Showing 4 results for SH. Ayoubi
Sh. Ayoubi, M. H. Alizadeh,
Volume 10, Issue 3 (fall 2006)
Abstract
Overgrazing is the most important agent which causes accelerated soil erosion and land degradation in arid and semi-arid zones of Iran. Appropriate planning and land use in these areas based on land suitability evaluation provide a suitable base for conserving the land and controling desertification. Land evaluation identifies possible alternatives in land use which will more effectively meet national or local needs and assists in assessing the consequences of these alternatives. Extensive grazing refers to the land utilization type in which animals feed in natural pastures. This study was performed to evaluate physical potential of the given watershed for grazing by sheep and goats, and assess the limiting factors for the land utilization type in Mehr watershed, Sabzevar, Khorasan province. Land qualities which were evaluated include accessibility to animals, soil erodibility, moisture availability, rooting conditions, salinity and alkalinity, and drinking water availability for animals. Above mentioned land qualities were assessed by appropriate land characteristics. The requirement of grazing land utilization type was defined in terms of rated land characteristics. Matching of requirements of LUT with the land qualities of each pixel of DEM (prepared in 200×200m by GIS software) resulted in a rating for every land characteristics. Some characteristics such as slope, aspect, and distance to drinking water for animals were calculated directly by GIS. Land index for every pixel was calculated by square root method. Finally, qualitative and physical land suitability classes were determined based on land indices and classified to polygons which would be suitable in grazing management. The results were interpreted under two different scenarios. In the first scenario, drinking water for animals was supplied by permanent sources and in the second one, the supplying of water was developed to temporary rivers besides the permanent sources. With the analysis of spatial modeling it was possible to assess the land suitability with higher accuracy. Overall results showed that the given area was not highly suitable for grazing at all. The most limiting factors included moisture availability for plant growth, slope, rock fragment and outcrops and distance to drinking water. Also during the late winter, spring and early summer, when the seasonal rivers were supplying the drinking water, the limitation of given area was decreased.
A. Jalalian, J. Givi, M. Bazgir, Sh. Ayoubi,
Volume 10, Issue 4 (winter 2007)
Abstract
In Iran, the development of cultivated areas becomes gradually impossible due to ever-increasing population growth and urban area development. Therefore, it is very important to use the existing cultivated lands more efficiently. Land suitability evaluation makes the sustainable use of the lands feasible. The objective of this study was qualitative, quantitative and economic assessment of land suitability in Talandahst area for rainfed wheat, barley and chickpea. Talandasht plain with a surface area of 4500 ha is located southwest of Kermanshah city. The climate is semi-arid with cold winter and moderate summer. The successive stages of this research included soil survey in the field, soil analysis, qualitative and quantitative and economic evaluations of land suitability. In qualitative evaluation of land, climatic, topographic and soil suitability classes were determined according to the degree of the matching. Limitation and parametric methods were used in qualitative evaluation. Quantitative and economic evaluations made based on the observed yield and gross benefit, respectively. Based on qualitative evaluation, the studied area is marginally suitable for rainfed farming of wheat, barley and chickpea. This is due to water deficiency occurring during some stages of the growing cycle. The solution for this problem is supplementary irrigation. In addition to climate limitation, there are also topographic and soil restriction for the growth of the studied crops. On the basis of observed yield, the land units are moderately to highly suitable for rainfed wheat and barley production. Among the three named crops, the most and least profitable ones are chickpea and barley, respectively, and wheat ranks between them.
S. Mohammad Zamani, Sh. Ayoubi, F. Khormali,
Volume 11, Issue 40 (summer 2007)
Abstract
Evaluating agricultural land management practices requires a thorough knowledge of soil spatial variability and understanding their relationships. This study was conducted at a traditionally operated wheat field in Sorkhankalateh district, located about 25 km northeast of Gorgan, in Golestan province, Iran. Soil samples of the 0-30 cm depth were collected right after planting at the end of autumn 2004 , 100 × 180m plot in a nested grid pattern (n=101). A 1 m2 plot of wheat was harvested at each of 101 sites previously sampled at the end of spring. Statistical results showed that frequency distribution of all data was normal. The highest and lowest CV was related to grain yield (20.40%) and pH (0.59%) respectively. Variogram analysis showed that all parameters had spatial structure and the range values showed considerable variability among the measured parameters. The ranges of spatial dependence showed a variation from 23.99m for total N up to 93.92m for K. Among the parameters, total N and ESP had stronger spatial dependence while P had the lower spatial dependence. Interpolated maps of Kriging demonstrated that crop and soil properties did not have a random pattern but had a spatial distribution. The spatial distribution of total N was similar to organic matter and also there was similarity between spatial distribution of harvest index and available P. The results demonstrated that, the spatial distribution and spatial dependence level of soil properties can be different even within similarly managed farms. Variography and Kriging can be useful tools for designing soil sampling strategies, characterizing management zones and variable application rates of inputs in the precision agriculture.
A. Jafari, H. Khademi, Sh. Ayoubi,
Volume 16, Issue 62 (Winte - 2013 2013)
Abstract
Digital soil mapping includes soils, spatial prediction and their properties based on the relationship with covariates. This study was designed for digital soil mapping using binary logistic regression and boosted regression tree in Zarand region of Kerman. A stratified sampling scheme was adopted for the 90,000 ha area based on which, 123 soil profiles were described. In both approaches, the occurrence of relevant diagnostic horizons was first mapped, and subsequently, various maps were combined for a pixel-wise classification by combining the presence or absence of diagnostic horizons. Covariates included a geomorphology map, terrain attributes and remote sensing indices. Among the predictors, geomorphology map was identified as an important tool for digital soil mapping approaches as it helped increase the prediction accuracy. After geomorphic surfaces, the terrain attributes were identified as the most effective auxiliary parameters in predicting the diagnostic horizons. The methods predicted high probability of salic horizon in playa landform, gypsic horizon in gypsiferous hills and calcic horizon in alluvial fans. Both models predicted Calcigypsids with very low reliability and accuracy, while prediction of Haplosalids and Haplogypsids was carried out with high accuracy.
