weather process prediction is the tool for managers to planning the future political for maximum operation. the aim of this research is relation investigation of large scale synoptically patterns with seasonal rainfall of khorasan province. in this research, we have analyzed 37 years of rainfall data in khorasan province that is located the northeastern part of iran .we attempted to train adapt...

Despite advances over the last two decades in the capacity to predict the evolution of the El Niño–southern oscillation (ENSO) phenomenon and advances in understanding of the relationship between ENSO and climate, there has been little use of climate predictions for water resources management in the tropics. As part of an effort to develop such a prediction scheme, the ENSO influences on stream...

[1] The primary advantage of radar observations of precipitation compared with traditional rain gauge measurements is their high spatial and temporal resolution and large areal coverage. Unfortunately, radar data require vigorous quality control before being converted into precipitation products that can be used as input to hydrologic models. In this study we coupled a physically based atmosphe...

In this paper, models for short-term prediction of influent flow rate in a wastewater-treatment plant are discussed. The prediction horizon of the model is up to 180 min. The influent flow rate, rainfall rate, and radar reflectivity data are used to build the prediction model by different data-mining algorithms. The multilayer perceptron neural network algorithm has been selected to build the p...

Most runoff and soil erosion models take into account rainfall intensity, since higher storm intensities lead to greater runoff and losses of soil due to erosion. Accurate prediction of soil erosion requires rainfall intensity data with a high temporal resolution. This places a restriction on the simulation of soil erosion, since high temporal resolution data are usually not available. One way ...

This study uses a stochastic ensemble-based representation of satellite rainfall error to predict the propagation in flood simulation of three quasi-global-scale satellite rainfall products across a range of basin scales. The study is conducted on the Tar-Pamlico River basin in the southeastern United States based on 2 years of data (2004 and 2006). The NWSMultisensor Precipitation Estimator (M...

The nonlinear convectively coupled character of the summer monsoon intraseasonal oscillation (ISO) that manifests in its event-to-event variations is a major hurdle for skillful extended-range prediction of the active/break episodes. The convectively coupled character of the monsoon ISO implies that a particular nonlinear phase of the precipitation ISO is linked to a unique pattern of the large...

The need for accurate modeling of rainfall-runoff-sediment processes has grown rapidly in the past decades. This study investigates the efficiency of black-box models including Artificial Neural Network (ANN) and Autoregressive Integrated Moving Average with eXogenous input (ARIMAX) models for forecasting the rainfall-runoff-sediment process. According to the complex behavior of the rainfall-ru...