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Showing 2 results for Behmanesh
Comparison of Rangeland Vegetation Cover and Soil Properties Variations Affected by Flood Spreading, Enclosure and Grazing Uses
F. Jalilian, B. Behmanesh, M. Mohammad Esmaeili, P. Gholami,
Volume 21, Issue 2 (Summer 2017)
Abstract

In this study, different indices of vegetation cover variations and different physicochemical properties of soil in three treatments of flood spreading, enclosure and grazing (control) were investigated and compared in in the region of Peshert in Mazandaran province. In order to measure different soil characteristics, 18 soil samples (six withdrawals at any treatment) from a depth of zero to 30 cm were taken from the desired treatments. In order to investigate different vegetation indices, a total of 90 plots (nine transects of 100 m) were run using systematic random sampling in the studied treatments and the necessary measurements were done (30 plots at any treatment). Then, in each of these plots, canopy coverage percentage was determined separately for each species and to evaluate and assess the diversity and richness in all three treatments, Shannon-Wiener and Simpson diversity indices and Menhink and Margalef richness indices were used. Finally, the data obtained from both sections of soil and vegetation in three studied treatments were compared and analyzed using one-way ANOVA and Duncan test. The results showed that floodwater spreading and enclosure significantly increased the percentage of sand and total Nitrogen, and significantly reduced the percentage of silt and potassium compared to control treatment. Also, percentage of clay and organic matter, soil pH levels, conductivity and soil phosphorus showed no significant differences in the treatments under study. The results of variance analysis of various indices of diversity, richness and species evenness showed that all indicators had significant responses in three treatments and the highest diversity and species richness were observed in flood spreading and enclosure treatments. Due to changes in soil properties and vegetation in flood spreading and enclosure treatments compared to the control treatment, it can be stated that operations of floodwater spreading and enclosure in the studied region has had positive effect on modification of soil texture, increasing the permeability of the soil and ultimately improvement of the vegetation.


Simulation of Spatiotemporal Annual Precipitation Using Stochastic Models
H. Faghih, J. Behmanesh, K. Khalili,
Volume 22, Issue 1 (Spring 2018)
Abstract
Precipitation is one of the most important components of water balance in any region and the development of efficient models for estimating its spatiotemporal distribution is of considerable importance. The goal of the present research was to investigate the efficiency of the first order multiple-site auto regressive model in the estimation of spatiotemporal precipitation in Kurdistan, Iran. For this purpose, synoptic stations which had long time data were selected. To determine the model parameters, data covering 21 years r (1992-2012) were employed. These parameters were obtained by computing the lag zero and lag one correlation between the annual precipitation time series of stations. In this method, the region precipitation in a year (t) was estimated based on its precipitation in the previous year (t-1). To evaluate the model, annual precipitation in the studied area was estimated using the developed model for the years 2013 and 2014; then, the obtained data were compared with the observed data. The results showed that the used model had a suitable accuracy in estimating the annual precipitation in the studied area. The  percentages of the model in estimating the region's  annual precipitation for the years 2013 and 2014 was obtained to be 7.9% and 17.3%, respectively. Also, the correlation coefficient between the estimated and observed data was significant at the significance level of one percent (R=0.978). Furthermore, the model performance was suitable in terms of data generation; so the statistical properties of the generated and historical data were similar and their difference was not significant. Therefore, due to the suitable efficiency of the model in estimating and generating the annual precipitation, its application could be recommended to help the better management of water resources in the studied region.

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