dr. m. r. ekhtesasi

Seasonal floodwater has been kept in the lands by using watershed projects so that it penetrates into underground beds, but this case causes different influences on graining, permeability, underground water and vegetation. Three sections were chosen as experiment sites to measure soil changes of watershed projects in Nodoushan watershed area of Yazd province. Seven permeability experiments with double cylinder inside every section and three experiments in the control group were performed. Along with each of these experiments, one sample was collected from 0.5 meter of the surface soil and graining experiment was performed on it. The significance of permeability was investigated by the use of non-parametric Mann-Whitney test and Kolmogorov–Smirnov test. The results show that permeability in Sadrabad, Nodoushan and Alaviyeh in control group were 4.92, 3.52 and 5.89 cm/ hr, respectively. After some periods of dewatering they were reduced 94 percent, 89 percent and 92 percent, respectively. And finally reached to 0.28, 0.37 and 0.47, respectively. Also, the average diameter of the particles decreased about 90 percent. The results of experiments showed that the decrease of permeability was significant in the level of 95 percent.

The drainage networks as the most prominent landscapes on earth are basis of many hydrological and geomorphological models. Due to the geomorphological properties of the region, the drainage network shows its own fractal properties that are saved as code in it. In fact, drainage networks are fractal phenomena with fractal behavior. Fractal dimension is a parameter used to indicate the complexity of data. The analysis of fractal dimensions of drainage networks and their morphometric properties facilitate the perdition of their behavior in the future. This paper focuses on the relationship between fractal dimensions of drainage networks and their morphometric properties of drainage networks in Yazd- Ardakan basin. Therefore, through an analysis of fractal dimension of drainage networks and its comparison with morphometric properties, the fractal behavior of these drainage networks are investigated. Results showed Pck and Ktl formations indicate highest and lowest fractal dimension respectively. The results indicated a significant relationship between fractal dimensions of drainage networks and morphometric properties. In this research, a positive relationship was observed between morphometric parameters and fractal dimension, so that the greatest correlation coefficient was found between the fractal dimension and the drainage density (0.99).

Identifying the saline soils and preparing digital maps of soil salinity, is an effective step in correct management of saline lands. Since vast areas of Iran are covered by saline soils, so these maps are very important. Soil salinity is one of the stages of land degradation that eventually leads to decrease in soil productivity. Soil salinity could be caused by natural processes or human activities. However, soil salinity is a major environmental hazard. So, providing a soil salinity map for these regions, can improve the level of management. Soil salinity maps are prepared by using satellite images as easily as possible. Considering the difficulty of mapping salinity from satellite data, in this study, two approaches for modeling and classification of soil salinity maps were evaluated. The purpose of this study is to evaluate the modeling method and supervised classification of soil salinity mapping using ASTER and ETM images in the East of Semnan plain.
After site selection and spreading a net over the image of area, we determined the location of sampling points. The soil salinity map was prepared After the following steps: measuring EC of soil samples, geometrical and radiometric modification of satellite data, applying some processing such as principal components analysis, fusion of ASTER multispectral bands with ETM panchromatic band, transformation of tasseled cap, filtering, producing the salinity indexes, assessment of spectral, and also using supervised classification method.
the salinity map was obtained using modeling method from the eighth band of Aster satellite. The results show that the component that is obtained from integration of an ETM panchromatic band and band 5 of ASTER, and a component of salinity index (Salinity2) have a significant relationship. The model validation by the MAE, RMSE and R showed that the selected model has good performance. The accuracy of the salinity map which was produced by Supervised Classification method has been estimated as 84% based on maximum likelihood method and 74% based on minimum distance method. This represents that the accuracy obtained by the above mentioned methods is lower than modeling method for preparing the salinity map.
According to the results of the study, adjusting the salinity indicators resulted in obtaining new indicators for mapping soil salinity. A better diagnosis of soil salinity was resulted from the use of band 3 of Aster image. . So it can be suggested that a part of the electromagnetic spectrum, including (0.52 – 0.86, 2.145-2.185 and 2.295-2.365 micrometers) can be useful in mapping soil salinity in different areas.