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This item was digitized as part of the Million Books Project led by Carnegie Mellon University and supported by grants from the National Science Foundation (NSF). Cornell University coordinated the participation of land-grant and agricultural libraries in providing historical agricultural information for the digitization project; the University of Arizona Libraries, the College of Agriculture and Life Sciences, and the Office of Arid Lands Studies collaborated in the selection and provision of material for the digitization project.

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The application of the crop water stress index (CWSI) method to irrigation scheduling is enhanced by knowledge of the relationship between CWSI and soil water potential (SWP) and how this relationship is affected by soil texture. A study using the same cultivar of cotton on three different soils was conducted in southern Arizona over a single growing season. Detailed data were collected of CWSI and soil moisture content for several treatments that scheduled irrigations at threshold CWSI values. CWSI was correlated with soil water potential values calculated from pressure plate determined moisture release curves. Spatial variability of soil characteristics necessitated use of average rather than plot specific moisture release curves. Analysis showed a linear CWSI-SWP relationship that varied greatly with soil depth and study site. The study concluded that soil profile average SWP alone does not normalize the CWSI between sites with different soil textures.

The investigation reported in this dissertation is a portion of a larger effort to determine how allocation of water resources affects economic and social development in an arid environment. The study focuses on irrigated crop agriculture in Western Yuma County, Arizona, where irrigation water supplies are obtained from diversions from the Colorado River. Irrigated agriculture accounts for nearly 95 percent of total water use in this area. Linear programming techniques are used to determine optimum farm output and resource use patterns for five different farm models representing different farm size groups. The farm models were synthesized from data collected in a survey of 102 farms within the study area in 1964. This sample represented about one-fourth of the total universe. The linear programming analysis proceeds in four phases. In the first phase solutions are obtained for each model under the assumption that the size structure of agricultural firms and the resource base is fixed at current levels. In the second phase additional activities are added to permit land acquisition or disposal by each model farm. In the third phase the original formulation is modified to permit reclamation of new lands under the assumption that existing water rights will be perfected. The fourth phase combines the individual models analyzed in phase two into an integrated general model in which resource disposals by one farm size model must be balanced by acquisition in another. The final stage of the analysis includes estimates of crop output, and resource use under conditions specified in each phase. The marginal value product of selected resources is discussed and demand schedule for additional water is estimated. Land transfer price ranges are also discussed.

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Secondary effluent from the Roger Road Wastewater Treatment Plant undergoes tertiary treatment of dual media filtration and chlorination. The tertiary effluent is recharged and subsequently extracted for irrigation in Tucson, Arizona. The fate of chlorinated organics in this recharge system was investigated in this research. Nonpurgeable organic carbon was found to reach a constant level in the groundwater after being recharged. Not all of the organic carbon was removed from the water. Nonpurgeable organic halogens increased as they flowed away from the recharge basins. Reasons for this increase were not determined. Attempts were made to define the apparent molecular weight distribution of the NPOC and the NPOX. Measured values of the two parameters were consistently greater after the analytical processing than before, making the determination impossible.

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