نشریه آب و خاک
سال بیست و هشتم شماره 5 (پیاپی 37، آذر و دی 1393)

Water shortage is the most important factors on crop production in the world. Several methods of deficit irrigation are solutions for reduction of irrigation water. To understand the effects of conventional deficit irrigation and partial root zone drying treatments on yield, yield components and water use efficiency of sunflower (Farrokh cultivar), one study was carried out. The research was conducted on Shahid Bahonar University of Kerman in the spring of 2011. A factorial experiment in a randomized complete block design with one control (full irrigation) and 18 deficit irrigation treatments in three replications was considered. Deficit irrigation treatments were: conventional deficit irrigation (irrigation with %80, %60 and %40 ETP) and partial root zone drying (irrigation with %80, %60 and %40 ETP). Every deficit irrigation treatment was conducted in three growth stage of sunflower (all periods of growth, vegetative growth stage and reproductive growth stage).The results showed that the conventional deficit irrigation treatments (irrigation with 80% ETP) in vegetative growth had the highest plant height, leaf area, leaf area index and head diameter. Also, the maximum biological yield equal to49054, maximum grain yield is equal to 9934/3 and maximum oil yield is equal to 2441/2 kg per hectare in the conventional deficit irrigation treatments (irrigation with 80% ETP) in vegetative growth occurred.The highest water use efficiency for grain yield is equal to 1/46,forbiological yield equal to7/21 and for dry forage yield is equal 5/7 kilograms per cubic meter of water. According to results,conventional deficit irrigation (irrigation with %80, %60 and %40 ETP) is recommended on based.

Streamflows, actual evapotranspiration and crops’ yield are the main variables to estimate agricultural water productivity. Thus, simulation of these variables is of great importance in evaluation of different measures to increase water productivity. For this, application of conceptual models is a relevant approach and SWAT (soil and water assessment tool) is one of the well known models in this regard. The present paper aims to assess SWAT in simultaneous simulation of streamflows, actual evapotranspiration and the main crops’ yield of the Zarineh Rud basin. The reason for selection of this basin as the study area relates to its role to meet the Urmia Lake’s water requirement. The lake faces with serious water shortage in recent years and escalating water inflow depend to increase water productivity in the upper catchments. To setup SWAT, the basin was divided to 11 subbasins and 908 hydrological response units, which enables us to introduce more accurately the basin’s cropping pattern and water resources, which meet the requirements of the agricultural area. For simulation of the river flows, data from 6 gauging stations were used for calibration and validation of the model for periods of 1987 to 1999 and 2000 to 2006 respectively that resulted R2 and RMSE between 0.49 to 0.71 and 3.9 to 44.9 (m3/sec) for calibration period, and values of 0.54 to 0.77 and 2.07 to 55.7(m3/sec) for validation period respectively. There is no observed data for actual evapotranspiration in the basin. So, it was verified in the wet years by maximum evapotranspiration reported in National Water Document that results presented the values of 0.97 and 52.5(mm/year) for R2and RMSE respectively. Finally, the estimated yields of the 7 staple crops by the model were compared with the recorded data that showed very close values(R2=0.9 and RMSE=1.65(ton/ha)).

The response of root to water stress is one of the most important parameters for researchers. Study of growth and distribution of root under different irrigation managements helpsresearchersto a better understanding of soil water content, and the availability of water and nutrition in water stress condition. To investigate the effects of four levels of irrigation under two different deficit irrigation managements on the root length of maize, a study was conducted in 2009. Irrigation managements included fixed irrigation interval-variable irrigation depth (M1) and variable irrigation interval-fixed irrigation depth (M2). Maize plants were planted in 120 large 110-liter containers in a strip-plot design in a randomized complete block with three replications. Root data sampling was done after root washing in five growth stages. The results showed that the effect of irrigation levels on root length was significant (Punder both managements. The maximum root length was 4.61 and 4.64 Km per m3 of soil profile in M1 and M2, respectively in the depth of 0-70 cm of soil profile which was observed in full irrigation treatment at milk stage. The results indicated that root length in mild-deficit-irrigation level was more than root length in moderate and mild-deficit-irrigation levels. The response of root maize to water stress was more severe in variable-irrigation-interval management and the same amount of reduction in applied water resulted in more decrease in root length under variable-irrigation-interval than fixed-irrigation-interval management. Therefore, due to the importance of root length as one of the most important characteristics of growth indices in maize to determine the amount of water absorption, determination of the optimum level of water stress and selection of an appropriate deficit-irrigation management can increase water use efficiency as well as maize yield.

Infiltration is a complex process that changing by soil infiltration properties, initial moisture and water head on the soil surface. Due to infiltration measurement problems and variability infiltration regarding initial moisture and water head on the soil surface, using simulation models to identify the infiltration equation has the least sensitivity makes sense and important. The main objective of this study was to estimate the coefficients of infiltration equations, Kostiakov-Lewis, Philip and Horton, and evaluate the sensitivity of these equations and their coefficients under various initial conditions (initial moisture soil) and boundary (water head on soil surface). Therefore, one-and two-dimensional infiltration for basin (or border) irrigation were simulated by changing the initial soil moisture (before irrigation) and water head on soil surface (during irrigation) using the solution of the Richards’ equation (HYDRUS model). To determine the coefficients of infiltration equations, outputs of the HYDRUS model (cumulative infiltration over time) were fitted using the Excel Solver. Comparison of infiltration sensitivity equations and their coefficients in one-and two-dimensional infiltration showed infiltration equations and their sensitivity coefficients were similar function but quantitatively in most cases sensitive two-dimensional equations and their coefficients were greater than one dimension. In both dimensions the soil adsorption coefficient Philip equation as the sensitive coefficient and Horton equation as the sensitive equation under various initial moisture soil and water head on soil surface were identified.

Uncertainty analysis is a useful tool to evaluate soil water simulations in order to get more information about the models output. These information provide more confidence for decision making processes. In this study, SWAP model is applied for soil water balance simulations in two fields which are planted by wheat and maize in an arid region. First the amount of uncertainty is estimated and compared for soil moisture simulation by using Generalized Likelihood Uncertainty Estimation (GLUE) in the two fields. Then based on the computed parameter uncertainty, the effect of uncertainty in soil moisture simulation is evaluated on soil water balance components. Results indicated that in arid regions with irrigated agricultural fields, prediction of actual evapotranspiration is relatively precise and the coefficient of variation for the two fields are less than 4%. Moreover, the prediction of deep percolation for the two fields are influenced by the uncertain hydraulic conductivity and showed lower precision according to the actual evapotranspiration.

The use of saline water for irrigation of crops is known as a strategy of on-farm irrigation water management. In this study, the cyclic use of saline and fresh water and its effect on soil salinity were investigated. Field experiments were carried out in randomized complete block under drip irrigation for maize crop with 9 treatments. The treatments were based on irrigation management of saline and fresh water use on three salinity levels 0.4, 3.5 and 5.7 dS/m and freshwater application in every one, three and five saline water application (1:1, 3:1 and 5:1, respectively). The hypothesis behind this research was periodic leaching compared with continuous leaching (leaching with every irrigation) causes better control of the leaching (controlling solute) while sustaining land was provided. The results showed that there was no significant accumulation of salt in the soil in 1:1 management at the end of growing season, compared to its beginning. This management would be recommended for sustainable agriculture. In cyclic managements, soil salinity was decreased in soil profile after irrigation with fresh water. When applicating saline water under drip irrigation, salt accumulation was higher in soil surface and salt accumulation decreased by increasing distance from the drippers.

Modeling of crop growth plays an important role in evaluation of drought impacts on rainfed yield, choosing an optimum sowing date, and managerial decision makings. Aquacrop model is a new crop model that developed by Food and Agriculture Organization (FAO), that is a model for simulation of crop yield based on “yield response to water“with meteorological, crop, soli and management practices data as inputs. This model has to be calibrated and validated for each crop species and each location. In this paper, the Aquacrop is calibrated and evaluated for rainfed wheat in Sisab station (Northern Khorasan). For this purpose, daily meteorological data and historical yield data from two cropping season (2007-2008 and 2008-2009) in the Sisab station are used to calibrate this model. Next, meteorological data and historical yield data of five cropping season (2002-2003 to 2006-2007) are used to validate the model. The result shows that the Aqucrop can accurately predict crop yield as the R2, RMSE, NRMSE, ME, and D-Index are achieved 0.86, 0.062, 5.235, 0.917 and 0.877, respectively.

In order to study the sensitivity of vegetative growth to water deficit stress of a late-maturing peach (Prunus persica L. cv. Elberta) under orchard conditions, an experiment was conducted as randomized complete-block design with three treatments and four repetitions in Shahdiran commercial orchard in Mashhad during 2011. Three irrigation treatments including 360 (low stress), 180 (moderate stress) and 90 (severe stress) m3ha-1week-1 using a drip irrigation system (minimum stem water potential near harvest: -1.2, -1.5 and -1.7 MPa, respectively) from the mid-pit hardening stage (12th of June) until harvest (23rd of Sep.) applied. Predawn, stem and leaf water potentials, leaf photosynthesis, transpiration, stomatal conductance and leaf temperature, the number of new shoots on fruit bearing shoots and vegetative shoots lengths during growing season as well as leaf area at harvest were measured. The results showed that water deficit stress had negative effects on peach tree water status, thereby resulting in decreased leaf gas exchange and tree vegetative growth. As significant decreased assimilate production of tree was resulted from both decreased leaf assimilation rate (until about 23 % and 50 %, respectively under moderate and severe stress conditions compared to low stress conditions) and decreased leaf area of tree (until about 57% and 79%, respectively under moderate and severe stress conditions compared to low stress conditions at harvest). The significant positive correlation between leaf water potential and vegetative growth of peach revealed that shoot growth would decrease by 30% and 50% of maximum at leaf water potential of –1.56 and –2.30 MPa, respectively.

To study the effect of Aquazorb super absorbent polymer (SAP) on reducing Drought stress of Acacia victoriae seedling, a split plot experiment based on the completely randomized design was conducted. In this research, stressed treatment as the main plots and amount of superabsorbent were considered as sub plot. Treatments were applied consisted of four levels of drought stress (15, 30, 60 and 100% of field capacity) and four levels of superabsorbent (0, 0.2, 0.4 and 0.6 wt%) Were studied. The results showed that survival of seedlings at the end of growth season between different treatments was the same, but the Acacia growth was responsed to the water stress and reduced growth traits were found. Using of the superabsorbent polymer had a significant effect on collar diameter, seedling height, fresh and dry root weight, relative water content of leaf and proline. According to the comparison of the means simple effects, in all of growth indices except the leaf area and root fresh weight the most means was obtained in 0.2% superabsorbent polymer treatment and also, in comparison the effect of diferent factors in most of the traits the highest means compared with 100% irrigation level without applying SAP related was to 60% irrigation level with 0.2 % SAP. That represents water savings is about 40%.

Annual fires might change many soil physical properties in semi steppe rangeland.The objective of this study was to investigate the impact of fire on soil physical properties and soil water infiltration parameters in semi-steppe rangeland of Karsanak region in Chaharmahal and Bakhtiari province. Therefore, several sites were chosen which were affected by fire at three, two and one years prior to this study (i.e. 2008, 2009 and 2010, respectively). Soil water infiltration was measured using tension infiltrometer in 54 points of the study sites. Since the soil samples were taken from to depth (0-10 cm and 15-25 cm) of each site, the numbers of soil samples for laboratory analysis were 108. Independent t-test and principle component analysis (PCA) was used to assess the difference between the measured properties at the burned and control sites. The results showed that aggregates stability coefficients (MWD and GMD) in the surface layer significantly reduced in 1 and 2 years after fire compared with control areas. Water dispersible clay (WDC) and bulk density significantly increased in surface layer of all burned areas compared with control areas. Saturation hydraulic conductivity significantly decreased in burned areas in 1, 2 and 3 years after. The results showed that annual fires occurs have meny negative effects on soil physical properties cause to shallow, low water retention capacity and high risk of erosion in semi steppe rangeland.

The high cost of fertilizers in farming systems, soil pollution and degradation of soil are factors that caused to full use of available renewable nutrient sources of plant (organic and biological) with optimal application of fertilizers in order to maintain fertility, structure, biological activity, exchange capacity and water-holding capacity of the water in soil. Therefore, in recent years, according to investigators biofertilizers and organic farming as an alternative to chemical fertilizers has been drawn. Through this study, we examined the effects of triple superphosphate, organic matters and phosphate solubilizing microorganisms on quantitative and qualitative yield of wheat and nutrient uptake. The experiment was carried out in the factorial based on randomized complete block design. The factors were: 1-phosphate solubilizing bacteria in three levels including control, Pseudomonas Putida and Bacillus Coagulans bacteria, 2- triple superphosphate in five levels of 0, 25%, 50%, 75% and 100% and 3-organic matter in 2 levels of 0 and 15 ton/ha in the soil with high phosphorous accessibility (13 mg/kg soil) but lower than sufficient limit for plant 15 mg/kg soil). The results showed that the highest amount of yield has been recorded in Pseudomonas Putida bacteria treatment with organic matter and 25% phosphate fertilizer. As a result, at the conditions of this experiment phosphate solubilizing bacteria and organic matter significantly had higher yield than control and their combination with phosphate fertilizer had significant effect on reducing phosphate fertilizer use.

Montmorillonite is the major mineral of Bentonite with many applications in industrial fields but some impurities decreases the quality of the bentonite. The main objective of this study was to investigate the suitable method for purification of Ghaen mine bentonite. A combination of methods was considered including wet sieving and sedimentation, centrifuge and ultrasound. The efficiency of purification methods was determined based on X-ray, particle size, cation exchange capacity (CEC) and ratio peak of the Quartz/Montmorillonite analysis before and after experiments. The results showed that such methods were efficient for preparing of the materials having high quantity of montmorillonite with less than 2 microns particle sizes. Cristobalite was the only mineral remained in samples, however many of particles were exempted from the samples. Cristobalite was the main impurity remained with montmorillonite. Chemical treatment is the only way for its complete removal. The results of this study revealed that by using easy, cheap and fast methods, it is possible for acceptable purification of bentonite.

There is an increasing demand for reliable large-scale soil datato meet the requirements of models for planning of land-usesystems, characterization of soil pollution, and prediction ofland degradation. Cation exchangecapacity (CEC) is among the most important soil propertiesthat are required in soil databases. This paper applied a novel method for whole-soil profile predictions of CEC (to 1 m) across Dorudlocated in LorestanProvince. At present research, we combined equal-area spline depth functions with digital soil mapping techniques to predict the vertical and lateral variations of CEC across the study area where limited soil information exists (103 soil profiles). To model the relationship between CEC and environmental factors (i.e. Representative soil forming factors), derived from a digital elevation model and Landsat imagery, a regression tree was applied. Results indicated that some auxiliary data had more influence on the prediction model (i.e. B3 and modified catchment area). Our results also confirmed the regression tree model predicted target variable at the five specific depths with coefficient of determination of 0.84, 0.84, 0.84, 0.66, 0.27 and root mean square of 1.75, 1.84, 1.84, 2.11, and 2.16, respectively. Results showed a reasonable R2 in first four depths ranged from 0.66 to 0.84; while, it decreases to 0.27 in the last depth. Our results also confirmed that the regression tree as a predictive model, digital soil mappingtechniqueand equal area splinesare powerful tools to predict lateral and vertical variation of CEC.

In order to comparision of the micromorphic properties of saline-sodic and nonsaline-nonsodic soils in the west of Urmia Lake, four soil profiles (2profile in saline-sodic soils and 2profiles in nonsaline-nonsodic soils) were investigated. These profiles were described and sampled using standard methods. soil samples were used for physico chemical analysis and undisturbed and oriented samples were used for thin section preparation. Thin sections were studied using polarizing microscope in PPL and XPL lights. Thin sections studies showed that saline-sodic soils are structure less (apedal), and their voids are mostly vughs and channel and as a result, their, nonsaline-nonsodic soils are pedal with compound packing voids, vughs and planar voids and as a result, The b.fabric in these to group of soils is crystallitic. In saline sodic soils pedofeatures are illuvial clay coatings, salt accumulations including coatings and infillings of halite in channel and vughs. These pedofeatures were not seen in nonsaline-nonsodic soils. Organic coatings were seen as black colored films on peds and in some cases mixed with groundmass of saline-sodic soils.Calcium carbonate accumulations as nodules and coatings and nodules and coatings of iron and Mn oxides were seen in both saline-sodic and nonsaline-nonsodic soils.

xture is an important soil physical property that governs most physical, chemical, biological, and hydrological processes in soils. Detailed information on soil texture variability is crucial for proper crop and land management and environmental studies. Therefore, at present research, 103 soil profiles were dogged and then sampled in order to prepare digital map of soil texture in Bijar, Kurdistan. Auxiliary data used in this study to represent predictive soil forming factors were terrain attributes, Landsat 7 ETM+ data and a geomorphologic surfaces map. To make a relationship between the soil data set (i.e. Clay, sand and silt) and auxiliary data, regression tree (RT) and artificial neural network (ANN) were applied. Results showed that the RT had the higher accuracy than ANN for spatial prediction of three parameters. For the clay fraction, determination of coefficient (R2) and root mean square root (RMSE) calculated for two models were 0.46, 0.81 and 17.10, 12.50, based on validation data set (20%). Our results showed some auxiliary variables had more influence on predictive soil class model which included: geomorphology map, wetness index, multi-resolution index of valley bottom flatness, elevation, slope length, and B3. In general, results showed that decision tree models had higher accuracy than ANN models and also their results are more convenient for interpretation. Therefore, it is suggested using of decision tree models for spatial prediction of soil properties in future studies.

In this study, the artificial neural networks (ANNs) and regression models were used to downscale the simulated outputs of the general circulation models (GCMs). The simulated precipitation for 25.18 º N to 34.51 º N and 45 º E to 60 º E, geopotential height at 850 mb and zonal wind at 200 mb for 12.56° N to 43.25° N and 19.68° E to 61.87° E data sets as the predictors were extracted from ECHAM5 GCM for the period 1960-2005. The observed monthly precipitation data of Abadan, Abadeh, Ahwaz, Bandar Abbas, Bushehr, Shiraz and Fasa stations as the predictand were extracted for the period 1960-2005. The principal components (PCs) of the simulated data sets were extracted and then six PCs were considered as the input file of the ANN and multiple regression models. Also the combinations of the simulated data sets were used as the input file of these models. The periods 1960-2000 and 2001-2005 were considered as the train and test data in the ANN, respectively. The Pearson correlation coefficient and normalized root mean square error results indicated that ANN predicts precipitation more accurate than multiple regression. For the monthly time scale, the geopotential height is the best predictor and for the seasonal time scale (winter) the simulated precipitation is the best predictor in ANN based standardized precipitation principal components.

Today, there arevarious statistical models for the discrete simulation of the rainfall occurrence/non-occurrence with more emphasizing on long-term climatic statistics. Nevertheless, the accuracy of such models or predictions should be improved in short timescale. In the present paper, it is assumed that the rainfall occurrence/non-occurrence sequences follow a two-layer Hidden Markov Model (HMM) consist of a hidden layer (discrete time series of rainfall occurrence and non-occurrence) and an observable layer (weather variables), which is considered as a case study in Khoramabad station during the period of 1961-2005. The decoding algorithm of Viterbi has been used for simulation of wet/dry sequences. Performance of five weather variables, as the observable variables, including air pressure, vapor pressure, diurnal air temperature, relative humidity and dew point temperature for choosing the best observed variables were evaluated using some measures oferror evaluation. Results showed that the variable of diurnal air temperatureis the best observable variable for decoding process of wet/dry sequences, which detects the strong physical relationship between those variables. Also the Viterbi output was compared with ClimGen and LARS-WG weather generators, in terms of two accuracy measures including similarity of climatic statistics and forecasting skills. Finally, it is concluded that HMM has more skills rather than the other two weather generators in simulation of wet and dry spells. Therefore, we recommend the use of HMM instead of two other approaches for generation of wet and dry sequences.

Characteristics of precipitation and the regionalization major role in the efficient use of water resources and soil and management of environmental hazards. Regionalization of rainfall can help to better use of water resources and to correct manage of environmental hazards. According to the analysis of climate phenomena such as precipitation, all data should be related to a homogeneous region, on the basis in this study, homogenous regions using data from long-term annual precipitation in Golestan province and the appropriate number of stations determined using the newer methods. Precipitation monthly data from 29 rain-gauge stations and evaporation poll in Golestan province from 1361 to 1391 were used to testing of homogeneity, the random and outlier data that 25 stations remained. Then using Wards hierarchicalclustering and with different variables was evaluated segmentation varies. Clustering in two clusters have higher average silhouette 0.48, accordingly, the province was divided into two regions. Homogeneity investigated by heterogeneity test for each region. according to investigations was performed by L- moments coefficient of skewness (τ_3^R) was smaller 0.23, The result Hosking and Wallis test was used to examine the homogeneity region. For this two region, the test statistic H11>, which is confirmed by the homogeneity of the two areas, Finally was divided into two regions. The high correlation coefficient between stations in each cluster and low correlation coefficient between two different cluster is another reason for separation of areas from each other.

The aim of this study is to assess some synoptic characteristics of heavy precipitations in southwestern parts of Iran and evaluate the relationship between them with the Madden-Julian Oscillation (MJO). Research is conducted with regard to distribution of precipitation per month and identifying their steam sources. Daily records of the November-April precipitation data in Abadan, Ahwaz, Bandar-Abbas, Bushehr, Shahr-e-kord and Shiraz stations for the 1975- 2011 period are collected as well as same panel data for Yasuj station from 1990 to 2011. Rainfall data are sorted in descending order and precipitation values that were fallen within the 5% and 10% of highest records are categorized as the heavy precipitation. The most frequent precipitations occurred in January, February and December. The most frequent heavy precipitations in Ahwaz, Bandar-Abbas, Bushehr, Shahr-e-kord and Shiraz stations occurred in phase 8, while in Abadan station occurred in phases 7 and 8. Apparently, due to the short duration precipitations data at Yasuj station, the most frequent heavy precipitation observed in phase 2.Synoptic maps show that harmonized with eastward movement of convective precipitation in Indian or pacific oceans.Heavy precipitation forms in the west region of Iran and moves toward southwest and south Central of Iran and then appears to Afghanistan.Formation of a cyclonic circulation that encompasses the Mediterranean Sea, Red Sea and Persian Gulf plays an important role for moisture supplement of these storm activities. The synoptic maps have indicated that main sources of these heavy rainfalls are moisture produced at the Arab sea and western parts of the Indian Ocean.