Vasudeva et al. (2025) Forecasting Future Water Requirements and Assessing Storage Capacities in Reservoirs

Identification

• Journal: Lecture notes in networks and systems
• Year: 2025
• Date: 2025-11-22
• Authors: H. G. Vasudeva, Geeta Kumar, Meeradevi, V. K. Abhishek, Vishal Nandyal
• DOI: 10.1007/978-981-96-8750-3_7

Research Groups

• Department of AI&ML, Ramaiah Institute of Technology, Bangalore, India
• Department of AI&DS, Ramaiah Institute of Technology, Bangalore, India

Short Summary

This study develops predictive models using data science techniques, time-series forecasting, machine learning, and optimization strategies to forecast future water requirements and assess reservoir storage capacities for sustainable water management.

Objective

• To comprehensively analyze water resource data and develop predictive models for forecasting future water requirements and evaluating reservoir storage capacities to ensure effective and sustainable water management.

Study Configuration

• Spatial Scale: Not explicitly defined in the provided text.
• Temporal Scale: Utilizes historical data for prediction to address short-term demands and long-term sustainability.

Methodology and Data

• Models used: Time-series forecasting, machine learning models, advanced statistical models, and optimization strategies.
• Data sources: Comprehensive water resource data, including historical data on rainfall, evapotranspiration, domestic usage, industrial usage, and agricultural demands.

Main Results

• Predictive models were developed for forecasting future water requirements.
• Reservoir storage capacities were evaluated to determine their adequacy in meeting projected demands.
• The integration of forecasting with capacity assessment provides actionable insights for enhancing decision-making in sustainable water management.

Contributions

• Proposes a multi-faceted approach combining time-series forecasting, machine learning, and optimization strategies for water resource management.
• Integrates water requirement forecasting with reservoir capacity assessment to provide actionable insights for sustainable decision-making.
• Addresses the challenge of increasing water demand due to global population growth, industrialization, urbanization, and climate variability.

Funding

• Not explicitly mentioned in the provided text.

Citation

@article{Vasudeva2025Forecasting,
  author = {Vasudeva, H. G. and Kumar, Geeta and Meeradevi and Abhishek, V. K. and Nandyal, Vishal},
  title = {Forecasting Future Water Requirements and Assessing Storage Capacities in Reservoirs},
  journal = {Lecture notes in networks and systems},
  year = {2025},
  doi = {10.1007/978-981-96-8750-3_7},
  url = {https://doi.org/10.1007/978-981-96-8750-3_7}
}