Showing 7 results for Nosrati
K. Nosrati, H. Ahmadi, F. Sharifi,
Volume 16, Issue 60 (Summer 2012)
Abstract
Sediment sources fingerprinting is needed as an autonomous tool for erosion prediction, validation of soil erosion models, monitoring of sediment budget and consequently for selecting soil conservation practices and sediment control methods at the catchment scale. Apportioning of eroded-soil into multiple sources using natural tracers is an integrated approach in soil erosion and sediment studies. The objectives of this study, as a first work, are to assess spatial variations of biochemical tracers and theirs validation in discriminating sediment sources under different land uses and water erosions at catchment scale and to apply them as fingerprints to determine relative contributions of sediment sources in Zidasht catchment, Iran. In view of this, 4 enzyme activities as biochemical tracers were measured in 42 different sampling sites from four sediment sources and 14 sediment samples. The results of discriminant function analysis (DFA) provided an optimum composite of two tracers, i.e. urease and dehydrogenase that afforded more than 92% correct assignations in discriminating between the sediment sources in the study area. Sediment source fingerprinting model was used based on optimum composite of two tracers resulting from DFA to explore the contributions of sediment from the four sources. The results showed that the relative contributions from rangeland/surface erosion, crop field/surface erosion, stream bank and dry-land farming/surface erosion sources were 11.3±5.3, 8.1±3.8, 75±8.5 and 3.6±2.5, respectively. Therefore, we can conclude that fingerprinting using biochemical tracers may help develop sediment fingerprinting models and as a first step facilitate a more complete tool for fingerprinting approach in the future.
K. , and M. R. Nosrati, M. Amini, A. Haddadchi, Zare3,
Volume 20, Issue 78 (Winter 2017)
Abstract
Accelerated soil erosion in Iran causes on-site and off-site effects and identifying of sediment sources and determination of their contribution in sediment yield is necessary for effective sediment control strategies in river basin. In spite of increasing sediment fingerprinting studies uncertainty associated with magnetic susceptibility properties has not been fully incorporated in models yet. The objective of this study is determination of the relative contribution of sediment sources using magnetic susceptibility properties (High frequency, Low frequency and Frequency dependence) incorporated in uncertainty mixing model. For this purpose, 25 bed sediment samples were collected from the outlet of drainage basin and outlet of sub-basins and their magnetic susceptibility was measured and calculated. The results of Kruskal–Wallis test and discriminant function analysis showed that magnetic susceptibility properties can be used as optimum set of tracers in the uncertainty mixing model. The results of Bayesian mixing model indicated that mean (uncertainty range) relative contribution of Sparan, Joyband and Boyoukchay are 92 (83.9-94.8), 2.8 (0.2-10.7), 5.7 (0.2- 10.5) percent, respectively. According to these results, the highest amount of sediment yield is related to Sparan sub-basin and these results could be used in soil conservation and management planning.
M. Zarea Khormizi, A. Kavian, K. Soleimani, K. Nosrati,
Volume 21, Issue 2 (Summer 2017)
Abstract
Obtaining information about relative importance of sediment sources and their contributions on sediment production and thus identification of on-site critical areas is required for implementing soil and water conservations and sediment control programs. For this reason, in this study 35 geochemical tracers and organic carbon were measured in 45 samples of sediment sources and in 11 watershed sediment samples to determine the sediment deposit contribution of each land use as sediment resources in Kond watershed of Tehran province. Based on the results of Kruskal-Wallis test, from among 35 measured traces, 10 tracers including Al, As, Be, Ca, Mo, P, Pb, S, Zn and OC had ability to discriminate sediment sources with less than 1% confidence level. Then, 5 tracers: OC, S, P, Zn and As were selected as optimum composite using Discriminant Function Analysis (DFA) with 0.000 confidence coefficient that had distinguishing capability of sediment sources by 97.8% correct assignation. Finally, the results of multivariate mixing model showed that contribution means of orchard, range and residential were 1.54, 14.27 and 84.18% in sediment production, respectively. Also, the sum of squares of the error was 0.33. The results of this study can be used in selecting an appropriate method for sediment control in studied area.
K. Nosrati, M. Majdi,
Volume 21, Issue 4 (Winter 2018)
Abstract
The soil pollution especially in urban soils is projected to increase drastically and its effects on chemical cycles are yet to be known. Approaches to measure air and water quality are well established, but urban soil quality assessment has received little attention. Soil quality assessment can help as a way to better understand the pollution increase outcomes in urban environments and to establish approaches and integrated soil quality assessment protocols in urban planning and landscape management. Considering lack of information in urban soil quality of Iran, the objective of this study was to assess soil quality under urban land use effect using minimum data set in western part of Tehran. In view of this, 56 soil samples were collected in three land use types of agricultural, parks and urban landscapes, and vacant urban lots and 12 physicochemical properties were measured. The results of analysis of variance (one-way ANOVA) showed that under influence of the land use types, organic carbon, total nitrogen, lime, bulk density and sodium have significant differences. The factor analysis was used to select minimum data set and the results showed that two factors with eigenvalues more than one, explaining more than 68% of total variance, have the most loading factors on organic carbon and sodium. Finally, soil quality indicator (SQI) was determined and compared in different land use types. The results showed that SQI has significant difference in urban land use types and the least soil quality is related to vacant urban lots.
K. Nosrati, M. Heydari, M. Hoseinzadeh, S. Emadoddin,
Volume 22, Issue 3 (Fall 2018)
Abstract
Ziarat drainage basin, in the southern part of Gorgan city, is exposed to mass movement, especially landslide occurrence, due to geologic, geomorphologic, and anthropogenic reasons. The objectives of this study were to predict landslide susceptibility and to analyze the effective factors using rare events logistic regression. In view of this, the map layers of the variables including geology, land use, slope, slope aspect, distance of road, distance of fault and distance of river were prepared using topographic and geologic maps and aerial photo interpretation. In addition, the map layers of the soil variables including the percent of clay, silt, sand, and saturation water as well as plasticity limit index were determined based on the laboratory analysis of 32 soil samples collected from landslide sites and 32 soil samples obtained from non-occurrence landslide sites. The controlling factors of landslide were determined using rare events logistic regression analysis; then based on their coefficients, the landslide risk zoning map was prepared and validated. The landslide risk zoning map was classified in five different hazard classes ranging from very low risk to very high risk; the very high risk class with 16.8 km2 was assigned as the having the highest percent of the catchment area. The results of the model validation showed that the rare events logistic regression model with the receiver operating characteristic (ROC) of 0.69 could be a suitable prediction model for the study area. The results of this study could be, therefore, useful for corrective actions and watershed management landslide high-risk zones.
K. Seydinaureh, S. Ayoubi, K. Nosrati,
Volume 23, Issue 4 (Special Issue of Flood and Soil Erosion, Winter 2019)
Abstract
The purpose of this study was to determine the relative contribution of sub-basin resources to sediment production by using magnetic susceptibility data as the tracer in Chehelgazi catchment, Sanandaj. For this purpose, 20 samples of the output 5 sub-basins were measured by harvesting and magnetic susceptibility. Kruskal-Wallis test results showed that in all three trackings, frequency high, low and dependent, at least two sources had the ability to differentiate. In the second step, the three tracers were tested on the discriminant analysis by the sub-basin source and two tracers with different power splitters showed the high frequency of 88% and the frequency dependence of 12%; power splitters both tracers together in the sub-basin splitters was 90%, so they were selected as the optimal combination; therefore, they have the capability to determine the relative contribution model of sediment. The results of Bayesian uncertainty model also indicated Todarsamadi sub-basin with 44.4% of the largest contribution and Doveyseh, Chatan and Cherendo sub-basins with 35.5, 7.9 and 4.5, respectively, and Madian Dol sub-basin with 4/4 percent had the lowest contribution to sediment production. Based on the available results, Todarsamadi and Doveyseh sub-basins had the highest amount of sediment production; so these results could be used in soil conservation and management planning.
S. Jalali, K. Nosrati, Z. Fathi,
Volume 27, Issue 2 (Summer 2023)
Abstract
The geomorphic characteristics of the watersheds are interrelated and the temporal and spatial scale in the form of season and sub-basins affect the concentration of suspended sediment. One of the objectives of this study was to investigate the relationship between suspended sediment concentration and watershed characteristics of Kan River using principal components regression and to recognize the effect of seasons and sub-basins on sediment concentration. The concentration of suspended sediment during four rainfall-runoff events in three seasons and in sub-basins was measured and calculated. The sixteen physiographic and land use characteristics were determined in the sub-basins and the main factors were identified and the scores of each factor for each feature were calculated using principal component analysis (PCA). The results of variance analysis showed that the concentration of suspended sediment was significant in terms of time scale and spring had the highest rate of sedimentation. Redundancy analysis and canonical analysis on the properties that participate in the first factor (PC1) showed the characteristics of the percentage of erodible formation, relatively erodible formation, and percentage of free construction activity, respectively. Road (slope leveling) and stream length are the most essential attributes of sub-basins in the production and concentration of suspended sediment in the study area.
