m. pajouhesh

Studying the process of soil erosion and evaluating its effective factors is one of the most important prerequisites for proper management of soil and water resources. This study was conducted to investigate the production of surface and pipe runoff and sediment using artificial rainfall on silt loam soil in the laboratory. So, the soil was collected from the study area and transported to the laboratory. Laboratory experiments were performed on a soil bed in a rectangular flume with three pipes, at slopes of 2%, 6%, 10%, 14%, and 18% under simulated rain (30 mm/h) for one hour. Related graphs were drawn in Excel to analyze the results, and Spearman's correlation test was used in SPSS software to check the correlation between runoff and sediment values in each slope. The results showed that with the increase in slope, the sum of surface and pipe runoff and sediment increased over time. For example, in a slope of 2%, the runoff and sediment in the initial moments of the experiment increased from 0 to 1.3 liters and 26.2 g m-2 at the end of the experiment. Also, the correlation coefficient between runoff and sediment in the slopes was 0.98, 0.62, 0.4, 0.93, and 0.15, respectively, which was significant in some, but in others, it was not significant because of soil loss.

Awareness of the number of changes in runoff and sediment on different slopes can be useful in modeling the production of runoff and sediment. Therefore, this study was conducted to investigate the production of surface and tunnel runoff and sediment in saline and sodic soils on different slopes. Saline-sodic soil was collected and transported to the laboratory. Laboratory experiments were performed on a soil bed in a rectangular flume at three different slopes (5%, 10%, and 15%) under simulated rain (30 mm/h) for one hour. An analysis of variance was used to investigate the effect of slope on runoff and sediment production, and the means were compared using Duncan's test at the five percent level using SPSS version 26 software. The results showed that there was a significant difference between the slopes of the runoff (P<0.001) and sediment (P<0.001). In the first minute of the experiments, due to the lack of moisture in the soil, the amount of runoff was low, but over time, the amount of runoff increased. It is because the pores are blocked by the dispersion of soil particles owing to the presence of sodium ions, which ultimately leads to a decrease in permeability. Similarly, in the last few minutes, outflow from the tunnel was observed, and this flow occurred only on slopes of 10% and 15%. The amount of sediment was also low in the first few minutes, which could be related to the low amount of runoff and the lack of sediment particle removal. Nonetheless, after the lapse of time, its amount increased, and the primary reasons were reduced permeability, increased runoff, and removal of fine particles from the soil surface.

The runoff curve number method is widely used to predict runoff and exists in many popular software packs for modeling. The curve number is an empirical parameter important but depends largely on the characteristics of soil hydrologic groups. Therefore, efforts to reduce this effect and extract more accurate soil information are necessary. The present study was conducted to integrate fuzzy logic for extraction runoff curve numbers. A new distribution model called CNS2 has been developed. In the first part of this research, the formulation and programming of the CNS2 model were done using the Python programming language environment, then the model was implemented in the Beheshtabad watershed. This model simulates the amount of runoff production in a watershed in the monthly time step with the fuzzy curve number and takes into account the factor of rainy days, the coefficient of management of the RUSLE-3D equation, and the soils theta coefficient. The results indicated that the model with Nash-Sutcliff 0.6 and the R2 coefficient 0.63 in the calibration set and Nash index 0.53 and R2 coefficient 0.56 in the validation set had appropriate efficiency in runoff simulation. The advantage of the model is that distributive and allows for the identification of areas with higher runoff production.

Land use changes identifying to assess and monitor sensitive areas for sustainable planning and land management is essential. Remote sensing and the use of GIS technology as some of the most common methods in the world in monitoring land changes, especially, in the study of large areas. In this study, the trend of spatial land use changes in the area of Karun 3 dam was investigated. in the before and after the construction periods and dam intake using remote sensing and GIS over 27 years. In this study, the satellite imagery of Landsat 5 TM sensors from 1991 and 2008 and Landsat 8 OLI sensors in 2018 were analyzed and processed. Using object-oriented classification with land use maps for the three periods 1991, 2008, and 2018 with the overall accuracy of the Kappa index of 0.93 and 0.89 percent for 1991, 0.94, and 0.88 percent in 2008 and 0.93, respectively, and 0.86% in 2018 was prepared. The results showed that the water use of the region with an area of 37.68 square kilometers is increasing and agricultural lands and residential areas with an area of 1349.04 and 226.56, respectively, forest lands with an area of 1041.49 remained as the dominant cover of the region and rangelands by going through a decreasing trend of increase in both periods after forest use, with an area of 878.87, they had the largest area. According to the obtained results, it can be said that the construction of the Karun 3 dam has caused the flooding of agricultural lands and their conversion to another use, as a result of which the villagers were forced to migrate due to losing their jobs and abandoned residential areas become other uses.

The aim of this study was to determine the possible difference in the amount of organic carbon and total nitrogen in the soil under the crown of tree species in a semi-arid forest at the level of a single tree. Also, the pattern of possible differences between these two main soil materials was observed in different size classes of trees and in top- and subsoil. For this purpose, 60 trees from four species of juniper (Juniperus excelsa), narrow-leafed ash (Fraxinus angustifolia), Brant's oak (Quercus brantii) and hawthorn (Crataegus azarolus) were randomly selected in a mixed stand of central Zagrosian forest that had been enclosd for over 30 years. The amounts of organic carbon and total nitrogen of topsoil (0-15 cm) and subsoil (15-50 cm) were measured and compared. The results showed that, first, both the amount of soil organic carbon and the total nitrogen from the samples beneath the tree crowns were higher than their corresponding values in soils outside the crowns. Second, only the amounts of soil organic carbon were affected by the species, and these values ranged from a minimum of 1.37% in topsoil and 0.52% in subsoil for hawthorn, to maximum values of 1.64 and 0.73 percent for Juniper in top- and subsoil, respectively. Third, the amount of total nitrogen in the soil with an average of 0.21 and 0.08 percent of dry weight in top- and subsoils, respectively were the same beneath the crowns of the four species. Fourth, the size of the trees only affected the amount of organic carbon and total nitrogen in the topsoil. This study showed that there is little difference in soil organic carbon and total nitrogen under the canopy of different tree species in a standard Zagros forest and therefore the whole stand may act as a mega-organism and has more or less homogeneous soil.