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Predictability of hydrological systems using the wavelet transformation: Application to drought prediction
R Maity,
Published in Springer Nature
2019
Pages: 109 - 137
Abstract
Hydrological processes are continuously evolving over time under the influence of a number of factors including climatic changes. The effect of these factors leads to the nonstationary nature of hydrologic time series. This chapter focuses on the potential of wavelet transform (WT) to deal with the hydrologic time series prediction considering its time-varying nature. This chapter first presents a brief theoretical background of wavelet transform. Next, a few applications of basin-scale drought predictions are presented to demonstrate the potential of wavelet-based models. When applied to two basins of different sizes, the wavelet-based method is found to satisfactorily capture the interrelationship between different types of droughts and their propagation from one type to another. It should also be noted that the methodology presented is general and can be applied to similar problems dealing with hydrologic prediction. © 2019, Springer Nature Switzerland AG.
About the journal
JournalData powered by TypesetHydrology in a Changing World
PublisherData powered by TypesetSpringer Nature
ISSN23646934
Open AccessNo