Thesis (M.S.)--Ohio State University, 1975. / Includes bibliographical references (leaves 41-44). Available online via OhioLINK's ETD Center

The scarcity of water resources is increasing and marginal quantities of water are becoming more important. The need for sound and conservative management of water supply is imperative. Intensified agricultural production, to feed the ever-increasing world population, is requiring more irrigation, which is the heaviest consumptive use of water. It is desirable, therefore, to seek new techniques that can modify the irrigation water supply regime. Such a modification implies the urgent need for the development of an irrigation water supply regime dictated by seasonal hydrologic considerations and agricultural production that is technologically fully controlled on the basis of long-range stochastic considerations. The fact that most observed historical hydrologic data are usually short and may constitute poor representation of the possibilities for long-term planning in irrigation systems management, reinforces the postulation that any meaningful approach to the optimal development and operation of irrigation systems must take full cognizance of hydrological uncertainty. To achieve optimum competence in irrigation systems management under the predominating constraint of hydrological uncertainty, a methodology that first considers the systems operational policies as well as several levels of water consumption is necessary. To be realistic with operating rules one has to consider the stochastic variability in irrigation planning and thus has to consider uncertainty and risk relating to the major decision input information-(hydrologic information); and other considerations other than strictly maximizing expected economic monetary value must be brought into the model formulation. Any meaningful planning in agricultural water utilization has to be man-centered in approach and must provide objective analysis of subjective considerations. The above rationale led to the development of a stochastic Bayesian Decision Theory optimization model, which specifies expected utility as the criterial objective function to maximize, and which could be realistically employed to identify the best decision-criterion and adequate policies for optimal long-term planning, development and operation of irrigation systems with storage under hydrological uncertainty. The model, which is behavioral in approach, is applied to the Nicola Valley Irrigation District located in the dry, semi-arid interior of Brutish Columbia. Two irrigation operational procedures, two decision criteria, and different crop response function are employed in the analysis to identify the best planning policy for astute irrigation systems management in the region. The results obtained from the model indicate that the optimal areas to irrigate under hydrological uncertainty are dependent on the degree of hydrological uncertainty, the systems operating procedure, the crops irrigated and their responses to water, and on the decision criterion and utility function employed. Post-optimal analyses indicate that optimal policies obtained are very sensitive to discretized probability distribution of the uncertain states of nature, crop response function, utility function and decision criterion, and system operating procedure employed. For Nicola Valley Irrigation District the model shows that the practice of irrigating more alfalfa hectarage at a water consumption level that is below the designated maximum water requirement of alfalfa, - Procedure II, is superior to the practice of irrigating less hectarage to maximum consumptive use of crop and maximum water holding capacity of the soil, - Procedure I. It is also shown that the criterion of maximizing total expected utility, EU, is superior to the criterion of maximizing total expected monetary value, EMV, under uncertainty and risk. The model also shows that it is desirable to have some hydrological forecasting device. In the Nicola region for improved output from the model. Thus, the model has considerable promise as a valid tool for optimal long-term irrigation systems management decision-making under hydrological uncertainty. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

Proefschrift (Ph.D) -- Wageningen University, 2009. / Description based on print version record.

Thesis (M.S.)--University of Hawaii at Manoa, 2005. / Includes bibliographical references (leaves 65-68). / xii, 68 leaves, bound 29 cm

Important stages in the development of a wind energy operated irrigation system, which is simple in design and easy to maintain, are described from model tests in wind tunnels through to a prototype prepared for field tests. The attention is focussed on gross features of the protoype including the blade geometry and aspect ratio; mast, sleeve and bearing assemblies; braking system and a load matching concept. Described towards the end are the field test arrangements of the prototype and associated instrumentation. Even according to the most conservative estimate, the prototype tests suggest that the windmill should be able to deliver around 3000 liters of water per day (eight hours of wind) to a head of 5 m in a 24 km/h wind. / Applied Science, Faculty of / Mechanical Engineering, Department of / Graduate

Call number: LD2668 .T4 1962 W77

Thesis (M.S. - Soils, Water and Engineering)--University of Arizona, 1985. / Bibliography: leaves 119-121.

Call number: LD2668 .T4 1979 B59 / Master of Science

A water allocation model was developed to assist with allocation of canal water to competing crop irrigation demands. Multi-period linear programming was utilized to optimally allocate water in both time and space to maximize benefits for an irrigated farm. Irrigation scheduling, crop response and canal water delivery models were used to support the water allocation decisions. The irrigation scheduling model supplied information on crop evapotranspiration and soil water storage. The crop response model predicted crop yield in response to the irrigation water applications. The canal delivery model checked the feasibility of supplying the allocation quantities through the control structures and turnouts. The allocation model was evaluated by tests of water allocation for the University of Arizona, Maricopa Agricultural Center demonstration farm. In crop scenarios which emphasized cotton production, the model recommended deficit irrigation for the barley, cotton, grapes and wheat fields during periods when the quantity of irrigation water demanded was greater than that supplied. Analysis of the effects of changes in water cost and crop returns showed the basis of the solution remained unchanged for a wide range of data. The basis was, however, found to be unstable with very limited water supplies. In addition to serving as a planning tool, the allocation model could be used as a real time management tool. It is believed to have broad applicability to other irrigation projects in other areas with characteristics similar to Arizona test conditions.

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