نشریه پژوهش های آبخیزداری
پیاپی 112 (پاییز 1395)

Prolonged recently drought in East Azerbaijan has significantly been caused decreasing in the availability of water resources. In this time, gardens and cultivated area has been increased as irregular and disproportional in terms of climate changes. As the highest rates of water consumption is in the agricultural sector, it is very necessary to investigate the alternative water resources and optimization methods in water supplying. Now day, Rainwater harvesting is one of the practical methods for this mean. This research project was executed(in1ha area) with aims to apply gravel filter to infiltration and optimization as well as increasing water storage of harvested rain water into plant root zone. Research area is located in southwest hillslope of Own-Eb neh-ali mountain of Tabriz city. This project was conducted as Randomized Complete Block with five treatments and four replications. Treatments included: Treatment A, control, Treatment B, system by collecting pebbles and vegetation cover from its area with gravel filter, Treatment C, system by collecting pebbles and vegetation cover from its area without gravel filter, Treatment D, system by semi isolated area and gravel filter and Treatment E, system by semi isolated area without gravel filter. The effect of Gravel filter on the penetration rate and increasing of the water storage, were measured in 20 and 50 cm depths using TDR after each rainfall event. Results showed that mean soil moisture rate in Treatment D (semi-isolated system with gravel filter) in both 20 and 50 cm depth are 35.94 and 30.56 respectively and significantly higher than other treatments (p

Recognition of regions susceptible to Landslide event is one of the basic measures taken to decrease the possible risk, and hazard management. The main purpose of this study was to produce landslide hazard mapping by LNRF model based on geographic information system (GIS) for the Ziarat watershed, Golestan province, Iran. At first, a landslide inventory map was prepared by using earlier reports and aerial photographs, and a total of 50 landslides were mapped and out of which 35 (70%) were randomly selected for building landslide Hazard model, while the remaining 15 (30%) were used for validating the model. Thirteen input data layers were employed as landslide conditioning factors in the landslide Hazard modeling. These factors are slope percent, slope aspect, altitude, plan curvature, precipitation amount, lithology, land use, distance from faults, distance from rivers, distance from roads, topographic wetness index (TWI) and stream power, CTI (Sediment Transport Index)and stream power index (SPI). Afterward, landslide susceptibility map was produced using LNRF model. For verification, receiver operating characteristics curve (ROC) and area under the curve (AUC) approaches were used. Verification results showed 82.15% accuracy. According to the results of the AUC (area under curve) evaluation, the map produced exhibits satisfactory properties.

The purpose of present study is to determine the gender of the sediment constituents and attribute sedimentary particles to the lithological units of basin in order to determine the relative importance of each lithology unit in creating sediment. In this study, the first profile is made on the sediment behind the mortar stone dam in Madabad 1 sub basin, located in Ghare Ghoush Khodabandeh, and different samples are collected. Formation is performed for all samples using wet sieving method. Then, sieves of 150 micron, 300 micron and 1.18 mm are selected as standard sieves. After that, 100 grains of sediment from each sample are selected and mineralogical analysis is carried out by using Binocular as well as considering the sedimentary aspects of the area. Particularities of rocks and minerals are determined by counting them and the results are compared with lithologic units by determining the contribution of every mineral and rock fragment. Then, particularities of stone and production unit of each mineral and rock fragment as well as the share of each stone unit in sediment production is determined. According to the obtained results, the share of Qt2 units which include new alluvial, is 34.65 percent. However, the share of M1q lithologic unit, which consists of fossil limestone and bio-micritic, is 65.88 percent. After including the factor of area and calculating the relative importance, it is revealed that the Qt2 unit, with the relative importance of 56.32, in comparison with M1q unit, with the relative importance of 43.68, has greater relative importance in sediment production.

Some noticeable areas of valuable land resources are degraded every year, due to improper management of land use activities. Soil degradation includes reduction of soil productivity or its nutrients loss by soil erosion. This research was executed in Honam sub-basin, located in Lorestan Province to study the soil quality degradation and mapping. The study area was segmented to unique soil degraded polygons, as working units, using TMU and Geopedology methods. Soil was sampled in each working unit and their organic carbon, total nitrogen, available phosphorus and potassium, bulk density and micronutrients such as Iron, Zinc, Manganese and copper were measured. Quality control charts were drawn for all measured soil specifications in each working unit. Soil degradation indices and their types, causes, degrees, extents and severities were determined by GLASOD model and consequently, soil degradation map were provided. For statistical comparison, soil degradation maps resulted from TMU and Geopedology work units were compared with ground control points using Vilkaksen and paired comparison tests. Results demonstrated that there are 46 types of working units at 61 locations in TMU working units map. These numbers are 45 types at 94 locations in Geopedology working units map. The accuracy of soil degradation maps provided from TMU and Geopedology methods were 66.3 and 68.9 percent, respectively. From precision view of point, coefficient of variation in work units of TMU and Geopedology methods were 25.58 and 30.26 percent, respectively. Results showed that there are no significant difference between fertility degradation degree of ground control points and TMU working units in both tests. Also, results showed that there are significant difference between fertility degradation degree of ground control points and Geopedology working units in both tests.

Residential and urban development in margins of rivers and floodplains have Changed rangeland and agricultural land toresidential and industrial land then the hydrological behavior of watershed has been unusual. In this study, the behavior of urban flood of Birjand in the shahroud watershed was studied. The shahroud watershed has hada lot ofnon-expert land use change in recent years. In this way initially runoff curve number of SCS model was determined using satellite images, land use and field visits. In the continue, flood discharge was simulated using HEC-HMS model after surveying geometrical characteristics of the main river and its hydraulical structures such as bridges. The results of the simulation show that 25 and 100-year return period leading to the occurrence of peak flood discharge amount of 207.63 and 463.56 cubic meter per second respectively.Results of the simulated flood with a return period of 25 years show that this flood is maximum flow that cross sections and hydraulical structures of the river are able to cross, So in order to reduce the risks of flooding in the city of Birjand more attention to the increased potential for flood passing is essential.

Rare earth elements (REE) are used for sedimentary provenance studies due to their immobility during weathering, transport, and sedimentation. In this research, in order to comparison REE and REE indices between different facieses, we collected 73 surface samples from there. For data analysis, we used Duncan and ANOVA method. Result showed that, there are significant difference in 99% level for La, Ce, Pr, Eu, Ho, Er, Yb and indices such as ∑REE, Eu/Euï, (Gd/Yb)n, (La/Yb)n between different facieses and there are significant difference in 95% level for Nd element and Nd/Yb index. Also, there aren’t significant differences for Sm, Gd, Tb, Tm, Lu, Dy and (La/Sm)n index between different facieses. Maximum and minimum correlation observed between Eu/Eu*:(La/Yb)n and (Gd/Yb)n:(La/Sm)n indices, respectively and also, Maximum and minimum correlation observed between Fe2O3 /Al2O3:Nd and CaO:Nd, respectively. CIA in all samples was less than 55, which indicat there aren’t any weathering in case study.

The amount of forage in the rangelands at different times during the grazing season and in the same year is different. In current conditions, grazing capacity is calculated once for grazing season which may coincides with the maximum production of the range plants. It causes many more livestock entrance during the grazing season in to the rangelands and the result is damaged pastures. The possibility of measuring rangelands production in different months of every year is not possible. Therefore, it is necessary to estimate the amount of forage production during the months of the grazing season, in a few years In order to calculate the long term grazing capacity of rangelands. The aim of this research is determine the seasonal changes in forage production and utilization of range plant Chrysopogon aucheri in during the growing season of the different years. The study area located at 265 meters above sea level far from about 40 kilometers from Bandar Abbas, in the Jevengane Genou. Vegetation type of area is Gymnocarpos decander-Euphorbia larica. For this purpose, inside the enclosure, the forage production of this species was measured every month in growth season. In outside the enclosure the remain forage production is measured and subtracted it from the forage production of inside the enclosure for estimating of consumed forage. The amount of forage production and consumption, after drying in the open air, was weighed and analysed with SAS soft ware.The results showed that, due to the high variability of monthly and annual rainfall, forage production and consumption of this key species in the study area, at the different months and years, have significant difference with each other.

Recognition and evaluation of influencing factors on desertification as well as determination of influenced area with this problem is necessary. The method of FAO-UNEP is one of the proper methods to evaluating the desertification which into study the different factors and process. Vegetation distraction, water and wind erosion, decreasing the quality and quantity of water supply, saltification of soil together with animal pressure and human population on the environment were the main factors and processes investigated in this research. A period time of 20 years (1989-2008) choose for assessment of desertification in this study and data were collected with considering the aerial photograph and remote sensing images. For investigation of each processes were evaluated several indices and scoring with field sampling and library studies. Four class of poor, moderate, intense and very intense were determined for discrimination of desertification levels. Each process was investigated from 3 aspects such as existing condition, speed and natural capability of desertification. Desertification maps was constructed in GIS and integrated for final desertification map. Base on the result were classified 116466ha (%20) in low, 273240ha (%48) in intermediate and 179123ha (%32) in severe class of desertification in Shazand watershed. Intense desertification were observed mainly in mountainous and rocky area with slop higher than %40 and poor vegetation. Severe desertification was observed mainly in mountainous ranges with slop higher than 15-30 percent and poor vegetation. Water erosion and vegetation destruction were the main factors of desertification in this watershed and whereas the animal pressure was the main factor of desertification intensity.

In order to assess drought situation in Yazd province and planning programs, zoning drought map should be prepare to reduce damage resulting from this phenomenon. For this aim, in this study after calculating standard precipitation index in time series of 6 and 12 months in 39 meteorological stations located in Yazd province, Kriging and Inverse Distance Weighted 1 to 5 were used to interpolate Standardized Precipitation Index in March 2010. Then error maps were estimated using cross-validation, root mean squared error (RMSE), mean absolute error (MAE) and coefficient between estimated and observed values (R2). The Results showed in time series of 6 and 12 months, IDW3 and 2 are more accurate, respectively. Also, the drought severity classification showed that the most percent of area belongs to low class of drought in time series of 6 and 12 months. However, with increasing time step the wet severity is decreased in the north and high drought has been changed to the moderate class in the south of the study area.

Soil hydraulic properties have key role in sugar cane cultivation management. The purpose of this study is to estimate soil moisture characteristic curve using an artificial neural network and its optimization with genetic algorithm. Therefore, based on the cultivation operations management and soil properties included: organic matter content, soil texture, electrical conductivity, sodium adsorption ratio, 4 land unit tracts in Debel-Khozaii, Amir-Kabir, Karoon and Haft-Tapeh agro-industries were selected. A total of 310 soil samples from both 0-40 and 40-80 cm of soil profiles were collected. In this study, five models were arranged in hierarchy to estimate soil hydraulic properties with ANNs. The performances of the models were evaluated using Spearman's correlation coefficient (r) between the observed and the estimated values, normalized mean square error (NMSE), and mean absolute error (MAE). Owing to the fact that the selection of each of the variable parameters of neural network necessitated recurring trails and errors, and consequently teaching a large number of networks with various topologies, genetic algorithm method was utilized for finding the optimization of these parameters and the efficiency of this method was examined in terms of the optimization of neural network. Results showed that the neural network has a high degree of accuracy in modeling and estimating soil moisture characteristic curve (R =0.943, MAE=0.019, NMSE=0.054). Also, combining artificial neural networks with genetic algorithm for optimizing the conditions of the artificial neural networks implementation was positive and combining approach indicated its superiority over non-optimized implementation of artificial neural networks in all cases (R=0.985, MAE=0.01, NMSE =0.0151).