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Sabit Erşahin, M. Rüştü Karaman Gazi Osmanpasa University, Faculty of Agriculture, Dept. of Soil Sci., 60100 Tokat, Turkey. ABSTRACT Irrigation water should be managed wisely to conserve natural resources and to increase water application efficiency. This study was conducted to divide a field into homogenous infiltration management zones for the purpose of increasing irrigation water use efficiency and decreasing water and nutrient losses. Infiltration tests were conducted at 50 sites, on an irregular regular grid consisting of 10 columns and 2 rows, on a 8.5 ha commercial wheat field (Typic Ustifluent). Data from the tests were evaluated to obtain coefficients of the infiltration equation from Kostiakov. Parameter B varied from 3.99 to 157.71 and parameter n from -0.69 to -0.13. Based on the joint frequency distribution of the coefficients B and n in Kostiakov's equation, nine infiltration rate categories were defined, and low, medium and high infiltration rate management zones were developed in the study area. High infiltration rate zones comprised 2.63 ha, moderate infiltration rate zones 3.70 ha, and low infiltration rate zones 2.16 ha of the study area. Irrigation water should be monitored more carefully to decrease volumes of water and nutrients moving beyond the root zone and to increase water application efficiency in the medium and high infiltration rate zones. Also, to decrease the adverse effects of high infiltration rate on groundwater, deep rooted crops with greater water requirements may be grown in the regions of the field residing in high and medium infiltration rate zones. INTRODUCTION Most of Turkey's land is in semi-arid climate regions where water is one of the key factors limiting agricultural production. Proper management of water is one of the key factors to increase agricultural production in these regions. In the past, due to improper use of irrigation water, serious problems such as groundwater pollution and soil alkalinity have occurred in some irrigated areas. In addition, industrial and domestic requirements for water increased dramatically, further limiting agricultural use of water and leading a great concern on prospective conflict among neighboring countries (Postel, 1993). Therefore, there is a need to adopt management practices that will help increase efficiency of water use in agriculture in these regions. Infiltration is one of the key processes controlling the water budget and transport processes in the soil profile. The magnitude and evolution of infiltration will determine the proportions of the water moving beyond the root zone, stored in the soil profile, and available for surface runoff (Serrano, 1990). Infiltration rates on a field may vary from very low to very high due to changes in the soil characteristics which control infiltration characteristics. If the infiltration characteristics on a field could be controlled by some means, then irrigation efficiency could be increased to a high level (Jensen et al., 1987). Since changing soil characteristics is difficult, the same result can be achieved through site-specific application of irrigation water. Based on this concept, the field is divided into zones with homogenous infiltration characteristics, with each zone being irrigated differently. For example, while a particular surface irrigation technique can safely be operated in a zone with relatively low infiltration rate, use of the same technique may be avoided in the nearby zone with high infiltration capacity. This approach allows one to decrease water and nutrient losses from the bottom of the root zone and to increase water application efficiency. Regression lines representing infiltration rates for different sites on a field may be combined to develop water management zones with homogenous infiltration characteristics. According to this procedure, if both slopes and intercepts of two regression lines are the same at a given level of significance, then those two lines can be combined, forming a single regression line, and the areas represented by those two regression line can be combined, too. Ersahin and Yesilsoy (1993) applied this method to combine regression lines describing infiltration rates for various test sites on the Harran Plain in the southeastern Turkey. They recognized that as the number of regression lines to be combined increased, the chance to meet above conditions decreased, drastically. Therefore, in the present study, this method was not considered efficient to develop water management zones with homogenous infiltration characteristics. On the other hand, the concept of joint frequency distribution may be applied to develop regions with low, medium and high infiltration rate. This procedure requires that the variables considered (here intercepts and slopes of regression lines) exhibit a normal distribution. The objective of this study was to apply the joint frequency distribution technique to the infiltration parameters in Kostiakov's equation to divide a 8.5 ha commercial wheat field into zones with homogenous infiltration properties so that a variable water management program could be operated for the purpose of increasing irrigation water application efficiency and decreasing water and nutrient losses through deep percolation. MATERIALS AND METHODS Infiltration tests were conducted using double-ring variable-water level infiltrometers until steady-state infiltration rates were reached at 50 sites, on a irregular grids consisting of 10 columns and two rows, on a 8.5 ha irrigated field (Typic Ustifluent) located in the 25 km north of Tokat Province in Central Anatolia of Turkey. At each test site, soil samples from the topsoil (0-30 cm) and the subsoil (30-60 cm) were taken. All 100 samples were analyzed for percent clay, silt and sand by the hydrometer method (Gee and Bouder, 1986), organic matter contents by the Walkley Black method (Jackson, 1956), CaCO3 and pH with a Scheibler Calcimeter (McLean, 1986), and water contents at -0.033, -0.1 and -1.5 MPa soil water pressure with a pressure plate apparatus (Klute, 1986). In addition, at each test site, undisturbed soil samples were taken using 100 cm3 steel cores from the topsoil and the subsoil to determine soil bulk density (Blake and Hartge, 1986). According to Hillel (1980) , the infiltration equation developed by Kostiakov, has the form: i = Bt-n, (1) where i is the infiltration rate, t is time, and parameters B and n are empirical constants. These two constants can be estimated by plotting log i against log t, then log B and n are calculated as the y intercept and slope, respectively, of the resulting straight line. Following the procedure from Criddle et al. (1956), parameters B and n were calculated for each test site. Basic statistical parameters for selected properties of topsoil and subsoil, and for infiltration parameters n and B were also calculated with the statistical package StatMost (Dataxiom Software Inc., 1997). Based on the frequency distribution of the parameters n and B, two cutoff values defining low, medium and high levels of infiltration rate were established as described below. Using these three pairs together, nine possible combinations (categories) representing a joint frequency distribution of the parameters B and n were defined (Mulla, 1989). Infiltration rate categories from the joint frequency distributions were combined to develop infiltration management zones. This was achieved by establishing an index representing low, medium and high infiltration rate management zones. First, cutoff values of the first and the third quartiles for the frequency distributions of the parameters B and n were coded as low, medium and high levels as follows: if B is below the first quartile then code =1, if B is between the first and the third quartiles then code = 2, and if B is above the third quartile then code = 3. Likewise, if n is below the first quartile then code = 1, if n is between the first and the third quartiles then code = 2, and if n is above the third quartile then code = 3. Second, the values of codes for each pair from the joint frequency distribution were summed to obtain an index (sum = index): if sum £3 then the combination was considered within low infiltration rate zone, if sum = 4 then the combination was considered within medium infiltration rate zone, and if sum ³5 then the combination was considered within high infiltration rate zone. Finally, the combinations comprised by each infiltration rate management zone were determined and area of each management zone was calculated. RESULTS AND DISCUSSION Topsoils in the study area had an average textural classification of loam, but some portions on the field were described as silt loam or clay loam. Likewise, subsoils had an average textural classification of clay loam, and some portions of the field had a sandy clay loam subsoil texture. Percent organic matter exhibited a high variability in the subsoils, and pH exhibited a low variability in both topsoils and subsoils. All the other parameters had a medium variability in the both topsoils and subsoils. Soil pH was highly tailed and skewed to right in the both topsoils and subsoils (Tables 1 and 2).   Both parameters, B and n, were slightly skewed to right. While parameter B had a relatively flat distribution, parameter n exhibited a relatively tailed distribution. Parameter B was more variable than parameter n (Table 3).  Spatial patterns of parameter B and n are shown in Figs. 1 and 2. Parameter n had high values in the southwest region, between 300 and 400 meters, and some isolated portions in the east side; and parameter B had high values in the west and the east regions of the field. A high degree of negative association was found between the values of B and n (r = -0.74, P< 6.5 x10-9).   Results from normality test (Shapiro-Wilks) indicated that both parameters had a gaussian distribution (results from normality tests are not given). Infiltration categories established based on the frequency distributions of these two parameters are shown in Table 4, in which high values of B were matched with high values of n to represent an area with high infiltration rate , and low values of B were matched with low values of n to represent an area with low infiltration rate. For example, category 8 represents a high infiltration rate zone, category 5 represents a medium infiltration rate zon, and category 2 represents a low infiltration rate zone.  Twenty five percent of the field was in the high infiltration rate zone, 44% in medium infiltration zone, and the rest of the field was in low infiltration rate zone (Table 5). Generally, the east side of the field was dominated by medium and high infiltration rate zones while the west side was occupied by low and medium infiltration rate zones (Fig. 3). Therefore, irrigation water should be monitored more carefully to decrease volumes of water and mobile nutrients (i.e. nitrate) moving beyond the root zone in the east side. In this region, since use of surface irrigation techniques would result in a lower water application efficiency due to deep percolation, their application should be avoided. In addition, growing crops with greater water use requirement or deeper rooted crop may increase water use efficiency. On the other hand, surface irrigation techniques may be practiced in the west side of the field. Further research is needed to evaluate feasibility of this approach.   CONCLUSIONS This study was conducted to divide a field into low, medium, and high infiltration rate zones for the purpose of decreasing volumes of water and nutrients moving beyond the root zone, and increasing agricultural water use efficiency. Infiltration tests were conducted using double-ring variable water level infiltrometers at 50 sites, on a regular grid spacing of 41 m, on a 8.5 ha irrigated commercial wheat field (Typic Ustifluent), and results from infiltration tests were evaluated to obtain constants B and n in the infiltration equation from Kostiakov. Based on the results from joint frequency distribution of the constants B and n, 25%, 44% , and 31% of the field were in high, medium and low infiltration rate zones, respectively. Irrigation water must be monitored more carefully to reduce losses of water and nutrients through deep percolation in the regions dominated by high and medium infiltration rate zones. Crop with greater water requirement and/or deep rooted annual crop may be grown to decrease volumes of water and nutrients moving beyond the root zone and to increase efficiency of agricultural water use in those regions. REFERENCES Blake, G. R., and Hartge, K. H. (1986). Bulk density. p. 363-375. In A. Klute (edit.) Methods of Soil Analyses. Part 1. 2nd ed. Agronomy 9. ASA and SSSA, Madison, WI. Criddle, D.W., Davis, S., Pair, C.H., and Shockley, D.G. (1956). Methods for evaluating irrigation systems. USDA Soil Conservation Service. U.S. Government Printing Office. Dataxiom Software Inc. (1997). User's guide: StatMost. 5th Ed. Dataxiom Soft. Inc., LA, CA. Ersahin, S., and Yesilsoy, M.S. (1993). The relationship between infiltration rates and some physical and chemical properties of six widely distributed and important soil series selected in Harran Plain. Turkish Journal of Agriculture and Forestry. Vol:17, No:4, 863-873. Gee, G. W., and Bouder, J. W. (1986). Particle size analysis. p.825-844. In A. Clute (edit.) Methods of Soil Analysis. Part 1, 2nd ed. Agronomy No. 9. ASA and SSSA, Madison, WI. Hillel, D. (1982). Introduction to Soil Physics. Academic Pres. Inc., London. Jackson, M. L. (1956). Soil Analysis. Adv. Course. Fourth Print. Dept. of Soil Sci. Univ. of Wisconsin, Madison. WI. Jensen, M.E., Swarner, L.R., and Phelan, J.T. (1987). Improving irrigation efficiencies. p.1120-1142. In R.M. Hagan, H.R. Haise, and T.W. Edminster (edit.). Irrigation of Agricultural Lands. Fifth Printing, Agronomy No. 11. ASA and SSSA, Madison, WI. Klute, A. Water retention: Laboratory methods. (1986). p.635-660. In A. Clute (edit.) Methods of Soil Analysis. Part 1, Agronomy No. 9. 2nd ed ASA and SSSA, Madison, WI. McLean, E.O. Soil pH and lime requirement (1986). p. 199-224. In Page, A. L. (ed.) Methods of Soil Analysis. Part 2. 2nd ed. Agron. Monogr. 9. ASA and SSSA, Madison, WI. Mulla, D.J. 1989. Soil spatial variability and methods of analysis. In C.Renard, R.J van Den Beldt, and J.F. Parr (edit.), Soil, Crop, and Water Management Systems for Rainfed Agriculture in the Sudano - Sahelian Zone, ICRISAT, Patancheru, India. Postel, S. (1993). The Politics of water. World Watch, 10-18. Serrano, E. S. (1990). Stochastic differential equation models of erratic infiltration. Water Resour. Res., Vol. 26, No: 4, 703-711. |