Abstract: River flow predictions are needed in many water resource management activities. Hydrologists have relied on individual techniques such as time series, conceptual, or artificial neural networks (ANNs) to model the complex ...

Abstract: Artificial neural network (ANN) and regression models are developed for the estimation of concrete slump using concrete constituent data. The concrete mix constituent and slump data from laboratory tests have been employed ...

Abstract: In the past, studies involving optimal design of composite channels have employed Horton’s equivalent roughness coefficient, which uses a lumped approach in assuming constant velocity across a composite channel cross ...

Abstract: Modeling of an event-based rainfall-runoff process has been of importance in hydrology. Historically, researchers have relied on conventional modeling techniques, either deterministic, which consider the physics of the ...

Abstract: The temporal and spatial characterization of unknown groundwater pollution sources remains an important problem in effective aquifer remediation and assessment of associated health risks. The characterization of contaminated ...

Abstract: Urban flooding is a common disaster occurring every year, leading to the loss of lives and properties throughout the world. Its frequency and severity have increased over the years and are expected to increase further due ...