JWSS - Journal of Water and Soil Science

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This research was conducted in Kooshkak Farm Research Station of Shiraz University in 1997 and 1998 in order to determine crop coefficient and water requirements of rice, using lysimeter. The variety used was Champa-Kamfiroozi which is an early mature variety and is grown by most farmers in the area. Results showed that potential evapotranspiration varied from 3.76 to 9.34 mm/day. Penman FAO method was used in calculating reference evapotranspiration. Crop coefficient was 0.97 in the initial growth stage, 1.25 in the mid-season growth stage, and 1.09 at the time of harvest. Total crop evapotranspiration rates in 1996 and 1997 were 560 and 757 mm, respectively. Average deep percolation rates in the growing season was 3.4 and 3.5 mm/day in 1996 and 1997, respectively. Finally the total water requirements of rice in 1996 and 1997 were 1983 and 2361 mm, respectively.

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In this study, the effect of deficit irrigation with every–other furrow irrigation method, which is an innovated method in farm irrigation management, was examined on sorghum (Sorghum durra L.) in Bajgah and Kooshkak areas of Fars Province. The experimental design was split plot with three main plots of irrigation interval (10, 15 and 20 days), three subplots of irrigation methods (ordinary furrow, fixed and variable every–other furrow), and 4 replications. Considering the crop production cost with real and subsidized prices of water in both areas, the net benefit per unit volume of irrigation water and benefit–cost ratio were calculated. The results showed that these economic parameters for the fixed and alternative furrow irrigation methods of 10-day intervals in both areas did not differ much with those of the ordinary furrow irrigation with 10-day intervals and were even higher in Bajgah area. Furthermore, the relationship between the amount of irrigation water, water application efficiency (Ea), water price per unit volume (Cw) and the net benefit per unit volume of irrigation water (B) with different conveyance efficiencies (Ec) were determined by multiple linear regression procedure. The regression coefficients of linear fit equation between the costs and irrigation water were determined. The results indicated that with higher price of water, the farmer should increase the farm irrigation application efficiency to avoid the economic losses.

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The vast pastures and agricultural development plans for dry farming and irrigated farming in Khuzestan Province depend on rain. This requires availability of annual precipitation prediction models to be used in the management decision-making process. In this research, the long-term daily precipitation data from 15 rain gauge stations in the study area were collected for study and a relationship between the early fall season precipitations of 42.5 mm (t_42.5) and the annual precipitation was obtained. The results showed that the relationship was an inverse one such that the later the fall precipitation occurred, the greater the annual precipitation would be. To increase the coefficient of determination in the models, climatic variables such as Persian Gulf sea surface temperature and geographical characteristics (longitude, latitude, altitude, and long term mean annual precipitation) were used. Except for the long term mean annual precipitation and altitude, other variables did not increase the coefficient of determination. The final simple model found is as follows: P_a=184.787-1.891t_42.5+0.855P_m , R²=0.704 where, P_a is the annual precipitation, t_42.5 is the time from beginning of fall season for 42.5 mm of precipitation, and P_m is the long term mean annual precipitation.

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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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Hydraulic coefficients of a porous media such as hydraulic conductivity K(θ) and diffusivity D(θ) have a controlling role in the evaluation of groundwater flow and pollutant transport behavior. Therefore, successful porous media flow evaluation depends on the accurate determination of its hydraulic coefficients. But it is hard and time consuming to measure. Values for these coefficients accurately as measurements usually task place at a moisture range close to saturation. This situation justifies the preference for prediction models to be used. One method for evaluation of K(θ) and D(θ) coefficients is to use models which take measured soil moisture characteristic curve data into consideration. For the purposes of the present study, pressure plates apparatus measured the required data to develop soil moisture characteristic curve for nine various soil textures. The volume of instantaneous outgoing water was measured with respect to time and the total volume of water released at the end of each experiment was measured for a given pressure (0.1 to 1.5 Mpa) imposed on undisturbed soil samples. A simple equation based on Richard’s equation is provided for the estimation of K(θ) and D(θ). Application of Mualem, van Genuchten et. al, Burdine, Green and Corey, and Gardner models for estimation of the K(θ) and D(θ) values at a variety of nine varied soil textures under experiment showed a wide range of variation. Therefore, it is hard to simulate the accurate hydraulic conductivity behavior for the given varied soil textures by means of the models available. However, if the minimum and maximum simulated values obtained from the models at respective soil moisture contents are considered to be a permitted range, one may state that the results of the estimated hydraulic coefficients by the proposed method in this study lie within the permitted range or agree with the results of other models considered. Therefore, the proposed method for determination of K(θ) and D(θ) is capable of selecting the best simulation model to estimate hydraulic coefficient values.

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Estimation of seepage is essential prior to lining of earth canals. In Iran such investigation has been achieved in some irrigation networks using empirical relationships derived in other countries. Estimation of water loss in canal is required in design, operation and management of water distribution systems. Water seepage may be determind by using empirical equations proposed by F.A.O. These equations are applicable for different soils and hydraulic parameters. However, the appropriate estimating equation should be determined for each region. Therefore, these equations should be calibrated for local usage and different canal vegetation conditions. In this investigation water losses in canals at the Rudast region of Isfahan were measured by inflow and outflow procedure. Different canals reaches were selected in soils of relatively heavy, medium and light textures. The density of vegetation population in canals were low, medium and high. The estimated seepage losses by different empirical equations were not corresponded to those of measured values. Therefore, by using the measured seepage at different soil textures and vegetation densities the empirical coefficients of six empirical equations of F.A.O. (Ingham, Davis and Wilson, Affengendon, Moritz, Molesworth and Yennidumia, Misra) were modified for the study region. The relationships between measured seepage and estimated seepage before and after modification of the empirical equations were determined by regression analysis. These equations estimated the seepage loss much smaller than the measured values. The regression parameters (selope, intercept, and coefficient of determination of regression equation) indicated that after modification, the Ingham and moritz equation with higher slopes (0.91, 1.01), lower intercepts (-0.096, -0.039) and higher coefficient of determination (0.96) estimated the closest seepage values to the measured values respectively. The misra equation was the next best equation for seepage estimation. The results of present investigation indicated that the modified Ingham and Moritz equations were the most appropriate ones for estimation of seepage losses at different soil textures and vegetation densities in the study region.

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Iran with a cultivation area of 45000 ha and production of 150 ton/year is the number one saffron producer in the world. Planting of large size corms will increase flowering, but production of corms (number and size) may be affected by irrigation method or frequency. In this research which is performed in the farm of College of Agriculture, Shiraz University, the effects of method and frequency of irrigation on corm production, and the effect of produced corms on flowering were evaluated in two consecutive years. Two irrigation methods (basin and furrow) with four levels of irrigation frequencies (12, 24 and 36 days and dryland farming) were applied. In August of 2000 sample corm was taken from every plot, and the effect of applied treatment from previous growing period on corm production and the effect of produced corms on future flowering were evaluated and analyzed. Based on the results, in furrow irrigation, total number of corms and total number of corms smaller than 4 gr is significantly higher than basin irrigation. In all of the above cases, irrigation frequencies did not show a meaningful difference between themselves or in comparison with dryland farming treatment. Total weight of corms and number and weight of corms larger than 8 gr in basin irrigation were more than furrow irrigation. This is to the extent that it is considered as the main reason for the difference in the flowering of corms, and has caused the flowering of basin irrigation to be significantly higher than furrow irrigation. In basin irrigation, irrigation frequencies of 12 and 24 days had the highest amount of flowering. No significant difference was observed on average corm production between the treatments in the two irrigation methods. However, irrigation treatments in both irrigation methods showed significant differences when compared with dryland farming treatment. So, basin irrigation with irrigation frequency of 24 days is preferred over furrow irrigation due to lower water consumption and production of larger size corms which is effective in flowering.

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In the present research, for the development of Fars province minimum temperature atlas, minimum daily temperature data of 20 evaporative stations of Fars Regional Water Organization and five synoptic stations of Fars Meteorological Organization were used. At first, two starting times were selected for all of the stations. The first was the first day of Farvardin for analyzing the spring frost and the secend was the first day of Mehr for analyzing the autumn and winter frost. Also, the temperature range of 0 to –1.5 was classified as mild frost or freeze, the temperature range of -1.5 to –3 as the moderate frost or freeze and temperature below –3 as severe frost or freeze. The data of minimum temperatures, the first and the last days in which the three temperature ranges occurred and the day of the lowest temperature based on the two starting times were recorded. The selected number of days (dates) were fitted to the distribution functions by SMADA software and the best distribution function was identified using the statistical parameter Root Mean Square. The best fitted distribution functions were Pearson type III and log Pearson type III. Then, based on the fitted distribution function, the number of days for the occurrence of the first and last frost and number of days for the occurrence of the first lowest temperature were determined at 50 and 70% probability levels. Finally, each of these occurrence dates was plotted with Surfer software using the geographical positions of each station (longitude and latitude) for Fars province. Based on these plotted maps, the best days of planting and harvesting of the crops can be determined throughout the Fars province.

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Agricultural investigations use computer models for simulation of crop growth and field water management. By using these models, the effects of plant growth parameters on crop yields are simulated, hence, the experimental costs are reduced. In this paper, the model of MSM (Maize Simulation Model) was calibrated and validated for the prediction of maize forage production at Agricultural College, Shiraz University in 1382 and 1383 by using maize forage yield under furrow irrigation with four irrigation and three nitrogen treatments. Irrigation treatments were I4, I3, I2, and I1, with the depth of water 20% greater than, equal to, 20% and 40% less than potential crop water requirements, respectively. Nitrogen treatments were N3, N2, and N1, with the application of N as urea equal to 300, 150, and 0 kg N ha^-1, respectively. After calibration and validation of MSM, it was used to estimate suitable planting dates, forage yield and net requirement of water discharge for planting at different dates. The results indicated that the net requirement of water discharge was reduced by gradual planting at different planting dates. By considering different planting dates for maize, from Ordibehest 20th to Tir 10th, the planting area might be increased 17.9%, compared with single planting date on Ordibehesht 30th under a given farm water discharge and full irrigation.

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Irrigation water Scarcity is the major limiting factor for crop production in irrigated farming. Therefore, optimal use of water is influenced by seasonal rainfall especially where the water price is high. Nitrogen also plays a key role in plant nutrition. In this study, wheat grain yield production as a function of applied water (irrigation plus seasonal rainfall) and nitrogen fertilizer (applied plus soil residual nitrogen) using existing data of a field experiment, were used. This function was obtained based on the data from the Maraghah Agricultural Experiment station. Based on this production function, maximum attainable yield can be 8.12 t/ha obtained by the consumption of 1.56 m of water (irrigation plus rainfall) and 193 kg/ha of nitrogen. An economic analysis based on the Iso-Quant curve was conducted to optimize the application rates of production inputs (water and nitrogen). When land is limited, the optimum water and nitrogen use will be based on maximizing net returns from land unit area. The optimal levels of these inputs were determined on the basis of farmer ability for paying the costs of water and nitrogen. Furthermore, optimum amounts of water and nitrogen were determined for different levels of wheat yield. The results indicated that despite low price of irrigation water and nitrogen fertilizer, at present market value, optimum values of water were more variable than those of nitrogen, for its high effective role in wheat production. The results also indicated that when there is no limitation of the source and use of water and nitrogen, and farmers are also able to pay their costs, application of 1.47 m of water (irrigation plus rainfall) and 190 kg/ha of nitrogen (applied plus soil residual) will produce maximum profit per hectare, reaching Rls 12,207,506. When water is limited, optimum levels of water and nitrogen will be based on the maximizing profit per unit of water. In this analysis, the use of 0.556 m of water (irrigation plus rainfall) and 190 kg/ha of nitrogen (applied plus soil residual) resulted in maximum net income per unit of applied water (irrigation plus rainfall) amounting to Rls/m3 1203. This amount of water use, which is 64.4 % lower than its amount under maximum yield condition, resulted in 181 % increase of cultivated area. Graphic expansion path on the isolines of yield showed more dependence of wheat production on water than nitrogen. Therefore, the optimum amounts of nitrogen in the three mentioned conditions are close to each other due to its subsidized price and lower effect on wheat production relative to water.

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Optimal crop water requirement is needed for precise irrigation scheduling. Prediction of crop water requirements is a basic factor to achieve this goal. In this study, maize potential evapotranspiration (ET_p) was prediced by maize simulation model (MSM). Then, it was evaluated and validated using experimental field data obtained in Agricultural Research Station of Shiraz University (Bajghah, Fars province) during 2003 and 2004. Comparison of measured volumetric soil water content with predicted values by MSM model in 2003 and 2004 indicated that this subroutine (prediction of maize evapotranspiration) did not need modification. Also, daily potential evapotranspiration of maize was estimated by using Penman-Monteith equation considering single and dual crop coefficients. Comparison between the results of predicted ET_p by MSM model, calculated ET_p by Penman-Monteith, and measured irrigation water and soil water content indicated that the prediction of ET_p by MSM model was satisfactory. Model prediction of seasonal ET_p, potential transpiration (T_p) and soil evaporation (E) were 831, 536 and 329 mm, respectively, in 2003, and 832, 518 and 314 mm, respectively, in 2004. The values of ET_p, T_p and E calculated by Penman-Monteith method using dual crop coefficients were 693, 489 and 205 mm, respectively, in 2003, and 700, 487 and 213, respectively in 2004. Maximum rate of predicted potential ET_p, Tp and E were 11.1, 8.2 and 5.1 mm d^-1, respectively in 2003 and 13.0, 9.0 and 4.0 mm d^-1, respectively in 2004. The values of calculated seasonal ET_p by Penman-Monteith method using single crop coefficient were 615 and 632 mm in 2003, and 2004, respectively. Comparison between the results of predicted ET_p by MSM model, calculated ET_p by Penman-Monteith equation with single and dual crop coefficients (FAO-56) and measured values of irrigation water and soil water contents of root depth indicated that FAO-56 methods underestimated the ET_p.

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The objective of this study was to evaluate the effects of crop residues management on soil physical and biological properties. The impacts of residue management on yield of forage corn and barley and soil micro-organisms population were also studied. The results showed that application of crop residues increased soil organic matter (22.2 %), saturated hydraulic conductivity (51.9 %), porosity (3.7 %), mean weight diameter (MWD) of the aggregates (5.4 %), and field capacity (5.8 %) and decreased bulk density (3.7 %) Whereas crop residues burring decreased soil organic matter (31.8 %), saturated hydraulic conductivity (36.6 %), porosity (0.5 %), mean weight diameter (MWD) of the aggregates (5.1 %), and field capacity (4.1 %) and increased soil bulk density (1 %). Soil water characteristic curves showed that the observed differences in soil water retention of application and burning residues treatments were higher at low matric suctions than those at high water matric suction. The results demonstrated that micro-organisms population significantly (P<0.05) decreased in residues burning treatment compared with the residues application treatment. Therefore, based on the results of this study residues' burning is not recommended in Ardabil.