the methods ranged from 0.025 to 0.044. The minimum was related to Lynie and Holick, and the maximum related to the One-parameter digital filter. Over all, conclusion of the results of the calibration process and investing the correlation between calculated and measured data showed that there was a correlation with a coefficient of explanation of more than 80%. Calibration method with dry season data in the absence of tracer-based methods is suggested as the most suitable method for calibrating digital separation filters in the study area.

The purpose of this study was to investigate the effect of climate change on the monthly discharge of Karoon Catchment as the largest basin in the country. In this study, five hydrometric stations (Bamdgeh, Telezang, Gharmaleh, Gotvand and Dezful) and three synoptic stations (Ahwaz, Dezful and Masjed Soleiman) were considered. Using the SDSM software, NCEP data and large-scale data from the general circulation model (HadCM3 for temperature and CgCM3 for water discharge) were scaled parameters under two climate scenarios A1B and A2 in the Karun Basin. Then, the climate change data and the output of the microscale model were applied to the SPSS 19 and Minitab 17 to predict the significance of water discharge for future climate courses (2020-2070) be simulated. Results of climate change analysis showed that under different scenarios, monthly air temperature in the scenario A1B increases by 1.60°C and in the scenario A2 1.58°C, but the average annual rate of stations in the scenario A1B is 19.82 m S-1 in size and 16.27 m S-1 in the A2 scenario. The modified Kendall and age tests were used to identify seasonal and semi-annual seasonal time series trends. Results also showed that under climate scenarios of discharge in spring and first half of the year, there was no significant trend at 95% of confidence, but in other seasons of the second half of the year, there was a significant decrease.

Groundwater resources management is one of the most important issues of natural resources management. Lack of proper management of these resources has caused serious problems such as land subsidence, aquifer salinity and the annihilation of wetlands. With population growth, has increased demand groundwater and led to water scarcity in many parts of the world including Iran. Estimating the economic value of groundwater is a fundamental step in water resources management strategies. The present study was conducted using interviews and questionnaires to estimate the average willingness to pay the population of the villagers living in Alashtar Plain. In this regard, some of the most important socio-economic variables of the studied population and their role in optimizing the management of groundwater resources have been studied. The statistical society in this research includes the population of villagers residing in the Alashtar Plain as the beneficiaries of groundwater resources in the area with a sample size of 490 was calculated by the Cochran formula. However, the average willingness to pay to protect groundwater resources for each household of the Alashtar Plain was estimated as 1,758,920 Rials per year. Results showed that the total value of groundwater protection in the Alashtar Plain is 8,913 Milion Rials per year. The protective value of one cubic meter of groundwater for the population that has stated their willingness to pay is based on a contingent valuation method of 208.647 Rials. It was also observed that the offered price variables, annual household income and level of education significantly affect willingness to pay for the respondents. Given the fact that there is no market for groundwater non-use value, the findings of this paper can be a powerful tool for decision making and water resources management for water sector managers.

The hydrological effects of climate change is a great challenge for water resources management. Determining climate change impacts on hydrological process is a prerequisite for adaptation strategies to climate change; which in turn is necessary for water scarcity crisis in future. The purpose of this research is to determine climate change impacts on hydrologic regim of Chehlcahy Watershed in Golestan Province. J2000 distributed process based model was used for simulation of the hydrological process. Output results of seven climate models including CanESM2، CCSM, BBC-CSM1.1, CESM1-BG, CESM1-CAM5, ICHEC- EC-EART and MPI-M-MPI-ESM-LR for two representative concentration pathways scenarios (RCP 4.5 and RCP 8.5) for 2071-2100 were used for climate change analysis. Results revealed that the maximum temperature for RCP 4.5 and RCP 8.5 in 2071-2100 will increase by 2.6 and 4.7 C and the minimum temperature will increase by 2.4 and 4.5 C, respectively by the end of the 21st century . In addition, precipitation for RCP 4.5 will increase by 0.6 percent and for RCP 8.5 decrease by 0.6 percent. Modeling results showed that these will lead to significant changes in the hydrological regime. In particular, evapotranspiration will increase by 9.6 and 16.7 percent and stream flow will decrease by 4.2 and 3.2 percent. The results of the  hydrological changes will cause a decrease in stream flow in April –June  and  for RCP 8.5 will be continued till October.

In order to monitor spatiotemporal variability of snow in mountainous areas such as Zagros in Iran, long-term records of snow observations with high spatial resolution are required. However, no such data are either observed or available for the stations of the Zagros region. Therefore, in this study, the Era-Interim/Land snow depth data for the period 1979-2010 were used in order to investigate the spatiotemporal variability of snow season length and the associated starting and ending dates in the Zagros region. To do so, for each hydrological year starting from October and ending in September, the first and last snow dates with snow depth equal to or greater than one centimeter were defined as the first and last day of observed snow on the ground and the time period between these two dates was considered as the snow season length. For each grid points over the study area, the time series of snow start and end dates, as well as the length of the snow season, were extracted and the rate of their temporal changes was estimated using the Sen Slope estimator and were examined using the Mann-Kendal trend test to test if they are statistically significant. Moreover, the considered time period was divided into three different sub-periods and the mean values of these parameters (i.e., first and last snow dates and snow season length) in the three sub-periods were also compared. The links between these parameters and the latitude, longitude, and altitude of the grid points were also examined. Results indicated that the spatial pattern of the first and last snow dates and snow season length fairly follow the geographical features of the study area and thus have a statistically significant relationship with the latitude, longitude, and altitude. Time variability of the considered parameters over all the studied grid points revealed that the date of the first snow in the most proportion of the study area retreated towards the late autumn and January and the date of the last snow also retreated towards March and February, thus, resulting in the shorter winter season in recent years. The observed statistically significant decreasing trend in the time series of the last snow dates towards March and February has the most contribution in shortening the length of the snow season.

Awareness of the drought status and the prediction of its future conditions play an important role in water resources management programs. In this regard, rainfall and temperature variables have a great influence on the severity and duration of this phenomenon. Regarding the status of the Urmia Lake in recent years and the water stress in its watershed, in this study, the drought situation in Saghez synoptic station as one of the important stations of this basin in different time-scales using the Standardized Evapotranspiration Index (SPEI) and SVM model with three linear, polynomial, and radial basis function and Bayesian network (BN) models, were investigated. For this purpose, the SPEI index in the short-term (1 and 3 months), mid-term (6, 12-months) and long-term (24 and 48-months) during the 49-year statistical period for monitoring the drought status at this station was used. Results showed that there was 8 prolonged periods of drought for the years 1962-1968, 1972-1974, 1978-1979, 1980-1982, 1983-1984, 1986-1987, 1999-2003 and 2007-2009 during the statistical period. Then SPEI values were applied to five input models with a delay of 1 to 5 months and SVM and BN models were used to predict drought. The results showed that in both methods, the model with 5-time delay had better performance and the linear basic function in the SVM method was more accurate than the other two functions. Also, the predictive accuracy of these models is directly correlated with increasing the SPEI scale, so that the correlation coefficient in the Bayesian network method at the test stage ranged from 0.174 in 1-month time-scale to 0.985 on a 48-month time-scale and in the SVM method with a linear basic function, it has risen from 1.149 to 0.983.

Measuring soil erosion and sediment yield using different methods is necessary to achieve integrated and reliable information from amount of soil loss. In this regards, the application of new and up-to-date innovative methods is required and important to facilitate the measurements, which leads to increase the accuracy. However, there is no enough information for the efficiency assessment of innovative techniques. An optic scanner method therefore was used in the present study to measure soil particles detached/transported by splash/runoff. Then, the obtained results were compared with two traditional methods. Including rillmeter and paraffin, which were applied for the measurement of rill erosion in the laboratory. For this study, first a clay loam soil was poured in experimental plots with 30×40 cm dimensions and slope of 20%. The study plots were then exposed to sheet erosion under simulated rainfall intensity of 50 mm h-1 with duration of 20 minutes. In the next stage, two simulated rainfall intensities of 90 and 100 mm h-1 with duration of 20 and 80 minutes, were applied, respectively. The output runoff and sediment were collected and measured. Consequently, the results of optic scanner were compared with sediment measurements and also rillmeter and paraffin methods. Average soil erosion amount at the intensity of 90 mm h-1 with duration of 20 minutes based on optic scanner, rillmeter and paraffin were 283.30±79.73, 35.8±49.27, and 45.93±9.22 gr, whereas average soil erosion amount at the intensity of 100 mm h-1 with duration of 80 minutes were 377.94±274.22, 41.5±45.71, and 46.20±11.45 gr, respectively. According to the results, it was clear that the results of optic scanner was significantly different from other methods and overestimated soil erosion.

During last decades hydrological models were extesively used in rainfall-runoff modeling. These models contain some constant parameters that must be optimized through appropraite mthods. In addation to model structur, the efficieny of hydrological models depend on these optimized parameters. In this study, the efficiency of three automatic optimizing algorithms including Dynamically Dimensioned Search (DDS), Shuffled Complex Evolution and Genetic algorithms in calibration lumped hydrological model HyMod in Ghorchay Ramian Catchment were investigated. For these mehods, convergence speed and variability of final optimized values were investigated. Results showed that Genetic algorithm converged faster than two other methods. Following, DDS algorithm converged faster than Shuffled Complex Evolution algorithm. Shuffled Complex Evolution and Genetic algorithms took shorter and longer time per each epock, respectively. Highest and the least variability of final results were obtained for DDS and Shuffled Complex Evolution algorithms, respectively. With respect to final results variability, Shuffled Complex Evolution algorithm was more satable and had better performance than other methods. Using analyse variance and comper means in Shuffled Complex Evolution algorithms for complexes less than 12, the model performance was increased as the number of complexe increased. As alpha value increased, the model performance decreased and model had the best performance at the value of 0.58. Conversely, model performance was increase as beta values increasd and the best perfromnce was obtained for beta equal to 1. For Genetic algorithm, the best performance was obtained when the value of values crossover, mutation and chromosome number was equal to 0.2 and 0.3 and 16, respectively.

In sedimentary rivers, mining of materials regardless of their location, can lead to rapid river displacement, destruction of river banks, arable lands, water structures and consequently makes social and economic problems. The main aim of this study is to recognize and evaluate all the effective parameters in material mining and determination of optimal site selection. In this study, the effective parameters that influence the extraction of river materials in Talvar River of Kurdistan Province have been evaluated using indexes as environmental, geological, geotechnical, hydrologic characteristics, social and economic conditions. For this purpose, Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) are used. The priority of input indexes into the model is obtained using questionnaires from experts related to water and river engineering. The weighting of the parameters is performed afterward using AHP method binary comparison. The GIS technique is then applied to integrate the information layers by overlaying them. Eventually, the maps of optimum and suitable points were extracted for river mining. The morphological results of this study showed that the straight lengths of the river are more sensitive to the variations of bed level compared to meander sections and it is necessary to extract the material in these lengths with same depth and width. According to the results, sediment hydraulic index has the maximum weight due to determination of sediment deposit sites. The results also demonstrated that the first priority of river materials mining came to places that have low longitudinal slopes, placed in bends and are close to access roads.

Chaharmahal and Bakhtiari Province with one percent of total area in Iran, covers 10 percent of total precipitation. Also, Karoon and Zayandehrood rivers are originated from this province. In recent years, the different watershed operations have been performed to control and maintain surface water in the province. This research analyzed effective factors on rural participation in watershed management operations in Monj-Bideleh Basin of Lordegan in Chaharmahal and Bakhtiari Province. Required data were compiled with questionnaire and analyzed with descriptive and inferential statistics in SPSS. The results showed that relationship between age, main gob and experience in agriculture with participation is negative and insignificant. In contrast, the relationship between satisfaction, social versatility, socio-economic situation, membership in public institutes and village, and use of informational resources with participation is positive and significant in one percent. The results of multiple regression estimation in stepwise indicate that knowledge of the objectives and characteristics of the watershed management plan has the highest portion in participation in watershed management activities.

In most water resources studies, the bed load transport rate is considered as a constant proportion of total load due to the difficulty and costs associated with measuring of it, which is not reasonable due to the high variability of this ratio. In this study, data collected from 19 coarse-grained rivers in the United States were employed to predict bed load, total load transport rates and the ratio of bed to total sediment load using Support Vector Machine which is a branch of intelligent methods. Next, the results were compared and evaluated with classical methods. Results showed that this method has a very high performance compared to the classical methods and performance criteria in predicting the bed to total sediment load ratio has acceptable results. In addition, the modeling showed that the ratio of average velocity to shear flow velocity and the Froude number is the most effective parameters in predicting bed load, total load and the ratio of these.

The rain process is affected by numerous environmental factors such as dust events and the interaction of these two events can influence the hydrological cycle. According to various reports on increasing of dust occurrences in different regions, this study aimed to investigate the potential impact of dust storms on rainfall in Khorasan Razavi during 2000-2013. The statistical method of "historical regression" was used to investigate dust effect on rainfall, which is based on comparison of observed rainfall with its prediction. Nine synoptic stations were selected as target stations. Regression equations were used to predict precipitation of target stations using the daily rainfall data of the hydrometric stations using the Least Squares Method. Then, the statistical ratio index for historical regression was calculated for each target station based on the observed and predicted rainfall values. The statistical ratio of each station was evaluated by Monte Carlo of permutation test using R-software. Since relative humidity variations play important role in the precipitation process, the correlation coefficient was calculated between the relative humidity and the statistical ratio index of each target station. The statistical test of correlation between relative humidity variables and the statistical ratio of historical regression were significant for all stations. The permutation tests for each station statistical ratio index showed a variable effect of dust on rainfall. The lowest statistical ratio index of 0.8 belonged to the Neyshabur Station with a relative humidity of 38%, whereas the highest statistical ratio index of 1.5 was found for Torbat Heydarieh Station with a relative humidity of 59.45%. In the present study, precipitation response to dust events was affected by relative humidity conditions. In a general conclusion, components of hydrological cycle does not have constant response to environmental variables and therefore, obtained comprehensive conclusions in atmospheric processes need more extensive studies.

Metaheuristic algorithms have been increasingly used in different fields. The application of these algorithms for identifying and modelling natural phenomena such as flood and drought in terms of complexity and non-linear interactions can be considered as their capability in hydrology. In this paper, Symbiotic Organism Search (SOS) algorithm was first introduced, then its application in tuning fuzzy expert system, aiming to find the region of influence area of hydrometric stations in the Southern Caspian Sea Basin. This basin has regularly experienced flood events, causing human loss and properties damages every year. The outcome of this research is used to estimate floods, and subsequently, to design flood control structures. A total of 61 hydrometric stations were selected in the study area and their physical, climatic and hydrologic characteristics including area, perimeter, minimum elevation, maximum elevation, mean slope, stream length, slope of main stream, equivalent rectangle length, equivalent rectangle width, form factor, shape coefficient, Gravelious factor, round coefficient, and mean annual precipitation were determined. Results indicated that out of 16 parameters, area, mean elevation, form factor, Gravelious factor, and mean annual rainfall, were the most significant parameters in relation to flood by employing the SOS. These variables were used as the input variables into the fuzzy system and SOS algorithm to tune the fuzzy system. Finally, the efficiency of the SOS algorithm was evaluated using the linear torque heterogeneity statistic. Therefore, 61 influence areas were determined that show homogenous areas in 61 watersheds. Results indicated the performance of SOS in determining region of influence of the sub-basins in the study area. In addition, the geographical vicinity is not a suitable criterion for finding homogenous areas.

Fertile soil loss is one of the negative effects of wind erosion that reduces soil productivity. In this research, the effect of two stabilizers has been studied for reducing nutrients loss of western Khuzestan soils in the soil laboratory of Ahvaz unit of Azad University in summer 2018. For this reason, wind erosion simulator was designed and built. The effectiveness of two stabilizers (anionic polyacrylamide polymer and vegetable-based mulch), in four concentration levels (0, 15, 30 and 60 percent) on three types of soils with three replications were studied in 47 km h-1 wind speed in the wind erosion simulator. In total, 72 soil samples were examined in a Factorial test and in the form of complete random design. Results showed that wind erosion happened between 27.04 and 44.7 gr m-2 min-1. Statistical analysis showed that there is a significant difference between the stabilizers and control. The polymer reduced soil loss by 99%. The vegetable-based mulch reduced soil loss more than 98% in Alvan and Hoveyzeh samples. But, in Borvayeh samples at 15 and 30 percent of concentrations soil loss has been reduced by 13 and 67 percent, respectively. The average loss of nitrogen, phosphorus and organic matter were 1.59, 0.64 and 0.6 gr m-2 min-1 that causes serious environmental and economic problems for the land exposed to erosion. The polymer reduced the loss of nitrogen, phosphorus and organic matter by 99 percent. The vegetable-based mulch reduced the loss of nitrogen, phosphorus and organic matter by 98 percent in Alvan and Hoveyzeh samples and 56.6 percent in Borvayeh samples. Using stabilizers with cultivation of native plants can stabilize the soil against wind erosion.

Analysis of suspended sediment load data in rivers is the basis for understanding the trend of erosion and sediment in the management and planning of soil and water resources. Due to lack of access to daily suspended sediment loading data with direct measurement, it is important to use methods for modeling and estimating it in watersheds. One of the best methods used in this field is the use of artificial neural networks. To evaluate daily suspended sediment load, Sira hydrometric station was studied in Karaj River watershed. The number of data used in this study included 624 information records of 31 years (1981–2011) statistical period .Input data to the artificial neural network models included instantaneous flow discharge, average daily flow discharge, average daily flow discharge with a delay of three days, average daily precipitation and average daily precipitation with a delay of three days. Output data to models was daily suspended sediment load. In this research, gamma test and genetic algorithm were used to obtain optimal variables and best combination of variables for entering the model. Then, these combinations with some combination of test and error variables were entered to artificial neural network models. The self-organizing map neural network was used for data clustering and all data were divided into three homogeneous groups: 70 percentage training data, 15 percentage validation data and 15 percentage test data. Then, the combination of variables entered to neural network models with activation functions log sigmoid and tangent sigmoid. The results showed that the neural networks using the optimal variable combinations in comparison with manual combinations have a more accurate estimate for suspended sediment load. In all combinations of inputs to neural network models, a model with tangent sigmoid activation function, with input variables combination including, instantaneous flow discharge (Q), average daily flow discharge (Qi), average daily flow discharge for two day ago (Qi-2), average daily flow discharge for three day ago (Qi-3), average daily precipitation (Pi), average daily precipitation for two day ago (Pi-2) and average daily precipitation for three day ago (Pi-3), was the best model for estimating daily suspended sediment load. This model has the lowest of error (MAE=500.05 (ton/day), RMSE=1995.33(ton/day) and Erel=7%), the highest accuracy (R2=0.96), the highest performance model (NSE=0.96) and has the lowest general standard deviation (GSD=0.97) compared to other models. Also, this model is the best combination with the most influential input variables derived from gamma test and genetic algorithm for estimating SSL.

This research focused on studying the morphometric characteristics, topographic threshold of gullies and their relationships, dominant process of gully initiation and development stages as well, in agricultural and rangeland land uses. Also, morphometric characteristics of 120 gullies including top width, bottom width and headcut height and surface characteristics of gullies contributing area including vegetation, rock fragment and bare soil by 1 m2 plot and soil samples from top soil and gullies wall were collected in semi-arid part of Ilam Province. Results showed that top width–depth ratio of gullies in cropland and rangeland is 2.1 and 1.5, respectively that widening and deepening has more important role in gully growth. Top width-length ratios are 0.41 and 0.57 in croplands and rangelands, respectively that shows rangeland gullies are more elongated. Negative exponential relationship between those ratios and slope shows the effect of topographic factors especially slope on final shape of gullies. Bottom width-top width ratio in croplands and rangelands is about 0.33 and 0.3, respectively and cross section shapes are trapezoidal and V shape. Results showed that slope describes 16 percent of cross sections area variation and lateral growth of gullies in croplands and rangelands and describes 84 and 73 percent of gully volume variation. Effective factors on gully volume are sand content in top soil, land use and slope. Studied gullies in both land uses have mean fractal dimension of 1.08 and has linear growth with length and power growth with volume of gully. Power of Hack law in studied gullies in croplands and rangelands gullies are 0.5 and 0.54, respectively.

Tectonic activity affects the formation, deployment and evolution of  landforms as well as erosion processes. The existence of several faults and anticline in the west of Khuzestan Plain has also led to changes in morphology and the establishment of landforms such as sand dunes. Therefore, the research is aimed to determine the effect of tectonic activities on the morphology and behavior of sandy hills in west of Khuzestan Plain. To achieve the above goal, the following information layers were provided. The layers included Ahwaz geological map with a scale of 1: 100,000 and a topography of 1: 25000, field observations, as well as results from the processing of Landsat satellite images and IRS from 1991, 1998, 2002 and 2006. In addition, other GIS layers was used such as faults, anticlines and units, geomorphic units, sedimentary environments and drainage networks. Data analysis was also conducted based on field observations and geomorphic techniques and a comparison method. The results of geomorphologic indices such as coefficient of sinousity and integral hypersometry showed that the study area was strongly influenced by tectonic activity and morphotectonic units such as Hamidyeh-Ahwaz, Zeynol Abbas and Abol Gharib anticlines. However, other secondary factors such as the wind direction and the pattern of the flow of the Karkheh River, change the overall trend of sand dunes. It also causes sediment transfer from sand dunes to flood plains and dust production centers in the west of Khuzestan Plain. Therefore, the findings of this research can lead to the provision of necessary information for soil protection against wind erosion in the province, especially in the center of number one dust (Hooralazim), erosion and sediment sources along the Karkheh River Basin.

The geomorphological changes of the bed and bank of rivers can affect the migration and expansion rate of the meandering rivers. A knickpoint in the bed slope is one of the most common geomorphologic changes in the river. Measuring the migration and expansion rate of meandering rivers, in addition to taking the necessary actions in order to protect the structures located along and over the river are considered as engineering measures in the field of river engineering. In this regard, to study and measure the rate of migration and expansion of meandering rivers with knickpoint in the flow at downstream, experiments were carried out in a laboratory flume with an erodible bed. The channel was carved on the sedimentary bed, and was studied and evaluated the migration and the expansion rate in to two experimental groups in the presence and absence of the knickpoint (control tests) for three different widths of the channel (different wavelengths of the initial bend), three discharges, and three different bed slopes. Results showed that the flow began to create meandering bends at a very high rate in order to modify the knickpoint at downstream, and as a result, the migration rate of meander has increased compared to the control experiments and decreased the expansion rate. An increase in the rate of migration up to 32% and the decrease in the rate of expansion up to 36% are achieved by comparing the results of experiments with presence of the knickpoint at downstream and its absence.

The climate change over the past few decades, and consequently decrease in the precipitation, along with the population growth in different regions in Iran have led to an increase in demand for water for domestic agricultural, industrial, etc. consumption. This has led to uncontrolled exploitation of groundwater resources, causing severe decrease in the groundwater level. Artificial recharge technique is one of the methods to compensate for the groundwater deficit, especially in arid and semi-arid regions. Selection of suitable sites before artificial recharge can help improve the efficiency of the project and ensure its success. Having in mind the problems related to decrease in groundwater resources in Tehran due to the increasing population and the expansion of industry and agriculture. This study aims to identify and zoning of regions that are suitable for artificial recharge of groundwater in Tehran Province. The GIS can help determine such regions more precisely, faster, and with better results. For this purpose, the present study integrated GIS and Fuzzy AHP to weigh and combine factors that play a positive role in artificial recharge, such as the depth and changes in the groundwater level, precipitation, drainage density, elevation and land slope, distance from fault, distance from river, geological properties, and land use. After investigating the views of experts about the binary comparison of the criteria, and prioritizing them using AHP, it was found that the hydrological properties were the most effective criteria for the subject under study. Results indicated that 6.2% and 15.75% of the entire area of the region under study are very suitable and suitable for artificial recharge of groundwater, respectively. Very suitable regions are mostly located in the east of the province, with suitable geologic formations, short distance from river, and predominant rangeland and agricultural land use. They also, have a very low and decreasing groundwater level.

Increasing the greenhouse gases not only has impacts on the weather parameters, but also, has impact on water resources, agriculture, environment, health and economy. Climate change has significant effects on water resources by changing the hydrological cycle. There are several simulation methods for investigating the effects of climate change on different systems in the future, like climate models. The AOGCM model is able to simulate global climate in an area of some ten dousant km2, but, while they are not suitable for regional scale. For this reason, downscaling methods such as dynamic methods are used. These methods are based on high resolution and analysis of climate models. In this research, the impact of climate change was investigated on the low flow of Karkheh Basin as one the most important basins due to its water product and agricultural point of view. For this purpose, the PRECIS which is exponential dynamics and downscaling model, was used to estimate the temperature and precipitation in the period of 2070 to 2100 under A2 and B2 scenarios. The SWAT model, a comprehensive and continuous hydrological model was also used to estimate the flow discharge for the watershed. After calibration and validation of the SWAT model, the amount of rainfall and temperature used as input for PRECIS model under different climate scenarios and finally the daily flow rate was estimated for sub-basins. Then the indices of low flow rates (Q75, Q90 and Q95) and low flow series frequency analysis of 10 and 30 days were assessed. Results showed that rainfall and flow rate have negative and temperature have positive trend. In general, the results of PRECIS model indicated that this model has a good estimate of temperature and precipitation in the region, but, it is not strong for rainfall in autumn and spring, due to the local nature of the precipitation. The climate change assessment under scenario A2, indicated the rise of low flow rate by 70 percent, and this increase of low flow was more in the northern parts of basin, while under the scenario B2 the low flow rate droped by 50 percent for the period of 2080. But, low flow distribution had no change compared to base period.Thus, sever droughts would happen in the central and some northern parts of basin. It can be concluded that under different scenarios, climate change has different impact on the low flow rate. Therefore, due to the different impacts of climate change on low flow rate under different scenarios, uncertainties of scenarios as well as regional economic and social status should be considered in the management plans.

Gully erosion is one of the main types of water erosion and is known as one of the destroying forms of land degradation and soil loss in the world. Therefore, knowing the most effective factors on extending this type of erosion is utmost important. Beside, management and control of gully erosion require knowing the most effective factors on gullies extension. So, the present study was performed to determine the most effective factors on gullies in Khorrambid Watershed, North of Fars Province through measuring the permanent gullies during 13 years (2004-2016). Results showed that the average of gully length extension was 21.67 m throughout this period. This data indicated that the length of gully extension was 1.67 m per year. Further, it is determined that the length expansion of permanent gullies in this region was a function of bare soil and saturated electrical conductivity, using SPSS and backward multivariable regression. In conclusion, it is suggested different management solutions to increase the soil resistance against the erosion be prioritized in management and implementation plans such as increasing adoptable cover vegetation for the natural condition of the region and exclude the area to restore vegetation cover and pay more attention to control erosion in gully head cuts.

People participation in the implementation of natural resources practices is one of the approeches that ensure the fulfillment of the goals and success of the projects. In this study, based on expert experience and different projects of natural resources implemented in watershed area surrounding city of Tehran, the preventing social indices and sub-indices affecting on people participation were recognized and determined into three indices and 10 sub-indices. Obtained results from prioritizing effective social indices on preventing people participation in natural resources plans based on obtained weights from AHP method and expert questionary indicate that “unfavorable behaviorial indices” with weight of 0.623 and “unfavorable demographic indices” with weight of 0.130 have respectively maximum and minimum priorities, in the manner that prioritization of indices based on weights from maximum to minimum importance are “unfavorable behaviorial indices”, “cultural problems” and “unfavorable demographic indices”.Obtained results from prioritizing effective sub-indices based on expert questionary and the Kendalls' W rank test indicate that sub-indices have different roles on preventing people participation in natural resources plans, in the manner that the indices of “shortage of people trust in considering their ideas” with rank mean of 6.80 and “being low literacy and knowledge” with rank mean of 3.16 have respectively maximum and minimum priorities. The results also show that the index of “shortage of people trust” has the most priority as a preventing factor affecting on people participation, in the manner that two sub-indices of “shortage of people trust in considering their ideas” and “shortage of trust to continue projects”are two first priorities, respectively. Sub-indices of “shortage of young people in villages” from index of “unfavorable demographic indices” and also “being low or lack of culture of participation” from index of “cultural problems” were ranked as the most important social sub-indices.

In the last decades, greenhouse gases in atmosphere have increased as a result of natural and human activities and thus, earth temperature has increased. Rising global temperature, in turn, leads to significant changes in related fields, especially water resources and agriculture. So, investigating and modeling climate changes can be considered as a very important factor in water resources management planning. Different studies have been done in the field of climate change issues in the world, but, at the moment, AOGCM model is the most reliable tool to generate climate scenarios. It is necessary to downscale AOGCM data using different techniques in station scale and compare linear and nonlinear downscaling models. In liner method SDSM and in nonlinear method ANN programming were used in MATLAB. For investigating the amount of error, mean biomass monthly and annual and for extreme data, variance and for analyzing uncertainty Man-Witney test were used in 95 percent level. Results showed the amount of mean monthly errors are 0.75, 12, 11 and 7 mm in Ghaemshahr, Babolsar, Ghoran Talar and Bandpey in SDSM model and 3, 2, 26 and 4 mm in ANN model and the amount of mean annual errors are 9, 146, 141 and 87 mm in SDSM model and 45, 32, 321 and 48 mm in ANN model (increased or decreased), respectively. Examining the performance of variance showed that ANN model was somewhat better than SDSM model. Also, results of uncertainty for 12 months in Ghaemshar, Babolsar, Quran Talar and Bandpey stations showed 8, 3, 6 and 4 in SDSM model and 4, 2, 2 and 3 in ANN model, respectively. In general, this study showed that in studies on climate change effects on runoff, uncertainty, and when limited data are available, SDSM model should be used and when the aim is investigating the flood and its minimum and maximum estimation, it is better to use ANN model.