Showing 3 results for Karoon
M. Shafaei Bajestan, M. Salimi Golshaikhi,
Volume 6, Issue 4 (1-2003)
Abstract
Downslope soil movement along riverbanks is a significant erosion process. Plant roots, particularly of woody vegetation, apparently stabilize soil on slopes because in most areas where the vegetation is removed, frequent bank failure occurs. Plant roots increase soil-shearing resistance both directly by mechanical reinforcement and indirectly through removal of pore water by transpiration. In this study, the effects of two plant species on the stability of the Karoon River has been investigated. To determine the In-situ shear strength of soil, a special device was designed and manufactured. This device is capable of measuring the shear strength of soil blocks as large as two cubic meters. In this study, twelve soil blocks, four blocks with roots of each tree and four blocks of root permitted were measured.
Comparison of the soil shear strength with roots and root permitted soil shows that tree roots can significantly increase the shear strength of the soil. The amount of increase depends on the type of plant, the age of plant, the diameter of the roots and the percentage of roots in the block. In this study, the amount of increase varied between 20-66%. From the analysis of the data, two equations were developed to determine the increased shear strength.
H Tabari, S Marofi, H Zare Abiane, R Amiri Chayjan, M Sharifi, A.m Akhondali,
Volume 13, Issue 50 (1-2010)
Abstract
In mountainous basins, snow water equivalent is usually used to evaluate water resources related to snow. In this research, based on the observed data, the snow depth and its water equivalent was studied through application of non-linear regression, artificial neural network as well as optimization of network's parameters with genetic algorithm. To this end, the estimated values by artificial neural network, neural network-genetic algorithm combined method and regression method were compared with the observed data. The field measurement were carried out in the Samsami basin in February 2006. Correlation coefficient (r) mean square error (MSE) and mean absolute error (MAE) were used to evaluate efficiency of the various models of artificial neural networks and nonlinear regression models. The results showed that artificial neural network and genetic algorithm combined methods were suitable to estimate snow water equivalent. In general, among the methods used, neural network-genetic algorithm combined method presented the best result (r= 0.84, MSE= 0.041 and MAE= 0.051). Of the parameters considered, elevation from sea level is the most important and effective to estimate snow water equivalent.
S. Jafari, M. Karimzadeh, A. Abdeshahi,
Volume 25, Issue 2 (9-2021)
Abstract
Characteristics of most soils in arid and semi-arid regions affected by carbonates. The study aimed to determine the distribution of carbonates in the size components of some soils in Khuzestan province. Upward to the bottom of Karun, Karkheh, and Jarahi rivers were studied at depths of 0-50, 50-100, and 150-100 cm. The results showed that the average amount of carbonates in the soils of the Jarahi river basin (37%) was significantly different from the amount in the soils of the other two rivers (33%). Carbonates were observed in all soil size components but the maximum was present in the clay component. The highest regression relationship between soil particles was in the clay component (0.375). The highest percentage of particle reduction after carbonate removal was related to coarse silt particles (0.75). Therefore, the soil texture changed from clay in Jarahi, from clay and silty clay in Karun, and silty clay in Karkheh due to the removal of carbonates to sandy loam. There was no significant difference in the distribution of carbonates at different depths for river soils and all studied soils. The relatively uniform distribution of carbonates in the four components studied in these soils from the surface to the depth showed that the carbonates originated from the parent material, namely alluvial flood sediments of these rivers.
