Journal of Range and Watershed Managment
Year:2011 | Volume:64 | Issue:3|Papers Count:9

Desertification, after climate changes and deficiency of freshwater, is the third important global challenge during 21th century. Investigating and assessment of the effective factors on desertification trend are very important issues for better land management. The study area is located at south of Neishabour township. This region has been faced to increasing rate of desertification because of drought, vegetation removal, change of rangelands to dry farming lands, water and wind erosion and lack of proper land management over previous years. In this research, data of field study, analysis of aerial photo and satellite image were collected and analyzed in geographic information system. Then FAO-UNEP desertification method (1984) was used in this study. According to this method, vegetation condition, rangeland condition, water and wind erosion and salinity were defined and categorized as the factors defining the status of desertification. Finally, desertification map was prepared. Based on the result, desertification in this region is severe in the northern part of the region mostly due to reduction of canopy, vegetation removal and water erosion. Meanwhile, 57% and 30% of the studied region could be categorized in moderate and slight desertification conditions, respectively. To compare the results and effects of input parameters and their weights; artificial neural networks have been used. After data collection, classification and categorization of and input parameters in four levels including slight, moderate, severe and very severe, desertification map of FAO-UNEP method was used in GIS based on the artificial neural networks approach for predicting desertification condition. Final optimized perception model with one input layer composed of 4 neurons (vegetation condition, water and wind erosion and salinity) and one hidden layer including 39 neurons; and one output layer (desertification condition) based on momentum training algorithm for hidden and output layers was accepted to reach the Mean Square Error (MSE) of 0.07975. Comparison of the outputs of artificial neural network with FAO-UNEP method, shows artificial neural network capability to explain desertification condition. It was also revealed that, definition of structure of networks, training algorithm and cycles in addition to input neurons may effectively influence on the performance of various structures of artificial neural networks.

There are several methods for aquifer recharge that one of them is flood water spreading. The goals of this method consist of feeding of ground water table, increasing the vegetation cover and soil quality. The purpose of this study was investigating the effects of water spreading on the quantity and quality changes of vegetation cover in flood water spreading area of Tangestan over the period of 2000 to 2005. Flood water spreading network consist of 5 strips and12 fixed plots (2×2 m) were established in each strip based on randomized-systematic method. To evaluate the results, an intact land was selected as control area and 8 plots with the same characteristics were established. To investigate of vegetation cover changes in the experiment and control networks, parameters of vegetation such as percent of cover, density, diversity, rate of production, quality and presence and absence of plant species was measured and analyzed with SPSS software. The results showed that in addition to the successful growing of planted trees and shrubs species in the water spreading area, the amount of the dry forage productive increased about 135 kg/ha. Also rangeland trend towards a positive way and change in combination of herbal species had resulted compared to the control area. Also the results showed that there are significant variation between the rate of production and percent of vegetation cover in the experiment and control areas.

Nowadays rangeland restoration is an important task because of severe degradation. It is important to know the ecological processes involved in restoration and the restoration success. This study assessed the effect of a biological restoration after seven years on vegetation and soil in Melerd of Savadkooh located in Mazandaran province. For this purpose vegetation and soil were sampled in different vegetation types (grassland, shrubland and abandoned arable lands) in the restoration area and control site. Data were analyzed at the scale of whole restoration area and control site to evaluate the response of individual species and functional groups. This was also done at the scale of three vegetation types inside restoration area. Results showed that soil humidity was greater in restoration area while soil sand content was greater in the control site. Also three vegetation types within restoration area showed significant differences in the sand, silt, K and EC. It was found 35 common species, 31 species restricted to restoration area and only 6 species restricted to control site from vegetation data. Five plant family, 13 species and some functional groups significantly responded to the restoration project. The biomass of forbs, grasses and total biomass significantly increased due to restoration project. Moreover, the biomass of forbs within restoration area was significantly greater in grassland and restored arable land than that in shrub land. Restoration project produced greater species diversity and richness. This study showed restoration project induced some positive changes in vegetation but little effect was found on soil properties.

This research was conducted to validate a conceptual fuzzy model for predicting gully hazard zonation under arid climatic condition in Bousher province. Based on gully map of the Province, Dareh Koreh Watershed was selected and terrain mapping unit was prepared through overlaying different maps including landuse, land component, lithology and slope. In order to determine the soil attributes, soil infiltration and land protection cover, three gullies were chosen in each terrain unit and soil samples were taken. Based on gully density ratio in every terrain unit, quantitative values of the model parameters were obtained as an input for standard fuzzy set operations including fuzzy intersections and union, fuzzy Gamma operator and index overlay in GIS. The results indicated that the model which includes lithology, slope gradient, soil type, average annual precipitation, landuse and land protection cover is adequetly able to predict vulnerable areas to gully erosion. Moreover, based on observed gully and predicted maps, the fuzzy Gamma operator of 0.8 showed to be the most reliable method for gully hazard zonation map. In the method, slope class of 0-5%, hilly landforms and soil protection areas less than 10% are the most influencing components for gully development.

Nowadays, hazard mitigation strategies in avalanche prone areas, rely both on practical experience and avalanche models that predict snow avalanche path, run out distance and impact pressure. Increasing the reliability and accuracy of avalanche zoning methods is of primary importance in heavily populated areas. Avalanche hazard zones are defined by the frequency and impact pressure of a potential avalanche event. Potential avalanche is the biggest avalanche that an avalanche path can release and is related to snow supply and path geometry. Therefore it is necessary to accurately estimate the release frequency and release areas for a specific avalanche track. Avalanche frequency can be calculated by analyzing avalanche records. But in the case of lacking data it can be estimated by climatic data. In this research, Voellmy-Salm model is used for computing run out distances and velocities for extreme avalanches. Geomorphologic parameters like elevation, slope and aspect were derived from DEM, or aerial photos interpreting. Then potential avalanche release areas are defined and impact pressure and avalanche volume are calculated for a potential avalanche by dynamic models. Consequently, run out distances are defined with respect to avalanche speed that will be zero in run out zone. Finally avalanche hazard zones are defined by impact pressure and avalanche frequency. In this paper we analyzed Karaj road (between Nesa and Gachsar) and provide avalanche hazard map. It can be fined that this area is avalanche prone by analyzing topographic parameters. Steep slopes without dense forests are the most important factor in avalanche releasing. High mountains and climatic parameters can supply instable snow pack that can release. The results show that the road is in red and blue zones.

Floods deposit huge amounts of suspended and dissolve materials of different sources on alluvial fans and therefore change soil characteristics such as permeability over the time. This research was carried out in Chandab-Varamin basin to assess the effect of floodwater spreading practices on topsoil infiltration rate using Double Rings. 10 cm of topsoil layer was collected from the profile and analyzed in the laboratory. Results showed that fine sediments (silt and clay) have been deposited in soil surface layer. Meanwhile, the permeability rate in the first row was measured control about 50 percent, in the third row of about 35 percent and about 42 percent of total area has decreased compared to the control area. Also, infiltration rate was decreased about 73 percent in the first band, 31 percent in the third band and about 52 percent in the whole area compared to the control area. Comparison of clay amount in control and treatment areas showed that their accumulation on soil surface changes negatively, soil physical characteristics including soil texture and makes soil more crusty which gradually decrease soil infiltration in floodwater spreading site.

Slope instability in steep mountainous areas is the basic problem for land managers around the world. Although, many physically-based models have been presented for hillslope stability in recent years, but none of them consider the effects of plan shape and profile curvature together. The purpose of this research is presenting a physically-based hydrological model to investigate the shallow landslides (1-2 m) in forested areas. In this study, 10 hillslopes were selected using the satellite images of Google Earth. Then, by computing the necessary parameters for the physically-based model obtained from field studies, experimental data and topographic analysis, the factor of safety was calculated for each hillslope and with different rainfall return periods. Finally, the map of landslide zonation was provided for all hillslopes in the research area. The results show that the presented model is able to analysis the slope stability in hillslopes with landslide under natural conditions because the hillslopes with landslide have FS less than 1. Therefore, it can be concluded that combination of topographic and hydrologic models with hillslope stability models which consider the effect of root zone can be used as a physically-based model for investigating the hillslope stability in natural hillslopes.

Determination of tensile strength of various plant roots is an important indicator for selecting proper plant species to be used for soil reinforcement and for evaluation of the effects of various species on stability improvement. Thus, the main objective of present study was to determine and compare root tensile strength of three important species of Hyrcanian forests and to investigate the diameter-tensile force and diameter-tensile strength relations. For this purpose, root samples of beech, hornbeam and Persian ironwood were collected from up and down slopes and tensile strength tests were carried out using a standard Instron apparatus. To evaluate the effects of species, root diameter, and location on profiles on the tensile strength, analysis of covariance (ANCOVA) was employed. The results showed that tensile force increased following a power law with increasing root diameter. But tensile strength increased following a power law with decreasing root diameter. Based on the results, magnitudes of a and b coefficients in diameter-tensile force relations decreased from beech to hornbeam and ironwood, respectively. However, the magnitude of a in the relation between diameter and tensile strength, decreased from beech to hornbeam and ironwood. Meanwhile b increased from beech to hornbeam and ironwood, respectively. The results of ANCOVA revealed significant differences between species and profiles. The highest and lowest tensile strengths among species were also observed for beech and ironwood. It was also observed that down slope roots were stronger than upslope ones.

The aim of this research was to investigate the effect of index specie of Artemisia sieberi on associate plant of Stipa barbata from different aspects. The study was carried out in Anjedan rangeland located in Markazi province. After delimitation of study area, to consider their density and correlation, totally 30 A. sieberi individuals were determined randomly and individuals of index and associated plants (A. Sieberi and St. barbata) for each 30 points in 50 cm distance were counted. Presence of index and associated plants were recorded along four transects of 50m length based on randomized-systematic method. At starting and end points of each transect, soil samples were taken from adjacent control area to compare soil properties in control area and index species habitat soils to find out the effects of index species on soil properties. Soil samples were analyzed in laboratory to determine texture, pH, Ec, OM, lime, Na, K, P and N. Data were analyzed and comparisons were made using SPSS software. Results showed that density changes of A. sieberi and S. barbata were similar along the transects. Correlation studies using Chi-square indicated that there was a huge positive correlation between A. sieberi and S. barbata. Soil characteristics comparison in two areas revealed that only lime content was significantly different which was higher in A. sieberi habitat soil. Totally, it was found that A. sieberi has positive effect on presence of S. barbata.