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Monitoring, Controlling, and Management of Water Quality

This special issue belongs to the section “Resources and Sustainable Utilization“.

Special Issue Information

Dear Colleagues,

Water security is a pressing issue in our society, with both water quantity and quality playing crucial roles. However, water quality is often overlooked over water quantity, resulting in the degradation of ecosystems and multiple health, as well as environmental, consequences. The ever-increasing threats to water quality are complicated by population growth, increasing economic activities, climate change, land use development, and technological advancements, such as the conversion of forested areas into commercial or residential areas, increasing the impervious surface cover resulting from the alteration of magnitude and volume of surface runoff, leading to the transportation of more nutrients, metals, pharmaceuticals, and toxic substances into waterways. Therefore, the improvement of water quality is one of the highest-ranking agendas endorsed by the United Nations, due to the looming global water crisis. In order to secure our future generations’ availability of adequate and safe freshwater, additional research regarding water quality is the need of the hour to fulfill the daunting task. Consequently, the goal of this Special Issue is to gather both contemporary as well as emerging techniques in water quality research in one location, making access convenient for researchers and policymakers.

This Special Issue ranges from a wide spectrum of topics, including water quality monitoring, water quality modeling as well as water quality policies (water quality management). Water quality monitoring consists of long-term in situ platforms (nutrient sensors), remote sensing systems (Landsat, Sentinel, Modis) as well as airborne imagery sensors (drone with camera) for various water quality parameters such as nutrients, harmful algal blooms, sediments, etc. Water quality modeling includes physically based watershed-scale models, empirical models as well as relatively new machine learning approaches to recommend research outcomes to policymakers on a large-scale basis. The water quality policies consist of a cost-benefit analysis to differentiate between existing water quality policies to assess their values to societies. The overarching goal of this Special Issue is to capture the new paradigms of water quality research and, therefore, I invite all my colleagues to contribute their innovative concepts of water quality research.

Dr. Subhasis Giri
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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.

Keywords

  • water quality monitoring
  • climate change
  • harmful algal bloom
  • remote sensing
  • watershed modeling
  • machine learning
  • cost-benefit analysis

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Sustainability - ISSN 2071-1050