This study was conducted to examine both spatial and temporal variability of infiltration rates on a rangeland site in west-central Utah. The experiment utilized a grid 20 m long and 18 m wide in both grazed and ungrazed sites with a sample spacing of 2 m within the grid. investigate the seasonal effect on variability of infiltration rates, data were collected for 3 seasons (summer, fall, and spring). Measured infiltration rates at 10 and 30 min during all seasons and under grazed versus ungrazed conditions were all found to approximate a two-parameter log normal distribution. Regionalized variable theory was applied to the data through the development of autocorrelograms and semivariograms, revealing a complete lack of variance structure among the infiltration rates. This finding excluded the possibility of using the Kriging technique for interpolation. Seasonal effect was found to be very important in influencing infiltration rates. The difference between the measured infiltration rates at both grazed and ungrazed sites was very significant for the 3 seasons under study. Variability is considered one of the most important aspects of the infiltration process. Many difficulties arise due to natural variability which is characteristic of all field studies. This characteristic complicates analytical expressions developed to describe and predict the infiltration process. In this matter, Vieira (1980) stated, To estimate the infiltration rate of a given field, the variance structure of the observations throughout the field must be identified in order to appropriately analyze each set of measurements, and obtain the best estimate of the expected mean Also, Nielsen et al. ( 1 973) emphasized that it is important to assess to some degree the confidence that can be attached to predictions made by models. Though many factors contribute to variability of infiltration rates, they can often be expressed simply in terms of time and space. The variation can be attributed to source combination of experimental error, time variations, and spatial variation (Campbell 1978). Several studies have investigated the spatial variability relationships among measured infiltration rates; however, there has been little attempt to investigate seasonal changes. In addition, most studies of spatial variability of infiltration rates have been conducted on agriculture lands. This study examines both spatial and temporal variability on a rangeland site in Utah. The study uses regionalized variable theory to assess the spatial relationships of field measured infiltration rates on a seasonal basis. The experiment had 4 objectives: first, to study seasonal infiltration rates; second, to determine the approximate frequency distribution of measured infiltration rates on a seasonal basis; third, to determine the spatial variability Authors are research assistant and professor, respectively, Watershed Science Unit, College of Natural Resources, Utah State University, Logan, 84322. Dr. Gifford is currently Head, Dept. of Range, Wildlife and Forestry, University of Nevada, Reno, 89506. This project was supported in part by the Food and Agricultural Organization of the United Nations and in part by the Utah Agricultural Experiment Station, Project 749 and 771. Paper Number 2783, Utah Agricultural Experiment Station, Logan. Manuscript accepted December 29, 1983. relationships among measured infiltration rates by using semivariograms and autocorrelograms; and last, to compare infiltration rates from grazed and ungrazed pastures. Concept of Regionalized Variables The term regionalized was proposed by Matheron (1971) to describe a phenomenon distributed in space (and/or time) which exhibits a specific structure. A variable which characterizes such a phenomenon is called a regionalized variable. Almost all variables describing subsurface water movement or atmospheric water movement may be considered regionalized variables (Delhomme 1976). From the mathematical viewpoint, a regionalized variable is simply a function x(z) which gives the value at point z (in a 1, 2, or 3-dimensional space) of a characteristic x of the natural phenomenon being studied. Regionalized variable theory is used for the analysis of the spatial variation of infiltration rates. Autocorrelograms and semivariograms are used to identify the degree of dependence (zone of influence) of infiltration rates on the distance between pairs of measurements. The Autocorrelogram If x(z) is the value of the regionalized variable x at a point z, and x (z+h) is the value of x at a point z+h at a distance h from z, the autocovariance between x(z) and x(z+h) for a given h is (Rendu 1978): o(h) = E { [x(z) E [x(z)] [x(z+h) E[x(z+h)]]} where E denotes expected value. The function a(h) is the autocovariogram of the regionalized variable x. Assuming o l to be the variance of x(z) and a2 variance of x(z+h): 2 a = E {[x(z) E (x(z))]2} 2 a2= E {[x(z+h) E[x(z+h)]]2} The coefficient of correlation between x(z) and x(z+h) is:
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