H. Azimzadeh, F. Fotoohi, M. R. Ekhtesasi,
Volume 18, Issue 68 (summer 2014)
Abstract
Soil surface roughness (SSR) is one of the important factors in wind and water erosion studies and control. Several parameters such as surface rock fragments influence SSR. Main objectives of this paper are to study and compare (Allmarass) random roughness (RR) and tortuosity (Tb) indices in coarse, medium and fine grain plains of Yazd-Ardakan and investigate the relationship between indices and desert pavement coverage. Roughness data were obtained by pin roghness-meter and roller chain in the three mentioned plains. RR and Tb were measured in 90cm transect length with systematic sampling pattern after determining the boundary of three kinds of plains. In each plain, 30 transects were randomly sampled and the height of soil surface roughness fractions was recorded. Distance of pins in the applied roughness meter is about 2cm. Therefore, in each 90 cm transect the height of 46 points was measured. Desert pavement coverage was measured in 20×20cm2 plots. The result showed that desert pavement coverage in coarse, medium and fine grain plains were in the range of 55-100, 40-85 and less than 5%, respectively. The relationship between RR and desert pavement was significant. The result of ANOVA (Duncan) showed, RR and Tb were significantly different in coarse, medium and fine grain plains (p-value<0.01). In addition, by increasing desert pavement percentage RR and Tb increased exponentially in base of Neper number. The relation between RR and desert pavement coverage is stronger than Tb and desert pavement coverage. Correlation between the two measured indices was calculated and compared in different plains. The result revealed that about 54, 33 and 14% of the arability in Tb could be explained by RR in coarse and medium grain plains, respectively. The correlations of two indices were significant in coarse and medium plain and insignificant in fine grain plain. The trend of RR and Tb decreased from mountain to plain center. Although RR increased slightly in fine grain plain, the difference was not significant.
M. Hayatzadeh, M. R. Ekhtesasi, H. Malekinezhad, A. Fathzadeh, H. R. Azimzadeh,
Volume 21, Issue 1 (Spring 2017)
Abstract
Soil erosion is undoubtedly one of the most important problems in natural areas of Iran and has destructive effects on different ecosystems. Considering that calculation of the sediment rate in sediment stations and direct measurements of erosion process is costly and difficult, it is critical to find ways to accurately estimate the amount of sediment yield in catchments especially in arid and hyper arid areas because of their high ecological sensitivity. One of the most commonly used methods in these areas is the sediment rating regression method. Therefore, in this study sediment observed data for 48 events (the corresponding discharge and sediment) in a 23-year period from Fkhrabad basin (Mehriz) were compared to the estimated data obtained from Multi-line rating method, extent middle class, middle class rating curve with correction factor QMLE, SMEARING correction coefficient FAO and Artificial Neural networks (ANNs). Finally, the accuracy of these methods were assessed using different evaluation criteria such as Root Mean Square Error (RMSE), coefficient of determination (R2) and the standard Nash (ME). Results showed that ANN outperformed the other methods with the RMSE, R2 and ME of 203.3, 0.86 and 0.66, respectively. The results suggest that these methods should be used cautiously in estimating the suspended sediment load in arid and hyper arid regions due to the nature of the observed data and temporal and seasonal flow systems in these regions. It was also indicated that the artificial neural network models have higher flexibility than other methods which makes them to be useful tools for modeling in poor data conditions.
Z. Abbasi, H. Azimzadeh, A. Talebi, A. Sotoudeh,
Volume 22, Issue 4 (Winter 2019)
Abstract
Groundwater quality evaluation is very necessary to provide drinking water. Groundwater excessive consumption can cause subsidence and penetration of saline groundwater into freshwater aquifers in Ajabshir Plain, on the Urmia lake margin. The main goal of the current project was to evaluate the groundwater quality by employing the qualitative indices of groundwater and GIS. Ten parameters of 15 wells including EC, TDS, total hardness as well as the concentration of Ca++, Na+, Mg++, K+, SO4--, HCO3- and Cl- were analyzed. At first, the maps of parameters concentration were prepared by the kiriging method. Then based on WHO drinking water standards, the maps were standardized and ranked for drawing the maps of quality indices. The results showed that quality index changes were in the range of moderate (61) to acceptable (81). Removing the single map method of sensitivity analysis detected the quality index was more sensitive to the K+ parameter. Finally, the quality index from the eastern north to the western south of Ajabshir Plain and the other areas was ranked in the acceptable and moderate classes, respectively.
