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dc.contributor.authorDvoracek, M. J.
dc.contributor.authorRoefs, T. G.
dc.date.accessioned2013-08-28T17:18:52Z
dc.date.available2013-08-28T17:18:52Z
dc.date.issued1971-04-23
dc.identifier.issn0272-6106
dc.identifier.urihttp://hdl.handle.net/10150/300124
dc.descriptionFrom the Proceedings of the 1971 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - April 22-23, 1971, Tempe, Arizonaen_US
dc.description.abstractPlaya lakes usually occur in arid or semiarid regions where lands are flat and there is an absence of well-developed surface drainage nets. They are usually filled by surface runoff from highly erratic precipitation patterns. There are about 20,000 of them in the high plains of Texas and their volume of storage is an estimated 2.5-3 maf. As such, they represent a major underutilized water source. The major drawbacks to their utilization are high evaporation losses, questionable depth-area relations and the stochastic nature of the rainfall source. This paper assumes that the water is available and presents a dynamic programming model useful in determining the optimal utilization of the water for irrigation. If irrigation is the major use, its timing of application is of paramount importance. A deterministic dynamic programming model, utilizing the state variables of antecedent soil moisture and amount of available water, is presented, and provides the time and amount of irrigation required to maximize crop response. A better stochastic model is also presented which considers rainfall probability and resulting lake filling. The models are only first attempts and do not incorporate all possible variables.
dc.language.isoen_USen_US
dc.publisherArizona-Nevada Academy of Scienceen_US
dc.rightsCopyright ©, where appropriate, is held by the author.en_US
dc.subjectWater resources development -- Arizona.en_US
dc.subjectHydrology -- Arizona.en_US
dc.subjectHydrology -- Southwestern states.en_US
dc.subjectWater resources development -- Southwestern states.en_US
dc.subjectPlayasen_US
dc.subjectWater sourcesen_US
dc.subjectDynamic programmingen_US
dc.subjectStochastic processesen_US
dc.subjectRainfallen_US
dc.subjectIrrigation wateren_US
dc.subjectSemiarid climatesen_US
dc.subjectModel studiesen_US
dc.subjectMathematical modelsen_US
dc.subjectCrop responseen_US
dc.subjectTimingen_US
dc.subjectProbabilityen_US
dc.titleOptimal Utilization of Playa Lake Water in Irrigationen_US
dc.typetexten_US
dc.typeProceedingsen_US
dc.contributor.departmentHydrology & Water Resources, University of Arizonaen_US
dc.identifier.journalHydrology and Water Resources in Arizona and the Southwesten_US
dc.description.collectioninformationThis article is part of the Hydrology and Water Resources in Arizona and the Southwest collections. Digital access to this material is made possible by the Arizona-Nevada Academy of Science and the University of Arizona Libraries. For more information about items in this collection, contact anashydrology@gmail.com.en_US
refterms.dateFOA2018-06-12T17:31:26Z
html.description.abstractPlaya lakes usually occur in arid or semiarid regions where lands are flat and there is an absence of well-developed surface drainage nets. They are usually filled by surface runoff from highly erratic precipitation patterns. There are about 20,000 of them in the high plains of Texas and their volume of storage is an estimated 2.5-3 maf. As such, they represent a major underutilized water source. The major drawbacks to their utilization are high evaporation losses, questionable depth-area relations and the stochastic nature of the rainfall source. This paper assumes that the water is available and presents a dynamic programming model useful in determining the optimal utilization of the water for irrigation. If irrigation is the major use, its timing of application is of paramount importance. A deterministic dynamic programming model, utilizing the state variables of antecedent soil moisture and amount of available water, is presented, and provides the time and amount of irrigation required to maximize crop response. A better stochastic model is also presented which considers rainfall probability and resulting lake filling. The models are only first attempts and do not incorporate all possible variables.


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