Reservoir Outflow Forecasting.pdf

nhess-2022-171-manuscript-version3.pdf
Preview of Reservoir Outflow Forecasting
🔗 Source: nhess.copernicus.org
📊 Size: 2.48 MB
👤 Author: Martin Rasmussen
⬇️ Downloads: 108

Summary

Reservoirs manage water resources, supply water, produce hydropower, and mitigate floods. Machine learning techniques, including multivariate linear regression (MLR), multilayer perceptron (MLP), nonlinear autoregressive exogenous (NARX), and long short-term memory (LSTM), are used to forecast reservoir outflow. These techniques are applied to eight water reservoirs in the Miño River, Spain, and the results show that the proposed models provide good outflow estimations, with NARX being the best option on average.

Description

Reservoirs manage water resources, supply water, produce hydropower, and mitigate floods.

Technical Information

  • File Format: PDF
  • File Size: 2.48 MB
  • Pages: 29
  • Language: EN
  • Author: Martin Rasmussen
  • Total Downloads: 108
  • Last Updated: 1 week ago

Document Overview

This PDF document about Reservoir Outflow Forecasting provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Reservoir Outflow Forecasting.

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