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Urmia Lake is the largest lake in the country which during recent years faces a dramatic reduction in the water level. Many reasons such as climate change, continuous droughts, development of cultivation and land use changes as well as construction of dams were mentioned, but the provided reasons have less been well documented by scientific evidences. This study is an attempt to investigate the later problem with scientific point of view. In this regard, the effects land use changes on Ajichai river on Urmia Lake were investigated.In order to evaluate the land use change impacts, Landsat images of 1976, 1989, 2002 and 2008 years were considered as inputs to SWAT model and under the same input data, models were calibrated within the year of their application. All four models were run monthly for years from 1976 to 2008. Output results of four models indicated significant 51% output water volume reduction and increase actual evapotranspiration rate 13% during these years for the basin. Generally, Results from this paper showed that the land use change has effective role on reduction in the water level of the lake in three past decades.
The purpose of this study is evaluation and improvement of production functions to estimate Alfalfa yields under different deficit irrigations conditions and determination of “production of yield - water use” in Qazvin plain. This investigation was applied by Factorial experiment in a randomized complete block design with four water treatments including E4, E3, E2, and E1, respectively, equal to 60, 90,120 and 150 mm evaporation from class A evaporation pan as irrigation period, with three replications at the Agricultural Research Station Qazvin Esmaeelabad which run for three years. Since irrigation water applied in different years varied, treatments were separated from T1 to T12. So production functions based on evapotranspiration data for each treatment are reviewed. The result show that water requirement of Alfalfa in total of growth period is 1678 mm, T1 treatment had maximum yield with 16830 kg/ha and T12 treatment had minimum yield with 10020 kg/ha. And According to Statistical match, Tafteh et al. (2013) method that estimates amount of plant response factor based on defined power coefficient, which estimated at monthly intervals by rate response coefficients, had minimum of root mean square error (RMSE) and normal root mean square error (NRMSE). And it had maximum amount of agreement index and the correlation coefficient (r2).The amount of Plant yield response factors were determined in Ordibehesht, Khordad, Tir, Mordad, Shahrivar and Mehr respectively, equal to 0.85, 0.9, 0.99, 1.1, 1.1, 1 and for initial growth
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The most widespread method to determine temporal and spatial variations of LAI in a regional scale is empirical relationships based on the normalized difference of reflectance bands of satellite data. This study was done to evaluate the equations of remotely sensed LAI estimation and optimize their parameters. Therefore, LAI was measured in the field for summer growing season in irrigated fields in the Qazvin irrigation network. Remotely sensed LAI was estimated using the soil adjusted vegetation index (SAVI) that derived from the TERRA-MODIS images. Results of this paper showed that LAI estimating by reference equations for all crops have high value of the root mean square error (RMSE) (3- 4.7). Calibration of LAI according to SAVI was done to determine the best model constants. The modified version of the equation was obtained as the best LAI estimation equation with RMSE equal to 1.57 and coefficient of determination (R2) equal to 0.72.
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The aim of this study was to assess the conversion of forest to vineyard on different physical pools of organic matter in Zrebar Lake watershed. Soil samples were collected from the two major land use types including forest and vineyard land at 0-30; 30-60, and 60-90-cm depths. In each land use, different SOC fractions were measured. According to the results of size fractionation of organic carbon in 0-30-cm layer, the highest and lowest amount of sand sized fraction organic carbon was obtained in forest and vineyard land use; respectively. The amount of sand sized fraction SOC was decreased with depth. In the forest land the content of light fraction in each depths was more relative to vineyard. The light and sand sized fractions in surface layers were showed high response to management changes. Organic carbon storage in the surface layer has been more than other depths. It is proposed to apply special management in surface layers of soils to mitigate the loss of different SOC fractions.
This study aimed to evaluate the potential of image ratioing techniques to detect and map the extent and particle composition of sand dunes in the Erg of Gavkhouni in Isfahan province. The 6/4 ratio index and also a new index called SaDI which was calculated using Landsat band 3, 6 and 7 were applied to a georeferenced Landsat TM image. To evaluate the performance of ratio techniques, the extracted images were correlated with the percentage of different particles collected in 33 sampling sites. Results showed that both ratioing techniques were able to detect and map the spatial distribution of sand dunes and there was more than 70% agreement between image indices and field data. The results also indicated that the performance of SaDI was 50% better in mapping carbonate particles and this confirms that this index is more appropriate than 6/4 index for mapping sand dunes dominated by carbonate particles.
In the present study, five log-normal models, normal model (N), and two four- parameter models namely Gompertz (G) and Fredlund (Fr) were tested on 71 PSD data from 10 soil textural classes. The Jaky (J) and Fr models had the smallest and largest R2 values for all of the soils, respectively. The results of comparing the N and simple log-normal (SL) models showed that the accuracy of the N model increased with decrease soil clay content. In other words, the mass-size distribution of soil samples tends to a normal statistical pattern from the finer to the coarser textural classes. The result of F, Cp and AIC statistics showed that the Fr was the best model to describe PSD for majority of soils and the modified log-normal models namely ORL and ONL was the next in rank, respectively. The range of R2 values for the sandy and sandy loam soil texture classes indicated that the G, ONL, ORL, N and Fr models had a better fit on the data than the SL and Shiozawa-Campbell (SC) models. However, the performance of the SL and SC models improved compare to G and N models in clay and silty clay soil texture classes.
This study was done with the aim of investigating the kinetics of available phosphorus changes in treated soils with municipal solid waste compost, fertilizer and the mixture of these in two levels of first and second percent in eight calcareous soil samples and in a period of zero to 3600 hours in incubation conditions (FC moisture and 250c). The results showed that with time increasing, extractable phosphorus amount by Olsen decreased and increased in fertilizer and municipal solid waste compost treatment respectively in both level of one and two percent. Six mathematical equations (simplified Elovich, power function, parabolic diffusion, zero-order, first-order and second-order) were used to describe kinetics of conversion of available to unavailable phosphorus. The comparison of models showed that with the respect of coefficient of determination and standard error of the estimate, second order equation is the best equation to describe kinetics of extractable phosphorus changes in the all treatments. Also results showed that with increasing calcium carbonate equivalent, the conversion speed of available to unavailable phosphorus in fertilizer treatment and unavailable to available phosphorus in municipal solid waste compost treatment was increased significantly
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