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Showing 27 results for Amini
Sustainability Assessment and Cropping Pattern Determination in Farming Systems Based on the Optimization of Soil and Water Resources Utilization Using Non-linear Mathematical Programming Models
A. Amini Fasakhodi, S. H. Nouri,
Volume 15, Issue 55 (spring 2011)
Abstract
Studying the sustainability of farming systems entails the integrated assessment of the strong interdependence between their environmental, economic and social attributes. Optimum allocation of water resources in a farming system improves the conservation and sustainability status of resources in addition to reducing the socio-economical damages. In order to analyze and assess the different aspects of farm management and agricultural systems planning, a number of mathematical programming models have been developed in recent decades. The purpose of this article was to assess and analyse the sustanability and determine the appropriate pattern of cropping in a rural farming system, namely, south Baraan located in the east of Isfahan city. In order to incorporate environmental, economic and social dimentions, two criteria of maximum net return and employment creation per unit of agricultural water consumption were defined as system’s sustainability indicators. Thus, the ratios “net return / water consumption” and “employment / water consumption” were optimized by using single and multiple objective fractional programming models. The economic and social efficiency of each unit of agricultural water consumption was computed and compared in several single and multiple objective scenarios of linear and fractional programming models, and finally the most appropriate patterns of cropping for the region were determined based on the available land, water and human resources of the region.
Soil Surface and Leave Plantain (Platanus Orientalis)Contamination to Pb and Cd Mapping in Rasht City
M. Amini, A. Forghani,
Volume 19, Issue 71 (spring 2015)
Abstract

Any change in the characteristics of air, soil, water and food that adversely affect the health of the ecosystem, activities of human and other organismsis called contamination. Heavy metal uptake by plants depends on the type and concentration of metalin soil, its bioavailability, and plant species. The use of new sciences such as geostatistics is useful for fast and simple determination of soil and leaf contamination risk. This study studied the amount of soil and leaves of Platanus orientalis contamination in order to map the lead (Pb) and cadmium (Cd) concentration in Rasht city using a geostatistic method. To achieve the goal, 126 samples of surface soil (0-30 cm) and 76 leaf samples (Platanus orientalis) were collected from city streets. Total concentrations of lead and cadmium in the soils and leaves were determined, and clay, silt and sand particle percentage, organic matters, and soil pH were measured. Average concentrations of elements in terms of mg/kg were as follows: soil’s Lead: 86.62, soil’s Cadmium: 0.6, leaf’s Lead: 8.99. For soil Pb and Cd and leaf Pb, spherical model yielded a better fit in the experimental variogram in GS+ program by using trial and error method. According to the spatial structure, Kriging and IDW estimators were used for interpolation. Kriging estimation was mapped using Arc GIS 9.2 software.


Farmers' and Authorities' Attitudes towards the Water Conflict Resolution Methods in Zayandeh-Rud River
A. Yousefi, A. M. Amini, O. Fathi, A. Yadegari,
Volume 20, Issue 76 (Summer 2016)
Abstract

Water, as a limiting factor, has played a decisive role in shaping and development of Iranian culture and civilization. Water scarcity and a great variety of water users lead to conflicts in rivers' environment. Conflict resolution is conceptualized by the methods and processes involved in peaceful facilitating and ending of the conflict through active communication about their thinking and causes of disagreement as well as persistence in collective negotiations. Currently, the Zayandeh-Rud River basin (ZRR) has been facing severe water scarcity. The aim of this study is to evaluate the methods of water conflict resolution in the ZRR from the viewpoint of farmers and authorities. The statistical population of this study includes all farmers in ZRR and selected staff of Regional Water Authority and Agricultural Organization (Jahad-Keshavarzi) in both Isfahan and Chaharmahal & Bakhtiyari provinces. Data were collected through a sample of 171 farmers and census of authorities through face-to-face interviews based on a comprehensive structured questionnaire. Before the survey, the reliability and validity of the questionnaire was initially evaluated on a pre-test study respectively by using Cronbach’s alpha coefficient and Kaiser-Meyer-Olkin (KMO) criteria. The results showed that the main factors in creating the conflict are drought, increased water use in industry and increased water consumption in other provinces. Furthermore, the most suitable methods of water conflict resolution are the conditions where everybody is able to speak freely, mediation and negotiation. On one hand, in the current situation, farmers prefer violent manners and on the other hand, authorities consider negotiation as the most appropriate solution to the conflict.


Determination of Sub-Basin Contribution in Sediment Yield using Magnetic Susceptibility Properties and Uncertainty Mixing Model (Case Study: Ashan Drainage Basin, Maragheh County)
K. , and M. R. Nosrati, M. Amini, A. Haddadchi, Zare3,
Volume 20, Issue 78 (Winter 2017)
Abstract

Accelerated soil erosion in Iran causes on-site and off-site effects and identifying of sediment sources and determination of their contribution in sediment yield is necessary for effective sediment control strategies in river basin. In spite of increasing sediment fingerprinting studies uncertainty associated with magnetic susceptibility properties has not been fully incorporated in models yet. The objective of this study is determination of the relative contribution of sediment sources using magnetic susceptibility properties (High frequency, Low frequency and Frequency dependence) incorporated in uncertainty mixing model. For this purpose, 25 bed sediment samples were collected from the outlet of drainage basin and outlet of sub-basins and their magnetic susceptibility was measured and calculated. The results of Kruskal–Wallis test and discriminant function analysis showed that magnetic susceptibility properties can be used as optimum set of tracers in the uncertainty mixing model. The results of Bayesian mixing model indicated that mean (uncertainty range) relative contribution of Sparan, Joyband and Boyoukchay are 92 (83.9-94.8), 2.8 (0.2-10.7), 5.7 (0.2- 10.5) percent, respectively. According to these results, the highest amount of sediment yield is related to Sparan sub-basin and these results could be used in soil conservation and management planning.


Accuracy Analysis of Precipitation Regionalization Methods Based on Spatial Interpolation Techniques in Zayandeh-Rud River Basin
M. A. Amini, G. Torkan, S. S. Eslamian, M. J. Zareian, A. A. Besalatpour,
Volume 23, Issue 1 (Spring 2019)
Abstract
In the present study, we used 27 precipitation average monthly data from synoptic, climatologic, rain-guage and evaporative stations located in Zayandeh-Rud river basin for the period of 1970-2014. Before interpolating, the missing data in the time series of each station was reconstructed by the normal ratio method. Also, for the data quality control, the Dickey-Fuller and Shapiro-Wilk tests were used to check the data stationarity and normality. Then, these data were interpolated by six interpolation methods including   Inverse Distance Weighting, Natural Neighbor, Tension Spline, Regularized Spline, Ordinary Kriging and Universal Kriging; then each method was evaluated using the cross-validation technique with MAE, MBE and RMSE indices. The results showed that among the spatial interpolation methods, Natural Neighbor method with MAE of 0.24 had the best performance for interpolating precipitation among all of the methods. Also, among Ordinary Kriging, Universal Kriging, Spline and Inverse Distance Weighting methods, respectively, Exponential Kriging with MAE 0.54, Quadratic Drift Kriging with MAE of 0.5, Tension Spline with the MAE of 0.54 and Inverse Distance Weighting with the power of 4 with MAE of 0.57 had the least error compared to other IDW methods.

Digital Mapping of Soil Family Class Using the Machine Learning Approach (A Case Study: Semi-Arid lands in the West of IRAN)
Z. Maghsodi, M. Rostaminia, M. Faramarzi, A Keshavarzi, A. Rahmani, S. R. Mousavi,
Volume 24, Issue 2 (Summer 2020)
Abstract
Digital soil mapping plays an important role in upgrading the knowledge of soil survey in line with the advances in the spatial data of infrastructure development. The main aim of this study was to provide a digital map of the soil family classes using the random forest (RF) models and boosting regression tree (BRT) in a semi-arid region of Ilam province. Environmental covariates were extracted from a digital elevation model with 30 m spatial resolution, using the SAGAGIS7.3 software. In this study area, 46 soil profiles were dug and sampled; after physico-chemical analysis, the soils were classified based on key to soil taxonomy (2014). In the studied area, three orders were recognized: Mollisols, Inceptisols, and Entisols. Based on the results of the environmental covariate data mining with variance inflation factor (VIF), some parameters including DEM, standard height and terrain ruggedness index were the most important variables. The best spatial prediction of soil classes belonged to Fine, carbonatic, thermic, Typic Haploxerolls. Also, the results showed that RF and BRT models had an overall accuracy and of 0.80, 0.64 and Kappa index 0.70, 0.55, respectively. Therefore, the RF method could serve as a reliable and accurate method to provide a reasonable prediction with a low sampling density.

Investigation of Ground Waters Quality Using Multivariate Statistical Techniques (Case Study: Maragheh-Bonab Plain, East Azerbaijan Province)
M. Amini,
Volume 25, Issue 4 (Winiter 2022)
Abstract
Investigation and analysis of groundwater quality to monitor contamination and identify the most important pollutants and pollution points is one of the research fields. The objective of this research was to plan to improve groundwater quality on various spatial and temporal scales. Groundwater information of Maragheh-Bonab plain was collected from 26 wells in 10 years (2001-2011) with 454 sampling points from East Azerbaijan Regional Water Organization and was analyzed using multivariate statistical techniques such as DFA and PCA. Analyzed Variables are included Mg, Ca, Cation, K, Na, TDS, TH, SAR, EC, Anion, pH, Cl, SO4, CO3, and HCO3. Results of PCA showed that variables such as cation, HCO3، TDS، SAR، EC، Anion ،Cl, Ca, and TH were identified as important variables which they can great impacts on the groundwater quality of this region and in the other hand DFA showed which mentioned variables can discriminate land uses and geology formations in primary and normal distribution data with power discriminatory of 68.7 %, 92.2 %, and 66.5 %, 89.1 %, respectively. Investigation of the spatial position of elements using interpolation technique in Maragheh-Bonab plain showed that variables concentration in lowlands are high and 20 villages and their surrounding farms are exposed to high contamination risk of groundwater.

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