Applications of Remote Sensing and Machine Learning in Water Resources Management
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".
Deadline for manuscript submissions: closed (25 October 2024) | Viewed by 4843
Special Issue Editors
Interests: water resources management; computational ecohydrology; soil and water conservation; environmental impact assessment; machine learning applications
Special Issues, Collections and Topics in MDPI journals
Interests: water resources management; drought analysis; remote sensing; hydrology; sustainable agriculture; soil moisture
Special Issue Information
Dear Colleagues,
I cordially invite you to contribute to the Special Issue in the open access journal Water, entitled “Applications of Remote Sensing and Machine Learning in Water Resources Management”.
Water resources management addresses complex issues in the control of such resources available on Earth. Countries establish systems and regulations that oversee water for a variety of uses. When water resources are managed well, communities and governments benefit; if they are not, serious global consequences ensue. Adequate water resources management requires accurate assessment and prediction using advanced and effective techniques (e.g., machine learning, remote sensing, etc.). Thus, this Special Issue offers researchers the opportunity to share their achievements in the following topics using remote sensing and machine learning:
- Surface and groundwater interactions for watershed management;
- Advancement of watershed management modelling;
- Quantitative analysis of floods or droughts;
- Computational advances in water resources modelling;
- Analysis of water use and water availability;
- Sustainable water resources for agriculture;
- Potential and limitations of natural-based solutions (NBS) to water resources management;
- The impact of climatic changes on water resources management;
- Retrospective urban inundation modelling;
- Advancement in urban inundation forecasting technique;
- Validation of satellite products related to water resources (e.g., soil moisture and vegetation indices);
- Development of innovative numerical techniques for integrating machine learning with satellite-based remote sensing data to enhance drought monitoring and forecasting;
- Other topics related to water resources management.
Dr. Won Seok Jang
Dr. Jiwan Lee
Dr. Seungsoo Lee
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. Water 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 2600 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
- climate change
- droughts
- evapotranspiration
- floods
- forecasting
- hydrological drought indices
- machine learning
- modelling
- real-time forecasting
- remote sensing
- soil moisture
- sustainable water resources
- urban inundation
- watershed management
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