Forecasting the Colorado River Discharge Using an Artificial Neural Network (ANN) Approach

TL;DR

This paper evaluates an Artificial Neural Network model to predict Colorado River discharge based on climatic factors, aiding water resource management by accurately modeling complex hydrological relationships.

Contribution

It demonstrates the effectiveness of ANN in predicting river discharge using climatic parameters, providing a novel application for hydrological forecasting.

Findings

ANN accurately predicts river discharge based on climatic data

Climatic parameters significantly influence river flow predictions

The model enhances water resource planning accuracy

Abstract

Artificial Neural Network (ANN) based model is a computational approach commonly used for modeling the complex relationships between input and output parameters. Prediction of the flow rate of a river is a requisite for any successful water resource management and river basin planning. In the current survey, the effectiveness of an Artificial Neural Network was examined to predict the Colorado River discharge. In this modeling process, an ANN model was used to relate the discharge of the Colorado River to such parameters as the amount of precipitation, ambient temperature and snowpack level at a specific time of the year. The model was able to precisely study the impact of climatic parameters on the flow rate of the Colorado River.