• Input Specifications to a Stochastic Decision Model

      Clainos, D. M.; Duckstein, L.; Roefs, T. G.; Systems and Industrial Engineering Department, University of Arizona; Hydrology and Water Resources Department, University of Arizona (Arizona-Nevada Academy of Science, 1972-05-06)
      The use of discrete conditional dependency matrices as input to stochastic decision models is examined. Some of the problems and initial assumptions involved with the construction of the above mentioned matrices are discussed. Covered in considerable detail is the transform used to relate the gamma space with the normal space. A new transform is introduced that should produce reasonable results when the record of streamflow (data) has a highly skewed distribution. Finally, the possibility of using the matrices to provide realistic inputs to a stochastic dynamic program is discussed.
    • Role of Modern Methods of Data Analysis for Interpretation of Hydrologic Data in Arizona

      Kisiel, Chester C.; Duckstein, Lucien; Fogel, Martin M.; Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona 85721; Department of Systems and Industrial Engineering | Department of Watershed Management (Arizona-Nevada Academy of Science, 1972-05-06)
      Mathematical models, requiring substantial data, of hydrologic and water resources systems are under intensive investigation. The processes of data analysis and model building are interrelated so that models may be used to forecast for scientific reasons or decision making. Examples are drawn from research on modeling aquifers, watersheds, streamflow and precipitation in Arizona. Classes of problems include model choice, parameter estimates, initial condition, input identification, forecasting, valuation, control, presence of multiple objectives, and uncertainty. Classes of data analysis include correlation methods, system identification, stationarity, independence or randomness, seasonality, event based approach, fitting of probability distributions, and analysis for runs, range and crossing levels. Time series, event based and regression methods are reviewed. The issues discussed are applied to tree-ring analyses, streamflow gaging stations, and digital modeling of small watersheds and the Tucson aquifers.