Water

19 pages, 4240 KiB

Open AccessEditor’s ChoiceArticle

Towards Groundwater-Level Prediction Using Prophet Forecasting Method by Exploiting a High-Resolution Hydrogeological Monitoring System

by Davide Fronzi, Gagan Narang, Alessandro Galdelli, Alessandro Pepi, Adriano Mancini and Alberto Tazioli

Water 2024, 16(1), 152; https://doi.org/10.3390/w16010152 - 30 Dec 2023

Cited by 7 | Viewed by 3756

Abstract

Forecasting of water availability has become of increasing interest in recent decades, especially due to growing human pressure and climate change, affecting groundwater resources towards a perceivable depletion. Numerous research papers developed at various spatial scales successfully investigated daily or seasonal groundwater level [...] Read more.

Forecasting of water availability has become of increasing interest in recent decades, especially due to growing human pressure and climate change, affecting groundwater resources towards a perceivable depletion. Numerous research papers developed at various spatial scales successfully investigated daily or seasonal groundwater level prediction starting from measured meteorological data (i.e., precipitation and temperature) and observed groundwater levels, by exploiting data-driven approaches. Barely a few research combine the meteorological variables and groundwater level data with unsaturated zone monitored variables (i.e., soil water content, soil temperature, and bulk electric conductivity), and—in most of these—the vadose zone is monitored only at a single depth. Our approach exploits a high spatial-temporal resolution hydrogeological monitoring system developed in the Conero Mt. Regional Park (central Italy) to predict groundwater level trends of a shallow aquifer exploited for drinking purposes. The field equipment consists of a thermo-pluviometric station, three volumetric water content, electric conductivity, and soil temperature probes in the vadose zone at 0.6 m, 0.9 m, and 1.7 m, respectively, and a piezometer instrumented with a permanent water-level probe. The monitored period started in January 2022, and the variables were recorded every fifteen minutes for more than one hydrologic year, except the groundwater level which was recorded on a daily scale. The developed model consists of three “virtual boxes” (i.e., atmosphere, unsaturated zone, and saturated zone) for which the hydrological variables characterizing each box were integrated into a time series forecasting model based on Prophet developed in the Python environment. Each measured parameter was tested for its influence on groundwater level prediction. The model was fine-tuned to an acceptable prediction (roughly 20% ahead of the monitored period). The quantitative analysis reveals that optimal results are achieved by expoiting the hydrological variables collected in the vadose zone at a depth of 1.7 m below ground level, with a Mean Absolute Error (MAE) of 0.189, a Mean Absolute Percentage Error (MAPE) of 0.062, a Root Mean Square Error (RMSE) of 0.244, and a Correlation coefficient of 0.923. This study stresses the importance of calibrating groundwater level prediction methods by exploring the hydrologic variables of the vadose zone in conjunction with those of the saturated zone and meteorological data, thus emphasizing the role of hydrologic time series forecasting as a challenging but vital aspect of optimizing groundwater management. Full article

(This article belongs to the Special Issue Data-Driven Approach Supporting Groundwater Resource Understanding, Protection and Management)

► Show Figures

Figure 1

19 pages, 865 KiB

Open AccessEditor’s ChoiceArticle

Planning and Design Strategies for Green Stormwater Infrastructure from an Urban Design Perspective

by Jianxi Ou, Junqi Li, Xiaojing Li and Jianqin Zhang

Water 2024, 16(1), 29; https://doi.org/10.3390/w16010029 - 20 Dec 2023

Cited by 6 | Viewed by 3323

Abstract

With the rapid advancement of ecological civilization construction, prioritizing green stormwater infrastructure to address urban stormwater management issues has become an important strategy for ecological priority and green development in sustainable urban development. Green stormwater infrastructure, as a major facility in the construction [...] Read more.

With the rapid advancement of ecological civilization construction, prioritizing green stormwater infrastructure to address urban stormwater management issues has become an important strategy for ecological priority and green development in sustainable urban development. Green stormwater infrastructure, as a major facility in the construction of sponge cities, can reduce the generation and external discharge of runoff and play a purification role. However, there are various types of green stormwater infrastructure, each with different control effects and applicable conditions. Therefore, to facilitate the planning, design, acceptance, assessment, and monitoring evaluation of sponge city green stormwater infrastructure, this study proposes the “sponge equivalent” method. By comparing the control effects of different facilities with bioretention facilities, the method standardizes the effects, making them easier to understand and apply. Taking a typical area of Beijing and its urban roads as examples, the study analyzed and applied planning and design control strategies. The results show that for a residential area of 1 km², to achieve the annual runoff total control rate target of 85%, the method of converting runoff volume control equivalents, using bioretention pools as a benchmark, allows for the calculation of various combinations of areas of different types of green stormwater infrastructure, such as sunken green spaces, permeable paving bricks, green roofs, and water storage tanks. This optimizes the planning index of Beijing, which mandates stormwater detention facilities for new projects with a hardened surface area of 2000 m² or more. The sponge equivalent method can optimize the planning and design control strategy of green stormwater infrastructure, allowing for rapid assessment and application of the design scale of green stormwater infrastructure in areas during the planning and design stage, providing theoretical and technical support for ecological and green urban stormwater management. The application of this research method helps promote green development and ecological priority in urban sustainable development strategies, and the conclusions provide valuable references for decision-makers and practitioners in related fields. Full article

(This article belongs to the Special Issue Urban Water Management and Hydrological Process)

► Show Figures

Figure 1

21 pages, 4842 KiB

Open AccessEditor’s ChoiceArticle

Reference Evapotranspiration Estimation Using Genetic Algorithm-Optimized Machine Learning Models and Standardized Penman–Monteith Equation in a Highly Advective Environment

by Shafik Kiraga, R. Troy Peters, Behnaz Molaei, Steven R. Evett and Gary Marek

Water 2024, 16(1), 12; https://doi.org/10.3390/w16010012 - 20 Dec 2023

Cited by 7 | Viewed by 2359

Abstract

Accurate estimation of reference evapotranspiration (ET_r) is important for irrigation planning, water resource management, and preserving agricultural and forest habitats. The widely used Penman–Monteith equation (ASCE-PM) estimates ET_r across various timescales using ground weather station data. However, discrepancies persist between [...] Read more.

Accurate estimation of reference evapotranspiration (ET_r) is important for irrigation planning, water resource management, and preserving agricultural and forest habitats. The widely used Penman–Monteith equation (ASCE-PM) estimates ET_r across various timescales using ground weather station data. However, discrepancies persist between estimated ET_r and measured ET_r obtained from weighing lysimeters (ET_r-lys), particularly in advective environments. This study assessed different machine learning (ML) models in comparison to ASCE-PM for ET_r estimation in highly advective conditions. Various variable combinations, representing both radiation and aerodynamic components, were organized for evaluation. Eleven datasets (DT) were created for the daily timescale, while seven were established for hourly and quarter-hourly timescales. ML models were optimized by a genetic algorithm (GA) and included support vector regression (GA-SVR), random forest (GA-RF), artificial neural networks (GA-ANN), and extreme learning machines (GA-ELM). Meteorological data and direct measurements of well-watered alfalfa grown under reference ET conditions obtained from weighing lysimeters and a nearby weather station in Bushland, Texas (1996–1998), were used for training and testing. Model performance was assessed using metrics such as root mean square error (RMSE), mean absolute error (MAE), mean bias error (MBE), and coefficient of determination (R²). ASCE-PM consistently underestimated alfalfa ET across all timescales (above 7.5 mm/day, 0.6 mm/h, and 0.2 mm/h daily, hourly, and quarter-hourly, respectively). On hourly and quarter-hourly timescales, datasets predominantly composed of radiation components or a blend of radiation and aerodynamic components demonstrated superior performance. Conversely, datasets primarily composed of aerodynamic components exhibited enhanced performance on a daily timescale. Overall, GA-ELM outperformed the other models and was thus recommended for ET_r estimation at all timescales. The findings emphasize the significance of ML models in accurately estimating ET_r across varying temporal resolutions, crucial for effective water management, water resources, and agricultural planning. Full article

(This article belongs to the Topic Hydrology and Water Resources in Agriculture and Ecology)

► Show Figures

Figure 1

16 pages, 6284 KiB

Open AccessEditor’s ChoiceArticle

A Quantitative Approach for Identifying Nitrogen Sources in Complex Yeongsan River Watershed, Republic of Korea, Based on Dual Nitrogen Isotope Ratios and Hydrological Model

by Seoyeon Hong, Youngun Han, Jihae Kim, Bo Ra Lim, Si-Young Park, Heeju Choi, Mi Rae Park, Eunmi Kim, Soohyung Lee, Yujeong Huh, Kyunghyun Kim, Won-Seok Lee, Taewoo Kang and Min-Seob Kim

Water 2023, 15(24), 4275; https://doi.org/10.3390/w15244275 - 14 Dec 2023

Cited by 8 | Viewed by 1608

Abstract

Effective management of nitrate loading in complex river systems requires quantitative estimation to trace different nitrogen sources. This study aims to validate an integrated framework using soluble nitrogen isotope ratios (δ¹⁵N–NH₄ and δ¹⁵N–NO₃) and hydrological modeling [...] Read more.

Effective management of nitrate loading in complex river systems requires quantitative estimation to trace different nitrogen sources. This study aims to validate an integrated framework using soluble nitrogen isotope ratios (δ¹⁵N–NH₄ and δ¹⁵N–NO₃) and hydrological modeling (hydrological simulation program SPARROW) of the main stream and tributaries in the Yeongsan River to determine anthropogenic nitrogen fluxes among different land-use types in the complex river watershed. The δ¹⁵N–NH₄ and δ¹⁵N–NO₃ isotopic compositions varied across different land-use types (4.9 to 15.5‰ for δ¹⁵N–NH₄ and −4.9 to 12.1‰ for δ¹⁵N–NO₃), reflecting the different sources of nitrogen in the watershed (soil N including synthetic fertilizer N, manure N, and sewage treatment plant effluent N). We compared the soluble nitrogen isotopic compositions (δ¹⁵N–NH₄ and δ¹⁵N–NO₃) of the river water with various nitrogen sources (soil N, manure N, and sewage N) to assess their contribution, revealing that N from sewage treatment plant effluent as a point source was dominant during the dry season and N from forest- and soil-derived non-point sources was dominant due to intensive rainfall during the wet season. The coefficient of determination (R²) between the measured pollution load and the predicted pollution load calculated by the SPARROW model was 0.95, indicating a high correlation. In addition, the EMMA-based nitrogen contributions compared to the SPARROW-based nitrogen fluxes were similar to each other, indicating that large amounts of forest- and soil-derived N may be transported to the Yeongsan River watershed as non-point sources, along with the effect of sewage treatment plant effluent N as a point source. This study provides valuable insights for the formulation of management policies to control nitrogen inputs from point and non-point sources across different land-use types for the restoration of water quality and aquatic ecosystems in complex river systems. Given the recent escalation in human activity near aquatic environments, this framework is effective in estimating the quantitative contribution of individual anthropogenic nitrogen sources transported along riverine systems. Full article

(This article belongs to the Special Issue Transport of Pollutants in Agricultural Watersheds)

► Show Figures

Figure 1

19 pages, 2026 KiB

Open AccessEditor’s ChoiceArticle

Mitigating Ammonia, Methane, and Carbon Dioxide Emissions from Stored Pig Slurry Using Chemical and Biological Additives

by Oumaima El bied, Martire Angélica Terrero Turbí, Amalia García-Valero, Ángel Faz Cano and José A. Acosta

Water 2023, 15(23), 4185; https://doi.org/10.3390/w15234185 - 4 Dec 2023

Cited by 6 | Viewed by 2441

Abstract

This study addresses the challenge of mitigating ammonia and greenhouse gas (GHG) emissions from stored pig slurry using chemical and biological additives. The research employs dynamic chambers to evaluate the effectiveness of these additives. Chemical agents (sulfuric acid) and biological additives (DAB bacteria) [...] Read more.

This study addresses the challenge of mitigating ammonia and greenhouse gas (GHG) emissions from stored pig slurry using chemical and biological additives. The research employs dynamic chambers to evaluate the effectiveness of these additives. Chemical agents (sulfuric acid) and biological additives (DAB bacteria) containing specific microbial strains are tested (a mixture of Rhodopseudomonas palustris, Bacillus subtilis, Bacillus amyloliquefaciens, Bacillus licheniformis, Nitrosomona europea, Nictobacter winogradaskyi, and nutritional substrate). Controlled experiments simulate storage conditions and measure emissions of ammonia, methane, and carbon dioxide. Through statistical analysis of the results, this study evaluates the additives’ impact on emission reduction. Sulfuric acid demonstrated a reduction of 92% in CH₄, 99% in CO₂, and 99% in NH₃ emissions. In contrast, the biological additives showed a lesser impact on CH₄, with an 8% reduction, but more substantial reductions of 71% for CO₂ and 77% for NH₃.These results shed light on the feasibility of employing these additives to mitigate environmental impacts in pig slurry management and contribute to sustainable livestock practices by proposing strategies to reduce the ecological consequences of intensive animal farming. Full article

(This article belongs to the Section Wastewater Treatment and Reuse)

► Show Figures

Figure 1

14 pages, 4757 KiB

Open AccessEditor’s ChoiceArticle

Analysis of Heavy Metal Contaminants and Mobility in Sewage sludge-soil Mixtures for Sustainable Agricultural Practices

by Agata Janaszek and Robert Kowalik

Water 2023, 15(22), 3992; https://doi.org/10.3390/w15223992 - 16 Nov 2023

Cited by 10 | Viewed by 2143

Abstract

This study presents a comprehensive analysis of the potential utilization of sewage sludge in agriculture, focusing on the assessment of heavy metal contaminants and their mobility in sewage sludge-soil mixtures. The innovative approach of investigating heavy metal fractions in these mixtures sheds light [...] Read more.

This study presents a comprehensive analysis of the potential utilization of sewage sludge in agriculture, focusing on the assessment of heavy metal contaminants and their mobility in sewage sludge-soil mixtures. The innovative approach of investigating heavy metal fractions in these mixtures sheds light on their environmental implications. In this study, sludge and soil samples from three different soil categories were collected, and the mobility of heavy metals was investigated using sequential BCR analysis. A thorough assessment of the risk of environmental contamination associated with the agricultural use of sludge was also carried out. This study included the calculation of various risk indicators, such as the Geoaccumulation Index of heavy metals in soil (Igeo), the risk assessment code (RAC), and the author’s element mobility ratio (EMR), which included a comparison of the overall metal concentrations in sludge, soil, and mixtures. This study demonstrates that the key to using sludge is to know the form of mobility of the metals present in the sludge and how they behave once they are introduced into the soil. Full article

(This article belongs to the Special Issue Resource Use of Sewage Sludge for Soil Application)

► Show Figures

Figure 1

18 pages, 2944 KiB

Open AccessEditor’s ChoiceArticle

Flood Forecasting Using Hybrid LSTM and GRU Models with Lag Time Preprocessing

by Yue Zhang, Zimo Zhou, Jesse Van Griensven Thé, Simon X. Yang and Bahram Gharabaghi

Water 2023, 15(22), 3982; https://doi.org/10.3390/w15223982 - 16 Nov 2023

Cited by 17 | Viewed by 3952

Abstract

Climate change and urbanization have increased the frequency of floods worldwide, resulting in substantial casualties and property loss. Accurate flood forecasting can offer governments early warnings about impending flood disasters, giving them a chance to evacuate and save lives. Deep learning is used [...] Read more.

Climate change and urbanization have increased the frequency of floods worldwide, resulting in substantial casualties and property loss. Accurate flood forecasting can offer governments early warnings about impending flood disasters, giving them a chance to evacuate and save lives. Deep learning is used in flood forecasting to improve the timeliness and accuracy of flood water level predictions. While various deep learning models similar to Long Short-Term Memory (LSTM) have achieved notable results, they have complex structures with low computational efficiency, and often lack generalizability and stability. This study applies a spatiotemporal Attention Gated Recurrent Unit (STA-GRU) model for flood prediction to increase the models’ computing efficiency. Another salient feature of our methodology is the incorporation of lag time during data preprocessing before the training of the model. Notably, for 12-h forecasting, the STA-GRU model’s R-squared (R2) value increased from 0.8125 to 0.9215. Concurrently, the model manifested reduced root mean squared error (RMSE) and mean absolute error (MAE) metrics. For a more extended 24-h forecasting, the R2 value of the STA-GRU model improved from 0.6181 to 0.7283, accompanied by diminishing RMSE and MAE values. Seven typical deep learning models—the LSTM, the Convolutional Neural Networks LSTM (CNNLSTM), the Convolutional LSTM (ConvLSTM), the spatiotemporal Attention Long Short-Term Memory (STA-LSTM), the GRU, the Convolutional Neural Networks GRU (CNNGRU), and the STA-GRU—are compared for water level prediction. Comparative analysis delineated that the use of the STA-GRU model and the application of the lag time pre-processing method significantly improved the reliability and accuracy of flood forecasting. Full article

► Show Figures

Figure 1

30 pages, 2691 KiB

Open AccessEditor’s ChoiceReview

Urban Wastewater Mining for Circular Resource Recovery: Approaches and Technology Analysis

by Andrea G. Capodaglio

Water 2023, 15(22), 3967; https://doi.org/10.3390/w15223967 - 15 Nov 2023

Cited by 15 | Viewed by 3600

Abstract

Urban areas comprise less than 1% of the Earth’s land surface, yet they host more than half the global population and are responsible for the majority of global energy use and related CO₂ emissions. Urbanization is increasing the speed and local intensity [...] Read more.

Urban areas comprise less than 1% of the Earth’s land surface, yet they host more than half the global population and are responsible for the majority of global energy use and related CO₂ emissions. Urbanization is increasing the speed and local intensity of water cycle exploitation, with a large number of cities suffering from water shortage problems globally. Wastewater (used water) contains considerable amounts of embedded energy and recoverable materials. Studies and applications have demonstrated that recovering or re-capturing water, energy, and materials from wastewater is a viable endeavor, with several notable examples worldwide. Reclaiming all these resources through more widespread application of effective technological approaches could be feasible and potentially profitable, although challenging from several points of view. This paper reviews the possibilities and technical opportunities applicable to the mining of resources within the urban water cycle and discusses emerging technologies and issues pertaining to resource recovery and reuse applications. The present and future sustainability of approaches is also discussed. Since sewage management issues are not “one size fits all”, local conditions must be carefully considered when designing optimal local resource recovery solutions, which are influenced not just by technology but also by multiple economic, geographical, and social factors. Full article

(This article belongs to the Special Issue Resource Recovery Monitoring and Circular Economy Model in Wastewater)

► Show Figures

Figure 1

16 pages, 7610 KiB

Open AccessEditor’s ChoiceReview

Systematic Review of Contaminants of Emerging Concern (CECs): Distribution, Risks, and Implications for Water Quality and Health

by Weiying Feng, Yuxin Deng, Fang Yang, Qingfeng Miao and Su Kong Ngien

Water 2023, 15(22), 3922; https://doi.org/10.3390/w15223922 - 10 Nov 2023

Cited by 17 | Viewed by 7667

Abstract

The introduction of contaminants of emerging concern (CECs) into the environment has raised concerns due to the significant risks they pose to both ecosystems and human health. In this sys-tematic review, we investigate research trends on CECs worldwide over the past 10 years, [...] Read more.

The introduction of contaminants of emerging concern (CECs) into the environment has raised concerns due to the significant risks they pose to both ecosystems and human health. In this sys-tematic review, we investigate research trends on CECs worldwide over the past 10 years, focus-ing on four critical aspects: (i) the identification and distribution of typical CECs across various media, (ii) the sources and environmental behavior of CECs, (iii) the implications of CECs expo-sure on human health, and (iv) risk assessment and control measures for CECs. The review re-veals a comprehensive understanding of the typical types and distribution of CECs in different environmental media, shedding light on their prevalence and potential impact on ecosystems. Furthermore, insights into the sources and behavior of CECs provide crucial information for de-vising effective strategies to mitigate their release into the environment. By examining the health effects of EC exposure, we highlight the importance of considering potential risks to human well-being. This aspect of the review emphasizes the significance of monitoring and managing CECs to safeguard public health. The review also synthesizes the advancements in risk assessment methodologies and control measures for CECs, which are essential for developing comprehensive regulations and guidelines to manage these contaminants effectively. Drawing from the findings, we identify future research directions for CECs in aquatic environments. Full article

(This article belongs to the Special Issue Water Environment Pollution and Control, Volume II)

► Show Figures

Figure 1

18 pages, 2493 KiB

Open AccessEditor’s ChoiceArticle

Use of Sawdust (Aspidosperma polyneuron) in the Preparation of a Biocarbon-Type Adsorbent Material for Its Potential Use in the Elimination of Cationic Contaminants in Wastewater

by Rodrigo Ortega-Toro, Ángel Villabona-Ortíz, Candelaria Tejada-Tovar, Adriana Herrera-Barros and Daniela Cabrales-Sanjuan

Water 2023, 15(21), 3868; https://doi.org/10.3390/w15213868 - 6 Nov 2023

Cited by 8 | Viewed by 1603

Abstract

Chemically modified bioadsorbents were prepared using sawdust (Aspidosperma polyneuron) functionalized with urea at different concentrations (BC-1M, BC-3M, and BC-6M) to evaluate their adsorption capacity by the methylene blue method. Fourier transform spectroscopy (FTIR) analysis and scanning electron microscopy (SEM) were employed to characterize [...] Read more.

Chemically modified bioadsorbents were prepared using sawdust (Aspidosperma polyneuron) functionalized with urea at different concentrations (BC-1M, BC-3M, and BC-6M) to evaluate their adsorption capacity by the methylene blue method. Fourier transform spectroscopy (FTIR) analysis and scanning electron microscopy (SEM) were employed to characterize the surface morphology of the biomaterials. The best adsorption capacity was obtained using the biocarbon modified with urea 6M (BC-6M), displaying a methylene blue index of 12.4 mg/g with a zero-charge point (pHpzc) at 5.5, suggesting the potential application of this chemically modified bioadsorbent for the removal of cationic contaminants in aqueous media. Full article

(This article belongs to the Section Wastewater Treatment and Reuse)

► Show Figures

Figure 1

12 pages, 725 KiB

Open AccessEditor’s ChoiceArticle

Circular Economy in Wastewater Treatment Plants—Potential Opportunities for Biogenic Elements Recovery

by Alina Dereszewska and Stanislaw Cytawa

Water 2023, 15(21), 3857; https://doi.org/10.3390/w15213857 - 6 Nov 2023

Cited by 7 | Viewed by 3342

Abstract

Technologies used in municipal wastewater treatment plants (WWTPs) allow the recovery of energy and valuable elements (phosphorus, nitrogen, and organic carbon) for the soil. This article presents, in schematic form, the carbon, nitrogen, and phosphorus cycling in a WWTP with a load of [...] Read more.

Technologies used in municipal wastewater treatment plants (WWTPs) allow the recovery of energy and valuable elements (phosphorus, nitrogen, and organic carbon) for the soil. This article presents, in schematic form, the carbon, nitrogen, and phosphorus cycling in a WWTP with a load of 70,000 Population Equivalent and develops a spreadsheet to estimate their recovery. Biogas generation enables the recovery of 1126 Mg of organic carbon per year and the generation of 12.6 GWh of energy. The most rational form of organic waste recycling is the production of compost with fertilizing parameters, but efforts should be made to reduce iron compounds in its composition. It has been estimated that compost production provides the recovery of 30% of carbon, 98% of phosphorus, and 18% of nitrogen from the streams of these elements entering the WWTP. The possibility of partially replacing the iron coagulants used to precipitate phosphorus with waste magnesium salt is presented, leading to the precipitation of struvite, which is well absorbed by plants. The article presents the advantages of combining sewage treatment with organic waste management in WWTPs. The developed spreadsheet allows for the control of energy recovery through the quantitative selection of organic waste for fermentation. Full article

(This article belongs to the Special Issue Biological Wastewater Treatment towards a Sustainable Circular Economy)

► Show Figures

Figure 1

13 pages, 9237 KiB

Open AccessEditor’s ChoiceArticle

Numerical Study on the Influence of Combined Rectification Facilities on the Flow in the Forebay of Pumping Station

by Xiaobo Zheng, Pengli Zhang, Wenjing Zhang, Yue Yu and Yaping Zhao

Water 2023, 15(21), 3847; https://doi.org/10.3390/w15213847 - 3 Nov 2023

Cited by 6 | Viewed by 1506

Abstract

The flow pattern of the forebay of the pumping station has a considerable effect on the operating efficiency and stability of the pump unit. A good forebay flow pattern can enable the pump unit to improve efficiency and operating conditions. This study takes [...] Read more.

The flow pattern of the forebay of the pumping station has a considerable effect on the operating efficiency and stability of the pump unit. A good forebay flow pattern can enable the pump unit to improve efficiency and operating conditions. This study takes a large pumping station as the research object and considers two rectification schemes, namely, a single bottom sill and a “bottom sill + diversion pier”. Without rectification facilities under different start-up schemes, the forebay flow pattern after the addition of rectification facilities is calculated, and the influence of single and combined rectification facilities is analyzed. Results show large-scale undesirable flow structures such as backflow and vortex in the forebay of the original design that without rectification facilities and uneven flow distribution occurs in the operating unit. The addition of a bottom sill in the forebay can control the central water beam from the water diversion pipe. The flow is divided to spread to both sides of the forebay and can be rectified twice after installing the diversion piers. The combined rectifier facility of “bottom sill + diversion pier” is beneficial to disperse incoming flow and make the flow distribution of each unit more uniform. The backflow and vortex inside the forepond are basically eliminated, and the flow state of the forepond is significantly improved. Full article

(This article belongs to the Special Issue Advances in Hydrodynamics of Water Pump Station System)

► Show Figures

Figure 1

24 pages, 8585 KiB

Open AccessEditor’s ChoiceReview

Biological Invasions in Fresh Waters: Micropterus salmoides, an American Fish Conquering the World

by Maria Letizia Costantini, Jerzy Piotr Kabala, Simona Sporta Caputi, Matteo Ventura, Edoardo Calizza, Giulio Careddu and Loreto Rossi

Water 2023, 15(21), 3796; https://doi.org/10.3390/w15213796 - 30 Oct 2023

Cited by 7 | Viewed by 4010

Abstract

Biological invasions in fresh waters cause biodiversity loss and impairment of ecosystem functioning. Many freshwater invasive species are fish, including the largemouth bass Micropterus salmoides, which is considered one of the 100 worst invasive species in the world. Fast individual growth rates, [...] Read more.

Biological invasions in fresh waters cause biodiversity loss and impairment of ecosystem functioning. Many freshwater invasive species are fish, including the largemouth bass Micropterus salmoides, which is considered one of the 100 worst invasive species in the world. Fast individual growth rates, high dispersal ability, ecological tolerance, and trophic plasticity are among the characteristics contributing to its success. The negative impact of M. salmoides on littoral fish communities is believed to be mitigated by habitat structural complexity resulting from aquatic vegetation and coarse woody debris, while the main limits on its spread seem to be strong water flows and high turbidity, which impairs visual predation. Together with the human overexploitation of its potential fish antagonists, habitat alteration could result in M. salmoides having seriously detrimental effects on native biodiversity. The purpose of this study is to critically review the life history and ecology of M. salmoides, its impact on ecosystems outside North America, and the effects of anthropogenic activities on its spread. This will highlight environmental factors that favor or limit its invasive success, helping to identify management measures that might mitigate its negative effects on freshwater biodiversity. Full article

► Show Figures

Figure 1

21 pages, 4621 KiB

Open AccessEditor’s ChoiceReview

Surface Velocity to Depth-Averaged Velocity—A Review of Methods to Estimate Alpha and Remaining Challenges

by Hamish Biggs, Graeme Smart, Martin Doyle, Niklas Eickelberg, Jochen Aberle, Mark Randall and Martin Detert

Water 2023, 15(21), 3711; https://doi.org/10.3390/w15213711 - 24 Oct 2023

Cited by 10 | Viewed by 3814

Abstract

The accuracy of discharge measurements derived from surface velocities are highly dependent on the accuracy of conversions from surface velocity

u_{s}

to depth-averaged velocity

U

. This conversion factor is typically known as the ‘velocity coefficient’, ‘velocity index’, ‘calibration factor’, ‘alpha coefficient’, [...] Read more.

The accuracy of discharge measurements derived from surface velocities are highly dependent on the accuracy of conversions from surface velocity

u_{s}

to depth-averaged velocity

U

. This conversion factor is typically known as the ‘velocity coefficient’, ‘velocity index’, ‘calibration factor’, ‘alpha coefficient’, or simply ‘alpha’, where

α = {U / u}_{s}

. At some field sites detailed in situ measurements can be made to calculate alpha, while in other situations (such as rapid response flood measurements) alpha must be estimated. This paper provides a review of existing methods for estimating alpha and presents a workflow for selecting the appropriate method, based on available data. Approaches to estimating alpha include: reference discharge and surface velocimetry measurements; extrapolated ADCP velocity profiles; log law profiles; power law profiles; site characteristics; and default assumed values. Additional methods for estimating alpha that require further development or validation are also described. This paper then summarises methods for accounting for spatial and temporal heterogeneity in alpha, such as ‘stage to alpha rating curves’, ‘site alpha vs. local alpha’, and ‘the divided channel method’. Remaining challenges for the accurate estimation of alpha are discussed, as well as future directions that will help to address these challenges. Although significant work remains to improve the estimation of alpha (notably to address surface wind effects and velocity dip), the methods covered in this paper could provide a substantial accuracy improvement over selecting the ‘default value’ of 0.857 for alpha for every discharge measurement. Full article

(This article belongs to the Special Issue River Flow Monitoring: Needs, Advances and Challenges)

► Show Figures

Figure 1

19 pages, 5828 KiB

Open AccessEditor’s ChoiceArticle

Assessing the Water–Energy–Food Nexus and Resource Sustainability in the Ardabil Plain: A System Dynamics and HWA Approach

by Kazem Javan, Ali Altaee, Mariam Darestani, Mehrdad Mirabi, Farshad Azadmanesh, John L. Zhou and Hanieh Hosseini

Water 2023, 15(20), 3673; https://doi.org/10.3390/w15203673 - 20 Oct 2023

Cited by 3 | Viewed by 2105

Abstract

Ardabil Plain, which holds significant political and economic importance in agricultural production in Iran, has faced various challenges including climate change, economic sanctions, and limited access to global trade. Ensuring food security has become a key priority for the region. The main objective [...] Read more.

Ardabil Plain, which holds significant political and economic importance in agricultural production in Iran, has faced various challenges including climate change, economic sanctions, and limited access to global trade. Ensuring food security has become a key priority for the region. The main objective of this research is to identify a suitable crop for this critical region with regard to future climate change conditions. This study employs a new framework of the system dynamics model (SDM) and the Hybrid Weighted Averaging (HWA) method to assess the Water–Energy–Food (WEF) nexus and resource sustainability in the Ardabil Plain under different climate change scenarios (RCP 2.6, RCP 4.5, and RCP 8.5). The research addresses current and future water challenges, emphasizing the need for additional energy and selecting optimal crops. Using the SDM, the study analyzes the impact of water supply fluctuations on agriculture, economic gain, and energy consumption from 2021 to 2050. The results indicate that barley is the most suitable crop for the Ardabil Plain in the near future, based on the overall ranking derived from the HWA method, which is as follows: barley > wheat > soybeans > potatoes > pears. The study highlights the significant challenges in energy supply for agriculture due to declining water levels and the increased force required by pumps to supply water to farms. These findings provide valuable insights for policymakers and stakeholders to make informed decisions in addressing water scarcity and rising energy demands in the Ardabil Plain. Full article

(This article belongs to the Special Issue Sustainable Developments Goals: Water and Wastewater Management)

► Show Figures

Figure 1

14 pages, 4690 KiB

Open AccessEditor’s ChoiceArticle

Automatic Extraction Method of Aquaculture Sea Based on Improved SegNet Model

by Weiyi Xie, Yuan Ding, Xiaoping Rui, Yarong Zou and Yating Zhan

Water 2023, 15(20), 3610; https://doi.org/10.3390/w15203610 - 16 Oct 2023

Cited by 4 | Viewed by 2024

Abstract

Timely, accurate, and efficient extraction of aquaculture sea is important for the scientific and rational utilization of marine resources and protection of the marine environment. To improve the classification accuracy of remote sensing of aquaculture seas, this study proposes an automatic extraction method [...] Read more.

Timely, accurate, and efficient extraction of aquaculture sea is important for the scientific and rational utilization of marine resources and protection of the marine environment. To improve the classification accuracy of remote sensing of aquaculture seas, this study proposes an automatic extraction method for aquaculture seas based on the improved SegNet model. This method adds a pyramid convolution module and a convolutional block attention module based on the SegNet network model, which can effectively increase the utilization ability of features and capture more global image information. Taking the Gaofen-1D image as an example, the effectiveness of the improved method was proven through ablation experiments on the two modules. The prediction results of the proposed method were compared with those of the U-Net, SegNet, and DenseNet models, as well as with those of the traditional support vector machine and random forest methods. The results showed that the improved model has a stronger generalization ability and higher extraction accuracy. The overall accuracy, mean intersection over union, and F1 score of the three test areas were 94.86%, 87.23%, and 96.59%, respectively. The accuracy of the method is significantly higher than those of the other methods, which proves the effectiveness of the method for the extraction of aquaculture seas and provides new technical support for automatic extraction of such areas. Full article

(This article belongs to the Special Issue The Interrelationship between Climate Change, Human Activities and Hydrological Processes, Volume II)

► Show Figures

Figure 1

17 pages, 3331 KiB

Open AccessEditor’s ChoiceArticle

A Machine Learning Framework for Enhancing Short-Term Water Demand Forecasting Using Attention-BiLSTM Networks Integrated with XGBoost Residual Correction

by Shihao Shan, Hongzhen Ni, Genfa Chen, Xichen Lin and Jinyue Li

Water 2023, 15(20), 3605; https://doi.org/10.3390/w15203605 - 15 Oct 2023

Cited by 10 | Viewed by 2455

Abstract

Accurate short-term water demand forecasting assumes a pivotal role in optimizing water supply control strategies, constituting a cornerstone of effective water management. In recent times, the rise of machine learning technologies has ushered in hybrid models that exhibit superior performance in this domain. [...] Read more.

Accurate short-term water demand forecasting assumes a pivotal role in optimizing water supply control strategies, constituting a cornerstone of effective water management. In recent times, the rise of machine learning technologies has ushered in hybrid models that exhibit superior performance in this domain. Given the intrinsic non-linear fluctuations and variations in short-term water demand sequences, achieving precise forecasts presents a formidable challenge. Against this backdrop, this study introduces an innovative machine learning framework for short-term water demand prediction. The maximal information coefficient (MIC) is employed to select high-quality input features. A deep learning architecture is devised, featuring an Attention-BiLSTM network. This design leverages attention weights and the bidirectional information in historical sequences to highlight influential factors and enhance predictive capabilities. The integration of the XGBoost algorithm as a residual correction module further bolsters the model’s performance by refining predicted results through error simulation. Hyper-parameter configurations are fine-tuned using the Keras Tuner and random parameter search. Through rigorous performance comparison with benchmark models, the superiority and stability of this method are conclusively demonstrated. The attained results unequivocally establish that this approach outperforms other models in terms of predictive accuracy, stability, and generalization capabilities, with MAE, RMSE, MAPE, and NSE values of 544 m³/h, 915 m³/h, 1.00%, and 0.99, respectively. The study reveals that the incorporation of important features selected by the MIC, followed by their integration into the attention mechanism, essentially subjects these features to a secondary filtration. While this enhances model performance, the potential for improvement remains limited. Our proposed forecasting framework offers a fresh perspective and contribution to the short-term water resource scheduling in smart water management systems. Full article

► Show Figures

Figure 1

20 pages, 15137 KiB

Open AccessEditor’s ChoiceArticle

Groundwater Level Dynamic Impacted by Land-Cover Change in the Desert Regions of Tarim Basin, Central Asia

by Wanrui Wang, Yaning Chen, Weihua Wang, Yapeng Chen and Yifeng Hou

Water 2023, 15(20), 3601; https://doi.org/10.3390/w15203601 - 14 Oct 2023

Cited by 5 | Viewed by 2556

Abstract

Groundwater is essential to residents, ecology, agriculture, and industry. The depletion of groundwater impacted by climatic variability and intense human activities could threaten water, food, and socioeconomic security in arid regions. A thorough understanding of groundwater level dynamics and its response to land-cover [...] Read more.

Groundwater is essential to residents, ecology, agriculture, and industry. The depletion of groundwater impacted by climatic variability and intense human activities could threaten water, food, and socioeconomic security in arid regions. A thorough understanding of groundwater level dynamics and its response to land-cover change is necessary for groundwater management and ecosystem improvement, which are poorly understood in arid desert regions due to a scarcity of field monitoring data. In our study, spatiotemporal characteristics of groundwater level impacted by land-cover change and its relationship with vegetation were examined using 3-years in-situ monitoring data of 30 wells in the desert regions of Tarim Basin during 2019–2021. The results showed that the depth to groundwater level (DGL) exhibited obvious spatial and seasonal variations, and the fluctuation of DGL differed significantly among the wells. The cultivated land area increased by 1174.6, 638.0, and 732.2 km² during 2000–2020 in the plains of Yarkand, Weigan-Kuqa, and Dina Rivers, respectively, mainly transferring from bare land and grassland. Annual average Normalized Difference Vegetation Index (NDVI) values increased with time during the period in the plains. DGL generally exhibited a weakly increasing trend from 2019 to 2021, mainly due to human activities. Land-cover change significantly affected the groundwater level dynamic. Generally, the groundwater system was in negative equilibrium near the oasis due to agricultural irrigation, was basically in dynamic equilibrium in the desert region, and was in positive equilibrium near the Tarim River Mainstream due to irrigation return water and streamflow. NDVI of natural desert vegetation was negatively correlated with DGL in the desert regions (R² = 0.78, p < 0.05). Large-scale land reclamation and groundwater overexploitation associated with water-saving irrigation agriculture development have caused groundwater level decline in arid oasis-desert regions. Hence, controlling groundwater extraction intensity, strengthening groundwater monitoring, and promoting water-saving technology would be viable methods to sustainably manage groundwater and maintain the ecological environment in arid areas. Full article

(This article belongs to the Special Issue Water Management in Arid and Semi-arid Regions)

► Show Figures

Figure 1

20 pages, 4634 KiB

Open AccessEditor’s ChoiceArticle

Experimental Study on Mode I Fracture Characteristics of Granite after Low Temperature Cooling with Liquid Nitrogen

by Linchao Wang, Yi Xue, Zhengzheng Cao, Hailing Kong, Jianyong Han and Zhizhen Zhang

Water 2023, 15(19), 3442; https://doi.org/10.3390/w15193442 - 30 Sep 2023

Cited by 47 | Viewed by 2612

Abstract

Liquid nitrogen fracturing has emerged as a promising technique in fluid fracturing, providing significant advantages for the utilization and development of geothermal energy. Similarly to hydraulic fracturing in reservoirs, liquid nitrogen fracturing entails a common challenge of fluid–rock interaction, encompassing the permeation and [...] Read more.

Liquid nitrogen fracturing has emerged as a promising technique in fluid fracturing, providing significant advantages for the utilization and development of geothermal energy. Similarly to hydraulic fracturing in reservoirs, liquid nitrogen fracturing entails a common challenge of fluid–rock interaction, encompassing the permeation and diffusion processes of fluids within rock pores and fractures. Geomechanical analysis plays a crucial role in evaluating the transfer and diffusion capabilities of fluids within rocks, enabling the prediction of fracturing outcomes and fracture network development. This technique is particularly advantageous for facilitating heat exchange with hot dry rocks and inducing fractures within rock formations. The primary objective of this study is to examine the effects of liquid nitrogen fracturing on hot dry rocks, focusing specifically on granite specimens. The experimental design comprises two sets of granite samples to explore the impact of liquid nitrogen cooling cycles on the mode I fracture characteristics, acoustic emission features, and rock burst tendency of granite. By examining the mechanical properties, acoustic emission features, and rock burst tendencies under different cycling conditions, the effectiveness of liquid nitrogen fracturing technology is revealed. The results indicate that: (1) The ultimate load-bearing capacity of the samples gradually decreases with an increase in the number of cycling times. (2) The analysis of acoustic emission signals reveals a progressive increase in the cumulative energy of the samples with cycling times, indicating that cycling stimulates the release of stored energy within the samples. (3) After undergoing various cycling treatments, the granite surface becomes rougher, exhibiting increased porosity and notable mineral particle detachment. These results suggest that the cyclic application of high-temperature heating and liquid nitrogen cooling promotes the formation of internal fractures in granite. This phenomenon is believed to be influenced by the inherent heterogeneity and expansion–contraction of internal particles. Furthermore, a detailed analysis of the morphological sections provides insights into the structural changes induced by liquid nitrogen fracturing in granite samples. Full article

(This article belongs to the Special Issue Advances in Water–Rock Interactions and Thermo-Hydro-Mechanical Processes)

► Show Figures

Figure 1

17 pages, 3185 KiB

Open AccessEditor’s ChoiceArticle

Effect of pH, COD, and HRT on the Performance of Microbial Fuel Cell Using Synthetic Dairy Wastewater

by Aritro Banerjee, Rajnish Kaur Calay and Subhashis Das

Water 2023, 15(19), 3472; https://doi.org/10.3390/w15193472 - 30 Sep 2023

Cited by 12 | Viewed by 2900

Abstract

Microbial fuel cells (MFC) are emerging technologies that can produce electricity while treating wastewater. A series of tests were carried out to evaluate the efficiency of this technology for treating dairy wastewater (DWW). The experiments used Shewanella baltica as an exoelectrogen in a [...] Read more.

Microbial fuel cells (MFC) are emerging technologies that can produce electricity while treating wastewater. A series of tests were carried out to evaluate the efficiency of this technology for treating dairy wastewater (DWW). The experiments used Shewanella baltica as an exoelectrogen in a small single MFC to treat simulated DWW. The impacts of various operational factors, specifically pH, hydraulic retention time (HRT), and chemical oxygen demand (COD) in the influent to the anode chamber, were investigated, and the effect of these variables on the output performance of the cell was evaluated. The best performance of the MFC was found when the pH, HRT, and COD were 8, 6.66 h, and 20,632 mg/L, respectively, in the scaled experimental setup. Under these conditions, the maximum power density and percentage removal of COD in terms of wastewater treatment ability were found to be 138 mW/m² and 71%, respectively. It may be concluded that MFCs are suitable treatment technologies for treating dairy wastewater while potentially simultaneously generating power. Full article

(This article belongs to the Special Issue Biological Wastewater Treatment around the Globe)

► Show Figures

Graphical abstract

21 pages, 23300 KiB

Open AccessEditor’s ChoiceArticle

Cloud Modelling of Property-Level Flood Exposure in Megacities

by Christos Iliadis, Vassilis Glenis and Chris Kilsby

Water 2023, 15(19), 3395; https://doi.org/10.3390/w15193395 - 27 Sep 2023

Cited by 4 | Viewed by 1979

Abstract

Surface water flood risk is projected to increase worldwide due to the growth of cities as well as the frequency of extreme rainfall events. Flood risk modelling at high resolution in megacities is now feasible due to the advent of high spatial resolution [...] Read more.

Surface water flood risk is projected to increase worldwide due to the growth of cities as well as the frequency of extreme rainfall events. Flood risk modelling at high resolution in megacities is now feasible due to the advent of high spatial resolution terrain data, fast and accurate hydrodynamic models, and the power of cloud computing platforms. Analysing the flood exposure of urban features in these cities during multiple storm events is essential to understanding flood risk for insurance and planning and ultimately for designing resilient solutions. This study focuses on London, UK, a sprawling megacity that has experienced damaging floods in the last few years. The analysis highlights the key role of accurate digital terrain models (DTMs) in hydrodynamic models. Flood exposure at individual building level is evaluated using the outputs from the CityCAT model driven by a range of design storms of different magnitudes, including validation with observations of a real storm event that hit London on the 12 July 2021. Overall, a novel demonstration is presented of how cloud-based flood modelling can be used to inform exposure insurance and flood resilience in cities of any size worldwide, and a specification is presented of what datasets are needed to achieve this aim. Full article

(This article belongs to the Special Issue Water Supplies, Sewerage and Stormwater Networks: New Challenges and Advances in Modelling and Management)

► Show Figures

Figure 1

23 pages, 9543 KiB

Open AccessEditor’s ChoiceArticle

Basin-Scale Hydraulic Evaluation of Groundwater Flow Controlled Biogenic Gas Migration and Accumulation in the Central Pannonian Basin

by Brigitta Czauner, Zsóka Szabó, Béla Márton and Judit Mádl-Szőnyi

Water 2023, 15(18), 3272; https://doi.org/10.3390/w15183272 - 15 Sep 2023

Cited by 4 | Viewed by 1375

Abstract

Biogenic or microbial methane has an increasing share in the global gas resource base, though its exploration still faces challenges and welcomes innovations. Critical elements of its migration and accumulation models are the groundwater flows which gather and transport the gas in aqueous [...] Read more.

Biogenic or microbial methane has an increasing share in the global gas resource base, though its exploration still faces challenges and welcomes innovations. Critical elements of its migration and accumulation models are the groundwater flows which gather and transport the gas in aqueous solution, and the seal rocks or aquifers which lead groundwater flows horizontally over great distances. This paper intends to introduce the hydraulic trap concept into these models, which is able to drive fluids horizontally without an overlying seal rock. Since hydraulic traps can evolve as a result of the interplay of regional groundwater flow systems, the basin-scale hydraulic evaluation methodology which was developed for the analysis of these systems was further improved by this study to focus on their interplay. The improved methodology was applied on measured hydraulic data in a study area in the Central Pannonian Basin (Hungary) around the Hajdúszoboszló gas field where as a result, the first groundwater flow controlled dissolved biogenic gas migration and accumulation model could be set up. In addition, the proposed methodology can be used in any terrestrial sedimentary basin, and in particular, where topography-driven flow systems are underlaid by an abnormal pressure regime. Full article

(This article belongs to the Special Issue Regional Groundwater Flow Concept and Its Potential for Interdisciplinary Application)

► Show Figures

Figure 1

22 pages, 5749 KiB

Open AccessEditor’s ChoiceArticle

CMADS and CFSR Data-Driven SWAT Modeling for Impacts of Climate and Land-Use Change on Runoff

by Bailin Du, Lei Wu, Bingnan Ruan, Liujia Xu and Shuai Liu

Water 2023, 15(18), 3240; https://doi.org/10.3390/w15183240 - 12 Sep 2023

Cited by 6 | Viewed by 1769

Abstract

Climate and land-use change significantly impact hydrological processes and water resources management. However, studies of runoff simulation accuracy and attribution analysis in large-scale basins based on multi-source data and different scenario projections are limited. This study employed the Soil and Water Assessment Tool [...] Read more.

Climate and land-use change significantly impact hydrological processes and water resources management. However, studies of runoff simulation accuracy and attribution analysis in large-scale basins based on multi-source data and different scenario projections are limited. This study employed the Soil and Water Assessment Tool (SWAT) model in conjunction with spatial interpolation techniques to evaluate the accuracy of Climate Forecast System Reanalysis (CFSR), China Meteorological Assimilation Driven Dataset (CMADS), and observation (OBS) in runoff simulations, and configured various scenarios using the Patch-generating Land-use Simulation (PLUS) model to analyze effects of climate and land-use changes on runoff in the Jing River Basin from 1999 to 2018. Results demonstrated the superior performance of the CMADS+SWAT model compared to than CFSR+SWAT model, as the latter underestimated peak runoff. Changes in precipitation had a stronger impact on runoff than temperature, with increased flow from farmland and strong interception effects from forestland. Integrated climate and land-use changes led to an average annual runoff reduction of 1.24 m³/s (I₂), primarily attributed to climate change (1.12 m³/s, I₃), with a small contribution from land-use change (0.12 m³/s, I₄). CMADS exhibited robust applicability under diverse scenarios, effectively enhancing runoff simulation accuracy. The findings provide invaluable guidance for water resources management in semi-arid regions. Full article

► Show Figures

Figure 1

21 pages, 3671 KiB

Open AccessEditor’s ChoiceArticle

Anaerobic Membrane Bioreactor for Microalgae and Primary Sludge Co-Digestion at Pilot Scale: Instrumentation, Control and Automation Implementation, and Performance Assessment

by Juan Francisco Mora-Sánchez, Rebecca Serna-García, Alberto Bouzas, Aurora Seco and Maria Victoria Ruano

Water 2023, 15(18), 3225; https://doi.org/10.3390/w15183225 - 11 Sep 2023

Cited by 5 | Viewed by 2314

Abstract

Anaerobic membrane bioreactor (AnMBR) technology is gaining interest for circular economy integration in the water sector. However, its complexity, arising from the integration of anaerobic processes with membrane technology, poses a key challenge. Developing an appropriate instrumentation, control, and automation (ICA) system is [...] Read more.

Anaerobic membrane bioreactor (AnMBR) technology is gaining interest for circular economy integration in the water sector. However, its complexity, arising from the integration of anaerobic processes with membrane technology, poses a key challenge. Developing an appropriate instrumentation, control, and automation (ICA) system is essential for its reliable long-term operation. In this study, an ICA system was developed to successfully manage an AnMBR pilot plant co-digesting two waste streams (microalgae and primary sludge). The ICA implementation enabled its stable long-term operation for 576 days, ensuring the proper performance of biological and filtration processes and yielding 215 NmLCH₄·gCOD_inf⁻¹ at 35 °C. Variables such as temperature, oxidation-reduction potential, permeate flux and biogas flow were identified as key parameters and controlled. This included a 23% reduction in the integral of absolute error compared to a PID controller for permeate flow and the maintenance of a 0.5% standard deviation for digester temperature. These controls enabled AnMBR performance optimization, the rapid detection of process issues, and early corrective actions. As a start-up strategy to ensure proper filtration performance in the long term, critical flux tests were conducted, guaranteeing a competitive total annualized equivalent cost of 0.0016 EUR/m³ for optimal conditions. The study also calculated greenhouse gas emissions in different scenarios, proposing optimal and more sustainable pilot plant operations, mesophilic conditions, biogas upgrading through microalgae cultivation, and grid injection, reducing emissions by 423 kgCO₂e·tCOD⁻¹. To ensure the viability of emerging technologies such as AnMBR, proper start-up protocols are crucial, including favorable filtration and biological process operating conditions, ICA implementation, and key parameter control for technical, economic and environmental success. Full article

(This article belongs to the Special Issue The Role of Anaerobic MBR for Resources Recovery in a Circular Economy Context)

► Show Figures

Graphical abstract

20 pages, 1731 KiB

Open AccessEditor’s ChoiceReview

A Review of Non-Contact Water Level Measurement Based on Computer Vision and Radar Technology

by Zeheng Wu, Yu Huang, Kailin Huang, Kang Yan and Hua Chen

Water 2023, 15(18), 3233; https://doi.org/10.3390/w15183233 - 11 Sep 2023

Cited by 6 | Viewed by 6142

Abstract

As pioneering non-contact water level measurement technologies, both computer vision and radar have effectively addressed challenges posed by traditional water level sensors in terms of maintenance cost, real-time responsiveness, and operational complexity. Moreover, they ensure high-precision measurements in appropriate conditions. These techniques can [...] Read more.

As pioneering non-contact water level measurement technologies, both computer vision and radar have effectively addressed challenges posed by traditional water level sensors in terms of maintenance cost, real-time responsiveness, and operational complexity. Moreover, they ensure high-precision measurements in appropriate conditions. These techniques can be seamlessly integrated into unmanned aerial vehicle (UAV) systems, significantly enhancing the spatiotemporal granularity of water level data. However, computer-vision-based water level measurement methods face the core problems of accurately identifying water level lines and elevation calculations, which can lead to measurement errors due to lighting variations and camera position offsets. Although deep learning has received much attention in improving the generation, the effectiveness of the models is limited by the diversity of the datasets. For the radar water level sensor, the hardware structure and signal processing algorithms have to be further improved. In the future, by constructing more comprehensive datasets, developing fast calibration algorithms, and implementing multi-sensor data fusion, it is expected that the robustness, accuracy, and computational efficiency of water level monitoring will be significantly improved, laying a solid foundation for further innovations and developments of hydrological monitoring. Full article

(This article belongs to the Special Issue High-Resolution Monitoring and Modelling for Water Resources Management: New Sensors, New Approaches and Applications)

► Show Figures

Figure 1

30 pages, 1247 KiB

Open AccessEditor’s ChoiceReview

Discrimination Methods of Mine Inrush Water Source

by Donglin Dong and Jialun Zhang

Water 2023, 15(18), 3237; https://doi.org/10.3390/w15183237 - 11 Sep 2023

Cited by 9 | Viewed by 2425

Abstract

Ensuring mining safety and efficiency relies heavily on identifying the source of mine water inrush. This review article aims to provide a comprehensive overview of standard methods used to pinpoint the origin of mine water inrush, highlighting the development and progress in the [...] Read more.

Ensuring mining safety and efficiency relies heavily on identifying the source of mine water inrush. This review article aims to provide a comprehensive overview of standard methods used to pinpoint the origin of mine water inrush, highlighting the development and progress in the research of discrimination methods. These methods are systematically classified into various categories, encompassing hydrochemistry examination, water level and temperature analysis, geostatistical approaches, machine learning and deep learning methods, as well as the utilization of other analytical techniques. The review not only presents a quantitative and visual analysis of the theoretical methods proposed by scholars but also emphasizes their strengths, weaknesses, and applicability to various mining operations. Furthermore, it explores the increasing utilization of artificial neural networks and machine learning algorithms in source discrimination models, indicating the advancement in this area of research. To further advance the field, specific examples of these methods and their effectiveness in identifying the source of mine water inrush are provided, aiming to stimulate further research. The article also offers detailed recommendations for future research directions and emerging trends, underlining the importance of comprehensive multidisciplinary and multi-method analysis. It suggests exploring emerging technologies such as the Internet of Things (IoT) and cloud computing, while emphasizing the need to develop more accurate and reliable models for source identification. The fusion of artificial intelligence (AI), heightened computational capabilities, online programming, and intelligent data collection systems presents the prospect of transforming the way industries respond to these critical events. By providing a comprehensive overview, analyzing the effectiveness of existing methods, and proposing future research directions, this review aims to contribute to the continuous development and progress of discrimination methods for mine water inrush incidents. Ultimately, it seeks to enhance mining safety and efficiency by facilitating the prompt and accurate identification of the sources of mine water inrush. Full article

(This article belongs to the Special Issue Recent Advances in Hydrogeology: Featured Reviews)

► Show Figures

Figure 1

14 pages, 2614 KiB

Open AccessEditor’s ChoiceArticle

Service Pressure and Energy Consumption Mitigation-Oriented Partitioning of Closed Water Distribution Networks

by Enrico Creaco, Carlo Giudicianni and Alessandro Tosco

Water 2023, 15(18), 3218; https://doi.org/10.3390/w15183218 - 10 Sep 2023

Cited by 3 | Viewed by 1290

Abstract

This paper presents the partitioning of the closed water distribution network (WDN) serving the city of Pavia, Italy. As a thus far poorly explored aspect in the scientific literature, clustering for the definition of size and extension of district metered areas (DMAs) and [...] Read more.

This paper presents the partitioning of the closed water distribution network (WDN) serving the city of Pavia, Italy. As a thus far poorly explored aspect in the scientific literature, clustering for the definition of size and extension of district metered areas (DMAs) and of inter-DMA boundary pipes is performed by ensuring that the DMAs respect the altimetric areas of the WDN by leaning on a modified formulation of modularity. To define the boundary pipes to be closed or alternatively fitted with a flow meter for the monitoring of DMA consumption, the dividing is performed with an innovative heuristic algorithm. This technique operates by sequentially implementing the boundary closures that do not cause significant head losses, to obtain an approximation of the Pareto front in the trade-off between number of flow meters installed and WDN reliability. In the last part of the work, the pumps present in the network are assumed to be equipped with the variable speed drive, and their hourly settings are optimized to regulate service pressure. Overall, WDN partitioning and pump setting optimization are proven to mitigate the service pressure and energy consumption of the WDN, offering evident and attractive benefits up to about 50% for water utilities. Full article

(This article belongs to the Special Issue Smart Technologies for Urban Water Systems)

► Show Figures

Figure 1

25 pages, 1509 KiB

Open AccessEditor’s ChoiceReview

Water Masses of the Mediterranean Sea and Black Sea: An Overview

by Serafeim E. Poulos

Water 2023, 15(18), 3194; https://doi.org/10.3390/w15183194 - 7 Sep 2023

Cited by 5 | Viewed by 6026

Abstract

This overview presents the different water masses present in the various primary and secondary marine regions of the Mediterranean Sea and Black Sea, providing information on their main physical characteristics (i.e., temperature, salinity, density), the water depths at which they have been observed [...] Read more.

This overview presents the different water masses present in the various primary and secondary marine regions of the Mediterranean Sea and Black Sea, providing information on their main physical characteristics (i.e., temperature, salinity, density), the water depths at which they have been observed and the processes involved in their formation. There is a characteristic difference in the overall hydrology of the Mediterranean Sea compared to the Black Sea, in terms of the number and characteristics of water masses and their formation processes, although they form a single (integrated) marine system. This difference is explained by the limited communication between the two seas through the Sea of Marmara and its straits (the Dardanelles and Bosporus) and by the fact that the Mediterranean Sea is a condensation basin while the Black Sea is a dilution basin; therefore, the deficit of water in the former is compensated by the inflow of Atlantic waters, while the surplus in the latter outflows to the Aegean Sea. In total, 21 different water masses have been identified in the Mediterranean Sea (excluding the Straits of Gibraltar and the Sea of Marmara) compared to the 5 water masses identified in the Black Sea (excluding the Sea of Azov). This large number of water masses is attributed to coastal morphology (i.e., presence of straits) and submarine relief (i.e., deep basin separated by shallow sills) and different formation processes. Full article

(This article belongs to the Topic Aquatic Environment Research for Sustainable Development)

► Show Figures

Figure 1

23 pages, 10543 KiB

Open AccessEditor’s ChoiceArticle

Impact of Vegetation Differences on Shallow Landslides: A Case Study in Aso, Japan

by Hiroki Asada and Tomoko Minagawa

Water 2023, 15(18), 3193; https://doi.org/10.3390/w15183193 - 7 Sep 2023

Cited by 7 | Viewed by 3470

Abstract

Climate change has increased the frequency and scale of heavy rainfall, increasing the risk of shallow landslides due to heavy rainfall. In recent years, ecosystem-based disaster risk reduction (Eco-DRR) has attracted attention as one way to reduce disaster risks. Vegetation is known to [...] Read more.

Climate change has increased the frequency and scale of heavy rainfall, increasing the risk of shallow landslides due to heavy rainfall. In recent years, ecosystem-based disaster risk reduction (Eco-DRR) has attracted attention as one way to reduce disaster risks. Vegetation is known to increase soil strength through its root system and reduce the risk of shallow landslides. To reduce the risk of shallow landslides using vegetation, it is necessary to quantitatively evaluate the effects that vegetation has on shallow landslides. In this study, we constructed a generalized linear model (GLM) and random forest (RF) model to quantitatively evaluate the impact of differences in the vegetation, such as grasslands and forests, on the occurrence of shallow landslides using statistical methods. The model that resulted in the lowest AIC in the GLM included elevation, slope angle, slope aspect, undulation, TWI, geology, and vegetation as primary factors, and the hourly rainfall as a trigger factor. The slope angle, undulation, and hourly rainfall were selected as significant explanatory variables that contribute positively to shallow landslides. On the other hand, elevation and TWI were selected as significant explanatory variables that contribute negatively to shallow landslides. Significant differences were observed among multiple categories of vegetation. The probability of shallow landslide in secondary grasslands was approximately three times that of coniferous and broadleaf forests, and approximately nine times that of broadleaf secondary forests. The landslide probability of shrubs was approximately four times that of coniferous and broadleaf forests, and approximately ten times that of broadleaf secondary forests. The results of constructing the RF model showed that the importance was highest for the hourly rainfall, followed by geology, then elevation. AUC values for the GLM and RF model were 0.91 and 0.95, respectively, indicating that highly accurate models were constructed. We quantitatively showed the impact of differences in vegetation on shallow landslides. The knowledge obtained in this study will be essential for considering appropriate vegetation management to reduce the risk of future shallow landslides. Full article

(This article belongs to the Topic Landslide Prediction, Monitoring and Early Warning)

► Show Figures

Figure 1

12 pages, 2681 KiB

Open AccessEditor’s ChoiceArticle

A Probabilistic Analysis of Drought Areal Extent Using SPEI-Based Severity-Area-Frequency Curves and Reanalysis Data

by Nunziarita Palazzolo, David J. Peres, Brunella Bonaccorso and Antonino Cancelliere

Water 2023, 15(17), 3141; https://doi.org/10.3390/w15173141 - 1 Sep 2023

Cited by 6 | Viewed by 1993

Abstract

Assessing and monitoring the spatial extent of drought is of key importance to forecasting the future evolution of drought conditions and taking timely preventive and mitigation measures. A commonly used approach in regional drought analysis involves spatially interpolating meteorological variables (e.g., rainfall depth [...] Read more.

Assessing and monitoring the spatial extent of drought is of key importance to forecasting the future evolution of drought conditions and taking timely preventive and mitigation measures. A commonly used approach in regional drought analysis involves spatially interpolating meteorological variables (e.g., rainfall depth during specific time intervals, deviation from long-term average rainfall) or drought indices (e.g., Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index) computed at specific locations. While plotting a drought descriptor against the corresponding percentage of affected areas helps visualize the historical extent of a drought, this approach falls short of providing a probabilistic characterization of the severity of spatial drought conditions. That can be overcome by identifying drought Severity-Area-Frequency (SAF) curves over a region, which establishes a link between drought features with a chosen probability of recurrence (or return period) and the corresponding proportion of the area experiencing those drought conditions. While inferential analyses can be used to estimate these curves, analytical approaches offer a better understanding of the main statistical features that drive the spatial evolution of droughts. In this research, a technique is introduced to mathematically describe the Severity-Area-Frequency (SAF) curves, aiming to probabilistically understand the correlation between drought severity, measured through the SPEI index, and the proportion of the affected region. This approach enables the determination of the area’s extent where SPEI values fall below a specific threshold, thus calculating the likelihood of observing SAF curves that exceed the observed one. The methodology is tested using data from the ERA5-Land reanalysis project, specifically studying the drought occurrences on Sicily Island, Italy, from 1950 to the present. Overall, findings highlight the improvements of incorporating the spatial interdependence of the assessed drought severity variable, offering a significant enhancement compared to the traditional approach for SAF curve derivation. Moreover, they validate the suitability of reanalysis data for regional drought analysis. Full article

(This article belongs to the Special Issue Drought Monitoring and Risk Assessment)

► Show Figures

Figure 1

19 pages, 651 KiB

Open AccessEditor’s ChoiceReview

A Review of Data Quality and Cost Considerations for Water Quality Monitoring at the Field Scale and in Small Watersheds

by Robert Daren Harmel, Heather Elise Preisendanz, Kevin Wayne King, Dennis Busch, Francois Birgand and Debabrata Sahoo

Water 2023, 15(17), 3110; https://doi.org/10.3390/w15173110 - 30 Aug 2023

Cited by 6 | Viewed by 3234

Abstract

Technological advances and resource constraints present scientists and engineers with renewed challenges in the design of methods to conduct water quality monitoring, and these decisions ultimately determine the degree of project success. Many professionals are exploring alternative lower-cost options because of cost constraints, [...] Read more.

Technological advances and resource constraints present scientists and engineers with renewed challenges in the design of methods to conduct water quality monitoring, and these decisions ultimately determine the degree of project success. Many professionals are exploring alternative lower-cost options because of cost constraints, and research and development is largely focused on in situ sensors that produce high temporal resolution data. While some guidance is available, contemporary information is needed to balance water quality monitoring decisions with financial and personnel constraints, while meeting data quality needs. This manuscript focuses on monitoring constituents, such as sediment, nutrients, and pathogens, at the field scale and in small watersheds. Specifically, the impacts on the costs and data quality of alternatives related to site selection, discharge measurement, and constituent concentration measurement, are explored. The present analysis showed that avoiding sites requiring extensive berm construction and the installation of electric power to reach distant sites greatly reduces the initial costs with little impact on data quality; however, other decisions directly impact data quality. For example, proper discharge measurement, high-frequency sampling, frequent site and equipment maintenance, and the purchase of backup power and monitoring equipment can be costly, but are important for high quality data collection. In contrast, other decisions such as the equipment type (mechanical samplers, electronic samplers, or in situ sensors) and whether to analyze discrete or composite samples greatly affect the costs, but have minimal impact on data quality. These decisions, therefore, can be based on other considerations (e.g., project goals, intended data uses, funding agency specifications, and agency protocols). We hope this guidance helps practitioners better design and implement water quality monitoring to satisfy resource constraints and data quality needs. Full article

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

► Show Figures

Figure 1

21 pages, 9916 KiB

Open AccessEditor’s ChoiceArticle

Groundwater Level Prediction with Deep Learning Methods

by Hsin-Yu Chen, Zoran Vojinovic, Weicheng Lo and Jhe-Wei Lee

Water 2023, 15(17), 3118; https://doi.org/10.3390/w15173118 - 30 Aug 2023

Cited by 11 | Viewed by 4574

Abstract

The development of civilization and the preservation of environmental ecosystems are strongly dependent on water resources. Typically, an insufficient supply of surface water resources for domestic, industrial, and agricultural needs is supplemented with groundwater resources. However, groundwater is a natural resource that must [...] Read more.

The development of civilization and the preservation of environmental ecosystems are strongly dependent on water resources. Typically, an insufficient supply of surface water resources for domestic, industrial, and agricultural needs is supplemented with groundwater resources. However, groundwater is a natural resource that must accumulate over many years and cannot be recovered after a short period of recharge. Therefore, the long-term management of groundwater resources is an important issue for sustainable development. The accurate prediction of groundwater levels is the first step in evaluating total water resources and their allocation. However, in the process of data collection, data may be lost due to various factors. Filling in missing data is a main problem that any research field must address. It is well known that to maintain data integrity, one effective approach is missing value imputation (MVI). In addition, it has been demonstrated that machine learning may be a better tool. Therefore, the main purpose of this study was to utilize a generative adversarial network (GAN) that consists of a generative model and a discriminative model for imputation. Although the GAN could not capture the groundwater level endpoints in every section, the overall simulation performance was still excellent to some extent. Our results show that the GAN can improve the accuracy of water resource evaluations. In the current study, two interdisciplinary deep learning methods, univariate and Seq2val (sequence-to-value), were used for groundwater level estimation. In addition to addressing the significance of the parameter conditions, the advantages and disadvantages of these two models in hydrological simulations were also discussed and compared. Regarding parameter selection, the simulation results for univariate analysis were better than those for Seq2val analysis. Finally, univariate was employed to examine the limits of the models in long-term water level simulations. Our results suggest that the accuracy of CNNs is better, while LSTM is better for the simulation of multistep prediction. Therefore, the interdisciplinary deep learning approach may be beneficial for providing a better evaluation of water resources. Full article

(This article belongs to the Section Hydrogeology)

► Show Figures

Figure 1

13 pages, 2116 KiB

Open AccessEditor’s ChoiceArticle

Analysis of the Coupling Relationship between Water Quality and Economic Development in Hongjiannao Basin, China

by Xiaoping Liu, Shengdong Cheng, Ziyao Miao, Zhanbin Li, Peng Li, Tong Liu, Hegang Zhi, Shen Zhang, Yifan Wang and Xing Zheng

Water 2023, 15(16), 2965; https://doi.org/10.3390/w15162965 - 17 Aug 2023

Cited by 6 | Viewed by 1520

Abstract

Hongjiannao is the largest inland lake in China’s deserts. In recent years, the water quality and area of the Hongjiannao Lake have continued to decline, which is closely associated with the economic development in the Hongjiannao basin. To explore the coupling relationship between [...] Read more.

Hongjiannao is the largest inland lake in China’s deserts. In recent years, the water quality and area of the Hongjiannao Lake have continued to decline, which is closely associated with the economic development in the Hongjiannao basin. To explore the coupling relationship between the water quality and economic development in the Hongjiannao basin, the water quality and economic development index of the basin has been analyzed in terms of the monthly water quality and socio-economic development from 2013 to 2020. The coupling relationship and interaction mechanism between water quality and regional economic development has been studied by coupling coordination degree model. The results show that the water pollution increased and then decreased with the seasons, while the water quality was the worst in the summer. The coordinated degree between the water quality and economic development in Hongjiannao shows an upward trend from 2013 to 2020, which has transformed from the process of lagging economic development to the process of primary coordination, finally to the process of lagging water environment. The coupling relationship between water quality and economic development changed from a state of nearly un-coordination to primary coordination from 2013 to 2016, with economic development lagging behind. The coupling relationship between the two systems changed from barely coordinated to the primary coordinated from 2017 to 2018, with the rapid development of economy and slight decline in water quality. After 2018, those two systems gradually stepped into a virtuous cycle during 2019–2020, but the phenomenon of lagging water quality still existed. Therefore, in order to maintain the stable economic development of resource-based cities, it is necessary to keep improving the current situation of water environment and water shortage in Hongjiannao, which will promote the coordinated and sustainable development of water environment and economy. Full article

(This article belongs to the Special Issue Effects of Hydrology on Soil Erosion and Soil Conservation)

► Show Figures

Figure 1

30 pages, 841 KiB

Open AccessEditor’s ChoiceReview

Are Indicator Microorganisms Predictive of Pathogens in Water?

by Lisa Richiardi, Cristina Pignata, Elisabetta Fea, Silvia Bonetta and Elisabetta Carraro

Water 2023, 15(16), 2964; https://doi.org/10.3390/w15162964 - 17 Aug 2023

Cited by 12 | Viewed by 4607

Abstract

The microbiological quality assessment of drinking water (DW) and drinking water sources (DWSs) is based on the detection of indicator microorganisms (IMs). However, the relationship between IMs and pathogens has been questioned, as pathogens have been detected even in the absence of IMs, [...] Read more.

The microbiological quality assessment of drinking water (DW) and drinking water sources (DWSs) is based on the detection of indicator microorganisms (IMs). However, the relationship between IMs and pathogens has been questioned, as pathogens have been detected even in the absence of IMs, and vice versa. Therefore, the aim of this review was to evaluate the reliability of IMs by analysing the correlation between the presence of IMs and pathogens in water. This review focused on studies that reported statistical analyses of the relationship between traditional and alternative IMs and enteric pathogens in DWSs (groundwater, surface water, and rainwater) and in DW. Additionally, the main DW guidelines and regulations, along with a focus on the application of Quantitative Microbial Risk Assessment (QMRA), were also reported. The overall analysis of publications revealed a controversial correlation, characterised by high spatiotemporal variability, indicating the impossibility of identifying a reliable IM for any specific pathogen or water type. The association was also influenced by numerous factors, such as intrinsic characteristics of microorganisms, seasonal variations, sample number, water sample volume, and the detection method used. In conclusion, the detection of IMs should be considered complementary to, rather than a substitute for, the detection of pathogens. Full article

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

► Show Figures

Figure 1

15 pages, 3830 KiB

Open AccessEditor’s ChoiceArticle

Rapid Urbanization Has Changed the Driving Factors of Groundwater Chemical Evolution in the Large Groundwater Depression Funnel Area of Northern China

by Long Wang, Qianqian Zhang and Huiwei Wang

Water 2023, 15(16), 2917; https://doi.org/10.3390/w15162917 - 12 Aug 2023

Cited by 5 | Viewed by 1536

Abstract

With the rapid development of urbanization, the chemical evolution of groundwater has been significantly affected by human activities. However, the driving mechanisms of groundwater chemical evolution at different stages of urbanization are still unclear, which severely affects the implementation of groundwater protection. This [...] Read more.

With the rapid development of urbanization, the chemical evolution of groundwater has been significantly affected by human activities. However, the driving mechanisms of groundwater chemical evolution at different stages of urbanization are still unclear, which severely affects the implementation of groundwater protection. This study investigated the driving mechanisms of groundwater chemical evolution based on the long-term series (from 1985 to 2015) of hydrochemical data from 19 groundwater monitoring sites in rapidly urbanizing areas (Shijiazhuang, Hebei Province, China). The results show that the concentrations of various chemical components in groundwater gradually increase with the acceleration of the urbanization process, especially NO₃⁻, which has increased from 13.7 mg/L in the primary stage of urbanization (PSU) to 65.1 mg/Lin the advanced stage of urbanization (ASU), exceeding the World Health Organization (WHO) drinking water standard (50 mg/L), indicating that the groundwater chemistry has been significantly affected by human activities. The main hydrochemical types have changed from the HCO₃•SO₄-Ca•Mg-type water in the primary stage of urbanization (PSU) to the SO₄•HCO₃-Ca•Mg-type water in the advanced stage of urbanization (ASU). It is worth noting that there are obvious differences in driving factors of groundwater chemical evolution at different urbanization stages. In the primary stage of urbanization (PSU), the driving factors were carbonate and rock salt dissolution, cation exchange, and industrial activities. However, in the intermediate stage and advanced stage, the driving factors were changed to carbonate and gypsum dissolution, groundwater over-exploitation, agricultural fertilization, and domestic sewage. Based on the above conclusions, it is suggested that future groundwater management should control the amount of agricultural fertilizers, apply scientific fertilization, and prohibit the discharge of various types of non-compliant sewage, while strengthening the supervision of groundwater extraction to reduce the impact of urbanization development on the groundwater chemical evolution process. Full article

► Show Figures

Figure 1

22 pages, 2302 KiB

Open AccessEditor’s ChoiceReview

Greenhouse Gases Emissions of Constructed Wetlands: Mechanisms and Affecting Factors

by Xiaoxue Yin, Cancan Jiang, Shengjun Xu, Xiaojuan Yu, Xiaolin Yin, Jinglin Wang, Mairemu Maihaiti, Cong Wang, Xiaoxu Zheng and Xuliang Zhuang

Water 2023, 15(16), 2871; https://doi.org/10.3390/w15162871 - 9 Aug 2023

Cited by 12 | Viewed by 4777

Abstract

Constructed wetlands (CWs) widely applied for wastewater treatment release significant greenhouse gases (GHGs), contributing to global warming. It is essential to characterize the comprehensive source-sink effects and affecting factors of GHGs in CWs, offering references and guidance for designing and operating CWs to [...] Read more.

Constructed wetlands (CWs) widely applied for wastewater treatment release significant greenhouse gases (GHGs), contributing to global warming. It is essential to characterize the comprehensive source-sink effects and affecting factors of GHGs in CWs, offering references and guidance for designing and operating CWs to better control GHG emissions. However, current reviews focus on individual GHG emission mechanisms. With the aid of the Web of Science Core Collection database, the relevant literature on carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) emissions in CWs after 2010 was collected and organized. As highlighted in the review, CWs can produce and transmit these GHGs into the atmosphere, forming sources of GHGs and sequestration CO₂ through plants photosynthesis, forming sinks of GHGs. Their overall performance depends on many factors. Hybrid CWs, Cyperus papyrus, Cyperus alternifolius, and Iris pseudacorus, adsorption substrates like Fe-C, low temperatures, and a C/N ratio of five are beneficial for GHG mitigation in CWs. Future studies should focus on in-depth research into the mechanisms and overall source-sink benefits of plants and microorganisms in relation to GHGs. This review provided a comprehensive understanding of the emission mechanisms and affecting factors of the major GHGs in CWs, bridging the research gap in this field, helping researchers to clarify the context, and providing valuable in-sights for further scientific investigations. Full article

(This article belongs to the Special Issue Nitrogen Cycles and Non-CO₂ Greenhouse Gases in Aquatic Ecosystem: Microbial Process, Mechanisms, and Effects)

► Show Figures

Figure 1

15 pages, 4159 KiB

Open AccessEditor’s ChoiceArticle

Scour Development Around an Oblong Bridge Pier: A Numerical and Experimental Study

by Ana Margarida Bento, João Pedro Pêgo, Teresa Viseu and Lúcia Couto

Water 2023, 15(16), 2867; https://doi.org/10.3390/w15162867 - 8 Aug 2023

Cited by 11 | Viewed by 2552

Abstract

The complex flow structure around bridge piers is challenging for both experimental and numerical studies. Therefore, investigating the capabilities of Computational Fluid Dynamics (CFD) tools in resolving the flow structure and the mechanism of sediment entrainment into and out of the scour hole [...] Read more.

The complex flow structure around bridge piers is challenging for both experimental and numerical studies. Therefore, investigating the capabilities of Computational Fluid Dynamics (CFD) tools in resolving the flow structure and the mechanism of sediment entrainment into and out of the scour hole remains a challenging task. In this study, the scour depth around an oblong bridge pier and the bed shear stress distributions in time and space were numerically investigated using the Computational Fluid Dynamics (CFD) tool Sediment Simulation In Intakes with Multiblock option (SSIIM). Clear water scour conditions and sand of known granulometric composition were considered in accordance with the experimental study carried out. Laboratory data and the results of a scour characterization around a 0.11 m wide oblong bridge pier were considered to calibrate and validate the numerical model. The averaged form of the Navier–Stokes equations was considered to simulate the turbulent flow fields in anticipation of long time scales. The results show that calibrated numerical models can reproduce measured scour depths in the laboratory environment with considerable accuracy, with an average relative error of less than 3%, especially around oblong bridge piers. Full article

(This article belongs to the Special Issue The Application of Hydraulic Model and Numerical Simulation in River Engineering)

► Show Figures

Figure 1

34 pages, 1680 KiB

Open AccessEditor’s ChoiceArticle

Parameterization for Modeling Blue–Green Infrastructures in Urban Settings Using SWMM-UrbanEVA

by Birgitta Hörnschemeyer, Malte Henrichs, Ulrich Dittmer and Mathias Uhl

Water 2023, 15(15), 2840; https://doi.org/10.3390/w15152840 - 6 Aug 2023

Cited by 9 | Viewed by 2837

Abstract

Blue–green infrastructures (BGI) play an important role in addressing contemporary challenges posed by urbanization, climate change, and demographic shifts. This study focuses on the parameterization of BGI within hydrological models, specifically emphasizing the Low Impact Development (LID) module of the Storm Water Management [...] Read more.

Blue–green infrastructures (BGI) play an important role in addressing contemporary challenges posed by urbanization, climate change, and demographic shifts. This study focuses on the parameterization of BGI within hydrological models, specifically emphasizing the Low Impact Development (LID) module of the Storm Water Management Model (SWMM), supplemented by the SWMM-UrbanEVA evapotranspiration model. Employing a systematic approach, a transferable framework is developed to categorize BGI types, leading to a comprehensive parameterization toolset. This toolset includes parameter estimates for predefined BGI types, encompassing both natural and technical systems with a specific emphasis on plant-specific parameterization. The justification of these parameter estimates is supported by an extensive literature review. Sensitivity analyses reveal the influence of plant-specific parameters, such as the crop factor (K_C), and soil storage capacity, on water balance and peak runoff. Additionally, this study presents practical guidelines to enhance the comprehension of model behavior and ensure the highest possible quality in model parameterization. While further research on validity and transferability of the toolset is required, the findings of this study provide useful support for the differentiated representation and analysis of hydrological processes in urban environments. As a result, this study serves as a valuable resource for researchers, practitioners, and decision makers, facilitating the implementation of sustainable water management practices in urban settings. Full article

(This article belongs to the Special Issue Challenges and Sustainability of Water Sensitive Cities)

► Show Figures

Figure 1

15 pages, 2692 KiB

Open AccessEditor’s ChoiceArticle

Variability and Heavy Metal Pollution Levels in Water and Bottom Sediments of the Liwiec and Muchawka Rivers (Poland)

by Mariusz Kluska and Joanna Jabłońska

Water 2023, 15(15), 2833; https://doi.org/10.3390/w15152833 - 5 Aug 2023

Cited by 12 | Viewed by 2361

Abstract

In recent years, human impact on the Earth’s ecological environment has become increasingly visible, with serious negative consequences. One of the most important pollutants are heavy metals which can easily bind to sediments. Due to their toxic behavior, persistence, lack of biodegradability and [...] Read more.

In recent years, human impact on the Earth’s ecological environment has become increasingly visible, with serious negative consequences. One of the most important pollutants are heavy metals which can easily bind to sediments. Due to their toxic behavior, persistence, lack of biodegradability and bioaccumulation, they are considered key river pollutants that need to be controlled. This study examined two rivers: the Liwiec and Muchawka rivers located in south-eastern Poland. The mouth of the Liwiec River is the Bug River, which is partly the border between Poland and Belarus. In turn, the mouth of the Muchawka River is the Liwiec River. The objectives of the study were the following: (1) To complete a qualitative analysis of heavy metals (Cd, Pb, Cu, Ni, Zn) in the waters and bottom sediments of the Liwiec and Muchawka rivers; (2) To assess the degree of heavy metal contamination; (3) To identify the sources of contamination. The analysis included samples of surface water and bottom sediments collected (16 water and 16 bottom sediment samples were taken from the Muchawka River and 32 water and 32 bottom sediment samples were taken from the Liwiec River) in June and September 2022. The variability of characteristics, such as temperature, precipitation and humidity, contributes to seasonal changes in the distribution characteristics and sources of heavy metals. The study showed that only a small part of the heavy metals entering rivers are present in the water depth in the dissolved state, and most of them enrich the sediment, resulting in much higher concentrations of heavy metals in the sediment than in the water column. The differences in the distribution of some elements in water and sediment are due to the fact that surface sediments retain long-term records. Therefore, sediment can be considered a potential source of heavy metals in the aquatic environment. In general, the content of heavy metals determined in bottom sediments was not high but indicative of anthropogenic human activity. There is a possibility of re-release of heavy metals from the sediment into the water when hydrodynamic conditions or environmental factors (pH, redox potential, etc.) change, which could lead to secondary water pollution. The data obtained will be of great importance to both researchers studying river systems and the population living in the area. Full article

(This article belongs to the Special Issue Water and Sediment Quality Assessment)

► Show Figures

Figure 1

17 pages, 3876 KiB

Open AccessEditor’s ChoiceArticle

Long-Term Performance of Blue-Green Roof Systems—Results of a Building-Scale Monitoring Study in Hamburg, Germany

by Michael Richter and Wolfgang Dickhaut

Water 2023, 15(15), 2806; https://doi.org/10.3390/w15152806 - 3 Aug 2023

Cited by 7 | Viewed by 2534

Abstract

For the first time, a long-term monitoring study with different full-scale blue-green roof (BGR) types was conducted. Within a pilot project from Hamburg’s Rainwater InfraStructure Adaptation (RISA) framework, four different BGR types were built in 2015 for long-term evaluation and comparison with each [...] Read more.

For the first time, a long-term monitoring study with different full-scale blue-green roof (BGR) types was conducted. Within a pilot project from Hamburg’s Rainwater InfraStructure Adaptation (RISA) framework, four different BGR types were built in 2015 for long-term evaluation and comparison with each other. The test site was created to find out to what extent BGRs are able to improve hydrological performance and if increased water supply affects vegetation development and species diversity. Therefore, the roofs were equipped with hydrologic monitoring systems, their retention performance was evaluated, and vegetation analysis was conducted. During 2017–2023, between 64 and 74% of the precipitation was retained on the roofs, and in the summer months there was hardly any outflow from the roofs. For single (heavy) rain events, high retention capacities, low outflow intensities, and high detention times were demonstrated. On the BGRs where rainwater is permanently stored on the roof, the vegetation species’ composition changed in the long term, resulting in an increase in biodiversity. The studied BGRs are effective in reducing flood risk from heavy rain events and can increase evaporative cooling and biodiversity. Therefore, such BGRs are a blue-green infrastructure with far-reaching positive effects. Full article

(This article belongs to the Special Issue Challenges and Sustainability of Water Sensitive Cities)

► Show Figures

Figure 1

40 pages, 5612 KiB

Open AccessEditor’s ChoiceReview

Toxic Algae in Inland Waters of the Conterminous United States—A Review and Synthesis

by Reynaldo Patiño, Victoria G. Christensen, Jennifer L. Graham, Jane S. Rogosch and Barry H. Rosen

Water 2023, 15(15), 2808; https://doi.org/10.3390/w15152808 - 3 Aug 2023

Cited by 14 | Viewed by 7504

Abstract

Cyanobacteria are the most common toxigenic algae in inland waters. Their toxins can affect the health of aquatic and terrestrial organisms, including humans. Other algal groups, such as haptophytes (e.g., Prymnesium parvum) and euglenoids (e.g., Euglena sanguinea), can also form harmful [...] Read more.

Cyanobacteria are the most common toxigenic algae in inland waters. Their toxins can affect the health of aquatic and terrestrial organisms, including humans. Other algal groups, such as haptophytes (e.g., Prymnesium parvum) and euglenoids (e.g., Euglena sanguinea), can also form harmful algal blooms (HABs) whose toxins cause injury to aquatic biota but currently have no known effects on human health. Prymnesium parvum, however, is responsible for some of the worst HAB-related ecological disasters recorded in inland waters. Here, we provide an overview of the primary toxigenic algae found in U.S. inland waters: cyanobacteria (planktonic forms), P. parvum, and E. sanguinea with the objective of describing their similarities and differences in the areas of HAB ecology, algal toxins, and the potential for future range expansion of HABs. A detailed account of bloom habitats and their known associations with land cover and use is provided from the perspective of water quality. This review revealed that salinity may have an influence on inland cyanobacterial blooms and cyanotoxins that had not been fully recognized previously. Full article

► Show Figures

Figure 1

15 pages, 5229 KiB

Open AccessEditor’s ChoiceArticle

HYPER: Computer-Assisted Optimal Pump-as-Turbine (PAT) Selection for Microhydropower Generation and Pressure Regulation in a Water Distribution Network (WDN)

by Gustavo Marini, Francesco Di Menna, Marco Maio and Nicola Fontana

Water 2023, 15(15), 2807; https://doi.org/10.3390/w15152807 - 3 Aug 2023

Cited by 6 | Viewed by 1196

Abstract

Although pressure reducing valves (PRVs) have traditionally been employed to regulate pressure and reducer water leakage, researchers have been increasingly investigating the strategy of micro-hydropower generation using pumps as turbines (PATs) to enable both pressure reduction and energy production as an alternative strategy [...] Read more.

Although pressure reducing valves (PRVs) have traditionally been employed to regulate pressure and reducer water leakage, researchers have been increasingly investigating the strategy of micro-hydropower generation using pumps as turbines (PATs) to enable both pressure reduction and energy production as an alternative strategy in water distribution networks (WDNs). However, due to the continuous variability of flow discharge during the day, selecting the optimal PAT remains a challenging issue. To address this, the authors have developed HYPER, a freely available software app that implements an innovative approach for selecting the most suitable PAT in systems that involve both hydraulic and/or electrical regulation. In enabling the identification of the PAT parameters that maximize energy production, HYPER thus provides a fast and effective PAT selection tool. The effectiveness of the proposed approach was further demonstrated with application to a real WDN. Four operational patterns varying in terms of available flow and head drop were considered, showing that the most efficient pumps consistently tended to be located in close proximity to the maximum produced energy. Furthermore, the results confirmed that hydraulic regulation and coupled hydraulic/electric regulation-based installation layouts represent the best solutions in terms of energy produced. The solely electrical regulation option, given its poor flexibility, returns in all cases lower energy production with the lower adaptability of commercial pumps. Full article

(This article belongs to the Special Issue Integrated Management of Water Distribution Systems)

► Show Figures

Figure 1

51 pages, 6085 KiB

Open AccessEditor’s ChoiceReview

Selection Frameworks for Potential Rainwater Harvesting Sites in Arid and Semi-Arid Regions: A Systematic Literature Review

by Safaa Ahmed, Mike Jesson and Soroosh Sharifi

Water 2023, 15(15), 2782; https://doi.org/10.3390/w15152782 - 31 Jul 2023

Cited by 5 | Viewed by 3595

Abstract

Water shortage is a concern in arid and semi-arid regions across the globe due to their lack of precipitation and unpredictable rainfall patterns. In the past few decades, many frameworks, each with their own criteria, have been used to identify and rank sites [...] Read more.

Water shortage is a concern in arid and semi-arid regions across the globe due to their lack of precipitation and unpredictable rainfall patterns. In the past few decades, many frameworks, each with their own criteria, have been used to identify and rank sites for rainwater harvesting (RWH), a process which is critical for the improvement and maintenance of water resources, particularly in arid and semi-arid regions. This study reviews the present state of the art in rainwater harvesting site selection for such regions and identifies areas for additional research. The results of a systematic review performed based on two major databases of engineering research, Scopus and Engineering Village, are presented. Sixty-eight relevant studies were found and critically analysed to identify patterns and unique features in the frameworks used. The results of this study show that 41% of the frameworks consider both biophysical and socioeconomic criteria, whereas the remaining 59% of the frameworks depend on biophysical criteria alone. The importance of each criterion is encapsulated through a suitability score, with 21% of the frameworks using a binary (0 or 1) indicator of whether the site matches a criterion or not and the other frameworks using graded scales of differing granularities, with 52% using a low-resolution scale of 1 to 3, 4, or 5, 7% using a medium-resolution scale of 1 to 10, and a further 7% using a high-resolution scale of 1 to 100. The remaining 13% of the frameworks did not specify the scale used. Importantly, this paper concludes that all existing frameworks for selecting RWH sites are solely based on biophysical and/or socioeconomic criteria; ecological impacts, the consideration of which is vital for building RWH systems sustainably, are currently ignored. Full article

► Show Figures

Figure 1

28 pages, 7266 KiB

Open AccessEditor’s ChoiceArticle

Photodegradation of Rhodamine B and Phenol Using TiO₂/SiO₂ Composite Nanoparticles: A Comparative Study

by Maria-Anna Gatou, Evangelos Fiorentis, Nefeli Lagopati and Evangelia A. Pavlatou

Water 2023, 15(15), 2773; https://doi.org/10.3390/w15152773 - 31 Jul 2023

Cited by 17 | Viewed by 2715

Abstract

Organic pollutants found in industrial effluents contribute to significant environmental risks. Degradation of these pollutants, particularly through photocatalysis, is a promising strategy ensuring water purification and supporting wastewater treatment. Thus, photodegradation of rhodamine B and phenol under visible-light irradiation using TiO₂/SiO [...] Read more.

Organic pollutants found in industrial effluents contribute to significant environmental risks. Degradation of these pollutants, particularly through photocatalysis, is a promising strategy ensuring water purification and supporting wastewater treatment. Thus, photodegradation of rhodamine B and phenol under visible-light irradiation using TiO₂/SiO₂ composite nanoparticles was within the main scopes of this study. The nanocomposite was synthesized through a wet impregnation method using TiO₂ and SiO₂ nanopowders previously prepared via a facile sol–gel approach and was fully characterized. The obtained results indicated a pure anatase phase, coupled with increased crystallinity (85.22%) and a relative smaller crystallite size (1.82 nm) in relation to pure TiO₂ and SiO₂ and an enhanced specific surface area (50 m²/g) and a reduced energy band gap (3.18 eV). Photodegradation of rhodamine B upon visible-light irradiation was studied, showing that the TiO₂/SiO₂ composite reached total (100%) degradation within 210 min compared to pure TiO₂ and SiO₂ analogues, which achieved a ≈45% and ≈43% degradation rate, respectively. Similarly, the composite catalyst presented enhanced photocatalytic performance under the same irradiation conditions towards the degradation of phenol, leading to 43.19% degradation within 210 min and verifying the composite catalyst’s selectivity towards degradation of rhodamine B dye as well as its enhanced photocatalytic efficiency towards both organic compounds compared to pure TiO₂ and SiO₂. Additionally, based on the acquired experimental results, ●O₂⁻, h⁺ and e⁻ were found to be the major reactive oxygen species involved in rhodamine B’s photocatalytic degradation, while ●OH radicals were pivotal in the photodegradation of phenol under visible irradiation. Finally, after the TiO₂/SiO₂ composite catalyst was reused five times, it indicated negligible photodegradation efficiency decrease towards both organic compounds. Full article

(This article belongs to the Special Issue Advanced Applications of Nanoparticles in Water and Wastewater)

► Show Figures

Figure 1

14 pages, 8931 KiB

Open AccessEditor’s ChoiceArticle

Spatiotemporal Evolution and Nowcasting of the 2022 Yangtze River Mega-Flash Drought

by Miaoling Liang, Xing Yuan, Shiyu Zhou and Zhanshan Ma

Water 2023, 15(15), 2744; https://doi.org/10.3390/w15152744 - 29 Jul 2023

Cited by 14 | Viewed by 2084

Abstract

Flash droughts challenge early warnings due to their rapid onset, which requires a proper drought index and skillful nowcasting system. A few studies have assessed the nowcast skill for flash droughts using a one-dimensional index, but whether the models can capture their spatiotemporal [...] Read more.

Flash droughts challenge early warnings due to their rapid onset, which requires a proper drought index and skillful nowcasting system. A few studies have assessed the nowcast skill for flash droughts using a one-dimensional index, but whether the models can capture their spatiotemporal evolution remains unclear. In this study, a three-dimensional meteorological flash drought index based on the percentile of 15-day moving average precipitation minus evapotranspiration (P-ET) is developed. The index is then used to investigate the spatiotemporal evolution of a mega-flash drought that occurred in the Yangtze River basin during the summer of 2022. The results show that the mega-flash drought started at the beginning of July in the upper reaches of the river and expanded to the middle and lower reaches at the beginning of August due to the spread of the high-pressure system. The evolution is well captured by the proposed three-dimensional index. The spatial correlations between the China Meteorological Administration global medium-range ensemble forecast system (CMA-GFS)’s nowcast and reanalysis ranged from 0.58 to 0.85, and the hit rate and equitable threat score are 0.54 and 0.26, respectively. This study shows that the CMA-GFS nowcast of the P-ET index roughly captured the drought’s evolution, which can be used for flash drought early warnings and water resource management. Full article

(This article belongs to the Special Issue Challenges of Hydrological Drought Monitoring and Prediction)

► Show Figures

Graphical abstract

17 pages, 4010 KiB

Open AccessEditor’s ChoiceArticle

Advancing Water Quality Research: K-Nearest Neighbor Coupled with the Improved Grey Wolf Optimizer Algorithm Model Unveils New Possibilities for Dry Residue Prediction

by Hichem Tahraoui, Selma Toumi, Amel Hind Hassein-Bey, Abla Bousselma, Asma Nour El Houda Sid, Abd-Elmouneïm Belhadj, Zakaria Triki, Mohammed Kebir, Abdeltif Amrane, Jie Zhang, Amin Aymen Assadi, Derradji Chebli, Abdallah Bouguettoucha and Lotfi Mouni

Water 2023, 15(14), 2631; https://doi.org/10.3390/w15142631 - 20 Jul 2023

Cited by 20 | Viewed by 2255

Abstract

Monitoring stations have been established to combat water pollution, improve the ecosystem, promote human health, and facilitate drinking water production. However, continuous and extensive monitoring of water is costly and time-consuming, resulting in limited datasets and hindering water management research. This study focuses [...] Read more.

Monitoring stations have been established to combat water pollution, improve the ecosystem, promote human health, and facilitate drinking water production. However, continuous and extensive monitoring of water is costly and time-consuming, resulting in limited datasets and hindering water management research. This study focuses on developing an optimized K-nearest neighbor (KNN) model using the improved grey wolf optimization (I-GWO) algorithm to predict dry residue quantities. The model incorporates 20 physical and chemical parameters derived from a dataset of 400 samples. Cross-validation is employed to assess model performance, optimize parameters, and mitigate the risk of overfitting. Four folds are created, and each fold is optimized using 11 distance metrics and their corresponding weighting functions to determine the best model configuration. Among the evaluated models, the Jaccard distance metric with inverse squared weighting function consistently demonstrates the best performance in terms of statistical errors and coefficients for each fold. By averaging predictions from the models in the four folds, an estimation of the overall model performance is obtained. The resulting model exhibits high efficiency, with remarkably low errors reflected in the values of R, R², R²_ADJ, RMSE, and EPM, which are reported as 0.9979, 0.9958, 0.9956, 41.2639, and 3.1061, respectively. This study reveals a compelling non-linear correlation between physico-chemical water attributes and the content of dry tailings, indicating the ability to accurately predict dry tailing quantities. By employing the proposed methodology to enhance water quality models, it becomes possible to overcome limitations in water quality management and significantly improve the precision of predictions regarding critical water parameters. Full article

(This article belongs to the Special Issue Water Treatment Modeling and Nutrient Recovery Processes)

► Show Figures

Figure 1

18 pages, 8410 KiB

Open AccessEditor’s ChoiceArticle

Representation of Hydrological Components under a Changing Climate—A Case Study of the Uruguay River Basin Using the New Version of the Soil and Water Assessment Tool Model (SWAT+)

by Osvaldo Luis Barresi Armoa, Sabine Sauvage, Tobias Houska, Katrin Bieger, Christoph Schürz and José Miguel Sánchez Pérez

Water 2023, 15(14), 2604; https://doi.org/10.3390/w15142604 - 18 Jul 2023

Cited by 7 | Viewed by 2824

Abstract

SWAT+ is a revised version of the SWAT model that has the capability to route flow across landscape units in the catchment, which is expected to improve the spatial representation of processes in watersheds. We applied the SWAT+ model in the Uruguay River [...] Read more.

SWAT+ is a revised version of the SWAT model that has the capability to route flow across landscape units in the catchment, which is expected to improve the spatial representation of processes in watersheds. We applied the SWAT+ model in the Uruguay River Basin, an international river basin in South America with a total surface area of 370,000 km², in order to (1) assess the water balance components, (2) represent their spatial distribution, and (3) examine their changes over time. The catchment was divided into uplands and floodplains and a decision table rule was developed based on streamflow data. The SPOTPY Python library was linked to SWAT+ and used as a tool to perform sensitivity analyses and calibration. The model represented the fluctuations of discharge well, although there was a general tendency to underestimate peak flows. Blue (precipitation and runoff) and green (evapotranspiration and soil water content) hydrological components were spatially plotted. Overall, SWAT+ simulated a realistic spatial distribution of the water cycle components. A seasonal Mann–Kendall test suggests a positive increasing trend in the average temperature (p-value = 0.007; Sen’s slope = 0.09), the soil water content (p-value = 0.02; Sen’s slope = 1.29), and evapotranspiration (p-value: 0.03; Sen’s slope = 1.97), indicating that the ecosystem experienced a changing climate during the simulation period. The findings presented in this study are of significant value for the impacts of sustainable management and the evaluation of climate change on water resources in the Uruguay River Basin. Full article

► Show Figures

Figure 1

13 pages, 2585 KiB

Open AccessEditor’s ChoiceArticle

Comparative Analysis of Composition and Porosity of the Biogenic Powder Obtained from Wasted Crustacean Exoskeletonsafter Carotenoids Extraction for the Blue Bioeconomy

by Fran Nekvapil, Maria Mihet, Geza Lazar, Simona Cîntă Pinzaru, Ana Gavrilović, Alexandra Ciorîță, Erika Levei, Tudor Tamaș and Maria-Loredana Soran

Water 2023, 15(14), 2591; https://doi.org/10.3390/w15142591 - 16 Jul 2023

Cited by 5 | Viewed by 2149

Abstract

The recovery and recycling of wasted resources are at the forefront of contemporary global issues. Methods of addressing several different issues may go hand-in-hand with each other, such as linking food waste recycling into bio-based adsorbent materials and wastewater treatment. Crustacean exoskeletons are [...] Read more.

The recovery and recycling of wasted resources are at the forefront of contemporary global issues. Methods of addressing several different issues may go hand-in-hand with each other, such as linking food waste recycling into bio-based adsorbent materials and wastewater treatment. Crustacean exoskeletons are promising candidates for bio-friendly adsorbents; however, maximizing their efficiency requires the optimization of processing technology. Crustacean meat offers an (often luxury) culinary delicacy, while their waste exoskeletons offer opportunities for smart recycling of the magnesian calcite nanoporous biocomposite. Here, we conduct a structural characterization of the exoskeletons of three crustacean species to assess how the extraction of valuable carotenoids affects prospects for the further valorization of their porous powder. The exoskeleton powder’s composition and morphology were investigated by SEM, Raman spectroscopy, FTIR and XRD. The biomineral component magnesian calcite was recorded both in native and in post-extraction exoskeleton powder. Acetone extraction, however, partially removed organic matter from the exoskeletons, resulting in the porosity of the respective powder increasing significantly from below 10 m² g⁻¹ in the native powder to over 32 m² g⁻¹ in post-extraction samples of blue crab and spider crab exoskeletons—while the spiny lobster exoskeleton exhibited low porosity, as measured by the BET method. This new insight could improve exoskeleton processing in the sustainable circular economy and applied blue bioeconomy—most notably for adsorbent materials for pollutants dissolved in water or as ordered, nature-derived nanostructured templates. Full article

(This article belongs to the Special Issue Biological Wastewater Treatment towards a Sustainable Circular Economy)

► Show Figures

Figure 1

17 pages, 1446 KiB

Open AccessEditor’s ChoiceArticle

Exploring the Viability of Utilizing Treated Wastewater as a Sustainable Water Resource for Green Hydrogen Generation Using Solid Oxide Electrolysis Cells (SOECs)

by Marina Maddaloni, Matteo Marchionni, Alessandro Abbá, Michele Mascia, Vittorio Tola, Maria Paola Carpanese, Giorgio Bertanza and Nancy Artioli

Water 2023, 15(14), 2569; https://doi.org/10.3390/w15142569 - 13 Jul 2023

Cited by 13 | Viewed by 3662

Abstract

In response to the European Union’s initiative toward achieving carbon neutrality, the utilization of water electrolysis for hydrogen production has emerged as a promising avenue for decarbonizing current energy systems. Among the various approaches, Solid Oxide Electrolysis Cell (SOEC) presents an attractive solution, [...] Read more.

In response to the European Union’s initiative toward achieving carbon neutrality, the utilization of water electrolysis for hydrogen production has emerged as a promising avenue for decarbonizing current energy systems. Among the various approaches, Solid Oxide Electrolysis Cell (SOEC) presents an attractive solution, especially due to its potential to utilize impure water sources. This study focuses on modeling a SOEC supplied with four distinct streams of treated municipal wastewaters, using the Aspen Plus software. Through the simulation analysis, it was determined that two of the wastewater streams could be effectively evaporated and treated within the cell, without generating waste liquids containing excessive pollutant concentrations. Specifically, by evaporating 27% of the first current and 10% of the second, it was estimated that 26.2 kg/m³ and 9.7 kg/m³ of green hydrogen could be produced, respectively. Considering the EU’s target for Italy is to have 5 GW of installed power capacity by 2030 and the mass flowrate of the analyzed wastewater streams, this hydrogen production could meet anywhere from 0.4% to 20% of Italy’s projected electricity demand. Full article

(This article belongs to the Special Issue The Transition of Water and Wastewater Treatment Plants into Facilities for Resources and Energy Production: Solutions and Innovation)

► Show Figures

Figure 1

19 pages, 2900 KiB

Open AccessEditor’s ChoiceArticle

Utopian River Planning and Hydrosocial Territory Transformations in Colombia and Spain

by Bibiana Duarte-Abadía

Water 2023, 15(14), 2545; https://doi.org/10.3390/w15142545 - 11 Jul 2023

Cited by 7 | Viewed by 2168

Abstract

This paper examines how utopian river planning has arisen in Colombia and Spain since the late nineteenth century. Specifically, the paper contributes to understanding how particular ideologies of modernism and development present in territorial planning connect both countries. Taking Thomas More’s classic work [...] Read more.

This paper examines how utopian river planning has arisen in Colombia and Spain since the late nineteenth century. Specifically, the paper contributes to understanding how particular ideologies of modernism and development present in territorial planning connect both countries. Taking Thomas More’s classic work ‘Utopia’ as the analytical reference, I analyze how utopian tendencies have traveled through time and space to shape territorial planning and water governance. In both countries, this was evident in the late nineteenth century through the political project to strengthen the nation state. For Spain, I describe the regenerationist movement and the hydraulic utopia led by the Spanish intellectual Joaquín Costa, who forged the dream of a water nationhood. By contrast, in Colombia, several political intellectuals looked at Europe and North America as a source of inspiration to achieve progress by controlling rivers. Through the method of disjunctive comparison, I show how the same utopian notions are expressed in similar ways in distinct contexts: violently governing the flows of rivers, standardizing minds and ordering territories towards capital growth. This paper contributes to grasping the notions and roots of the discourses that have colonized the political water agendas in both countries. Full article

(This article belongs to the Special Issue Water Contestations: Socio-Technical Entanglements, Politics and Social Mobilisation)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Editor’s Choice Articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI