JWSS - Journal of Water and Soil Science

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To obtain soil-moisture characteristic curve experimentally is time-consuming and usually subject to considerable errors. So, many investigators have tried to predict soil-moisture characteristic curve by different models. One of these models predicts soil moisture characteristic curve based on soil particle size distribution and bulk density. In this model, soil particle size distribution curve is divided into a number of segments, each with a specific particle radius and cumulative particle mass greater than that of the radius. Using these data, soil-moisture characteristic curve was estimated. In this model, a scale factor, α, is used which may be considered as a constant, or obtained by logistic or linear procedures. The average values of α for clay, silty clay, sandy loam, two loam soils, and two silty clay loam soils were 1.159, 1.229, 1.494, 1.391, 1.393, 1.253 and 1.254, respectively. For most conditions, soil particle size distribution curve is not available, but only the percentages of clay, silt, and sand could be obtained using soil textural data, which is not enough to draw a precise soil particle size distribution curve. In this situation, a precise soil particle size distribution curve must be initially developed on the basis of which the soil moisture characteristic curve can be predicted. In this study, using soil textural data of seven different soils, soil moisture characteristic curve of each was estimated. In these estimations, logistic and linear methods were used to obtain the α value. Then, the results were compared with those of measured soil moisture characteristic curve. For estimation of soil particle size distribution curve, two extreme values for soil particle radius, 125 and 999 m, were used. The results indicated that using particle radius of 999 µm is more appropriate. On the other hand, it was found that for clay, silty clay, and sitly clay loam texture, it is more appropriate to employ a linear equation to determine for estimating soil-moisture characteristic curve while the logistic equation can be more appropriately used for loam and sand loam textures.

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A research was conducted in Fars province Agricultural Research Center in Zarghan area from 1999 to 2002 to determine the water requirement and crop coefficient of wheat, applying lysimeter. The results indicated that the water requirements of wheat were 720, 712 and 674 mm in the years of 1999-2000, 2000-2001 and 2001-2002, respectively. Using Penman-Monteith method for estimating reference crop potential evapotranspiration, the crop coefficients for wheat at a four-stage crop growth were 0.37, 0.64, 1.10 and 0.51, respectively. Due to the inaccessibility of the whole weather data, we tried to figure out a solution to determine wheat water requirement to schedule irrigation planning for future. In this respect, we made use of a ten-day class A pan mean evaporation and crop coefficient.

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To investigate the effects of different irrigation levels on yield and oil content of rapeseed, and to determine the irrigation requirement and irrigation scheduling, an experiment with Randomized Complete Block Design consisting of four irrigation treatments replicated 3 times, was conducted in Zarghan Agric. Expt. Station during the years of 2000-2003. The treatments were based on the cumulative evaporation values of 50, 75,100 and 125 mm from class A pan (T₅₀, T₇₅, T₁₀₀ and T₁₂₅). The depth of water for each treatment was determined according to the deficit of field capacity and soil moisture content before irrigation. In the three years of experiment, the cultivars: Okapi, Orient and Likord were cultivated and the annual data related to yield and seed oil contents of each cultivar was analyzed separately. In the first year of experiment, the effect of different treatments on yield of Okapi cultivar was not significant, but the maximum and minimum yields were obtained at the T₇₅ and T₁₀₀ treatments equal to 2678 and 2050 kg ha^-1, respectively. The effect of different treatments on seed oil content was significant at the level of 5 %, and the maximum and minimum seed oil contents were obtained at the T₁₀₀ and T₇₅ treatments equal to 42.50 and 41.66 %, respectively. In the second year of experiment, the effect of different treatments on the yield of Orient cultivar was significant at the level of 5 %, and the maximum and minimum yields were obtained at the T₅₀ and T₁₂₅ treatments equal to 3133 and 2133 kg ha^-1, respectively. The effect of different treatments on seed oil content was significant at the level of 5 %, and the maximum and minimum seed oil contents were obtained at the T₇₅ and T₅₀ treatments equal to 46.38 and 44.82 %, respectively. In the third year of experiment, the effect of different treatments on the yield of Likord cultivar was significant at the level of 5 %, and the maximum and minimum yields were obtained at the T₅₀ and T₁₂₅ treatments equal to 3667 and 2250 kg ha^-1, respectively. The effect of different treatments on seed oil content was significant at the level of 1 %, and the maximum and minimum seed oil contents were obtained at the T₅₀ and T₁₂₅ treatments equal to 47.63 and 44.60 %, respectively. Also, the best irrigation frequency for the three rapeseed cultivars in the Zarghan area was obtained equal to 10 to 12 days.

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In this paper, the effect of irrigation water salinity levels on seed germination, dry matter weight of seedlings at eight-leave stage, and the salt tolerance of 8 rapeseed cultivars was investigated. Relative yield reduction in saline and non saline conditions, salt sensitivity index and Van Genuchten-Hoffman methods were used to determine the salt tolerance of the cultivars. Results showed that the effect of different salt levels, cultivars and their interactions on germination and dry matter weight of seedlings was significant at 0.01(the higher the salt level, the lower the germination and dry matter). Also, using the Van Genuchten-Hoffman method, the irrigation water salinity corresponding to 10%, 25%, 50% and 90% reducts in germination and dry matter of seedlings were determined. Statistical analysis showed that a single cultivar gives different responses to salinity during growth stages and it may be tolerant in one stage, but sensitive to salinity in another growth stage. In this research, ACSN1, Falcon, and Shirali in germination stage and ACSN1, Falcon, and Cobra in seedling growth stage were salt tolerant. The three cultivars Oyerka, Global, and Ceres and the next three Shirali, Global, and Oyerka were sensitive to salinity in germination and seedling growth stages, respectively. Finally, the ACSN1 and Falcon cultivars were introduced as salt tolerant, and Oyerka and Global were considered as salt sensitive.