Artificial Intelligence in Water Resources Management
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".
Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 15331
Special Issue Editors
Interests: water resource management; hydrological analysis; impact of climate change; soft computing techniques; explainable artificial intelligence; catchment analysis
Special Issues, Collections and Topics in MDPI journals
Interests: urban water management; resilient urban water systems; climate change mitigation; nature based solutions; sustainable and liveable cities; machine learning techniques
Special Issues, Collections and Topics in MDPI journals
Interests: climate change; coastal disasters; vulnerable mapping; sustainability
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) plays an important role in predicting the majority of non-linear scenarios in engineering applications. Out of them, water resources management is significant due to its non-linear applications, including flash floods, drinking water supply, wastewater treatment, hydropower development, irrigation, etc. Therefore, the usage of AI systems in water resources management is quite popular in today’s world. Nevertheless, the research depth of AI is being further developed along with new advances, including the expandability of AI. Therefore, the outcomes are evolving, and better solutions to non-linear systems in water resources management are being promoted. Therefore, this Special Issue proposes to publish novel research views of AI in water resource management and to form a discussion forum where researchers can share their state-of-the-art findings.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Prediction of flash floods under changing climatic scenarios;
- Natural disasters involved in hydrological cycle;
- Irrigation water management;
- Hydropower development under climatic scenarios;
- Drinking water supply systems;
- Energy enhancing through water supply systems;
- Wastewater system management;
- Wastewater treatment operation.
We look forward to receiving your contributions.
Prof. Dr. Upaka Rathnayake
Dr. Nitin Muttil
Dr. Komali Kantamaneni
Guest Editors
Manuscript Submission Information
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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
- machine learning approaches
- expandability
- soft computing approaches
- water resources
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