Multivariate Modeling of Hydrological Time Series for Generation of Reservoir Operating Rulesby Mohammad Karamouz, Polytechnic Univ, Brooklyn, NY, USA,
Abstract: A multivariate model and a disaggregation model are used in this study to generate annual and monthly time series of streamflow data for multiple sites. The parameters of the models are first estimated by using historical annual and monthly data. Then monthly series are generated by using the synthetic annual flows and normally distributed random components which are inputs for the disaggregation model. The standardized annual and seasonal data were normalized by a transformation that minimizes the sum of square of residuals from the standard normal distribution. The generated monthly series are used for development of monthly release rules for operation of multiple reservoir systems.
Subject Headings: Hydrologic models | Data processing | Reservoirs | Model analysis | Time series analysis | Mathematical models | Streamflow | Hydrologic data
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