habib beigi
Abstract
Boroujen–Fradonbeh plain is one of the nine main agricultural hubs of Charmahal Provine. The aim of this study was to define and map a deficiency index of soil micronutrients and the effect of wastewater application on it. For this, 200 surface soil (0-30 cm) samples were randomly collected and plant ...
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Boroujen–Fradonbeh plain is one of the nine main agricultural hubs of Charmahal Provine. The aim of this study was to define and map a deficiency index of soil micronutrients and the effect of wastewater application on it. For this, 200 surface soil (0-30 cm) samples were randomly collected and plant available concentrations of copper, zinc, iron, and manganese were determined. After variography and determining the most suitable spatial estimation method, maps of each micronutrient was drawn, normalized, and ranked. An integrated deficiency map was then constructed using the weights from rank maps. According to the maps of copper, zinc and iron, the available concentrations increased from west to east of the plain. This increase was attributed to the wastewater irrigation. The mean value of the integrated map, namely 85.5, indicated the seroius soil deficiency of micronutrients in this plain where 34% of the area was showing severe deficiency. Wastewater application has increased the overall availability of micronutrients by 4%. Sensivity analysis indicated that the map was most sensitive to zinc. Therefore, zinc concentration must be monitored with more precision and frequency across the plain.
M. Akbarzadeh; B. Ghahraman
Abstract
In geo-statistics, prediction of an unknown value of random field has been performed in specified time and position, using spatio-temporal Kriging. In some circumstances, a suitable covariate increase the estimation prediction. Geo-statistical methods of Universal Kriging (UK) and Kriging with External ...
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In geo-statistics, prediction of an unknown value of random field has been performed in specified time and position, using spatio-temporal Kriging. In some circumstances, a suitable covariate increase the estimation prediction. Geo-statistical methods of Universal Kriging (UK) and Kriging with External Trend (KwET) were applied to Mashhad plain water quality data sets. The optimal network to monitor groundwater quality was presented, using Entropy. All wells ranked based on the criterion of Entropy and mutual information. Then, the optimal network was determined based on the percentages of acquired information and relying on the spatio-temporal Kriging. Based on UK and KwET, electrical conductivity (EC) was the best covariate. KwET with EC as a covariate was the superior Kriging method. A network covering 111 wells showed to be as informative as the existing monitoring network with a total of 237 wells.
