Faculty of Earth Sciences and Spatial Management, Nicolaus Copernicus University, Toruń, PolandHydrology Drought; Floods; Water Resources Management; Waterways; Hydropower Plants; Water Law
Katarzyna Kubiak-Wójcicka is an Assistant Professor in the Department of Hydrology and Water Management, Faculty of Earth Sciences and Spatial Management, Nicolaus Copernicus University in Torun (Poland). She obtained a PhD in Earth Sciences in the field of geography in 2006 at the Nicolaus Copernicus University in Toruń. Dr. Kubiak-Wójcicka’s research interests focus on the following issues: hydrological droughts, floods, water resource management, hydropower plants, water law, and water quality in river and reservoirs.
As global water resource pressures increase, efficient and precise water quality monitoring has become crucial. Traditional methods rely on manual sampling and laboratory analysis, which are time-consuming and labor-intensive, making real-time monitoring difficult. Recent advancements in artificial intelligence (AI), especially large language models (LLMs), have revolutionized water quality monitoring by extracting valuable information from vast amounts of real-time data and automatically generating detailed natural language reports, significantly enhancing monitoring efficiency and accuracy.
However, effectively transforming real-time water quality data into understandable and actionable natural language reports remains a challenge. This special issue aims to explore the latest research advancements and technical solutions in this field, particularly in automatic correlation analysis.
This special issue will cover, but is not limited to, the following topics:
- Showcase the latest technological advancements:
Introduce the latest technologies and methodologies in real-time water quality data analysis and natural language generation.
- Share practical application cases:
Provide successful application cases of these technologies to demonstrate their effectiveness in various environments.
- Discuss future development trends:
Explore the future development directions and potential impacts of automatic correlation analysis technologies.
- Address existing challenges:
Identify the challenges faced by current technologies in practical applications and propose possible solutions.
We invite experts in relevant fields to submit high-quality research papers, review articles, sharing their latest findings and insights in this cutting-edge area.