فصلنامه پژوهش های فرسایش محیطی
سال سوم شماره 1 (پیاپی 9، بهار 1392)

One of the important parameters، that reduce negative influence of the other known parameters، is cover vegetation. In this study were estimated cover vegetation influence in soil erosion of rasin basin in Kermanshah privance that is our study area. The first step is preparation map of NDVI obtained & category of cover vegetation by the landsat TM data. Then Revised Universal Soil Loss Equation with six factors (Annual Rainfall Erocivitie، Soil Erodibility، Vegetation cover & Toographic) & hydrophysic model with five factors (Rainfall، Topography، vegetation، area، erosion) Were used for evaluating & estimating of soil erosion in rasin basin. Ofter product data layut of models factors to estimating of influence of cover vegetation، each models twoist performance، with calculating ratio coverage & without calculating this ratio. For estimating of intensity erosion by hydrophysic model، the sediment load potential calculated in surface unit. Result indicated that erosion in different land cover is variable. With the influence of other factors in the different land cover، the influence of these factors can be changed. The highest erosion have been estimated in the south، south-west & north، north-east of rasin basin. Without calculating of cover vegetation by RUSLE equation erosion emount increase from 485 ton per hectar per year to 650 ton per hectar per year، & in hydrophysic model sediment load potential emount increase from 834/259 ton per km2 per year to 1900/56 ton per km2 per year.

The presence of human in nature and his willing or unwilling activities have culminated in a series of destruction and balance clash in the nature. Today، the increase of population and high demand for agriculture production has resulted in the destruction of plant coverage on the land particularly forests and grassland by human and increase the erosion. In this paper، via using world soil erosion equation and applying TM satellites images (1998) and ETM (2009) the erosion of Sivand River was highlighted for two periods of 1998 and 2009. For the extraction and processing of satellite images the ERDAS was used and for mapping and its related analysis the Arc GIS and SPSS software were used. The results showed that the erosion in 1998 was 406172389 tons and in 2009 was 416364377 tons which shows 1. 87 tons increase in each hectare. The main cause of erosion changes during the course of study was the decrease of plant coverage which resulted from population increase as well as the interference in nature and immethodical grazing in grassland areas which decreased the soil coverage and weakened the soil against rainfall and other factors.

Planting Haloxylon aphyllum under oil mulches has frequently been used for stabilizing mobile sands in Iran for during the last three decades. This study is carried out in stabilized sandy desert of Samad Abad-e-Sarakhs to evaluate the implications of planting Haloxylon aphyllum on the vegetation and soil attributes. Sampling was carried out random-systematically in the representative areas of the treatment and control plots. In each treatment and control area nine transects of 50 m were placed and data including the density and the canopy cover of the two dominant species of the field (viz. Astragalus squarrosus & Convolvolus hamadae) as well as the total canopy cover of the understory plants were recorded. In addition، in each area 220 plants of the two species were selected and examined for their total and living aerial foliage volumes. What’s more، four soil profiles were used in each area and sampling was made at the depths of 0-20 cm and 20-80 cm to be further analyzed for the organic matter content. Data analysis was performed using the independent t-test. Results indicated that planting Haloxylon aphyllum has reduced the total canopy cover beside the canopy cover and densities of the two dominant species. The implications also include the reduction of the total volume of Astragalus squarrosus، yet there was no such reduction for Convolvolus hamadae. As a result there was significantly reduction of organic matter content at the surface depth and accumulation of it in the deeper depth.

Common methods to determine the soil infiltration would need lots of time as well as costs. On the other hand، the existence of non linear behaviors in soil infiltration would make it difficult to be modeled. Regard to the difficulties of direct measurement of soil infiltration، using indirect methods for estimation of this parameter، has received attention in recent years. In spite of the existence of various theoretic as well as experimental equations، some other indirect methods such as artificial neural networks are used to estimate this soil phenomenon. Now a day، artificial neural networks are shown high efficiency in modeling non linear equations. In the present study، 200 soil samples were collected from Ghoshe location in Semnan Province. Half of samples were collected from agricultural lands and the other half were collected from pastures nearby lands. Some soil chemical as well as physical properties such as electrical conductivity (EC)، soil texture، lime percentage، sodium adsorption ration (SAR) and bulk density were considered as easy and fast obtainable features and soil permeability as difficult and time consuming feature. The collected data randomly divided in two categories of training and testing and they used for train and test of two artificial neural networks، multi-layer perception using back-propagation algorithm (MLP/BP) and Radial basis functions (RBF) and nonlinear regression model. Results of this research show high efficiency of artificial neural network compare with multiple regression and also MLP network was better than RBF network. Sensitive analysis was used to determine correlation between independed parameters and permeability.

The estimation of sediment loads in rivers is one of the most important and difficult part of sediment transport studies and river engineering. Then، accessing the new methods (that can be effective in this background)، are more important and weird. In this research، using the artificial neural network (ANN) for optimization of the results of sediment rating curve (SRC) has been investigated to predict the suspended sediment loads. For doing that، the Yadakan station on Ghatoor-Chai River was considered. An equation by SRC method was obtained and then an ANN method by the same data was used and finally by combining them، the new model was built. It should be mentioned that before using the combined model، each method was used and the obtained results were compared with the observed data. Based on this research، the results of using the combined model is more precise than the using ANN and SRC separately as the Dr value from 1. 402 (in SRC) and -2. 395 (in ANN) is changed to 0. 963 in combined model. The RMSE has also obtained 692. 286 and 616. 96 for SRC and ANN respectively while this value is decreased to 603. 094 for combined model.

Rarely found in nature can be quite direct route to the river. Most rivers have channels that bend are quite complex scour pattern is dominated. To study the behavior patterns necessary to scour a river known as the dominant bends. Numerical models as a powerful instrument for the prediction of such arenas can provide a good understanding of them. In the present study using three-dimensional numerical model Flow-3D، the effects of parameter U/Uc، flow rate and channel width of the scour pattern at a 90 degree arc of the moving bed is. The results were compared with experimental data. Analysis of results relevant to scour pattern in cross sections and different plans are among other points introduced in this paper.

In spite of successfulness of watershed management project، this science could not be able to combat soil erosion lonely and it needs the participation of habitants of watersheds that their livelihood completely depends on sustainable resources. So، this research through analysis of collaboration network between state and formal public institutions in implementation of mechanical and biological watershed management projects and comparing them together tries to answer this question: Whether the extent of collaboration of formal public institutions with state institutions in implementation of mechanical and biological watershed management projects differ? The data was gathered through questionnaires were filled by asking from formal public institutions of Rural District of Berentin located in Hormozgan province and the experts and managers of Organization of Natural Resources and Watershed Management. Data analysis was done by Network Analysis Method. The results showed that in spite of allocation of the most budget of watershed management to mechanical projects in order to combat soil erosion، the formal public institution had much more participation and collaboration in biological projects. Also، the network connectivity and involvement of public and state institutions of these projects is more than the other one. So، because of the high social support of public institutions from biological watershed management projects in this Rural District، these projects could be the best، the most effective and the cheapest solution for soil erosion decrease in this Rural District and even in Hormozgan Province.