Estimating the potential water reuse based on fuzzy reasoning.

Area of Science:

• Environmental Science
• Water Resource Management
• Climate Change Adaptation

Background:

• Global climate change is exacerbating water scarcity in many regions.
• Treated wastewater offers a viable alternative water resource for non-potable uses, particularly in arid areas.
• Effective decision support tools are crucial for anticipating and mitigating future water supply challenges.

Purpose of the Study:

• To develop a decision support system (DSS) for assessing current water reuse potential.
• To identify key variables influencing wastewater reclamation levels.
• To support governmental planning for water resource management under climate change.

Main Methods:

• Utilized a fuzzy inference system (FIS) as the core analytical tool.
• Employed a multi-criteria decision-making approach for conceptual framework.
• Constructed a dataset analyzing 155 regions and 183 cities, incorporating factors like drought, water exploitation, usage, population density, and treatment rates.

Main Results:

• Identified a correlation between water reuse levels and environmental factors including drought, water exploitation index, water use, population density, and wastewater treatment rates.
• The FIS demonstrated suitability in identifying water reuse trends, despite minor discrepancies in agricultural and urban potential classification.
• The system successfully analyzed water reuse potential across numerous geographical areas.

Conclusions:

• The developed DSS effectively identifies water reuse potential and trends.
• Findings highlight the importance of environmental and anthropogenic factors in determining water reclamation viability.
• This tool provides critical information for proactive decision-making to address future water shortages driven by climate change.