In this paper, the wavelet transform methods were briefly introduced, and present
researches and applications of them in hydrology were summarized and reviewed from six …

Discrete wavelet transform (DWT) is commonly used for wavelet threshold de-noising,
wavelet decomposition, wavelet aided hydrologic series simulation and prediction, as well …

Increasingly, natural resource management agencies and nongovernmental organizations
are sharing monitoring data across geographic and jurisdictional boundaries. Doing so …

Investigating the interaction of water resources such as rainfall, river flow and groundwater
level can be useful to know the behavior of water balance in a basin. In this study, using the …

Identification of periods is a key issue in hydrologic time series analysis. It is also a difficult
task in practice when analyzing hydrologic series with complicated stochastic …

Identification of dominant periods is a typical and important issue in hydrologic series data
analysis, since it is the basis of building effective stochastic models, understanding complex …

Quantifying the uncertainty in hydrological forecasting is valuable for water resources
management and decision-making processes. The hydrological uncertainty processor …

This work focuses on developing a forecasting model for the water inflow at an hydroelectric
plant's reservoir for operations planning. The planning horizon is 5 years in monthly steps …

In this paper, the influence of four key issues on wavelet-based analysis of hydrologic series'
complexity under multi-temporal scales, including the choice of mother wavelet, noise …

Dynamic Quantile Linear Models: A Bayesian Approach Page 1 Bayesian Analysis (2020) 15,
Number 2, pp. 335–362 Dynamic Quantile Linear Models: A Bayesian Approach Kelly CM …