The past decade has witnessed a flurry of hydrologic research activity related to artificial neural networks (ANNs). This volume is a compilation of chapters that have been contributed by researchers from several countries, and represents a wide spectrum of ANN applications in hydrology. Future potential of ANN applications has been identified at appropriate places. Readers of the book will find chapters dealing with preliminary aspects as well as advanced features of ANNs. With a unique focus towards hydrologic applications, this book will serve as a valuable reference for graduate students,...

Design of water control structures, reservoir management, economic evaluation of flood protection projects, land use planning and management, flood insurance assessment, and other projects rely on knowledge of magnitude and frequency of floods. Often, estimation of floods is not easy because of lack of flood records at the target sites. Regional flood frequency analysis (RFFA) alleviates this problem by utilizing flood records pooled from other watersheds, which are similar to the watershed of the target site in flood characteristics.

Clustering techniques are used to identify...

To accommodate the inherent non-linearity and non-stationarity of many natural time series, empirical mode decomposition (EMD) and Hilbert-Huang transform (HHT) provide an adaptive and efficient method. The HHT is based on the local characteristic time scale of the data. The HHT method provides not only a precise definition in time-frequency representation than the other conventional signal processing methods, but also more physically meaningful interpretation of the underlying dynamic processes. The EMD also works as a filter to extract the variability of signals with different scales and is...