Satellite-based precipitation (SBP) is emerging as a reliable source for high-resolution
rainfall estimates over the globe. However, uncertainty in SBP is still significant, limiting their …

Producing the accurate forecasting of solar radiation time series is a difficult assignment. To
accomplish it, this paper employs the wavelet artificial neural network model for long-term …

Six interpolation methods for infilling daily in situ soil moisture are evaluated at 36 Oklahoma
Mesonet stations from 2000 to 2007. The performance of artificial neural network (ANN) …

A precise predictive model is important for obtaining a clear understanding of the changes in
dissolved oxygen content in crab ponds. Highly accurate interval forecasting of dissolved …

The statistical study of rainfall time series is one of the approaches for efficient hydrological
system design. Identifying, and characterizing long-term rainfall time series could aid in …

RESUMO O conhecimento da variabilidade espacial da precipitação é importante em
diversos ramos das ciências agrárias e ambientais, como, por exemplo, na produção das …

An accurate, high-resolution precipitation estimation based on rain gauge and radar
observations is essential in various meteorological applications. Although numerous studies …

O objetivo deste trabalho foi desenvolver e avaliar um método de espacialização dos
elementos do balanço hídrico climatológico (BHC). O método utiliza modelos digitais do …

The complex topography and inherent nonlinearity affiliated with influential hydrological
processes of urban catchments, coupled with limited availability of measured data, limits the …

Spatial interpolation is a required method to generate a continuous surface such as Digital
Elevation Model (DEM) because field investigation for most of the surface's part is time …