پژوهشنامه مدیریت حوزه آبخیز
پیاپی 24 (پاییز و زمستان 1400)

Implementing management practices and involving stakeholders is associated with challenges due to changing perceptions and expectations of stakeholders. Active participation in decision making of watershed management measures is determining the community characteristics, involved people and diverse groups of stakeholders. In this regards, the present research was planned to determine the different groups approach in participatory decision-making for watershed management measures in the Unar Chay Watershed of Meshgin Shahr, Ardabil Province via Policy Profile Ratio (PPR) and Index of Resolution (IR).

To achieve the considered goal, the target experts/managers have been chosen based on different background including natural resources, environment, regional water company, nomadic affairs, Jahad griculture, NGOs members, watershed residents, students, university professors and citizen groups. Through designing a questionnaire, the approach of different groups was examined based on analyzing the effect of watershed management projects on improving the income of watershed residents and evaluating the watershed community participation in the projects implementation and conflict reducing and increasing of local community’s cooperation. Then, the PPR and IR were calculated and analyzed for all stakeholder groups.

The results showed that the value of PPR is between zero and -11. So that, among the study groups, the least PPR value was related to the subject of improving the watershed community income for the NGOs group which they were as opponents of the decision. Some of the study groups have a moderate approach towards the considered subjects. Additionally, the IR value was ranged between -50 and 12. The lowest value of IR was obtained for students group (opponents of the decision) towards the Women's empowerment and support via local cooperatives and organizations.

The social profile ratio, while determining and prioritizing the views of different decision-maker and stakeholder groups, can be useful in effectively managing actions based on the strengths and weaknesses of the watershed participation process. In this regard, strengthening the participation of stakeholders and effective groups as well as removing barriers in low-impact groups can be considered in the planning process.

Strategic management process including setting objectives, Identifying strengths and weaknesses (internal factors), identifying opportunities and threats (external factors), setting long-term goals and determining various strategies, calculating and evaluating performance. The aim of current study is to evaluate the efficiency of SWOT model in preparing strategic plan for integrated watershed management in Meymeh watershed, Ilam.

The current research has been done in three subwatersheds of Meymeh watershed. This watershed has been selected as pilot watershed study of Ilam province in line with the National Megaproject on Integrated Watershed Management which has 20584 ha area and located in Dehloran county, Ilam province. Data collection was done in different kinds of library and field information and after discussion to scientists and experts, weakness, strength, opportunities and threat of the catchment are identified. In this research, 22 strength and opportunities as advantages and 25 weakness and threats as limitations in the studied watershed are specified. All of this characteristics are used for data analysis and preparing strategies using SWOT model. For this analysis, 30 questionnaire are filled by academic, non-academic and local experts, then for weighting and scoring of factors, AHP method is applied for factor classification. Finally, Using SWOT strategic plan for integrated watershed management is suggested and for strategies priorities, QSPM planning matrix has been used.

Results show that between different strengths, "permanent rivers" with 0.364 score as the most important strength and "no applied agriculture and natural resources planting pattern" with 0.312 score as the most important weakness of the catchment have been identified. Also, between opportunities, "involve the local communities in natural resource projects" with 0.351 score as the most important opportunity and "The negative consequences of climate change due to the definite impact of the province's natural resources" with 0.507 score as the most important threat of the studied catchment have been recognized.

Investigations of IFE, EFE and weights of strategies indicated that in future planning, opportunities in the catchment should be taken in account.

Nowadays, it is necessary to use the facilities available in the communities to prevent all kinds of possible crises or to reduce the amount of damage. To deal with these crises, it is necessary to establish crisis management centers with the aim of carrying out preventive measures, crisis preparedness and response, providing relief to crisis areas, and temporary accommodation of victims. This study was conducted with the aim of locating the optimal areas for the construction of crisis management sites in the city of Babol.

In this study, effective criteria include of slope, slope direction, altitude, distance from commercial, medical, administrative, disciplinary, religious, educational use, distance from road and river in the location have been selected and weighted by experts with AHP method. After synchronizing all information layers, hierarchical analysis algorithms and fuzzy algorithms were applied to them in order to find the optimal location.

The results showed that, in AHP zoning, an area of ​​168 hectares, equivalent to 5.56 percent, has the best conditions for creating a crisis management site in the city of Babol. In fuzzy method, four operators in cloud of GAMA, Product, AND, OR were used. The AND operator had a better result than the other operators. In the operator, 103 hectares' area of the city equals 3.4 percent, is prone to creating a crisis management site.

The output of the models designed by the hierarchical method and fuzzy logic were different. The reason for this difference was considering the criteria with the same weight in the fuzzy model and considering the layers with different weights in the AHP model. The output results of the AHP model, which was a combination of standardized information layers using the opinions of experts, were more accurate due to the involvement of expert opinions.

Lack of proper management of land use in a watershed, has negative impacts on the available resources. Land use optimization is one of the suitable solutions for achieving a sustainable development and reducing wasted resources. The present study was carried out in the Kasilian watershed located in the Savadkoh County to determine the most appropriate composition of land use to reduce flood occurrence and maximize benefit.

At first, all available studies including physiographic, soil science, vegetation, hydrology, socio-economic studies from Mazandaran Regional Water Company and Natural Resources and Watershed Management office were collected and completed during field visits. The costs and benefit for each land uses was obtained using a questionnaire. The amount of flood in different land uses was also obtained using HEC-HMS software and the use of information on three rainfall events in the years 1991-95 related to Sangdeh synoptic station and flood hydrograph of the same events in Valikbon hydrometric station located in the watershed outlet. The slope and soil depth  maps based on land use standard as input to objective functions and constraints land use optimization model was prepared. Multi-objective linear programming model using the simplex method in ADBASE software was written and solved.

The results showed that flood amount reduced from 0.89 m3 s-1 before optimization to 0.74 m3 s-1 after land use optimization in general and this indicates 24.49% reduction in flood amount. The benefit of different land uses in the studied watershed has also increased from 2505.102.285 million Rails per year, before land use optimization, to 14692.902 million Rails after land use optimization, and this indicates a decrease of 58.56% of benefit of the watershed after land use optimization according to the standard criteria.

The most sensitive factor is the reduction of rainfed land use and the increase of forest land uses in the Kasilian watershed, which have the greatest impact on reducing benefit and flood amount.

Nowadays, with development of urban, industrial and agricultural, apply of groundwater is more important. So sustainability and development the exploitation of groundwater for types of different customers and goals, it is necessary that quantitative and qualitative characteristics it be investigated and evaluated.

Fuzzy Adaptive Neural Network (FANN) and Geostatistical method on based Geographic Information System are used for Komijan plain, Markazi province, Iran. The first, data 36 wells was collected from Rural Water and Sewage Company. Then using semi variogram types such as: gussian, linear, spherical and also Kriging and Co-Kriging methods, geostatistical model was evaluated using indicators: R2 and RMSE. Then, for Fuzzy Adaptive Neural Network model Membership functions such as:  triangular, generalized bells and gaussian was investigated and the best model was determined using indicators: R2 and RMSE.

According to results R2 and RMSE in geostatistical, spherical, linear and exponential modle was selected  as best for EC,  TDS and pH variables, repectively. Also on based semi variogram, Kriging method has a better performance than the cokriging method for all studied variables with high determination coefficient 0.73, 0.66 and 0.85 respectively for EC, TDS and pH and lower in RMSE. The results showed in Fuzzy Adaptive Neural Network, EC variable, the fuzzy generalized bell function with a correlation coefficient of 0.98 and mean square error of 144.59 in the test stage, is good. For TDS variable, gaussian function with a correlation coefficient of 0.98 and mean square error of 0.33 119 at the test stage is best. also for pH variable, the generalized bell function with a correlation coefficient of 0.99 and mean square error of 103.10 at the test stage has a better performance than other fuzzy functions in the modeling. By comparing the results of Geostatistical and Fuzzy Adaptive Neural Network, it can be seen that the FANN model has a higher efficiency than Geostatistical model.

Regarding the results of zoning maps, it is shown that in the northern part of the plain, EC has low, while in the central and west, EC is above 2000 µSiemens/cm. Also for TDS variable, t is low in the northern part of the plain, while in the south and southwest, is above 1000 mg /lit. Alos changes in pH value showed that variation of this variable is low and the highest level of pH is in the northern part and the lowest in the southern part.

Surface soil moisture is an essential variable in the Earth's climate system and hydrological cycle that plays a crucial role in scientific and practical applications such as numerical weather forecasting, extreme event monitoring, hydrological modeling, climate models study, and water resources management. Microwave remote sensing has a unique capability to retrieve global soil moisture over a wide range; in this context, The European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite is the first specific mission to monitor global soil moisture, which has been operating since 2009. This study aimed to extract soil moisture data from SMOS satellite products (BEC _L3_SM_SMOS), generate soil moisture maps at different time scales for Iran, and evaluate the spatial and temporal variations of soil moisture data (from 2010 to 2019).

In line with the research objectives, we developed a model by Model Builder in ArcGIS that read and derived soil moisture values from the BEC _L3_SM_SMOS products and produced average soil moisture maps over Iran. This study evaluated the sources of Radio Frequency Interference (RFI) in the SMOS products by evaluating RFI probability maps. The results found that the SMOS ascending orbit products have the lowest RFI in Iran. This study evaluated the sources of Radio Frequency Interference (RFI) in the SMOS products by evaluating RFI probability maps. The results found that the SMOS ascending orbit products have the lowest RFI percentage in Iran. Therefore, we used the BEC _L3_SM_SMOS (ASC) products to generate the soil moisture maps in Iran.

In this study, the outcomes of the developed model are the preparation of monthly, seasonal, and annual maps of the average soil moisture for Iran. Evaluation of temporal variations of the soil moisture monthly average maps shows that the highest maximum monthly value (0.854 m3m-3) occurred in May. The highest monthly average of soil moisture values was related to February (0.087 m3m-3), March (0.086 m3m-3), and April (0.086 m3m-3), and the lowest monthly average of soil moisture values were occurred in August (0.034 m3m-3) and September (0.037 m3m-3). Evaluation of the annual average map (10 years) obtained from SMOS data shows that soil moisture varies between the lowest value of 0.002 and the highest value of 0.78 m3m-3 in Iran. The annual average value of soil moisture is 0.063 m3m-3 based on SMOS data over Iran

Due to the scarce soil moisture data over Iran and the ability of SMOS to produce soil moisture data with desirable quality, SMOS products can be used for various applications. The monthly, seasonal, and annual maps of the average soil moisture obtained in this study can be used in regional studies of hydrological models, improving weather forecasting models, water resources management, climate change studies, irrigation schedule, and smart irrigation.

 Over the past 20 years, flood disasters have consisted of 47% of the world's weather-related disasters, which has affected over 2.19 lives in Asia. Likewise, Iran has not been an exception and has always experienced severe damages due to floods. Hence, flood vulnerability assessment (FVA) is vital to mitigate incoming damages. However, the assessments require thorough theoretical knowledge and excellent software skills, limiting widespread usage of such evaluations and increasing financial and temporal requirements. This research aims to create an ArcGIS tool for non-expert ArcMap users to enable them to assess the flood vulnerability without any in-depth knowledge of the software. 

 Firstly, different papers regarding urban FVA were reviewed, and accordingly, the most frequent assessment indicators were identified. Hence, to assign weights to the indicators, the questionnaire method has been employed to ask experts' opinions. Then, indicators were scored, employing the AHP method, using Expert Choice software. Afterward, to create the tool, ModelBuilder was used to design and arrange process flow, and Python language was used to create required ArcMap processing tools that are not built-in in the software. 

 The created tool consists of 56 processes, 15 ArcMap built-in processing tools, and three Python scripted processing tools, namely a logical tool. To run the tool, users must determine six input files, a saving directory, and the name of the case study. The tool saves the outputs in a GDP named after the case study within the user-defined directory. Moreover, to increase the tool's usability for different case studies, the weights of the default indicators' weights can easily be changed in the dialog box. Moreover, the dialog box's language is Persian to provide a user-friendly interface. The tool generates an FVA map and six vulnerability indicator maps to enable users to analyze vulnerability status according to each indicator. The tool is available in TLX format and can be easily added to ArcToolbox. Furthermore, to test the tool's performance, Chaloos city was assessed using it. According to the results, 14 percent of the city, most of which are located proximate to the Chaloos river, is marked as highly vulnerable; 56 percent of the city is marked as vulnerable, and 30 percent of the city is marked as least vulnerable.

 According to the performance test, the processes were completed in nearly nine minutes, and all the outcomes were generated and saved correctly.

Natural ecosystems have their own order and balance unless they are disordered under the influence of a foreign force, which unfortunately, human have caused disordering in many watersheds by unconsumed exploitation of some of its elements. One of the most main of its results is run off production that resulted to increasing flood production and erosion and soil poverty. Gachsaran Formation is one of the most important erodible formations in Iran. This formation has about 1600 meters of thickness and in terms of petrology includes salt, anhydrite, colorful lime marls and some shale. Therefore, scientific research on runoff and erosion of Gachsaran Formation is essential, which is one of the main objectives of this study.

In this research for determination of the most important factors in runoff production of various land uses in Gachsaran formation studied a part of the gypsum mountain watershed in Izeh Township. It has 1202 hectares area. This investigation in order to determination of the relationship between produced runoff by rain simulator with some soil physicochemical characteristics like percent of very tiny sand, sand, clay, silt, pH, Ec, soil moisture, Calcium Carbonate and organic materials in different land uses of Gachsaran formation done. Then run off samples in 6 points and with three replicates in Gachsaran formation in the precipitation intensities of 0/75, 1 and 1/25 millimeter in minute in range, residential and agricultural land uses using rain simulator done. In order to investigate efficacious factors in runoff production, sampling was done in 0-20 centimeters of soil layers and also the same number of runoff. In order to do statistical analysis used EXCEL and SPSS software.

The most important soil factors in runoff production were identified by multi regression. The results showed that runoff production in different land uses at different intensities had significant differences. In this study, it was shown that the recognition of the soil parameters is very important in increasing and decreasing runoff in Gachsaran formation.

  Regression models showed that clay and calcium carbonate had the highest role in increasing and decreasing runoff of different land uses among the measured factors in Gachsaran Formation.

Today, the flood phenomenon is one of the most complex and dangerous events that, more than other natural disasters, leads to human and financial losses and destruction of agricultural lands in different parts of the world every year.

Due to the flooding of Zolachai Watershed, Salmas County, it seems necessary to study and simulate the risk of floods in this area. Therefore, in this study, a combination of artificial perceptron neural network (MLP) and GIS has been used. First, the effective parameters in simulating flood areas such as: slope layer, height, flow direction, soil and land use were examined and these information layers were entered into GIS software. The information layers were processed with the Fishnet command. And each layer became a point.This data, along with the educational data received from Google Earth, was introduced to the perceptron neural network.

In the perceptron neural network, the input layers including 5 neurons and 16 nodes entered the model and the results showed that the height has the lowest weight (R2=0.713) and the highest weight related to the flow direction (R2=0.913) in simulating the Zolachai Watershedflood., Is the city of Salmas.

It can be said that the combination of GIS and artificial neural network can be very useful for modeling and simulating floods in different spatial environments to prevent and reduce environmental hazards.

Given the limited available water resources, the conflict-laden issues of water allocation have become a challenging issue for planners and water consumers. The existence of different types of uncertainties and climate change conditions in the water resources systems intensify the complexity of the optimal allocation process of water resources in the agricultural field. Therefore, In the present study, it is tried to optimally allocate water resources in Marand watershed by developing a mathematical planning model that is capable of dynamics and uncertainty conditions both in the parameters of objective functions and in constraints.

In this study, an uncertainty-based interactive multi-stage stochastic programming (UIMSP) approach is proposed by incorporating the fractile criterion method and chance-constrained programming within a multi-stage decision-making framework for agricultural water resource management in various planning horizon. A two-period scenario tree with different probabilities for violating constraints (α) and various satisfactory levels of the objective function (β) were selected.

The results indicates that the minimum and maximum benefits of the system are [46.6, 983.6] × 1010 (Rials) and [699.7, 1483.1] × 1010 (Rials) when α=0.01  and , β=0.9 , respectively. In addition, an increase in satisfactory levels of the objective function (β) led to a gradual decrease in both upper and lower bound of the total net benefits at each given probability level of violating constraint (α), while any change in probability of constraint violation (α) resulted in creating a significant change in the system profits. Also, the results of the UIMSP model show that water scarcity is observed in different scenarios due to insufficient water resources in Marand watershed. However, according to the results, in the second period, despite the decrease in the amount of water available, the amount of water shortage has decreased with increasing irrigation efficiency. For example, under medium flow level, the amount of surface and groundwater shortages in the first period is 43.6% and 32.5%, respectively, while it is reduced by [36.9, 24.5] and [24.5, 0] percent in the second period.

The results can help decision-makers examine potential interactions between risks related to the stochastic objective function and constraints. Also, increasing irrigation efficiency and upgrading irrigation systems are among the main strategies that can provide an economic benefit to farmers while reducing environmental damage.

Due to the lack of discharge stations and rainfall in the Vazroud basin, it is not possible to have a relatively accurate hydrological behavior of the region. Therefore, by addressing the geomorphic features, this problem can be overcome to reduce the damage caused by floods in the future. In this study, in order to determine the flood risk of flood-prone areas, two geomorphic factors including topographic wetness index and stream power index were used.

Due to the lack of sufficient data related to the discharge of Vazroud watershed, the characteristics of historical flood risk were determined in this area. In the first step, the SCS method was used to simulate the peak discharge. After determining the quantitative characteristics of flood risk (peak discharge) in the next step, the qualitative risk of flood was predicted. In order to determine the qualitative risk of floods, a combination of two factors, the strength of the river and the level of floodplains, was used as the damage that could be caused. The amount of flood-prone regions with different return periods was determined by topographic moisture index threshold method.

The results of this method showed that with increasing the flood return period, the amount of flood-prone lands increases and the amount of topographic moisture index should decrease with increasing the flood return period. The results of flood risk maps with different return periods showed that as the flood return period becomes larger, the areas affected by flood risk in the hazard classes generally increase. The results of total lands that will be at risk of floods with return periods of 2, 10, 25, 50 and 100 years will reach 2.2, 3, 4.2 and 9.8% in the whole basin, respectively. Also, Vaz Tangeh, Nojmeh and Vaz olia villages with 20.6, 16.4 and 13.1% of flood-affected lands were determined as the most vulnerable rural areas in Vazrood watershed, respectively.

Flood risk prediction depends on the characteristics of the catchment and the hydrological and geomorphic factors of the region. So that in areas that have incomplete and low statistics as one of the non-structural flood management tools and complementary to structural methods, it plays an important role in flood control and reduction of potential damages.

Accurate estimation of river suspended sediment load (SSL) has an important role in water resources, watershed management and related sciences. Due to the high fluctuations of SSL in different seasons of the year as well as its severely nonlinear and complexity nature, it is necessary to use appropriate methods that can simulate and estimate such phenomena.

In this study, data log transformation and multi-objective particle swarm optimization (MOPSO) algorithm were used for optimal training of neural network models. For this purpose, at first, by using unsupervised neural network (SOM), data of flow discharge and suspended sediment load of the studied hydrometric station (Statistical Period 1995-2016) were clustered. Then, by sampling the clusters, the data set needed to train and test the neural network models were prepared. After it, three scenarios were defined to evaluate the impact of applying logarithmic transformations and MOPSO optimization algorithm In the first scenario, the initial data (without logarithmic transformation) and the common base gradient algorithm in training neural network models (error propagation), in the second scenario, the error propagation algorithm and the logarithmic transforms, and in the third scenario, the logarithmic transforms and the MOPSO algorithm, was used to train neural network models.

Evaluation and comparison of the model validation results showed that applying a logarithmic transforms and MOPSO algorithm, by reducing RMSE error and bias percentage (PBIAS) from 49 ton/day and -21%, in the best model of the first scenario, to 30.3 ton/day and -6.3%, in the best model of scenario III, increased the efficiency of the models. Other results of the study are non-estimation of negative values for suspended sediment, which is one of the common errors in using neural network models in estimating suspended sediment.

The use of multiple objective functions makes it possible to sensitize the models to more accurately estimate the suspended sediment at low or high flows, thus improving the validation and skewness indices of the base data models.

Soil erosion is one of the most important problems in natural resources management, especially on the e rangeland hillslopes. Further, soil erosion estimation using field measurement is expensive and time-consuming. Therefore, models can be efficient tool for performing an exact estimation in a short time and a low cost. The aim f this study is to present a methodology to estimate soil erosion on the rangeland hillslopes.

 In this study, the annual rates of soil erosion have been studied using erosion pins on the rangeland hillslope in the of Kasilian watershed in Mazandaran Province. Annual soil erosion rates were measured using 109 erosion pins (one year after the its establishment) due to changes in soil surface and soil specific gravity. An artificial neural network (ANN) was used in NeuroSolutions software. Soil erosion rates were as the model output and the affecting factors of soil erosion were the inputs. The model inputs rangeland cover percentage, land slope, slope length, slope shape (land curvature) and soil texture (sand, clay and silt percentage). The modeling process was performed using the MLP network. All of the data were separated into three classes included training (65% data), cross-validation (10%), and test stage (25% data). The model was performed and optimized. Further, geographic information system (GIS) was used for mapping soil erosion rates based on the simulated erosion values.

The results of the test stage proved the high performance of the ANN in estimating soil erosion (Rsqr = 0.9). Further, statistical analysis using SPSS software  and the optimum structure of the network and sensitivity analysis showed that the most important factors of soil erosion are vegetation cover, slope shape, land slope, slope length and soil characteristics, respectively. Finally, the optimized network inputs were combined in a GIS environment with a pixel size of ten meters, and annual soil erosion map was generated by coupling the capabilities of ANN and GIS on the studied rangelands.

The proposed methodology can be used as an efficient and alternative method for field measurements of soil erosion in the highlands with a high performance.

Stream sediment load usually acts as an important source and indicator in geochemical elements concentration changes especially heavy metals and the extent of human impact. Studying the trend of downstream changes in sediment pollution indices and the factors affecting it is one of the most important interdisciplinary research needs. In present research, the concentration of heavy metals and pollution indices of bed sediments were investigated in the main river of Khamsan representative watershed and the factors affecting the downstream changes of indices were analyzed. This river is one of the two important rivers entering the lake of Gawshan dam and for this reason; the study of water and sediment pollution of this river is of special importance.

To achieve the research purposes, along the main stream, 10 bed sediment samples were taken from upstream to downstream and the concentrations of heavy metals including beryllium, chromium, nickel, copper, zinc, arsenic, selenium, cadmium, mercury, thallium and lead were measured using ICP-MS. Then the indices of contamination factor (Cf), degree of contamination (Cd), modified degree of contamination (mCd), pollution load index (PLI) and geo accumulation index (Igeo) and the downstream changes of these indices were calculated and analyzed. In addition, the percentage change index was used to determine the downstream change of the heavy metals concentrations.

The results showed that reducing the steam slope and increasing the density of vegetation along the stream was effective in downstream reduction of the heavy metals concentrations and neutralizing the effect of residential area. Toxic elements such as selenium, cadmium, mercury and arsenic have been reduced by about 40% in the downstream direction and the effect of check dams in reducing the transfer of lead, zinc, cadmium, copper and selenium along with bed sediment was also confirmed. The results also showed that after the qanat water joined the main stream, the concentration of heavy metals in the bed sediments increased and the highest increase with 1/116, 3/114, 0/100 and 5/79% was observed in selenium, cadmium, mercury and beryllium, respectively.

Conclusion of the present study shows that although according to the studied indices, none of the bed sediment samples of the studied river from the upstream to the downstream is contaminated, but the trend of changes is especially worrying for heavy metals nickel, zinc and cadmium and can be an alarm for water and sediments entering the Gawshan dam reservoir.

Land use change is a major factor in changes in soil organic carbon and nitrogen storage and the global carbon cycle. The aim of this study was to investigate the changes in soil organic carbon and nitrogen storage after afforestation and rangeland cultivation along with flood spreading.

This investigation was carried out on the sandy lands of Gareh-Bygone Plain of Fasa located at southeastern of Fars province. A total of 45 soil composite samples were collected from Acacia, Eucalyptus, Atriplex and Planted Range from a depth of 0-30 cm in two conditions with and without flood spreading. The organic carbon and the total nitrogen content were measured in laboratory. Then, the amount of carbon and nitrogen storage was calculated and their economic value was determined by carbon tax method. The data were analyzed using SAS software as a factorial experiment in a completely randomized block design and the means were compared with Duncan's test at p<0.05.

The results showed that the effect of flood spreading on the percentage of organic carbon and the amount of organic carbon storage in the soil was significant at the p<0.01, not significant on the percentage of the total nitrogen, but its effect on the amount of nitrogen storage at the p<0.05 was significant. The effect of land use (vegetation type) on all these indices were significant at the p<0.01. The interaction effect of flood spreading and land use on the percentage of organic carbon and soil nitrogen storage at the p<0.01 was significant, but its effect on the amount of carbon storage and the percentage of total nitrogen was not significant. The amount of organic carbon storage in the soils of Acacia, Eucalyptus, Atriplex and Range, from 10.23, 22.49, 12.3 and 6.21 Mg/ha in conditions without flood spreading, respectively, increased to 23.14, 40.23, 24.12 and 13.96 Mg/ha in flood spreading conditions. The spread of floods on these land uses increased the economic value of carbon and nitrogen storage equal to 53.59, 48.00, 75.46 and 43.52 percent, respectively.

On average, flood spreading increased the economic value of total carbon and nitrogen storage in the soil equal to 54.31%.

Low efficient sloping rainfed lands are one of land uses being exposed to severe erosion in Iran which is definitely one of important sediment sources for rivers and reservoirs. These lands are most sensitive to erosion while being plowed and fallow. This period in most regions of Iran coincides with the rainy season. A large part of rainfed agricultural lands of Gachsaran city is much erodible while the income of many residents of this area is from agriculture. Therefore, the aim of this study is to investigate the impact of various rainfall intensities in different slopes on the amount of erosion and runoff in rainfed lands of Gachsaran city in Kohgiluyeh & Boyerahmad Province.

First, the soil surface was saturated in order to prepare the environment for the experiment. Then, rainfall intensities of 33, 64 and 110 mmh-1 on three slopes of 6, 12 and 25% were generated using a rainfall simulator. Therefore, nine treatments with four replications were analyzed. Runoff and sediment were collected using special containers and transferred to the laboratory. After data collection, statistical analyses of runoff and sediment were conducted by SPSS software and analysis of variance method along with Duncan test. The other analyses were also accomplished in terms of the effect of factors on the amount of runoff, sediment, quality elements of water, soil and sediment.

Comparison of mean of the studied parameters showed significant (p<0.05) effect of rainfall intensity and slope percentage on the amount of runoff and sediment; so that, the rainfall intensity of 110 mmh-1 caused runoff and sediment 4 and 1.7 times higher than the 33 mmh-1. Also, the slope 25% caused runoff and sediment 2.3 and 1.7 times higher than the 6% on the three measured slopes. Comparison of the results of rainfall intensity and slope impact on the studied components indicated that rainfall intensity has a more considerable impact than the slope percent, on the amount of runoff and sediment. Also, measuring the amount of nutrients in soil and sediment indicated the impact of soil erosion on nutrient transport and reducing fertility; so that, higher amount of carbon, phosphorus and potassium in the collected sediments than the soil.

According to the results, slope percent and rainfall intensity have a significant effect on runoff and sediment production independently and in interaction with each other, in the experimental plots. Based on the result analysis of sediment concentration, only high amounts of rainfall intensity affect sediment concentration and weight of sediment. Moreover, increase of slope caused amount, volume and runoff coefficient; but this increase of runoff in the slope of 25% was much higher than the slopes of 6 and 12%. So, as the slope increases, the runoff will also increase.

Estimation and forecasting of precipitation pattern in different parts of the world, especially in arid and semi-arid regions such as Iran is very important. In addition, various numerical methods such as artificial intelligence methods due to high accuracy and speed have the ability to simulate the phenomenon of precipitation and similar subjects. The use of these techniques plays an important role in saving time and costs in field and laboratory studies. Therefore, the application and popularity of various artificial intelligence techniques to estimate and simulate different issues such as rainfall is increasing day by day. The purpose of this study is to estimate the long-term rainfall in Rasht by a hybrid ANFIS and wavelet transform model.

In this study, long-term rainfall of Rasht city was simulated using an optimum artificial intelligence model for a 62 years period from 1956 to 2017. In other words, the wavelet transform was utilized to enhance the performance of the ANFIS model and hybrid WANFIS (Wavelet-ANFIS) model was defined. Firstly, the effective lags of time series data were detected through the autocorrelation function (ACF). Then, using the lags, eight models were developed for each ANFIS and WANFIS model. It should be noted that 42 years data was applied for training and 20 years data to test the artificial intelligence models. Next, the number of optimal membership functions of ANFIS model was selected equal to two.

results of ANFIS 1 to ANFIS 8 were evaluated. Additionally, different mother wavelets were examined to optimize the ANFIS model. This means that the demy was introduced as the best mother wavelet for increasing the performance of the ANFIS model. The comparison between ANFIS and WANFIS models signified that the wavelet transform enhanced the performance of the ANFIS model. Also, results of the hybrid WANFIS models were analyzed, indicating that WANFIS 8 was the superior model. The model estimated the rainfall with an acceptable accuracy. For instance, the R, MARE and RMSE for the superior model were computed 0.961, 0.855 and 24.510, respectively. Additionally, the values of VAF and NSC for this model were respectively estimated as 92.273 and 0.913.

Results showed that (t-1), (t-2), (t-3) and (t-12) were identified as the most influenced lags for estimation of long-term rainfall of Rasht city using the hybrid WANFIS model.

Climate change is one of the most important issues that have affected various parts of human life in recent decades. Undoubtedly, this phenomenon will change the water resources of each basin. Therefore, estimating and predicting the future of river discharge is of great importance due to its harmful effects on the environment, economy and society. This research is aimed at checking and predicting the discharge of the river Gelevard Dam under different climatic conditions.

To this end, the HadGEM2-EM model was used under three scenarios RCP 2.6, RCP 4.5 and RCP 8.5. Also, the IHACRES model was used to simulate surface flow for the intended periods.

The results of the annual changes in the meteorological parameters under the RCP 2.6 climate change scenario showed that the maximum increase in minimum and maximum temperatures would occur during the period 2061-2080. The greatest change in precipitation will occur during the period 2021-2040. Regarding the results of modeling using IHACRES, it was found that the correlation coefficient of the model in the calibration stage is 0.61 and in the verification stage it is 0.79. The results showed that the average river flow rate decreased by 4, 8.7, 13 and 5 percent, respectively, in the four study periods (2021-2040, 2041-2060, 2061-2080, 2081-2100).

Due to the declining trend of Neka River discharge in the coming decades, the projected targets for the Gelevard Dam for drinking water, agriculture, industry, etc. will face significant shortages.

 The accurate estimation of actual evapotranspiration (ETA), i.e. crop water requirements, is an important issue for irrigation water allocation at fields and improving water efficiency. In the present study, ETA for Sorghum crop was estimated using surface energy balance algorithm for land (SEBAL) and by employing Landsat8 satellite images; meteorological data and DEM map and then compared with the measured values of lysimeter.

 For carrying out the sensitivity analysis, the key parameters of SEBAL algorithm was altered at the range of ±10 , ±20 , ±30 , ±40  , ±50  and resultantly the variation of ETA corresponding to decrease and increase of these parameters was investigated. The changes of key parameters on the days of 206, 238 and 254, based on Julian days calendar, were evaluated at eight points with different vegetation densities. Albedo parameters have moderate to high sensitivity, so that the albedo parameter has medium and high sensitivity in the areas with ET> 10 and ET <10, respectively.

 The results of SEBAL showed the value of accuracy indices were acceptable at a significant level of 95%, while compared with those of lysimeter measurements. The results of the sensitivity analysis also showed the surface temperature and input shortwave radiation are more sensitive especially at the areas having low ETA values. The wind speed and

In general, in addition to high economic efficiency compared to other conventional methods, the SEBAL algorithm has a good efficiency in estimating ET. Also, performing sensitivity analysis and determining the key input parameters, while increasing the accuracy of measuring those parameters, can greatly improve the modeling results.

Teleconnection patterns are one of the effective hydro-climatological factors in predicting precipitation, temperature and discharge on a large scale. Oppositely, comprehensive and integrated management of water resources requires that rainfall variables and consequently runoff flow can be predicted. From a dynamic and synoptic approach, teleconnection patterns can affect the precipitation pattern of different regions. The purpose of this study is to inspect the relationship between these indicators and autumn rainfall in the Caspian Sea basin and forecast it using various statistical models.

Therefore, in this study, Caspian Sea sub-basins were selected and autumn rainfall in the 28-year period from 1987 to 2015 was calculated. Then the correlation of MEI, SOI, NCP, NAO, AO, CSST, P-SST and MSST indices with autumn rainfall in July, Aug, Sep, Oct, Nov, summer, Aug-Sep-Oct and Sep-Oct-Nov was calculated. And the most important ones that had the highest correlation were considered as inputs to different models. Finally, autumn rainfall forecasting was done using a statistical model and three artificial intelligence models with different structures.

The study showed that various teleconnection patterns were effective depending on the type of sub-basin and time step. Prediction results showed that the difference between observational and modeled data in the training period was small and increased somewhat in the test period and reached about -25.7 to 47.6 mm in the whole sub-basins. Thoughtfulness of the type of analytical model showed that both SVR and MLP models had higher accuracy than GRNN and MLR models, so that the Root Mean Square Error by SVR model in Aras, Atrak, Haraz-Sefidrood, Qarahsu-Gorgan, Serazod-Haraz, and Haraz-Qarahsu sub-basins. 6.18, 7.34, 35.44, 18.25, 19.58, 17.68 and 47.22 mm, respectively, and the coefficient of determination will be 0.94, 0.91, 0.92, 0.84, 0.88, 0.88 and 0.87, respectively.

Therefore, the results show a strong relationship between teleconnection indices with autumn rainfall in the study basin. These include NAO, SOI, AO and Caspian and Mediterranean Sea surface temperatures at different time delays. With these results, steps can be taken to more accurately predict and manage the water resources of the Caspian Sea basin.

Karkheh River, as the third largest river in Iran, flows a large volume of water to the Khuzestan plain every year. The construction of the Karkheh Reservoir Dam, along with several advantages, widely affects the river flow in its downstream. Ignoring the effects of these structures on the elimination or reduction of river flows, especially flood capacities, leads to investment in agriculture, industry and urban development along rivers, downstream of dams and in flood high-risk areas.

In the present study, the trend of changes in the annual and flooding regime of Karkheh River over time and in the relationship with the establishment of Karkheh Dam were investigated. For this purpose, four statistical tests (Pettitt, SNHT, Buishand and von Neumann) were used to examine the homogeneity of peak and average annual flow data at the downstream of hydrometric station and to determine the points of change and mutation. In order to determine the role of climatic parameters on river discharge, Pearson correlation test was used.

According to the opening of Karkheh Dam in 2001, the results of the study showed that the flood peak discharges in the hydrometric station downstream of the dam (Pay-e-Pol station) was equal to 1978 cubic meters per second, in the period of 32 years before the Karkheh dam opening, and with a significant reduction of 78%, is equivalent to 417 cubic meters per second in the 16 years period after the dam opening. Therefore, considering the removal of flood peaks immediately after the construction of Karkheh Dam, we can definitely observe the effect of the dam on controlling the flood peaks of Karkheh River. The results showed that the highest peak discharge correlation with SPEI parameter, at 95% significance level. Also, monitoring of satellite images show that before the opening of Karkheh Dam (2001), the floodplains were covered by water in flood conditions and after this year, despite the occurrence of floods and high peak discharge reports in Karkheh River, no water intake from Karkheh River has been observed in the floodplains.

The flood regime of the River downstream of Karkheh Dam has indicated a decreasing trend due to changes in climate drought index since 1997, which has had a steady trend since 2001 due to the opening of Karkheh Dam and shows the control of floods by the dam.

River systems are subject to serious changes over the time. These changes vary from region to region depending on the conditions of the river. Forecasting the process of river changes and presenting engineering plans depends on understanding the current behavior and morphology of the river and evaluating changes in the past. The purpose of this study was to investigate the effective factors (hydraulic, soil properties, vegetation, and river pattern) on instability and bank erosion of Kashafrood River in Khorasan-Razavi province of Iran.

In order to better evaluation of the effects of different factors, the river path was divided into 14 reaches and geometrical parameters needed to show the changes in river morphology were measured and calculated. The HEC-RAS hydraulic model through the HEC-Geo RAS annex was used to investigate the flow hydraulic properties of the Kashafrood River. Next, the analysis of the model output results was performed for flow discharges with different return periods for 14 cross-sections along the river. Soil samples were also taken from the riverbank, and transferred to the laboratory for granolometery and other studies. Other factors such as the type and density of vegetation, geometrical properties, erosion rate and the impact of human factors on river changes were also studied during the field visits.

The results of river morphological analysis showed that the meandering coefficient (MC) for most of the reaches studied in this study is less than 1.99. Therefore, based on the Wollmann-Leopold and Schumm methods some reaches are classified as straight and some others as light meandering reaches. Hydraulic properties of the flow such as flow velocity, Froude number, and hydraulic depth of flow, shear stress and flow power have been varied from one reach to another, but in the present study they had no considerable effect on bank erosion. The results also showed that soil salinity was more affective to bank erosion among the studied soil properties, and the other soil parameters had no significant effect on river bank erosion. Vegetation status of the river bed and banks has played an important role in the stability of the banks. The river pattern was also found affective to bank erosion, as the erosion rate at the concave parts of the river was higher.

Among the various factors studied in the field of hydraulic, morphological, soil and vegetation characteristics of the Kashafrood bed and banks in the present study, soil salinity, vegetation cover density and meandering status of the reaches have been effective in bank erosion.

This project was carried out, in order to food security, according developing agriculture and sustainable natural resources and optimum utilization of water resources with evaluation and quality effects of infiltrated runoff to aquifer.

 In this study use of determine local Pollution Sources, sampling of surface runoff and groundwater in the aquifer that feeds the violation of pollution sources, according to FAO and WHO standards methods for agricultural, domestics and provided layer maps with geographic information system software and quality indexes analysis duration three years. The current research was conducted, for evaluation of transferred run off on water quality aquifer. In this study, were taken seasonal samples from 16 tube wells for determine the concentrations of sodium (Na), potassium (K), calcium Ca), magnesium (Mg), chloride (Cl), sulfate (SO4), carbonate (CO3), bicarbonate (HCO3), Electrical conductivity (EC), acidity (pH), total dissolved solid (TDS), in order to determine the water qualitative indicators including, sodium absorption ratio (SAR), percent sodium (%Na), residual sodium carbonate (RSC), permeability index (PI), total hardness (TH), were indexes of water quality, The groundwater quality is categorized into various levels based on the FAO and WHO standards for the purpose of irrigation and domestic use respectively.

Contamination view of the BOD5 concentration was measured and all samples in various locations under artificial recharge project located were complete infected for drinking purposes. Amounts of acidity were 6.4 to 8.4, SAR less than 3, Sodium percent less than 40 percent and infiltration index equal 0.39 to 0.68. In terms of drinking water, chloride, sodium, sulfate, were normal and unrestricted, but water hardness was a little beyond the normal Limit. Of view contamination, was measured BOD5 concentrations in the regional. Concentration of heavy metals, arsenic, aluminum, chromium, cadmium, lead, manganese, iron, zinc and copper were measured and analyzed then were less than normal level and were complete suitable for various activities.

The implementation of artificial recharge project has a positive effect on the aquifer recharge of the region and the aquifer water of Sefiddasht- Faradenbeh plain is suitable for irrigating the agricultural lands of the region and does not have any restrictions.

 Todays, considering climate change and its impact on the state of sea waves and the dangers caused by its severity, assessing and estimating the height of the significant wave in the seas is of great importance. Predicting the height of the significant wave in Amirabad port by using a combination of variables representing the characteristics of waves and meteorology, developing artificial intelligence models and de-noising the data using wavelet theory, and finally extracting the mathematical relationships governing the principles of marine-meteorological engineering to estimate altitude Wave is one of the unique goals and innovations in this study.

In this study, wave height in the Caspian Sea port of Amirabad, using single and hybrid-wavelet artificial intelligence methods, including Artificial Neural Network (ANN, WANN), multilayer perceptron with the Levenberg-Margaret training algorithm, Adaptive Fuzzy-neural Inference System (ANFIS, WANFIS), and Gene Expression Programming (GEP, WGEP) in different short time lags including no time lag, 3 and 6 hour time lags is estimated. For this purpose, hourly waves and meteorological data were used in 2018.

The results indicate that noise removed by wavelet analysis can improve performance in all models. Also, in this study, hybrid-wavelet models have presented better results than single models. Among all the models, the WGEP model was the best model and the ANN model was the weakest model for all time steps. The highest values of correlation coefficient and Nash-Sutcliffe efficiency coefficient are related to no time lags and WGEP model and its values are 0.960 and 0.980 and root of the mean squared error and the mean absolute value of the error values are 0.037 and 0.078 meters, respectively. The lowest values of correlation coefficient and Nash-Sutcliffe efficiency coefficient and the highest values of RMSE and MAE are related to the single ANN model for 6 hours lags with the values 0.509, 0.607, 0.181, and 0.286.

The results of their three single and hybrid-wavelet methods can be acceptable for estimating the significant wave height in Amirabad port. Also, disruption of observational data reduces many measurement errors and increases the performance of artificial intelligence models. This study has a significant impact on crisis and coastline management and can be a strategic model for managers, policymakers, and researchers for future research.

Intakes are structures that are used to divert water from a river or canal. Optimizing the performance of intakes and increasing the inflow to the intake, while controlling the sediment bed of the canal in terms of erosion and sedimentation has been one of the topics of water engineering. The use of spur dikes is effective in modifying the flow pattern, controlling erosion and transferring sediment to the intake. The purpose of this study is to use spur dikes to increase the inflow to the lateral intake, in a way that causes the least turbulence, erosion and sedimentation.

In order to perform the experiments, a rectangular channel with a length of 15 meters and a width of 1.5 meters with a fixed slope was used as the main channel. Lateral intake is a rectangular canal with a width of 0.6 and a length of 5 meters at an angle of 90 degrees to the main canal, at a distance of 10 meters from the beginning of the main canal. The model without spur dike was considered as a control model and in other models, the spur dike is located upstream of the intake, upstream in front of the intake, downstream in front of the intake and also as a series of spur dike upstream and in front of the intake. The laboratory models were modeled in FLOW-3D software and calibrated based on laboratory results and data.

Examination of laboratory results showed that the condition of the spur dike at the downstream and in front of the intake has the best scouring results and branching ratio and increase of 66 and 41% at 40 and 60 liters per second, respectively, for branching flow ratio Shown to the control model. According to the results of laboratory models, the model was selected as the best model and modeled numerically with the location of the spur dike in the downstream and in front of the lateral intake (the position of No. 4). Validation of the results of numerical and laboratory models in the hydraulic values ​​of water flow points (R2=0.95) and the number of bed points (R2=0.74) showed that the acceptable accuracy of the numerical model and analysis performed by Flow3D software. Then, first by changing the distance and then by changing the length of the spur dike in the position of No. 4, the numerical model was examined and the best distance of the spur dike, a distance of 58% of the width of the intake and the best length of the spur dike, a length of 30% of the channel width The original was calculated.

This study showed that the use of spur dike downstream and in front of the intake in appropriate dimensions can not only increase the ratio of inlet flow to the intake, but also reduce the scouring of the canal bed, as a result of the use of these spur dike in lateral intake of canals And rivers are recommended.

Gully erosion is one of the main sources of soil loss in watersheds and also one of the main causes of sediment storage in dam reservoirs and river alluvium. In addition, human activities can exacerbate this erosion, which has very worrying consequences. Therefore, the present study was conducted to determine the environmental thresholds of gully erosion and also the morphoclimatic classification of these areas in Kermanshah province.

To do this, first by collecting information from relevant authorities and also using aerial photographs 1: 20,000 and 1: 50,000, the main gully of the province that were visible on the pictures and then this information using field operations and specifying them on corrected on topographic map. Climatic zones of gully in the province were identified using existing maps based on the modified Domarten method. Then, in each climate, one to three gully were identified as targets, and in each of them, a representative gully was identified and two replications were identified, and the field identification of these gully was completed by field operations and field visits. These characteristics included location, land type, dimensions at the head of the gully and at intervals of 25, 50 and 75% of the top, length, profile and general plan of the gully. In addition, soil sampling was performed in the above sections and some physical and chemical properties of soil were measured in the laboratory. The classical statistical method of cluster analysis was also used to classify gully.

The results of this study showed that there are differences in the important morphometric characteristics and topographic threshold of the studied gully in different gully in the province and in different climates, which are mainly due to the climate, type of formation, topography and vegetation of this area. Classification of gully based on the classification method showed that with a similarity level of 97.5%, three general classes can be identified for gully.

gully areas in arid desert climates (warm regions) of the province in one class, gully zones located in the middle altitudes and cold semi-arid climate in the second class and gully zones in cold semi-arid climates to the Mediterranean colds are in the third class similar to gully. The active gully of the province are mainly located in the hill and plain lands. The results of this study show a picture of effective and influential factors in creating gully, based on which it is possible to apply how to control them in future planning and management of officials.

Given the importance of soil and its significant role in the countries evolution, numerous methods are presented to preserve this national capital and to combat the soil erosion consequences. In recent years, Iran like other countries, has taken an effective step to protect soil using organic and inorganic soil preservatives. Therefore, the aim of this study was to investigate the effect of corn mulch on rate and changes runoff and sediment.

This study was in loam – sandy soil in scale small plots laboratory and using a rain simulation with an intensity of 50 mm / h with a10-minute duration has been done. For this purpose, three levels of protective cover of 25, 50 and 75% of corn mulch one control treatment (without conservation cover) with four levels of moisture, air dry, 15, 20 and 30% were considered in three replications.

The results of this study showed that application of corn mulch has a significant effect on runoff and sediment reduction at 99% level. Considering the moisture levels, the amount of runoff and sediment yield in uncoated (control) and 25, 50 and 75% plots were 4422, 4290, 3943 and 3619 ml and 296, 136, 62 and 33 g, respectively. The results of percentage change of runoff, sediment and start time of them showed that the cover at 25, 50 and 75 percent protective cover and different moisture levels were 3.14, 11.25 and 19.29 percent, respectively. Sediment reduction was 62.06%, 77.09% and 88.85%, respectively, compared to the control treatment (without protective cover). The percentage of changes in runoff and sediment of them increased by 32.23%, 73.38% and 136.82%, respectively.

Based on the changes in hydrograph and sediment graph, it was found that 75% corn mulch at 15, 20, and 30% moisture content at 645, 452, 215 and 99 seconds, respectively, was more effective in increasing runoff and sediment time to runoff compared to the control treatment other cover surfaces have been used. However, two more (25 and 50%) were also effective in increasing production time to runoff and sediment. knowledge the trends of runoff and sediment changes and their time by applying conservation cover can be a useful tool and effective solution for soil and water conservation.