Manouchehr Amiri; Hamidreza Pyrowan; Ahmad Ahmadi Khalaj
Abstract
Since marls are highly sensitive to erosion and they annually sent thousands tons of fine grains sediments and clay to reservoirs of dam and artificial feeding stations and increase the cost of filtration of drinkable water and phytoremediation of artificial feeding water greatly, so the studies of different ...
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Since marls are highly sensitive to erosion and they annually sent thousands tons of fine grains sediments and clay to reservoirs of dam and artificial feeding stations and increase the cost of filtration of drinkable water and phytoremediation of artificial feeding water greatly, so the studies of different aspects of marls are important for experts and researchers. In this study we have tried to classifying them and recognizing effective variables of marls classification and examine the relationship between marls groups whit the types and erosional intensity of them. For this purpose, samples were taken from 41 points and they were sent to the laboratory to determine the values of the physical and chemical parameters. The characteristics of the location of the samples such as slope, geographical location and the privilege of seven parameters for soil surface factor and so on were noted. The test of artificial rain was done by kamphorst΄s rainfall simulator apparatus in the adjacent of mentioned points and samples were taken to measure the amount of runoff and sediment of them in the laboratory by simple methods. Furthermore, to identify the types of minerals presenting in the marls and diagnosis of their age, seven samples were analyzed by x-ray diffractometer and eight thin sections of marl and rocks collected along with them such as sandstone and limestones were provided and studied by polarizing microscope. Then, the abnormal data were normalized by logarithm and afterwards, all data were evaluated by cluster analysis, discriminant analysis and scalogram method. Results indicate that the marls are respectively divided into four (S1, S2, S3, S4), five (P1, P2, P3, P4, P5) and six (T1, T2, T3, T4, T5, T6) groups based on their chemical, physical variable and their combination. Fisher linear functions obtained from the classification predict the marl groups, respectively, with an accuracy of about 96.5, 83.9 and 96.9 percent in a correct way that the chemical variables are more appropriate for classification. This study shows that the marls containing a small amount of neutralizating material with high liquid limit are capable of higher erodibility.
