Storage capacity for river reservoirs by wavelet-based generation of sequent-peak algorithm

Selection of a storage capacity for the design of a river reservoir is made traditionally by the Rippl mass curve method or the sequent-peak algorithm. Both methods offer a single value of storage capacity to a water resources engineer. Synthetic hydrology approach by which long synthetic flow data are generated is also commonly used. In the present study a hybrid technique combining these two approaches is developed. The technique is based on wavelets, which are functions of zero-mean and finite variance, and it generates synthetic sequent-peak algorithms. Haar wavelet is used in the generation 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 be a useful tool in the selection of a storage capacity for the design of a river reservoir.