Innovative Trends to Reshape the Water Science, Technology and Engineering

A special issue of Water (ISSN 2073-4441).

Deadline for manuscript submissions: 20 June 2025 | Viewed by 3725

Special Issue Editor


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Guest Editor
Department of Civil Engineering, Architecture and Environment, CERIS, Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, Portugal
Interests: hydropower; hydraulic transients; pumped-storage; water and energy nexus; hydrodynamic; renewables integration; water-energy efficiency
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Special Issue Information

Dear Colleagues,

This Special Issue comprises selected papers from the Proceedings of the 8th International Electronic Conference on Water Science (ECWS-8), held from 14 to 16 October 2024 on sciforum.net, an online platform for hosting scholarly e-conferences and discussion groups.

The ECWS-8 will be a conference to explore and discuss the following key issues: adaptive water resources management; new technologies in the water science; enhancement of water safety and security for humans, their economic activities and the environment; and the formulation of new numerical methods and structures for water resources adaptation, management and development.

The ECWS-8 invites researchers from academia, as well as water practitioners, to contribute original findings, novel ideas, scientific concepts and new technologies and experiences.

Papers for this Special Issue, entitled “Innovative Trends to Reshape the Water Science, Technology and Engineering”, will include but are not limited to the following topics:

  1. Rivers, Dams and Reservoirs;
  2. Hydrodynamics, Hydraulic Transients, Hydropower and Pumped Storage in Water-Energy Nexus;
  3. Estuaries, Coasts and Ports;
  4. Urban Water, Systems Efficiency and Smart Water Grids and Technology;
  5. Numerical and Experimental Methods, Data Analyses, Digital Twin, IoT Machine Learning and AI in Water Sciences;
  6. Water Resources Management, Floods and Risk Mitigation.

Prof. Dr. Helena M. Ramos
Guest Editor

Manuscript Submission Information

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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

  • river, dam and reservoir conservation
  • hydrodynamics
  • hydraulic transients
  • hydropower
  • pumped storage
  • energy-water nexus
  • energy and water efficiency
  • estuaries, coasts and ports management
  • urban water
  • water systems
  • smart water grids
  • numerical and experimental methods
  • data analyses in water science
  • digital twin in water science
  • IoT in water science
  • machine learning in water science
  • AI in water science
  • water resources management
  • floods and risk mitigation

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Published Papers (2 papers)

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Research

13 pages, 2014 KiB  
Article
Prediction of Blue-Green Algae Cells in a City Water Source Based on the LSTM Model
by Liangzhi Sun, Yangyang Chu, Hui Li, Xiaomeng Han and Shihu Shu
Water 2025, 17(2), 237; https://doi.org/10.3390/w17020237 - 16 Jan 2025
Viewed by 401
Abstract
China’s freshwater resources are relatively small per capita, and the traditional passive control of hydrographic outbreaks can no longer meet modern water management needs. Data-driven models, such as Long Short-Term Memory Networks (LSTMs), have been gradually applied to water resources management, but most [...] Read more.
China’s freshwater resources are relatively small per capita, and the traditional passive control of hydrographic outbreaks can no longer meet modern water management needs. Data-driven models, such as Long Short-Term Memory Networks (LSTMs), have been gradually applied to water resources management, but most of the research has focused on the enhancement of the prediction effect of hybrid models while neglecting the importance of data structure. In this study, we predicted the number of dominant algae (blue-green algae) in a water source based on LSTM and explored the effects of different feature combinations and time window steps on the prediction performance. It was found that the model prediction was significantly improved by adding multiple features, and the R2 improved by 31.98% compared with single feature prediction. Meanwhile, as the time window (T-value) increased from 7 to 300, the R2 improved by 0.4%, but the iteration time increased by 96%. The results suggested that appropriate input feature selection is beneficial for model prediction, while longer time windows led to reduced model prediction benefits. Lastly, this study offers insights into future research directions from three key dimensions: the input indicator, optimization algorithm, and model combination. Full article
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33 pages, 12193 KiB  
Article
Energy Transition in Urban Water Infrastructures towards Sustainable Cities
by Helena M. Ramos, Modesto Pérez-Sánchez, Prajwal S. M. Guruprasad, Armando Carravetta, Alban Kuriqi, Oscar E. Coronado-Hernández, João F. P. Fernandes, Paulo J. Costa Branco and Petra Amparo López-Jiménez
Water 2024, 16(3), 504; https://doi.org/10.3390/w16030504 - 4 Feb 2024
Cited by 3 | Viewed by 2067
Abstract
The world’s water infrastructures suffer from inefficiencies, such as high energy consumption and water losses due to inadequate management practices and feeble pressure regulation, leading to frequent water and energy losses. This strains vital water and energy resources, especially in the face of [...] Read more.
The world’s water infrastructures suffer from inefficiencies, such as high energy consumption and water losses due to inadequate management practices and feeble pressure regulation, leading to frequent water and energy losses. This strains vital water and energy resources, especially in the face of the worsening challenges of climate change and population growth. A novel method is presented that integrates micro-hydropower plants, with pumps as turbines (PATs), in the water network in the city of Funchal. Sensitivity analyses evaluated the microgrid’s response to variations in the cost of energy components, showing favorable outcomes with positive net present value (NPV). PV solar and micro-wind turbines installed exclusively at the selected PRV sites within the Funchal hydro grid generate a combined 153 and 55 MWh/year, respectively, supplementing the 406 MWh/year generated by PATs. It should be noted that PATs consistently have the lowest cost of electricity (LCOE), confirming their economic viability and efficiency across different scenarios, even after accounting for reductions in alternative energy sources and grid infrastructure costs. Full article
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