m. tazeh

Nebkha and the plant that creates it together form a system. nebkha formation parameters have a significant effect on the transfer rate of aeolian deposits. Adequate information on nebkha will help plan more accurately and efficiently and better manage wind erosion-prone lands to identify appropriate wind erosion programs and deal with this phenomenon. This study aimed to compare regression methods and artificial neural networks to investigate the relationship between the quantitative characteristics of Tamarix and Seidlitzia Rosmarinus plant species and quantitative parameters of nebkha. The regression methods used in this study include PCR, PLS, and OLS. In this study, the plant characteristics used are plant height, length, width, and type, and morphometric characteristics include nebkha length, height, slope, and width. The number of sampling points was 80 selected randomly from nebkha in Khour va Biabanak County. 70% of the data was used for training the network and 30% for validation. According to the results of this study, the highest R2 between nebkha length and Seidlitzia Rosmarinus plant characteristics is related to the OLS method with 0.8, followed by nebkha area and width. R2 levels in the neural network were lower, i.e., 0.76. In the case of the Tamarix species, the highest R2, i.e., 0.797, is related to the characteristics of the plant with nebkha length, followed by nebkha area and width. This value is 0.78 in the neural network method. Moreover, the evaluation results of different predictive models showed that the OLS model is superior to other models.

This research was an attempt to investigate the quality and quantity of groundwater resources in Yazd-Ardakan plain as the biggest watershed in Yazd Province and its relationships with the geological formations. For this purpose, qualitative data of the wells in the plain for the decades of 80 and 90 (according to the Iranian calender for the pre- and post-water transfer from Zayandehroud River to Yazd) were studied. Furthermore, the geological formations map of the region was prepared based on the geological maps and Google-Earth images. Then, the type and facies of water for each well was determined using Aq.QA 1.1 software. The suitability of water usage for agriculture and drinking purposes was also evaluated. Results showed that the chloride type of the groundwater was dominant in the southern and central parts of the watershed and also in 90s rather than 80s. Results of the qualitative zoning showed that the amount of EC was increased as 3 dSm-1 from 80s to 90s. Quantitative zoning of the groundwater showed that the elevation of the water surface decreased toward northern part of the watershed. The water depth in the wells was also decreased on the average of 10 m from 80s to 90s. Results also showed that the wells were dug often on the alluvium formations. Correlation analysis between water quality and frequency percentages of geologic formations revealed that the highest correlation (r=0.99) was observed between calcareous geologic (Ktl) unit and EC of the groundwater; whereas, there was the least correlation between Acidic volcanic rocks (Pc-cr) geologic unit and EC of the groundwater (r=0.07).

Particle-size and their distribution are important in various sciences such as: agricultural, natural resources, and even engineering and medical engineering. Using mechanical sieves requires considerable cost and time. The purpose of this study was to investigate the capability of image processing techniques for desert pavement. Thus, random sampling of desert pavement was carried out in bare and epandage pediments. Samples were transferred to the laboratory and was grading using standard sieve series. The collected samples taken were also photographed. Photos were analyzed using Image Processing and Analysis in Java and Geological Image Analysis Softwares.Then the results of the software were compared with the values measured by the sieve series. Results, show that the values obtained for particle aggregation using Image j software have a correlation of 93% in the epandage Pediment particles and 96% in the bare Pediments with mechanical sieve. Results of correlation between mechanical sieving and GIAS software in epandage pediment have an average correlation of 91% and in bare pediment has a correlation of 96%. It can be concluded that the use of these softwares can be a good substitute for mechanical sieve in particle size distribution. Using the results of this study can be effective in reducing cost and time in perform grading.