Storage Capacity for River Reservoirs by Wavelet-Based Generation of Sequent-Peak Algorithm

Abstract

Selection of a storage capacity for the design ofa river reservoir is made traditionally by the Rippl masscurve method or the sequent-peak algorithm. Both methods offera single value of storage capacity to a water resourcesengineer. Synthetic hydrology approach by which long syntheticflow data are generated is also commonly used. In the presentstudy a hybrid technique combining these two approaches isdeveloped. The technique is based on wavelets, which arefunctions of zero-mean and finite variance, and it generatessynthetic sequent-peak algorithms. Haar wavelet is used in thegeneration scheme. The generation scheme is applicable to non-skewed sequences. The application of the technique to a 64-year long annual flow data suggests that the technique can bea useful tool in the selection of a storage capacity for thedesign of a river reservoir.