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This study is intended as a step toward a better underst and ing of the small scale structure in the wall region of a turbulent boundary layer. To achieve this goal, the smallest reported hot-wire U-probes (typical dimensions: = 25 (mu)m, d = 0.5 (mu)m) have been constructed. In the new wind tunnel facility in which these probes were used, the dimensionless length scale of these probes, based on wall parameters, is u(,(tau))/(upsilon) = 0.3. Theoretical analyses of the static and dynamic response of small aspect ratio wires (operated in the constant-current mode) show that, though the hot-wires are uniformly less sensitive to velocity fluctuations, their frequency response is not affected. The analyses indicate that, for the small probes used in this study, the frequency response is uniform to 10 kHz, which is more than adequate for the present work. Measurements of the mean velocity profile and streamwise turbulence intensity profile are reported with the small U-probes. Comparison of the turbulence intensity data with larger probes shows that the smaller probes measure more energy due to their better spatial resolution. The data measured by the small probes are also analyzed to determine the burst frequency at various distances from the wall and at two Reynolds numbers. The results show that the burst frequency scaled with respect to the wall parameters is less a function of Reynolds number than the burst frequency scaled with respect to the outer flow variables. To obtain more quantitative information regarding the turbulence structure, measurements are reported with two small U-probes. From the correlation coefficient deduced from the measured data, it can be concluded that the turbulence structure increases in size, in both the spanwise and transverse direction, as the distance from the wall increases. Data for two probes less than two viscous lengths apart are analyzed to reveal the small scale features during a burst and in the absence of a burst. The main conclusions that can be drawn are that (1) intermittent small-scale shear layers occur more frequently when bursts are present than when they are not present and (2) on occasions, the velocity gradient of these small-scale shear layers is as large as the mean velocity gradient at the wall.

Water supply has always exerted a major influence on the development of the economy of any community, state or nation. It has been observed through history that people frequently built homes, settlements and cities adjacent to waterways, though the divides between watersheds were often steep and heavily forested, and travel across them was difficult. As time advanced population increased, communication improved, and people started moving farther away from the streams or waterways. Recently the United States population and industrial and agricultural development have reached a stage of growth where local water supplies are failing to meet the demand (29,30). Individuals and organizations have frequently been enjoined from withdrawing water from upstream channels, because such withdrawals would have seriously impaired the activities of downstream water users. To improve public water supply is, therefore, the problem on which research is required. Consequently, efforts are being made to study the full life history of the waters of the earth, and in particular the factors affecting water yield of the watersheds. Several aspects of water yield of a watershed are of concern to those engaged in the development of water supplies. These aspects are total quantity, fluctuations in quantity, and quality. Climate over a watershed,.and watershed characteristics are such that conditions varying from droughts to floods exist. Probably little can be done about the climate, consequently interest has centered on the effects of watershed characteristics upon water yield. Soil within the watershed is among the dominant factors causing variations in water yield. Hursh and Fletcher (15) state that an analogy of the storage function of the soil profile to the storage in an artificial reservoir is justifiable. Parks and Longwell (25) state that soil moisture is Tennessee's greatest water reservoir. Moisture storage in the soil profile, however, is not static; it is dynamic. The dynamic moisture conditions in the soil profile affect watershed hydrology to a considerable extent. Thus, a knowledge of moisture storage in the soil profile of a watershed is necessary.

Corn (Zea mays L.) is one of the major crops of American agriculture. It is a dual purpose crop since it is grown both for grain and forage. The grain is consumed directly and in-directly in different forms by human beings. A high quality silage is made from the forage for livestock. Thus the wide uses of corn indicate its importance. In United States the average per acre yield of corn is 61.8 bushels and the total production per year is 3.55 billion bushels. The productivity of land for a given crop is a function of three major influences--the soil, the climate, and the management practices. Each of these three major influences is made up of several components. The soil includes its physical, chemical, and biological conditions. The climate includes rain fall, temperature, light, etc. The management practices include the application of fertilizer, weed control, plant protection measures, tillage, cropping system, etc. Considerable efforts have been made in recent years to study the relationships between corn yields and one or more components. Probably less work has been done to study the relationships between corn yields and all the components together. The need to predict corn yield on various soils with different types and amounts of management inputs under different environmental conditions has been recognized. Since soil types in Tennessee vary greatly in their capacity to produce corn, more precise prediction information is needed for farmers to better utilize their land and other resources by selecting an appropriate cropping system and management level. The objectives of this study were; 1. to interpret rainfall and soil moisture information in terms of drought as one production factor; 2. to develop methodology for fitting appropriate drought values along with varying levels of selected management factors in quadratic prediction equations; 3. to develop a mathematical relationship in terms of a quadratic function between observed yields and varying levels of selected production factors; 4. to develop "effective" prediction equations for pre-dicting corn yields; and 5. to make an agronomic interpretation of the findings of this study.