Evaluation of Methods for Estimating Long-Term Flow Fluctuations Using Frequency Characteristics from Wavelet Analysis

Abstract

This study was aimed at exploring different indices to quantify flow fluctuations and calculate long-term flow indicators (L-FFI). Three approaches were considered to calculate the indicators: Method (1)—calculate the annual index and then average it; Method (2)—average the annual flow characteristics and then calculate the index; and Method (3)—calculate the index considering all available data. Wavelet analysis was performed to evaluate the derived L-FFI. The evaluation index was based on the period corresponding to the highest spectral power from the wavelet transformation of seasonally differenced data. Strong and negative positive correlations were observed between the L-FFI and the high- and low-flow variations, respectively. The correlation coefficient (R) between L-FFIs and the frequency with maximum global wavelet power showed that Method (2) consistently yielded the most reliable results across various facets, having a determination coefficient of 0.73 (R2) on average. In the regionalization analysis using the Ward method, it was consistently observed that the two largest dams (the Chungju Dam and the Uiam Dam) were significantly differentiated from the other dams. Furthermore, Method (2) showed the most similar characteristics to the clustering of the wavelet features. The outcomes are expected to facilitate long-term water resource management.