Novel Procedures and Methodologies for Surface and Underground Water Quality Analysis: Theory and Application

Dear Colleagues,

Water quality is a critical factor for sustaining human activities and ecological balance. Both surface and underground water resources are subject to significant influences from natural and anthropogenic activities, which affect the maximum allowable concentrations of various water quality parameters. Considering these multifaceted impacts, this Special Issue addresses the pressing need for advanced methodologies to predict future water quality levels and analyze the current conditions. We invite contributions exploring predictive modeling techniques for forecasting water quality, focusing on integrating physical-based models with time series analysis, artificial intelligence (AI) and machine learning (ML) methods. Papers that assess the chemical and physical parameters of surface and underground water and examine the effects of anthropogenic activities, such as industrial discharge and agricultural runoff, are welcome.

Compared to the standard time series modeling procedures used in the past, artificial intelligence and machine learning have raised the level of knowledge and experience obtained. Despite that, a combination of the above is strongly welcomed in this Special Issue.

This Special Issue seeks to compile groundbreaking research that enhances our understanding of the complex interactions affecting water quality. By leveraging modern technological advancements, the collected works aim to provide valuable insights and innovative solutions for sustainable water resource management. We encourage submissions from researchers and practitioners developing these advanced analytical frameworks to contribute to this critical discourse.

This Special Issue tends to collect papers dealing with surface and underground water quality chemical and physical parameter analysis using time series modeling, artificial intelligence and machine learning to assess the impact of meteorological parameters.

This Special Issue will welcome manuscripts that link the following themes:

• Predictive modeling for future water quality levels;
• Assessment of the current water quality conditions;
• Integration of time series analysis techniques;
• Utilization of artificial intelligence in water quality assessment;
• Application of machine learning methods;
• Analysis of surface water quality parameters;
• Examination of underground water quality parameters;
• Consideration of anthropogenic impacts on water resources;
• Incorporation of meteorological factors in water quality assessment;
• Improving understanding of natural and human-induced effects on water quality.

We look forward to receiving your original research articles and reviews.

Dr. Bojan Đurin
Dr. Osman Fetoshi
Dr. Gabriel-Ionut Plavan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Hydrology is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• water quality analysis
• groundwater
• surface water
• parameters
• machine learning
• artificial intelligence
• water resources