The main goal of this study was to evaluate the different feed-forward back-propagation artificial neural networks’ (ANNs) potential to estimate and interpolate the reference crop evapotranspiration (ET<Subscript>0</Subscript>) in Fars province of Iran. ET<Subscript>0</Subscript> was calculated using the FAO-56 Penman–Monteith method...</subscript></subscript>

Deep drainage can contribute to groundwater table rises and salinity, and is a complex function of rainfall, land management and soil hydraulic properties. Each of these components is uncertain and variable in space and time. This study quantifies the associated uncertainty using a Monte Carlo...

The impact of topography on the diurnal patterns of surface flow is of great importance, significantly modifying the wind speed spatial distribution and the vertical structure of the lower atmosphere. In this work, two feed forward neural network architectures are examined for their ability to...

A GIS-based decision support system, which incorporates local topographic and rainfall effects on debris flow vulnerability is developed. Rainfall at a scale compatible with the digital elevation model resolution is obtained using a neural network with a wind-induced topographic effect and...