نشریه پژوهش های حفاظت آب و خاک
سال هجدهم شماره 4 (زمستان 1390)

In this study landslides occurred in a part of Haraz watershed were determined using aerial photos and field studies, then landslide hazard zonation was determined using geomorphological factors (slope, aspect and elevation) and geological factors (lithology and distance fault) as the most important effective factors on landslide hazard. So each of the effective factors as information layer was used in ILWIS environment for analysis based on fuzzy set theory using MATLAB 7.1 software before that membership functions were determined for each effective element on landslide. Then output of software computed hazard for each pixel inacase study map transformed to ILWIS software environment and landslide hazard zonation was made using fuzzy Gaussian and Triangular membership functions. Evaluation of results showed that landslide hazard mapping using gaussian membership function QS (0.23) is more accurate in comparison with map made by using triangular membership function QS (0.0515).

Flood is one of natural hazardous disasters that causes economic and life damages every year. Therefore, scientists have tried to assess the variability of this phenomenon. In this study, the ability of Artificial Neural Network (ANN) and Geographical Information System (GIS) in the estimation of flood discharges of 90 sub-basins of Hamedan Province (with concentration time less than 24 hours) was assessed using a data period of 16 years collected at the 17 hydrometric stations throughout the area. In this regard, area of the basins, elevation and mean slope, bindery of hydrologic groups of soil, weighted curve number as well as daily and 5 day precipitations which occured before the corresponding floods used as the input variables and the flood discharge defined as the output. Considering the training, validation and testing sets the results showed that the best structure was a feed forward ANN with two hidden layers of 5 and 4 processing elements. In this model, the coefficient of determination, root mean squared error and mean absolute error were 0.87, 0.72 and 2.83, respectively. Finally, using the maximum daily and 5 day precipitations for a return period of 25 years and application of the model, the spatial distribution of the direct runoff was predicted. Therefore, flood mapping of the province was specified to determine the priorities of flood control between the regions. Finally, the results indicated that ANN method was an appropriate tool for flood discharge modeling, especially in the case of missing data or inadequate hydrometric stations.

Nowadays new models have developed that provide us more with evaluating water resource systems omplications moreover; they are used extensively in quantitative operation of water resources. Therefor extensive studies have been done about optimized operation of single reservoir systems.With attention to the desirable results from optimized operation of single reservoir systems, nowadays extensive researches about multireservoir systems have been done with more complexities. So a multireservoir system was studied. One of the modern methods of optimization is Ga used in this study for optimal operation of a double reservoir system consisting Golestan and Voshmgir reservoir located in Gorganrood river basin. Both reservoirs are used to supply agriculture demands of the area, considering many floods occurred in the understudy area, Golestan reservoir plays a key role in yearly flood control in the region. So exact calculation of control volume in this reservoir is very important. To continue the research consists of:stages of Ga method, study of Gorganrood basin and reservoirs built on this river, becoming familiar with the goals for building of each reservoir and calculating control volume in Golestan reservoir through flood routing using hec-5, introducing continuing equations of doubleb reservoirs system, objective and penalty functions. Finally analysis of results through charts and graphs and comparing to real demands was demonstrated that with mutation probability 0.1 and crossover probability 0.8 after 600 generations will have reliability coefficient of 100% for Golestan reservoir and 85.74% for Voshmgir reservoir.

There are more than 70000 hectares of Mollisols in the southern part of Gorgan River, in the Golestan province, Iran. Taking into account the mollic intergrades, it reaches to 150000 hectares. Parent materials of the studied lands are loess materials. The main objectives of the present study were to examine the mineralogy of Mollisols and Mollisols like soils and also effective factors on the distribution of clay minerals. Clay mineralogical studies showed that the dominant minerals of loess parent materials were illite, smectite, chlorite, and kaolinite. The general order of the dominance of clay minerals in the studied Mollisols, were: Illite > Smectite > Chlorite > Kaolinite. Illite was the dominant clay mineral in most of the studied soils especially toward the eastern parts of the province. Smectite was the dominant mineral in the poorly drained soils in low lands of the western parts. Drainage condition therefore seems to play an important role for the occurrence of smectite besides the inherited origin in the studied area.

Hydrological conceptual models such as SWAT lay on numerous inputs and parameters that make calibration process complicated and time consuming. Digital Elevation Model (DEM) is one of the important inputs that its resolution affects watershed delineation and models simulations. However, DEM with more fine pixels is costly. This paper aims to assess the effect of DEM resolution on parameters calibration and estimation of runoff and sediment in the SWAT model. To this end, three sources of DEM with 50, 90 and 1000 meter pixel sizes are applied for daily rainfall-runoff and sediment simulation within the Gamasyab watershed. Furthermore the parameters, which are directly derived from DEM like watershed slope and river slope, are excluded from calibration process. The calibration of the model was done by SWAT-CUP that uses inverse modeling approach. It is observed that the runoff simulation results by the three DEMs are relatively similar. However, in case of sediment, the differences were a little more significant. The reason for these similarities can be attributed to the non-uniquness property of inverse modeling, in which an observe signal could be reproduced by many different parameter sets. Therefore, considering limitations about available observations for calibration process; significant improvement in results cannot be expected while using three DEM cell sizes.

Results of a Non-Linear Programming (NLP) model were used to develop Fuzzy Rule Bases for optimal Ilanjogh reservoir operation located in Daregaz, north‌east of Iran. The dam is desiged for agriculture of three crops (winter, barley, and sorghum). Making decision is considered in two levels: reservoir and farm levels. The reservoir level Fuzzy logic model extracts important features of the system from the input-output data set by NLP and represents features as general operating rules. The developed model serves not only as efficient decision making tool in easy and understandable Fuzzy Inference Systems, but also provides operators with a limited number of the most meaningful operating rules using Clustering-Based approach. The model is set properly in a yearly based with initial storage and monthly steps. Results showed that the changing trend of water releases in both models is the same with R2=0.97 such that over the 12 months period, both trends had increased from October to May but since then, they decreased gradually. But in general, the amount of annual released water in Fuzzy model is almost less than NLP, especially in competitive month, May and June, when there was a competition between all 3 crops for water, the percentage of water deficit to the percentage of annual mean water deficit were 0.57 and 0.81 in training and 0.93 and 1.145 in the test stage, respectively.

With sprinkling irrigation, determining water distribution uniformity of coefficient (cu) from a single sprinkler is time consuming due to overlap vsprinkling by neighboring sprinklers and also different pressure heads (P), riser heads (RH), sprinkler gaps on laterals (Sl) and the distance between laterals (Sm). The best combination of the above parameters for maximum CU, is still unknown for applicators. In this research, CU quantities of zb model sprinkler (made in Iran) were measured at Hashemabad cotton research station of Gorgan under 3 different pressure heads (2.5, 3 and 3.5 atm), 2 riser heads (60 and 100 cm) and 7 sprinkler (SlSm including 912, 915, 1212, 1512, 1218, 1515, 1518m) arrangements. Different equations for genetic algorithm using mentioned parameters were evaluated using a written program with Matlab software. Based on R2, RMSE and standard deviations obtained between estimated and measured data using genetic algorithm, the equation of (R2=0.92, RMSE=3.57) was selected as a final model.

Susceptibility of soil to rain-induced erosion processes is assumed as detachability and re-detachability parameters. In some conditions, generated overland flow can entrain and transport soil particles therefore, affects on the erodibility results. This study was conducted to investigate the effect of process changes in rain- induced erosion experiments on these parameters using four scenarios. Different rain intensities and flume slopes were simulated by a rainfall simulator on 3 cropland soils. The results showed that including stream powers less than the critical values and considering steady state conditions, the re-detachability was 100-212 order of magnitude of the detachability, while considering all stream powers, this ratio was from 62 to 122. Depending on the soil properties, there are some differences between two conditions of steady and unsteady. Compared to the former status, taking into account all stream powers, detachability and re-detachability parameters were over calculated 2-4 and 1.2-2.5 times, respectively. This finding reveals the importance of experimental design on determination of succeptibilty to rain-induced erosion.

Drought is a weather condition which accompanies with lack of precipitation over a certain time periods that human activities in the area located under its impact will experience negative effects. In this research daily rainfall data of nine synoptic stations in Khorasan Razavi province in the static period of 1989 to 2008 were used. Standardized Precipitation Index for one-month and three-month scales was calculated and then drought and wet periods were determinated and counted. Monthly average of isobars, isotemps, iso- RH, and iso-PWC (6 months of autumn and winter) were considered for 20 years (1989-2008). Results showed that three cities, Sarakhs, Quchan and Gonabad in autumn and cities of Torbat heydariye, Sarakhs, Quchan, Kashmar and Gonabad in winter have experienced the most drought. Lowest dry autumn and winter periods, were related to the Kashmar and Nishabur stations respectively. Also consideration of every year drought situation of study period shows that in 2001, all stations have experienced different intensity (acute, severe and moderate) of this phenomenon, so this year was considered as the base year of droughts in the period under review and its synoptic maps were presented. The study of synoptic patterns in base year showed that despite of good conditions for precipitation (low temperature, high relative humidity and precipitable water content of cloud) in all months of autumn and winter, due to interaction of Siberian high pressure system with Azores high pressure system and strengthening of Siberian high pressure and its complete domination over the region, not only rainfall has not happened, but also local and orographic precipitation faced with constraints and therefore moderate, severe and acute droughts, occurred entire region of our study.

Solar radiation (Rs) is one of the most input parameters in hydrological models and crop growth. Despite its importance for many cases but Rs measurements are not easily available due to the cost, maintenance and calibration requirements of the measuring equipment. Over the past decades, many researchers have developed various equations and none linear models for accurately estimating RS from meteorological parameters. In this study, daily maximum and minimum air temperature, relative humidity, extraterrestrial radiation and actual sunshine duration values from 1992 to 12001 for Kermanshah synoptic station, were used as inputs. In first stage, the measured Rs data were investigated to control errors and inconsistencies. After quality control test appropriate combination and dataset requiring for training nonlinear model and calibrating empirical equations were determined by using gamma test (GT). Based on GT finding, appropriate combination consists of all input parameters and dataset was needed to training Local Linear Regression (LLR), Artificial Neural Network (ANN) and empirical equations equal to1300 datasets. The LLR and ANN with two learning methods (Levenberg-Marquardt (LM) and Conjugate Gradient (SCG)) models based on gamma test have been implemented and compared with eight locally calibrated empirical RS equations. The comparisons have been based on statistical error criteria, using measured daily RS values. The results indicate that nonlinear model have high accuracy than empirical equation and ANN (LM) with R2 equal 0.9599 and RMSE and MAPE 1.4213 MJ.m-2.d-1 and 6.7616 percent respectively has minimum error.

Soil erosion is a major issue in agricultural production and food security. Soil conservation is important in farm productivity increase, food security and sustainable agriculture. Soil degradation is increasing due to unsuitable use of farmland condition, so investigation of socio-economic factors is necessary in increasing adoption rate and decreasing soil degradation costs. The aim of this study is analyzing socio-economic factors that affect the level of terracing acceptance by farmers in Deh-chenashk village in Chamani watershed, in Gorgan river basin, Golestan province. Necessary information has been collected through 74 questionnaires including individual, farmland features, and awareness level of farmers about soil conservation practices in the study area. Effective socio-economic factors on terracing adoption analyzed through statistic-economic model using Logit regression. The results showed a significant positive correlation between farmer’s education, main occupation (farming), farmland ownership, farmland slope, farmer’s awareness level about soil conservation practices, using extension services, farming income and terracing acceptance. Interpreting weighted aggregate elasticity and marginal effects of effective factors showed that one percent increase in education, one percent increase in farmer’s awareness level, and increasing farmer’s income lead to 0.11, 0.48 and 78 percent increase in acceptance of terracing, respectively. According to the study finding applied suggestion offered to decision makers for better management of watershed and reducing soil erosion.

Pollutant sources of water, are agricultural, industrial and urban – rural pollutants. In order to identify chemical contamination of groundwater due to agricultural activities, the spatial distribution of agricultural pollutants around drinkable water area of Sabzevar City and their role in creating critical areas, should be studied. Results showed that regarding nitrogen pollution, Eastern Qhasabeh District with 358.5 tons has produced the higher pollution, mainly due to the establishment of industries and service units and are among the areas considered as critical region. Therefore highest pollution of various agricultural activities is resulted. Regarding to the findings the following recommendations are proposed: 1-Creating a management plan for water system twirl, 2-refining wastewater for agriculture, 3-reform and clean water in the existent stream,4-recognition of sabzevar water status.

In order to study and evaluate wind erosion, despite experimental formulas and field measurements, nebka analyzing by natural methods is a suitable and cost reduced way. Considering significant distribution of nebkas in Miankaleh coastal barrier system, southeast of Caspian sea,31 nebkas were analyzed in 4 geographical zones from east to west, in order to measure and monitor their functions.In each nebka morphometric parameters such as long axis length, short axis length and height were measured. Also, Nebka' s concentration per 100 m2, stabilization percentage and dominated biological cover were analyzed. Because nebkas in zone 3 were higher than other zones and Nebka's stabilization is less than 50 percent, wind erosion in this region is more than other regions and zone 3 is considered as a prefered region for projects. Textural parameters in sand sediments such as average size, sorting, skweness and kurtosis were determinded. Results show that textural parameters are not different from each other in 4 zones. Nebka sediments were classified texturally in medium to small average size, very well sorted, positive skewness and leptokurtic sediments. Local distribution shows the pattern of wind erosion and ways of soil conservation.

In this investigation, two dimensional simulations of marine currents in the Gorgan Bay in the summer 2009, by using Mike21 simulator software were done for calculating flow pattern, water level fluctuations and velocity components. The hydrodynamic equations included the depth average equations of continuity and momentum. The fluctuations of water level in the Ashooradeh station, wind stress as constant in space but varying in time, the average river flow and evaporation were applied to the model. Water surface elevations and flow patterns were computed by the model via the Tide Pole and continued through tracing three floaters. The results of the model expresses, the flow pattern has been affected by wind stress, bottom topography, input and output of the only open boundary model (entranced of Ashooradeh–Bandaretorkaman) and surround by the Miankaleh peninsula and is a counterclockwise pattern in the summer season.