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Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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11 pages, 2275 KiB  
Article
Rainfall Threshold for Shallow Landslide Triggering Due to Rising Water Table
by Antonello Troncone, Luigi Pugliese and Enrico Conte
Water 2022, 14(19), 2966; https://doi.org/10.3390/w14192966 - 21 Sep 2022
Cited by 17 | Viewed by 3019
Abstract
In the present study, a simple-to-use method is proposed for a preliminary prediction of the occurrence of shallow landslides (generally, with a thickness of 1–2 m) due to rainfall. This method can be used when a water table forms within the slope or [...] Read more.
In the present study, a simple-to-use method is proposed for a preliminary prediction of the occurrence of shallow landslides (generally, with a thickness of 1–2 m) due to rainfall. This method can be used when a water table forms within the slope or the existing groundwater level rises due to rain infiltration, resulting in an increase in the pore water pressure. A relationship is also provided to establish when these conditions occur and the method can consequently be used. The proposed method combines a simplified solution to evaluate the change in pore water pressure within the slope due to infiltration, with the simple scheme of infinite slope to calculate a critical value of the pore water pressure that determines the incipient failure condition of the slope. In this way, a threshold curve can be also determined to readily assess whether a rainfall event with expected intensity and duration is capable of causing a slope failure at a given depth, where the initial pore water pressure is known. The method is completely analytical and only requires a few parameters as input data, which in addition can be obtained from conventional tests. A well-documented case study is considered to show how the method can be used for routine applications. Full article
(This article belongs to the Special Issue Susceptibility Assessment of Rainfall-Induced Landslides)
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23 pages, 8041 KiB  
Article
Flood-Frequency Analysis for Dams in Romania
by Cornel Ilinca and Cristian Gabriel Anghel
Water 2022, 14(18), 2884; https://doi.org/10.3390/w14182884 - 15 Sep 2022
Cited by 19 | Viewed by 6347
Abstract
Accurately determining the maximum designed water discharges of dams is extremely important, considering the economic costs of carrying out these types of hydrotechnical works and the possible disastrous consequences resulting from their incorrect design. This article describes and applies probability distributions used in [...] Read more.
Accurately determining the maximum designed water discharges of dams is extremely important, considering the economic costs of carrying out these types of hydrotechnical works and the possible disastrous consequences resulting from their incorrect design. This article describes and applies probability distributions used in hydrology, with some recommended by Romanian legislation standard NP 129-2011. The methods for estimating the parameters presented in this article, as well as the establishment of directions for correlating the normative with international regulations, resulting from the research on many rivers with different characteristics, conducted within the Faculty of Hydrotechnics, were completed with specialized computer applications for applying the normative. In this article, two case studies reflecting this research are presented. The verification of the proposed recommendations, on rivers with hydrographic basins with different physiographic characteristics, confirmed the opportunity to implement rigorous and simple criteria. The presentation of the quantile form of some distributions (especially Pearson III) and of the expressions of moments (central and raw) of high order, as well as the presentation of the frequency factors of each analyzed distribution necessary to calculate the confidence interval, constitute novelties, thus facilitating the ease of use of these distributions. Full article
(This article belongs to the Section Hydrology)
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15 pages, 2472 KiB  
Article
The Effect and Influence Mechanism of Soil Salinity on Phosphorus Availability in Coastal Salt-Affected Soils
by Wenping Xie, Jingsong Yang, Shan Gao, Rongjiang Yao and Xiangping Wang
Water 2022, 14(18), 2804; https://doi.org/10.3390/w14182804 - 9 Sep 2022
Cited by 50 | Viewed by 6875
Abstract
Soil salinization is a problem that arouses the world’s attention. Soil salinity is an important limitation for agriculture production in coastal area. Phosphorus is a very important nutrient element in the process of plant growth, and its effectiveness affects plant growth to a [...] Read more.
Soil salinization is a problem that arouses the world’s attention. Soil salinity is an important limitation for agriculture production in coastal area. Phosphorus is a very important nutrient element in the process of plant growth, and its effectiveness affects plant growth to a great extent. In this study, soil available phosphorus and its component in Hedley phosphorus classification were found to be affected by soil salinity in coastal areas of Jiangsu Province. Several key environmental factors changed under the saline environment of the coastal areas, such as soil salinity, soil pH, and soil alkaline phosphatase activity. These environmental factors were significantly correlated with soil available phosphorus. Results showed that there were significant correlations between soil salinity and other environmental factors, and soil salinity and alkaline phosphatase activity were the main influencing factors of soil available phosphorus in this study. Significant positive correlation was found between alkaline phosphatase activity and soil salt content, and soil salinity was considered as the most important impact factor for soil available phosphorus as it affected the surrounding environment, and the soil alkaline phosphatase could be considered as the direct influencing factor for soil available phosphorus. Analysis between the soil alkaline phosphatase activity and phosphorus component showed that soil alkaline phosphatase activity could increase the proportion of active inorganic phosphorus and medium active inorganic phosphorus in soil phosphorus pool, which explained the effect of soil alkaline phosphatase activity on soil available phosphorus. Full article
(This article belongs to the Special Issue Monitoring, Reclamation and Management of Salt-Affected Lands)
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14 pages, 2822 KiB  
Article
Analyzing the Impacts of Sewer Type and Spatial Distribution of LID Facilities on Urban Runoff and Non-Point Source Pollution Using the Storm Water Management Model (SWMM)
by Jimin Lee, Jinsun Kim, Jong Mun Lee, Hee Seon Jang, Minji Park, Joong Hyuk Min and Eun Hye Na
Water 2022, 14(18), 2776; https://doi.org/10.3390/w14182776 - 6 Sep 2022
Cited by 14 | Viewed by 3506
Abstract
The negative changes in the hydrological cycle are increasing due to climate change and urbanization, resulting in deterioration of water quality and environmental issues. Although Low-Impact Development (LID) techniques studies have been conducted to solve this problem, the spatial distribution of LID facilities [...] Read more.
The negative changes in the hydrological cycle are increasing due to climate change and urbanization, resulting in deterioration of water quality and environmental issues. Although Low-Impact Development (LID) techniques studies have been conducted to solve this problem, the spatial distribution of LID facilities and sewer types has received less attention. In this study, it is proposed to analyze the effects of sewer type, the spatial distribution of LID facilities, and LID type on runoff and water quality using the Storm Water Management Model and to identify effective ways of improving the hydrological cycle and Non-Point Source (NPS) pollution associated with urbanization. As a result of the runoff reduction analysis, 68% of the rainfall was discharged at the outlet for separate sewers, 79% for combined sewers without storage tank, and 49% for combined sewers with storage tank. The LID scenario results showed the distributed LID application method has higher reduction efficiency of runoff and NPS pollution than the intensive application method. Moreover, intensive application of LID in downstream areas resulted in higher runoff reduction efficiency than the application of LID in upstream areas. It will be used not only in the hydrological cycle plan but also in NPS pollution management. Full article
(This article belongs to the Special Issue Stormwater Management in Urban and Rural Areas)
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17 pages, 2738 KiB  
Article
Crop Water Deficit and Supplemental Irrigation Requirements for Potato Production in a Temperate Humid Region (Prince Edward Island, Canada)
by Serban Danielescu, Kerry T. B. MacQuarrie, Bernie Zebarth, Judith Nyiraneza, Mark Grimmett and Mona Levesque
Water 2022, 14(17), 2748; https://doi.org/10.3390/w14172748 - 3 Sep 2022
Cited by 18 | Viewed by 3652
Abstract
The global increase in potato production and yield is expected to lead to increased irrigation needs and this has prompted concerns with respect to the sustainability of irrigation water sources, such as groundwater. The magnitude, and inter- and intra-annual variation, of the crop [...] Read more.
The global increase in potato production and yield is expected to lead to increased irrigation needs and this has prompted concerns with respect to the sustainability of irrigation water sources, such as groundwater. The magnitude, and inter- and intra-annual variation, of the crop water requirements and irrigation needs for potato production together with their impact on aquifer storage in a temperate humid region (Prince Edward Island, Canada) were estimated by using long-term (i.e., 2010–2019) daily soil water content (SWC). The amount of supplemental irrigation required for the minimal irrigation scenario (SWC = 70% of field capacity; 0.7 FC) was relatively small (i.e., 17.0 mm); however, this increased significantly, to 85.2 and 189.6 mm, for the moderate (SWC = 0.8 FC) and extensive (SWC = 0.9 FC) irrigation scenarios, respectively. The water supply requirement for the growing season (GS) increased to 154.9 and 344.7 mm for a moderately efficient irrigation system (55% efficiency) for the SWC = 0.8 FC and SWC = 0.9 FC irrigation scenarios, respectively. Depending on the efficiency and the areal extent of the irrigation system, the irrigation water supply requirement can approach or exceed both the GS and annual groundwater recharge. The methodology developed in this research has been translated into a free online tool (SWIB—Soil Water Stress, Irrigation Requirement and Water Balance), which can be applied to other areas or crops where an estimation of soil water deficit and irrigation requirement is sought. Full article
(This article belongs to the Special Issue Agricultural Water Saving: Advanced Technologies for Water Resources Efficient Utilization)
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22 pages, 2591 KiB  
Review
Artificial Intelligence-Based Regional Flood Frequency Analysis Methods: A Scoping Review
by Amir Zalnezhad, Ataur Rahman, Nastaran Nasiri, Khaled Haddad, Muhammad Muhitur Rahman, Mehdi Vafakhah, Bijan Samali and Farhad Ahamed
Water 2022, 14(17), 2677; https://doi.org/10.3390/w14172677 - 29 Aug 2022
Cited by 15 | Viewed by 4572
Abstract
Flood is one of the most destructive natural disasters, causing significant economic damage and loss of lives. Numerous methods have been introduced to estimate design floods, which include linear and non-linear techniques. Since flood generation is a non-linear process, the use of linear [...] Read more.
Flood is one of the most destructive natural disasters, causing significant economic damage and loss of lives. Numerous methods have been introduced to estimate design floods, which include linear and non-linear techniques. Since flood generation is a non-linear process, the use of linear techniques has inherent weaknesses. To overcome these, artificial intelligence (AI)-based non-linear regional flood frequency analysis (RFFA) techniques have been introduced over the last two decades. There are limited articles available in the literature discussing the relative merits/demerits of these AI-based RFFA techniques. To fill this knowledge gap, a scoping review on the AI-based RFFA techniques is presented. Based on the Scopus database, more than 1000 articles were initially selected, which were then screened manually to select the most relevant articles. The accuracy and efficiency of the selected RFFA techniques based on a set of evaluation statistics were compared. Furthermore, the relationships among countries and researchers focusing on AI-based RFFA techniques are illustrated. In terms of performance, artificial neural networks (ANN) are found to be the best performing techniques among all the selected AI-based RFFA techniques. It is also found that Australia, Canada, and Iran have published the highest number of articles in this research field, followed by Turkey, the United Arab Emirates (UAE), India, and China. Future research should be directed towards identification of the impacts of data quantity and quality, model uncertainty and climate change on the AI-based RFFA techniques. Full article
(This article belongs to the Special Issue Advances in Modeling and Risk Analysis of Floods under Changing Climate)
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23 pages, 3734 KiB  
Article
Conceptualising and Implementing an Agent-Based Model of an Irrigation System
by Dengxiao Lang and Maurits Willem Ertsen
Water 2022, 14(16), 2565; https://doi.org/10.3390/w14162565 - 20 Aug 2022
Cited by 8 | Viewed by 3665
Abstract
The literature on irrigated agriculture is primarily concerned with irrigation techniques, irrigation water-use efficiency, and crop yields. How human and non-human agents co-shape(d) irrigation landscapes through their activities and how these actions impact long-term developments are less well studied. In this study, we [...] Read more.
The literature on irrigated agriculture is primarily concerned with irrigation techniques, irrigation water-use efficiency, and crop yields. How human and non-human agents co-shape(d) irrigation landscapes through their activities and how these actions impact long-term developments are less well studied. In this study, we aim to (1) explore interactions between human and non-human agents in an irrigation system; (2) model the realistic operation of an irrigation system in an agent-based model environment, and; (3) study how short-term irrigation management actions create long-term irrigation system patterns. An agent-based model (ABM) was used to build our Irrigation-Related Agent-Based Model (IRABM). We implemented various scenarios, combining different irrigation control methods (time versus water demand), different river discharges, varied gate capacities, and several water allocation strategies. These scenarios result in different yields, which we analyse on the levels of individual farmer, canal, and system. Demand control gives better yields under conditions of sufficient water availability, whereas time control copes better with water deficiency. As expected, barley (Hordeum vulgare, Poaceae) yields generally increase when irrigation time and/or river discharge increase. The effect of gate capacity is visible with yields not changing linearly with changing gate capacities, but showing threshold behaviour. With the findings and analysis, we conclude that IRABM provides a new perspective on modelling the human-water system, as non-human model agents can create the dynamics that realistic irrigation systems show as well. Moreover, this type of modelling approach has a large potential to be theoretically and empirically used to explore the interactions between irrigation-related agents and understand how these interactions create water and yields patterns. Furthermore, the developed user-interface model allows non-technical stakeholders to participate and play a role in modelling work. Full article
(This article belongs to the Special Issue Water and Crops)
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17 pages, 967 KiB  
Article
Impact of log(Kow) Value on the Extraction of Antibiotics from River Sediments with Pressurized Liquid Extraction
by Amélie Chabilan, Nicolette Landwehr, Harald Horn and Ewa Borowska
Water 2022, 14(16), 2534; https://doi.org/10.3390/w14162534 - 18 Aug 2022
Cited by 15 | Viewed by 3503
Abstract
The quantification of antibiotics (ABs) in sediments is an analytical challenge, but at the same time, it is indispensable to understand the fate of ABs in aquatic systems such as rivers. The aim of this study was to develop a comprehensive method to [...] Read more.
The quantification of antibiotics (ABs) in sediments is an analytical challenge, but at the same time, it is indispensable to understand the fate of ABs in aquatic systems such as rivers. The aim of this study was to develop a comprehensive method to determine 19 ABs classified as macrolides, sulfonamides, fluoroquinolones, tetracyclines, clindamycin and trimethoprim in river sediments, using a combination of pressurized liquid extraction and solid phase extraction with the separation and detection with liquid chromatography coupled with mass spectrometry. Our results showed that the physical-chemical properties (e.g., log(Kow) value) of the analytes affected the extraction efficiency. Therefore, we propose to order ABs based on their log(Kow) values instead of traditional classification (macrolides, sulfonamides etc.) to select a suitable extraction solvent. ABs with log(Kow) values below zero (mainly fluoroquinolones and tetracyclines) were difficult to extract with all of the tested protocols compared to ABs with a log(Kow) larger than zero. After comparing different extraction protocols for ABs from solid and sediments, we concluded that recoveries in the range of 0.8 to 64.8% could be achieved for ABs with a log(Kow) value larger than zero using a mixture of acetonitrile and 50 mM phosphoric acid (50/50, v/v) in two extraction cycles at 100 °C. Full article
(This article belongs to the Section Water Quality and Contamination)
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24 pages, 4340 KiB  
Article
Climate Change over the Mediterranean Region: Local Temperature and Precipitation Variations at Five Pilot Sites
by Valeria Todaro, Marco D’Oria, Daniele Secci, Andrea Zanini and Maria Giovanna Tanda
Water 2022, 14(16), 2499; https://doi.org/10.3390/w14162499 - 13 Aug 2022
Cited by 69 | Viewed by 6588
Abstract
The Mediterranean region is one of the most responsive areas to climate change and was identified as a major “hot-spot” based on global climate change analyses. This study provides insight into local climate changes in the Mediterranean region under the scope of the [...] Read more.
The Mediterranean region is one of the most responsive areas to climate change and was identified as a major “hot-spot” based on global climate change analyses. This study provides insight into local climate changes in the Mediterranean region under the scope of the InTheMED project, which is part of the PRIMA programme. Precipitation and temperature were analyzed in an historical period and until the end of this century for five pilot sites, located between the two shores of the Mediterranean region. We used an ensemble of 17 Regional Climate Models, developed in the framework of the EURO-CORDEX initiative, under two Representative Concentration Pathways (RCP4.5 and RCP8.5). Over the historical period, the temperature presents upward trends, which are statistically significant for some sites, while precipitation does not show significant tendencies. These trends will be maintained in the future as predicted by the climate models projections: all models indicate a progressive and robust warming in all study areas and moderate change in total annual precipitation, but some seasonal variations are identified. Future changes in droughts events over the Mediterranean region were studied considering the maximum duration of the heat waves, their peak temperature, and the number of consecutive dry days. All pilot sites are expected to increase the maximum duration of heat waves and their peak temperature. Furthermore, the maximum number of consecutive dry days is expected to increase for most of the study areas. Full article
(This article belongs to the Special Issue Evolution of the Hydrological Regime in Relation to Climate Change)
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21 pages, 1701 KiB  
Review
MinION Nanopore Sequencing Accelerates Progress towards Ubiquitous Genetics in Water Research
by David Werner, Kishor Acharya, Adrian Blackburn, Rixia Zan, Jidapa Plaimart, Ben Allen, Shaaban Mrisho Mgana, Shadrack Mwita Sabai, Franella Francos Halla, Said Maneno Massawa, Alemseged Tamiru Haile, Andualem Mekonnen Hiruy, Jemila Mohammed, Soydoa Vinitnantharat, Thunchanok Thongsamer, Kalyan Pantha, Cesar Rossas Mota Filho and Bruna Coelho Lopes
Water 2022, 14(16), 2491; https://doi.org/10.3390/w14162491 - 12 Aug 2022
Cited by 15 | Viewed by 11470
Abstract
In 2014, Oxford Nanopore Technologies (ONT) introduced an affordable and portable sequencer called MinION. We reviewed emerging applications in water research and assessed progress made with this platform towards ubiquitous genetics. With >99% savings in upfront costs as compared to conventional platforms, the [...] Read more.
In 2014, Oxford Nanopore Technologies (ONT) introduced an affordable and portable sequencer called MinION. We reviewed emerging applications in water research and assessed progress made with this platform towards ubiquitous genetics. With >99% savings in upfront costs as compared to conventional platforms, the MinION put sequencing capacity into the hands of many researchers and enabled novel applications with diverse remits, including in countries without universal access to safe water and sanitation. However, to realize the MinION’s fabled portability, all the auxiliary equipment items for biomass concentration, genetic material extraction, cleanup, quantification, and sequencing library preparation also need to be lightweight and affordable. Only a few studies demonstrated fully portable workflows by using the MinION onboard a diving vessel, an oceanographic research ship, and at sewage treatment works. Lower nanopore sequencing read accuracy as compared to alternative platforms currently hinders MinION applications beyond research, and inclusion of positive and negative controls should become standard practice. ONT’s EPI2ME platform is a major step towards user-friendly bioinformatics. However, no consensus has yet emerged regarding the most appropriate bioinformatic pipeline, which hinders intercomparison of study results. Processing, storing, and interpreting large data sets remains a major challenge for ubiquitous genetics and democratizing sequencing applications. Full article
(This article belongs to the Special Issue Field Methods for Water Quality Surveying)
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19 pages, 10256 KiB  
Article
DRASTIC Index GIS-Based Vulnerability Map for the Entre-os-Rios Thermal Aquifer
by Vanessa Gonçalves, Antonio Albuquerque, Pedro G. Almeida and Victor Cavaleiro
Water 2022, 14(16), 2448; https://doi.org/10.3390/w14162448 - 9 Aug 2022
Cited by 13 | Viewed by 3774
Abstract
The sulphurous mineral waters of ‘Entre-os-Rios’, which is sited in NW Portugal, are famous for their long history as thermal baths dating back at least to the mid-sixteenth century. Because of the singularity of its water composition, especially the highest sulphur content, the [...] Read more.
The sulphurous mineral waters of ‘Entre-os-Rios’, which is sited in NW Portugal, are famous for their long history as thermal baths dating back at least to the mid-sixteenth century. Because of the singularity of its water composition, especially the highest sulphur content, the mineral waters of ‘Entre-os-Rios’ are one of the most important sulphurous waters in Portugal. Despite these mineral waters having a protection perimeter buffer zone to avoid water contamination, there are potentially damaging installations (e.g., fuel station) in the closed protection buffer zone that, according to existing law, are not permitted within the protection perimeters, which defeats the purpose of their delineation. A vulnerability map was created using geographic information system (GIS) tools based on multi-criteria analysis, combining thematic maps and parameters of the DRASTIC index, for evaluating the risk of contamination in the protection area. The results showed that within the perimeter, there was a low risk of pollution. The alluvium-covered terrain was vulnerable to moderate contamination, but it was far from the catchment point. Areas of minimal risk corresponded to locations where the granitic massif had not been significantly weathered. The map enables information collection for a better definition of local resource structures and planning, namely, for restricted areas emplacement where some activities should not be allowed (e.g., agriculture and water prospection), given its influence on the confined granitic aquifer. Full article
(This article belongs to the Special Issue Groundwater Protection: Contaminant Transport Processes and Remediation Approaches)
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24 pages, 1958 KiB  
Review
Research Progress on Integrated Treatment Technologies of Rural Domestic Sewage: A Review
by Peizhen Chen, Wenjie Zhao, Dongkai Chen, Zhiping Huang, Chunxue Zhang and Xiangqun Zheng
Water 2022, 14(15), 2439; https://doi.org/10.3390/w14152439 - 6 Aug 2022
Cited by 56 | Viewed by 12528
Abstract
The improvement of rural living standards in developing countries and the continuous upgrading of the rural industrial economy have prompted the diversification of rural areas and residential forms. Thus, an integrated rural sewage treatment process has gradually become the mainstream technology for rural [...] Read more.
The improvement of rural living standards in developing countries and the continuous upgrading of the rural industrial economy have prompted the diversification of rural areas and residential forms. Thus, an integrated rural sewage treatment process has gradually become the mainstream technology for rural sewage treatment. Numerous studies have reported the effects of ecological wastewater treatment. Meanwhile, the relevant process technologies, evaluations, and operating models of the integrated rural sewage treatment process have yet to be thoroughly summarized. This review aims to fill these gaps. First, the applicability of artificial wetland, soil infiltration, stabilization pond, and integrated rural sewage treatment process technology in rural sewage treatment are outlined and compared. Second, the process flow, technical characteristics, and economic indicators of typical integrated sewage treatment processes (i.e., Anoxic/Oxic (A/O) process, Membrane Bio-Reactor (MBR) process, biological contact oxidation process, Sequencing Batch Reactor Activated Sludge (SBR) process) are introduced. The engineering application effects of the integrated rural sewage treatment process in different countries are also described. Third, the practical and effective evaluation methods of the integrated rural sewage treatment process are introduced. Bearing in mind the current operation and maintenance management modes of the integrated rural sewage treatment process in developed and developing countries, combined with the national conditions of developing countries, the prospect section provides development proposals for further optimization and improvement of the integrated rural sewage treatment process in developing countries. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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14 pages, 4288 KiB  
Article
Elimination of Microplastics at Different Stages in Wastewater Treatment Plants
by Hyuk Jun Kwon, Haerul Hidayaturrahman, Shaik Gouse Peera and Tae Gwan Lee
Water 2022, 14(15), 2404; https://doi.org/10.3390/w14152404 - 3 Aug 2022
Cited by 74 | Viewed by 11340
Abstract
Microplastic pollution has been widely studied as a global issue due to increased plastic usage and its effect on human and aquatic life. Microplastics originate from domestic and industrial activities. Wastewater treatment plants (WWTPs) play an important role in removing a significant amount [...] Read more.
Microplastic pollution has been widely studied as a global issue due to increased plastic usage and its effect on human and aquatic life. Microplastics originate from domestic and industrial activities. Wastewater treatment plants (WWTPs) play an important role in removing a significant amount of microplastics; otherwise, they end up in bioaccumulation. This study provides knowledge about the characteristics of microplastics, removal efficiency, and the correlation between wastewater quality and microplastic concentrations from three different WWTPs that differ in the type of biological and advanced wastewater treatment techniques that are believed to play an important role in microplastic removal. Microplastics of different types, such as fragments, fibers, and beads, are identified by using an optical microscope before and after the treatment process at each stage to assess the effect of different treatment techniques. In the screening unit and primary clarifier unit, WWTP-B shows the highest removal efficiency with 74.76% due to a distribution flow system installed before the primary clarifier to ensure a constant flow of wastewater. WWTP-B uses a bioreactor consisting of a filter plate coated with activated carbon (BSTS II) that can enhance the adaptability and adhesion of microorganisms and showed that 91.04% of the microplastic was removed. Furthermore, only WWTP-A and WWTP-B were applied coagulation, followed by the disc filter; they showed significant results in microplastic removal, compared to WWTP-C, which only used a disc filter. In conclusion, from all WWTP, WWTP-B shows good treatment series for removing microplastic in wastewater; however, WWTP-B showed a high rate of microplastic removal; unfortunately, large amounts of microplastics are still released into rivers. Full article
(This article belongs to the Special Issue Microplastics Pollution and Solutions)
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12 pages, 2136 KiB  
Article
CME-YOLOv5: An Efficient Object Detection Network for Densely Spaced Fish and Small Targets
by Jianyuan Li, Chunna Liu, Xiaochun Lu and Bilang Wu
Water 2022, 14(15), 2412; https://doi.org/10.3390/w14152412 - 3 Aug 2022
Cited by 53 | Viewed by 6937
Abstract
Fish are indicative species with a relatively balanced ecosystem. Underwater target fish detection is of great significance to fishery resource investigations. Traditional investigation methods cannot meet the increasing requirements of environmental protection and investigation, and the existing target detection technology has few studies [...] Read more.
Fish are indicative species with a relatively balanced ecosystem. Underwater target fish detection is of great significance to fishery resource investigations. Traditional investigation methods cannot meet the increasing requirements of environmental protection and investigation, and the existing target detection technology has few studies on the dynamic identification of underwater fish and small targets. To reduce environmental disturbances and solve the problems of many fish, dense, mutual occlusion and difficult detection of small targets, an improved CME-YOLOv5 network is proposed to detect fish in dense groups and small targets. First, the coordinate attention (CA) mechanism and cross-stage partial networks with 3 convolutions (C3) structure are fused into the C3CA module to replace the C3 module of the backbone in you only look once (YOLOv5) to improve the extraction of target feature information and detection accuracy. Second, the three detection layers are expanded to four, which enhances the model’s ability to capture information in different dimensions and improves detection performance. Finally, the efficient intersection over union (EIOU) loss function is used instead of the generalized intersection over union (GIOU) loss function to optimize the convergence rate and location accuracy. Based on the actual image data and a small number of datasets obtained online, the experimental results showed that the mean average precision (mAP@0.50) of the proposed algorithm reached 94.9%, which is 4.4 percentage points higher than that of the YOLOv5 algorithm, and the number of fish and small target detection performances was 24.6% higher. The results show that our proposed algorithm exhibits good detection performance when applied to densely spaced fish and small targets and can be used as an alternative or supplemental method for fishery resource investigation. Full article
(This article belongs to the Special Issue Emerging Solutions for Active Water Governance: Intellectual Decision and Smart Control)
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15 pages, 855 KiB  
Review
Resource Utilization of Acid Mine Drainage (AMD): A Review
by Jiaqiao Yuan, Zhan Ding, Yunxiao Bi, Jie Li, Shuming Wen and Shaojun Bai
Water 2022, 14(15), 2385; https://doi.org/10.3390/w14152385 - 1 Aug 2022
Cited by 48 | Viewed by 15085
Abstract
Acid mine drainage (AMD) is a typical type of pollution originating from complex oxidation interactions that occur under ambient conditions in abandoned and active mines. AMD has high acidity and contains a high concentration of heavy metals and metalloids, posing a serious threat [...] Read more.
Acid mine drainage (AMD) is a typical type of pollution originating from complex oxidation interactions that occur under ambient conditions in abandoned and active mines. AMD has high acidity and contains a high concentration of heavy metals and metalloids, posing a serious threat to ecological systems and human health. Over the years, great progress has been made in the prevention and treatment of AMD. Remediation approaches like chemical neutralization precipitation, ion exchange, membrane separation processes, and bioremediation have been extensively reported. Nevertheless, some limitations, such as low efficacy, excessive consumption of chemical reagents, and secondary contamination restrict the application of these technologies. The aim of this review was to provide updated information on the sustainable treatments that have been engaged in the published literature on the resource utilization of AMD. The recovery and reuse of valuable resources (e.g., clean water, sulfuric acid, and metal ions) from AMD can offset the cost of AMD remediation. Iron oxide particles recovered from AMD can be applied as adsorbents for the removal of pollutants from wastewater and for the fabrication of effective catalysts for heterogeneous Fenton reactions. The application of AMD in beneficiation fields, such as activating pyrite and chalcopyrite flotation, regulating pulp pH, and leaching copper-bearing waste rock, provides easy access to the innovative utilization of AMD. A review such as this will help researchers understand the progress in research, and identify the strengths and weaknesses of each treatment technology, which can help shape the direction of future research in this area. Full article
(This article belongs to the Special Issue Mining Wastewater Treatment and Reuse)
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21 pages, 2877 KiB  
Article
Data-Driven Community Flood Resilience Prediction
by Moustafa Naiem Abdel-Mooty, Wael El-Dakhakhni and Paulin Coulibaly
Water 2022, 14(13), 2120; https://doi.org/10.3390/w14132120 - 2 Jul 2022
Cited by 13 | Viewed by 5107
Abstract
Climate change and the development of urban centers within flood-prone areas have significantly increased flood-related disasters worldwide. However, most flood risk categorization and prediction efforts have been focused on the hydrologic features of flood hazards, often not considering subsequent long-term losses and recovery [...] Read more.
Climate change and the development of urban centers within flood-prone areas have significantly increased flood-related disasters worldwide. However, most flood risk categorization and prediction efforts have been focused on the hydrologic features of flood hazards, often not considering subsequent long-term losses and recovery trajectories (i.e., community’s flood resilience). In this study, a two-stage Machine Learning (ML)-based framework is developed to accurately categorize and predict communities’ flood resilience and their response to future flood hazards. This framework is a step towards developing comprehensive, proactive flood disaster management planning to further ensure functioning urban centers and mitigate the risk of future catastrophic flood events. In this framework, resilience indices are synthesized considering resilience goals (i.e., robustness and rapidity) using unsupervised ML, coupled with climate information, to develop a supervised ML prediction algorithm. To showcase the utility of the framework, it was applied on historical flood disaster records collected by the US National Weather Services. These disaster records were subsequently used to develop the resilience indices, which were then coupled with the associated historical climate data, resulting in high-accuracy predictions and, thus, utility in flood resilience management studies. To further demonstrate the utilization of the framework, a spatial analysis was developed to quantify communities’ flood resilience and vulnerability across the selected spatial domain. The framework presented in this study is employable in climate studies and patio-temporal vulnerability identification. Such a framework can also empower decision makers to develop effective data-driven climate resilience strategies. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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15 pages, 1464 KiB  
Article
Artificial Neural Networks for the Prediction of the Reference Evapotranspiration of the Peloponnese Peninsula, Greece
by Stavroula Dimitriadou and Konstantinos G. Nikolakopoulos
Water 2022, 14(13), 2027; https://doi.org/10.3390/w14132027 - 24 Jun 2022
Cited by 35 | Viewed by 4037
Abstract
The aim of the study was to investigate the utility of artificial neural networks (ANNs) for the estimation of reference evapotranspiration (ETo) on the Peloponnese Peninsula in Greece for two representative months of wintertime and summertime during 2016–2019 and to test if using [...] Read more.
The aim of the study was to investigate the utility of artificial neural networks (ANNs) for the estimation of reference evapotranspiration (ETo) on the Peloponnese Peninsula in Greece for two representative months of wintertime and summertime during 2016–2019 and to test if using fewer inputs could lead to satisfactory predictions. Datasets from sixty-two meteorological stations were employed. The available inputs were mean temperature (Tmean), sunshine (N), solar radiation (Rs), net radiation (Rn), vapour pressure deficit (es-ea), wind speed (u2) and altitude (Z). Nineteen Multi-layer Perceptron (MLP) and Radial Basis Function (RBF) models were tested and compared against the corresponding FAO-56 Penman Monteith (FAO PM) estimates of a previous study, via statistical indices. The MLP1 7-2 model with all the variables as inputs outperformed the rest of the models (RMSE = 0.290 mm d−1, R2 = 98%). The results indicate that even ANNs with simple architecture can be very good predictive models of ETo for the Peloponnese, based on the literature standards. The MLP1 model determined Tmean, followed by u2, as the two most influential factors for ETo. Moreover, when one input was used (Tmean, Rn), RBFs slightly outperformed MLPs (RMSE < 0.385 mm d−1, R2 ≥ 96%), which means that even a sole-input ANN resulted in satisfactory predictions of ETo. Full article
(This article belongs to the Special Issue Remote Sensing Application on Soil Moisture)
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18 pages, 3739 KiB  
Article
Water Level Forecasting Using Deep Learning Time-Series Analysis: A Case Study of Red River of the North
by Vida Atashi, Hamed Taheri Gorji, Seyed Mojtaba Shahabi, Ramtin Kardan and Yeo Howe Lim
Water 2022, 14(12), 1971; https://doi.org/10.3390/w14121971 - 20 Jun 2022
Cited by 48 | Viewed by 9980
Abstract
The Red River of the North is vulnerable to floods, which have caused significant damage and economic loss to inhabitants. A better capability in flood-event prediction is essential to decision-makers for planning flood-loss-reduction strategies. Over the last decades, classical statistical methods and Machine [...] Read more.
The Red River of the North is vulnerable to floods, which have caused significant damage and economic loss to inhabitants. A better capability in flood-event prediction is essential to decision-makers for planning flood-loss-reduction strategies. Over the last decades, classical statistical methods and Machine Learning (ML) algorithms have greatly contributed to the growth of data-driven forecasting systems that provide cost-effective solutions and improved performance in simulating the complex physical processes of floods using mathematical expressions. To make improvements to flood prediction for the Red River of the North, this paper presents effective approaches that make use of a classical statistical method, a classical ML algorithm, and a state-of-the-art Deep Learning method. Respectively, the methods are seasonal autoregressive integrated moving average (SARIMA), Random Forest (RF), and Long Short-Term Memory (LSTM). We used hourly level records from three U.S. Geological Survey (USGS), at Pembina, Drayton, and Grand Forks stations with twelve years of data (2007–2019), to evaluate the water level at six hours, twelve hours, one day, three days, and one week in advance. Pembina, at the downstream location, has a water level gauge but not a flow-gauging station, unlike the others. The floodwater-level-prediction results show that the LSTM method outperforms the SARIMA and RF methods. For the one-week-ahead prediction, the RMSE values for Pembina, Drayton, and Grand Forks are 0.190, 0.151, and 0.107, respectively. These results demonstrate the high precision of the Deep Learning algorithm as a reliable choice for flood-water-level prediction. Full article
(This article belongs to the Special Issue Advances in Flood Forecasting and Hydrological Modeling)
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23 pages, 6099 KiB  
Article
Three-Dimensional Hole Size (3DHS) Approach for Water Flow Turbulence Analysis over Emerging Sand Bars: Flume-Scale Experiments
by Mohammad Amir Khan, Nayan Sharma, Giuseppe Francesco Cesare Lama, Murtaza Hasan, Rishav Garg, Gianluigi Busico and Raied Saad Alharbi
Water 2022, 14(12), 1889; https://doi.org/10.3390/w14121889 - 12 Jun 2022
Cited by 26 | Viewed by 3872
Abstract
The many hydrodynamic implications associated with the geomorphological evolution of braided rivers are still not profoundly examined in both experimental and numerical analyses, due to the generation of three-dimensional turbulence structures around sediment bars. In this experimental research, the 3D velocity fields were [...] Read more.
The many hydrodynamic implications associated with the geomorphological evolution of braided rivers are still not profoundly examined in both experimental and numerical analyses, due to the generation of three-dimensional turbulence structures around sediment bars. In this experimental research, the 3D velocity fields were measured through an acoustic Doppler velocimeter during flume-scale laboratory experimental runs over an emerging sand bar model, to reproduce the hydrodynamic conditions of real braided rivers, and the 3D Turbulent Kinetic Energy (TKE) components were analyzed and discussed here in detail. Given the three-dimensionality of the examined water flow in the proximity of the experimental bar, the statistical analysis of the octagonal bursting events was applied to analyze and discuss the different flume-scale 3D turbulence structures. The main novelty of this study is the proposal of the 3D Hole Size (3DHS) analysis, used for separating the extreme events observed in the experimental runs from the low-intensity events. Full article
(This article belongs to the Special Issue Experimental Analysis and Numerical Modeling in Ecohydrolgy and Ecohydraulics: From Groundwater to River Hydraulics)
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20 pages, 1440 KiB  
Article
Impact of Participation in Groundwater Market on Farmland, Income, and Water Access: Evidence from Pakistan
by Amar Razzaq, Meizhen Xiao, Yewang Zhou, Hancheng Liu, Azhar Abbas, Wanqi Liang and Muhammad Asad ur Rehman Naseer
Water 2022, 14(12), 1832; https://doi.org/10.3390/w14121832 - 7 Jun 2022
Cited by 28 | Viewed by 5957
Abstract
Groundwater irrigation has a critical role in the sustainability of arable farming in many developing countries including Pakistan. Groundwater irrigation is generally practiced to supplement surface water supplies in Pakistan. Nevertheless, uninterrupted and extensive use of groundwater irrigation has raised several concerns about [...] Read more.
Groundwater irrigation has a critical role in the sustainability of arable farming in many developing countries including Pakistan. Groundwater irrigation is generally practiced to supplement surface water supplies in Pakistan. Nevertheless, uninterrupted and extensive use of groundwater irrigation has raised several concerns about its sustainability and resultant environmental implications. Due to the scarcity of groundwater and heterogeneity in farmers’ resources, informal groundwater markets have emerged in Pakistan, where farmers trade water using a contractual system. Yet, the effects of these markets on agricultural productivity and equity remain largely unknown. This paper aims to analyze the impact of participation in the groundwater market on farmland utilization, cropping patterns, water access, and income. We analyze these impacts using primary data collected from 360 farmers in three different zones of the country’s largest province. The farmers were categorized as buyers, sellers, and self-users of water. Results indicate that participation in water markets increased agricultural land utilization, evinced by a higher cropping intensity among participants. A horizontal and vertical equity analysis of water markets shows that although large farmers have better access to groundwater irrigation, water market participation improves equity to water access. Based on income inequality measures such as the Gini coefficient and the Lorenz curve, water market participation also improves farmer incomes regardless of farm size. Propensity score matching revealed that wheat yield and income among water-market participants went up by approximately 150 kg and PKR 4503 per acre compared with non-participants. Groundwater market participants’ higher crop productivity and income level suggest that water markets need a thorough revisit in terms of policy focus and institutional support to ensure sustainable rural development. Full article
(This article belongs to the Special Issue Integrated Water Resources Management (IWRM), a Holistic Approach to Sustainable Water Management)
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26 pages, 2857 KiB  
Review
Recent and Emerging Trends in Remediation of Methylene Blue Dye from Wastewater by Using Zinc Oxide Nanoparticles
by Shreya Modi, Virendra Kumar Yadav, Amel Gacem, Ismat H. Ali, Dhruv Dave, Samreen Heena Khan, Krishna Kumar Yadav, Sami-ullah Rather, Yongtae Ahn, Cao Truong Son and Byong-Hun Jeon
Water 2022, 14(11), 1749; https://doi.org/10.3390/w14111749 - 29 May 2022
Cited by 71 | Viewed by 8513
Abstract
Due to the increased demand for clothes by the growing population, the dye-based sectors have seen fast growth in the recent decade. Among all the dyes, methylene blue dye is the most commonly used in textiles, resulting in dye effluent contamination. It is [...] Read more.
Due to the increased demand for clothes by the growing population, the dye-based sectors have seen fast growth in the recent decade. Among all the dyes, methylene blue dye is the most commonly used in textiles, resulting in dye effluent contamination. It is carcinogenic, which raises the stakes for the environment. The numerous sources of methylene blue dye and their effective treatment procedures are addressed in the current review. Even among nanoparticles, photocatalytic materials, such as TiO2, ZnO, and Fe3O4, have shown greater potential for photocatalytic methylene blue degradation. Such nano-sized metal oxides are the most ideal materials for the removal of water pollutants, as these materials are related to the qualities of flexibility, simplicity, efficiency, versatility, and high surface reactivity. The use of nanoparticles generated from waste materials to remediate methylene blue is highlighted in the present review. Full article
(This article belongs to the Special Issue Application of Nanomaterials in Water Treatment)
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16 pages, 7088 KiB  
Review
Efficient Use of Water in Tailings Management: New Technologies and Environmental Strategies for the Future of Mining
by Carlos Cacciuttolo and Fernando Valenzuela
Water 2022, 14(11), 1741; https://doi.org/10.3390/w14111741 - 28 May 2022
Cited by 31 | Viewed by 12788
Abstract
Nowadays, many major copper mining projects in desert areas with extremely dry climates, as in northern Chile and the southern coast of Peru, process sulfide ores at high production rates; in some cases over 100,000 metric tonnes per day (mtpd), generating large amounts [...] Read more.
Nowadays, many major copper mining projects in desert areas with extremely dry climates, as in northern Chile and the southern coast of Peru, process sulfide ores at high production rates; in some cases over 100,000 metric tonnes per day (mtpd), generating large amounts of tailings, that are commonly managed and transported to tailings storage facilities (TSF) hydraulically using fresh water. Considering the extremely dry climate, water scarcity, community demands, and environmental constraints in these desert areas, the efficient use of water in mining is being strongly enforced. For this reason, water supply is recognized as one of the limiting factors for the development of new mining projects and for the expansion of the existing ones in these areas. New water supply alternatives, such as sea water desalinization, direct use of sea water, or water recovery from tailings, represent the strategy developed by the mining industry to deal with this growing scarcity. The focus of this paper is the possibility of applying different water supply technologies or a combination of these, implementing improved water management strategies that consider: environmental issues, technical issues, stringent regulatory frameworks, community requests and cost-effective strategies, that result in a reduction of freshwater make-up water requirements for mining (m3 per metric tonnes of treated ore). Full article
(This article belongs to the Special Issue Integrated Water Resources Management (IWRM), a Holistic Approach to Sustainable Water Management)
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36 pages, 9545 KiB  
Review
Research Progress on Adsorption of Arsenic from Water by Modified Biochar and Its Mechanism: A Review
by Yongchang Sun, Fangxin Yu, Caohui Han, Chouarfa Houda, Mingge Hao and Qiongyao Wang
Water 2022, 14(11), 1691; https://doi.org/10.3390/w14111691 - 25 May 2022
Cited by 38 | Viewed by 7022
Abstract
Arsenic (As) is a non-metallic element, which is widely distributed in nature. Due to its toxicity, arsenic is seriously harmful to human health and the environment. Therefore, it is particularly important to effectively remove arsenic from water. Biochar is a carbon-rich adsorption material [...] Read more.
Arsenic (As) is a non-metallic element, which is widely distributed in nature. Due to its toxicity, arsenic is seriously harmful to human health and the environment. Therefore, it is particularly important to effectively remove arsenic from water. Biochar is a carbon-rich adsorption material with advantages such as large specific surface area, high porosity, and abundant functional groups, but the original biochar has limitations in application, such as limited adsorption capacity and adsorption range. The modified biochar materials have largely enhanced the adsorption capacity of As in water due to their improved physicochemical properties. In this review, the changes in the physicochemical properties of biochar before and after modification were compared by SEM, XRD, XPS, FT-IR, TG, and other characterization techniques. Through the analysis, it was found that the adsorbent dosage and pH are the major factors that influence the As adsorption capacity of the modified biochar. The adsorption process of As by biochar is endothermic, and increasing the reaction temperature is conducive to the progress of adsorption. Results showed that the main mechanisms include complexation, electrostatic interaction, and precipitation for the As removal by the modified biochar. Research in the field of biochar is progressing rapidly, with numerous achievements and new types of biochar-based materials prepared with super-strong adsorption capacity for As. There is still much space for in-depth research in this field. Therefore, the future research interests and applications are put forward in this review. Full article
(This article belongs to the Special Issue Application of Biochar, Adsorbent and Nanomaterials in Wastewater Treatment)
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19 pages, 846 KiB  
Review
A Review of the Techno-Economic Feasibility of Nanoparticle Application for Wastewater Treatment
by Ncumisa Mpongwana and Sudesh Rathilal
Water 2022, 14(10), 1550; https://doi.org/10.3390/w14101550 - 12 May 2022
Cited by 52 | Viewed by 6985
Abstract
The increase in heavy metal contamination has led to an increase in studies investigating alternative sustainable ways to treat heavy metals. Nanotechnology has been shown to be an environmentally friendly technology for treating heavy metals and other contaminants from contaminated water. However, this [...] Read more.
The increase in heavy metal contamination has led to an increase in studies investigating alternative sustainable ways to treat heavy metals. Nanotechnology has been shown to be an environmentally friendly technology for treating heavy metals and other contaminants from contaminated water. However, this technology is not widely used in wastewater treatment plants (WWTPs) due to high operational costs. The increasing interest in reducing costs by applying nanotechnology in wastewater treatment has resulted in an increase in studies investigating sustainable ways of producing nanoparticles. Certain researchers have suggested that sustainable and cheap raw materials must be used for the production of cheaper nanoparticles. This has led to an increase in studies investigating the production of nanoparticles from plant materials. Additionally, production of nanoparticles through biological methods has also been recognized as a promising, cost-effective method of producing nanoparticles. Some studies have shown that the recycling of nanoparticles can potentially reduce the costs of using freshly produced nanoparticles. This review evaluates the economic impact of these new developments on nanotechnology in wastewater treatment. An in-depth market assessment of nanoparticle application and the economic feasibility of nanoparticle applications in WWTPs is presented. Moreover, the challenges and opportunities of using nanoparticles for heavy metal removal are also discussed. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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23 pages, 5868 KiB  
Review
Sponge City Practices in China: From Pilot Exploration to Systemic Demonstration
by Dingkun Yin, Changqing Xu, Haifeng Jia, Ye Yang, Chen Sun, Qi Wang and Sitong Liu
Water 2022, 14(10), 1531; https://doi.org/10.3390/w14101531 - 10 May 2022
Cited by 50 | Viewed by 17843
Abstract
In recent years, China has been committed to strengthening environmental governance and trying to build a sustainable society in which humans and nature develop in harmony. As a new urban construction concept, sponge city uses natural and ecological methods to retain rainwater, alleviate [...] Read more.
In recent years, China has been committed to strengthening environmental governance and trying to build a sustainable society in which humans and nature develop in harmony. As a new urban construction concept, sponge city uses natural and ecological methods to retain rainwater, alleviate flooding problems, reduce the damage to the water environment, and gradually restore the hydrological balance of the construction area. The paper presents a review of sponge city construction from its inception to systematic demonstration. In this paper, research gaps are discussed and future efforts are proposed. The main contents include: (1) China’s sponge city construction includes but is not limited to source control or a drainage system design. Sponge city embodies foreign experience and the wisdom of ancient Chinese philosophy. The core of sponge city construction is to combine various specific technologies to alleviate urban water problems such as flooding, water environment pollution, shortage of water resources and deterioration of water ecology; (2) this paper also introduces the sponge city pilot projects in China, and summarizes the achievements obtained and lessons learned, which are valuable for future sponge city implementation; (3) the objectives, corresponding indicators, key contents and needs of sponge city construction at various scales are different. The work at the facility level is dedicated to alleviating urban water problems through reasonable facility scale and layout, while the work at the plot level is mainly to improve the living environment through sponge city construction. The construction of urban and watershed scales is more inclined to ecological restoration and blue-green storage spaces construction. Besides, the paper also describes the due obligations in sponge city construction of various stakeholders. Full article
(This article belongs to the Special Issue Urban Runoff Control and Sponge City Construction)
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25 pages, 1985 KiB  
Review
Watershed Ecohydrological Processes in a Changing Environment: Opportunities and Challenges
by Zhe Cao, Shuangtao Wang, Pingping Luo, Danni Xie and Wei Zhu
Water 2022, 14(9), 1502; https://doi.org/10.3390/w14091502 - 7 May 2022
Cited by 63 | Viewed by 12395
Abstract
Basin ecohydrological processes are essential for informing policymaking and social development in response to growing environmental problems. In this paper, we review watershed ecohydrology, focusing on the interaction between watershed ecological and hydrological processes. Climate change and human activities are the most important [...] Read more.
Basin ecohydrological processes are essential for informing policymaking and social development in response to growing environmental problems. In this paper, we review watershed ecohydrology, focusing on the interaction between watershed ecological and hydrological processes. Climate change and human activities are the most important factors influencing water quantity and quality, and there is a need to integrate watershed socioeconomic activities into the paradigm of watershed ecohydrological process studies. Then, we propose a new framework for integrated watershed management. It includes (1) data collection: building an integrated observation network; (2) theoretical basis: attribution analysis; (3) integrated modeling: medium- and long-term prediction of ecohydrological processes by human–nature interactions; and (4) policy orientation. The paper was a potential solution to overcome challenges in the context of frequent climate extremes and rapid land-use change. Full article
(This article belongs to the Special Issue Research Progress on Watershed Ecohydrological Processes)
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23 pages, 3788 KiB  
Article
Nitrogen Modulates the Effects of Short-Term Heat, Drought and Combined Stresses after Anthesis on Photosynthesis, Nitrogen Metabolism, Yield, and Water and Nitrogen Use Efficiency of Wheat
by Chen Ru, Xiaotao Hu, Dianyu Chen, Tianyuan Song, Wene Wang, Mengwei Lv and Neil C. Hansen
Water 2022, 14(9), 1407; https://doi.org/10.3390/w14091407 - 28 Apr 2022
Cited by 33 | Viewed by 4347
Abstract
More frequent and more intense heat waves and greater drought stress will occur in the future climate environment. Short-term extreme heat and drought stress often occur simultaneously after winter wheat anthesis, which has become the major constraint threatening future wheat yield. In this [...] Read more.
More frequent and more intense heat waves and greater drought stress will occur in the future climate environment. Short-term extreme heat and drought stress often occur simultaneously after winter wheat anthesis, which has become the major constraint threatening future wheat yield. In this study, short-term heat, drought and their combination stress were applied to wheat plants after anthesis, and all wheat plants were restored to the outdoor normal temperature and full watering after stress treatment. The aim of the current study was to evaluate the role of nitrogen (N) in modulating the effects of post-anthesis short-term heat, drought and their combination stress on photosynthesis, N metabolism-related enzymes, the accumulation of N and protein and growth, as well as on the yield and water (WUE) and N use efficiency (NUE) of wheat after stress treatment. The results showed that compared with low N application (N1), medium application (N2) enhanced the activities of nitrate reductase (NR) and glutamine synthase (GS) in grains under post-anthesis heat and drought stress alone, which provided a basis for the accumulation of N and protein in grains at the later stage of growth. Under post-anthesis individual stresses, N2 or high application (N3) increased the leaf photosynthetic rate (An), PSII photochemical efficiency and instantaneous WUE compared with N1, whereas these parameters were usually significantly improved by N1 application under post-anthesis combined stress. The positive effect of increased An by N application on growth was well represented in a higher green leaf area, aboveground dry mass and plant height, and the variation in An can be explained more accurately by the N content per unit leaf area. Short-term heat, drought and combined stress after anthesis resulted in a pronounced decrease in yield by reducing grain number per spike and thousand kernel weight. The reduction in NUE under combined stress was higher than that under individual heat and drought stress. Compared with N1, N2 or N3 application significantly prevented the decrease in yield and NUE caused by post-anthesis heat and drought stress alone. However, N1 application was conducive to improving the productivity, WUE and NUE of wheat when exposed to post-anthesis combined stress. The current data indicated that under short-term individual heat and drought stress after anthesis, appropriately increasing N application effectively improved the growth and physiological activity of wheat compared with N1, alleviating the reduction in yield, WUE and NUE. However, under combined stress conditions, reducing N application (N1) may be a suitable strategy to compensate for the decrease in yield, WUE and NUE. Full article
(This article belongs to the Section Water, Agriculture and Aquaculture)
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28 pages, 750 KiB  
Review
A Review on Machine Learning, Artificial Intelligence, and Smart Technology in Water Treatment and Monitoring
by Matthew Lowe, Ruwen Qin and Xinwei Mao
Water 2022, 14(9), 1384; https://doi.org/10.3390/w14091384 - 24 Apr 2022
Cited by 216 | Viewed by 27399
Abstract
Artificial-intelligence methods and machine-learning models have demonstrated their ability to optimize, model, and automate critical water- and wastewater-treatment applications, natural-systems monitoring and management, and water-based agriculture such as hydroponics and aquaponics. In addition to providing computer-assisted aid to complex issues surrounding water chemistry [...] Read more.
Artificial-intelligence methods and machine-learning models have demonstrated their ability to optimize, model, and automate critical water- and wastewater-treatment applications, natural-systems monitoring and management, and water-based agriculture such as hydroponics and aquaponics. In addition to providing computer-assisted aid to complex issues surrounding water chemistry and physical/biological processes, artificial intelligence and machine-learning (AI/ML) applications are anticipated to further optimize water-based applications and decrease capital expenses. This review offers a cross-section of peer reviewed, critical water-based applications that have been coupled with AI or ML, including chlorination, adsorption, membrane filtration, water-quality-index monitoring, water-quality-parameter modeling, river-level monitoring, and aquaponics/hydroponics automation/monitoring. Although success in control, optimization, and modeling has been achieved with the AI methods, ML models, and smart technologies (including the Internet of Things (IoT), sensors, and systems based on these technologies) that are reviewed herein, key challenges and limitations were common and pervasive throughout. Poor data management, low explainability, poor model reproducibility and standardization, as well as a lack of academic transparency are all important hurdles to overcome in order to successfully implement these intelligent applications. Recommendations to aid explainability, data management, reproducibility, and model causality are offered in order to overcome these hurdles and continue the successful implementation of these powerful tools. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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19 pages, 2546 KiB  
Article
Determination of Potential Aquifer Recharge Zones Using Geospatial Techniques for Proxy Data of Gilgel Gibe Catchment, Ethiopia
by Tarekegn Dejen Mengistu, Sun Woo Chang, Il-Hwan Kim, Min-Gyu Kim and Il-Moon Chung
Water 2022, 14(9), 1362; https://doi.org/10.3390/w14091362 - 22 Apr 2022
Cited by 36 | Viewed by 4877
Abstract
The lack of valuable baseline information about groundwater availability hinders the robust decision-making process of water management in humid, arid, and semi-arid climate regions of the world. In sustainable groundwater management, identifying the spatiotemporal and extrapolative monitoring of potential zone is crucial. Thus, [...] Read more.
The lack of valuable baseline information about groundwater availability hinders the robust decision-making process of water management in humid, arid, and semi-arid climate regions of the world. In sustainable groundwater management, identifying the spatiotemporal and extrapolative monitoring of potential zone is crucial. Thus, the present study focused on determining potential aquifer recharge zones using geospatial techniques for proxy data of the Gilgel Gibe catchment, Ethiopia. Proxy data are site information derived from satellite imageries or conventional sources that are operated as a layer attribute in the geographical information system (GIS) to identify groundwater occurrence. First, GIS and analytical hierarchy process (AHP) were applied to analyze ten groundwater recharge controlling factors: slope, lithology, topographic position index lineament density, rainfall, soil, elevation, land use/cover, topographic wetness index, and drainage density. Each layer was given relative rank priority depending on the predictive implication of groundwater potentiality. Next, the normalized weight of thematic layers was evaluated using a multi-criteria decision analysis AHP algorithm with a pairwise comparison matrix based on aquifer infiltration relative significance. Lithology, rainfall, and land use/cover were dominant factors covering a weight of 50%. The computed consistency ratio (CR = 0.092, less than 10%) and consistency index (CI = 0.1371) revealed the reliability of input proxy layers’ in the analysis. Then, a GIS-based weighted overlay analysis was performed to delineate very high, high, moderate, low, and very low potential aquifer zones. The delineated map ensures very high (29%), high (25%), moderate (28%), low (13%), and very low (5%) of the total area. According to validation, most of the inventory wells are located in very high (57%), high (32), and moderate (12%) zones. The validation results realized that the method affords substantial results supportive of sustainable development and groundwater exploitation. Therefore, this study could be a vigorous input to enhance development programs to alleviate water scarcity in the study area. Full article
(This article belongs to the Special Issue Drought and Groundwater Development)
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26 pages, 1832 KiB  
Review
Some Well-Known Alginate and Chitosan Modifications Used in Adsorption: A Review
by Asmaa Benettayeb, Soumya Ghosh, Muhammad Usman, Fatima Zohra Seihoub, Ihsanullah Sohoo, Chin Hua Chia and Mika Sillanpää
Water 2022, 14(9), 1353; https://doi.org/10.3390/w14091353 - 21 Apr 2022
Cited by 75 | Viewed by 7417
Abstract
Owing to environmental pollution and increasingly strict regulations, heavy metals have attracted the attention of many researchers in various disciplines. Alginate and chitosan derivatives have gained popularity as biosorbents for water treatment. An increase in the number of publications on modified biosorbents for [...] Read more.
Owing to environmental pollution and increasingly strict regulations, heavy metals have attracted the attention of many researchers in various disciplines. Alginate and chitosan derivatives have gained popularity as biosorbents for water treatment. An increase in the number of publications on modified biosorbents for the biosorption of toxic compounds reveals widespread interest in examining the requirements and positive contribution of each modification type. This paper reviews the advantages and disadvantages of using alginate and chitosan for adsorption. Well-known modifications based on chitosan and alginate, namely, grafting, functionalization, copolymerization and cross-linking, as well as applications in the field of adsorption processes, especially amino acid functionalization, are reviewed. The selection criteria for the best biosorbents and their effectiveness and proposed mechanism of adsorption are discussed critically. In the conclusion, the question of why these adsorbents need modification before use is addressed. Full article
(This article belongs to the Special Issue Wastewater Treatment via the Adsorption Method)
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17 pages, 3772 KiB  
Article
New Challenges towards Smart Systems’ Efficiency by Digital Twin in Water Distribution Networks
by Helena M. Ramos, Maria Cristina Morani, Armando Carravetta, Oreste Fecarrotta, Kemi Adeyeye, P. Amparo López-Jiménez and Modesto Pérez-Sánchez
Water 2022, 14(8), 1304; https://doi.org/10.3390/w14081304 - 17 Apr 2022
Cited by 66 | Viewed by 7373
Abstract
Nowadays, in the management of water distribution networks (WDNs), particular attention is paid to digital transition and the improvement of the energy efficiency of these systems. New technologies have been developed in the recent years and their implementation can be crucial to achieve [...] Read more.
Nowadays, in the management of water distribution networks (WDNs), particular attention is paid to digital transition and the improvement of the energy efficiency of these systems. New technologies have been developed in the recent years and their implementation can be crucial to achieve a sustainable level of water networks, namely, in water and energy losses. In particular, Digital Twins (DT) represents a very innovative technology, which relies on the integration of virtual network models, optimization algorithms, real time data collection, and smart actuators information with Geographic Information System (GIS) data. This research defines a new methodology for an efficient application of DT expertise within water distribution networks. Assuming a DMA of a real water distribution network as a case study, it was demonstrated that a fast detection of leakage along with an optimal setting of pressure control valves by means of DT together with an optimization procedure can ensure up to 28% of water savings, contributing to significantly increase the efficiency of the whole system. Full article
(This article belongs to the Special Issue Urban Water Networks Modelling and Monitoring, Volume II)
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14 pages, 6430 KiB  
Article
Deep Learning-Based Algal Detection Model Development Considering Field Application
by Jungsu Park, Jiwon Baek, Jongrack Kim, Kwangtae You and Keugtae Kim
Water 2022, 14(8), 1275; https://doi.org/10.3390/w14081275 - 14 Apr 2022
Cited by 39 | Viewed by 4635
Abstract
Algal blooms have various effects on drinking water supply systems; thus, proper monitoring is essential. Traditional visual identification using a microscope is a time-consuming method and requires extensive labor. Recently, advanced machine learning algorithms have been increasingly applied for the development of object [...] Read more.
Algal blooms have various effects on drinking water supply systems; thus, proper monitoring is essential. Traditional visual identification using a microscope is a time-consuming method and requires extensive labor. Recently, advanced machine learning algorithms have been increasingly applied for the development of object detection models. The You-Only-Look-Once (YOLO) model is a novel machine learning algorithm used for object detection; it has been continuously improved in newer versions, and a tiny version of each standard model presented. The tiny versions applied a less complicated architecture using a smaller number of convolutional layers to enable faster object detection than the standard version. This study compared the applicability of the YOLO models for algal image detection from a practical aspect in terms of classification accuracy and inference time. Therefore, automated algal cell detection models were developed using YOLO v3 and YOLO v4, in which a tiny version of each model was also applied. The cell images of 30 algal genera were used for training and testing the models. The model performances were compared using the mean average precision (mAP). The mAP values of the four models were 40.9, 88.8, 84.4, and 89.8 for YOLO v3, YOLO v3-tiny, YOLO v4, and YOLO v4-tiny, respectively, demonstrating that YOLO v4 is more precise than YOLO v3. The tiny version models presented noticeably higher model accuracy than the standard models, allowing up to ten times faster object detection time. These results demonstrate the practical advantage of tiny version models for the application of object detection with a limited number of object classes. 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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36 pages, 993 KiB  
Review
A Review on Interpretable and Explainable Artificial Intelligence in Hydroclimatic Applications
by Hakan Başağaoğlu, Debaditya Chakraborty, Cesar Do Lago, Lilianna Gutierrez, Mehmet Arif Şahinli, Marcio Giacomoni, Chad Furl, Ali Mirchi, Daniel Moriasi and Sema Sevinç Şengör
Water 2022, 14(8), 1230; https://doi.org/10.3390/w14081230 - 11 Apr 2022
Cited by 58 | Viewed by 11577
Abstract
This review focuses on the use of Interpretable Artificial Intelligence (IAI) and eXplainable Artificial Intelligence (XAI) models for data imputations and numerical or categorical hydroclimatic predictions from nonlinearly combined multidimensional predictors. The AI models considered in this paper involve Extreme Gradient Boosting, Light [...] Read more.
This review focuses on the use of Interpretable Artificial Intelligence (IAI) and eXplainable Artificial Intelligence (XAI) models for data imputations and numerical or categorical hydroclimatic predictions from nonlinearly combined multidimensional predictors. The AI models considered in this paper involve Extreme Gradient Boosting, Light Gradient Boosting, Categorical Boosting, Extremely Randomized Trees, and Random Forest. These AI models can transform into XAI models when they are coupled with the explanatory methods such as the Shapley additive explanations and local interpretable model-agnostic explanations. The review highlights that the IAI models are capable of unveiling the rationale behind the predictions while XAI models are capable of discovering new knowledge and justifying AI-based results, which are critical for enhanced accountability of AI-driven predictions. The review also elaborates the importance of domain knowledge and interventional IAI modeling, potential advantages and disadvantages of hybrid IAI and non-IAI predictive modeling, unequivocal importance of balanced data in categorical decisions, and the choice and performance of IAI versus physics-based modeling. The review concludes with a proposed XAI framework to enhance the interpretability and explainability of AI models for hydroclimatic applications. 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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20 pages, 3134 KiB  
Article
Sluice Gate Design and Calibration: Simplified Models to Distinguish Flow Conditions and Estimate Discharge Coefficient and Flow Rate
by Arash Yoosefdoost and William David Lubitz
Water 2022, 14(8), 1215; https://doi.org/10.3390/w14081215 - 10 Apr 2022
Cited by 19 | Viewed by 17265
Abstract
Sluice gates are common hydraulic structures for controlling and regulating flow in open channels. This study investigates five models’ performance in distinguishing conditions of flow regimes, estimating the discharge coefficient (Cd) and flow rate. Experiments were conducted for different gate [...] Read more.
Sluice gates are common hydraulic structures for controlling and regulating flow in open channels. This study investigates five models’ performance in distinguishing conditions of flow regimes, estimating the discharge coefficient (Cd) and flow rate. Experiments were conducted for different gate openings, flow rates, upstream and downstream conditions. New equation forms and methods are proposed to determine Cd for energy–momentum considering losses (EML) and HEC-RAS models. For distinguishing the flow regimes, results indicated a reasonable performance for energy–momentum (EM), EML, and Swamee’s models. For flow rate and discharge coefficient performance of EM, EML, and Henry’s models in free flow and for EM and EML in submerged flow were reasonable. The effects of physical scale on models were investigated. There were concerns about the generality and accuracy of Swamee’s model. Scaling effects were observed on loss factor k in EML. A new equation and method were proposed to calibrate k that improved the EML model’s accuracy. This study facilitates the application and analysis of the studied models for the design or calibration of sluice gates and where the flow in open channels needs to be controlled or measured using sluice gates such as irrigation channels or water delivery channels of small run-of-river hydropower plants. Full article
(This article belongs to the Special Issue Hydraulic Transient of Hydropower Station and Pump Station)
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15 pages, 1931 KiB  
Article
Impacts of Fishing Vessels on the Heavy Metal Contamination in Sediments: A Case Study of Qianzhen Fishing Port in Southern Taiwan
by Yee-Cheng Lim, Chih-Feng Chen, Mei-Ling Tsai, Chung-Hsin Wu, Yi-Li Lin, Ming-Huang Wang, Frank Paolo Jay B. Albarico, Chiu-Wen Chen and Cheng-Di Dong
Water 2022, 14(7), 1174; https://doi.org/10.3390/w14071174 - 6 Apr 2022
Cited by 42 | Viewed by 5622
Abstract
Routine maintenance of fishing vessels and wastewater discharges are primary sources of heavy metals in fishing ports. Sediment pollution assessment is necessary in fishing port management, including sediment dredging and disposal, sewage treatment facility construction, and pollution source control. In this study, sediment [...] Read more.
Routine maintenance of fishing vessels and wastewater discharges are primary sources of heavy metals in fishing ports. Sediment pollution assessment is necessary in fishing port management, including sediment dredging and disposal, sewage treatment facility construction, and pollution source control. In this study, sediment heavy metal contents in Qianzhen Fishing Port, the largest pelagic fishery port in Taiwan, were investigated to assess the contamination levels and related potential ecological risks using multiple sediment pollution indices. Normalization methods were applied to identify the potential sources of heavy metals in fishing port sediments. Results showed that Cu, Zn, Pb, and Cr contents in the sediments of the inner fishing port (averages of 276, 742, 113, and 221 mg/kg, respectively) were 3–5 times greater compared to those along the port entrance and outside, indicating the strong impacts of anthropogenic pollution (EFCu: 5.6–12.5; EFZn: 2.8–4.3; EFPb: 2.4–5.4; EFCr: 1.1–3.2). Copper pollution was more severe, with high maxima contamination factor (CFCu: 15.1–24.8), probably contributed by copper-based antifouling paints used in fishing vessels. The sediments in the inner fishing port are categorized as having considerable ecological risk and toxicity (mERMq: 0.61–0.91; ΣTU: 7.5–11.7) that can potentially cause adverse effects on benthic organisms. Qianzhen Fishing Port sediments can be characterized as high Cu/Fe and Pb/Fe, moderate Zn/Fe, and high total grease content, indicating that the potential sources of heavy metals are primarily antifouling paints and oil spills from the fishing vessels. This study provides valuable data for pollution control, remediation, and environmental management of fishing ports. Full article
(This article belongs to the Special Issue The Relationship between Ships and Marine Environment)
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18 pages, 4511 KiB  
Review
Satellite Detection of Surface Water Extent: A Review of Methodology
by Jiaxin Li, Ronghua Ma, Zhigang Cao, Kun Xue, Junfeng Xiong, Minqi Hu and Xuejiao Feng
Water 2022, 14(7), 1148; https://doi.org/10.3390/w14071148 - 2 Apr 2022
Cited by 75 | Viewed by 13757
Abstract
Water is an imperative part of the Earth and an essential resource in human life and production. Under the effects of climate change and human activities, the spatial and temporal distribution of water bodies has been changing, and the shortage of water resources [...] Read more.
Water is an imperative part of the Earth and an essential resource in human life and production. Under the effects of climate change and human activities, the spatial and temporal distribution of water bodies has been changing, and the shortage of water resources is becoming increasingly serious worldwide. Therefore, the monitoring of water bodies is indispensable. Remote sensing has the advantages of real time, wide coverage, and rich information and has become a brand-new technical means to quickly obtain water information. This study summarizes the current common methods of water extraction based on optical and radar images, including the threshold method, support vector machine, decision tree, object-oriented extraction, and deep learning, as well as the advantages and disadvantages of each method. These methods were applied to the Huai River Basin in China and Nam Co on the Qinghai-Tibet Plateau. The extraction results show that all the aforementioned approaches can obtain reliable results. Among them, the threshold segmentation method based on normalized difference water index is more robust than others. In the water extraction process, there are still many problems that restrict the accuracy of the results. In the future, researchers will continue to search for more automatic, extensive, and high-precision water extraction methods. Full article
(This article belongs to the Special Issue Application of Remote Sensing Technology to Water-Related Ecosystems)
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17 pages, 1294 KiB  
Review
Water Quality and Water Pollution in Time of COVID-19: Positive and Negative Repercussions
by Valentina-Mariana Manoiu, Katarzyna Kubiak-Wójcicka, Alexandru-Ioan Craciun, Çiğdem Akman and Elvettin Akman
Water 2022, 14(7), 1124; https://doi.org/10.3390/w14071124 - 1 Apr 2022
Cited by 48 | Viewed by 13556
Abstract
On 11 March 2020, the World Health Organization declared the new COVID-19 disease a pandemic. Most countries responded with a lockdown to reduce its effects, which brought beneficial consequences to the environment in many regions, but the pandemic also raised a series of [...] Read more.
On 11 March 2020, the World Health Organization declared the new COVID-19 disease a pandemic. Most countries responded with a lockdown to reduce its effects, which brought beneficial consequences to the environment in many regions, but the pandemic also raised a series of challenges. This review proposes an assessment of the COVID-19 pandemic positive and negative impacts on water bodies on different continents. By applying a search protocol on the Web of Science platform, a scientific bank of 35 compatible studies was obtained out of the 62 open-access articles that were initially accessible. Regarding the positive impacts, the SARS-CoV-2 monitoring in sewage waters is a useful mechanism in the promptly exposure of community infections and, during the pandemic, many water bodies all over the world had lower pollution levels. The negative impacts are as follows: SARS-CoV-2 presence in untreated sewage water amplifies the risk to human health; there is a lack of adequate elimination processes of plastics, drugs, and biological pollution in wastewater treatment plants; the amount of municipal and medical waste that pollutes water bodies increased; and waste recycling decreased. Urgent preventive measures need to be taken to implement effective solutions for water protection. Full article
(This article belongs to the Special Issue Water Quality Management and Pollution Control under the Impact of Human Actions and Climate Change)
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20 pages, 4514 KiB  
Article
Flood Detection in Urban Areas Using Satellite Imagery and Machine Learning
by Ahad Hasan Tanim, Callum Blake McRae, Hassan Tavakol-Davani and Erfan Goharian
Water 2022, 14(7), 1140; https://doi.org/10.3390/w14071140 - 1 Apr 2022
Cited by 95 | Viewed by 17785
Abstract
Urban flooding poses risks to the safety of drivers and pedestrians, and damages infrastructures and lifelines. It is important to accommodate cities and local agencies with enhanced rapid flood detection skills and tools to better understand how much flooding a region may experience [...] Read more.
Urban flooding poses risks to the safety of drivers and pedestrians, and damages infrastructures and lifelines. It is important to accommodate cities and local agencies with enhanced rapid flood detection skills and tools to better understand how much flooding a region may experience at a certain period of time. This results in flood management orders being announced in a timely manner, allowing residents and drivers to preemptively avoid flooded areas. This research combines information received from ground observed data derived from road closure reports from the police department, with remotely sensed satellite imagery to develop and train machine-learning models for flood detection for the City of San Diego, CA, USA. For this purpose, flooding information are extracted from Sentinel 1 satellite imagery and fed into various supervised and unsupervised machine learning models, including Random Forest (RF), Support Vector Machine (SVM), and Maximum Likelihood Classifier (MLC), to detect flooded pixels in images and evaluate the performance of these ML models. Moreover, a new unsupervised machine learning framework is developed which works based on the change detection (CD) approach and combines the Otsu algorithm, fuzzy rules, and iso-clustering methods for urban flood detection. Results from the performance evaluation of RF, SVM, MLC and CD models show 0.53, 0.85, 0.75 and 0.81 precision measures, 0.9, 0.85, 0.85 and 0.9 for recall values, 0.67, 0.85, 0.79 and 0.85 for the F1-score, and 0.69, 0.87, 0.83 and 0.87 for the accuracy measure, respectively, for each model. In conclusion, the new unsupervised flood image classification and detection method offers better performance with the least required data and computational time for enhanced rapid flood mapping. This systematic approach will be potentially useful for other cities at risk of urban flooding, and hopefully for detecting nuisance floods, by using satellite images and reducing the flood risk of transportation design and urban infrastructure planning. Full article
(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)
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17 pages, 4146 KiB  
Article
Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale
by Wentao Xiong, Guoqiang Tang, Tsechun Wang, Ziqiang Ma and Wei Wan
Water 2022, 14(7), 1122; https://doi.org/10.3390/w14071122 - 31 Mar 2022
Cited by 30 | Viewed by 4813
Abstract
The precipitation phase (i.e., rain and snow) is important for the global hydrologic cycle and climate system. The objective of this study is to evaluate the precipitation-phase partitioning capabilities of remote sensing and reanalysis modeling methods on the global scale. Specifically, observation data [...] Read more.
The precipitation phase (i.e., rain and snow) is important for the global hydrologic cycle and climate system. The objective of this study is to evaluate the precipitation-phase partitioning capabilities of remote sensing and reanalysis modeling methods on the global scale. Specifically, observation data from the National Centers for Environmental Prediction (NCEP) Automated Data Processing (ADP), from 2000 to 2007, are used to evaluate the rain–snow discrimination accuracy of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) and the fifth-generation reanalysis product of the European Centre for Medium Range Weather Forecasts (ERA5). The results show that: (1) the ERA5 performs better than the IMERG at distinguishing rainfall and snowfall events, overall. (2) The ERA5 has high accuracy in all continents except for South America, while the IMERG performs well only in Antarctica and North America. (3) Compared with the IMERG, the ERA5 can more effectively capture snowfall events at high latitudes but shows worse performance at mid-low latitude regions. Both the IMERG and ERA5 have lower accuracy for rain–snow partitioning under heavy precipitation. Overall, the results of this study provide references for the application and improvement of global rain–snow partitioning products. Full article
(This article belongs to the Section Hydrology)
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16 pages, 3860 KiB  
Article
Enhancing Real-Time Prediction of Effluent Water Quality of Wastewater Treatment Plant Based on Improved Feedforward Neural Network Coupled with Optimization Algorithm
by Yifan Xie, Yongqi Chen, Qing Lian, Hailong Yin, Jian Peng, Meng Sheng and Yimeng Wang
Water 2022, 14(7), 1053; https://doi.org/10.3390/w14071053 - 27 Mar 2022
Cited by 55 | Viewed by 7602
Abstract
To provide real-time prediction of wastewater treatment plant (WWTP) effluent water quality, a machine learning (ML) model was developed by combining an improved feedforward neural network (IFFNN) with an optimization algorithm. Data used as input variables of the IFFNN included hourly influent water [...] Read more.
To provide real-time prediction of wastewater treatment plant (WWTP) effluent water quality, a machine learning (ML) model was developed by combining an improved feedforward neural network (IFFNN) with an optimization algorithm. Data used as input variables of the IFFNN included hourly influent water quality parameters, influent flow rate and WWTP process monitoring and operational parameters. Additionally, input variables included historical effluent water quality parameters for future prediction. The model was demonstrated in a WWTP in Jiangsu Province, China, where prediction of effluent chemical oxygen demand (COD) and total nitrogen (TN) with large variations were tested. Relative to the traditional feedforward neural network (FFNN) model without considering historical effluent water quality parameter input, the IFFNN enhanced prediction performance by 52.3% (COD) and 72.6% (TN) based on the mean absolute percentage errors of test datasets, after its model structure was optimized with a genetic algorithm (GA). The problem of over-fitting could also be overcome through the use of the IFFNN, with the determination of coefficient increased from 0.20 to 0.76 for test datasets of effluent COD. The GA-IFFNN model, which was efficient in capturing complex non-linear relationships and extrapolation, could be a useful tool for real-time direction of regulatory changes in WWTP operations. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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22 pages, 16353 KiB  
Article
Mapping Groundwater Potential Zones Using Analytical Hierarchical Process and Multicriteria Evaluation in the Central Eastern Desert, Egypt
by Mohd Yawar Ali Khan, Mohamed ElKashouty and Fuqiang Tian
Water 2022, 14(7), 1041; https://doi.org/10.3390/w14071041 - 25 Mar 2022
Cited by 36 | Viewed by 5385
Abstract
Exploring alternative freshwater resources other than those surrounding the Nile is critical to disperse Egypt’s population to other uninhabited desert areas. This study aims to locate groundwater potential zones (GWPZs) in the water-scarce desert between the Qina and Safga-Bir Queh regions to build [...] Read more.
Exploring alternative freshwater resources other than those surrounding the Nile is critical to disperse Egypt’s population to other uninhabited desert areas. This study aims to locate groundwater potential zones (GWPZs) in the water-scarce desert between the Qina and Safga-Bir Queh regions to build groundwater wells, thereby attracting and supporting people’s demand for water, food, and urban development. Multi-criteria evaluation (MCE) and analytical hierarchical process (AHP) techniques based on remote sensing (RS) and Geographic Information System (GIS) were used to map GWPZs. The outcome of the GWPZs map was divided into six different classes. High and very-high aquifer recharge potentials were localized in the middle and western parts, spanning 19.3% and 17% (16.4% and 15.7%) by MCE (AHP). Low and very low aquifer recharge potentials were distributed randomly in the eastern part over an area of 29% and 14.3% (26.9% and 6.1%) by MCE (AHP). Validation has been undertaken between the collected Total Dissolved Solid (TDS) and with the calculated GWPZs, indicating that the highest and lowest TDS concentrations of most aquifers are correlated with low to very low and high to very high aquifer potential, respectively. The study is promising and can be applied anywhere with similar setups for groundwater prospect and management. Full article
(This article belongs to the Special Issue Sustainable Water Futures: Climate, Community and Circular Economy)
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13 pages, 2147 KiB  
Article
Prediction of Flow Based on a CNN-LSTM Combined Deep Learning Approach
by Peifeng Li, Jin Zhang and Peter Krebs
Water 2022, 14(6), 993; https://doi.org/10.3390/w14060993 - 21 Mar 2022
Cited by 88 | Viewed by 10948
Abstract
Although machine learning (ML) techniques are increasingly used in rainfall-runoff models, most of them are based on one-dimensional datasets. In this study, a rainfall-runoff model with deep learning algorithms (CNN-LSTM) was proposed to compute runoff in the watershed based on two-dimensional rainfall radar [...] Read more.
Although machine learning (ML) techniques are increasingly used in rainfall-runoff models, most of them are based on one-dimensional datasets. In this study, a rainfall-runoff model with deep learning algorithms (CNN-LSTM) was proposed to compute runoff in the watershed based on two-dimensional rainfall radar maps directly. The model explored a convolutional neural network (CNN) to process two-dimensional rainfall maps and long short-term memory (LSTM) to process one-dimensional output data from the CNN and the upstream runoff in order to calculate the flow of the downstream runoff. In addition, the Elbe River basin in Sachsen, Germany, was selected as the study area, and the high-water periods of 2006, 2011, and 2013, and the low-water periods of 2015 and 2018 were used as the study periods. Via the fivefold validation, we found that the Nash–Sutcliffe efficiency (NSE) and Kling–Gupta efficiency (KGE) fluctuated from 0.46 to 0.97 and from 0.47 to 0.92 for the high-water period, where the optimal fold achieved 0.97 and 0.92, respectively. For the low-water period, the NSE and KGE ranged from 0.63 to 0.86 and from 0.68 to 0.93, where the optimal fold achieved 0.86 and 0.93, respectively. Our results demonstrate that CNN-LSTM would be useful for estimating water availability and flood alerts for river basin management. Full article
(This article belongs to the Special Issue Optimization and Prediction of Water Quality Model Based on Artificial Intelligence)
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15 pages, 2832 KiB  
Article
Sunflower Photosynthetic Characteristics, Nitrogen Uptake, and Nitrogen Use Efficiency under Different Soil Salinity and Nitrogen Applications
by Tao Ma, Kaiwen Chen, Pingru He, Yan Dai, Yiqun Yin, Suhan Peng, Jihui Ding, Shuang’en Yu and Jiesheng Huang
Water 2022, 14(6), 982; https://doi.org/10.3390/w14060982 - 20 Mar 2022
Cited by 21 | Viewed by 5829
Abstract
Understanding salinity and fertilizer interaction is of great importance to improve crop production and fertilizer use efficiency in saline areas. To evaluate the interactive effects of different soil salinity levels and nitrogen (N) applications rates on the sunflower photosynthetic characteristics of N uptake [...] Read more.
Understanding salinity and fertilizer interaction is of great importance to improve crop production and fertilizer use efficiency in saline areas. To evaluate the interactive effects of different soil salinity levels and nitrogen (N) applications rates on the sunflower photosynthetic characteristics of N uptake and N use efficiency, a two-year field experiment was conducted in Hetao Irrigation District, China. The experiment consisted of three initial salinity (IS) levels expressed as the electrical conductivity of a saturated soil extract (ECe) (S0: 1.72–2.61 dS/m; S1: 4.73–5.90 dS/m; S2: 6.85–9.04 dS/m) and four N rates (45, 90, 135, and 180 kg/ha), referred as N0–N3, respectively. The results indicated that the net photosynthetic rate (Pn) of sunflowers treated with S0 and S1 levels both had a significant decrease in the bud stage, and then reached their maximum at anthesis. However, during the crop cycle, the Pn at S2 level only had small fluctuations and still remained at a high level (>40 μmol CO2/(m2 s)) at the early mature stage. When increasing IS levels from S0 to S1, the plant N uptake (PNU) under the same N rates were only decreased by less than 10% at maturity, whereas the decline was expanded to 17.2–45.7% from S1 to S2. Additionally, though applying the N2 rate could not increase sunflower PNU at the S0 and S1 levels, its N use efficiency was better than those under N3. Meanwhile, at the S2 level, the application of the N0 rate produced a higher N productive efficiency (NPE) and N uptake efficiency (NUPE) than the other N rates. Therefore, our study proposed recommended rates of N fertilizer (S0 and S1: 135 kg/ha, S2: 45 kg/ha) for sunflowers under different saline conditions. Full article
(This article belongs to the Special Issue Efficient Use of Water and Soil Resources)
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31 pages, 8526 KiB  
Article
Occurrence of Antibiotic Resistant Bacteria in Urban Karst Groundwater Systems
by Rachel A. Kaiser, Jason S. Polk, Tania Datta, Rohan R. Parekh and Getahun E. Agga
Water 2022, 14(6), 960; https://doi.org/10.3390/w14060960 - 18 Mar 2022
Cited by 28 | Viewed by 4908
Abstract
Antibiotic resistance is a global concern for human, animal, and environmental health. Many studies have identified wastewater treatment plants and surface waters as major reservoirs of antibiotic resistant bacteria (ARB) and genes (ARGs). Yet their prevalence in urban karst groundwater systems remains largely [...] Read more.
Antibiotic resistance is a global concern for human, animal, and environmental health. Many studies have identified wastewater treatment plants and surface waters as major reservoirs of antibiotic resistant bacteria (ARB) and genes (ARGs). Yet their prevalence in urban karst groundwater systems remains largely unexplored. Considering the extent of karst groundwater use globally, and the growing urban areas in these regions, there is an urgent need to understand antibiotic resistance in karst systems to protect source water and human health. This study evaluated the prevalence of ARGs associated with resistance phenotypes at 10 urban karst features in Bowling Green, Kentucky weekly for 46 weeks. To expand the understanding of prevalence in urban karst, a spot sampling of 45 sites in the Tampa Bay Metropolitan area, Florida was also conducted. Specifically, this study considered tetracycline and extended spectrum beta-lactamase (ESBLs) producing, including third generation cephalosporin, resistant E. coli, and tetracycline and macrolide resistant Enterococcus spp. across the 443 Kentucky and 45 Florida samples. A consistent prevalence of clinically relevant and urban associated ARGs were found throughout the urban karst systems, regardless of varying urban development, karst geology, climate, or landuse. These findings indicate urban karst groundwater as a reservoir for antibiotic resistance, potentially threatening human health. Full article
(This article belongs to the Special Issue Antibiotic Resistance in Environmental Waters)
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20 pages, 9741 KiB  
Article
UV/TiO2 Photocatalysis as an Efficient Livestock Wastewater Quaternary Treatment for Antibiotics Removal
by Yeji Park, Sanghyeon Kim, Jungyeon Kim, Sanaullah Khan and Changseok Han
Water 2022, 14(6), 958; https://doi.org/10.3390/w14060958 - 18 Mar 2022
Cited by 23 | Viewed by 4814
Abstract
Antibiotics are the most common pharmaceutical compounds, and they have been extensively used for the prevention and treatment of bacterial diseases for more than 50 years. However, merely a small fraction of antibiotics is metabolized in the body, while the rest is discharged [...] Read more.
Antibiotics are the most common pharmaceutical compounds, and they have been extensively used for the prevention and treatment of bacterial diseases for more than 50 years. However, merely a small fraction of antibiotics is metabolized in the body, while the rest is discharged into the environment through excretion, which can cause potential ecological problems and human health risks. In this study, the elimination of seventeen antibiotics from real livestock wastewater effluents was investigated by UV/TiO2 advanced oxidation process. The effect of process parameters, such as TiO2 loadings, solution pHs, and antibiotic concentrations, on the efficiency of the UV/TiO2 process was assessed. The degradation efficiency was affected by the solution pH, and higher removal efficiency was observed at pH 5.8 and 9.9, while the catalyst loading had no significant effect on the degradation efficiency at these experimental conditions. UV photolysis showed a good removal efficiency of the antibiotics. However, the highest removal efficiency was shown by the UV/photocatalyst system due to their synergistic effects. The results showed that more than 90% of antibiotics were removed by UV/TiO2 system during the 60 min illumination, while the corresponding TOC and COD removal was only 10 and 13%, respectively. The results of the current study indicated that UV/TiO2 advanced oxidation process is a promising method for the elimination of various types of antibiotics from real livestock wastewater effluents. Full article
(This article belongs to the Special Issue Advances in Water and Wastewater Monitoring and Treatment Technology 2.0)
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22 pages, 9022 KiB  
Review
Groundwater Level Modeling with Machine Learning: A Systematic Review and Meta-Analysis
by Arman Ahmadi, Mohammadali Olyaei, Zahra Heydari, Mohammad Emami, Amin Zeynolabedin, Arash Ghomlaghi, Andre Daccache, Graham E. Fogg and Mojtaba Sadegh
Water 2022, 14(6), 949; https://doi.org/10.3390/w14060949 - 17 Mar 2022
Cited by 79 | Viewed by 13551
Abstract
Groundwater is a vital source of freshwater, supporting the livelihood of over two billion people worldwide. The quantitative assessment of groundwater resources is critical for sustainable management of this strained resource, particularly as climate warming, population growth, and socioeconomic development further press the [...] Read more.
Groundwater is a vital source of freshwater, supporting the livelihood of over two billion people worldwide. The quantitative assessment of groundwater resources is critical for sustainable management of this strained resource, particularly as climate warming, population growth, and socioeconomic development further press the water resources. Rapid growth in the availability of a plethora of in-situ and remotely sensed data alongside advancements in data-driven methods and machine learning offer immense opportunities for an improved assessment of groundwater resources at the local to global levels. This systematic review documents the advancements in this field and evaluates the accuracy of various models, following the protocol developed by the Center for Evidence-Based Conservation. A total of 197 original peer-reviewed articles from 2010–2020 and from 28 countries that employ regression machine learning algorithms for groundwater monitoring or prediction are analyzed and their results are aggregated through a meta-analysis. Our analysis points to the capability of machine learning models to monitor/predict different characteristics of groundwater resources effectively and efficiently. Modeling the groundwater level is the most popular application of machine learning models, and the groundwater level in previous time steps is the most employed input data. The feed-forward artificial neural network is the most employed and accurate model, although the model performance does not exhibit a striking dependence on the model choice, but rather the information content of the input variables. Around 10–12 years of data are required to develop an acceptable machine learning model with a monthly temporal resolution. Finally, advances in machine and deep learning algorithms and computational advancements to merge them with physics-based models offer unprecedented opportunities to employ new information, e.g., InSAR data, for increased spatiotemporal resolution and accuracy of groundwater monitoring and prediction. Full article
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20 pages, 1981 KiB  
Review
A Review on Coagulation/Flocculation in Dewatering of Coal Slurry
by Atousa Khazaie, Mahmoud Mazarji, Bijan Samali, Dave Osborne, Tatiana Minkina, Svetlana Sushkova, Saglara Mandzhieva and Alexander Soldatov
Water 2022, 14(6), 918; https://doi.org/10.3390/w14060918 - 15 Mar 2022
Cited by 65 | Viewed by 12285
Abstract
Coal slurry is an essential component of mining operations, accounting for more than half of operating costs. Dewatering technology is simultaneously confronted with obstacles and possibilities, and it may yet be improved as the crucial step for reducing the ultimate processing cost. Coagulation/flocculation [...] Read more.
Coal slurry is an essential component of mining operations, accounting for more than half of operating costs. Dewatering technology is simultaneously confronted with obstacles and possibilities, and it may yet be improved as the crucial step for reducing the ultimate processing cost. Coagulation/flocculation is used as a dewatering process that is reasonably cost-effective and user-friendly. This paper reviews application of different coagulants/flocculants and their combinations in dewatering mechanisms. In this context, various polymeric flocculants are discussed in the coal slurry in depth. Many operational parameters that influence the performance of coal slurry flocculation are also presented. Furthermore, a discussion is provided on the mechanism of flocculants’ interaction, the strategy of combining flocculants, and efficient selection methods of flocculants. Finally, coagulation/flocculation remaining challenges and technological improvements for the better development of highly efficient treatment methods were highlighted, focusing on the intricate composition of slurry and its treatment difficulties. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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20 pages, 989 KiB  
Review
The WHO Guidelines for Safe Wastewater Use in Agriculture: A Review of Implementation Challenges and Possible Solutions in the Global South
by Pay Drechsel, Manzoor Qadir and David Galibourg
Water 2022, 14(6), 864; https://doi.org/10.3390/w14060864 - 10 Mar 2022
Cited by 42 | Viewed by 11427
Abstract
Globally, the use of untreated, often diluted, or partly treated wastewater in agriculture covers about 30 million ha, far exceeding the area under the planned use of well-treated (reclaimed) wastewater which has been estimated in this paper at around 1.0 million ha. This [...] Read more.
Globally, the use of untreated, often diluted, or partly treated wastewater in agriculture covers about 30 million ha, far exceeding the area under the planned use of well-treated (reclaimed) wastewater which has been estimated in this paper at around 1.0 million ha. This gap has likely increased over the last decade despite significant investments in treatment capacities, due to the even larger increases in population, water consumption, and wastewater generation. To minimize the human health risks from unsafe wastewater irrigation, the WHO’s related 2006 guidelines suggest a broader concept than the previous (1989) edition by emphasizing, especially for low-income countries, the importance of risk-reducing practices from ‘farm to fork’. This shift from relying on technical solutions to facilitating and monitoring human behaviour change is, however, challenging. Another challenge concerns local capacities for quantitative risk assessment and the determination of a risk reduction target. Being aware of these challenges, the WHO has invested in a sanitation safety planning manual which has helped to operationalize the rather academic 2006 guidelines, but without addressing key questions, e.g., on how to trigger, support, and sustain the expected behaviour change, as training alone is unlikely to increase the adoption of health-related practices. This review summarizes the perceived challenges and suggests several considerations for further editions or national adaptations of the WHO guidelines. Full article
(This article belongs to the Special Issue Section Wastewater Treatment and Reuse: Feature Papers)
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18 pages, 4265 KiB  
Article
Monitoring Recent Changes in Drought and Wetness in the Source Region of the Yellow River Basin, China
by Yanqun Ren, Jinping Liu, Masoud Jafari Shalamzari, Arfan Arshad, Suxia Liu, Tie Liu and Hui Tao
Water 2022, 14(6), 861; https://doi.org/10.3390/w14060861 - 10 Mar 2022
Cited by 22 | Viewed by 3870
Abstract
The source region of the Yellow River Basin (SRYRB) is not only sensitive to climate change and the vulnerable region of the ecological environment but also the primary runoff generating region of the Yellow River Basin (YRB). Its changes of drought and wetness [...] Read more.
The source region of the Yellow River Basin (SRYRB) is not only sensitive to climate change and the vulnerable region of the ecological environment but also the primary runoff generating region of the Yellow River Basin (YRB). Its changes of drought and wetness profoundly impact water resources security, food production and ecological environment in the middle and downward reaches of YRB. In the context of global warming, based on daily precipitation, maximum and minimum temperature of 12 national meteorological stations around and within SRYRB during 1960–2015, this study obtained standardized precipitation index (SPI) and reconnaissance drought index (RDI) on 1-, 3-, 6- and 12-month scales, and then compared the consistency of SPI and RDI in many aspects. Finally, the temporal and spatial variation characteristics of drought and wetness in the SRYRB during 1960–2015 were analyzed in this study. The results showed that SPI and RDI have high consistency on different time scales (correlation coefficient above 0.92). According to the average distribution and change trend of the RDI, SRYRB presented an overall wetness state on different time scales. We found an increasing trend in wetness since the early 1980s. In terms of wetness events of different magnitudes, the highest frequency for moderate and severe ones was in June (12.7%) and February (5.5%), respectively, and for extreme wetness events, both September and January had the highest frequency (1.8%). Among the four seasons, the change rate of RDI in spring was the largest with a value of 0.38 decade−1, followed by winter (0.36 decade−1) and autumn (0.2 decade−1) and the smallest in summer (0.1 decade−1). There was a greater consistency between RDI values of larger time scales such as annual and vegetation growing seasonal (VGS) scales in SRYRB. There was generally a growing trend in wetness in the VGS time scale. These findings presented in this study can provide data support for drought and wetness management in SRYRB. Full article
(This article belongs to the Special Issue The Interrelationship between Climate Change, Human Activities and Hydrological Processes)
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31 pages, 2768 KiB  
Review
Nitrate Water Contamination from Industrial Activities and Complete Denitrification as a Remediation Option
by Karabelo M. Moloantoa, Zenzile P. Khetsha, Esta van Heerden, Julio C. Castillo and Errol D. Cason
Water 2022, 14(5), 799; https://doi.org/10.3390/w14050799 - 3 Mar 2022
Cited by 76 | Viewed by 23792
Abstract
Freshwater is a scarce resource that continues to be at high risk of pollution from anthropogenic activities, requiring remediation in such cases for its continuous use. The agricultural and mining industries extensively use water and nitrogen (N)-dependent products, mainly in fertilizers and explosives, [...] Read more.
Freshwater is a scarce resource that continues to be at high risk of pollution from anthropogenic activities, requiring remediation in such cases for its continuous use. The agricultural and mining industries extensively use water and nitrogen (N)-dependent products, mainly in fertilizers and explosives, respectively, with their excess accumulating in different water bodies. Although removal of NO3 from water and soil through the application of chemical, physical, and biological methods has been studied globally, these methods seldom yield N2 gas as a desired byproduct for nitrogen cycling. These methods predominantly cause secondary contamination with deposits of chemical waste such as slurry brine, nitrite (NO2), ammonia (NH3), and nitrous oxide (N2O), which are also harmful and fastidious to remove. This review focuses on complete denitrification facilitated by bacteria as a remedial option aimed at producing nitrogen gas as a terminal byproduct. Synergistic interaction of different nitrogen metabolisms from different bacteria is highlighted, with detailed attention to the optimization of their enzymatic activities. A biotechnological approach to mitigating industrial NO3 contamination using indigenous bacteria from wastewater is proposed, holding the prospect of optimizing to the point of complete denitrification. The approach was reviewed and found to be durable, sustainable, cost effective, and environmentally friendly, as opposed to current chemical and physical water remediation technologies. Full article
(This article belongs to the Special Issue Biological Treatment of Mining and Industrial Effluents and Groundwaters)
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