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Showing 3 results for Yonesi

H. Torabipoudeh, H. Yonesi, A. Arshia,
Volume 24, Issue 2 (Summer 2020)
Abstract

Understanding the quality of groundwater resources, which are the largest available freshwater reservoir, is one of the needs in planning and developing water resources. The purpose of this research was to study the quality changes of groundwater resources in the upstream aquifers of Zayandehrood Dam (1995-2016) and to evaluate water quality in terms of drinking and agricultural consumption and evaluation of IRWQIGC. For this purpose, EC, TDS, SAR, PH, TH, Cl, CO3, Ca, Mg, Na, K, HCO3 and NO3 parameters and heavy elements including zinc, copper, lead, cadmium and arsenic were investigated from laboratory samples. In the upstream aquifers of the Zayandehrood Dam, the water classification was mainly agricultural in the C2-S1 range, and it was generally acceptable in the drinking classes. The amount of heavy elements was allowed. The average amount of nitrate in the Chehelkhaneh, Damanehdaran, Boein-Miandasht and Chadegan aquifers was calculated to be 43.77, 48.08, 35.53 and 26.36 mg / l, respectively, and the maximum nitrate levels in these areas, however, were often exceeded. Nitrate zoning and IRWQIGC were performed by the kriging method. The lowest index values, which fell into relatively poor classes, were in the south and southwestern parts of Boein-Miandasht and south and south-west of the Chehelkhaneh, and in the central parts of Damanehdaran, and the south of Chadegan.

N. Hasanzadeh, L. Gholami, A. Khaledi Darvishan, H. Yonesi,
Volume 25, Issue 1 (Spring 2021)
Abstract

Soil erosion is one of the most serious environmental issues in the world, causing soil degradation, reduction of land productivity, increasing flood, water pollution and pollutions transportation; it is also a serious threat to sustainable development in the world. Therefore, the soil conservation and the prevention of soil erosion and use of conditioners as the nanoclay can be considered as a solution to improve   land productivity and protect environment. The present study was, therefore, conducted to address the effect of the application of montmorillonite nanoclay with three rates of 0.03, 0.06 and 0.09 t ha-1 on changing runoff and soil loss variables under laboratory conditions. The results showed that the nanoclay with the rate of 0.03 t ha-1 could decrease the runoff coefficient, soil loss and sediment concentration with the rate of 40.65, 88.38 and 82.19 percent, respectively. The average of soil loss in control treatment and conservation treatments of nanoclay with various rates was measured to be 3.76, 0.44, 1.33 and 3.16 g, respectively. Also, the results showed that the most sediment concentration was the control treatment with the rate of 5.84 g l-1 and the conservation treatments with nanoclay in the applied rates was 1.04, 3.47 and 2.96 g l-1, respectively. Also, the results showed that the nanoclay effect was significant on changing the soil loss and sediment concentration at the level of 99 percent. Finally, due to the effect, the use of this conditioner in natural conditions and investigation of the effects on environment and aggregates stability are recommended.

B. Shahinejad, A. Parsaei, H. Yonesi, Z. Shamsi, A. Arshia,
Volume 26, Issue 4 (Winiter 2023)
Abstract

In the present study, the flow rate in flues containing lateral semi-cylinders (SMBF) was simulated and estimated under free and submerged conditions using back vector machine models (SVM), spin multivariate adaptive regression (MARS), and multilayer artificial neural network (MLPNN) model. In free flow mode, the dimensionless parameters extracted from the dimensional analysis include the ratio of upstream flow to throat width and contraction ratio (throat width to channel width), and in the submerged state, in addition to these two parameters, the depth-to-throat width, and bottom-depth parameters upstream depth were used as input and the two-dimensional form of flow rate was used as the output of the models. The results showed that in free flow mode in the validation stage, the MARS model with statistical indices of R2 = 0.985, RMSE = 0.008, MAPE = 0.87%, and the SVM model with statistical indices of  R2 = 0.971, RMSE = 0.0012, MAPE =1.376%, and MLPNN model with statistical indices of R2 = 0.973,  RMSE = 0.011, MAPE = 1.304% have modeled and predicted the flow rate. In the submerged state, the statistical indices of the developed MARS model were R2 = 0.978, RMSE = 0.018, MAPE = 3.6%, and the statistical indices of the SVM model were R2 = 0.988, RMSE = 0.014, 2%. MAPE = 4, and the statistical indicators of the MLPNN model were R2 = 0.966, RMSE = 0.022, and MAPE = 5.7%. In the development of SVM and MLPNN models, radial kernel and hyperbolic tangent functions were used, respectively.


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