Abstract
Stochastically generated hydrologic data have been used in the past by water worhorities world-wide for long-term planning of water resources development projects. These data are also currently being used in short- and medium-term planning and operation of water resource systems. For valid and realistic results, it is necessary that the generated data sequences preserve all statistical properties of historical data. This paper presents an improved disaggregation method for generation of alternative sequences of monthly hydrologic data. The method is designed explicitly to preserve the over-year monthly serial and cross correlations, in addition to other monthly and annual parameters of the historic sequence. The method is applied to both single-site and multi-site cases, and compared with two other disaggregation models that are used in Australia. The comparison of results shows that the developed method satisfactorily preserves both monthly and annual statistical parameters of the historic data sequences including the over-year monthly correlations.
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