Ghosh et al. (2025) Water Withdrawal Trends Across Multiple UN Member Nations Using Time Series Forecasting

Identification

• Journal: Lecture notes in networks and systems
• Year: 2025
• Date: 2025-11-22
• Authors: Mainak Ghosh, Paramita Ray, Joydeep Mukherjee, Amlan Chakrabarti
• DOI: 10.1007/978-981-96-5860-2_18

Research Groups

• Department of Computer Science and Engineering, Adamas University, Kolkata, West Bengal, India
• Department of Computer Science and Engineering, SRM University, AP, Guntur, India
• A.K. Choudhury School of Information Technology, University of Calcutta, Kolkata, West Bengal, India

Short Summary

This study comprehensively analyzes historical freshwater withdrawal patterns in six UN member nations using the ARIMA time series model to identify driving factors and forecast future water demands, revealing significant inter-country differences and the need for proactive policy interventions.

Objective

• To comprehensively analyze freshwater withdrawal patterns, explore time-related trends, identify driving factors, and forecast future water demands in China, France, India, Russia, United Kingdom, and the United States.

Study Configuration

• Spatial Scale: Six UN member countries: China, France, India, Russia, United Kingdom, and the United States.
• Temporal Scale: Analysis of historical data and forecasting of future water demands.

Methodology and Data

• Models used: ARIMA (Autoregressive Integrated Moving Average) model.
• Data sources: Historical freshwater withdrawal data.

Main Results

• Significant differences were observed among the six countries in their water withdrawal patterns and the primary drivers, which include agricultural practices, industrial activities, demographic growth, and governmental policies.
• The ARIMA model successfully represented customized water usage for each country and provided reliable forecasts, highlighting future challenges and opportunities for water resource management.

Contributions

• Provides a comprehensive, multi-national analysis of freshwater withdrawal trends and their underlying drivers.
• Utilizes the ARIMA model to generate country-specific, reliable forecasts for future water demands.
• Underscores the necessity for proactive policy interventions to promote sustainable water use in the context of rising demand and environmental variability.

Funding

• Not explicitly stated in the provided paper text.

Citation

@article{Ghosh2025Water,
  author = {Ghosh, Mainak and Ray, Paramita and Mukherjee, Joydeep and Chakrabarti, Amlan},
  title = {Water Withdrawal Trends Across Multiple UN Member Nations Using Time Series Forecasting},
  journal = {Lecture notes in networks and systems},
  year = {2025},
  doi = {10.1007/978-981-96-5860-2_18},
  url = {https://doi.org/10.1007/978-981-96-5860-2_18}
}