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Environmental Water Monitoring for Sustainable Development in Urban and Rural Areas

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Social Ecology and Sustainability".

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 18283

Special Issue Editors


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Assistant Guest Editor
Institute of Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, GR-118 10 Athens, Greece
Interests: earth observation; synthetic aperture radar; SAR interferometry; persistent scatterer interferometry; machine learning and information extraction; disaster management
Special Issues, Collections and Topics in MDPI journals

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Assistant Guest Editor
KIOS Research Centre, University of Cyprus (UCY), Nicosia, Cyprus
Interests: intelligent systems; smart water networks

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Chief Guest Editor
Centre for Research and Technology Hellas (CERTH), Information Technologies Institure (ITI), Thessaloniki, Greece
Interests: multimodal fusion; information retrieval; data mining in social media; earth observation

Special Issue Information

Dear Colleagues,

The United Nation’s Sustainable Development Goals are a universal call to action to end poverty, protect the planet and improve the lives and prospects of everyone, everywhere. The 17 Goals were adopted by all UN Member States in 2015, as part of the 2030 Agenda for Sustainable Development which set out a 15-year plan to achieve the Goals. Among these, Goal 6 refers to “Ensuring availability and sustainable management of water and sanitation for all”. This decomposes to focused targets, including the improvement of water quality by reducing pollution, increasing water-use efficiency across all sectors and ensure sustainable withdrawals and supply of freshwater to address water scarcity, implementing an integrated water resources management at all levels, and protecting and restoring water-related ecosystems, including mountains, forests, wetlands, rivers, aquifers and lakes.

To this end, new technologies have emerged for monitoring water resources over the last years, which aim to secure the society’s long-term resilience, stability, sustainability and security. According to Water Europe the challenges of the water sector are pertinent to water quality monitoring, water quantity monitoring, and mitigation of the effects of climate change, via monitoring the more frequent extreme weather events such as floods or severe drought periods. The abundance data on the monitoring of water resources is expected to create new emerging technologies and innovative Artificial Intelligence (AI) and big data analytics techniques for sustainable development in urban and rural areas.

This special issue aims to publish high-quality research papers on the inter-disciplinary field of real-time water quality and quantity monitoring, flood mapping and risk assessment, using low-cost sensors, satellite images, UAVs, CCTVs, photonic technologies and community-based in-situ observations from social media and crowdsourcing platforms. Big data analytics aim to extract meaningful insights and patterns from very large and heterogeneous data sources in water resource monitoring. Multimodal data fusion aims to effectively combine data and information from the abovementioned technologies. Semantic technologies may also offer novel mitigation strategies through the enrichment of extracted knowledge, interlinking and reasoning for decision-making. Moreover, model-based and simulation-based approaches can be considered to optimize the operation and reduce the risk of an unforeseen event. Novel methodologies, frameworks and tools should include both experimental evaluation and valuable recommendations for policymakers in the water sector.

Dr. Ilias Gialampoukidis
Dr. Stefanos Vrochidis
Dr. Ioannis Papoutsis
Dr. Demetris Eliadis
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. 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
  • water management
  • water scarcity
  • flash floods
  • climate change
  • sensor networks
  • crowdsourcing
  • earth observation

Published Papers (5 papers)

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Research

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14 pages, 1128 KiB  
Article
Assessment of Drinking Water Quality and Associated Socio-Economic Impacts in Arid Mountainous Regions
by Muhammad Asif Saeed, Ghulam Murtaza, Shafaqat Ali, Humera Aziz, Mohammed F. Albeshr, Shahid Mahboob, Irfan Manzoor, Zia Ur Rahman Farooqi, Muhammad Sabir, Hamaad Raza Ahmad, Ayesha Abdul Qadir and Muhammad Sajjad ur Rehman
Sustainability 2022, 14(19), 12567; https://doi.org/10.3390/su141912567 - 2 Oct 2022
Cited by 2 | Viewed by 1914
Abstract
We investigated the quality of drinking water and its possible effects on human health in the Dera Ghazi Khan (D. G. Khan) district of Pakistan. Samples were collected from three tehsils of the D. G. Khan district, namely D. G. Khan, Kot Chutta, [...] Read more.
We investigated the quality of drinking water and its possible effects on human health in the Dera Ghazi Khan (D. G. Khan) district of Pakistan. Samples were collected from three tehsils of the D. G. Khan district, namely D. G. Khan, Kot Chutta, and Taunsa. A total of 50 samples (n = 50) were collected from the study area using standard procedures. The pH of the water samples ranged from 6.52–8.75, EC 0.31–9.78 dS m−1, and TDS 105–985 mg L−1. The bacterial analysis showed that 9 out of 50 samples (18%) contained pathogenic E. coli bacterial. The results showed that the pH and EC values of some sampling sites exceeded the WHO guidelines for drinking water. It was observed that the pH of only 1 sample, and the EC of 18 samples in D. G. Khan—5 in Kot Chutta and 16 in Tehsil Taunsa—exceeded the WHO guidelines. In terms of E. coli presence and related diseases (hepatitis A, B, and C), we collected data, which were screened and belonged to the sampling sites, from 1378 patients receiving treatment related to hepatitis A, B, and C. It was revealed that 530 patients belonged to the D. G. Khan site, followed by Taunsa (460), and Kot Chutta (388). Based on the results, it was concluded that the quality of drinking water samples generally was good, except for 6% of the samples, assessed using (SAR) and Kelly’s ratio (KR), and 9 sites were positive for E. coli. Full article
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12 pages, 1171 KiB  
Article
Assessment of Arsenic Contamination in Groundwater and Associated Human Health Risk
by Rana Muhammad Yasir Riaz, Ghulam Murtaza, Zia Ur Rahman Farooqi, Shafaqat Ali, Humera Aziz, Shahid Mahboob, Khalid A. Al-Ghanim, Gary Owens, Hamaad Raza Ahmad and Umair Riaz
Sustainability 2022, 14(19), 12460; https://doi.org/10.3390/su141912460 - 30 Sep 2022
Cited by 7 | Viewed by 2167
Abstract
Drinking water contamination by arsenic (As) is of significant concern due to its potential cause of cancer and arsenicosis. In this study, out of the 200 samples (n = 200), the mean As concentrations ranged from below detection limit (BDL) to 3.30, [...] Read more.
Drinking water contamination by arsenic (As) is of significant concern due to its potential cause of cancer and arsenicosis. In this study, out of the 200 samples (n = 200), the mean As concentrations ranged from below detection limit (BDL) to 3.30, 4.81, 4.42 and 3.85 µg L−1 in small residential, roadside, industrial and household areas, respectively. From 200 total samples, 9% of the groundwater samples showed As levels higher than the WHO safe guideline limit of 10 μg L−1. Human health risk was assessed using average daily intake (ADD), hazard quotient (HQ) and cancer risk (CR) values which were found to be greater than the recommended values by the United States Environmental Protection Agency (1.0 and 10−6) for health risk assessment. The CR were ranged from 0–5.7 × 10−1, 4.0 × 10−1, 2.0 × 10−1 and 1.0 × 10−1 in small residential areas for children, adolescents, males and females, respectively. In roadside areas, the values ranged from 0–2.8 × 10−1, 4.0 × 10−1, 2.0 × 10−1 and 2.8 × 10−1 for children, adolescents, males and females, while 0–5.9 × 10−1, 4.1 × 10−1, 2.1 × 10−1 and 1.6 × 10−1 in industrial areas and 0–8.0 × 10−1, 2.91 × 10−1, 2.6 × 10−1 and 3.9 × 10−1 were calculated in household sites. All the CR values were found to be exceeding the US-EPA limit (10−6) recommending that the people in the study area are more prone to carcinogenic risk. Overall, it was concluded that due to presence of As in drinking water, these areas tend to be at higher cancer risks. To provide safe drinking water for the people living in these As-affected areas, urgent remedial and management steps are required. Full article
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23 pages, 28548 KiB  
Article
A Vision-Based Motion Control Framework for Water Quality Monitoring Using an Unmanned Aerial Vehicle
by Fotis Panetsos, Panagiotis Rousseas, George Karras, Charalampos Bechlioulis and Kostas J. Kyriakopoulos
Sustainability 2022, 14(11), 6502; https://doi.org/10.3390/su14116502 - 26 May 2022
Cited by 1 | Viewed by 1587
Abstract
In this paper, we present a vision-aided motion planning and control framework for the efficient monitoring and surveillance of water surfaces using an Unmanned Aerial Vehicle (UAV). The ultimate goal of the proposed strategy is to equip the UAV with the necessary autonomy [...] Read more.
In this paper, we present a vision-aided motion planning and control framework for the efficient monitoring and surveillance of water surfaces using an Unmanned Aerial Vehicle (UAV). The ultimate goal of the proposed strategy is to equip the UAV with the necessary autonomy and decision-making capabilities to support First Responders during emergency water contamination incidents. Toward this direction, we propose an end-to-end solution, based on which the First Responder indicates visiting and landing waypoints, while the envisioned strategy is responsible for the safe and autonomous navigation of the UAV, the refinement of the way-point locations that maximize the visible water surface area from the onboard camera, as well as the on-site refinement of the appropriate landing region in harsh environments. More specifically, we develop an efficient waypoint-tracking motion-planning scheme with guaranteed collision avoidance, a local autonomous exploration algorithm for refining the way-point location with respect to the areas visible to the drone’s camera, water, a vision-based algorithm for the on-site area selection for feasible landing and finally, a model predictive motion controller for the landing procedure. The efficacy of the proposed framework is demonstrated via a set of simulated and experimental scenarios using an octorotor UAV. Full article
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28 pages, 14863 KiB  
Article
Flood Hazard and Risk Mapping by Applying an Explainable Machine Learning Framework Using Satellite Imagery and GIS Data
by Gerasimos Antzoulatos, Ioannis-Omiros Kouloglou, Marios Bakratsas, Anastasia Moumtzidou, Ilias Gialampoukidis, Anastasios Karakostas, Francesca Lombardo, Roberto Fiorin, Daniele Norbiato, Michele Ferri, Andreas Symeonidis, Stefanos Vrochidis and Ioannis Kompatsiaris
Sustainability 2022, 14(6), 3251; https://doi.org/10.3390/su14063251 - 10 Mar 2022
Cited by 27 | Viewed by 5441
Abstract
Flooding is one of the most destructive natural phenomena that happen worldwide, leading to the damage of property and infrastructure or even the loss of lives. The escalation in the intensity and number of flooding events as a result of the combination of [...] Read more.
Flooding is one of the most destructive natural phenomena that happen worldwide, leading to the damage of property and infrastructure or even the loss of lives. The escalation in the intensity and number of flooding events as a result of the combination of climate change and anthropogenic factors motivates the need to adopt real-time solutions for mapping flood hazards and risks. In this study, a methodological framework is proposed that enables the assessment of flood hazard and risk levels of severity dynamically by fusing optical remote sensing (Sentinel-1) and GIS-based data from the region of the Trieste, Monfalcone and Muggia Municipalities. Explainable machine learning techniques were utilised, aiming to interpret the results for the assessment of flood hazard. The flood inventory was randomly divided into 70%, used for training, and 30%, employed for testing. Various combinations of the models were evaluated for the assessment of flood hazard. The results revealed that the Random Forest model achieved the highest F1-score (approx. 0.99), among others utilised for generating flood hazard maps. Furthermore, the estimation of the flood risk was achieved by a combination of a rule-based approach to estimate the exposure and vulnerability with the dynamic assessment of flood hazard. Full article
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Review

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25 pages, 7835 KiB  
Review
Modern Analytical Techniques for Detection of Bacteria in Surface and Wastewaters
by Alexandra Canciu, Mihaela Tertis, Oana Hosu, Andreea Cernat, Cecilia Cristea and Florin Graur
Sustainability 2021, 13(13), 7229; https://doi.org/10.3390/su13137229 - 28 Jun 2021
Cited by 20 | Viewed by 5840
Abstract
Contamination of surface waters with pathogens as well as all diseases associated with such events are a significant concern worldwide. In recent decades, there has been a growing interest in developing analytical methods with good performance for the detection of this category of [...] Read more.
Contamination of surface waters with pathogens as well as all diseases associated with such events are a significant concern worldwide. In recent decades, there has been a growing interest in developing analytical methods with good performance for the detection of this category of contaminants. The most important analytical methods applied for the determination of bacteria in waters are traditional ones (such as bacterial culturing methods, enzyme-linked immunoassay, polymerase chain reaction, and loop-mediated isothermal amplification) and advanced alternative methods (such as spectrometry, chromatography, capillary electrophoresis, surface-enhanced Raman scattering, and magnetic field-assisted and hyphenated techniques). In addition, optical and electrochemical sensors have gained much attention as essential alternatives for the conventional detection of bacteria. The large number of available methods have been materialized by many publications in this field aimed to ensure the control of water quality in water resources. This study represents a critical synthesis of the literature regarding the latest analytical methods covering comparative aspects of pathogen contamination of water resources. All these aspects are presented as representative examples, focusing on two important bacteria with essential implications on the health of the population, namely Pseudomonas aeruginosa and Escherichia coli. Full article
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