نشریه پژوهش های حفاظت آب و خاک
سال بیست و هفتم شماره 5 (آذر و دی 1399)

Changes in meteorological and hydrological patterns have led to the use of water resources management tools to find a suitable solution for optimal reservoir operation. Regarding to the inability of conventional optimization methods in solving the complex optimization problems, the use of meta-heuristic algorithms has been considered more than before.

In the present study, a combined model of Crow Search (CSA) and Gray Wolf (GWO) Optimization algorithms called Gray Wolf - Crow Search Hybrid algorithm was introduced for the first time in the field of reservoir operation optimization. And its performance was evaluated in comparison with its constituent elements as a powerful tool for optimizing the operation of the single reservoir system of Golestan Dam, considering the objective function (providing downstream water demand). To compare the convergence and performance of these algorithms, the statistical parameters of each algorithm were calculated and compared with each other, as well as with the solution of non-linear problem solving model (i.e., GAMS Software). Then, in order to analyze the performance of the algorithms, the Combinative Distance-based Assessment (CODAS) Multi-Criteria Decision Making Model was used to rank the decision alternatives (e.g., optimization algorithms) based on volumetric and time based reliability, reversibility, vulnerability criteria and the optimized objective function.

The results suggest that the GWOCSA hybrid approach has a response closer to the absolute optimal value, with an average response rate of 93% of the absolute optimal response and an average of 92% and 83% of the GWO and CSA ones. In addition, the correlation coefficient in the hybrid algorithm is 23 and 1.67 times lower than that of the gray wolf and the crow search algorithm, respectively. On the other hand, the GWOCSA hybrid algorithm performs the best, except in terms of reversibility index in other indicators. The CODAS Multi-Criteria Decision Making Model also identified the GWOCSA algorithm as the first to solve the problem of the reservoir operation compared to the other two passive algorithms. The gray wolf and the crow search algorithm then rank second and third, respectively.

The CODAS Multi-Criteria Decision Making Model identifies the GWOCSA algorithm in optimizing the objective function better than its constituent algorithms, namely CSA Optimization and GWO algorithm. And the gray wolf and crow search algorithm are then ranked second and third, respectively, so that not only is GWOCSA better at finding the optimal answer, but it also improves performance and increases the efficiency of the hybrid algorithm according to the model performance evaluation indicators.

Quantifying the uncertainties of the parameters of hydrological models are the role of great importance in water resource management and is a challenge that due to the large number of parameters and lack of proper physical understanding of them, these models face problems in the calibration stage. Considering the importance of water resources in Iran and the need to investigate uncertainty in order to achieve reliable results, the purpose of this study is to investigate, identify and quantify parameters uncertainty of Soil and Water Assessment Tool (SWAT) and their performance to predict watershed runoff. The Kashfrood river is a semi-arid large-scale basin in northeastern Iran using a Monte Carlo chain-based Markov chain simulation method called the Differential Evolution Adaptive Metropolis algorithm (DREAM-ZS).

With the purpose of assess the uncetainty in this study only 20 out of 29 available parameters were selected and evaluated based on Regional Sensitivity Analysis (RSA) as sensitive parameters. In order to optimize the model and quantify the parameters uncertainty, scenarios S1 (first scenario) and S2 (second scenario), which belong to the DREAM-ZS algorithm, have been defined. The prior parameter ranges of the S1 scenario were determined using the final calibration of parameter ranges in SWAT-Calibration and Uncertainty Program (SWAT-CUP) software and Sequential Uncertainty Fitting version 2 (SUFI 2) algorithm, and the prior ranges of the S2 scenario were determined using a compromising approach between the prior ranges of the SWAT-CUP and posterior ranges from S1 scenario. In this study, the parameters, uncertainties and statistical analysis have to be computed via an appropriate likelihood function. Therefore, the Differential Evolution Adaptive Metropolis (DREAM-ZS) combined with the standard least squares (SLS) as a simple formal likelihood function. Also, to evaluate the performance of the model uncertainty in the two mentioned scenarios, evaluation criteria including P-factor, d-factor, Nash–Sutcliffe (NS), Total Uncertainty Index (TUI) and Average Deviation Amplitude (ADA) were used.

P-factor, d-factor, Nash–Sutcliffe (NS), Total Uncertainty Index (TUI) and Average Deviation Amplitude (ADA) showed that the S2 scenario has a better performance than scenario S1 in reducing forecast uncertainties. According to S1 simulation, the NS coefficient ranged from 0.54 to 0.72, while in S2 simulation, it ranged from 0.63 to 0.78. The TUI for total uncertainty was in a range of 0.2–0.6 and 0.22–0.66 for S1 and S2 scenarios, respectively. The S1 and S2 simulations led to the TUI of 0.63–0.94 and 0.74–1.22 for parameter uncertainty, respectively. Finally, ADA index for total uncertainty was 0.098 and 0.445 for S1 and S2 scenarios, while in accordance to S1 and S2 simulations, the ADA index for parameter uncertainty was 0.098 and 0.451, respectively.

The DREAM-ZS algorithm improved the calibration efficiency of the model and led to the presentation of more real values of runoff simulation parameters by the SWAT model in the Kashafrood River Basin.

One of the newest techniques for pollutant removal from soil and water resources is utilizing nanotechnology. Application of zerovalent iron nanoparticles (ZVINs) for filtration of soil and water resources is growing as fast as possible due to non-toxic, high reactivity, high surface area, and high adsorbent power characteristics. By increasing ZVINs transport, the reduction and removal efficiency of different pollutants from the goal media will increase. So analyzing the effective factors on ZVINs mobility and transport and realizing the effective mechanisms on ZVINs transport and retention of them in the soil is so vital. Utilizing the guar gum as the natural and green polymer will cause to improve the ZVINs stability. The guar gum as a water soluble and natural polymer from polysaccharide groups has beneficial characteristics comprising of non-toxic, hydrophilic, high stability, low sedimentation due to high static viscosity, low injection pressure due to low dynamic viscosity and especially non-expensive and reducing project costs. The objective of this research was to simulate biodegradable polymer stabilized ZVINs transport in sand columns using HYDRUS-1D software and investigation the effects of initial particles concentration and ionic strength on ZVINs transport and retention in porous media.

The ZVINs were synthesized using chemical reduction of ferrous sulfate by sodium borohydride. In this research, five different ZVINs stabilized with different polymers including biodegradable polyacrylamide (PAM) and polyvinylpyrrolidone (PVP), green natural guar gum (GG) and polystyrene sulfonate (PSS), and bare zero-valent iron nanoparticles were synthesized for preventing ZVINs from being aggregated. The ZVINs were injected in the sand columns in the form of pulse input for a fixed period of time (15 minutes.) using peristaltic pump. The research was conducted using two separate factorial experiments designs as a completely randomized with two factors and three replications (factors of experiment 1: ZVINs types and ZVINs dosages; factors of experiment 2: ZVINs types and ionic strength). Transport of ZVINs and chloride (Cl-1) were simulated by HYDRUS-1D and CXTFIT software, respectively. Kinetic attachment-detachment model colloid with filtration theory (CFT), physical straining, lungmuirian, and blocking models were used to simulate ZVINs transport in soil.

The results revealed that with increasing ZVINs concentration and solution ionic strength, the ZVINs transport in the sand columns decreased. The results also indicated that colloid filtration theory (CFT), physical straining and lungmuirian blocking mechanisms had more accurate to predict ZVINs transport in the porous media, respectively. The results showed that PAM, PVP, PSS, GG stabilized ZVINs and the bare ones had maximum transport in sand columns, respectively.

Transport of ZVINs in the sand columns were increased by stabilizing and application of biodegradable polyacrylamide (PAM), polyvinylpyrrolidone (PVP) and Gurgum (GG) coatings as natural and green biopolymers. The findings of this research showed that applying of guar gum as a natural and green polymer improves the ZVINs stability. Therefore, current polymer is a suitable substitute for artificial polymers. The results also revealed that guar gum due to non- expensive, non-toxic, abundance, and low dynamic viscosity could be used as the ZVINs stabilizer for field scales; therefore, the field injection and target pollutants reduction costs would be diminished as a result. Overall, simulation ZVINs transport is so vital for understanding of mechanisms which control ZVINs transport and retention in soil.

Determining the optimal water consumption in Iran with a large percentage of arid and semi-arid climates is important. several methods, including linear and goal programming, have been used for this purpose. Applying Game Theory Method to Solve Management Problems that Facing Conflicts between Goals can be a different approach to optimizing water use in agriculture. It can offer a different approach to optimizing water use in agriculture, therefore in this study cropp pattern and the optimal harvesting of groundwater resources was determined in Ghare-Su basin.

Golestan province has less rainfall than other northern provinces despite being located in northern parts of Iran. Most of the demand water in this province is supplied by groundwater resources, which, if not properly managed, will face the risks of reducing groundwater aquifers level. So the cities of Gorgan and Kordkuy in west of Golestan province, located in Gharasso basin, are considered as a study area in this research. After providing information on the area of cultivation, the cost of production and the price of sales of major agricultural products, net irrigation demand was calculated considering irrigation efficiency the potential of water resorces and recharge basin from Regional Water Company of golestan. After preparing the data with considering water resource constraints and arable lands and also considering the goals of increasing profits and reducing water use to optimize the water harvesting values was determined by game theory conflict resolution methodology that including non-symmetric Nash equilibrium, Kalai-Smordinsky solution, area monotic solution and equal loss function method.

The optimal operation of water resources with non-symmetric Nash equilibrium, Kalai-Smordinsky solution and equal loss function method of game theory while considering equal weight for economic and environmental purposes and It is equal to 205 million cubic meters per year and optimum harvesting value was obtained 183 million cubic meters per year by using area monotic solution. This is in a situation that is considered for economic purposes as 0.575 weight and for environmental purposes as a weight 0.475. Therefore, the harvesting of water resources can be reduced by 43% to 49% to achieve environmental goals. In this method, planting of crops such as cotton, tomato, barley and soybean in Gorgan and barley in Kordkoye city is not recommended. Wheat is also the most cultivated area in Gorgan and spring soybean in Kordkoye.

The results showed that is no optimal crop pattern in the current condition and the current harvesting value is higher than the aquifer recharge. Therefore, using game theory, can determine the crop pattern and optimal harvesting value that economic and environmental goals were met by applying different weights.

Iran is one of the major date-producing countries and not only has a long history in this field, but also it currently has the second grade of Date production in the world. Therefore, the cultivation and production of Dates in Iran is of particular importance both nationally and for the inhabitants of the producing provinces. In this regard, planning for optimal utilization of production resources such as soil and lands for development of the yield in the country has a special place. Consequently, evaluation of land suitability and utilization of lands in proportion to their potential and capacity for specific land use seems an important solution. However, one of the necessities of land suitability assessment is to determine the crop requirements of the plants such as the status of the soil as a production bed. The objective of this study was to investigate the effect of soil characteristics on Date yield and their rating for use in land suitability evaluation studies.

First, 91 palm Date orchards were selected with diversity of soil and yield in Kerman, Fars, Khuzestan, Hormozgan and Bushehr provinces, in each garden, a soil profile was studied and a land use questionnaire completed. Physicochemical and fertility analyses were carried out on the collected soil samples. Multivariate regression was investigated between yield as dependent variable and independent variables including salinity, percentage of exchangeable sodium, pH, gypsum, calcium carbonate equivalent, clay, sand, silt, gravel, available potassium and phosphorus by stepwise method. Then, by checking the relations of simple regression between the important and effective characteristics with yield, related equations and diagrams were drawn and the rating of land characteristics set. The proposed crop requirement table was evaluated and validated using soil and yield data of 20 orchards.

Results showed that potassium, sand percentage, soil salinity, ESP and CaCO3 had the highest and soil organic carbon content and pH had the least variation. Maximum amount of lime and gypsum was 74 and 17% and soil texture varied from sandy to clay, respectively. Regression results showed that independent variables including soil salinity, ESP, CaCO3, gypsum, gravel, available potassium and phosphorus were effective on yield, respectively. The determination coefficient of multivariate regression indicated that the variables entered into the model can determine 79% of the variance related to the dependent variable. In simple regression equations, soil salinity, ESP, gypsum, CaCO3 and gravel had a decreasing effect and organic carbon, available phosphorus and potassium had increasing effect on yield. The highest contribution to the decline in Date yields was related to soil salinity, gravel, ESP and calcium carbonate.

The coefficient of determination between yield and soil index obtained from the proposed soil and landscape requirements table for the Date was about 0.79 which showed acceptable accuracy of the prepared table. Soil salinity, ESP, gypsum and calcium carbonate limit for Date palm were determined 8 dS/m, 12, 8 and 38 percent, respectively.

Evaluation of irrigation systems consists of analyzing the measurable performance of the system in operation conditions, is a management tool that allows the system users to make the best use of the irrigation systems. Since various regions in Iran have arid and semi-arid climates, obtaining the actual wind drift and evaporation losses and also making optimized use of water towards sustainable water resources management has a great importance. Since estimation of evaporation and wind losses that has been presented in different climatic conditions has different results, and it is not possible to present a reference model, so the purpose of this study is to investigate the effective climatic parameters on evaporation and wind losses of the Center Pivot system and to present an optimal model using multivariate regression in the study area.

This research has been carried out in the city of Pars-Abad in Ardabil province. The study was conducted in Part of the Moghan Agro-Industrial Complex, at wind speeds of 0-3 and 3-6 meters per second with three replications. Experiments were performed on two Center Pivot Irrigation System in sections 5 and 6 of Moghan Agro-Industrial Complex (1-4-6 and 1-8-6), which included two design treatments. The average altitude of this area is 32 meters above the sea.

Results indicated that the efficiencies of the system at wind speeds of 0-3, 3-6 meters per second were 89.47, 84.47 percent, respectively, and wind speed, temperature, relative humidity, nozzle diameter, and vapor pressure deficit (saturation deficit) were among the factors that influenced wind drift and evaporation losses. Base on the results, the wind factor had the most and vapor pressure deficit had the least effect on wind drift and evaporation losses. Also, the equation of wind drift and evaporation losses was also obtained with the atmospheric conditions of the region, which had the best fit with the measured values. Results shown that the difference between results of the model and observed data was not significant in 1% level of confidence. Moreover, the measured and the modeled percentages obtained for wind drift and evaporation losses varied from 7 to 18 and from 10 to 18 percent, respectively.

The results show a direct relationship between the evaporation and wind losses with wind speed in the region. So that at wind speeds of less than 3 m/s the parameters of Coefficient of Uniformity, Distribution Uniformity and potential and Application Efficiency of the low quarter are in the appropriate range, and at medium and high wind speeds, evaluation parameters are not in the desired range, it is indicating the importance of center pivot system design in windy regions.

This research has been carried out in the city of Pars-Abad in Ardabil province. The study was conducted in Part of the Moghan Agro-Industrial Complex Province at wind speeds of 0-3 and 3-6 meters per second with three replications. For the experiment, two rows of cans at an angle of 3 ͦ were positioned radially along the center of the centripivot system 10 m apart. The sprayer used in this study was F33AS 11/64˝ with 26 m of spraying diameter and operating pressure of the sprinklers varied from about 2 to 2.5 bars.

Results indicated that the efficiencies of the system at wind speeds of 0-3, 3-6 meters per second were 89.47, 84.47 percent, respectively, and wind speed, temperature, relative humidity, nozzle diameter, and vapor pressure deficit (saturation deficit) were among the factors that influenced wind drift and evaporation losses.

Contamination of soil and water by heavy metals have accelerated since the beginning of the industrial revolution. So cleaning up and removing of the contaminants is one of the major challenges of human societies. There are different methods for remediation of contaminated environments and adsorption and immobilization of heavy metals by the adsorbents is one of them. In addition to being effective and fast, the immobilization technique is simple, inexpensive, and environmentally safe. In recent years, the use of polymeric composites, among the various adsorbents of heavy metals, has attracted the attention of many researchers due to their higher efficiency in comparison of pure adsorbents. Chitosan composites are among those polymeric composites that, due to their properties, can have a high ability to absorb heavy metals in contaminated environments. Chitosan composites have often been used to remove heavy metals from industrial wastewater, however, the efficiency of these composites in immobilization of heavy metals in soils has not been studied. Due to the great variety and environmental safety of these composites, this study aimed to investigate the efficiency of pure and chitosan coated adsorbents in immobilization of soil cadmium.

For this purpose, a pot factorial experiment was conducted in greenhouse conditions using a completely randomized design and three replications. Factors studied were soil cadmium levels (0, 8, 25 and 75 mg/kg soil) and types of adsorbent including pure chitosan, biochar, zeolite and nanomagnetite and composites of chitosan- biochar, chitosan- zeolite and chitosan- magnetite and control (without adsorbents). Each adsorbent was applied to soil at the rate of 0.5% W/W. Uncontaminated soil samples were spiked with different amounts of cadmium sulfate and incubated for two months to achieve relative equilibrium. After two months the samples were treated with different adsorbents and incubated for another two months. Then the amounts of DTPA extractable cadmium and its different chemical forms were determined.

The results showed that the application of adsorbents to soil decreased the concentrations of DTPA extractable cadmium. The results also showed that chitosan composites had higher ability for immobilization of cadmium in the soil than the pure chitosan, biochar, zeolite and nanomagnetite and the highest cadmium immobilization ability was observed for the composite of chitosan- magnetite. Reductions in DTPA- extractable cadmium for pure chitosan, biochar, nanomagnetite, and zeolite were 26.11, 19.38, 18.00 and 7.71% and for composites of chitosan- magnetite, chitosan- biochar and chitosan- zeolite were 34.02, 32.04 and 30.56% respectively when compared to the control treatment. Sequential extraction at the contamination level of 75 mg Cd/kg soil also showed that the use of adsorbents significantly reduced the soluble + exchangeable and carbonate forms of cadmium compared to the control treatment and increased its more stable forms including iron and manganese oxide, organic matter and residue fractions.

According to the results, it can be concluded that coating the pure adsorbents with chitosan by creating more adsorption sites reduces the cadmium mobility in the soils and increased the efficiency of pure adsorbents in the immobilization of cadmium. It was also observed that among the composites that used in this experiment, the highest ability to reduce the cadmium concentration was related to the chitosan-magnetite composite.

Urban water distribution networks consider as one of the essential infrastructural facilities and equipment in urban areas. The pipes are one of the primary and essential components of a water distribution network break during operation due to various factors. So, developing models for pipes failure rate prediction can be one of the most crucial tools for managers and stakeholders to the optimal operation of the water distribution network. In the last decade, various studies have performed to predict the failure rate of water distribution pipes using statistical and soft models - each of which has strengths and weaknesses. This study aims to present a new approach based on the development of a hybrid prediction model, considering the capabilities of soft and statistical models, to more accurately predict the water distribution network pipes failure rate compared to statistical and soft models used in previous research.

In order to achieve the study goals, 4-year (2015-2018) time duration statistics of Gorgan water distribution network characteristics including diameter, length, age, depth of installation, and the number of pipe failures used to predict future pipes failure rates. To modeling the pipe failure rate of the investigated network, five different models, including three statistical models (linear regression, generalized linear regression, support vector regression) and two soft models (feed-forward neural network, and radial basis function neural network) has studied. Optimal parameters of the models were selected based on appropriate statistical error indicators, including correlation coefficient (R), Mean Square Error (MSE), and Correlation Mean square error Ratio (CMR) for the training and testing data. In order to select the best model from different models to predict the failure rate of network pipes, the values of R and MSE indicators of the above models were calculated in the validation stage and compared with each other. Finally, to predict pipes failure rate more accurately, a new approach is developed based on the hybrid prediction model in which the predicted values of pipe failure rates by statistical and soft computing models considered as independent variables of the best model inputs and the observed values of failure rates as dependent variables of the best model outputs.

Comparing the values of R and MSE indicators of each statistical and soft computing model used in this study in the validation phase show that these models cannot predict the pipes' failure rate with reasonable accuracy. Feed forward neural network model with the highest R = 0.69 and the lowest MSE = 0.062 values has the best estimates. Using the new approach developed based on hybrid soft and statistical models, the R index is equal to 0.96, and the MSE index is equal to 0.046.

A significant increase in the R index (39%) and decrease in the MSE index (25%) through using the proposed hybrid approach compared to the feed-forward neural network model demonstrates that using the new approach provides perfect accuracy prediction of the pipes failure rate of the water distribution network.

Conservation of soil and water resources could be an important role in the health of crop. The use of wastewaters and the presence of heavy metals in these waters as well as the pollution of soil resources due to the entry of heavy metals can cause many problems for quantity and quality of crop. The high retention of heavy metals in the environment causes transfer to plants and food chains and cause irreparable damage to humans, plant growth, soil and the environment. This study was conducted to investigate the contamination caused by the application of different amounts of heavy metal Cadmium (Cd) in irrigation water and also in soil on its growth and accumulation in organs of corn variety (cultivar) 201 in Shahrekord University farm.

To this aim, the factorial test was done based on the completely randomized design with three replicates as a pot culture with Silt Loam texture. The first factor was the addition Cd in soil from the Cd Nitrate Salt at three levels (0 (control), 10 mg/kg soil, and 50 mg/kg soil) and the second was the Cd concentration in irrigation water from Cd Nitrate Salt at five levels (0 (control), 0.01, 0.05, 1, 2 mg/L).After using Cd treatments in the soil, corn was cultivated and irrigated with water with different levels of Cd during the growing period. At the end of the growing period, the concentration of Cd in different components of the plant (stem, leaves and seed), soil as well as the relative components of corn were determined. Also, the amount of evaporation and transpiration and water requirement were recorded during the experiment.

The results showed that water and soil contamination with Cd had a significant effect (at a1% level) on yield components including grain yield per plant unit, number of rows in corn, number grain at the row, dry leaf weight and dry stem weight. However, the effect of water and soil contamination with Cd was not significant on yield components. High levels of Cd in soil and water had the highest reduction in yield. The results showed that the stem had the highest (2.283mgkg-1) and the grain (undetectable) had the lowest Cd concentration. In this study, the highest and lowest yields of corn plant components due to the using of different levels of Cd in soil, in grain yield and the number of rows in corn obtained11.46%, 15.51% and 2.47%, 3.81%, respectively. Water and soil contamination with Cd had a significant effect (p < 0.05) level on water use efficiency in corn. Water use efficiency due to the using of high levels of Cd in water and soil decreased by 15.45% and 17.21%, respectively.

The results showed that the combined use of contaminated water and contaminated soil with Cd leads to a quantitative and qualitative reduction of corn yield. Therefore, efforts should be made to prevent the contamination of water and soil, to minimize the use of contaminated water in contaminated soil in order to protect soil resources as well as water. According to the results, the amount of Cd concentration in leaves and stem was higher than the allowable limit. Contamination of water with Cd also led to a further reduction in corn yield in contaminated soil.

Today, the instability of the debris slopes is a huge problem that human has been facing due to maladministration and overexploitation of existing resources. One of these methods is to apply the Vegetation because of features such as bioengineering capabilities, economical issues, bio-technical issues and high durability, self-regeneration, self-renewal and no negative impacts on the environment at slope stability.The purpose of this study is to investigate the role of plant species in the stability of debris slopes of Tuskestan-Chaharbagh road as a bioengineering approach.

To do so, firstly, the study area was investigated and 35 locations (14 locations were stable and 21 locations were debris) were selected for sampling from plants and soil. The sampling of roots was done at the depth of 0-30 cm of the dominant species at each slope and the sampling of soil was conducted at the depth of 0-20 cm. The density and canopy percentage of the vegetation at the grasslands and forests were measured respectively with square plots (1 m2) and circular plots (100 m2). Some of the soil characteristics such as: shear strength, cohesion, internal friction angle, humidity, aggregate stability, slope, gradation curves (the percentage of fine-grained and course-grained particles) and the root tensile strength of the dominant species were measured at some of the slopes. The study was tested by the Independent T- test at the SAS software.

The results of the experimentations showed that the average mean of the above parameters on the stable and debris slopes were: 0.1739_15.82 kg/cm2 for shear strength, 0.0996_0.0999 kpascal for cohesion, 11.071_0.928 % for humidity, 0.4343_0.4588% for aggregate stability, 35.5_43 % for slope and 183.34_108.93 megapascal for root tensile strength. Vegetation also had meaningful impacts on the above parameters at the 5% level and it should be added that the density and canopy percentage of vegetation, were more at stable slopes in comparison wit the debris slopes. The dominant rangeland species (Melica persica) and (Astragalus sp) at the stable slopes and specie (Tussilago farfara) at the debris slopes. On the other hand, dominant tree specie (Carpinus betulus) at the stable slopes and shrub species (Rubus sp) at the debris slopes. The species (Melica persica) and (Astragalus sp), with the highest density average of grassland herbaceous and bush plants with the highest average of canopy percentage and also the tree species (Carpinus betulus) with the highest average of canopy percentage, has had the most impact on the slopes stability and soil conservation and on the conterary. On the other hand, the specie of (Crataegus monogyna) with the highest density average of shrubs plants and the highest average of canopy percentage, has had the most impact on the slopes instability.

It could be also concluded that a vegetation with a high density and canopy percentage leads to the increase of shear strength, internal friction angle, course-grain percentage, soil humidity and root tensile strength and causes a decline at cohesion, fine-grain percentage, aggregate stability and slope at the stable slopes in comparison with the debris slope and therefore results in the fixation of the slope. Therefore, vegetation is considered as bioengineering method for the fixation of the debris slopes.

Soil conservation dams are constructed across waterways or gullies to reduce the intensity of water flow, sediment retention and monitoring, reduce the peak discharge of floods, increase concentration and lag time in a basin area, and finally correct channels width and length of channel. Gabion dams are porous structures, they are mostly used in many watersheds covering water reservoirs in Iran where soil erosion by water is occurred steadily in uplands. Various factors such as the location of the dam along waterway, waterway slope, the drainage area of each dam and watershed soil’s particles size affect the performance of these dams. Up to now, the effectiveness of the gabion dams has not been investigated in sediment deposition in semi-arid watersheds. The study was carried out to determine the performance of gabion dams and the role of different factors in trapping sediment and its grain size distribution in a semi-arid watershed in west of Iran.

In this study, eleven gabion dams named G1 (in the lowest part of the waterway) to G11 (in the highest part of the waterway) in the resin watershed located in the north of Kermanshah were studied during the year 2018. Sediment sampling was performed from three locations behind each dam from a depth of 0 to 20 cm. Then the physical properties of sediments and watershed soil including the percentage of sand, silt and clay particles were determined. The granulation of sand particles was measured by separating the particles through appropriate sieves and washing the particles on each sieve and the particle size distribution of gravel and boulder was measured by separating the particles by weight method. The volume of sediment was calculated by measuring height and area of deposition area behind the dams. The drainage surface area for each dam was obtained by ground survey and google earth images. Slope gradient of drainage area of each dam was obtained through the slope of the waterway.

The results indicated that the performance of the gabion dams in trapping of sediment is different in different sections of the waterway. The dams constructed upstream of waterway received more sand but less clay and silt than the downstream dams. Also, the amount of sand in the sediments of the dams was higher than the watershed soil. The particle size distribution of sand showed that the most sedimented particles in the back of the dams were related to particles with a size of 1 to 2 mm and the frequency of particles with a diameter of 0.053 to 0.075 mm was the lowest. Particles with a diameter from 2-4.75 mm had the highest share of coarse particles (pebbles) in sediment, while the share of larger particles with a diameter of 9.37 to 12.5 was the lowest. Also, among the various factors, waterway slope had a significant effect on amount of sediment behind the dams.

The distribution of sediment grain size behind the gabion dams varies due to the location of the dams along the waterway. The gabion dams, which are constructed upstream play an important role in trapping coarse-grained sediments. Sediment volume behind the dams is positively affected by drainage surface area and particularly slope gradient of waterway. Therefore, slope gradient of waterway and location of the dams along waterway could be taken into consideration for enhancing their effectiveness in amount of sediment trapping and type of sediment material. Construction of these dams with lower porosity such as masonry check dams in lower parts of waterways is necessary to trapping fine sediment particles as well as preventing the pollution of surface runoff.

Erosion, sediment yield (SY) as well as rainfall erosivity and vegetation cover show seasonality during a year. Basically, most SY occurs during high erosivity and poor soil cover periods. Therefore, in selecting crop and vegetation management programs at the basin level, it is necessary to underestand the temporal changes of erosivity and SY.

Two watersheds, Kasilian in Northern Alborz and Latyan in Southern Alborz were selected and their landuse maps were extracted. Then, spatiotemporal variations of NDVI for three hydrological years including dry, normal and wet years, were derived bimonthly form MODIS data. For estimating suspended sediment, we used a combination sediment rating curve and average daily discharge records. Erosivity factor, EI30, was calculated in the nearest gauging sites for both basins based on 1-minute interval rain records. Simultaneous to the NDVI, suspended SY and rainfall erosivity were computed. Then, based on the correlation of SY with erosivity and vegetation, the relationship was analyzed and finally, the appropriate time of exploitation for forests, rangelands and suitable crops with best ground cover during the erosion risk peaks was proposed.

In Kasilian, four main landuses were forest (97%), orchards, croplands and rangeland, and in Latyan, two landuses of rangeland (94%) and orchards were dominat. The average NDVI of Kasilian and Latyan was 0.67 was 0.13 respectively. However, the NDVI of similar landuses was measured to be about half and less in Latyan than Kasilian. For all landuses, NDVI reaches its lowest value in the colder months. Erosivity did not indicate a clear seasonal cycle, possibly due to occurring erosive storms even during the dry periods. The peaks of the SY did not occur at the same period of time in the studied years in Kasilian basin; while, for Latyan basin, the peaks were concurrent with snow melting and percipitation in the beginning of spring in all three years. In studied dry, normal and wet years, high negative correlations (-0.54, -0.45 and -0.85 respectively) were found between the NDVIs and SYs in Kasilian basin. In contrast, no significant correlation was observed between the two aforementioned factors in the studied years of Latyan basin. There was also no correlation between erosivities and basin SYs. Finally, according to the SY cycle, June and July were proposed as the best time for grazing of rangelands and exploiting the forests in Kasilian basin, and early June to September were proposed in the Latyan basin to minimize the risk of erosion. Due to the high sediment production in the Latyan basin, the number of livestock entering the area and the capacity of the grazing should be more closely monitored. From the point of view of erosion risk, summer Soybeans, Canola and Wheat and Barley, were introduced as suitable and spring Soybeans as unsuitable crops for Kasilian based on to their growth stages.

For soil conservation and management and sediment yield prevention, it is essential agricultural products and the time of exploitation of rangelands and forests be planned and managed based on the erosivity and sediment yield cycles in a way to limit soil erosion.

Due to the population increase and growing need for food production development in cities and to improve urban agriculture through urban greenhouses, there is an urgent requirement to provide optimal subsurface irrigation methods. Optimal irrigation methods mean methods that reduce water consumption and allow the use of lower quality water for irrigation while maintaining product quality. There are different methods for subsurface irrigation in greenhouses, for example there are some hydroponic methods which need special equipment and many studies have been conducted on them. In this research, performance of a new sub-irrigated planter method (SIP) for panting basil plant in two seasons in a greenhouse, in term of water productivity was evaluated and compared with conventional surface irrigation.

In SIP system, plant was planted in pot and a water reservoir (saturated gravel reservoir) was prepaid below the growing medium in pot (bottom of pot) to provide the water for plants through capillary action in growing medium (upper part of pot). Variable parameters to study were: depth of growing medium (D1: 50 cm and D2: 30 cm), Type of growing medium: (clay loam + cocopeat + perlit (SC) and cocopeat + perlit (C)) and three irrigation salinity levels (1.2, 3.5 and 5 dS.m-1: basil tolerance to irrigation water salinity: 1.5 dS.m-1); which were compared in both SIP and surface systems.

All SIP-C treatments had considerably higher water productivity in 5% statistical level compared to surface treatments which proved the superiority of C growing medium to be used in SIP systems in order to increase water productivity in a greenhouse. Considering optimum depth, water productivity in SIP-SC-D1 was not meaningfully higher than SIP-SC-D2; although in SIP-C, all D2 treatments had considerably higher water productivities than D1s. As a result it is recommended to use lower depth of growing medium while using C growing medium in SIP systems. Increasing irrigation water salinity level did not affect the fresh yield weight in SIP systems; although the salinity level was remarkably high in surface layers of SIP pots unlike the higher salinity layers observed at bottom of surface pots; which shows the need to monitor the growing medium salinity levels during growing season and applying the leaching between growing seasons when necessary in SIP systems.

This study showed that sub-irrigated planter method while is a very simple method and has no need to complex technology and expensive equipment and installation, significantly reduces the amount of water required for irrigation and also is able to compete with conventional surface irrigation systems. Therefore this method can be used as conservative system to save both water and soil as an agricultural goal and keep the productivity in high levels.

One of the main important strategies can be achieved to preserve the water resources is the optimal use of water in the agricultural sector. Water infiltration as a key component of water resource plays a significant role in this challenging problem. Water permeability in soil strongly depends on environmental factors, climatic conditions, latitude and soil characteristics, and has high spatial variability. The various simulation models are used to predict the amount of water infiltration in the soil. there have been a lot of research on the estimation of water infiltration models in the soil, which has been studied in the public only to study the models of infiltration and influence only one of the effective factors on infiltration. The proper prediction of the infiltration and the uncertainty assessment of these models through GLUE (Generalized Likelihood Uncertainty Estimation) algorithm, considering the region conditions and the combined effect of several factors affecting the infiltration process, is main aim of this study.

Their measurement is conducted in one of the farms of the county in Roshtkhar. The required measurements through double cylindrical method were carried out in three iterations and in two different soil textures, sandy loam and clay loam. In this research, the uncertainty assessment was performed by four models of Kostiakov, SCS, Philip and Horton infiltration. Uncertainty prediction of these four models through GLUE (Generalized Likelihood Uncertainty Estimation) algorithm was used in the MATLAB programming environment, with 100,000 iterations. GLUE mapped all sources of uncertainty into parameter uncertainty. Moreover GLUE conceptual simplicity and it flexibility has led to this method being considered as one of the most applied methods in the uncertainty evaluation in other sciences in last decade studies. Here one percent of best simulations were selected to define the 95percent prediction uncertainty. Hence posterior distribution of each model parameters is plotted and assessed.

In order to quantify the results of uncertainty, four indicators "the percentage of data placement measured in the desired confidence ranges, the bandwidth of the simulated data in the desired confidence range, the degree of asymmetry of the simulated data in the desired confidence range", which is briefly depicted in letters" P, d, s, and T ", respectively. The results showed that the parameters of the Kostiakov model in both soil texture with a value of P greater, d less, s between zero and 0.5 And T between zero and one show more certainty, so that the values of these indicators in sandy loam soils equal to 100, 0.378, 0.055 and 0.388 respectively, and in clay loam soils In 100, 0.519, 0.147 and 0.558 respectively.

According to the four P, d, s, and T indices, it was found that the paramteres of Kostiakov model has more certainty than other model parameters, which can be considered as an appropriate model.