Forecasting the Colorado River Discharge Using an Artificial Neural Network (ANN) Approach
This work addresses water resource management for river basin planning, but it is incremental as it applies an existing ANN method to a specific dataset.
The researchers tackled the problem of predicting Colorado River discharge by developing an Artificial Neural Network model that relates discharge to precipitation, temperature, and snowpack, achieving precise analysis of climatic impacts.
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.