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...

There are many models that have been used to simulate the rainfall-runoff relationship. The artificial neural network (ANN) model was selected to investigate an approach of improving daily runoff forecasting accuracy in terms of data preprocessing. Singular spectrum analysis (SSA) as one data preprocessing technique was adopted to deal with the model inputs and the SSA-ANN model was developed. ...

The present research work was undertaken to estimate the ground water recharge in Shankergarh block, Allahabad (India) during the year 2008. The data set used consisted of satellite derived rainfall and actual evapotranspiration and SCS-CN model estimated runoff values. The monthly values of the different components of water balance equation were estimated and subsequently the ground water rech...

In California, pre-emergence herbicide residues have been measured in runoff water from citrus orchards that resulted from winter rainfall. This study measured the effect of rainfall on the redistribution of herbicides within a citrus orchard and the effect that shallow mechanical incorporation had on residue movement. Simulated rainfall treatments were applied to plots within a citrus orchard ...

Rainfall patterns and land cover are two important factors that affect the runoff generation process. To determine the surface and subsurface flows associated with different rainfall patterns on sloping Ferralsols under different land cover types, observational data related to surface and subsurface flows from 5 m × 15 m plots were collected from 2010 to 2012. The experiment was conducted to as...

Excessive manure phosphorus (P) application increases risk of P loss from fields. This study assessed total runoff P (TPR), bioavailable P (BAP), and dissolved reactive P (DRP) concentrations and loads in surface runoff after liquid swine (Sus scrofa domesticus) manure application with or without incorporation into soil and different timing of rainfall. Four replicated manure P treatments were ...

Runoff forecasting in mountainous regions with processed based models is often difficult and inaccurate due to the complexity of the rainfall-runoff relationships and difficulties involved in obtaining the required data. Machine learning models offer an alternative for runoff forecasting in these regions. This paper explores and compares two machine learning methods, support vector regression (...