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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Article

Article
Data-Driven Community Flood Resilience Prediction
Water 2022, 14(13), 2120; https://doi.org/10.3390/w14132120 - 02 Jul 2022
Cited by 2 | Viewed by 1530
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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Article
Sluice Gate Design and Calibration: Simplified Models to Distinguish Flow Conditions and Estimate Discharge Coefficient and Flow Rate
Water 2022, 14(8), 1215; https://doi.org/10.3390/w14081215 - 10 Apr 2022
Viewed by 5946
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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Article
Sensitivity, Hazard, and Vulnerability of Farmlands to Saltwater Intrusion in Low-Lying Coastal Areas of Venice, Italy
Water 2022, 14(1), 64; https://doi.org/10.3390/w14010064 - 30 Dec 2021
Cited by 5 | Viewed by 1222
Abstract
Saltwater intrusion is a growing threat for coastal aquifers and agricultural practices in low-lying plains. Most of the farmlands located between the margin of the Southern Venice lagoon and the Northern Po delta, Italy, lie a few meters below mean sea level and [...] Read more.
Saltwater intrusion is a growing threat for coastal aquifers and agricultural practices in low-lying plains. Most of the farmlands located between the margin of the Southern Venice lagoon and the Northern Po delta, Italy, lie a few meters below mean sea level and are drained by a large network of artificial channels and hydraulic infrastructures to avoid frequent flooding and allow agricultural practices. This work proposes an assessment of the vulnerability to saltwater intrusion, following a new concept of the hazard status, resulting in combining the depth of the freshwater/saltwater interface and the electrical resistivity of the shallow subsoil. The sensitivity of the farmland system was assessed by using ground elevation, distance from freshwater and saltwater sources, permeability, potential runoff, land subsidence, and sea-level rise indicators. Relative weights were assigned by a pairwise comparison following the Analytic Hierarchy Process approach. The computed vulnerability map highlights that about 30% of the farmlands is under strong and extreme conditions, 28% between marginal and moderate, and 40% under negligible conditions. Results from previous vulnerability assessments are discussed in order to explain their differences in terms of hazard status conceptualization and sensitivity characterization of farmland system. Full article
(This article belongs to the Special Issue Salinization of Water Resources: Ongoing and Future Trends)
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Article
Diversity of Silica-Scaled Chrysophytes in Central Vietnam
Water 2022, 14(1), 65; https://doi.org/10.3390/w14010065 - 30 Dec 2021
Cited by 7 | Viewed by 844
Abstract
This paper focuses on the flora of scale-bearing chrysophytes from eight provinces located in the central part of Vietnam. Khanh Hoa, Phu Yen, Binh Dinh, Thua Thien Hue, Quang Tri, and Quang Binh provinces are located in the coastal area of Vietnam. Lam [...] Read more.
This paper focuses on the flora of scale-bearing chrysophytes from eight provinces located in the central part of Vietnam. Khanh Hoa, Phu Yen, Binh Dinh, Thua Thien Hue, Quang Tri, and Quang Binh provinces are located in the coastal area of Vietnam. Lam Dong and Dak Lak provinces represent mountain territories with an elevation of 500–2000 metres above sea level. In total, 212 water bodies of different origins were studied. Samples were obtained from swamp areas, lakes, rivers, reservoirs, ponds, and small temporary water bodies. In total, 76 taxa were identified by electron microscopic observations of samples. A total of 54 taxa were found in the mountainous provinces, while 73 were found in the coastal provinces. Of these, 51 species are common for both areas. The most diverse was the genus Mallomonas with 66 species, varieties, and forms; followed by Synura with 7 taxa; Chrysosphaerella with 2; and Spiniferomonas with 1. Seven taxa of the genus Mallomonas were not identified to the lower rank. All these unidentified specimens may potentially represent new species for science. Ten taxa are reported for the first time in Vietnam. Full article
(This article belongs to the Special Issue Species Richness and Diversity of Aquatic Ecosystems)
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Article
Monitoring Water Quality of the Haihe River Based on Ground-Based Hyperspectral Remote Sensing
Water 2022, 14(1), 22; https://doi.org/10.3390/w14010022 - 22 Dec 2021
Cited by 14 | Viewed by 2733
Abstract
The Haihe River is a typical sluice-controlled river in the north of China. The construction and operation of sluice dams change the flow and other hydrological factors of rivers, which have adverse effects on water, making it difficult to study the characteristics of [...] Read more.
The Haihe River is a typical sluice-controlled river in the north of China. The construction and operation of sluice dams change the flow and other hydrological factors of rivers, which have adverse effects on water, making it difficult to study the characteristics of water quality change and water environment control in northern rivers. In recent years, remote sensing has been widely used in water quality monitoring. However, due to the low signal-to-noise ratio (SNR) and the limitation of instrument resolution, satellite remote sensing is still a challenge to inland water quality monitoring. Ground-based hyperspectral remote sensing has a high temporal-spatial resolution and can be simply fixed in the water edge to achieve real-time continuous detection. A combination of hyperspectral remote sensing devices and BP neural networks is used in the current research to invert water quality parameters. The measured values and remote sensing reflectance of eight water quality parameters (chlorophyll-a (Chl-a), phycocyanin (PC), total suspended sediments (TSS), total nitrogen (TN), total phosphorus (TP), ammonia nitrogen (NH4-N), nitrate-nitrogen (NO3-N), and pH) were modeled and verified. The results show that the performance R2 of the training model is above 80%, and the performance R2 of the verification model is above 70%. In the training model, the highest fitting degree is TN (R2 = 1, RMSE = 0.0012 mg/L), and the lowest fitting degree is PC (R2 = 0.87, RMSE = 0.0011 mg/L). Therefore, the application of hyperspectral remote sensing technology to water quality detection in the Haihe River is a feasible method. The model built in the hyperspectral remote sensing equipment can help decision-makers to easily understand the real-time changes of water quality parameters. Full article
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Article
Optimization of Magnetic Nanoparticles Draw Solution for High Water Flux in Forward Osmosis
Water 2021, 13(24), 3653; https://doi.org/10.3390/w13243653 - 20 Dec 2021
Cited by 6 | Viewed by 1781
Abstract
In this study, bare iron oxide nanoparticles were synthesized using a co-precipitation method and used as a draw solute in forward osmosis. The synthesis conditions of the nanoparticles were optimized using the Box-Behnken method to increase the water flux of the forward osmosis [...] Read more.
In this study, bare iron oxide nanoparticles were synthesized using a co-precipitation method and used as a draw solute in forward osmosis. The synthesis conditions of the nanoparticles were optimized using the Box-Behnken method to increase the water flux of the forward osmosis process. The studied parameters were volume of ammonia solution, reaction temperature, and reaction time. The optimum reaction conditions were obtained at reaction temperature of 30 °C, reaction time of 2.73 h and 25.3 mL of ammonia solution. The water flux from the prediction model was found to be 2.06 LMH which is close to the experimental value of 1.98 LMH. The prediction model had high correlation factors (R2 = 98.82%) and (R2adj = 96.69%). This study is expected to be the base for future studies aiming at developing magnetic nanoparticles draw solution using co-precipitation method. Full article
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Article
Uncertainty in Drought Identification Due to Data Choices, and the Value of Triangulation
Water 2021, 13(24), 3611; https://doi.org/10.3390/w13243611 - 16 Dec 2021
Cited by 6 | Viewed by 1658
Abstract
Droughts are complex and gradually evolving conditions of extreme water deficits which can compromise livelihoods and ecological integrity, especially in fragile arid and semi-arid regions that depend on rainfed farming, such as Kitui West in south-eastern Kenya. Against the background of low ground-station [...] Read more.
Droughts are complex and gradually evolving conditions of extreme water deficits which can compromise livelihoods and ecological integrity, especially in fragile arid and semi-arid regions that depend on rainfed farming, such as Kitui West in south-eastern Kenya. Against the background of low ground-station density, 10 gridded rainfall products and four gridded temperature products were used to generate an ensemble of 40 calculations of the Standardized Precipitation Evapotranspiration Index (SPEI) to assess uncertainties in the onset, duration, and magnitude of past droughts. These uncertainties were driven more by variations between the rainfall products than variations between the temperature products. Remaining ambiguities in drought occurrence could be resolved by complementing the quantitative analysis with ground-based information from key informants engaged in disaster relief, effectively formulating an ensemble approach to SPEI-based drought identification to aid decision making. The reported trend towards drier conditions in Eastern Africa was confirmed for Kitui West by the majority of data products, whereby the rainfall effect on those increasingly dry conditions was subtler than just annual and seasonal declines and greater annual variation of rainfall, which requires further investigation. Nevertheless, the effects of increasing droughts are already felt on the ground and warrant decisive action. Full article
(This article belongs to the Topic Water Management in the Era of Climatic Change)
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Article
A Synergic Use of Sentinel-1 and Sentinel-2 Imagery for Complex Wetland Classification Using Generative Adversarial Network (GAN) Scheme
Water 2021, 13(24), 3601; https://doi.org/10.3390/w13243601 - 15 Dec 2021
Cited by 5 | Viewed by 2037
Abstract
Due to anthropogenic activities and climate change, many natural ecosystems, especially wetlands, are lost or changing at a rapid pace. For the last decade, there has been increasing attention towards developing new tools and methods for the mapping and classification of wetlands using [...] Read more.
Due to anthropogenic activities and climate change, many natural ecosystems, especially wetlands, are lost or changing at a rapid pace. For the last decade, there has been increasing attention towards developing new tools and methods for the mapping and classification of wetlands using remote sensing. At the same time, advances in artificial intelligence and machine learning, particularly deep learning models, have provided opportunities to advance wetland classification methods. However, the developed deep and very deep algorithms require a higher number of training samples, which is costly, logistically demanding, and time-consuming. As such, in this study, we propose a Deep Convolutional Neural Network (DCNN) that uses a modified architecture of the well-known DCNN of the AlexNet and a Generative Adversarial Network (GAN) for the generation and classification of Sentinel-1 and Sentinel-2 data. Applying to an area of approximately 370 sq. km in the Avalon Peninsula, Newfoundland, the proposed model with an average accuracy of 92.30% resulted in F-1 scores of 0.82, 0.85, 0.87, 0.89, and 0.95 for the recognition of swamp, fen, marsh, bog, and shallow water, respectively. Moreover, the proposed DCNN model improved the F-1 score of bog, marsh, fen, and swamp wetland classes by 4%, 8%, 11%, and 26%, respectively, compared to the original CNN network of AlexNet. These results reveal that the proposed model is highly capable of the generation and classification of Sentinel-1 and Sentinel-2 wetland samples and can be used for large-extent classification problems. Full article
(This article belongs to the Special Issue Mapping and Monitoring of Wetlands)
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Article
Hydrogeochemical Assessment of Groundwater and Suitability Analysis for Domestic and Agricultural Utility in Southern Punjab, Pakistan
Water 2021, 13(24), 3589; https://doi.org/10.3390/w13243589 - 14 Dec 2021
Cited by 19 | Viewed by 2147
Abstract
Groundwater is a critical water supply for safe drinking water, agriculture, and industry worldwide. In the Khanewal district of Punjab, Pakistan, groundwater has severely deteriorated during the last few decades due to environmental changes and anthropogenic activities. Therefore, 68 groundwater samples were collected [...] Read more.
Groundwater is a critical water supply for safe drinking water, agriculture, and industry worldwide. In the Khanewal district of Punjab, Pakistan, groundwater has severely deteriorated during the last few decades due to environmental changes and anthropogenic activities. Therefore, 68 groundwater samples were collected and analyzed for their main ions and trace elements to investigate the suitability of groundwater sources for drinking and agricultural purposes. Principal component analysis (PCA) and cluster analysis (CA) were employed to determine the major factors influencing groundwater quality. To assess the groundwater’s appropriateness for drinking and irrigation, drinking and agricultural indices were used. The pH of the groundwater samples ranged from 6.9 to 9.2, indicating that the aquifers were slightly acidic to alkaline. The major cations were distributed as follows: Na+ > Ca2+ > Mg2+ > K+. Meanwhile, the anions are distributed as follows: HCO3 > SO42− > Cl > F. The main hydrochemical facies were identified as a mixed type; however, a mixed magnesium, calcium, and chloride pattern was observed. The reverse ion exchange process helps in exchanging Na+ with Ca2+ and Mg2+ ions in the groundwater system. Rock weathering processes, such as the dissolution of calcite, dolomite, and gypsum minerals, dominated the groundwater hydrochemistry. According to the Weight Arithmetic Water Quality Index (WAWQI), 50% of the water samples were unsafe for drinking. The Wilcox diagram, USSL diagram, and some other agricultural indices resulted in around 32% of the groundwater samples being unsuitable for irrigation purposes. The Khanewal’s groundwater quality was vulnerable due to geology and the influence of anthropogenic activities. For groundwater sustainability in Khanewal, management strategies and policies are required. Full article
(This article belongs to the Section Hydrogeology)
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Article
Anaerobic Digestion for Biogas Production from Municipal Sewage Sludge: A Comparative Study between Fine Mesh Sieved Primary Sludge and Sedimented Primary Sludge
Water 2021, 13(24), 3532; https://doi.org/10.3390/w13243532 - 10 Dec 2021
Cited by 7 | Viewed by 1619
Abstract
Two different types of primary sewage sludge have been used as feedstock for production of biogas through anaerobic digestion (AD): the one type was sludge from a typical primary clarifier (PC), while the other type of sludge produced by a rotating belt filter, [...] Read more.
Two different types of primary sewage sludge have been used as feedstock for production of biogas through anaerobic digestion (AD): the one type was sludge from a typical primary clarifier (PC), while the other type of sludge produced by a rotating belt filter, commonly called microsieve (MS). Initially the main physicochemical characteristics of the sludges, such as total solids (TS), volatile solids (VS), VS/TS, pH and carbon to nitrogen ratio (C/N) were determined, for MS: 37.86 ± 0.08%, 83.00 ± 0.41%, 0.83 ± 0.00, 6.67 ± 0.08 and 19.68 ± 0.69, respectively, and for PC: 2.61 ± 0.08%, 78.77 ± 1.91%, 0.79 ± 0.02, 6.61 ± 0.10 and 14.46 ± 1.23, respectively. Then, calculated amounts of the sludges were inserted into airtight vials and were inoculated using anaerobic sludge. The daily biogas production was measured over a period of 30 days. PC sludge maximized the daily biogas production (44.20 mlbiogas/gvsd) 11 days after inoculation, while the MS sludge reach a peak (37.74 mlbiogas/gvsd) 14 days after inoculation. The cumulative biogas production over the 30 days of AD was in the same laver (442.29 mlbiogas/gvs for PC versus 434.73 mlbiogas/gvs for MS). However, PC sludge indicated higher daily biogas production, compared to MS sludge, while the opposite was observed for the period following the peak point. The Volatile Solids Reduction for PC and MS sludges was recorded as 46.06% and 32.39%, respectively. Full article
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Article
Forest Fires Reduce Snow-Water Storage and Advance the Timing of Snowmelt across the Western U.S.
Water 2021, 13(24), 3533; https://doi.org/10.3390/w13243533 - 10 Dec 2021
Cited by 6 | Viewed by 1857
Abstract
As climate warms, snow-water storage is decreasing while forest fires are increasing in extent, frequency, and duration. The majority of forest fires occur in the seasonal snow zone across the western US. Yet, we do not understand the broad-scale variability of forest fire [...] Read more.
As climate warms, snow-water storage is decreasing while forest fires are increasing in extent, frequency, and duration. The majority of forest fires occur in the seasonal snow zone across the western US. Yet, we do not understand the broad-scale variability of forest fire effects on snow-water storage and water resource availability. Using pre- and post-fire data from 78 burned SNOTEL stations, we evaluated post-fire shifts in snow accumulation (snow-water storage) and snowmelt across the West and Alaska. For a decade following fire, maximum snow-water storage decreased by over 30 mm, and the snow disappearance date advanced by 9 days, and in high severity burned forests snowmelt rate increased by 3 mm/day. Regionally, forest fires reduced snow-water storage in Alaska, Arizona, and the Pacific Northwest and advanced the snow disappearance date across the Rockies, Western Interior, Wasatch, and Uinta mountains. Broad-scale empirical results of forest fire effects on snow-water storage and snowmelt inform natural resource management and modeling of future snow-water resource availability in burned watersheds. Full article
(This article belongs to the Section Hydrology)
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Article
Development of Boosted Machine Learning Models for Estimating Daily Reference Evapotranspiration and Comparison with Empirical Approaches
Water 2021, 13(24), 3489; https://doi.org/10.3390/w13243489 - 07 Dec 2021
Cited by 8 | Viewed by 2005
Abstract
Proper irrigation scheduling and agricultural water management require a precise estimation of crop water requirement. In practice, reference evapotranspiration (ETo) is firstly estimated, and used further to calculate the evapotranspiration of each crop. In this study, two new coupled models were developed for [...] Read more.
Proper irrigation scheduling and agricultural water management require a precise estimation of crop water requirement. In practice, reference evapotranspiration (ETo) is firstly estimated, and used further to calculate the evapotranspiration of each crop. In this study, two new coupled models were developed for estimating daily ETo. Two optimization algorithms, the shuffled frog-leaping algorithm (SFLA) and invasive weed optimization (IWO), were coupled on an adaptive neuro-fuzzy inference system (ANFIS) to develop and implement the two novel hybrid models (ANFIS-SFLA and ANFIS-IWO). Additionally, four empirical models with varying complexities, including Hargreaves–Samani, Romanenko, Priestley–Taylor, and Valiantzas, were used and compared with the developed hybrid models. The performance of all investigated models was evaluated using the ETo estimates with the FAO-56 recommended method as a benchmark, as well as multiple statistical indicators including root-mean-square error (RMSE), relative RMSE (RRMSE), mean absolute error (MAE), coefficient of determination (R2), and Nash–Sutcliffe efficiency (NSE). All models were tested in Tabriz and Shiraz, Iran as the two studied sites. Evaluation results showed that the developed coupled models yielded better results than the classic ANFIS, with the ANFIS-SFLA outperforming the ANFIS-IWO. Among empirical models, generally the Valiantzas model in its original and calibrated versions presented the best performance. In terms of model complexity (the number of predictors), the model performance was obviously enhanced by an increasing number of predictors. The most accurate estimates of the daily ETo for the study sites were achieved via the hybrid ANFIS-SFLA models using full predictors, with RMSE within 0.15 mm day−1, RRMSE within 4%, MAE within 0.11 mm day−1, and both a high R2 and NSE of 0.99 in the test phase at the two studied sites. Full article
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Article
Block-Greedy and CNN Based Underwater Image Dehazing for Novel Depth Estimation and Optimal Ambient Light
Water 2021, 13(23), 3470; https://doi.org/10.3390/w13233470 - 06 Dec 2021
Cited by 14 | Viewed by 2010
Abstract
A lack of adequate consideration of underwater image enhancement gives room for more research into the field. The global background light has not been adequately addressed amid the presence of backscattering. This paper presents a technique based on pixel differences between global and [...] Read more.
A lack of adequate consideration of underwater image enhancement gives room for more research into the field. The global background light has not been adequately addressed amid the presence of backscattering. This paper presents a technique based on pixel differences between global and local patches in scene depth estimation. The pixel variance is based on green and red, green and blue, and red and blue channels besides the absolute mean intensity functions. The global background light is extracted based on a moving average of the impact of suspended light and the brightest pixels within the image color channels. We introduce the block-greedy algorithm in a novel Convolutional Neural Network (CNN) proposed to normalize different color channels’ attenuation ratios and select regions with the lowest variance. We address the discontinuity associated with underwater images by transforming both local and global pixel values. We minimize energy in the proposed CNN via a novel Markov random field to smooth edges and improve the final underwater image features. A comparison of the performance of the proposed technique against existing state-of-the-art algorithms using entropy, Underwater Color Image Quality Evaluation (UCIQE), Underwater Image Quality Measure (UIQM), Underwater Image Colorfulness Measure (UICM), and Underwater Image Sharpness Measure (UISM) indicate better performance of the proposed approach in terms of average and consistency. As it concerns to averagely, UICM has higher values in the technique than the reference methods, which explainsits higher color balance. The μ values of UCIQE, UISM, and UICM of the proposed method supersede those of the existing techniques. The proposed noted a percent improvement of 0.4%, 4.8%, 9.7%, 5.1% and 7.2% in entropy, UCIQE, UIQM, UICM and UISM respectively compared to the best existing techniques. Consequently, dehazed images have sharp, colorful, and clear features in most images when compared to those resulting from the existing state-of-the-art methods. Stable σ values explain the consistency in visual analysis in terms of sharpness of color and clarity of features in most of the proposed image results when compared with reference methods. Our own assessment shows that only weakness of the proposed technique is that it only applies to underwater images. Future research could seek to establish edge strengthening without color saturation enhancement. Full article
(This article belongs to the Special Issue AI and Deep Learning Applications for Water Management)
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Article
Characteristics of Turbulence in the Downstream Region of a Vegetation Patch
Water 2021, 13(23), 3468; https://doi.org/10.3390/w13233468 - 06 Dec 2021
Cited by 7 | Viewed by 1158
Abstract
In presence of vegetation patches in a channel bed, different flow–morphology interactions in the river will result. The investigation of the nature and intensity of these structures is a crucial part of the research works of river engineering. In this experimental study, the [...] Read more.
In presence of vegetation patches in a channel bed, different flow–morphology interactions in the river will result. The investigation of the nature and intensity of these structures is a crucial part of the research works of river engineering. In this experimental study, the characteristics of turbulence in the non-developed region downstream of a vegetation patch suffering from a gradual fade have been investigated. The changes in turbulent structure were tracked in sequential patterns by reducing the patch size. The model vegetation was selected carefully to simulate the aquatic vegetation patches in natural rivers. Velocity profile, TKE (Turbulent Kinetic Energy), turbulent power spectra and quadrant analysis have been used to investigate the behavior and intensity of the turbulent structures. The results of the velocity profile and TKE indicate that there are three different flow layers in the region downstream of the vegetation patch, including the wake layer, mixing layer and shear layer. When the vegetation patch is wide enough (Dv/Dc > 0.5, termed as the patch width ratio, where Dv is the width of a vegetation patch and Dc is the width of the channel), highly intermittent anisotropic turbulent events appear in the mixing layer at the depth of z/Hv = 0.7~1.1 and distance of x/Hv = 8~12 (where x is streamwise distance from the patch edge, z is vertical distance from channel bed and Hv is the height of a vegetation patch). The results of quadrant analysis show that these structures are associated with the dominance of the outward interactions (Q1). Moreover, these structures accompany large coherent Reynolds shear stresses, anomalies in streamwise velocity, increases in the standard deviation of TKE and increases in intermittent Turbulent Kinetic Energy (TKEi). The intensity and extents of these structures fade with the decrease in the size of a vegetation patch. On the other hand, as the size of the vegetation patch decreases, von Karman vortexes appear in the wake layer and form the dominant flow structures in the downstream region of a vegetation patch. Full article
(This article belongs to the Special Issue Sediment Transport, Local Scour, and Fluvial Hydraulics)
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Article
Quantile-Based Hydrological Modelling
Water 2021, 13(23), 3420; https://doi.org/10.3390/w13233420 - 03 Dec 2021
Cited by 9 | Viewed by 2011
Abstract
Predictive uncertainty in hydrological modelling is quantified by using post-processing or Bayesian-based methods. The former methods are not straightforward and the latter ones are not distribution-free (i.e., assumptions on the probability distribution of the hydrological model’s output are necessary). To alleviate possible limitations [...] Read more.
Predictive uncertainty in hydrological modelling is quantified by using post-processing or Bayesian-based methods. The former methods are not straightforward and the latter ones are not distribution-free (i.e., assumptions on the probability distribution of the hydrological model’s output are necessary). To alleviate possible limitations related to these specific attributes, in this work we propose the calibration of the hydrological model by using the quantile loss function. By following this methodological approach, one can directly simulate pre-specified quantiles of the predictive distribution of streamflow. As a proof of concept, we apply our method in the frameworks of three hydrological models to 511 river basins in the contiguous US. We illustrate the predictive quantiles and show how an honest assessment of the predictive performance of the hydrological models can be made by using proper scoring rules. We believe that our method can help towards advancing the field of hydrological uncertainty. Full article
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Article
Development of a Deep Learning Emulator for a Distributed Groundwater–Surface Water Model: ParFlow-ML
Water 2021, 13(23), 3393; https://doi.org/10.3390/w13233393 - 01 Dec 2021
Cited by 11 | Viewed by 2629
Abstract
Integrated hydrologic models solve coupled mathematical equations that represent natural processes, including groundwater, unsaturated, and overland flow. However, these models are computationally expensive. It has been recently shown that machine leaning (ML) and deep learning (DL) in particular could be used to emulate [...] Read more.
Integrated hydrologic models solve coupled mathematical equations that represent natural processes, including groundwater, unsaturated, and overland flow. However, these models are computationally expensive. It has been recently shown that machine leaning (ML) and deep learning (DL) in particular could be used to emulate complex physical processes in the earth system. In this study, we demonstrate how a DL model can emulate transient, three-dimensional integrated hydrologic model simulations at a fraction of the computational expense. This emulator is based on a DL model previously used for modeling video dynamics, PredRNN. The emulator is trained based on physical parameters used in the original model, inputs such as hydraulic conductivity and topography, and produces spatially distributed outputs (e.g., pressure head) from which quantities such as streamflow and water table depth can be calculated. Simulation results from the emulator and ParFlow agree well with average relative biases of 0.070, 0.092, and 0.032 for streamflow, water table depth, and total water storage, respectively. Moreover, the emulator is up to 42 times faster than ParFlow. Given this promising proof of concept, our results open the door to future applications of full hydrologic model emulation, particularly at larger scales. Full article
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Article
Improving Drought Modeling Using Hybrid Random Vector Functional Link Methods
Water 2021, 13(23), 3379; https://doi.org/10.3390/w13233379 - 01 Dec 2021
Cited by 11 | Viewed by 1838
Abstract
Drought modeling is essential in water resources planning and management in mitigating its effects, especially in arid regions. Climate change highly influences the frequency and intensity of droughts. In this study, new hybrid methods, the random vector functional link (RVFL) integrated with particle [...] Read more.
Drought modeling is essential in water resources planning and management in mitigating its effects, especially in arid regions. Climate change highly influences the frequency and intensity of droughts. In this study, new hybrid methods, the random vector functional link (RVFL) integrated with particle swarm optimization (PSO), the genetic algorithm (GA), the grey wolf optimization (GWO), the social spider optimization (SSO), the salp swarm algorithm (SSA) and the hunger games search algorithm (HGS) were used to forecast droughts based on the standard precipitation index (SPI). Monthly precipitation data from three stations in Bangladesh were used in the applications. The accuracy of the methods was compared by forecasting four SPI indices, SPI3, SPI6, SPI9, and SPI12, using the root mean square errors (RMSE), the mean absolute error (MAE), the Nash–Sutcliffe efficiency (NSE), and the determination coefficient (R2). The HGS algorithm provided a better performance than the alternative algorithms, and it considerably improved the accuracy of the RVFL method in drought forecasting; the improvement in RMSE for the SPI3, SP6, SPI9, and SPI12 was by 6.14%, 11.89%, 14.14%, 24.5% in station 1, by 6.02%, 17.42%, 13.49%, 24.86% in station 2 and by 7.55%, 26.45%, 15.27%, 13.21% in station 3, respectively. The outcomes of the study recommend the use of a HGS-based RVFL in drought modeling. Full article
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Article
Citizen Science for Marine Litter Detection and Classification on Unmanned Aerial Vehicle Images
Water 2021, 13(23), 3349; https://doi.org/10.3390/w13233349 - 25 Nov 2021
Cited by 15 | Viewed by 3336
Abstract
Unmanned aerial vehicles (UAV, aka drones) are being used for mapping macro-litter in the environment. As drone images require a manual processing task for detecting marine litter, it is of interest to evaluate the accuracy of non-expert citizen science operators (CSO) in performing [...] Read more.
Unmanned aerial vehicles (UAV, aka drones) are being used for mapping macro-litter in the environment. As drone images require a manual processing task for detecting marine litter, it is of interest to evaluate the accuracy of non-expert citizen science operators (CSO) in performing this task. Students from Italian secondary schools (in this work, the CSO) were invited to identify, mark, and classify stranded litter items on a UAV orthophoto collected on an Italian beach. A specific training program and working tools were developed for the aim. The comparison with the standard in situ visual census survey returned a general underestimation (50%) of items. However, marine litter bulk categorisation was fairly in agreement with the in situ survey, especially for sources classification. The concordance level among CSO ranged between 60% and 91%, depending on the item properties considered (type, material, and colour). As the assessment accuracy was in line with previous works developed by experts, remote detection of marine litter on UAV images can be improved through citizen science programs, upon an appropriate training plan and provision of specific tools. Full article
(This article belongs to the Special Issue Pattern Analysis, Recognition and Classification of Marine Data)
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Antibiotic Resistance Genes and Potentially Pathogenic Bacteria in the Central Adriatic Sea: Are They Connected to Urban Wastewater Inputs?
Water 2021, 13(23), 3335; https://doi.org/10.3390/w13233335 - 24 Nov 2021
Cited by 9 | Viewed by 1705
Abstract
Despite last decades’ interventions within local and communitarian programs, the Mediterranean Sea still receives poorly treated urban wastewater (sewage). Wastewater treatment plants (WWTPs) performing primary sewage treatments have poor efficiency in removing microbial pollutants, including fecal indicator bacteria, pathogens, and mobile genetic elements [...] Read more.
Despite last decades’ interventions within local and communitarian programs, the Mediterranean Sea still receives poorly treated urban wastewater (sewage). Wastewater treatment plants (WWTPs) performing primary sewage treatments have poor efficiency in removing microbial pollutants, including fecal indicator bacteria, pathogens, and mobile genetic elements conferring resistance to antimicrobials. Using a combination of molecular tools, we investigated four urban WWTPs (i.e., two performing only mechanical treatments and two performing a subsequent conventional secondary treatment by activated sludge) as continuous sources of microbial pollution for marine coastal waters. Sewage that underwent only primary treatments was characterized by a higher content of traditional and alternative fecal indicator bacteria, as well as potentially pathogenic bacteria (especially Acinetobacter, Coxiella, Prevotella, Streptococcus, Pseudomonas, Vibrio, Empedobacter, Paracoccus, and Leptotrichia), than those subjected to secondary treatment. However, seawater samples collected next to the discharging points of all the WWTPs investigated here revealed a marked fecal signature, despite significantly lower values in the presence of secondary treatment of the sewage. WWTPs in this study represented continuous sources of antibiotic resistance genes (ARGs) ermB, qnrS, sul2, tetA, and blaTEM (the latter only for three WWTPs out of four). Still, no clear effects of the two depuration strategies investigated here were detected. Some marine samples were identified as positive to the colistin-resistance gene mcr-1, an ARG that threatens colistin antibiotics’ clinical utility in treating infections with multidrug-resistant bacteria. This study provides evidence that the use of sole primary treatments in urban wastewater management results in pronounced inputs of microbial pollution into marine coastal waters. At the same time, the use of conventional treatments does not fully eliminate ARGs in treated wastewater. The complementary use of molecular techniques could successfully improve the evaluation of the depuration efficiency and help develop novel solutions for the treatment of urban wastewater. Full article
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Article
Management of Urban Waters with Nature-Based Solutions in Circular Cities—Exemplified through Seven Urban Circularity Challenges
Water 2021, 13(23), 3334; https://doi.org/10.3390/w13233334 - 24 Nov 2021
Cited by 17 | Viewed by 4385
Abstract
Nature-Based Solutions (NBS) have been proven to effectively mitigate and solve resource depletion and climate-related challenges in urban areas. The COST (Cooperation in Science and Technology) Action CA17133 entitled “Implementing nature-based solutions (NBS) for building a resourceful circular city” has established seven urban [...] Read more.
Nature-Based Solutions (NBS) have been proven to effectively mitigate and solve resource depletion and climate-related challenges in urban areas. The COST (Cooperation in Science and Technology) Action CA17133 entitled “Implementing nature-based solutions (NBS) for building a resourceful circular city” has established seven urban circularity challenges (UCC) that can be addressed effectively with NBS. This paper presents the outcomes of five elucidation workshops with more than 20 European experts from different backgrounds. These international workshops were used to examine the effectiveness of NBS to address UCC and foster NBS implementation towards circular urban water management. A major outcome was the identification of the two most relevant challenges for water resources in urban areas: ‘Restoring and maintaining the water cycle’ (UCC1) and ‘Water and waste treatment, recovery, and reuse’ (UCC2). s Moreover, significant synergies with ‘Nutrient recovery and reuse’, ‘Material recovery and reuse’, ‘Food and biomass production’, ‘Energy efficiency and recovery’, and ‘Building system recovery’ were identified. Additionally, the paper presents real-life case studies to demonstrate how different NBS and supporting units can contribute to the UCC. Finally, a case-based semi-quantitative assessment of the presented NBS was performed. Most notably, this paper identifies the most typically employed NBS that enable processes for UCC1 and UCC2. While current consensus is well established by experts in individual NBS, we presently highlight the potential to address UCC by combining different NBS and synergize enabling processes. This study presents a new paradigm and aims to enhance awareness on the ability of NBS to solve multiple urban circularity issues. Full article
(This article belongs to the Special Issue Water and Circular Cities)
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Article
Health Risk of the Shallow Groundwater and Its Suitability for Drinking Purpose in Tongchuan, China
Water 2021, 13(22), 3256; https://doi.org/10.3390/w13223256 - 17 Nov 2021
Cited by 25 | Viewed by 1754
Abstract
Studying the quality and health risks of groundwater is of great significance for sustainable water resources utilization, especially in arid and semi-arid areas around the world. The current study is carried out to evaluate the quality and potential health risks of groundwater in [...] Read more.
Studying the quality and health risks of groundwater is of great significance for sustainable water resources utilization, especially in arid and semi-arid areas around the world. The current study is carried out to evaluate the quality and potential health risks of groundwater in the Tongchuan area on the Loess Plateau, northwest China. Water quality index (WQI) and hydrochemical correlation analysis were implemented to understand the status of groundwater quality. Daily average exposure dosages through the oral and dermal contact exposure pathways were taken into consideration to calculate the health risks to the human body. Additionally, graphical approaches such as Piper diagram, Durov diagram and GIS mapping were used to help better understand the results of this study. The WQI approach showed that 77.1% of the samples were of excellent quality. The most significant parameters affecting water quality were NO3, F, and Cr6+. The health risk assessment results showed that 27.1% and 54.2% of the samples lead to non-carcinogenic risks through oral intake for adults and children, respectively. In contrast, 12.5% of the groundwater samples would result in carcinogenic risks to the residents. This study showed that the WQI method needs to be supplemented by a health risk evaluation to obtain comprehensive results for groundwater quality protection and management in the Tongchuan area. Full article
(This article belongs to the Special Issue Groundwater Quality and Public Health)
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Article
Multi-Actor Platforms in the Water–Agriculture Nexus: Synergies and Long-Term Meaningful Engagement
Water 2021, 13(22), 3204; https://doi.org/10.3390/w13223204 - 12 Nov 2021
Cited by 7 | Viewed by 1918
Abstract
Solutions to current complex environmental challenges demand the consultation and involvement of various groups in society. In light of the WFD’s requirements of public participation, this paper presents an analysis of the establishment and development of nine different multi-actor platforms (MAPs) across Europe [...] Read more.
Solutions to current complex environmental challenges demand the consultation and involvement of various groups in society. In light of the WFD’s requirements of public participation, this paper presents an analysis of the establishment and development of nine different multi-actor platforms (MAPs) across Europe set up as arenas for long-term engagements to solve water quality challenges in relation to agriculture. The MAPs represent different histories and legacies of engagement; some are recent initiatives and some are affiliated with previous government-initiated projects, while other MAPs are long-term engagement platforms. A case study approach drawing on insights from the nine engagement processes is used to discuss conditions for enabling long-term multi-actor engagement. The perceived pressure for change and preferred prioritization in complying with mitigating water quality problems vary within and among the MAPs. The results show that governmental and local actors’ concern for water quality improvements and focusing on pressure for change are important for establishing meaningful multi-actor engagement when concerns translate into a clear mandate of the MAP. Furthermore, the degree to which the MAPs have been able to establish relationships and networks with other institutions such as water companies, agricultural and environmental authorities, farmers, and civil society organizations influences possibilities for long-term meaningful engagement. Full article
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Article
Comparison of Desalination Technologies Using Renewable Energy Sources with Life Cycle, PESTLE, and Multi-Criteria Decision Analyses
Water 2021, 13(21), 3023; https://doi.org/10.3390/w13213023 - 28 Oct 2021
Cited by 20 | Viewed by 5453
Abstract
Nowadays, desalination continues to expand globally, which is one of the most effective solutions to solve the problem of the global drinking water shortage. However, desalination is not a fail-safe process and has many environmental and human health consequences. This paper investigated the [...] Read more.
Nowadays, desalination continues to expand globally, which is one of the most effective solutions to solve the problem of the global drinking water shortage. However, desalination is not a fail-safe process and has many environmental and human health consequences. This paper investigated the desalination procedure of seawater with different technologies, namely, multi-stage flash distillation (MSF), multi-effect distillation (MED), and reverse osmosis (RO), and with various energy sources (fossil energy, solar energy, wind energy, nuclear energy). The aim was to examine the different desalination technologies’ effectiveness with energy sources using three assessment methods, which were examined separately. The life cycle assessment (LCA), PESTLE, and multi-criteria decision analysis (MCDA) methods were used to evaluate each procedure. LCA was based on the following impact analysis and evaluation methods: ReCiPe 2016, IMPACT 2002+, and IPCC 2013 GWP 100a; PESTLE risk analysis evaluated the long-lasting impact on processes and technologies with political, economic, social, technological, legal, and environmental factors. Additionally, MCDA was based on the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method to evaluate desalination technologies. This study considered the operational phase of a plant, which includes the necessary energy and chemical needs, which is called “gate-to-gate” analysis. Saudi Arabia data were used for the analysis, with the base unit of 1 m3 of the water product. As the result of this study, RO combined with renewable energy provided outstanding benefits in terms of human health, ecosystem quality, and resources, as well as the climate change and emissions of GHGs categories. Full article
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Article
Here Comes the Flood, but Not Failure? Lessons to Learn after the Heavy Rain and Pluvial Floods in Germany 2021
Water 2021, 13(21), 3016; https://doi.org/10.3390/w13213016 - 27 Oct 2021
Cited by 36 | Viewed by 6311
Abstract
Floods are a known natural hazard in Germany, but the amount of precipitation and ensuing high death toll and damages after the events especially from 14 to 15 July 2021 came as a surprise. Almost immediately questions about failure in the early warning [...] Read more.
Floods are a known natural hazard in Germany, but the amount of precipitation and ensuing high death toll and damages after the events especially from 14 to 15 July 2021 came as a surprise. Almost immediately questions about failure in the early warning chains and the effectiveness of the German response emerged, also internationally. This article presents lessons to learn and argues against a blame culture. The findings are based on comparisons with findings from previous research projects carried out in the Rhein-Erft Kreis and the city of Cologne, as well as on discussions with operational relief forces after the 2021 events. The main disaster aspects of the 2021 flood are related to issuing and understanding warnings, a lack of information and data exchange, unfolding upon a situation of an ongoing pandemic and aggravated further by critical infrastructure failure. Increasing frequencies of flash floods and other extremes due to climate change are just one side of the transformation and challenge, Germany and neighbouring countries are facing. The vulnerability paradox also heavily contributes to it; German society became increasingly vulnerable to failure due to an increased dependency on its infrastructure and emergency system, and the ensuing expectations of the public for a perfect system. Full article
(This article belongs to the Special Issue Smart Water Management and Flood Mitigation)
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Article
Genome Sequencing of SARS-CoV-2 Allows Monitoring of Variants of Concern through Wastewater
Water 2021, 13(21), 3018; https://doi.org/10.3390/w13213018 - 27 Oct 2021
Cited by 7 | Viewed by 2771
Abstract
Monitoring SARS-CoV-2 in wastewater has shown to be an effective tool for epidemiological surveillance. More specifically, RNA levels determined with RT-qPCR have been shown to track with the infection dynamics within the population. However, the surveillance of individual lineages circulating in the population [...] Read more.
Monitoring SARS-CoV-2 in wastewater has shown to be an effective tool for epidemiological surveillance. More specifically, RNA levels determined with RT-qPCR have been shown to track with the infection dynamics within the population. However, the surveillance of individual lineages circulating in the population based on genomic sequencing of wastewater samples is challenging, as the genetic material constitutes a mixture of different viral haplotypes. Here, we identify specific signature mutations from individual SARS-CoV-2 lineages in wastewater samples to estimate lineages circulating in Luxembourg. We compare circulating lineages and mutations to those detected in clinical samples amongst infected individuals. We show that especially for dominant lineages, the allele frequencies of signature mutations correspond to the occurrence of particular lineages in the population. In addition, we provide evidence that regional clusters can also be discerned. We focused on the time period between November 2020 and March 2021 in which several variants of concern emerged and specifically traced the lineage B.1.1.7, which became dominant in Luxembourg during that time. During the subsequent time points, we were able to reconstruct short haplotypes, highlighting the co-occurrence of several signature mutations. Our results highlight the potential of genomic surveillance in wastewater samples based on amplicon short-read data. By extension, our work provides the basis for the early detection of novel SARS-CoV-2 variants. Full article
(This article belongs to the Special Issue SARS-CoV-2 in Wastewater: Methods, Epidemiology and Future Goals)
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Article
Biodegradation of Brown 706 Dye by Bacterial Strain Pseudomonas aeruginosa
Water 2021, 13(21), 2959; https://doi.org/10.3390/w13212959 - 20 Oct 2021
Cited by 11 | Viewed by 1232
Abstract
Dyes are the most challenging pollutants for the aquatic environment that are not only toxic, but also interfering photosynthesis as light penetration into deep water is changed. A number of methods are used for the water reclamation, however, among them biological methods are [...] Read more.
Dyes are the most challenging pollutants for the aquatic environment that are not only toxic, but also interfering photosynthesis as light penetration into deep water is changed. A number of methods are used for the water reclamation, however, among them biological methods are preferably used due to their compatibility with nature. In the present research, 15 different bacterial strains were used to decolorize Brown 706 dye. Among the bacterial strains, Pseudomonas aeruginosa showed maximum decolorization activity; hence in the subsequent experiments Pseudomonas aeruginosa was used. First the decolorization activities were carried out under different physicochemical conditions to obtain the optimum decolorization benefits of the selected microorganism. The optimum conditions established were 37°C, pH of 7 and operation cycle time 72 h. In the subsequent experiment all optimum conditions were combined in a single experiment where 73.91% of decolorization efficiency was achieved. For the evaluation of metabolites formed after decolorization/degradation the aliquots containing bacteria were homogenized, filtered and then subjected to extraction. The extracted metabolites were then subjected to the silica gel column isolation. UV–Vis, FTIR, and NMR techniques were used to elucidate structures of the metabolites. Out of the collected metabolites only P-xylene was identified, which has been formed by cleavage of azo linkage by azo reductase enzyme of bacteria following the deamination and methylation of nitro substituted benzene ring. Full article
(This article belongs to the Special Issue Water Treatment by Adsorption and Catalytic Methods)
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Article
Hyper-Nutrient Enrichment Status in the Sabalan Lake, Iran
Water 2021, 13(20), 2874; https://doi.org/10.3390/w13202874 - 14 Oct 2021
Cited by 14 | Viewed by 1634
Abstract
Lakes/reservoirs are rapidly deteriorating from cultural eutrophication due to anthropogenic factors. In this study, we aimed to (1) explore nutrient levels in the Sabalan dam reservoir (SDR) of northwest Iran, (2) determine the reservoir water fertility using the total phosphorus (TP) based and [...] Read more.
Lakes/reservoirs are rapidly deteriorating from cultural eutrophication due to anthropogenic factors. In this study, we aimed to (1) explore nutrient levels in the Sabalan dam reservoir (SDR) of northwest Iran, (2) determine the reservoir water fertility using the total phosphorus (TP) based and total nitrogen (TN) based Carlson trophic state indices, and (3) specify primary limiting factors for the reservoir eutrophication. Our field observations showed a state of hyper-nutrient enrichment in the SDR. The highest variation of TN in the reservoir water column happened when the reservoir was severely stratified (in August) while the highest variation of TP took place when the thermocline was attenuated with the deepening of the epilimnion (in October). Both TP and TN based trophic indicators classified the SDR as a hypereutrophic lake. TN:TP molar ratio averaged at the epilimnion indicated a P–deficiency in the reservoir during warm months whilst it suggested a co–deficiency of P and N in cold months. Given the hyper-nutrient enrichment state in the reservoir, other drivers such as water residence time (WRT) can also act as the main contributor of eutrophication in the SDR. We found that WRT in the SDR varied from hundreds to thousands of days, which was much longer than that of other reservoirs/lakes with the same and even much greater storage capacity. Therefore, both hyper-nutrient enrichment and WRT mainly controlled eutrophication in the reservoir. Given time consuming and expensive management practices for reducing nutrients in the watershed, changes in the SDR operation are suggested to somewhat recover its hypereutrophic state in the short-term. However, strategic long-term recovery plans are required to reduce the transition of nutrients from the watershed to the SDR. Full article
(This article belongs to the Special Issue Water Quality Management of Inland Waters)
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Article
A Comparison of BPNN, GMDH, and ARIMA for Monthly Rainfall Forecasting Based on Wavelet Packet Decomposition
Water 2021, 13(20), 2871; https://doi.org/10.3390/w13202871 - 14 Oct 2021
Cited by 13 | Viewed by 1154
Abstract
Accurate rainfall forecasting in watersheds is of indispensable importance for predicting streamflow and flash floods. This paper investigates the accuracy of several forecasting technologies based on Wavelet Packet Decomposition (WPD) in monthly rainfall forecasting. First, WPD decomposes the observed monthly rainfall data into [...] Read more.
Accurate rainfall forecasting in watersheds is of indispensable importance for predicting streamflow and flash floods. This paper investigates the accuracy of several forecasting technologies based on Wavelet Packet Decomposition (WPD) in monthly rainfall forecasting. First, WPD decomposes the observed monthly rainfall data into several subcomponents. Then, three data-based models, namely Back-propagation Neural Network (BPNN) model, group method of data handing (GMDH) model, and autoregressive integrated moving average (ARIMA) model, are utilized to complete the prediction of the decomposed monthly rainfall series, respectively. Finally, the ensemble prediction result of the model is formulated by summing the outputs of all submodules. Meanwhile, these six models are employed for benchmark comparison to study the prediction performance of these conjunction methods, which are BPNN, WPD-BPNN, GMDH, WPD-GMDH, ARIMA, and WPD-ARIMA models. The paper takes monthly data from Luoning and Zuoyu stations in Luoyang city of China as the case study. The performance of these conjunction methods is tested by four quantitative indexes. Results show that WPD can efficiently improve the forecasting accuracy and the proposed WPD-BPNN model can achieve better prediction results. It is concluded that the hybrid forecast model is a very efficient tool to improve the accuracy of mid- and long-term rainfall forecasting. Full article
(This article belongs to the Special Issue Climate Changes and Hydrological Processes)
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Article
Inland Reservoir Water Quality Inversion and Eutrophication Evaluation Using BP Neural Network and Remote Sensing Imagery: A Case Study of Dashahe Reservoir
Water 2021, 13(20), 2844; https://doi.org/10.3390/w13202844 - 12 Oct 2021
Cited by 10 | Viewed by 1553
Abstract
In this study, an inland reservoir water quality parameters’ inversion model was developed using a back propagation (BP) neural network to conduct reservoir eutrophication evaluation, according to multi-temporal remote sensing images and field observations. The inversion model based on the BP neural network [...] Read more.
In this study, an inland reservoir water quality parameters’ inversion model was developed using a back propagation (BP) neural network to conduct reservoir eutrophication evaluation, according to multi-temporal remote sensing images and field observations. The inversion model based on the BP neural network (the BP inversion model) was applied to a large inland reservoir in Jiangmen city, South China, according to the field observations of five water quality parameters, namely, Chlorophyl-a (Chl-a), Secchi Depth (SD), total phosphorus (TP), total nitrogen (TN), and Permanganate of Chemical Oxygen Demand (CODMn), and twelve periods of Landsat8 satellite remote sensing images. The reservoir eutrophication was evaluated. The accuracy of the BP inversion model for each water parameter was compared with that of the linear inversion model, and the BP inversion models of two parameters (i.e., Chl-a and CODMn) with larger fluctuation range were superior to the two multiple linear inversion models due to the ability of improving the generalization of the BP neural network. The Dashahe Reservoir was basically in the state of mesotrophication and light eutrophication. The area of light eutrophication accounted for larger proportions in spring and autumn, and the reservoir inflow was the main source of nutrient salts. Full article
(This article belongs to the Special Issue Urban Water Security and Sustainable Development)
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Article
Combined Electro-Fenton and Anodic Oxidation Processes at a Sub-Stoichiometric Titanium Oxide (Ti4O7) Ceramic Electrode for the Degradation of Tetracycline in Water
Water 2021, 13(19), 2772; https://doi.org/10.3390/w13192772 - 06 Oct 2021
Cited by 13 | Viewed by 1793
Abstract
The mineralization of tetracycline by electrochemical advanced oxidation processes (EAOPs) as well as the study of the toxicity of its intermediates and degradation products are presented. Electro-Fenton (EF), anodic oxidation (AO), and electro-Fenton coupled with anodic oxidation (EF/AO) were used to degrade tetracycline [...] Read more.
The mineralization of tetracycline by electrochemical advanced oxidation processes (EAOPs) as well as the study of the toxicity of its intermediates and degradation products are presented. Electro-Fenton (EF), anodic oxidation (AO), and electro-Fenton coupled with anodic oxidation (EF/AO) were used to degrade tetracycline on carbon felt (cathode) and a sub-stoichiometric titanium oxide (Ti4O7) layer deposited on Ti (anode). As compared to EF and AO, the coupled EF/AO system resulted in the highest pollutant removal efficiencies: total organic carbon removal was 69 ± 1% and 68 ± 1%, at 20 ppm and 50 ppm of initial concentration of tetracycline, respectively. The effect of electrolysis current on removal efficiency, mineralization current efficiency, energy consumption, and solution toxicity of tetracycline mineralization were investigated for 20 ppm and 50 ppm tetracycline. The EF/AO process using a Ti4O7 anode and CF cathode provides low energy and high removal efficiency of tetracycline caused by the production of hydroxyl radicals both at the surface of the non-active Ti4O7 electrode and in solution by the electro-Fenton process at the cathodic carbon felt. Complete removal of tetracycline was observed from HPLC data after 30 min at optimized conditions of 120 mA and 210 mA for 20 ppm and 50 ppm tetracycline concentrations. Degradation products were elucidated, and the toxicity of the products were measured with luminescence using Microtox® bacteria toxicity test. Full article
(This article belongs to the Special Issue Application of Electrochemistry in Wastewater Treatment)
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Article
Living with Urban Flooding: A Continuous Learning Process for Local Municipalities and Lessons Learnt from the 2021 Events in Germany
Water 2021, 13(19), 2769; https://doi.org/10.3390/w13192769 - 06 Oct 2021
Cited by 8 | Viewed by 2899
Abstract
In 2021, heavy precipitation events in Germany have confirmed once again that pluvial flooding can cause catastrophic damage in large, medium, and small cities. However, despite several hazard-oriented strategies already in place, to date there is still a lack of integrated approaches to [...] Read more.
In 2021, heavy precipitation events in Germany have confirmed once again that pluvial flooding can cause catastrophic damage in large, medium, and small cities. However, despite several hazard-oriented strategies already in place, to date there is still a lack of integrated approaches to actually preventing negative consequences induced by heavy rainfall events. Furthermore, municipalities across the world are still learning from recent episodes and there is a general need to explore new techniques and guidelines that could help to reduce vulnerability, and enhance the resilience, adaptive capacity, and sustainability of urban environments, considering the already predicted future challenges associated with climate variability. To address this gap, this paper presents the outcomes of the research project “Heavy Rainfall Checklist for Sewer Operation” which was conducted by IKT Institute for Underground Infrastructure, to involve all the stakeholders affected by pluvial flooding within cities, and implement a series of documents that can be adopted by municipalities across the world to support organizations and their operational staff in preventing problems caused by heavy rainfall incidents. More in detail, three different rainfall scenarios have been deeply analysed, and for each of them a list of specific tasks and suggestions has been provided for aiding decision-making. Full article
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Article
Deep Learning Based Filtering Algorithm for Noise Removal in Underwater Images
Water 2021, 13(19), 2742; https://doi.org/10.3390/w13192742 - 02 Oct 2021
Cited by 6 | Viewed by 2474
Abstract
Under-water sensing and image processing play major roles in oceanic scientific studies. One of the related challenges is that the absorption and scattering of light in underwater settings degrades the quality of the imaging. The major drawbacks of underwater imaging are color distortion, [...] Read more.
Under-water sensing and image processing play major roles in oceanic scientific studies. One of the related challenges is that the absorption and scattering of light in underwater settings degrades the quality of the imaging. The major drawbacks of underwater imaging are color distortion, low contrast, and loss of detail (especially edge information). The paper proposes a method to address these issues by de-noising and increasing the resolution of the image using a model network trained on similar data. The network extracts frames from a video and filters them with a trigonometric–Gaussian filter to eliminate the noise in the image. It then applies contrast limited adaptive histogram equalization (CLAHE) to improvise the image contrast, and finally enhances the image resolution. Experimental results show that the proposed method could effectively produce enhanced images from degraded underwater images. Full article
(This article belongs to the Special Issue AI and Deep Learning Applications for Water Management)
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Article
Abundance and Temporal Distribution of Beach Litter on the Coast of Ceuta (North Africa, Gibraltar Strait)
Water 2021, 13(19), 2739; https://doi.org/10.3390/w13192739 - 02 Oct 2021
Cited by 9 | Viewed by 1925
Abstract
Twelve beaches located in Ceuta (Spain) were studied from February to April 2019 to assess litter amounts (expressed as number of items), categories and temporal distribution. At each beach, three surveys were conducted, i.e., one per month (i.e., 36 in total). Selected beaches [...] Read more.
Twelve beaches located in Ceuta (Spain) were studied from February to April 2019 to assess litter amounts (expressed as number of items), categories and temporal distribution. At each beach, three surveys were conducted, i.e., one per month (i.e., 36 in total). Selected beaches covered urban (7), rural (2) and remote (3) bathing areas. Plastic represented the dominant material, i.e., 35.2% of all debris, followed by glass (18.2%), pottery/ceramics (14.6%), wood (11.4%), metal (11.4%), paper/cardboard (4.8%), cloth (3.5%), rubber (0.7%), organic (0.3%) and other materials (0.1%). The Clean Coast Index was calculated to classify beaches in five categories for evaluating the cleanliness level of the coast observed at each survey: “Very Clean” (7 surveys), “Clean” (10), “Moderately Dirty” (8), “Dirty” (2) and “Extremely Dirty” (9). Litter occurrence was assessed by the Litter Grade methodology, which allowed to classify beaches in four grades: “A”: very good (0); “B”: good (4); “C”: fair (7); and “D”: poor (25). In a few surveys, some beaches were considered “good”, but their management should not be ignored because in other surveys those beaches reached fair and poor scores. Several potentially harmful litter items were related to beach users. Severe eastern storms removed litter at many of the beaches investigated and favored accumulation at others. Data analysis shows significant differences in litter abundance with respect to site, beach typology and the presence of cleaning operations but no important differences between the studied months. Rural beaches recorded the most litter, followed by urban and remote beaches. All beaches require immediate and more appropriate management actions to improve their environmental status. Full article
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Article
Natural and Anthropogenic Controls of Groundwater Quality in Sri Lanka: Implications for Chronic Kidney Disease of Unknown Etiology (CKDu)
Water 2021, 13(19), 2724; https://doi.org/10.3390/w13192724 - 01 Oct 2021
Cited by 7 | Viewed by 1485
Abstract
Poor groundwater quality in household wells is hypothesized as being a potential contributor to chronic kidney disease of unknown etiology (CKDu) in Sri Lanka. However, the influencing factors of groundwater quality in Sri Lanka are rarely investigated at a national scale. Here, the [...] Read more.
Poor groundwater quality in household wells is hypothesized as being a potential contributor to chronic kidney disease of unknown etiology (CKDu) in Sri Lanka. However, the influencing factors of groundwater quality in Sri Lanka are rarely investigated at a national scale. Here, the spatial characteristics of groundwater geochemistry in Sri Lanka were described. The relationships of groundwater quality parameters with environmental factors, including lithology, land use, and climatic conditions, were further examined to identify the natural and anthropogenic controlling factors of groundwater quality in Sri Lanka. The results showed that groundwater geochemistry in Sri Lanka exhibited significant spatial heterogeneity. The high concentrations of NO3 were found in the districts that have a higher percentage of agricultural lands, especially in the regions in the coastal zone. Higher hardness and fluoride in groundwater were mainly observed in the dry zone. The concentrations of trace elements such as Cd, Pb, Cu, and Cr of all the samples were lower than the World Health Organization guideline values, while some the samples had higher As and Al concentrations above the guideline values. Principal component analysis identified four components that explained 73.2% of the total data variance, and the first component with high loadings of NO3, hardness, As, and Cr suggested the effects of agricultural activities, while other components were primarily attributed to natural sources and processes. Further analyses found that water hardness, fluoride and As concentration had positive correlations with precipitation and negative correlations with air temperature. The concentration of NO3 and water hardness were positively correlated with agricultural lands, while As concentration was positively correlated with unconsolidated sediments. The environmental factors can account for 58% of the spatial variation in the overall groundwater geochemistry indicated by the results of redundancy analysis. The groundwater quality data in this study cannot identify whether groundwater quality is related to the occurrence of CKDu. However, these findings identify the coupled controls of lithology, land use, and climate on groundwater quality in Sri Lanka. Future research should be effectively designed to clarify the synergistic effect of different chemical constituents on CKDu. Full article
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Article
Economic and Sustainability Inequalities and Water Consumption of European Union Countries
Water 2021, 13(19), 2696; https://doi.org/10.3390/w13192696 - 29 Sep 2021
Cited by 4 | Viewed by 3677
Abstract
Water scarcity is becoming a global concern for many reasons as its consumption increases. This research aimed to analyze sustainability inequalities in the water consumption of EU countries. Descriptive statistics using data for four AQUASTAT periods (2002, 2007, 2012, and 2017), and quotients [...] Read more.
Water scarcity is becoming a global concern for many reasons as its consumption increases. This research aimed to analyze sustainability inequalities in the water consumption of EU countries. Descriptive statistics using data for four AQUASTAT periods (2002, 2007, 2012, and 2017), and quotients for the AQUASTAT 2017 period, were calculated using a proposed econometric model. The main results were that countries with high GPD and population showed high water stress and total water withdrawal. Countries with lower industry-value-added-to-GDP quotients were among those with higher industrial water use efficiency, while low water-services-use-efficiency quotients were associated with high services value added to GDP. Suggestions for policymakers are provided and formula application guidelines for regional-level comparisons are described. Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
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Article
Temporal Influences of Vegetation Cover (C) Dynamism on MUSLE Sediment Yield Estimates: NDVI Evaluation
Water 2021, 13(19), 2707; https://doi.org/10.3390/w13192707 - 29 Sep 2021
Cited by 1 | Viewed by 3763
Abstract
Vegetation cover is an important factor controlling erosion and sediment yield. Therefore, its effect is accounted for in both experimental and modelling studies of erosion and sediment yield. Numerous studies have been conducted to account for the effects of vegetation cover on erosion [...] Read more.
Vegetation cover is an important factor controlling erosion and sediment yield. Therefore, its effect is accounted for in both experimental and modelling studies of erosion and sediment yield. Numerous studies have been conducted to account for the effects of vegetation cover on erosion across spatial scales; however, little has been conducted across temporal scales. This study investigates changes in vegetation cover across multiple temporal scales in Eastern Cape, South Africa and how this affects erosion and sediment yield modelling in the Tsitsa River catchment. Earth observation analysis and sediment yield modelling are integrated within this study. Landsat 8 imagery was processed, and Normalised Difference Vegetation Index (NDVI) values were extracted and applied to parameterise the Modified Universal Soil Loss Equation (MUSLE) vegetation (C) factor. Imagery data from 2013–2018 were analysed for an inter-annual trend based on reference summer (March) images, while monthly imagery for the years 2016–2017 was analysed for intra-annual trends. The results indicate that the C exhibits more variation across the monthly timescale than the yearly timescale. Therefore, using a single month to represent the annual C factor increases uncertainty. The modelling shows that accounting for temporal variations in vegetation cover reduces cumulative simulated sediment by up to 85% across the inter-annual and 30% for the intra-annual scale. Validation with observed data confirmed that accounting for temporal variations brought cumulative sediment outputs closer to observations. Over-simulations are high in late autumn and early summer, when estimated C values are high. Accordingly, uncertainties are high in winter when low NDVI leads to high C, whereas dry organic matter provides some protection from erosion. The results of this study highlight the need to account for temporal variations in vegetation cover in sediment yield estimation but indicate the uncertainties associated with using NDVI to estimate C factor. Full article
(This article belongs to the Special Issue Modelling of Soil Conservation, Soil Erosion and Sediment Transport)
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Article
Modelling the Influence from Biota and Organic Matter on the Transport Dynamics of Microplastics in the Water Column and Bottom Sediments in the Oslo Fjord
Water 2021, 13(19), 2690; https://doi.org/10.3390/w13192690 - 28 Sep 2021
Cited by 6 | Viewed by 1703
Abstract
The fate of microplastics (MP) in seawater is heavily influenced by the biota: the density of MP particles can be changed due to biofouling, which affects sinking, or MP can be digested by zooplankton and transferred into fecal pellets with increased sinking rate. [...] Read more.
The fate of microplastics (MP) in seawater is heavily influenced by the biota: the density of MP particles can be changed due to biofouling, which affects sinking, or MP can be digested by zooplankton and transferred into fecal pellets with increased sinking rate. We hypothesize that seasonal production and degradation of organic matter, and corresponding changes in the plankton ecosystem affect the MP capacity for transportation and burying in sediments in different seasons. This is simulated with a coupled hydrodynamical-biogeochemical model that provides a baseline scenario of the seasonal changes in the planktonic ecosystem and changes in the availability of particulate and dissolved organic matter. In this work, we use a biogeochemical model OxyDep that simulates seasonal changes of phytoplankton (PHY), zooplankton (HET), dissolved organic matter (DOM) and detritus (POM). A specifically designed MP module considers MP particles as free particles (MPfree), particles with biofouling (MPbiof), particles consumed by zooplankton (MPhet) and particles in detritus, including fecal pellets (MPdet). A 2D coupled benthic-pelagic vertical transport model 2DBP was applied to study the effect of seasonality on lateral transport of MP and its burying in the sediments. OxyDep and MP modules were coupled with 2DBP using Framework for Aquatic Biogeochemical Modelling (FABM). A depletion of MP from the surface water and acceleration of MP burying in summer period compared to the winter was simulated numerically. The calculations confirm the observations that the “biological pump” can be one of the important drivers controlling the quantity and the distribution of MP in the water column. Full article
(This article belongs to the Section Oceans and Coastal Zones)
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Article
Socioeconomic Impact Assessment of Water Resources Conservation and Management to Protect Groundwater in Punjab, Pakistan
Water 2021, 13(19), 2672; https://doi.org/10.3390/w13192672 - 27 Sep 2021
Cited by 8 | Viewed by 1943
Abstract
Water is the most important resource; it is utilized largely in agricultural production and is fundamental to ensuring global food security. This study aims to assess sustainable water management interventions and their impact on the farm economy. To increase water productivity, the most [...] Read more.
Water is the most important resource; it is utilized largely in agricultural production and is fundamental to ensuring global food security. This study aims to assess sustainable water management interventions and their impact on the farm economy. To increase water productivity, the most important adaptations that have been proposed are high-efficiency irrigation systems, drought-resistant varieties, the substitution of water-intensive crops with less water-demanding crops, the mulching of soil, zero tillage, and all on-farm operations that can save water, especially ground water. The recent analysis utilized farm survey data from 469 representative farmers along with secondary statistics. The data were collected via a multi-stage sampling technique to ensure the availability of representative farm populations based on a comprehensive site selection criterion. The TOA-MD model estimates the adoption rate of a proposed adaptation based on net farm returns. The impact of high-efficiency irrigation systems and the substitution of high delta crops for low delta crops had a positive impact on net farm returns and per capita income, and a negative impact on farm poverty in the study area. It is recommended that policymakers consult farmer representatives about agricultural and water-related issues so that all the policies can be implemented properly. Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
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Article
Wildfires as a Source of PAHs in Surface Waters of Background Areas (Lake Baikal, Russia)
Water 2021, 13(19), 2636; https://doi.org/10.3390/w13192636 - 25 Sep 2021
Cited by 7 | Viewed by 1365
Abstract
Polycyclic aromatic hydrocarbons (PAHs) were detected in different types of PAH-containing samples collected in Lake Baikal during wildfires in the adjacent areas. The set of studied samples included the following: (i) water from the upper layer (5 m); (ii) water from the surface [...] Read more.
Polycyclic aromatic hydrocarbons (PAHs) were detected in different types of PAH-containing samples collected in Lake Baikal during wildfires in the adjacent areas. The set of studied samples included the following: (i) water from the upper layer (5 m); (ii) water from the surface microlayer; (iii) water from the lake tributaries; (iv) water from deep layers (400 m); and (v) aerosol from the near-water layer. Ten PAHs were detected in the water samples: naphthalene, 1-methylnaphthalene, 2-methylnaphthalene acenaphthylene, acenaphthene, fluorene, phenanthrene, fluoranthene, pyrene, and chrysene. The total PAH concentrations (ƩPAHs) were detected in a wide range from 9.3 to 160 ng/L, characterizing by seasonal, intersessional, and spatial variability. In September 2016, the ƩPAH concentration in the southern basin of the lake reached 610 ng/L in the upper water layer due to an increase in fluorene, phenanthrene, fluoranthene, and pyrene in the composition of the PAHs. In June 2019, ƩPAHs in the water from the northern basin of the lake reached 290 ng/L, with the naphthalene and phenanthrene concentrations up to 170 ng/L and 92 ng/L, respectively. The calculation of back trajectories of the atmospheric transport near Lake Baikal, satellite images, and ƩPAH concentrations in the surface water microlayer of 150 to 960 ng/L confirm the impact of wildfires on Lake Baikal, with which the seasonal increase in the ƩPAH concentrations was associated in 2016 and 2019. The toxicity of PAHs detected in the water of the lake in extreme situations was characterized by the total value of the toxic equivalent for PAHs ranging from 0.17 to 0.22 ng/L, and a possible ecological risk of the impact on biota was assessed as moderate. Full article
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Article
A Novel Hybrid Model for Developing Groundwater Potentiality Model Using High Resolution Digital Elevation Model (DEM) Derived Factors
Water 2021, 13(19), 2632; https://doi.org/10.3390/w13192632 - 25 Sep 2021
Cited by 9 | Viewed by 1308
Abstract
The present work aims to build a unique hybrid model by combining six fuzzy operator feature selection-based techniques with logistic regression (LR) for producing groundwater potential models (GPMs) utilising high resolution DEM-derived parameters in Saudi Arabia’s Bisha area. The current work focuses exclusively [...] Read more.
The present work aims to build a unique hybrid model by combining six fuzzy operator feature selection-based techniques with logistic regression (LR) for producing groundwater potential models (GPMs) utilising high resolution DEM-derived parameters in Saudi Arabia’s Bisha area. The current work focuses exclusively on the influence of DEM-derived parameters on GPMs modelling, without considering other variables. AND, OR, GAMMA 0.75, GAMMA 0.8, GAMMA 0.85, and GAMMA 0.9 are six hybrid models based on fuzzy feature selection. The GPMs were validated by using empirical and binormal receiver operating characteristic curves (ROC). An RF-based sensitivity analysis was performed in order to examine the influence of GPM settings. Six hybrid algorithms and one unique hybrid model have predicted 1835–2149 km2 as very high and 3235–4585 km2 as high groundwater potential regions. The AND model (ROCe-AUC: 0.81; ROCb-AUC: 0.804) outperformed the other models based on ROC’s area under curve (AUC). A novel hybrid model was constructed by combining six GPMs (considering as variables) with the LR model. The AUC of ROCe and ROCb revealed that the novel hybrid model outperformed existing fuzzy-based GPMs (ROCe: 0.866; ROCb: 0.892). With DEM-derived parameters, the present work will help to improve the effectiveness of GPMs for developing sustainable groundwater management plans. Full article
(This article belongs to the Section Hydrogeology)
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Article
A Case Study on Reliability, Water Demand and Economic Analysis of Rainwater Harvesting in Australian Capital Cities
Water 2021, 13(19), 2606; https://doi.org/10.3390/w13192606 - 22 Sep 2021
Cited by 11 | Viewed by 1857
Abstract
This paper presents reliability, water demand and economic analysis of rainwater harvesting (RWH) systems for eight Australian capital cities (Adelaide, Brisbane, Canberra, Darwin, Hobart, Melbourne, Perth and Sydney). A Python-based tool is developed based on a daily water balance modelling approach, which uses [...] Read more.
This paper presents reliability, water demand and economic analysis of rainwater harvesting (RWH) systems for eight Australian capital cities (Adelaide, Brisbane, Canberra, Darwin, Hobart, Melbourne, Perth and Sydney). A Python-based tool is developed based on a daily water balance modelling approach, which uses input data such as daily rainfall, roof area, overflow losses, daily water demand and first flush. Ten different tank volumes are considered (1, 3, 5, 10, 15, 20, 30, 50, 75 and 100 m3). It is found that for a large roof area and tank size, the reliability of RWH systems for toilet and laundry use is high, in the range of 80–100%. However, the reliability for irrigation use is highly variable across all the locations. For combined use, Adelaide shows the smallest reliability (38–49%), while Hobart demonstrates the highest reliability (61–77%). Furthermore, economic analysis demonstrates that in a few cases, benefit–cost ratio values greater than one can be achieved for the RWH systems. The findings of this study will help the Australian Federal Government to enhance RWH policy, programs and subsidy levels considering climate-sensitive inputs in the respective cities. Full article
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Article
Turbulent Flow through Random Vegetation on a Rough Bed
Water 2021, 13(18), 2564; https://doi.org/10.3390/w13182564 - 17 Sep 2021
Cited by 8 | Viewed by 1390
Abstract
River vegetation radically modifies the flow field and turbulence characteristics. To analyze the vegetation effects on the flow, most scientific studies are based on laboratory tests or numerical simulations with vegetation stems on smooth beds. Nevertheless, in this manner, the effects of bed [...] Read more.
River vegetation radically modifies the flow field and turbulence characteristics. To analyze the vegetation effects on the flow, most scientific studies are based on laboratory tests or numerical simulations with vegetation stems on smooth beds. Nevertheless, in this manner, the effects of bed sediments are neglected. The aim of this paper is to experimentally investigate the effects of bed sediments in a vegetated channel and, in consideration of that, comparative experiments of velocity measures, performed with an Acoustic Doppler Velocimeter (ADV) profiler, were carried out in a laboratory flume with different uniform bed sediment sizes and the same pattern of randomly arranged emergent rigid vegetation. To better comprehend the time-averaged flow conditions, the time-averaged velocity was explored. Subsequently, the analysis was focused on the energetic characteristics of the flow field with the determination of the Turbulent Kinetic Energy (TKE) and its components, as well as of the energy spectra of the velocity components immediately downstream of a vegetation element. The results show that both the vegetation and bed roughness surface deeply affect the turbulence characteristics. Furthermore, it was revealed that the roughness influence becomes predominant as the grain size becomes larger. Full article
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Article
Nature-Based Solutions for Agriculture in Circular Cities: Challenges, Gaps, and Opportunities
Water 2021, 13(18), 2565; https://doi.org/10.3390/w13182565 - 17 Sep 2021
Cited by 11 | Viewed by 3670
Abstract
Urban agriculture (UA) plays a key role in the circular metabolism of cities, as it can use water resources, nutrients, and other materials recovered from streams that currently leave the city as solid waste or as wastewater to produce new food and biomass. [...] Read more.
Urban agriculture (UA) plays a key role in the circular metabolism of cities, as it can use water resources, nutrients, and other materials recovered from streams that currently leave the city as solid waste or as wastewater to produce new food and biomass. The ecosystem services of urban green spaces and infrastructures and the productivity of specific urban agricultural technologies have been discussed in literature. However, the understanding of input and output (I/O) streams of different nature-based solutions (NBS) is not yet sufficient to identify the challenges and opportunities they offer for strengthening circularity in UA. We propose a series of agriculture NBS, which, implemented in cities, would address circularity challenges in different urban spaces. To identify the challenges, gaps, and opportunities related to the enhancement of resources management of agriculture NBS, we evaluated NBS units, interventions, and supporting units, and analyzed I/O streams as links of urban circularity. A broader understanding of the food-related urban streams is important to recover resources and adapt the distribution system accordingly. As a result, we pinpointed the gaps that hinder the development of UA as a potential opportunity within the framework of the Circular City. Full article
(This article belongs to the Special Issue Water and Circular Cities)
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Article
Spoiled for Choice during Cold Season? Habitat Use and Potential Impacts of the Invasive Silurus glanis L. in a Deep, Large, and Oligotrophic Lake (Lake Maggiore, North Italy)
Water 2021, 13(18), 2549; https://doi.org/10.3390/w13182549 - 17 Sep 2021
Cited by 8 | Viewed by 3040
Abstract
The ecological features of invasive alien species are crucial for their effective management. However, they are often lacking in newly invaded ecosystems. This is the case of the European catfish Silurus glanis L. in Lake Maggiore, where the species is present since 1990, [...] Read more.
The ecological features of invasive alien species are crucial for their effective management. However, they are often lacking in newly invaded ecosystems. This is the case of the European catfish Silurus glanis L. in Lake Maggiore, where the species is present since 1990, but no scientific information is available on its ecology. To start filling this knowledge gap, 236 catfish (67 cm to 150 cm of total length) were collected, measured, and dissected for stomach content analyses from three localities and in two habitats (littoral vs. pelagic) in late autumn/early winter. The NPUE and BPUE (individuals (N) and biomass (B, in grams) per unit effort (m2), respectively) of catfish were generally higher in littoral (NPUE > 0.01; BPUE > 96) than in pelagic habitats (NPUE < 0.009; BPUE < 114), but the catfish had, on average, larger sizes in pelagic habitats. Overall, 581 individual prey items were recorded, belonging to 12 taxa. Pelagic catfish specialized their diet exclusively on three prey fish (coregonids, shad, and roach), whilst the diet of littoral catfish was more variable and dominated by crayfish, perch, and roach. These results highlighted for the first time the interaction of larger catfish with the lake’s pelagic food web, and thus possible consequences are discussed, including the potential contrasting role S. glanis may have for the lake’s fishery. Full article
(This article belongs to the Special Issue Impacts of Human Activities and Climate Change on Freshwater Fish)
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Article
Evaluation of Vegetation Indices and Phenological Metrics Using Time-Series MODIS Data for Monitoring Vegetation Change in Punjab, Pakistan
Water 2021, 13(18), 2550; https://doi.org/10.3390/w13182550 - 17 Sep 2021
Cited by 23 | Viewed by 2640
Abstract
In arid and semi-arid regions, it is essential to monitor the spatiotemporal variability and dynamics of vegetation. Among other provinces of Pakistan, Punjab has produced a significant number of crops. Recently, Punjab, Pakistan, has been described as a global hotspot for extremes of [...] Read more.
In arid and semi-arid regions, it is essential to monitor the spatiotemporal variability and dynamics of vegetation. Among other provinces of Pakistan, Punjab has produced a significant number of crops. Recently, Punjab, Pakistan, has been described as a global hotspot for extremes of climate change. In this study, the soil adjusted vegetation index (SAVI), normalized vegetation difference index (NDVI), and enhanced vegetation index (EVI) were comprehensively evaluated to monitor vegetation change in Punjab, Pakistan. The time-series MODIS (Moderate Resolution Imaging Spectroradiometer) data of different periods were used. The mean annual variability of the above vegetation indices (VIs) from 2000 to 2019 was evaluated and analyzed. For each type of vegetation, two phenological metrics (i.e., for the start of the season and end of the season) were calculated and compared. The spatio-temporal image analysis of the mean annual vegetation indices revealed similar patterns and varying vegetation conditions. In the forests and vegetation areas with sparse vegetation, the EVI showed high uncertainty. The phenological metrics of all vegetation indices were consistent for most types of vegetation. However, the NDVI result had the greatest variance between the start and end of season. The lowest annual VI variability was mainly observed in the southern part of the study area (less than 10% of the study area) based on the statistical analysis of spatial variability. The mean annual spatial variability of NDVI was <20%, SAVI was 30%, and EVI ranged between 10–20%. More than 40% of the variability was observed in the NDVI and SAVI vegetation indices. Full article
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Article
The Life Cycle Environmental Performance of On-Site or Decentralised Wastewater Treatment Systems for Domestic Homes
Water 2021, 13(18), 2542; https://doi.org/10.3390/w13182542 - 16 Sep 2021
Cited by 3 | Viewed by 1490
Abstract
There is little knowledge regarding the environmental sustainability of domestic on-site or decentralised wastewater treatment systems (DWWTS). This study evaluated six unique life cycle environmental impacts for different DWTTS configurations of five conventional septic tank systems, four packaged treatment units, and a willow [...] Read more.
There is little knowledge regarding the environmental sustainability of domestic on-site or decentralised wastewater treatment systems (DWWTS). This study evaluated six unique life cycle environmental impacts for different DWTTS configurations of five conventional septic tank systems, four packaged treatment units, and a willow evapotranspiration system. Similar freshwater eutrophication (FE), dissipated water (DW), and mineral and metal (MM), burdens were noted between the packaged and conventional system configurations, with the packaged systems demonstrating significantly higher impacts of between 18% and 56% for climate change (CC), marine eutrophication (ME), and fossils (F). At a system level, higher impacts were observed in systems requiring (i) three vs. two engineered treatment stages, (ii) a larger soil percolation trench area, and (iii) pumping of effluent. The evapotranspiration system presented the smallest total environmental impacts (3.0–10.8 lower), with net benefits for FE, ME, and MM identified due to the biomass (wood) production offsetting these burdens. Further analysis highlighted the sensitivity of results to biomass yield, operational demands (desludging or pumping energy demands), and embodied materials, with less significant impacts for replacing mechanical components, i.e., pumps. The findings highlighted the variation in environmental performance of different DWTTS configurations and indicated opportunities for design improvements to reduce their life cycle impacts. Full article
(This article belongs to the Special Issue On-Site Wastewater Treatment)
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Article
Assessment of Ensemble Models for Groundwater Potential Modeling and Prediction in a Karst Watershed
Water 2021, 13(18), 2540; https://doi.org/10.3390/w13182540 - 16 Sep 2021
Cited by 13 | Viewed by 1345
Abstract
Due to numerous droughts in recent years, the amount of surface water in arid and semi-arid regions has decreased significantly, so reliance on groundwater to meet local and regional demands has increased. The Kabgian watershed is a karst watershed in southwestern Iran that [...] Read more.
Due to numerous droughts in recent years, the amount of surface water in arid and semi-arid regions has decreased significantly, so reliance on groundwater to meet local and regional demands has increased. The Kabgian watershed is a karst watershed in southwestern Iran that provides a significant proportion of drinking and agriculture water supplies in the area. This study identified areas with karst groundwater potential using a combination of machine learning and statistical models, including entropy-SVM-LN, entropy-SVM-SG, and entropy-SVM-RBF. To do this, 384 karst springs were identified and mapped. Sixteen factors that are related to karst potential were identified from a review of the literature, and these were compiled for the study area. The 384 locations were randomly separated into two categories for training (269 location) and validation (115 location) datasets to be used in the modeling process. The ROC curve was used to evaluate the modeling results. The models used, in general, were good at determining the location of karst groundwater potential. The evaluation showed that the E-SVM-RBF model had an area under the curve of 0.92, indicating that it was most accurate estimator of groundwater potential among the ensemble models. Evaluation of the relative importance of each of the 16 factors revealed that land use, a vector ruggedness measure, curvature, and topography roughness index were the most important explainers of the presence of karst groundwater in the study area. It was also found that the factors affecting the presence of karst springs are significantly different from non-karst springs. Full article
(This article belongs to the Special Issue Assessment and Management of Flood Risk in Urban Areas)
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Article
Key SARS-CoV-2 Mutations of Alpha, Gamma, and Eta Variants Detected in Urban Wastewaters in Italy by Long-Read Amplicon Sequencing Based on Nanopore Technology
Water 2021, 13(18), 2503; https://doi.org/10.3390/w13182503 - 13 Sep 2021
Cited by 13 | Viewed by 3174
Abstract
The emergence of SARS-CoV-2 variants of concern (VOCs) and variants of interest (VOIs) poses an increased risk to global public health and underlines the need to prioritise monitoring and research to better respond to the COVID-19 pandemic. Wastewater monitoring can be used to [...] Read more.
The emergence of SARS-CoV-2 variants of concern (VOCs) and variants of interest (VOIs) poses an increased risk to global public health and underlines the need to prioritise monitoring and research to better respond to the COVID-19 pandemic. Wastewater monitoring can be used to monitor SARS-CoV-2 spread and to track SARS-CoV-2 variants. A long read amplicon sequencing approach based on the Oxford Nanopore technology, targeting the spike protein, was applied to detect SARS-CoV-2 variants in sewage samples collected in central Italy on April 2021. Next-generation sequencing was performed on three pooled samples. For variant identification, two approaches–clustering (unsupervised) and classification (supervised)–were implemented, resulting in the detection of two VOCs and one VOI. Key mutations of the Alpha variant (B.1.1.7) were detected in all of the pools, accounting for the vast majority of NGS reads. In two different pools, mutations of the Gamma (P.1) and Eta (B.1.525) variants were also detected, accounting for 22.4%, and 1.3% of total NGS reads of the sample, respectively. Results were in agreement with data on variant circulation in Italy at the time of wastewater sample collection. For each variant, in addition to the signature key spike mutations, other less common mutations were detected, including the amino acid substitutions S98F and E484K in the Alpha cluster (alone and combined), and S151I in the Eta cluster. Results of the present study show that the long-read sequencing nanopore technology can be successfully used to explore SARS-CoV-2 diversity in sewage samples, where multiple variants can be present, and that the approach is sensitive enough to detect variants present at low abundance in wastewater samples. In conclusion, wastewater monitoring can help one discover the spread of variants in a community and early detect the emerging of clinically relevant mutations or variants. Full article
(This article belongs to the Special Issue SARS-CoV-2 in Wastewater: Methods, Epidemiology and Future Goals)
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Article
Adapting Water Management to Climate Change in the Murray–Darling Basin, Australia
Water 2021, 13(18), 2504; https://doi.org/10.3390/w13182504 - 12 Sep 2021
Cited by 16 | Viewed by 2621
Abstract
Climate change is threatening water security in water-scarce regions across the world, challenging water management policy in terms of how best to adapt. Transformative new approaches have been proposed, but management policies remain largely the same in many instances, and there are claims [...] Read more.
Climate change is threatening water security in water-scarce regions across the world, challenging water management policy in terms of how best to adapt. Transformative new approaches have been proposed, but management policies remain largely the same in many instances, and there are claims that good current management practice is well adapted. This paper takes the case of the Murray–Darling Basin, Australia, where management policies are highly sophisticated and have been through a recent transformation in order to critically review how well adapted the basin’s management is to climate change. This paper synthesizes published data, recent literature, and water plans in order to evaluate the outcomes of water management policy. It identifies several limitations and inequities that could emerge in the context of climate change and, through synthesis of the broader climate adaptation literature, proposes solutions that can be implemented when basin management is formally reviewed in 2026. Full article
(This article belongs to the Special Issue Integrated Water Assessment and Management under Climate Change)
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Article
Efficient Hazard Assessment for Pluvial Floods in Urban Environments: A Benchmarking Case Study for the City of Berlin, Germany
Water 2021, 13(18), 2476; https://doi.org/10.3390/w13182476 - 09 Sep 2021
Cited by 7 | Viewed by 1968
Abstract
The presence of impermeable surfaces in urban areas hinders natural drainage and directs the surface runoff to storm drainage systems with finite capacity, which makes these areas prone to pluvial flooding. The occurrence of pluvial flooding depends on the existence of minimal areas [...] Read more.
The presence of impermeable surfaces in urban areas hinders natural drainage and directs the surface runoff to storm drainage systems with finite capacity, which makes these areas prone to pluvial flooding. The occurrence of pluvial flooding depends on the existence of minimal areas for surface runoff generation and concentration. Detailed hydrologic and hydrodynamic simulations are computationally expensive and require intensive resources. This study compared and evaluated the performance of two simplified methods to identify urban pluvial flood-prone areas, namely the fill–spill–merge (FSM) method and the topographic wetness index (TWI) method and used the TELEMAC-2D hydrodynamic numerical model for benchmarking and validation. The FSM method uses common GIS operations to identify flood-prone depressions from a high-resolution digital elevation model (DEM). The TWI method employs the maximum likelihood method (MLE) to probabilistically calibrate a TWI threshold (τ) based on the inundation maps from a 2D hydrodynamic model for a given spatial window (W) within the urban area. We found that the FSM method clearly outperforms the TWI method both conceptually and effectively in terms of model performance. Full article
(This article belongs to the Special Issue Assessment and Management of Flood Risk in Urban Areas)
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