Hydrology and Climate Change Article Summaries

VODNALA RAMYA (2026) Flood Forecasting by Using Machine Learning

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

Research Groups

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Short Summary

This paper proposes a machine learning-based system for flood forecasting that integrates historical and real-time environmental data to predict flood possibility or severity, aiming to overcome limitations of traditional methods.

Objective

Study Configuration

Methodology and Data

Main Results

The provided text describes the system's design and methodology but does not present specific results, performance metrics, or validation outcomes from its application.

Contributions

This work proposes an integrated system that combines environmental data, machine learning, predictive analytics, and early-warning mechanisms to enhance flood monitoring and forecasting, addressing the limitations of traditional methods in handling complex environmental relationships.

Funding

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Citation

@article{VODNALARAMYA2026Flood,
  author = {VODNALA RAMYA,DR. P. VENKATESHWARLU,DR. P. VENKATESHWARLU},
  title = {Flood Forecasting by Using Machine Learning},
  journal = {International Journal of Engineering Research and Science & Technology},
  year = {2026},
  url = {https://openalex.org/W7220827025}
}

Original Source: https://openalex.org/W7220827025