Showing 9 results for Cn
S. A. Maybodi, A. R. Amini Hajiabadi, J. Khajeddin,
Volume 6, Issue 2 (7-2002)
Abstract
A number of halophytic species as Salicornia europea, Halocnemum strobilaceum, Aeluropus lagopoides, and Aeluropus littoralis were found to occupy a significant portion of the total vegetation of the surrounding area at the Zayande-Roud inlet to Gavkhoony wetland. However, their ecological demands and bioenvironmental factors by which vegetation community composition has been affected is not undestood. A compehensive knowledge of the establishment is essential for future improvements in using the above species on salanized regions. In this paper, using the ordination method. The establishment pattern of these four species in a range of varied habitats is evaluated based on the recongition of the relative significance of habitat soil chemical properties and vegetion crown cover to the establishment of the four species. For this purpose, 48 plants meansurements were taken along a transect, having more species variation in term of vegetation cover percentage. Furthermore, 48 soil samples were taken from the plot along the same transect in a one-year period in 1999. The soil samples were analysed for PH, EC, available Na, K, Ca and Mg as well as clay, and silt contents. The ground and field vegetation data were analysed using the Principlas Components Analysis (PCA), and Canonical Correspondence Analysis (CCA) to produce summary vectors (PCA axes) of both the soil chemistry and habitat vegetation structure datasets. The summary of ordination method quantified the degree to which soil variables and species cover were related to variability in ground vegetation composition. variation in community composition (type and percentage) was significantly related to gradient of the aforementioned soil factors. Generally, the vegatation community composition in this experiment could be considered as a key component to expand the growth and development patterns of these species to similar salinised regions.
A. A. Vali,
Volume 10, Issue 1 (4-2006)
Abstract
Saline soils and halophytic vegetations are common features and part of the habitat pattern in deserts and steppes. The saline area is developing in arid lands. Investigation effects of halophytes on soil characteristics and adaptive mechanisms of the various halophyte types is essential for controlling saline environments. Juncus gerardi is a perennial grass-like halophyte and Halocnemum strobilaceum is a succulent halophyte shrub. The distribution of these species is mound like in the field. The soil samples of the mounds for investigating the effect of these species on plant root environment were compared with near regions in Korsiah saline area in Darab. Also the consentration some ions of live and dead organs and tissues of these species were studied for recognition of their adapive types. The results show that Juncus gerardi decrease salinity in 0-30 cm of topsoil, therefore the Ec decreased 37%. But salinity increased significantly in 30-60 cm depth. The identification of ions in plant tissues showed that the concentration of ions is low in dry matter. This is 0.33% of dry matter for Sodium. This is a way to rescue from dry conditions by selective absorption of ions. The comparison of root environment of Halocnemum strobilaceum with near regions showed a significant decrease in salinity in 0-30 cm and 30-60 cm depth decreased 27% and 40% respectively. The identification of ions concentrations in plant tissues reflect the high amounts of ions, therefore the plant tissues composed of 8.18% of Sodium. The comparision of ion concentrations in different live and dead tissues of plants a Significant increase of the amounts of ion in the dead tissues in comparison with the live tissues. Therefore this species excrete much quality of salts in their dead tissues and organs and so combat this problem.
S. Rajaee, H. A. Alikhani, F. Raiesi,
Volume 11, Issue 41 (10-2007)
Abstract
Azotobacter chroococcum is an important PGPR (Plant Growth Promoting Rhizobacteria) producing compounds needed for plant growth. The aim of this research was to study the effects of different native strains of Azotobacter chroococcum on growth and yield of wheat under greenhouse counditions. Seeds of spring wheat (Triticum aestivum L. var. Pishtaz) were inoculated with some Azotobacter chroococcum strains capable of producing IAA, HCN, sidrophore and fixing molecular nitrogen. The inoculation of wheat with those strains had a positive, significant effect on biological yield, seed protein percentage, thousand seed weight, leaf area, N, P, Fe and Zn uptake, in particular, by wheat. The increased growth of wheat was most likely due to the production of IAA and enhanced nitrogen fixation by inoculated strains. Some strains of Azotobacter chroococcum native to Chaharmahal va Bakhtiari are established as PGPR. Results also support the efficiency of Azotobacter chroococcum as an important biofertilizer in wheat cropping systems. The selected strains had a significant effect on wheat growth and yield, including biological yield and seed quality under greenhouse counditions. This beneficial effect of Azotobacter chroococcum on wheat is attributed mainly to IAA production and, to some extent to non symbiotic nitrogen fixation in the rhizosphere. So, these strains can potentially be used to improve wheat nutrition of micronutrients such as Fe and Zn, in particular.
M. Najafi-Ghiri, A. R. Mahmoodi, S. Askari,
Volume 19, Issue 72 (8-2015)
Abstract
Potassium (K) is an important cation in saline soils of arid lands, and its content, distribution and availability may be affected by native plants. To study the effect of halophyte species on different K forms in Korsia region located in western Darab (Fars province), three dominant halophyte species including Juncus gerardi, Halocnemum strobilaceum, and Salsola rigida were selected. Sampling was done from soils in canopy and between plants at the depth of 0-15 (surface) and 15-30 cm (subsurface) in triplicate. Soil physical and chemical properties including soil texture, organic matter, calcium carbonate, pH, cation exchange capacity, saturation percentage and electrical conductivity and different K forms including soluble, exchangeable and non-exchangeable were determined. Results indicated that organic matter, CEC, pH, and EC were affected by plant species. Juncus gerardi increased exchangeable K and decreased soluble K, but it had no effect on non-exchangeable and HNO3-extractable K. Halocnemum strobilaceum significantly increased soluble, exchangeable and HNO3-extractable K in surface and subsurface soils rather than soils between plants. This finding may be due to K uptake by plants from subsoils and also transfer of soluble K from soils between plants to roots. Salsola rigida had no effect on K status. Generally, soils between plants had more soluble and exchangeable K in surface than subsurface horizon. The studied halophyte species showed differences in growth and development pattern, soluble salts and K absorption and secretion, grazing by livestock, returned organic matter to soil, soluble salts and K reserves in their organs, and water uptake and thereby water and K diffusion from soil far from rhizosphere to roots, which may have different effects on K distribution in soils. Juncus gerardi, as regards effects on decreasing salinity and soluble K and increasing exchangeable K, may be recommended as a suitable species for remediation of the studied soils.
R. Mostafazadeh, Sh. Mirzaei, P. Nadiri,
Volume 21, Issue 4 (2-2018)
Abstract
The SCS-CN developed by the USDA Soil Conservation Service is a widely used technique for estimation of direct runoff from rainfall events. The watershed CN represents the hydrological response of watershed as an indicator of watershed potential runoff generation. The aim of this research is determining the CN from recorded rainfall-runoff events in different seasons and analyzing its relationship with rainfall components in the Jafarabad Watershed, Golestan Province. The CN values of 43 simultaneous storm events were determined using SCS-CN model and the available storm events of each season have been separated and the significant differences of CN values were analyzed using ANOVA method. The Triple Diagram Models provided by Surfer software were used to analyze the relationships of CNs and rainfall components. Results showed that the mean values of CN were 60 for summer and winter seasons and the CN values in the spring and autumn seasons were 50 and 65, respectively. The inter-relationships of CN amounts and rainfall characteristic showed that the high values of CNs were related to high rainfall intensities (>10 mm/hr) and rain-storms with total rainfall more than 40 mm. Also the CN values were about >70 for the storm events with 40-80% runoff coefficient values.
F. Jahanbakhshi, M. R. Ekhtesasi,
Volume 22, Issue 4 (3-2019)
Abstract
Land use/cover maps are the basic inputs for most of the environmental simulation models; hence, the accuracy of the maps derived from the classification of the satellite images reduces the uncertainty in modeling. The aim of this study was to assess the accuracy of the maps produced by machine learning based on classification methods (Random Forest and Support Vector Machine) and to compare them with a common classification method (Maximum Likelihood). For this purpose, the image of the OLI sensor of Landsat 8 for the study area (Sattarkhan Dam’s basin in the Eastern Azerbaijan) was used after the initial corrections. Five land uses including urban, irrigated and rain-fed agriculture, range and water body were considered. For conducting the supervised classification, ground truth data were used in two sets of educational (70% of the total) and test (30%) data.
Accuracy indexes were used and the McNemar test was employed to show the significant statistical difference between the performances of the methods. The results indicates that the overall accuracy of Support Vector Machine, Random Forest, and Maximum Likelihood methods was 96.6, 90.8, and 90.8 %, respectively; also the Kappa coefficient for these methods was 0.93, 0.81 and 0.83, respectively. The
existence of a significant statistical difference at the 95% confidence between the performances of the Support Vector Machine algorithm and the other two algorithms was confirmed by the McNemar test.
Sh. Mohammadi, E. Karimian,
Volume 23, Issue 4 (12-2019)
Abstract
Nowadays, water supply for the sectors of household consumption, agriculture, green spaces and industry is currently one of the most important challenges for governments in many parts of the world, especially in arid and semi-arid climate regions such as Iran. The aim of this study was to simulate the amount of run-off from the daily precipitation for Sarpol-e Zahab city, for the purpose of estimating the required amount of water for the irrigation of the green spaces of the city. In this study. After providing information and using the Digital Elevation Model (DEM) map of city, all individual sub-basins of the basin were produced. All data related to creating and overlaying hydrologic, climatologic and physiographic layers were used according to the HEC-HMS hydrologic model. The run-off depth and flood volume of each sub-basin were obtained through the SCS method. Then the required amount of water for the green areas of Sarpol-e Zahab city was calculated. The efficient rainfall was estimated using four methods including SCS, 80 percentage, reliability, and USDA for each month, separately. Finally, the amount of needed water for the green area was obtained using these four mentioned methods. The results indicated that the role of curve number in the infiltration rate was more than other variants. Impermeability of urban basins and changes was created due to the growth and development of the city such as removal of vegetation, soil compaction, creation of the water collection and leading surface waters, decreasing the amount of water penetrating to soil significantly. The amount of surface water for sub-basins was estimated to be 266000 cubic meters. Besides, the results showed the amount of required water for 5 months of the year (from early May to September late) using four methods of SCS, 80percentage, reliability and USDA was equal to 243525, 238062, 267865 and 236458 cubic meters, respectively. The amount of the estimated runoff volume was 266,000 cubic meters. Regarding the area of green spaces in Sarpol-e Zahab city and its daily need of water, this volume of water could supply the required amount of water to irrigate the green area of the city for five months (From May to September).
A. Malekian1, A.a. Jafarazdeh, Sh. Oustan, M. Servati,
Volume 26, Issue 2 (9-2022)
Abstract
To study the soil-landscape change in the Chaldoran region, 9 representative soil profiles were studied in 5 dominant geomorphic units of the study area including piedmont plain, mantled pediment, alluvial fan, plain, and flood plain. The results showed that the accumulation of pedogenic carbonate in some soils was concretion and light in color. In control soils in the piedmont plain (profile 5 and 7), mantled pediment (profile 6), and flood plain (profile 8) clay transferred from the surface horizons and accumulated in the lower horizon, due to relatively good rainfall in the region and distinct dry and wet seasons has led to the formation of argillic horizons along with the formation of crust on the surfaces of aggregates and building units and has formed the Alfisoils order. Mineralogical results showed the presence of chlorite, illite, kaolinite, and smectite minerals. According to the evidence, illite, chlorite, and kaolinite minerals were inherited and smectite minerals were formed due to weathering and evolution of illite, chlorite, or palygorskite minerals. Also, the results of the CIA index in the region indicated that the soils of the region are in the stage of weak to moderate weathering. In general, the results indicated the critical role of drainage, land use, and parent materials in the soils of the study area.
T. Tahmasbi, Kh. Abdollahi, M. Pajouhesh,
Volume 26, Issue 2 (9-2022)
Abstract
The runoff curve number method is widely used to predict runoff and exists in many popular software packs for modeling. The curve number is an empirical parameter important but depends largely on the characteristics of soil hydrologic groups. Therefore, efforts to reduce this effect and extract more accurate soil information are necessary. The present study was conducted to integrate fuzzy logic for extraction runoff curve numbers. A new distribution model called CNS2 has been developed. In the first part of this research, the formulation and programming of the CNS2 model were done using the Python programming language environment, then the model was implemented in the Beheshtabad watershed. This model simulates the amount of runoff production in a watershed in the monthly time step with the fuzzy curve number and takes into account the factor of rainy days, the coefficient of management of the RUSLE-3D equation, and the soils theta coefficient. The results indicated that the model with Nash-Sutcliff 0.6 and the R2 coefficient 0.63 in the calibration set and Nash index 0.53 and R2 coefficient 0.56 in the validation set had appropriate efficiency in runoff simulation. The advantage of the model is that distributive and allows for the identification of areas with higher runoff production.
