Tip** bucket rain gauges (TBRs) continue to be one of the most widely used pieces of
equipment for rainfall monitoring; they are frequently used for the calibration, validation, and …

In recent decades, development of artificial intelligence, as a predictor for hydrological
phenomenon, has created a great change in predictions. This paper investigates the …

Drought causes huge losses in agriculture and has many negative influences on natural
ecosystems. In this study, the applicability of Adaptive Neuro-Fuzzy Inference System …

In this study, Generalized Regression Neural Networks (GRNN) and Feed Forward Neural
Networks (FFNN) approaches are used to predict the scour depth around circular bridge …

Recently, Computational Neural Networks (CNNs) and fuzzy inference systems have been
successfully applied to time series forecasting. In this study the performance of a hybrid …

The objective of the study was to use Support Vector Machines (SVM) to simulate runoff and
sediment yield from watersheds. Recently, pattern-recognition algorithms such as artificial …

The ability of least square support vector machine (LSSVM) is investigated in this paper for
modeling discharge-suspended sediment relationship. The daily stream flow and …

Monthly water consumption time series have been predicted using a series of Artificial
Neural Network (ANN) techniques including Generalized Regression Neural Networks …

The present study was conducted in the Nagwa watershed in Jharkhand state, India. The
watershed has been identified as a sensitive area for sediment and non-point source …

A correct estimation of the instantaneous peak flow (IPF) is crucial to reducing the
consequences of flash floods. An approach to estimate the IPF, obtained by combining Soil …