نشریه آب و خاک
سال بیست و چهارم شماره 3 (پیاپی 11، امرداد - شهریور 1389)

Osmoreguolation is a physiological processes that plant cell uses to maintain water balance and it is generally caused by metabolite accumulation inside the cell. Inoculated legumes by some drought tolerant Sinorhizobium isolates helps osmoreguolation by increasing biological nitrogen fixation. In order to find some drought tolerant sinorhizobium isolates, 80 isolates were isolated and purified from different parts of Kerman province. They were tested for drought tolerant in liquid Trypton Yeast medium with different water potential (0, -1, -2 and -3.5 MPa using PEG 6000) and then they were classified into tolerant and sensitive groups. Four out of eighty isolates of Sinorhizobium (two from each group) were selected for a greenhouse experiment. The experiment was carried out in a factorial arrangement with a completely randomized design. The results showed that in water stress condition, inoculated plant substantially increased the nitrogenase activity, shoot dry weight, proline content, root soluble sugars, soluble protein concentration, K/Na in shoot and root by 2, 3, 2.7, 1.7, 1.1, 3 and 2 times, respectively.

AbstractPrecipitation is an important variable which is used in definition of drought. Based on precipitation amounts, some indices are devised for drought monitoring including, the Standardized Precipitation Index (SPI) and the Standard Index of Annual Precipitation (SIAP). Each of these Drought indices are classified into some classes so that each class descripts a given severity of drought. Investigation of simultaneously occurrence situation for two drought indices can be an appropriate measure to evaluate the agreement of indices. Association Rules in DATA MINING is used to find rules and patterns in database. In this paper, two drought indices, SPI and SIAP, were computed at 11 meteorological stations belong to Ministry of Energy in Kermanshah province. Then, based on Association Rules, simultaneously occurrence situation of drought severity classes for both indices were determined in seasonally, half yearly and yearly time scales. Results showed that there is not any good agreement between most of drought category from these indices (less than 50 percent) and Shows different behavior of drought.

AbstractA previous study on agricultural drains in Khuzestan province of Iran has indicated that carbonate calcium is the main component of the deposited salts in drainage envelops. To investigate the process of precipitation of carbonate calcium under different conditions including chemical, bio-chemical, aerobic and an-aerobic, a through laboratory investigation on geotextile drain envelop was conducted. The results of the studies showed that activity of the micro-organisms in aerobic conditions causes an increase in the bicarbonate content and consequently, increase in the pH of the medium. Any increase in pH would intensify the precipitation of carbonate calcium. The results also indicated that due to the activity of micro-organisms, more than 90% of existing calcium would be precipitated. While in a chemical environment, only 30% of existing calcium would precipitate. Thus, in a biochemical environment, micro-organisms would cause more calcium to be deposited. The results also indicated that the activity of the bacteria would cause formation of bio-films which in turn would provide a more suitable environment for precipitation of salts. By intensifying deposition of salts, there is higher potential for clogging of the drainage envelops including geotextile filters.

Abstract Microbial contaminants transport to groundwater is a serious environmental problem that can result in large outbreaks of waterborne diseases. Some of bacteria can travel from vadose zone and cause contamination of groundwater resources. Thus, an accurate prediction of transport and fate of pathogenic microorganisms in unsaturated soil is needed to protect groundwater resources. The main objectives of this research were quantitative study of bacterial transport and deposition under unsaturated conditions in calcareous soils. A series of column leaching experiment with well-controlled suction and flow rate was conducted. Breakthrough curves (BTCs) of Pseudomonas fluorescens and Cl were measured. After the leaching experiment the bacteria was measured in difference layers of the soil columns. The HYDRUS-1D kinetic attachment-detachment model (AD) was used to evaluate the transport and deposition of bacteria in soil columns. The breakthrough curves in soils were described well by attachment-detachment model. Whereas the model fit underestimate the amount of bacteria retention in the soil columns. The detachment rate was less than 0.001 of the attachment rate, indicating irreversible attachment of bacteria. Most of the cells were retained close to the soil column inlet, and the rate of deposition decreased with depth. Microbial reduction rate for the soil was 10.18-13.34 log m-1. High reduction rate of bacteria was attributed to soil calcium carbonate that has favorable attachment site for bacteria.

AbstractSiderophores are of important factors influencing bioavailability and fate of heavy metals in the arid and semi-arid soils. They are low molecular weight organic ligands excreted by aerobic soil microorganisms and some plants roots to acquire Fe. Siderophores may also complex other metals such as Pb. The main objective of this study was to investigate the effects of DFOB-siderophore on sorption of Pb on montmorillonite. The sorption of Pb on montmorillonite was studied as a function of pH (sorption envelopes) and as a function of Pb concentration (sorption isotherms) in the presence of siderophore using a 24–h batch equilibration experiment. The results of sorption envelopes showed that the siderophore increased sorption of Pb onto montmorillonite in all solution pH, specially at pH ≥5. The results of equilibrium test (isotherms) revealed that removal of Pb from solution was not affected by siderophore at pH=4.5, while the siderophore strongly influenced the isotherm shape and increased Pb sorption onto montmorillonite at pH=6.5. The equilibrium data is best described by a Freundlich isotherm, in which the values obtained for the KF constant were 4.8 and 196.5 and for n constant were 0.8 and 2.1 in the absence and presence of the siderophore, respectively. These values are indication of high sorption affinity of Pb on montmorillonite in the presence of the siderophore.

AbstractIn this study, seven main field crops of the Rudasht and Abshar Irrigation Networks of Esfahan (with 54,000 ha designed command area) such as Wheat, Barley, Onion, Sunflower, Fodder Mays and Sugar beet were selected and SWAP model was calibrated by inverse modeling base on field experiments results in order to determine crop water salinity production functions. Field experiments were conducted with effect of saline water with different irrigation managements on crop yield at Research Station of Drainage and Soil Reclamation of Rudasht during 1996 to 1998 and 2005 to 2007. In terms of insufficient field treatments and in order to fit proper crop yield production function, SWAP calibrated model was run for different quantity and quality levels of irrigation water. Quadratic form of crop yield production function was calculated for 6 salinity levels of irrigation water include 1, 2, 4, 6, 8 and 10 dS/m and each crop. Optimal irrigation depth in different condition include scarcity of water quantity, land quantity and water quantity and quality was calculated base on crop yield production function, cost production function and marketable price of each crop based on 2008 with respect to maximize net benefit. Results of analysis showed that in scarcity of water quantity for 10000 m3 available water, maximum net benefit gain onion cultivation with 52.6×106 Rials beside with 1.16 ha of area cultivation. In land scarcity condition for specified available water, maximum net benefit gain onion cultivation, too. In scarcity of water quantity and quality condition, with increasing salinity of irrigation water, for 10000 m3 available water salinity level of irrigation water equal 2 dS/m, maximum net benefit gain onion cultivation with 35.11×106 Rials beside with 1.44 ha of area cultivation, too. In salinity level equal 6 dS/m, maximum net benefit gain wheat cultivation with 18.37×106 Rials and next maximum net benefit barely cultivation with 13.9×106 Rials. Yield of Onion and Fodder Maize decreased severely so that for higher than salinity level of irrigation water equal 6 dS/m, net benefit was negative. In salinity level equal 10 dS/m, maximum net benefit gain barely and next sugar beet cultivation.

AbstractDespite the significance of climate change assessment on regional planning of a basin, most of the previous researches have been focused on the point assessment of this phenomenon. This paper uses statistical tests as well as regional assessment to investigate the impact of climate change on the Gorganroud-Gharehsou basin. In this regard, various tests including Man-Kendall, Cumulating Deviation, and Worsley’s Liklyhood Ratio Test have been applied to recognize the homogeneity and probable trend of seasonal and annual rainfall as well as max and min temperature data in the period of 1977 through 2006. Then, the results were generalized over the basin to result in the regions affected by the climate change impact. The results show that first: Non-homogen time series (sig.99%) have been trends (sig.95%). Second: an increasing trend in Autumn and Anuual rainfall in the north-east of the basin (sig.90%). Furthermore, the climate change is demonstrated in the basin by increasing the minimum and maximum temperature during the summer and winter seasons (sig.95%).

AbstractLand use change, especially natural ecosystems transformation, has high effects on soil physico-chemical as well as biological characteristics and also, has effect on runoff and soil erosion. Analysis of runoff and soil erosion dynamics can be useful in improvement of management proposals and quantifying runoff and soil erosion changes. So, this research was carried out to investigate runoff and soil erosion in forest soils and to compare its results with dry farming and garden soils, which resulted from forest land use change. Also, effective quantitative soil parameters on runoff and soil erosion processes have recognized. For doing this, runoff and soil erosion were measured using simulated rainfall with 2 mm/min intensity and 15 min duration and soil samples were gathered in 15 replicates. Results showed that runoff was highest in native forest while the lowest was from garden land. Sediment yield was increased by 1.76 and 1.36 in conversion from forest to farming and garden land, respectively. Based on the results obtained from the correlation matrix, silt fraction, bulk density and antecedent soil moisture showed positive correlation with runoff and organic matter showed negative correlation with runoff. Also organic matter, clay and sand fraction reveal negative correlation with soil erosion, while antecedent soil moisture and silt fraction reveal positive correlation with erosion.

Abstract Information on spatial and temporal variations of soil hydraulic conductivity (k) is essential to improve soil and water management. However several techniques have been proposed for measuring of soil hydraulic conductivity above water surface table, but reliability and easy use of these methods in various conditions were always concern for engineers. The purposes of this study are measuring of the soli hydraulic conductivity by Guelph permeameter as a reliable method and determination of the best single-depth analysis method equivalent to two- depth method. To achieve this goal, 40 boreholes with depth of 60 cm were drilled in a grid of m in the research farm of agricultural faculty, Razi University, Kermanshah. Soil texture of the study area is silty-loam. After identification tests such as soil gradation, determination of the soil liquid and plasticity limits and determination of the specific gravity, soil saturated hydraulic conductivity and matric potential were measured by Guelph permeameter for three fixed ponding depths 5, 15 and 25 cm. Because of heterogeneous of equations in three-depth method only 17 success well obtained while in two-depth method for two ponding depths 5 and 15 cm, 26 successful well obtained. Data of these 26 boreholes were used for statistical analysis. The results of statistical analysis showed that: 1) Mean of soil hydraulic conductivity in the study area is, 2) Among the single depth methods, Richards regression basic analysis with values of 0.205 and 0.994 for and respectively is the nearest method to tow-depth method, 3) There is a significant difference at 5% level between the results from two-depths analysis of Guelph permeameter with Richards and Laplace single-depth methods, 4) Average values of and in the study area were calculated and respectively, and 5) Values of have less variation coefficients and standard deviation than values of sorptive number ().

AbstractInfiltration process is one of the most important components of the hydrological cycle. On the other hand, the direct measurement of infiltration process is laborious, time consuming and expensive. In this study, the possibility of predicting cumulative infiltration in specific time intervals, using readily available soil data and Artificial Neural Networks (ANNs) was investigated. For this purpose, 210 double ring infiltration data were collected from different regions of Iran. Basic soil properties of the two upper pedogenic layers including initial water content, bulk density, particle-size distributions, organic carbon, gravel content (>2mm size), CaCO3 percent and soil water contents at field capacity and permanent wilting point were determined on each soil sample. The feedforward multilayer perceptron was used for predicting the cumulative infiltration at times 5, 10, 15, 20, 30, 45, 60, 90, 120, 150, 180, 210, 240, 270 minutes after the start of the infiltration test and the time of basic infiltration rate. The developed ANNs were categorized into two groups; type 1 and type 2 ANNs. For developing type 1 ANNs, the basic soil properties of the first upper soil horizon were used as inputs, hierarchically. In developing the type 2 ANNs, the available soil properties of the two upper soil horizons were used as inputs, using principal component analysis technique. Results of Reliability test for developed ANNs indicated that type 1 ANNs with a RMSE of 1.136 to 9.312 cm had the best performance in estimating the cumulative infiltration. Also, type 1 ANNs with the mean RMSD of 6.307 cm had the best performance in estimating the cumulative infiltration curve.

AbstractThe limitation of water sources in most places all over the world, especially in arid and semi-arid lands is an important Issue for those who live in these areas. Many governments have dedicated their efforts toward finding new water resources to obtain water. Fog and cap clouds harvesting are one of the candidate methods to produce pure water. Many countries including Chile, Peru, Ecuador, Canada, Namibia and Nepal Have yet invested on fog harvesting. On the other hand, no significant calculation studies have been yet carried out on quantifying fog harvesting. In this work, we examined the Physical and dynamic relationship between cloud physics and atmosphere humidity; factors such as distribution of particle amounts, collection efficiency, water including base cloud and vapour flux were all considered. We also presented a new method to estimate fog harvesting, based on fractal theory and concerning the characteristics of collecting devices. Finally, we successfully evaluated the theories for fractal dimension of particle distribution, using the real data of fog harvesting. The incremental fractal dimension reliability was found to be 83% acceptable.

AbstractVarious mathematical water uptake models have been introduced for plants response to combined drought and salinity stress. The reduction functions are classified as additive, multiplicative and conceptual models. In this study six different macroscopic reduction functions, namely; Van Genuchten (additive and multiplicative), Dirksen et al., Van Dam et al, Skaggs et al and Homaee were evaluated. The experiment was carried out at Research farm of Birjand University in a factorial split plot design with 3 replicates. The treatments consisted of four levels of irrigation (50, 75, 100 and 120%of crop water requirement), and three water qualities (1.4, 4.5, 9.6 dS/m) and two wheat cultivars. The results indicated that the additive model estimates relative yield less than the actual amount. In other word, the effect of combined stresses on wheat yield was less than the summation of separate effects due to salinity and water stress. The effect of drought stress on yield reduction was more than salinity stress. The results also revealed that reduction function of Skaggs et al and Homaee's models agreed well with the measured data when compared with other functions.

AbstractThe association between Neotyphodium spp. endophytes and cool-season grasses, particularly tall fescue (Festuca arundinacea, Schreb), represents a widespread type of mutualism in nature. Numerous researches were performed about positive effect of symbiosis on plant resistance to different stresses but the role of symbiosis on nutrients uptake particularly potassium uptake and K-bearing mineral transformation is not well recognized. The objective of this research was to investigate the effect of endophyte-tall fescue symbiosis on the transformation of clay-sized micaceous minerals. A pot experiment under green house conditions was carried out in a completely randomized design with factorial combinations and three replicates. The culture medium was a mixture of quartz sand (as filling material) and phlogopite or muscovite. Tall fescue 75B genotype either infected by the natural endophyte Neotyphodium or non-infected isoline was chosen for cultivation. Pots were irrigated with distilled water and complete or K-free nutrient solutions during a period of 140 days. At the end of the experiment, shoots and roots were harvested. Plant samples were prepared with dry ashing method and their K concentration was determined with flame photometer. The clay-sized particles in each pot were mineralogically studied using an X-ray diffractometer. The results showed the vermiculitization of phlogopite under both nutrient solutions conditions, but with a much higher rate in pots treated with K-free nutrient solution. In addition to vermiculite, smectite and chlorite were also detected as newly formed minerals in phlogopite amended pots. Also, a very weak vermiculitization was observed in muscovite treated media. Under the K-free nutrient solution and in phlogopite amended treatments, the 1.4/1.0 nm peak ratio for endophyte infected plants was 4 times greater than that under non-infected plants. Such a significant difference in phlogopite vermiculitization is attributed to endophyte symbiosis and its positive effects on the type and quantity of tall fescue roots secretions. A significant decrease in pH values under the rhizosphere of infected plants further confirmed this hypothesis.

AbstractPlant roots absorb water and minerals from soil solution. Plant production is a function of root distribution and its activity in soil. By increasing root density in soil unit volume, roots absorb more water and minerals. This implies that knowledge of root development is an important factor for crop production. To determine the most suitable amount of water for the maximum development of corn (Zea mays L.) root, a greenhouse experiment was conducted in 2006-07. Water was applied in 55, 70, 85, 100 and 110 percent of water demand. The total corn roots were taken from the all pots in three stages: i.e. 8-9 leaves, the silk production and the dough. Wet and dry weights, volume, surface area and length of roots were measured in all three stages. In addition, ratio of root by dry matter of stem was calculated. The results revealed that weight, volume, surface area and length of roots were increased by increasing in the amount of water applied up to 100% water demand. A significant difference (5%) was found between treatments 85, 100, and 110% water demand with treatment 55% water demand, By an increase in the amount of water applied, the ratio of root to stem was decreased. It means, when water use is in optimum level, the root growth is stimulated, otherwise it is limited. It is concluded that optimum efficiency of water is taken with using 70 percent of water demand instead of 100 or 110 percent.

AbstractIn order to study the effects of different irrigation management on water productivity of local, improved and hybrid rice varieties an experiment was carried out on a split plot design with 3 replications. The varieties were splited on 5 irrigation methods (i.e. full irrigation, AWD, 5, 8 and 11 day irrigation interval) at Rice Research Institute of Iran, Rasht during cropping season of 2006. The results showed that interval irrigation reduced water use. Full irrigation with 593 mm had the highest water use and 11 day interval with 406 mm the lowest. Yield in hybrid, improved and local varieties were 6147, 5147 and 3987 kg/ha respectively. Results showed that yield loss in the varieties due to water stress (full irrigation, 5, 8 and 11 day interval irrigation) in hybrid were 9,19,23 and 44 percent, in improved were 14, 19, 23 and 29 percent and in local variety were 5,4,10 and 17 percent respectively. Local variety was the most resistant and hybrid was the most susceptible variety.

AbstractThis study was conducted to determine the impacts of different drip irrigation method and amount of water on yield and water use efficiency of tomato in Varamin Agricultural Research Center, Iran. The study was done during two years. Experimental design was randomized complete blocks design (RCBD) in split plot with three replications. Three different drip irrigation method; surface drip irrigation with in-line emitter tubes, surface drip irrigation (tape), and subsurface drip irrigation (tape) as main plot and three different amount of water (50, 75 & 100% water requirement) were as sub-plot. The result showed that subsurface drip irrigation (tape) and 100% water requirement treatment has the highest yield, but there was no significant difference between it and surface drip irrigation with in-line emitter tubes and 75% water requirement treatment. Water use efficiency in surface drip irrigation with in-line emitter tubes with 75% water use and subsurface drip irrigation (tape) with 100% water use were greater than other treatments. According to the results, under no limitation on water resources, the best option is subsurface drip irrigation (tape) with using 100% water requirement and under water limitation the best option is surface drip irrigation with in-line emitter tubes using 75% water requirement.

AbstractDifferent strategies are existed for adjusting with water shortage, of which the strategy of suitable policies adoption by determining optimum production function can be mentioned. Water shortage and quality degradation of soil and water resources is one of main factors of production reduction. Therefore, this study was carried out for determination of tomato sensitivity coefficients and its water-salinity-yield optimum function in Karaj. The experiment was performed as a complete randomized design with three replicates including two factors; Salinity and irrigation water. Salinity and irrigation water factors consisted of four levels (S1=0.7, S2=4, S3=8 and S4=12 dS/m) and three levels (W1=100, W2=75 and W3=50 percent of water requirement), respectively. The Soil texture was sandy loam. Yield data were fitted on different forms production functions (simple linear, logarithmic linear, Quadratic and Transcendental) and the optimum one was determined after sensitivity analysis. Then, the values of water use efficiency and plant sensitivity coefficients were determined. Results of sensitivity analysis showed that the quadratic production function is optimal production and it can be recommended. Investigation of the maximum values of error (ME) showed that the logarithmic linear and simple linear functions have had the highest error. In the irrigation treatments, W1S1 (control) and W2S1 (75% of water requirement) with 7.57 and 7.5 Kg /m3 respectively had the highest water use efficiency. However, water use efficiency decreases if the drought and salinity increases. The average value of Ky, in the condition of combined salinity and drought stress was 1.696. Moreover, Plant sensitivity values (Ks) decreases if salinity and drought increases and the lowest value of Ks were belong to W3S4 (0.57). The iso-yield curve showed that by increasing of irrigation amounts, water with higher salinity can be applied without yield change.

AbstractSouth-east basins of Iran which is including Sistan and Baluchistan, Kerman, Yazd and Hormozgan provinces has an extensive desert called " Loot " and this region is one of the hottest and driest parts of Iran. Few numbers and the lack of uniformity in scattering of hydrometric stations are main characteristics of this region.Another problem in this region is that data are short-term, so it leads to have unguaged sites.Data generation helped us to have at most 43 hydrometric stations with 20 years data plus 10 stations with 30 years data.On the other hand, in hydrology for fitting statistical distribution on rainfall and runoff, at least we need to have 30 years data and even more. Thus for analyzing different methods of flood estimation and presenting logical relationships in sub-basins, first of all we gathered meteorology, hydrology and ecological features and also morphometric characteristics were measured.Homogeneity test was done for data and they have been completed in a 20 years data.The group of homogeneous sub-basins has been determined using some methods like: Index Flood, cluster analysis and, multi-variable regression while some physiographic properties and ordinary and linear moments were used.Common statistical distributions have been tested and dominant statistical distribution of region was finally determined Log Pearson type III and based on that peak discharge with different return periods have been estimated to present mathematical models.Then, generated models have been tested using three other sub-basins which hadnt participated in presenting mathematical models.At last, the most appropriate mathematical relationships for flood discharge estimation in different return periods have been achieved in unguaged sites of south-east basins of Iran.

AbstractProcess of evapotranspiration (ETo) is a major component of the hydrologic cycle that its accurate estimation plays an important role to achieve sustainable development in water balance, irrigation system design and planning and management of water resources. Being a function of different metrological parameters and their interactions, evapotranspiration is a complex, nonlinear phenomenon. Preprocessing input parameters to select appropriate combinations is complex when modeling nonlinear systems. Using these methods reduce steps by trial and error by recognizing most important parameters for modeling by intelligent methods. In this study, two methods of stepwise regression (FS) and gamma test (GT) were used for preprocessing input parameters in multi layer perceptron neural network (MLP) to estimate daily estimation of ETo at Shiraz synoptic station. To evaluate the effect of Input parameters preprocessing in artificial neural networks using different statistical error criteria, ANN-FS and ANN-GT both with pre-processed parameters were compared against each other and also with ANN model without pre-processed parameters. The results showed that all three models have a high degree of accuracy to estimate daily ETo. ANN-GT model represented a determination coefficient (R2) of 0.9995 and the root mean square error (RMSE) of 0.0483. For ANN-FS and ANN models R2 values were 0.9984 and 0.9994 respectively and RMSEs were 0.0874 and 0.0548 respectively. Although the accuracy of ANN-GT model was slightly greater than ANN, but the ability of determination of importance of input parameters, education and recognition of the best combination of input parameters with 800 data in this study, makes this model a useful tool for fast preprocessing input parameters to model evapotranspiration.