Water

21 pages, 81233 KiB

Open AccessEditor’s ChoiceArticle

Recharge and Geochemical Evolution of Groundwater in Fractured Basement Aquifers (NW India): Insights from Environmental Isotopes (δ¹⁸O, δ²H, and ³H) and Hydrogeochemical Studies

by Rudra Mohan Pradhan, Ajit Kumar Behera, Sudhir Kumar, Pankaj Kumar and Tapas Kumar Biswal

Water 2022, 14(3), 315; https://doi.org/10.3390/w14030315 - 21 Jan 2022

Cited by 15 | Viewed by 4710

Abstract

Considering water as a limiting factor for socio-economic development, especially in arid/semi-arid regions, both scientific communities and policymakers are interested in groundwater recharge-related data. India is fast moving toward a crisis of groundwater due to intense abstraction and contamination. There is a lack [...] Read more.

Considering water as a limiting factor for socio-economic development, especially in arid/semi-arid regions, both scientific communities and policymakers are interested in groundwater recharge-related data. India is fast moving toward a crisis of groundwater due to intense abstraction and contamination. There is a lack of understanding regarding the occurrence, movement, and behaviors of groundwater in a fractured basement terrane. Therefore, integrated environmental isotopes (δ¹⁸O, δ²H, and ³H) and hydrogeochemical studies have been used to understand the recharge processes and geochemical evolution of groundwater in the fractured basement terranes of Gujarat, NW India. Our results show that the relative abundance of major cations and anions in the study basin are Ca²⁺ > Na⁺ > Mg²⁺ > K⁺ and HCO₃⁻ > Cl⁻ > SO₄²⁻ > NO₃⁻, respectively. This suggests that the chemical weathering of silicate minerals influences the groundwater chemistry in the aquifer system. A change in hydrochemical facies from Ca-HCO₃ to Na-Mg-Ca-Cl. HCO₃ has been identified from the recharge to discharge areas. Along the groundwater flow direction, the presence of chemical constituents with different concentrations demonstrates that the various geochemical mechanisms are responsible for this geochemical evolution. Furthermore, the chemical composition of groundwater also reflects that the groundwater has interacted with distinct rock types (granites/granulites). The stable isotopes (δ¹⁸O and δ²H) of groundwater reveal that the local precipitation is the main source of recharge. However, the groundwater recharge is affected by the evaporation process due to different geological conditions irrespective of topographical differences in the study area. The tritium (³H) content of groundwater suggests that the aquifer is mainly recharged by modern rainfall events. Thus, in semi-arid regions, the geology, weathering, and geologic structures have a significant role in bringing chemical changes in groundwater and smoothening the recharge process. The findings of this study will prove vital for the decision-makers or policymakers to take appropriate measures to design water budgets as well as water management plans more sustainably. Full article

(This article belongs to the Special Issue Water Resource Management through the Lens of Planetary Health Approach)

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36 pages, 4856 KiB

Open AccessFeature PaperEditor’s ChoiceReview

IoT-Based Solutions to Monitor Water Level, Leakage, and Motor Control for Smart Water Tanks

by Farmanullah Jan, Nasro Min-Allah, Saqib Saeed, Sardar Zafar Iqbal and Rashad Ahmed

Water 2022, 14(3), 309; https://doi.org/10.3390/w14030309 - 20 Jan 2022

Cited by 36 | Viewed by 32549

Abstract

Today, a large portion of the human population around the globe has no access to freshwater for drinking, cooking, and other domestic applications. Water resources in numerous countries are becoming scarce due to over urbanization, rapid industrial growth, and current global warming. Water [...] Read more.

Today, a large portion of the human population around the globe has no access to freshwater for drinking, cooking, and other domestic applications. Water resources in numerous countries are becoming scarce due to over urbanization, rapid industrial growth, and current global warming. Water is often stored in the aboveground or underground tanks. In developing countries, these tanks are maintained manually, and in some cases, water is wasted due to human negligence. In addition, water could also leak out from tanks and supply pipes due to the decayed infrastructure. To address these issues, researchers worldwide turned to the Internet-of-Things (IoT) technology to efficiently monitor water levels, detect leakage, and auto refill tanks whenever needed. Notably, this technology can also supply real-time feedback to end-users and other experts through a webpage or a smartphone. Literature reveals a plethora of review articles on smart water monitoring, including water quality, supply pipes leakage, and water waste recycling. However, none of the reviews focus on the IoT-based solution to monitor water level, detect water leakage, and auto control water pumps, especially at the induvial level that form a vast proportion of water consumers worldwide. To fill this gap in the literature, this study presents a review of IoT-controlled water storage tanks (IoT-WST). Some important contributions of our work include surveying contemporary work on IoT-WST, elaborating current techniques and technologies in IoT-WST, targeting proper hardware, and selecting a secure IoT cloud server. Full article

(This article belongs to the Special Issue Water Quality Engineering and Wastewater Treatment Ⅱ)

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14 pages, 1770 KiB

Open AccessEditor’s ChoiceArticle

Method Development for Low-Concentration PAHs Analysis in Seawater to Evaluate the Impact of Ship Scrubber Washwater Effluents

by Chih-Feng Chen, Yee Cheng Lim, Yun-Ru Ju, Frank Paolo Jay B. Albarico, Jia-Wei Cheng, Chiu-Wen Chen and Cheng-Di Dong

Water 2022, 14(3), 287; https://doi.org/10.3390/w14030287 - 19 Jan 2022

Cited by 13 | Viewed by 2806

Abstract

A naval ship’s exhaust gas scrubber may discharge polycyclic aromatic hydrocarbons (PAHs) into seawater. Due to the high lipophilicity and low water solubility of PAHs, their concentrations in seawater are extremely low, making them difficult to detect or accurately determine. To accurately assess [...] Read more.

A naval ship’s exhaust gas scrubber may discharge polycyclic aromatic hydrocarbons (PAHs) into seawater. Due to the high lipophilicity and low water solubility of PAHs, their concentrations in seawater are extremely low, making them difficult to detect or accurately determine. To accurately assess the impact of scrubber washwater effluent on the PAHs concentration of seawater, appropriate analysis methods must be established. In this study, a large-volume pre-concentration water sampler was used onboard to concentrate PAHs in surface seawater (100 L) from four sites offshore of southern Taiwan. The quantitative and qualitative analysis of dissolved PAHs in seawater and quality control samples were implemented using a GC/MS system with the aid of internal and surrogate standards. Results showed that the field and equipment blank samples of quality control samples were lower than twice the detection limit. The detection limit of individual PAHs is between 0.001 (naphthalene, NA) and 0.014 ng/L (dibenzo[a,h]anthracene, DBA), which meets the requirements for evaluating PAHs in seawater (that is, less than the maximum permissible concentrations (MPCs)). The concentration of total PAHs (TPAHs) in the four seawater samples ranged from 2.297 to 4.001 ng/L and had an average concentration of 3.056 ± 0.727 ng/L. The concentrations of 16 PAHs were determined in each seawater sample, indicating that the analytical method in this study is suitable for the determination of low-concentration PAHs in seawater. Phenanthrene (PHE) is the most dominant compound in seawater samples accounting for 59.6 ± 12.6% of TPAHs, followed by fluorine (FL) accounting for 8.5 ± 3.7%. The contribution of high-ring PAHs to TPAHs is not high (0.5–9.2%), but the observed concentrations can cause a higher risk to aquatic organisms than low-ring PAHs. The diagnostic ratio showed that the sources of PAHs in the seawater collected offshore of southern Taiwan may include mixed sources such as petrogenic, petroleum combustion, and biomass combustion. The results can be used for regular monitoring, which contributes to pollution prevention and management of the marine environment. Full article

(This article belongs to the Special Issue The Relationship between Ships and Marine Environment)

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17 pages, 2152 KiB

Open AccessEditor’s ChoiceArticle

Geographical Preference for Installation of Solar Still Water Desalination Technologies in Iran: An Analytical Hierarchy Process (AHP)-Based Answer

by Sina Jafari, Majid Aghel, Ali Sohani and Siamak Hoseinzadeh

Water 2022, 14(2), 265; https://doi.org/10.3390/w14020265 - 17 Jan 2022

Cited by 15 | Viewed by 2563

Abstract

Water shortage is one of the most crucial challenges worldwide, especially in the Middle Eastern countries, with high population and low freshwater resources. Considering this point and the increasing popularity of solar stills desalination systems, as the contribution, this study aims at finding [...] Read more.

Water shortage is one of the most crucial challenges worldwide, especially in the Middle Eastern countries, with high population and low freshwater resources. Considering this point and the increasing popularity of solar stills desalination systems, as the contribution, this study aims at finding the geographical preference for installation of those technologies in Iran, which is one of the biggest and most populated countries in the Middle East. For this purpose, from each climatic zone of Iran, one representative city is chosen, and analytical hierarchy process (AHP), as one of the most powerful tools for systematic decision-making, is applied. Annual fresh water production (AFWP) from the technical aspect, energy payback period (EPBP) from the energy perspective, and investment payback period from the economic point of view are selected as the decision criteria. Obtaining the three indicated indicators is done using artificial neural networks (ANNs) for yield and water temperature in the basin, which are developed by means of the recorded experimental data. The results indicate that hot arid cities with high received solar radiation, or the ones that have a higher water tariff compared to the others, are the preferred places for installation of solar stills. The example of the first category is Ahvaz, while Tehran is representative of the cities from the second category. AHP demonstrates that they are the first and second priorities for solar still installation, with scores of 26.9 and 22.7, respectively. Ahvaz has AWFP, EPBP, and IPP of 2706.5 L, 0.58 years, and 4.01 years; while the corresponding values for Tehran are 2115.3 L, 0.87 years, and 2.86 years. This study belongs to three classifications in the mathematical problems: 1. experimental work (code: 76–05), 2. Neural networks (code: 92B20), 3. and decision problems, (code: 20F10). Full article

(This article belongs to the Special Issue Renewable Energy Systems Flexibility for Water Desalination)

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20 pages, 12880 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Application of Artificial Neural Networks for Mangrove Mapping Using Multi-Temporal and Multi-Source Remote Sensing Imagery

by Arsalan Ghorbanian, Seyed Ali Ahmadi, Meisam Amani, Ali Mohammadzadeh and Sadegh Jamali

Water 2022, 14(2), 244; https://doi.org/10.3390/w14020244 - 15 Jan 2022

Cited by 16 | Viewed by 4094

Abstract

Mangroves, as unique coastal wetlands with numerous benefits, are endangered mainly due to the coupled effects of anthropogenic activities and climate change. Therefore, acquiring reliable and up-to-date information about these ecosystems is vital for their conservation and sustainable blue carbon development. In this [...] Read more.

Mangroves, as unique coastal wetlands with numerous benefits, are endangered mainly due to the coupled effects of anthropogenic activities and climate change. Therefore, acquiring reliable and up-to-date information about these ecosystems is vital for their conservation and sustainable blue carbon development. In this regard, the joint use of remote sensing data and machine learning algorithms can assist in producing accurate mangrove ecosystem maps. This study investigated the potential of artificial neural networks (ANNs) with different topologies and specifications for mangrove classification in Iran. To this end, multi-temporal synthetic aperture radar (SAR) and multi-spectral remote sensing data from Sentinel-1 and Sentinel-2 were processed in the Google Earth Engine (GEE) cloud computing platform. Afterward, the ANN topologies and specifications considering the number of layers and neurons, learning algorithm, type of activation function, and learning rate were examined for mangrove ecosystem mapping. The results indicated that an ANN model with four hidden layers, 36 neurons in each layer, adaptive moment estimation (Adam) learning algorithm, rectified linear unit (Relu) activation function, and the learning rate of 0.001 produced the most accurate mangrove ecosystem map (F-score = 0.97). Further analysis revealed that although ANN models were subjected to accuracy decline when a limited number of training samples were used, they still resulted in satisfactory results. Additionally, it was observed that ANN models had a high resistance when training samples included wrong labels, and only the ANN model with the Adam learning algorithm produced an accurate mangrove ecosystem map when no data standardization was performed. Moreover, further investigations showed the higher potential of multi-temporal and multi-source remote sensing data compared to single-source and mono-temporal (e.g., single season) for accurate mangrove ecosystem mapping. Overall, the high potential of the proposed method, along with utilizing open-access satellite images and big-geo data processing platforms (i.e., GEE, Google Colab, and scikit-learn), made the proposed approach efficient and applicable over other study areas for all interested users. Full article

(This article belongs to the Special Issue Mapping and Monitoring of Wetlands)

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12 pages, 2243 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of Soil Water Content Using SWAT for Southern Saskatchewan, Canada

by Mohammad Zare, Shahid Azam and David Sauchyn

Water 2022, 14(2), 249; https://doi.org/10.3390/w14020249 - 15 Jan 2022

Cited by 12 | Viewed by 3026

Abstract

Soil water content (SWC) is one of the most important hydrologic variables; it plays a decisive role in the control of various land surface processes. We simulated SWC using a Soil and Water Assessment Tool (SWAT) model in southern Saskatchewan. SWC was calibrated [...] Read more.

Soil water content (SWC) is one of the most important hydrologic variables; it plays a decisive role in the control of various land surface processes. We simulated SWC using a Soil and Water Assessment Tool (SWAT) model in southern Saskatchewan. SWC was calibrated using measured data and Soil Moisture Active Passive (SMAP) Level-4 for the surface (0–5 cm) SWC for hydrological response units (HRU) at daily and monthly (warm season) intervals for the years 2015 to 2020. We used the SUFI-2 technique in SWAT-CUP, and observed daily instrumented streamflow records, for calibration (1995 to 2004) and validation (2005–2010). The results reveal that the SWAT model performs well with a monthly PBIAS < 10% and Nash–Sutcliffe efficiency (NS) and R² ≥ 0.8 for calibration and validation. The correlation coefficient between ground measurement with SMAP and SWAT products are 0.698 and 0.633, respectively. Moreover, SMAP data of surface SWC coincides well with measurements in terms of both amount and trend compared with the SWAT product. The highest r value occurred in July when the mean r value in SWAT and SMAP were 0.87 to 0.84, and then in June for r value of 0.75. In contrast, the lowest values were in April and May (0.07 and 0.04, respectively) at the beginning of the growing season in southern Saskatchewan. Furthermore, calibration in the SWAT model is based on a batch form whereby parameters are adjusted to corresponding input by modifying simulations with observations. SWAT underestimates the abrupt increase in streamflow during the snowmelt months (April and May). This study achieved the objective of developing a SWAT model that simulates SWC in a prairie watershed, and, therefore, can be used in a subsequent phase of research to estimate future soil moisture conditions under projected climate changes. Full article

(This article belongs to the Section Soil and Water)

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14 pages, 846 KiB

Open AccessEditor’s ChoiceArticle

The Effect of Trophic Modes on Biomass and Lipid Production of Five Microalgal Strains

by Andonia Nicodemou, Michalis Kallis, Anastasia Agapiou, Androulla Markidou and Michalis Koutinas

Water 2022, 14(2), 240; https://doi.org/10.3390/w14020240 - 14 Jan 2022

Cited by 16 | Viewed by 2642

Abstract

Five microalgae strains, namely Isochrysis galbana, Microchloropsis gaditana, Scenedesmus obliquus, Nannochloropsis oculata and Tetraselmis suecica, were selected as potential candidates for polyunsaturated fatty acids’ production, evaluating biomass productivity and their capacity to accumulate high lipid contents under different trophic [...] Read more.

Five microalgae strains, namely Isochrysis galbana, Microchloropsis gaditana, Scenedesmus obliquus, Nannochloropsis oculata and Tetraselmis suecica, were selected as potential candidates for polyunsaturated fatty acids’ production, evaluating biomass productivity and their capacity to accumulate high lipid contents under different trophic modes. Microalgae strains were cultivated in the presence of 1% glucose using mixotrophic and heterotrophic conditions, while autotrophic cultures served as control experiments. The results demonstrate that S. obliquus performed the highest biomass productivity that reached 0.13 and 0.14 g L⁻¹ d⁻¹ under mixotrophic and heterotrophic conditions, respectively. I. galbana and S. obliquus utilized elevated contents of glucose in mixotrophy, removing 55.9% and 95.6% of the initial concentration of the carbohydrate, respectively, while glucose consumption by the aforementioned strains also remained high under heterotrophic cultivation. The production of lipids was maximal for I. galbana in mixotrophy and S. obliquus in heterotrophy, performing lipid productivities of 24.85 and 22.77 mg L⁻¹ d⁻¹, respectively. The most abundant saturated acid detected for all microalgae strains evaluated was palmitic acid (C16:0), while oleic and linolenic acids (C18:1n9c/C18:3n3) comprised the most abundant unsaturated fatty acids. I. galbana performed the highest linoleic acid (C18:2n6c) content under heterotrophic nutrition, which reached 87.9 mg g⁻¹ of ash-free dry weight. Among the microalgae strains compared, the biomass and lipid production monitored for I. galbana and S. obliquus confirm that both strains could serve as efficient bioproducers for application in algal biorefineries. Full article

(This article belongs to the Special Issue Nutrient Recovery from Wastewaters Using Microalgae-Based Systems and Potential Applications of the Produced Biomass)

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30 pages, 4076 KiB

Open AccessFeature PaperEditor’s ChoiceReview

Review on Methylene Blue: Its Properties, Uses, Toxicity and Photodegradation

by Idrees Khan, Khalid Saeed, Ivar Zekker, Baoliang Zhang, Abdulmajeed H. Hendi, Ashfaq Ahmad, Shujaat Ahmad, Noor Zada, Hanif Ahmad, Luqman Ali Shah, Tariq Shah and Ibrahim Khan

Water 2022, 14(2), 242; https://doi.org/10.3390/w14020242 - 14 Jan 2022

Cited by 485 | Viewed by 60691

Abstract

The unavailability of clean drinking water is one of the significant health issues in modern times. Industrial dyes are one of the dominant chemicals that make water unfit for drinking. Among these dyes, methylene blue (MB) is toxic, carcinogenic, and non-biodegradable and can [...] Read more.

The unavailability of clean drinking water is one of the significant health issues in modern times. Industrial dyes are one of the dominant chemicals that make water unfit for drinking. Among these dyes, methylene blue (MB) is toxic, carcinogenic, and non-biodegradable and can cause a severe threat to human health and environmental safety. It is usually released in natural water sources, which becomes a health threat to human beings and living organisms. Hence, there is a need to develop an environmentally friendly, efficient technology for removing MB from wastewater. Photodegradation is an advanced oxidation process widely used for MB removal. It has the advantages of complete mineralization of dye into simple and nontoxic species with the potential to decrease the processing cost. This review provides a tutorial basis for the readers working in the dye degradation research area. We not only covered the basic principles of the process but also provided a wide range of previously published work on advanced photocatalytic systems (single-component and multi-component photocatalysts). Our study has focused on critical parameters that can affect the photodegradation rate of MB, such as photocatalyst type and loading, irradiation reaction time, pH of reaction media, initial concentration of dye, radical scavengers and oxidising agents. The photodegradation mechanism, reaction pathways, intermediate products, and final products of MB are also summarized. An overview of the future perspectives to utilize MB at an industrial scale is also provided. This paper identifies strategies for the development of effective MB photodegradation systems. Full article

(This article belongs to the Special Issue Efficient Catalytic and Microbial Treatment of Water Pollutants)

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23 pages, 6504 KiB

Open AccessEditor’s ChoiceArticle

Underwater Fish Detection and Counting Using Mask Regional Convolutional Neural Network

by Teh Hong Khai, Siti Norul Huda Sheikh Abdullah, Mohammad Kamrul Hasan and Ahmad Tarmizi

Water 2022, 14(2), 222; https://doi.org/10.3390/w14020222 - 12 Jan 2022

Cited by 25 | Viewed by 5731

Abstract

Fish production has become a roadblock to the development of fish farming, and one of the issues encountered throughout the hatching process is the counting procedure. Previous research has mainly depended on the use of non-machine learning-based and machine learning-based counting methods and [...] Read more.

Fish production has become a roadblock to the development of fish farming, and one of the issues encountered throughout the hatching process is the counting procedure. Previous research has mainly depended on the use of non-machine learning-based and machine learning-based counting methods and so was unable to provide precise results. In this work, we used a robotic eye camera to capture shrimp photos on a shrimp farm to train the model. The image data were classified into three categories based on the density of shrimps: low density, medium density, and high density. We used the parameter calibration strategy to discover the appropriate parameters and provided an improved Mask Regional Convolutional Neural Network (Mask R-CNN) model. As a result, the enhanced Mask R-CNN model can reach an accuracy rate of up to 97.48%. Full article

(This article belongs to the Special Issue AI and Deep Learning Applications for Water Management)

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14 pages, 3206 KiB

Open AccessEditor’s ChoiceArticle

Research on the Non-Point Source Pollution Characteristics of Important Drinking Water Sources

by Lei Hou, Zhongyuan Zhou, Ruyan Wang, Jianxin Li, Fei Dong and Jingqiang Liu

Water 2022, 14(2), 211; https://doi.org/10.3390/w14020211 - 12 Jan 2022

Cited by 30 | Viewed by 4293

Abstract

In recent years, freshwater resource contamination by non-point source pollution has become particularly prominent in China. To control non-point source (NPS) pollution, it is important to estimate NPS pollution exports, identify sources of pollution, and analyze the pollution characteristics. As such, in this [...] Read more.

In recent years, freshwater resource contamination by non-point source pollution has become particularly prominent in China. To control non-point source (NPS) pollution, it is important to estimate NPS pollution exports, identify sources of pollution, and analyze the pollution characteristics. As such, in this study, we established the modified export coefficient model based on rainfall and terrain to investigate the pollution sources and characteristics of non-point source total nitrogen (TN) and total phosphorus (TP) throughout the Huangqian Reservoir watershed—which serves as an important potable water source for the main tributary of the lower Yellow River. The results showed that: (1) In 2018, the non-point source total nitrogen (TN) and total phosphorus (TP) loads in the Huangqian Reservoir basin were 707.09 t and 114.42 t, respectively. The contribution ratios to TN export were, from high to low, rural life (33.58%), farmland (32.68%), other land use types (20.08%), and livestock and poultry breeding (13.67%). The contribution ratios to TP export were, from high to low, rural life (61.19%), livestock and poultry breeding (21.65%), farmland (12.79%), and other land use types (4.38%). The non-point source pollution primarily originated from the rural life of the water source protection zone. (2) Non-point source TN and TP pollution loads and load intensities showed significantly different spatial distribution patterns throughout the water source protection area. Specifically, their load intensities and loads were the largest in the second-class protected zone, which is the key source area of non-point source pollution. (3) When considering whether to invest in agricultural land fertilizer control or rural domestic sewage, waste, and livestock manure pollution control, the latter is demonstrably more effective. Thus, in addition to putting low-grade control on agricultural fertilizer loss, to rapidly and effectively improve potable water quality, non-point source pollution should, to a larger extent, also be controlled through measures such as establishing household biogas digesters, introducing village sewage treatment plants, and improving the recovery rate of rural domestic garbage. The research results discussed herein provide a theoretical basis for formulating a reasonable and effective protection plan for the Huangqian Reservoir water source and can potentially be used to do the same for other similar freshwater resources. Full article

(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)

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18 pages, 9681 KiB

Open AccessEditor’s ChoiceArticle

Comparison of Rainfall-Runoff Simulation between Support Vector Regression and HEC-HMS for a Rural Watershed in Taiwan

by Shen Chiang, Chih-Hsin Chang and Wei-Bo Chen

Water 2022, 14(2), 191; https://doi.org/10.3390/w14020191 - 11 Jan 2022

Cited by 26 | Viewed by 3899

Abstract

To better understand the effect and constraint of different data lengths on the data-driven model training for the rainfall-runoff simulation, the support vector regression (SVR) approach was applied to the data-driven model as the core algorithm in the present study. Various features selection [...] Read more.

To better understand the effect and constraint of different data lengths on the data-driven model training for the rainfall-runoff simulation, the support vector regression (SVR) approach was applied to the data-driven model as the core algorithm in the present study. Various features selection strategies and different data lengths were employed in the training phase of the model. The validated results of the SVR were compared with the rainfall-runoff simulation derived from a physically based hydrologic model, the Hydrologic Modeling System (HEC-HMS). The HEC-HMS was considered a conventional approach and was also calibrated with a dataset period identical to the SVR. Our results showed that the SVR and HEC-HMS models could be adopted for short and long periods of rainfall-runoff simulation. However, the SVR model estimated the rainfall-runoff relationship reasonably well even if the observational data of one year or one typhoon event was used. In contrast, the HEC-HMS model needed more parameter optimization and inference processes to achieve the same performance level as the SVR model. Overall, the SVR model was superior to the HEC-HMS model in the performance of the rainfall-runoff simulation. Full article

(This article belongs to the Special Issue Mitigation Techniques for Water-Induced Natural Disasters: The State of the Art)

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16 pages, 2228 KiB

Open AccessEditor’s ChoiceArticle

Mind the Gap! Reconciling Environmental Water Requirements with Scarcity in the Murray–Darling Basin, Australia

by Matthew J. Colloff and Jamie Pittock

Water 2022, 14(2), 208; https://doi.org/10.3390/w14020208 - 11 Jan 2022

Cited by 12 | Viewed by 4498

Abstract

The Murray–Darling Basin Plan is a $AU 13 billion program to return water from irrigation use to the environment. Central to the success of the Plan, commenced in 2012, is the implementation of an Environmentally Sustainable Level of Take (ESLT) and a Sustainable [...] Read more.

The Murray–Darling Basin Plan is a $AU 13 billion program to return water from irrigation use to the environment. Central to the success of the Plan, commenced in 2012, is the implementation of an Environmentally Sustainable Level of Take (ESLT) and a Sustainable Diversion Limit (SDL) on the volume of water that can be taken for consumptive use. Under the enabling legislation, the Water Act (2007), the ESLT and SDL must be set by the “best available science.” In 2009, the volume of water to maintain wetlands and rivers of the Basin was estimated at 3000–7600 GL per year. Since then, there has been a steady step-down in this volume to 2075 GL year due to repeated policy adjustments, including “supply measures projects,” building of infrastructure to obtain the same environmental outcomes with less water. Since implementation of the Plan, return of water to the environment is falling far short of targets. The gap between the volume required to maintain wetlands and rivers and what is available is increasing with climate change and other risks, but the Plan makes no direct allowance for climate change. We present policy options that address the need to adapt to less water and re-frame the decision context from contestation between water for irrigation versus the environment. Options include best use of water for adaptation and structural adjustment packages for irrigation communities integrated with environmental triage of those wetlands likely to transition to dryland ecosystems under climate change. Full article

(This article belongs to the Special Issue Advances in Water Scarcity and Conservation)

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18 pages, 12583 KiB

Open AccessEditor’s ChoiceArticle

Development and Application of an Urban Flood Forecasting and Warning Process to Reduce Urban Flood Damage: A Case Study of Dorim River Basin, Seoul

by Yong-Man Won, Jung-Hwan Lee, Hyeon-Tae Moon and Young-Il Moon

Water 2022, 14(2), 187; https://doi.org/10.3390/w14020187 - 10 Jan 2022

Cited by 17 | Viewed by 3290

Abstract

Early and accurate flood forecasting and warning for urban flood risk areas is an essential factor to reduce flood damage. This paper presents the urban flood forecasting and warning process to reduce damage in the main flood risk area of South Korea. This [...] Read more.

Early and accurate flood forecasting and warning for urban flood risk areas is an essential factor to reduce flood damage. This paper presents the urban flood forecasting and warning process to reduce damage in the main flood risk area of South Korea. This process is developed based on the rainfall-runoff model and deep learning model. A model-driven method was devised to construct the accurate physical model with combined inland-river and flood control facilities, such as pump stations and underground storages. To calibrate the rainfall-runoff model, data of gauging stations and pump stations of an urban stream in August 2020 were used, and the model result was presented as an R² value of 0.63~0.79. Accurate flood warning criteria of the urban stream were analyzed according to the various rainfall scenarios from the model-driven method. As flood forecasting and warning in the urban stream, deep learning models, vanilla ANN, Long Short-Term Memory (LSTM), Stack-LSTM, and Bidirectional LSTM were constructed. Deep learning models using 10-min hydrological time-series data from gauging stations were trained to warn of expected flood risks based on the water level in the urban stream. A forecasting and warning method that applied the bidirectional LSTM showed an R² value of 0.9 for the water level forecast with 30 min lead time, indicating the possibility of effective flood forecasting and warning. This case study aims to contribute to the reduction of casualties and flood damage in urban streams and accurate flood warnings in typical urban flood risk areas of South Korea. The developed urban flood forecasting and warning process can be applied effectively as a non-structural measure to mitigate urban flood damage and can be extended considering watershed characteristics. Full article

(This article belongs to the Special Issue Urban and River Flooding: Theory, Experimental and Numerical Models, and Applications in Hydraulic Engineering)

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13 pages, 2790 KiB

Open AccessEditor’s ChoiceArticle

Development of a Distributed Mathematical Model and Control System for Reducing Pollution Risk in Mineral Water Aquifer Systems

by Alexander V. Martirosyan, Yury V. Ilyushin and Olga V. Afanaseva

Water 2022, 14(2), 151; https://doi.org/10.3390/w14020151 - 07 Jan 2022

Cited by 46 | Viewed by 2853

Abstract

The article is devoted to the problem of the growing need of the mineral water fields’ exploitation process automation. The implementation of control systems and mathematical modeling methods can significantly reduce the fields’ structural integrity violation and pollution of aquifers risks. This research [...] Read more.

The article is devoted to the problem of the growing need of the mineral water fields’ exploitation process automation. The implementation of control systems and mathematical modeling methods can significantly reduce the fields’ structural integrity violation and pollution of aquifers risks. This research is especially relevant for the fields with difficult conditions of mineral waters occurrence, since the insufficient accuracy of determining the fields’ operating mode parameters can lead to a severe incident. The article describes a distributed mathematical model developed from the geo-filtration equation. Based on this model, a new method for assessing the mutual influence of the fields, the production of which is carried out from one aquifer, is presented. For a more detailed study of the operating mode parameters influence on the object a physical model of the reservoir was developed. The using of Arduino sensors and the developed software allows us to construct a 3D graph of the input action and its response at the different points of the object as temperature distribution. The simulation results make it possible to use the proposed model for the automatic control system synthesis. Full article

(This article belongs to the Special Issue Groundwater Flow and Transport Models)

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16 pages, 2612 KiB

Open AccessFeature PaperEditor’s ChoiceReview

Application of Natural Coagulants for Pharmaceutical Removal from Water and Wastewater: A Review

by Motasem Y. D. Alazaiza, Ahmed Albahnasawi, Gomaa A. M. Ali, Mohammed J. K. Bashir, Dia Eddin Nassani, Tahra Al Maskari, Salem S. Abu Amr and Mohammed Shadi S. Abujazar

Water 2022, 14(2), 140; https://doi.org/10.3390/w14020140 - 06 Jan 2022

Cited by 59 | Viewed by 17255

Abstract

Pharmaceutical contamination threatens both humans and the environment, and several technologies have been adapted for the removal of pharmaceuticals. The coagulation-flocculation process demonstrates a feasible solution for pharmaceutical removal. However, the chemical coagulation process has its drawbacks, such as excessive and toxic sludge [...] Read more.

Pharmaceutical contamination threatens both humans and the environment, and several technologies have been adapted for the removal of pharmaceuticals. The coagulation-flocculation process demonstrates a feasible solution for pharmaceutical removal. However, the chemical coagulation process has its drawbacks, such as excessive and toxic sludge production and high production cost. To overcome these shortcomings, the feasibility of natural-based coagulants, due to their biodegradability, safety, and availability, has been investigated by several researchers. This review presented the recent advances of using natural coagulants for pharmaceutical compound removal from aqueous solutions. The main mechanisms of natural coagulants for pharmaceutical removal from water and wastewater are charge neutralization and polymer bridges. Natural coagulants extracted from plants are more commonly investigated than those extracted from animals due to their affordability. Natural coagulants are competitive in terms of their performance and environmental sustainability. Developing a reliable extraction method is required, and therefore further investigation is essential to obtain a complete insight regarding the performance and the effect of environmental factors during pharmaceutical removal by natural coagulants. Finally, the indirect application of natural coagulants is an essential step for implementing green water and wastewater treatment technologies. Full article

(This article belongs to the Special Issue Wastewater Treatment: Current and Future Techniques)

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15 pages, 4244 KiB

Open AccessEditor’s ChoiceArticle

Water Turbidity Retrieval Based on UAV Hyperspectral Remote Sensing

by Mengying Cui, Yonghua Sun, Chen Huang and Mengjun Li

Water 2022, 14(1), 128; https://doi.org/10.3390/w14010128 - 05 Jan 2022

Cited by 25 | Viewed by 4110

Abstract

The water components affecting turbidity are complex and changeable, and the spectral response mechanism of each water quality parameter is different. Therefore, this study mainly aimed at the turbidity monitoring by unmanned aerial vehicle (UAV) hyperspectral technology, and establishes a set of turbidity [...] Read more.

The water components affecting turbidity are complex and changeable, and the spectral response mechanism of each water quality parameter is different. Therefore, this study mainly aimed at the turbidity monitoring by unmanned aerial vehicle (UAV) hyperspectral technology, and establishes a set of turbidity retrieval models through the artificial control experiment, and verifies the model’s accuracy through UAV flight and water sample data in the same period. The results of this experiment can also be extended to different inland waters for turbidity retrieval. Retrieval of turbidity values of small inland water bodies can provide support for the study of the degree of water pollution. We collected the images and data of aquaculture ponds and irrigation ditches in Dawa District, Panjin City, Liaoning Province. Twenty-nine standard turbidity solutions with different concentration gradients (concentration from 0 to 360 NTU—the abbreviation of Nephelometric Turbidity Unit, which stands for scattered turbidity.) were established through manual control and we simultaneously collected hyperspectral data from the spectral values of standard solutions. The sensitive band to turbidity was obtained after analyzing the spectral information. We established four kinds of retrieval, including the single band, band ratio, normalized ratio, and the partial least squares (PLS) models. We selected the two models with the highest R² for accuracy verification. The band ratio model and PLS model had the highest accuracy, and R² was, respectively, 0.65 and 0.72. The hyperspectral image data obtained by UAV were combined with the PLS model, which had the highest R² to estimate the spatial distribution of water turbidity. The turbidity of the water areas in the study area was 5–300 NTU, and most of which are 5–80 NTU. It shows that the PLS models can retrieve the turbidity with high accuracy of aquaculture ponds, irrigation canals, and reservoirs in Dawa District of Panjin City, Liaoning Province. The experimental results are consistent with the conclusions of the field investigation. Full article

(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)

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13 pages, 2765 KiB

Open AccessEditor’s ChoiceArticle

Degradation of Azo Dyes with Different Functional Groups in Simulated Wastewater by Electrocoagulation

by Yang Liu, Chenglong Li, Jia Bao, Xin Wang, Wenjing Yu and Lixin Shao

Water 2022, 14(1), 123; https://doi.org/10.3390/w14010123 - 05 Jan 2022

Cited by 25 | Viewed by 4846

Abstract

Increasing attention has been paid to the widespread contamination of azo dyes in water bodies globally. These chemicals can present high toxicity, possibly causing severe irritation of the respiratory tract and even carcinogenic effects. The present study focuses on the periodically reverse electrocoagulation [...] Read more.

Increasing attention has been paid to the widespread contamination of azo dyes in water bodies globally. These chemicals can present high toxicity, possibly causing severe irritation of the respiratory tract and even carcinogenic effects. The present study focuses on the periodically reverse electrocoagulation (PREC) treatment of two typical azo dyes with different functional groups, involving methyl orange (MO) and alizarin yellow (AY), using Fe-Fe electrodes. Based upon the comparative analysis of three main parameters, including current intensity, pH, and electrolyte, the optimal color removal rates for MO and AY could be achieved at a rate of up to 98.7% and 98.6%, respectively, when the current intensity is set to 0.6 A, the pH is set at 6.0, and the electrolyte is selected as NaCl. An accurate predicted method of response surface methodology (RSM) was established to optimize the PREC process involving the three parameters above. The reaction time was the main influence for both azo dyes, while the condition of PREC treatment for AY simulated wastewater was time-saving and energy conserving. According to the further UV–Vis spectrophotometry analysis throughout the procedure of the PREC process, the removal efficiency for AY was better than that of MO, potentially because hydroxyl groups might donate electrons to iron flocs or electrolyze out hydroxyl free radicals. The present study revealed that the functional groups might pose a vital influence on the removal efficiencies of the PREC treatment for those two azo dyes. Full article

(This article belongs to the Special Issue Innovative Technologies for Wastewater and Water Treatment)

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29 pages, 3943 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Water Economics: An In-Depth Analysis of the Connection of Blue Water with Some Primary Level Aspects of Economic Theory I

by Kalomoira Zisopoulou, Dimitris Zisopoulos and Dionysia Panagoulia

Water 2022, 14(1), 103; https://doi.org/10.3390/w14010103 - 04 Jan 2022

Cited by 12 | Viewed by 5963

Abstract

An analysis of the following aspects of water economics was undertaken: Water as an Economic and Social Good, Modes of Government Intervention, Water Scarcity in Economic Theory and Agricultural Water Management Changes, with the support of over 300 sources. Emphasis was placed on [...] Read more.

An analysis of the following aspects of water economics was undertaken: Water as an Economic and Social Good, Modes of Government Intervention, Water Scarcity in Economic Theory and Agricultural Water Management Changes, with the support of over 300 sources. Emphasis was placed on the connection with primary aspects of economics, in contrast to the usual applicative expositions found in water economics literature. This is a novel approach comparing international bodies’ definitions with economic theory at primary level which leads, upon occasion, to serious contradictions which were exhibited in broad lines. Furthermore, it compares the global implications of these definitions to the existing reality at country level, and a lack of bilateral consistency is exhibited. The uniform picture presented at global level is shown to become a non-uniform one at country level, where sharp variations in resources and availability form a competitive market between nations, and water-rich countries already possessing a competitive advantage are shown to attain a water-based comparative advantage as well. It is shown that although at country level water has a quasi-public good character with minimal private good market existence, this is achieved with the existence of a private goods market at international level via international trade in virtual water. A novel approach to management problems stemming from authority levels starting at global level and ending at farm level is analyzed and redressed by employing reality gap theory. Full article

(This article belongs to the Special Issue The Economic Role of Water under Scarcity and Sustainability Constraints)

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15 pages, 2493 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

A Hybrid Model for Streamflow Forecasting in the Basin of Euphrates

by Huseyin Cagan Kilinc and Bulent Haznedar

Water 2022, 14(1), 80; https://doi.org/10.3390/w14010080 - 03 Jan 2022

Cited by 37 | Viewed by 3615

Abstract

River flow modeling plays a crucial role in water resource management and ensuring its sustainability. Therefore, in recent years, in addition to the prediction of hydrological processes through modeling, applicable and highly reliable methods have also been used to analyze the sustainability of [...] Read more.

River flow modeling plays a crucial role in water resource management and ensuring its sustainability. Therefore, in recent years, in addition to the prediction of hydrological processes through modeling, applicable and highly reliable methods have also been used to analyze the sustainability of water resources. Artificial neural networks and deep learning-based hybrid models have been used by scientists in river flow predictions. Therefore, in this study, we propose a hybrid approach, integrating long-short-term memory (LSTM) networks and a genetic algorithm (GA) for streamflow forecasting. The performance of the hybrid model and the benchmark model was taken into account using daily flow data. For this purpose, the daily river flow time series of the Beyderesi-Kılayak flow measurement station (FMS) from September 2000 to June 2019 and the data from Yazıköy from December 2000 to June 2018 were used for flow measurements on the Euphrates River in Turkey. To validate the performance of the model, the first 80% of the data were used for training, and the remaining 20% were used for the testing of the two FMSs. Statistical methods such as linear regression was used during the comparison process to assess the proposed method’s performance and to demonstrate its superior predictive ability. The estimation results of the models were evaluated with RMSE, MAE, MAPE, STD and R² statistical metrics. The comparison of daily streamflow predictions results revealed that the LSTM-GA model provided promising accuracy results and mainly presented higher performance than the benchmark model and the linear regression model. Full article

(This article belongs to the Special Issue Advances in Water Use Efficiency in a Changing Environment)

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23 pages, 10130 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Sensitivity, Hazard, and Vulnerability of Farmlands to Saltwater Intrusion in Low-Lying Coastal Areas of Venice, Italy

by Luigi Tosi, Cristina Da Lio, Alessandro Bergamasco, Marta Cosma, Chiara Cavallina, Andrea Fasson, Andrea Viezzoli, Luca Zaggia and Sandra Donnici

Water 2022, 14(1), 64; https://doi.org/10.3390/w14010064 - 30 Dec 2021

Cited by 16 | Viewed by 2973

Abstract

Saltwater intrusion is a growing threat for coastal aquifers and agricultural practices in low-lying plains. Most of the farmlands located between the margin of the Southern Venice lagoon and the Northern Po delta, Italy, lie a few meters below mean sea level and [...] Read more.

Saltwater intrusion is a growing threat for coastal aquifers and agricultural practices in low-lying plains. Most of the farmlands located between the margin of the Southern Venice lagoon and the Northern Po delta, Italy, lie a few meters below mean sea level and are drained by a large network of artificial channels and hydraulic infrastructures to avoid frequent flooding and allow agricultural practices. This work proposes an assessment of the vulnerability to saltwater intrusion, following a new concept of the hazard status, resulting in combining the depth of the freshwater/saltwater interface and the electrical resistivity of the shallow subsoil. The sensitivity of the farmland system was assessed by using ground elevation, distance from freshwater and saltwater sources, permeability, potential runoff, land subsidence, and sea-level rise indicators. Relative weights were assigned by a pairwise comparison following the Analytic Hierarchy Process approach. The computed vulnerability map highlights that about 30% of the farmlands is under strong and extreme conditions, 28% between marginal and moderate, and 40% under negligible conditions. Results from previous vulnerability assessments are discussed in order to explain their differences in terms of hazard status conceptualization and sensitivity characterization of farmland system. Full article

(This article belongs to the Special Issue Salinization of Water Resources: Ongoing and Future Trends)

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20 pages, 6692 KiB

Open AccessEditor’s ChoiceArticle

Diversity of Silica-Scaled Chrysophytes in Central Vietnam

by Evgeniy Gusev and Nikita Martynenko

Water 2022, 14(1), 65; https://doi.org/10.3390/w14010065 - 30 Dec 2021

Cited by 16 | Viewed by 2186

Abstract

This paper focuses on the flora of scale-bearing chrysophytes from eight provinces located in the central part of Vietnam. Khanh Hoa, Phu Yen, Binh Dinh, Thua Thien Hue, Quang Tri, and Quang Binh provinces are located in the coastal area of Vietnam. Lam [...] Read more.

This paper focuses on the flora of scale-bearing chrysophytes from eight provinces located in the central part of Vietnam. Khanh Hoa, Phu Yen, Binh Dinh, Thua Thien Hue, Quang Tri, and Quang Binh provinces are located in the coastal area of Vietnam. Lam Dong and Dak Lak provinces represent mountain territories with an elevation of 500–2000 metres above sea level. In total, 212 water bodies of different origins were studied. Samples were obtained from swamp areas, lakes, rivers, reservoirs, ponds, and small temporary water bodies. In total, 76 taxa were identified by electron microscopic observations of samples. A total of 54 taxa were found in the mountainous provinces, while 73 were found in the coastal provinces. Of these, 51 species are common for both areas. The most diverse was the genus Mallomonas with 66 species, varieties, and forms; followed by Synura with 7 taxa; Chrysosphaerella with 2; and Spiniferomonas with 1. Seven taxa of the genus Mallomonas were not identified to the lower rank. All these unidentified specimens may potentially represent new species for science. Ten taxa are reported for the first time in Vietnam. Full article

(This article belongs to the Special Issue Species Richness and Diversity of Aquatic Ecosystems)

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21 pages, 2514 KiB

Open AccessEditor’s ChoiceReview

A Review on the Application of Isotopic Techniques to Trace Groundwater Pollution Sources within Developing Countries

by Abdul Aziz Sankoh, Nana Sarfo Agyemang Derkyi, Ronnie A. D. Frazer-williams, Cynthia Laar and Ishmail Kamara

Water 2022, 14(1), 35; https://doi.org/10.3390/w14010035 - 24 Dec 2021

Cited by 16 | Viewed by 4880

Abstract

Owing to a lack of efficient solid waste management (SWM) systems, groundwater in most developing countries is found to be contaminated and tends to pose significant environmental health risks. This review paper proffers guidelines on the application of isotopic techniques to trace groundwater [...] Read more.

Owing to a lack of efficient solid waste management (SWM) systems, groundwater in most developing countries is found to be contaminated and tends to pose significant environmental health risks. This review paper proffers guidelines on the application of isotopic techniques to trace groundwater pollution sources from data spanning from 2010 to 2020 within developing countries. Earlier groundwater studies in those countries were mainly focused on using hydrochemical and geophysical techniques. The limitation of these techniques is that they can only monitor the concentration of pollutants in the water bodies and possible leachate infiltration but cannot determine the specific sources of the pollution. Stable isotopes of δ¹⁸O, δ²H and δ¹³C can confirm leachate migration to water bodies due to methanogenesis. The high tritium in landfill leachates is useful to identify leachate percolation in groundwater. The δ¹⁵N technique has been used to distinguish between synthetic and organic nitrogen sources but its application is limited to differentiating between atmospheric vs. inorganic nitrogen sources. The use of a dual isotope of δ¹⁵N–

{NO}_{3}^{-}

and δ¹⁸O–

{NO}_{3}^{-}

is beneficial in terms of identifying various sources of nitrogen such as atmospheric and inorganic fertilizers but is yet to be used to differentiate between nitrogen pollution sources from dumpsites, sewage and animal manure. The coupling of the ¹¹B isotope with δ¹⁵N–

{NO}_{3}^{-}

and δ¹⁸O–

{NO}_{3}^{-}

and other hydrochemical parameters has proven to be effective in distinguishing between nitrate fertilizer, animal manure, seawater contamination and sewage. Therefore, in areas affected by agricultural activities, landfill leachates, domestic or sewage effluent and seawater intrusion, it is incumbent to couple hydrochemical (

{Cl}^{-}

,

{NO}_{3}^{-}

, B, DO) and isotope techniques (δ¹⁸O, ²H, δ¹³C, δ¹⁸O–

{NO}_{3}^{-}

, δ¹⁵N–

{NO}_{3}^{-}

, δ¹¹B and ³H) to effectively determine pollution sources of groundwater in developing countries. The foregoing review will provide guidelines for studies that may aim to critically distinguish between seawater intrusion, dumpsites, sewage and septic leachates. Full article

(This article belongs to the Section Water Quality and Contamination)

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13 pages, 3044 KiB

Open AccessEditor’s ChoiceArticle

Monitoring Water Quality of the Haihe River Based on Ground-Based Hyperspectral Remote Sensing

by Qi Cao, Gongliang Yu, Shengjie Sun, Yong Dou, Hua Li and Zhiyi Qiao

Water 2022, 14(1), 22; https://doi.org/10.3390/w14010022 - 22 Dec 2021

Cited by 28 | Viewed by 5145

Abstract

The Haihe River is a typical sluice-controlled river in the north of China. The construction and operation of sluice dams change the flow and other hydrological factors of rivers, which have adverse effects on water, making it difficult to study the characteristics of [...] Read more.

The Haihe River is a typical sluice-controlled river in the north of China. The construction and operation of sluice dams change the flow and other hydrological factors of rivers, which have adverse effects on water, making it difficult to study the characteristics of water quality change and water environment control in northern rivers. In recent years, remote sensing has been widely used in water quality monitoring. However, due to the low signal-to-noise ratio (SNR) and the limitation of instrument resolution, satellite remote sensing is still a challenge to inland water quality monitoring. Ground-based hyperspectral remote sensing has a high temporal-spatial resolution and can be simply fixed in the water edge to achieve real-time continuous detection. A combination of hyperspectral remote sensing devices and BP neural networks is used in the current research to invert water quality parameters. The measured values and remote sensing reflectance of eight water quality parameters (chlorophyll-a (Chl-a), phycocyanin (PC), total suspended sediments (TSS), total nitrogen (TN), total phosphorus (TP), ammonia nitrogen (NH₄-N), nitrate-nitrogen (NO₃-N), and pH) were modeled and verified. The results show that the performance R² of the training model is above 80%, and the performance R² of the verification model is above 70%. In the training model, the highest fitting degree is TN (R² = 1, RMSE = 0.0012 mg/L), and the lowest fitting degree is PC (R² = 0.87, RMSE = 0.0011 mg/L). Therefore, the application of hyperspectral remote sensing technology to water quality detection in the Haihe River is a feasible method. The model built in the hyperspectral remote sensing equipment can help decision-makers to easily understand the real-time changes of water quality parameters. Full article

(This article belongs to the Topic Recent Advances in Hydroinformatics: Focusing on Machine Learning and Remote Sensing in Hydrology)

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14 pages, 4617 KiB

Open AccessEditor’s ChoiceReview

Flood Risk-Related Research Trends in Latin America and the Caribbean

by Juan Pinos and Adolfo Quesada-Román

Water 2022, 14(1), 10; https://doi.org/10.3390/w14010010 - 22 Dec 2021

Cited by 36 | Viewed by 7633

Abstract

Latin America and the Caribbean (LAC), like many other regions in the world, are areas that are prone to hydrometeorological disasters, which threaten livelihoods and cause economic losses. To derive LAC’s status in the field of flood risk-related research, we conducted a bibliometric [...] Read more.

Latin America and the Caribbean (LAC), like many other regions in the world, are areas that are prone to hydrometeorological disasters, which threaten livelihoods and cause economic losses. To derive LAC’s status in the field of flood risk-related research, we conducted a bibliometric analysis of the region’s publication record using the Web of Science journal database (WoS). After analysing a total of 1887 references according to inclusion-exclusion criteria, 302 articles published in the last 20 years were selected. The research articles published in the period 2000–2020 revealed that Mexico, Brazil, and certain South American countries such as Chile, Peru, and Argentina are more productive in flood risk research. Scientific research is increasing, and most of the available studies focus on lowland areas. The frequently-used keywords are generic, and there is often verbatim copying from the title of the article, which shows the poor coherence between the title, abstract, and keywords. This limited diversification of keywords is of little use in bibliometric studies, reducing their visibility and negatively impacting the citation count level. LAC flood studies are mainly related to hydrometeorological assessments, flood risk analyses, geomorphological and ecosystem studies, flood vulnerability and resilience approaches, and statistical and geographic information science evaluations. This systematic review reveals that although flood risk research has been important in the last two decades, future research linked with future climatic scenarios is key to the development of realistic solutions to disaster risks. Full article

(This article belongs to the Section Hydrology)

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14 pages, 3598 KiB

Open AccessEditor’s ChoiceArticle

Optimization of Magnetic Nanoparticles Draw Solution for High Water Flux in Forward Osmosis

by MhdAmmar Hafiz, Mohammed Talhami, Muneer M. Ba-Abbad and Alaa H. Hawari

Water 2021, 13(24), 3653; https://doi.org/10.3390/w13243653 - 20 Dec 2021

Cited by 10 | Viewed by 2858

Abstract

In this study, bare iron oxide nanoparticles were synthesized using a co-precipitation method and used as a draw solute in forward osmosis. The synthesis conditions of the nanoparticles were optimized using the Box-Behnken method to increase the water flux of the forward osmosis [...] Read more.

In this study, bare iron oxide nanoparticles were synthesized using a co-precipitation method and used as a draw solute in forward osmosis. The synthesis conditions of the nanoparticles were optimized using the Box-Behnken method to increase the water flux of the forward osmosis process. The studied parameters were volume of ammonia solution, reaction temperature, and reaction time. The optimum reaction conditions were obtained at reaction temperature of 30 °C, reaction time of 2.73 h and 25.3 mL of ammonia solution. The water flux from the prediction model was found to be 2.06 LMH which is close to the experimental value of 1.98 LMH. The prediction model had high correlation factors (R² = 98.82%) and (R²_adj = 96.69%). This study is expected to be the base for future studies aiming at developing magnetic nanoparticles draw solution using co-precipitation method. Full article

(This article belongs to the Special Issue Application of Membrane Processes in Purification and Power Generation Systems)

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20 pages, 3585 KiB

Open AccessEditor’s ChoiceArticle

Uncertainty in Drought Identification Due to Data Choices, and the Value of Triangulation

by Pius Borona, Friedrich Busch, Tobias Krueger and Philippe Rufin

Water 2021, 13(24), 3611; https://doi.org/10.3390/w13243611 - 16 Dec 2021

Cited by 8 | Viewed by 2807

Abstract

Droughts are complex and gradually evolving conditions of extreme water deficits which can compromise livelihoods and ecological integrity, especially in fragile arid and semi-arid regions that depend on rainfed farming, such as Kitui West in south-eastern Kenya. Against the background of low ground-station [...] Read more.

Droughts are complex and gradually evolving conditions of extreme water deficits which can compromise livelihoods and ecological integrity, especially in fragile arid and semi-arid regions that depend on rainfed farming, such as Kitui West in south-eastern Kenya. Against the background of low ground-station density, 10 gridded rainfall products and four gridded temperature products were used to generate an ensemble of 40 calculations of the Standardized Precipitation Evapotranspiration Index (SPEI) to assess uncertainties in the onset, duration, and magnitude of past droughts. These uncertainties were driven more by variations between the rainfall products than variations between the temperature products. Remaining ambiguities in drought occurrence could be resolved by complementing the quantitative analysis with ground-based information from key informants engaged in disaster relief, effectively formulating an ensemble approach to SPEI-based drought identification to aid decision making. The reported trend towards drier conditions in Eastern Africa was confirmed for Kitui West by the majority of data products, whereby the rainfall effect on those increasingly dry conditions was subtler than just annual and seasonal declines and greater annual variation of rainfall, which requires further investigation. Nevertheless, the effects of increasing droughts are already felt on the ground and warrant decisive action. Full article

(This article belongs to the Topic Water Management in the Era of Climatic Change)

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16 pages, 7411 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

A Synergic Use of Sentinel-1 and Sentinel-2 Imagery for Complex Wetland Classification Using Generative Adversarial Network (GAN) Scheme

by Ali Jamali, Masoud Mahdianpari, Fariba Mohammadimanesh, Brian Brisco and Bahram Salehi

Water 2021, 13(24), 3601; https://doi.org/10.3390/w13243601 - 15 Dec 2021

Cited by 9 | Viewed by 3319

Abstract

Due to anthropogenic activities and climate change, many natural ecosystems, especially wetlands, are lost or changing at a rapid pace. For the last decade, there has been increasing attention towards developing new tools and methods for the mapping and classification of wetlands using [...] Read more.

Due to anthropogenic activities and climate change, many natural ecosystems, especially wetlands, are lost or changing at a rapid pace. For the last decade, there has been increasing attention towards developing new tools and methods for the mapping and classification of wetlands using remote sensing. At the same time, advances in artificial intelligence and machine learning, particularly deep learning models, have provided opportunities to advance wetland classification methods. However, the developed deep and very deep algorithms require a higher number of training samples, which is costly, logistically demanding, and time-consuming. As such, in this study, we propose a Deep Convolutional Neural Network (DCNN) that uses a modified architecture of the well-known DCNN of the AlexNet and a Generative Adversarial Network (GAN) for the generation and classification of Sentinel-1 and Sentinel-2 data. Applying to an area of approximately 370 sq. km in the Avalon Peninsula, Newfoundland, the proposed model with an average accuracy of 92.30% resulted in F-1 scores of 0.82, 0.85, 0.87, 0.89, and 0.95 for the recognition of swamp, fen, marsh, bog, and shallow water, respectively. Moreover, the proposed DCNN model improved the F-1 score of bog, marsh, fen, and swamp wetland classes by 4%, 8%, 11%, and 26%, respectively, compared to the original CNN network of AlexNet. These results reveal that the proposed model is highly capable of the generation and classification of Sentinel-1 and Sentinel-2 wetland samples and can be used for large-extent classification problems. Full article

(This article belongs to the Special Issue Mapping and Monitoring of Wetlands)

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36 pages, 4513 KiB

Open AccessFeature PaperEditor’s ChoiceReview

Groundwater Impacts and Management under a Drying Climate in Southern Australia

by Glen R. Walker, Russell S. Crosbie, Francis H. S. Chiew, Luk Peeters and Rick Evans

Water 2021, 13(24), 3588; https://doi.org/10.3390/w13243588 - 14 Dec 2021

Cited by 12 | Viewed by 5379

Abstract

The trend to a hotter and drier climate, with more extended droughts, has been observed in recent decades in southern Australia and is projected to continue under climate change. This paper reviews studies on the projected impacts of climate change on groundwater and [...] Read more.

The trend to a hotter and drier climate, with more extended droughts, has been observed in recent decades in southern Australia and is projected to continue under climate change. This paper reviews studies on the projected impacts of climate change on groundwater and associated environmental assets in southern Australia, and describes groundwater planning frameworks and management responses. High-risk areas are spatially patchy due to highly saline groundwater or low-transmissivity aquifers. The proportional reduction in rainfall is amplified in the groundwater recharge and some groundwater discharge fluxes. This leads to issues of deteriorating groundwater-dependent ecosystems, streamflow depletion, reduced submarine discharge, groundwater inundation and intrusion in coastal regions and reduced groundwater supply for extraction. Recent water reforms in Australia support the mitigation of these impacts, but groundwater adaptation is still at its infancy. Risk management is being incorporated in regional water and groundwater management plans to support a shift to a more sustainable level of use and more climate-resilient water resources in affected areas. The emerging strategies of groundwater trade and managed aquifer recharge are described, as is the need for a national water-focused climate change planning process. Full article

(This article belongs to the Special Issue Integrated Water Assessment and Management under Climate Change)

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23 pages, 7591 KiB

Open AccessEditor’s ChoiceArticle

Hydrogeochemical Assessment of Groundwater and Suitability Analysis for Domestic and Agricultural Utility in Southern Punjab, Pakistan

by Javed Iqbal, Chunli Su, Abdur Rashid, Nan Yang, Muhammad Yousuf Jat Baloch, Shakeel Ahmed Talpur, Zahid Ullah, Gohar Rahman, Naveed Ur Rahman, Earjh and Meer Muhammad Sajjad

Water 2021, 13(24), 3589; https://doi.org/10.3390/w13243589 - 14 Dec 2021

Cited by 45 | Viewed by 4497

Abstract

Groundwater is a critical water supply for safe drinking water, agriculture, and industry worldwide. In the Khanewal district of Punjab, Pakistan, groundwater has severely deteriorated during the last few decades due to environmental changes and anthropogenic activities. Therefore, 68 groundwater samples were collected [...] Read more.

Groundwater is a critical water supply for safe drinking water, agriculture, and industry worldwide. In the Khanewal district of Punjab, Pakistan, groundwater has severely deteriorated during the last few decades due to environmental changes and anthropogenic activities. Therefore, 68 groundwater samples were collected and analyzed for their main ions and trace elements to investigate the suitability of groundwater sources for drinking and agricultural purposes. Principal component analysis (PCA) and cluster analysis (CA) were employed to determine the major factors influencing groundwater quality. To assess the groundwater’s appropriateness for drinking and irrigation, drinking and agricultural indices were used. The pH of the groundwater samples ranged from 6.9 to 9.2, indicating that the aquifers were slightly acidic to alkaline. The major cations were distributed as follows: Na⁺ > Ca²⁺ > Mg²⁺ > K⁺. Meanwhile, the anions are distributed as follows: HCO₃⁻ > SO₄²⁻ > Cl⁻ > F⁻. The main hydrochemical facies were identified as a mixed type; however, a mixed magnesium, calcium, and chloride pattern was observed. The reverse ion exchange process helps in exchanging Na⁺ with Ca²⁺ and Mg²⁺ ions in the groundwater system. Rock weathering processes, such as the dissolution of calcite, dolomite, and gypsum minerals, dominated the groundwater hydrochemistry. According to the Weight Arithmetic Water Quality Index (WAWQI), 50% of the water samples were unsafe for drinking. The Wilcox diagram, USSL diagram, and some other agricultural indices resulted in around 32% of the groundwater samples being unsuitable for irrigation purposes. The Khanewal’s groundwater quality was vulnerable due to geology and the influence of anthropogenic activities. For groundwater sustainability in Khanewal, management strategies and policies are required. Full article

(This article belongs to the Section Hydrogeology)

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12 pages, 3146 KiB

Open AccessEditor’s ChoiceArticle

Anaerobic Digestion for Biogas Production from Municipal Sewage Sludge: A Comparative Study between Fine Mesh Sieved Primary Sludge and Sedimented Primary Sludge

by Phillimon T Odirile, Potlako M Marumoloa, Anthoula Manali and Petros Gikas

Water 2021, 13(24), 3532; https://doi.org/10.3390/w13243532 - 10 Dec 2021

Cited by 13 | Viewed by 3551

Abstract

Two different types of primary sewage sludge have been used as feedstock for production of biogas through anaerobic digestion (AD): the one type was sludge from a typical primary clarifier (PC), while the other type of sludge produced by a rotating belt filter, [...] Read more.

Two different types of primary sewage sludge have been used as feedstock for production of biogas through anaerobic digestion (AD): the one type was sludge from a typical primary clarifier (PC), while the other type of sludge produced by a rotating belt filter, commonly called microsieve (MS). Initially the main physicochemical characteristics of the sludges, such as total solids (TS), volatile solids (VS), VS/TS, pH and carbon to nitrogen ratio (C/N) were determined, for MS: 37.86 ± 0.08%, 83.00 ± 0.41%, 0.83 ± 0.00, 6.67 ± 0.08 and 19.68 ± 0.69, respectively, and for PC: 2.61 ± 0.08%, 78.77 ± 1.91%, 0.79 ± 0.02, 6.61 ± 0.10 and 14.46 ± 1.23, respectively. Then, calculated amounts of the sludges were inserted into airtight vials and were inoculated using anaerobic sludge. The daily biogas production was measured over a period of 30 days. PC sludge maximized the daily biogas production (44.20 ml_biogas/g_vsd) 11 days after inoculation, while the MS sludge reach a peak (37.74 ml_biogas/g_vsd) 14 days after inoculation. The cumulative biogas production over the 30 days of AD was in the same laver (442.29 ml_biogas/g_vs for PC versus 434.73 ml_biogas/g_vs for MS). However, PC sludge indicated higher daily biogas production, compared to MS sludge, while the opposite was observed for the period following the peak point. The Volatile Solids Reduction for PC and MS sludges was recorded as 46.06% and 32.39%, respectively. Full article

(This article belongs to the Special Issue Advances in Wastewater Treatment: Resources Recovery, Energy Neutralization, Water Reuse)

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14 pages, 4730 KiB

Open AccessEditor’s ChoiceArticle

Forest Fires Reduce Snow-Water Storage and Advance the Timing of Snowmelt across the Western U.S.

by Emily E. Smoot and Kelly E. Gleason

Water 2021, 13(24), 3533; https://doi.org/10.3390/w13243533 - 10 Dec 2021

Cited by 15 | Viewed by 3654

Abstract

As climate warms, snow-water storage is decreasing while forest fires are increasing in extent, frequency, and duration. The majority of forest fires occur in the seasonal snow zone across the western US. Yet, we do not understand the broad-scale variability of forest fire [...] Read more.

As climate warms, snow-water storage is decreasing while forest fires are increasing in extent, frequency, and duration. The majority of forest fires occur in the seasonal snow zone across the western US. Yet, we do not understand the broad-scale variability of forest fire effects on snow-water storage and water resource availability. Using pre- and post-fire data from 78 burned SNOTEL stations, we evaluated post-fire shifts in snow accumulation (snow-water storage) and snowmelt across the West and Alaska. For a decade following fire, maximum snow-water storage decreased by over 30 mm, and the snow disappearance date advanced by 9 days, and in high severity burned forests snowmelt rate increased by 3 mm/day. Regionally, forest fires reduced snow-water storage in Alaska, Arizona, and the Pacific Northwest and advanced the snow disappearance date across the Rockies, Western Interior, Wasatch, and Uinta mountains. Broad-scale empirical results of forest fire effects on snow-water storage and snowmelt inform natural resource management and modeling of future snow-water resource availability in burned watersheds. Full article

(This article belongs to the Section Hydrology)

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22 pages, 1386 KiB

Open AccessEditor’s ChoiceReview

Treatment of Textile Wastewater Using Advanced Oxidation Processes—A Critical Review

by Yiqing Zhang, Kashif Shaad, Derek Vollmer and Chi Ma

Water 2021, 13(24), 3515; https://doi.org/10.3390/w13243515 - 09 Dec 2021

Cited by 43 | Viewed by 6961

Abstract

Textile manufacturing is a multi-stage operation process that produces significant amounts of highly toxic wastewater. Given the size of the global textile market and its environmental impact, the development of effective, economical, and easy-to handle alternative treatment technologies for textile wastewater is of [...] Read more.

Textile manufacturing is a multi-stage operation process that produces significant amounts of highly toxic wastewater. Given the size of the global textile market and its environmental impact, the development of effective, economical, and easy-to handle alternative treatment technologies for textile wastewater is of significant interest. Based on the analysis of peer-reviewed publications over the last two decades, this paper provides a comprehensive review of advanced oxidation processes (AOPs) on textile wastewater treatment, including their performances, mechanisms, advantages, disadvantages, influencing factors, and electrical energy per order (E_EO) requirements. Fenton-based AOPs show the lowest median E_EO value of 0.98 kWh m⁻³ order⁻¹, followed by photochemical (3.20 kWh m⁻³ order⁻¹), ozonation (3.34 kWh m⁻³ order⁻¹), electrochemical (29.5 kWh m⁻³ order⁻¹), photocatalysis (91 kWh m⁻³ order⁻¹), and ultrasound (971.45 kWh m⁻³ order⁻¹). The Fenton process can treat textile effluent at the lowest possible cost due to the minimal energy input and low reagent cost, while Ultrasound-based AOPs show the lowest electrical efficiency due to the high energy consumption. Further, to explore the applicability of these methods, available results from a full-scale implementation of the enhanced Fenton technology at a textile mill wastewater treatment plant (WWTP) are discussed. The WWTP operates at an estimated cost of CNY ¥1.62 m⁻³ (USD $0.23 m⁻³) with effluent meeting the China Grade I-A pollutant discharge standard for municipal WWTPs, indicating that the enhanced Fenton technology is efficient and cost-effective in industrial treatment for textile effluent. Full article

(This article belongs to the Special Issue New Advanced Oxidation Process and Catalyst for Water and Wastewater Treatment)

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21 pages, 6212 KiB

Open AccessEditor’s ChoiceArticle

Development of Boosted Machine Learning Models for Estimating Daily Reference Evapotranspiration and Comparison with Empirical Approaches

by Saeid Mehdizadeh, Babak Mohammadi, Quoc Bao Pham and Zheng Duan

Water 2021, 13(24), 3489; https://doi.org/10.3390/w13243489 - 07 Dec 2021

Cited by 20 | Viewed by 3054

Abstract

Proper irrigation scheduling and agricultural water management require a precise estimation of crop water requirement. In practice, reference evapotranspiration (ETo) is firstly estimated, and used further to calculate the evapotranspiration of each crop. In this study, two new coupled models were developed for [...] Read more.

Proper irrigation scheduling and agricultural water management require a precise estimation of crop water requirement. In practice, reference evapotranspiration (ETo) is firstly estimated, and used further to calculate the evapotranspiration of each crop. In this study, two new coupled models were developed for estimating daily ETo. Two optimization algorithms, the shuffled frog-leaping algorithm (SFLA) and invasive weed optimization (IWO), were coupled on an adaptive neuro-fuzzy inference system (ANFIS) to develop and implement the two novel hybrid models (ANFIS-SFLA and ANFIS-IWO). Additionally, four empirical models with varying complexities, including Hargreaves–Samani, Romanenko, Priestley–Taylor, and Valiantzas, were used and compared with the developed hybrid models. The performance of all investigated models was evaluated using the ETo estimates with the FAO-56 recommended method as a benchmark, as well as multiple statistical indicators including root-mean-square error (RMSE), relative RMSE (RRMSE), mean absolute error (MAE), coefficient of determination (R²), and Nash–Sutcliffe efficiency (NSE). All models were tested in Tabriz and Shiraz, Iran as the two studied sites. Evaluation results showed that the developed coupled models yielded better results than the classic ANFIS, with the ANFIS-SFLA outperforming the ANFIS-IWO. Among empirical models, generally the Valiantzas model in its original and calibrated versions presented the best performance. In terms of model complexity (the number of predictors), the model performance was obviously enhanced by an increasing number of predictors. The most accurate estimates of the daily ETo for the study sites were achieved via the hybrid ANFIS-SFLA models using full predictors, with RMSE within 0.15 mm day⁻¹, RRMSE within 4%, MAE within 0.11 mm day⁻¹, and both a high R² and NSE of 0.99 in the test phase at the two studied sites. Full article

(This article belongs to the Topic Recent Advances in Hydroinformatics: Focusing on Machine Learning and Remote Sensing in Hydrology)

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21 pages, 15505 KiB

Open AccessEditor’s ChoiceArticle

Block-Greedy and CNN Based Underwater Image Dehazing for Novel Depth Estimation and Optimal Ambient Light

by Fayadh Alenezi, Ammar Armghan, Sachi Nandan Mohanty, Rutvij H. Jhaveri and Prayag Tiwari

Water 2021, 13(23), 3470; https://doi.org/10.3390/w13233470 - 06 Dec 2021

Cited by 61 | Viewed by 3484

Abstract

A lack of adequate consideration of underwater image enhancement gives room for more research into the field. The global background light has not been adequately addressed amid the presence of backscattering. This paper presents a technique based on pixel differences between global and [...] Read more.

A lack of adequate consideration of underwater image enhancement gives room for more research into the field. The global background light has not been adequately addressed amid the presence of backscattering. This paper presents a technique based on pixel differences between global and local patches in scene depth estimation. The pixel variance is based on green and red, green and blue, and red and blue channels besides the absolute mean intensity functions. The global background light is extracted based on a moving average of the impact of suspended light and the brightest pixels within the image color channels. We introduce the block-greedy algorithm in a novel Convolutional Neural Network (CNN) proposed to normalize different color channels’ attenuation ratios and select regions with the lowest variance. We address the discontinuity associated with underwater images by transforming both local and global pixel values. We minimize energy in the proposed CNN via a novel Markov random field to smooth edges and improve the final underwater image features. A comparison of the performance of the proposed technique against existing state-of-the-art algorithms using entropy, Underwater Color Image Quality Evaluation (UCIQE), Underwater Image Quality Measure (UIQM), Underwater Image Colorfulness Measure (UICM), and Underwater Image Sharpness Measure (UISM) indicate better performance of the proposed approach in terms of average and consistency. As it concerns to averagely, UICM has higher values in the technique than the reference methods, which explainsits higher color balance. The

μ

values of UCIQE, UISM, and UICM of the proposed method supersede those of the existing techniques. The proposed noted a percent improvement of 0.4%, 4.8%, 9.7%, 5.1% and 7.2% in entropy, UCIQE, UIQM, UICM and UISM respectively compared to the best existing techniques. Consequently, dehazed images have sharp, colorful, and clear features in most images when compared to those resulting from the existing state-of-the-art methods. Stable

σ

values explain the consistency in visual analysis in terms of sharpness of color and clarity of features in most of the proposed image results when compared with reference methods. Our own assessment shows that only weakness of the proposed technique is that it only applies to underwater images. Future research could seek to establish edge strengthening without color saturation enhancement. Full article

(This article belongs to the Special Issue AI and Deep Learning Applications for Water Management)

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21 pages, 4783 KiB

Open AccessEditor’s ChoiceArticle

Characteristics of Turbulence in the Downstream Region of a Vegetation Patch

by Masoud Kazem, Hossein Afzalimehr and Jueyi Sui

Water 2021, 13(23), 3468; https://doi.org/10.3390/w13233468 - 06 Dec 2021

Cited by 14 | Viewed by 2352

Abstract

In presence of vegetation patches in a channel bed, different flow–morphology interactions in the river will result. The investigation of the nature and intensity of these structures is a crucial part of the research works of river engineering. In this experimental study, the [...] Read more.

In presence of vegetation patches in a channel bed, different flow–morphology interactions in the river will result. The investigation of the nature and intensity of these structures is a crucial part of the research works of river engineering. In this experimental study, the characteristics of turbulence in the non-developed region downstream of a vegetation patch suffering from a gradual fade have been investigated. The changes in turbulent structure were tracked in sequential patterns by reducing the patch size. The model vegetation was selected carefully to simulate the aquatic vegetation patches in natural rivers. Velocity profile, TKE (Turbulent Kinetic Energy), turbulent power spectra and quadrant analysis have been used to investigate the behavior and intensity of the turbulent structures. The results of the velocity profile and TKE indicate that there are three different flow layers in the region downstream of the vegetation patch, including the wake layer, mixing layer and shear layer. When the vegetation patch is wide enough (D_v/D_c > 0.5, termed as the patch width ratio, where D_v is the width of a vegetation patch and D_c is the width of the channel), highly intermittent anisotropic turbulent events appear in the mixing layer at the depth of z/H_v = 0.7~1.1 and distance of x/H_v = 8~12 (where x is streamwise distance from the patch edge, z is vertical distance from channel bed and H_v is the height of a vegetation patch). The results of quadrant analysis show that these structures are associated with the dominance of the outward interactions (Q1). Moreover, these structures accompany large coherent Reynolds shear stresses, anomalies in streamwise velocity, increases in the standard deviation of TKE and increases in intermittent Turbulent Kinetic Energy (TKE_i). The intensity and extents of these structures fade with the decrease in the size of a vegetation patch. On the other hand, as the size of the vegetation patch decreases, von Karman vortexes appear in the wake layer and form the dominant flow structures in the downstream region of a vegetation patch. Full article

(This article belongs to the Special Issue Fluvial Hydraulics Affected by River Ice and Hydraulic Structures)

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18 pages, 2145 KiB

Open AccessFeature PaperEditor’s ChoiceReview

Sustainable Treatment of Food Industry Wastewater Using Membrane Technology: A Short Review

by Md. Nahid Pervez, Monira Rahman Mishu, George K. Stylios, Shadi W. Hasan, Yaping Zhao, Yingjie Cai, Tiziano Zarra, Vincenzo Belgiorno and Vincenzo Naddeo

Water 2021, 13(23), 3450; https://doi.org/10.3390/w13233450 - 05 Dec 2021

Cited by 20 | Viewed by 7740

Abstract

Water is needed for food processing facilities to carry out a number of tasks, including moving goods, washing, processing, and cleaning operations. This causes them to produce wastewater effluent, and they are typically undesirable since it contains a high volume of suspended solids, [...] Read more.

Water is needed for food processing facilities to carry out a number of tasks, including moving goods, washing, processing, and cleaning operations. This causes them to produce wastewater effluent, and they are typically undesirable since it contains a high volume of suspended solids, bacteria, dyestuffs, salts, oils, fats, chemical oxygen demand and biological oxygen demand. Therefore, treatment of food industry wastewater effluent is critical in improving process conditions, socio-economic benefits and our environmental. This short review summarizes the role of available membrane technologies that have been employed for food wastewater treatment and analyse their performance. Particularly, electrospun nanofiber membrane technology is revealed as an emerging membrane science and technology area producing materials of increasing performance and effectiveness in treating wastewater. This review reveals the challenges and perspectives that will assist in treating the food industry wastewater by developing novel membrane technologies. Full article

(This article belongs to the Special Issue Contaminants of Emerging Concern in the Urban Water Cycle: Fate, Occurrence, Detection, Monitoring, and Control)

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15 pages, 2687 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Quantile-Based Hydrological Modelling

by Hristos Tyralis and Georgia Papacharalampous

Water 2021, 13(23), 3420; https://doi.org/10.3390/w13233420 - 03 Dec 2021

Cited by 16 | Viewed by 3299

Abstract

Predictive uncertainty in hydrological modelling is quantified by using post-processing or Bayesian-based methods. The former methods are not straightforward and the latter ones are not distribution-free (i.e., assumptions on the probability distribution of the hydrological model’s output are necessary). To alleviate possible limitations [...] Read more.

Predictive uncertainty in hydrological modelling is quantified by using post-processing or Bayesian-based methods. The former methods are not straightforward and the latter ones are not distribution-free (i.e., assumptions on the probability distribution of the hydrological model’s output are necessary). To alleviate possible limitations related to these specific attributes, in this work we propose the calibration of the hydrological model by using the quantile loss function. By following this methodological approach, one can directly simulate pre-specified quantiles of the predictive distribution of streamflow. As a proof of concept, we apply our method in the frameworks of three hydrological models to 511 river basins in the contiguous US. We illustrate the predictive quantiles and show how an honest assessment of the predictive performance of the hydrological models can be made by using proper scoring rules. We believe that our method can help towards advancing the field of hydrological uncertainty. Full article

(This article belongs to the Special Issue Using Statistical and Machine Learning Algorithms for Big Data Applications in Hydrology)

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16 pages, 5237 KiB

Open AccessEditor’s ChoiceArticle

Development of a Deep Learning Emulator for a Distributed Groundwater–Surface Water Model: ParFlow-ML

by Hoang Tran, Elena Leonarduzzi, Luis De la Fuente, Robert Bruce Hull, Vineet Bansal, Calla Chennault, Pierre Gentine, Peter Melchior, Laura E. Condon and Reed M. Maxwell

Water 2021, 13(23), 3393; https://doi.org/10.3390/w13233393 - 01 Dec 2021

Cited by 18 | Viewed by 4663

Abstract

Integrated hydrologic models solve coupled mathematical equations that represent natural processes, including groundwater, unsaturated, and overland flow. However, these models are computationally expensive. It has been recently shown that machine leaning (ML) and deep learning (DL) in particular could be used to emulate [...] Read more.

Integrated hydrologic models solve coupled mathematical equations that represent natural processes, including groundwater, unsaturated, and overland flow. However, these models are computationally expensive. It has been recently shown that machine leaning (ML) and deep learning (DL) in particular could be used to emulate complex physical processes in the earth system. In this study, we demonstrate how a DL model can emulate transient, three-dimensional integrated hydrologic model simulations at a fraction of the computational expense. This emulator is based on a DL model previously used for modeling video dynamics, PredRNN. The emulator is trained based on physical parameters used in the original model, inputs such as hydraulic conductivity and topography, and produces spatially distributed outputs (e.g., pressure head) from which quantities such as streamflow and water table depth can be calculated. Simulation results from the emulator and ParFlow agree well with average relative biases of 0.070, 0.092, and 0.032 for streamflow, water table depth, and total water storage, respectively. Moreover, the emulator is up to 42 times faster than ParFlow. Given this promising proof of concept, our results open the door to future applications of full hydrologic model emulation, particularly at larger scales. Full article

(This article belongs to the Special Issue Considerations of the Uses of Machine Learning in Subsurface Hydrology)

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22 pages, 2250 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Improving Drought Modeling Using Hybrid Random Vector Functional Link Methods

by Rana Muhammad Adnan, Reham R. Mostafa, Abu Reza Md. Towfiqul Islam, Alireza Docheshmeh Gorgij, Alban Kuriqi and Ozgur Kisi

Water 2021, 13(23), 3379; https://doi.org/10.3390/w13233379 - 01 Dec 2021

Cited by 38 | Viewed by 3310

Abstract

Drought modeling is essential in water resources planning and management in mitigating its effects, especially in arid regions. Climate change highly influences the frequency and intensity of droughts. In this study, new hybrid methods, the random vector functional link (RVFL) integrated with particle [...] Read more.

Drought modeling is essential in water resources planning and management in mitigating its effects, especially in arid regions. Climate change highly influences the frequency and intensity of droughts. In this study, new hybrid methods, the random vector functional link (RVFL) integrated with particle swarm optimization (PSO), the genetic algorithm (GA), the grey wolf optimization (GWO), the social spider optimization (SSO), the salp swarm algorithm (SSA) and the hunger games search algorithm (HGS) were used to forecast droughts based on the standard precipitation index (SPI). Monthly precipitation data from three stations in Bangladesh were used in the applications. The accuracy of the methods was compared by forecasting four SPI indices, SPI3, SPI6, SPI9, and SPI12, using the root mean square errors (RMSE), the mean absolute error (MAE), the Nash–Sutcliffe efficiency (NSE), and the determination coefficient (R²). The HGS algorithm provided a better performance than the alternative algorithms, and it considerably improved the accuracy of the RVFL method in drought forecasting; the improvement in RMSE for the SPI3, SP6, SPI9, and SPI12 was by 6.14%, 11.89%, 14.14%, 24.5% in station 1, by 6.02%, 17.42%, 13.49%, 24.86% in station 2 and by 7.55%, 26.45%, 15.27%, 13.21% in station 3, respectively. The outcomes of the study recommend the use of a HGS-based RVFL in drought modeling. Full article

(This article belongs to the Special Issue Projection of Groundwater Levels, Spring Flows, Lake Dynamics, Extreme Drought Events, and Floods under Future Climates Using Artificial Intelligence Models)

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15 pages, 3448 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Citizen Science for Marine Litter Detection and Classification on Unmanned Aerial Vehicle Images

by Silvia Merlino, Marco Paterni, Marina Locritani, Umberto Andriolo, Gil Gonçalves and Luciano Massetti

Water 2021, 13(23), 3349; https://doi.org/10.3390/w13233349 - 25 Nov 2021

Cited by 30 | Viewed by 4753

Abstract

Unmanned aerial vehicles (UAV, aka drones) are being used for mapping macro-litter in the environment. As drone images require a manual processing task for detecting marine litter, it is of interest to evaluate the accuracy of non-expert citizen science operators (CSO) in performing [...] Read more.

Unmanned aerial vehicles (UAV, aka drones) are being used for mapping macro-litter in the environment. As drone images require a manual processing task for detecting marine litter, it is of interest to evaluate the accuracy of non-expert citizen science operators (CSO) in performing this task. Students from Italian secondary schools (in this work, the CSO) were invited to identify, mark, and classify stranded litter items on a UAV orthophoto collected on an Italian beach. A specific training program and working tools were developed for the aim. The comparison with the standard in situ visual census survey returned a general underestimation (50%) of items. However, marine litter bulk categorisation was fairly in agreement with the in situ survey, especially for sources classification. The concordance level among CSO ranged between 60% and 91%, depending on the item properties considered (type, material, and colour). As the assessment accuracy was in line with previous works developed by experts, remote detection of marine litter on UAV images can be improved through citizen science programs, upon an appropriate training plan and provision of specific tools. Full article

(This article belongs to the Special Issue Pattern Analysis, Recognition and Classification of Marine Data)

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20 pages, 3508 KiB

Open AccessEditor’s ChoiceArticle

Antibiotic Resistance Genes and Potentially Pathogenic Bacteria in the Central Adriatic Sea: Are They Connected to Urban Wastewater Inputs?

by Viviana Fonti, Andrea Di Cesare, Jadranka Šangulin, Paola Del Negro and Mauro Celussi

Water 2021, 13(23), 3335; https://doi.org/10.3390/w13233335 - 24 Nov 2021

Cited by 12 | Viewed by 3368

Abstract

Despite last decades’ interventions within local and communitarian programs, the Mediterranean Sea still receives poorly treated urban wastewater (sewage). Wastewater treatment plants (WWTPs) performing primary sewage treatments have poor efficiency in removing microbial pollutants, including fecal indicator bacteria, pathogens, and mobile genetic elements [...] Read more.

Despite last decades’ interventions within local and communitarian programs, the Mediterranean Sea still receives poorly treated urban wastewater (sewage). Wastewater treatment plants (WWTPs) performing primary sewage treatments have poor efficiency in removing microbial pollutants, including fecal indicator bacteria, pathogens, and mobile genetic elements conferring resistance to antimicrobials. Using a combination of molecular tools, we investigated four urban WWTPs (i.e., two performing only mechanical treatments and two performing a subsequent conventional secondary treatment by activated sludge) as continuous sources of microbial pollution for marine coastal waters. Sewage that underwent only primary treatments was characterized by a higher content of traditional and alternative fecal indicator bacteria, as well as potentially pathogenic bacteria (especially Acinetobacter, Coxiella, Prevotella, Streptococcus, Pseudomonas, Vibrio, Empedobacter, Paracoccus, and Leptotrichia), than those subjected to secondary treatment. However, seawater samples collected next to the discharging points of all the WWTPs investigated here revealed a marked fecal signature, despite significantly lower values in the presence of secondary treatment of the sewage. WWTPs in this study represented continuous sources of antibiotic resistance genes (ARGs) ermB, qnrS, sul2, tetA, and bla_TEM (the latter only for three WWTPs out of four). Still, no clear effects of the two depuration strategies investigated here were detected. Some marine samples were identified as positive to the colistin-resistance gene mcr-1, an ARG that threatens colistin antibiotics’ clinical utility in treating infections with multidrug-resistant bacteria. This study provides evidence that the use of sole primary treatments in urban wastewater management results in pronounced inputs of microbial pollution into marine coastal waters. At the same time, the use of conventional treatments does not fully eliminate ARGs in treated wastewater. The complementary use of molecular techniques could successfully improve the evaluation of the depuration efficiency and help develop novel solutions for the treatment of urban wastewater. Full article

(This article belongs to the Special Issue The Impact of Treated Urban Wastewaters and Flood Discharge on the Quality of the Bathing Water)

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28 pages, 1120 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Management of Urban Waters with Nature-Based Solutions in Circular Cities—Exemplified through Seven Urban Circularity Challenges

by Hasan Volkan Oral, Matej Radinja, Anacleto Rizzo, Katharina Kearney, Theis Raaschou Andersen, Pawel Krzeminski, Gianluigi Buttiglieri, Derya Ayral-Cinar, Joaquim Comas, Magdalena Gajewska, Marco Hartl, David C. Finger, Jan K. Kazak, Harri Mattila, Patrícia Vieira, Patrizia Piro, Stefania Anna Palermo, Michele Turco, Behrouz Pirouz, Alexandros Stefanakis, Martin Regelsberger, Nadia Ursino and Pedro N. Carvalho Show full author list Hide full author list

Water 2021, 13(23), 3334; https://doi.org/10.3390/w13233334 - 24 Nov 2021

Cited by 39 | Viewed by 8304

Abstract

Nature-Based Solutions (NBS) have been proven to effectively mitigate and solve resource depletion and climate-related challenges in urban areas. The COST (Cooperation in Science and Technology) Action CA17133 entitled “Implementing nature-based solutions (NBS) for building a resourceful circular city” has established seven urban [...] Read more.

Nature-Based Solutions (NBS) have been proven to effectively mitigate and solve resource depletion and climate-related challenges in urban areas. The COST (Cooperation in Science and Technology) Action CA17133 entitled “Implementing nature-based solutions (NBS) for building a resourceful circular city” has established seven urban circularity challenges (UCC) that can be addressed effectively with NBS. This paper presents the outcomes of five elucidation workshops with more than 20 European experts from different backgrounds. These international workshops were used to examine the effectiveness of NBS to address UCC and foster NBS implementation towards circular urban water management. A major outcome was the identification of the two most relevant challenges for water resources in urban areas: ‘Restoring and maintaining the water cycle’ (UCC1) and ‘Water and waste treatment, recovery, and reuse’ (UCC2). s Moreover, significant synergies with ‘Nutrient recovery and reuse’, ‘Material recovery and reuse’, ‘Food and biomass production’, ‘Energy efficiency and recovery’, and ‘Building system recovery’ were identified. Additionally, the paper presents real-life case studies to demonstrate how different NBS and supporting units can contribute to the UCC. Finally, a case-based semi-quantitative assessment of the presented NBS was performed. Most notably, this paper identifies the most typically employed NBS that enable processes for UCC1 and UCC2. While current consensus is well established by experts in individual NBS, we presently highlight the potential to address UCC by combining different NBS and synergize enabling processes. This study presents a new paradigm and aims to enhance awareness on the ability of NBS to solve multiple urban circularity issues. Full article

(This article belongs to the Special Issue Water and Circular Cities)

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19 pages, 3407 KiB

Open AccessEditor’s ChoiceArticle

Health Risk of the Shallow Groundwater and Its Suitability for Drinking Purpose in Tongchuan, China

by Abel Nsabimana, Peiyue Li, Song He, Xiaodong He, S. M. Khorshed Alam and Misbah Fida

Water 2021, 13(22), 3256; https://doi.org/10.3390/w13223256 - 17 Nov 2021

Cited by 33 | Viewed by 3344

Abstract

Studying the quality and health risks of groundwater is of great significance for sustainable water resources utilization, especially in arid and semi-arid areas around the world. The current study is carried out to evaluate the quality and potential health risks of groundwater in [...] Read more.

Studying the quality and health risks of groundwater is of great significance for sustainable water resources utilization, especially in arid and semi-arid areas around the world. The current study is carried out to evaluate the quality and potential health risks of groundwater in the Tongchuan area on the Loess Plateau, northwest China. Water quality index (WQI) and hydrochemical correlation analysis were implemented to understand the status of groundwater quality. Daily average exposure dosages through the oral and dermal contact exposure pathways were taken into consideration to calculate the health risks to the human body. Additionally, graphical approaches such as Piper diagram, Durov diagram and GIS mapping were used to help better understand the results of this study. The WQI approach showed that 77.1% of the samples were of excellent quality. The most significant parameters affecting water quality were NO₃⁻, F⁻, and Cr⁶⁺. The health risk assessment results showed that 27.1% and 54.2% of the samples lead to non-carcinogenic risks through oral intake for adults and children, respectively. In contrast, 12.5% of the groundwater samples would result in carcinogenic risks to the residents. This study showed that the WQI method needs to be supplemented by a health risk evaluation to obtain comprehensive results for groundwater quality protection and management in the Tongchuan area. Full article

(This article belongs to the Special Issue Groundwater Quality and Public Health)

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20 pages, 689 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Multi-Actor Platforms in the Water–Agriculture Nexus: Synergies and Long-Term Meaningful Engagement

by Ingrid Nesheim, Frode Sundnes, Caroline Enge, Morten Graversgaard, Cors van den Brink, Luke Farrow, Matjaž Glavan, Birgitte Hansen, Inês A. Leitão, Jenny Rowbottom and Linda Tendler

Water 2021, 13(22), 3204; https://doi.org/10.3390/w13223204 - 12 Nov 2021

Cited by 8 | Viewed by 3298

Abstract

Solutions to current complex environmental challenges demand the consultation and involvement of various groups in society. In light of the WFD’s requirements of public participation, this paper presents an analysis of the establishment and development of nine different multi-actor platforms (MAPs) across Europe [...] Read more.

Solutions to current complex environmental challenges demand the consultation and involvement of various groups in society. In light of the WFD’s requirements of public participation, this paper presents an analysis of the establishment and development of nine different multi-actor platforms (MAPs) across Europe set up as arenas for long-term engagements to solve water quality challenges in relation to agriculture. The MAPs represent different histories and legacies of engagement; some are recent initiatives and some are affiliated with previous government-initiated projects, while other MAPs are long-term engagement platforms. A case study approach drawing on insights from the nine engagement processes is used to discuss conditions for enabling long-term multi-actor engagement. The perceived pressure for change and preferred prioritization in complying with mitigating water quality problems vary within and among the MAPs. The results show that governmental and local actors’ concern for water quality improvements and focusing on pressure for change are important for establishing meaningful multi-actor engagement when concerns translate into a clear mandate of the MAP. Furthermore, the degree to which the MAPs have been able to establish relationships and networks with other institutions such as water companies, agricultural and environmental authorities, farmers, and civil society organizations influences possibilities for long-term meaningful engagement. Full article

(This article belongs to the Special Issue Stakeholder Engagement and Governance Arrangements in Agricultural Catchments)

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27 pages, 3897 KiB

Open AccessEditor’s ChoiceArticle

Comparison of Desalination Technologies Using Renewable Energy Sources with Life Cycle, PESTLE, and Multi-Criteria Decision Analyses

by Huyen Trang Do Thi, Tibor Pasztor, Daniel Fozer, Flavio Manenti and Andras Jozsef Toth

Water 2021, 13(21), 3023; https://doi.org/10.3390/w13213023 - 28 Oct 2021

Cited by 59 | Viewed by 18498

Abstract

Nowadays, desalination continues to expand globally, which is one of the most effective solutions to solve the problem of the global drinking water shortage. However, desalination is not a fail-safe process and has many environmental and human health consequences. This paper investigated the [...] Read more.

Nowadays, desalination continues to expand globally, which is one of the most effective solutions to solve the problem of the global drinking water shortage. However, desalination is not a fail-safe process and has many environmental and human health consequences. This paper investigated the desalination procedure of seawater with different technologies, namely, multi-stage flash distillation (MSF), multi-effect distillation (MED), and reverse osmosis (RO), and with various energy sources (fossil energy, solar energy, wind energy, nuclear energy). The aim was to examine the different desalination technologies’ effectiveness with energy sources using three assessment methods, which were examined separately. The life cycle assessment (LCA), PESTLE, and multi-criteria decision analysis (MCDA) methods were used to evaluate each procedure. LCA was based on the following impact analysis and evaluation methods: ReCiPe 2016, IMPACT 2002+, and IPCC 2013 GWP 100a; PESTLE risk analysis evaluated the long-lasting impact on processes and technologies with political, economic, social, technological, legal, and environmental factors. Additionally, MCDA was based on the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method to evaluate desalination technologies. This study considered the operational phase of a plant, which includes the necessary energy and chemical needs, which is called “gate-to-gate” analysis. Saudi Arabia data were used for the analysis, with the base unit of 1 m³ of the water product. As the result of this study, RO combined with renewable energy provided outstanding benefits in terms of human health, ecosystem quality, and resources, as well as the climate change and emissions of GHGs categories. Full article

(This article belongs to the Special Issue Innovative Technologies for Lower Energy Consumption in Desalination and Water Reuse)

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20 pages, 4622 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Here Comes the Flood, but Not Failure? Lessons to Learn after the Heavy Rain and Pluvial Floods in Germany 2021

by Alexander Fekete and Simone Sandholz

Water 2021, 13(21), 3016; https://doi.org/10.3390/w13213016 - 27 Oct 2021

Cited by 87 | Viewed by 12500

Abstract

Floods are a known natural hazard in Germany, but the amount of precipitation and ensuing high death toll and damages after the events especially from 14 to 15 July 2021 came as a surprise. Almost immediately questions about failure in the early warning [...] Read more.

Floods are a known natural hazard in Germany, but the amount of precipitation and ensuing high death toll and damages after the events especially from 14 to 15 July 2021 came as a surprise. Almost immediately questions about failure in the early warning chains and the effectiveness of the German response emerged, also internationally. This article presents lessons to learn and argues against a blame culture. The findings are based on comparisons with findings from previous research projects carried out in the Rhein-Erft Kreis and the city of Cologne, as well as on discussions with operational relief forces after the 2021 events. The main disaster aspects of the 2021 flood are related to issuing and understanding warnings, a lack of information and data exchange, unfolding upon a situation of an ongoing pandemic and aggravated further by critical infrastructure failure. Increasing frequencies of flash floods and other extremes due to climate change are just one side of the transformation and challenge, Germany and neighbouring countries are facing. The vulnerability paradox also heavily contributes to it; German society became increasingly vulnerable to failure due to an increased dependency on its infrastructure and emergency system, and the ensuing expectations of the public for a perfect system. Full article

(This article belongs to the Special Issue Smart Water Management and Flood Mitigation)

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14 pages, 4226 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Genome Sequencing of SARS-CoV-2 Allows Monitoring of Variants of Concern through Wastewater

by Malte Herold, Aymeric Fouquier d'Hérouël, Patrick May, Francesco Delogu, Anke Wienecke-Baldacchino, Jessica Tapp, Cécile Walczak, Paul Wilmes, Henry-Michel Cauchie, Guillaume Fournier and Leslie Ogorzaly

Water 2021, 13(21), 3018; https://doi.org/10.3390/w13213018 - 27 Oct 2021

Cited by 17 | Viewed by 4328

Abstract

Monitoring SARS-CoV-2 in wastewater has shown to be an effective tool for epidemiological surveillance. More specifically, RNA levels determined with RT-qPCR have been shown to track with the infection dynamics within the population. However, the surveillance of individual lineages circulating in the population [...] Read more.

Monitoring SARS-CoV-2 in wastewater has shown to be an effective tool for epidemiological surveillance. More specifically, RNA levels determined with RT-qPCR have been shown to track with the infection dynamics within the population. However, the surveillance of individual lineages circulating in the population based on genomic sequencing of wastewater samples is challenging, as the genetic material constitutes a mixture of different viral haplotypes. Here, we identify specific signature mutations from individual SARS-CoV-2 lineages in wastewater samples to estimate lineages circulating in Luxembourg. We compare circulating lineages and mutations to those detected in clinical samples amongst infected individuals. We show that especially for dominant lineages, the allele frequencies of signature mutations correspond to the occurrence of particular lineages in the population. In addition, we provide evidence that regional clusters can also be discerned. We focused on the time period between November 2020 and March 2021 in which several variants of concern emerged and specifically traced the lineage B.1.1.7, which became dominant in Luxembourg during that time. During the subsequent time points, we were able to reconstruct short haplotypes, highlighting the co-occurrence of several signature mutations. Our results highlight the potential of genomic surveillance in wastewater samples based on amplicon short-read data. By extension, our work provides the basis for the early detection of novel SARS-CoV-2 variants. Full article

(This article belongs to the Special Issue SARS-CoV-2 in Wastewater: Methods, Epidemiology and Future Goals)

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15 pages, 5626 KiB

Open AccessEditor’s ChoiceArticle

Biodegradation of Brown 706 Dye by Bacterial Strain Pseudomonas aeruginosa

by Asad Ullah Khan, Mujaddad Ur Rehman, Muhammad Zahoor, Abdul Bari Shah and Ivar Zekker

Water 2021, 13(21), 2959; https://doi.org/10.3390/w13212959 - 20 Oct 2021

Cited by 43 | Viewed by 2923

Abstract

Dyes are the most challenging pollutants for the aquatic environment that are not only toxic, but also interfering photosynthesis as light penetration into deep water is changed. A number of methods are used for the water reclamation, however, among them biological methods are [...] Read more.

Dyes are the most challenging pollutants for the aquatic environment that are not only toxic, but also interfering photosynthesis as light penetration into deep water is changed. A number of methods are used for the water reclamation, however, among them biological methods are preferably used due to their compatibility with nature. In the present research, 15 different bacterial strains were used to decolorize Brown 706 dye. Among the bacterial strains, Pseudomonas aeruginosa showed maximum decolorization activity; hence in the subsequent experiments Pseudomonas aeruginosa was used. First the decolorization activities were carried out under different physicochemical conditions to obtain the optimum decolorization benefits of the selected microorganism. The optimum conditions established were 37°C, pH of 7 and operation cycle time 72 h. In the subsequent experiment all optimum conditions were combined in a single experiment where 73.91% of decolorization efficiency was achieved. For the evaluation of metabolites formed after decolorization/degradation the aliquots containing bacteria were homogenized, filtered and then subjected to extraction. The extracted metabolites were then subjected to the silica gel column isolation. UV–Vis, FTIR, and NMR techniques were used to elucidate structures of the metabolites. Out of the collected metabolites only P-xylene was identified, which has been formed by cleavage of azo linkage by azo reductase enzyme of bacteria following the deamination and methylation of nitro substituted benzene ring. Full article

(This article belongs to the Special Issue Water Treatment by Adsorption and Catalytic Methods)

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14 pages, 7880 KiB

Open AccessEditor’s ChoiceReview

Wastewater-Based Epidemiology for Cost-Effective Mass Surveillance of COVID-19 in Low- and Middle-Income Countries: Challenges and Opportunities

by Sadhana Shrestha, Emi Yoshinaga, Saroj K. Chapagain, Geetha Mohan, Alexandros Gasparatos and Kensuke Fukushi

Water 2021, 13(20), 2897; https://doi.org/10.3390/w13202897 - 15 Oct 2021

Cited by 29 | Viewed by 5481

Abstract

Wastewater-based epidemiology (WBE) is an approach that can be used to estimate COVID-19 prevalence in the population by detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. As the WBE approach uses pooled samples from the study population, it is an [...] Read more.

Wastewater-based epidemiology (WBE) is an approach that can be used to estimate COVID-19 prevalence in the population by detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. As the WBE approach uses pooled samples from the study population, it is an inexpensive and non-invasive mass surveillance method compared to individual testing. Thus, it offers a good complement in low- and middle-income countries (LMICs) facing high costs of testing or social stigmatization, and it has a huge potential to monitor SARS-CoV-2 and its variants to curb the global COVID-19 pandemic. The aim of this review is to systematize the current evidence about the application of the WBE approach in mass surveillance of COVID-19 infection in LMICs, as well as its future potential. Among other parameters, population size contributing the fecal input to wastewater is an important parameter for COVID-19 prevalence estimation. It is easier to back-calculate COVID-19 prevalence in the community with centralized wastewater systems, because there can be more accurate estimates about the size of contributing population in the catchment. However, centralized wastewater management systems are often of low quality (or even non-existent) in LMICs, which raises a major concern about the ability to implement the WBE approach. However, it is possible to mobilize the WBE approach, if large areas are divided into sub-areas, corresponding to the existing wastewater management systems. In addition, a strong coordination between stakeholders is required for estimating population size respective to wastewater management systems. Nevertheless, further international efforts should be leveraged to strengthen the sanitation infrastructures in LMICs, using the lessons gathered from the current COVID-19 pandemic to be prepared for future pandemics. Full article

(This article belongs to the Special Issue Health-Related Water Microbiology and Wastewater-Based Epidemiology)

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15 pages, 18832 KiB

Open AccessEditor’s ChoiceArticle

Hyper-Nutrient Enrichment Status in the Sabalan Lake, Iran

by Roohollah Noori, Elmira Ansari, Yong-Wook Jeong, Saber Aradpour, Mohsen Maghrebi, Majid Hosseinzadeh and Sayed M. Bateni

Water 2021, 13(20), 2874; https://doi.org/10.3390/w13202874 - 14 Oct 2021

Cited by 24 | Viewed by 3432

Abstract

Lakes/reservoirs are rapidly deteriorating from cultural eutrophication due to anthropogenic factors. In this study, we aimed to (1) explore nutrient levels in the Sabalan dam reservoir (SDR) of northwest Iran, (2) determine the reservoir water fertility using the total phosphorus (TP) based and [...] Read more.

Lakes/reservoirs are rapidly deteriorating from cultural eutrophication due to anthropogenic factors. In this study, we aimed to (1) explore nutrient levels in the Sabalan dam reservoir (SDR) of northwest Iran, (2) determine the reservoir water fertility using the total phosphorus (TP) based and total nitrogen (TN) based Carlson trophic state indices, and (3) specify primary limiting factors for the reservoir eutrophication. Our field observations showed a state of hyper-nutrient enrichment in the SDR. The highest variation of TN in the reservoir water column happened when the reservoir was severely stratified (in August) while the highest variation of TP took place when the thermocline was attenuated with the deepening of the epilimnion (in October). Both TP and TN based trophic indicators classified the SDR as a hypereutrophic lake. TN:TP molar ratio averaged at the epilimnion indicated a P–deficiency in the reservoir during warm months whilst it suggested a co–deficiency of P and N in cold months. Given the hyper-nutrient enrichment state in the reservoir, other drivers such as water residence time (WRT) can also act as the main contributor of eutrophication in the SDR. We found that WRT in the SDR varied from hundreds to thousands of days, which was much longer than that of other reservoirs/lakes with the same and even much greater storage capacity. Therefore, both hyper-nutrient enrichment and WRT mainly controlled eutrophication in the reservoir. Given time consuming and expensive management practices for reducing nutrients in the watershed, changes in the SDR operation are suggested to somewhat recover its hypereutrophic state in the short-term. However, strategic long-term recovery plans are required to reduce the transition of nutrients from the watershed to the SDR. Full article

(This article belongs to the Special Issue Water Quality Management of Inland Waters)

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