Water

22 pages, 5549 KB

Open AccessEditor’s ChoiceArticle

Evaluating Hydrologic Model Performance for Characterizing Streamflow Drought in the Conterminous United States

by Caelan Simeone, Sydney Foks, Erin Towler, Timothy Hodson and Thomas Over

Water 2024, 16(20), 2996; https://doi.org/10.3390/w16202996 - 21 Oct 2024

Cited by 5 | Viewed by 3188

Hydrologic models are the primary tools that are used to simulate streamflow drought and assess impacts. However, there is little consensus about how to evaluate the performance of these models, especially as hydrologic modeling moves toward larger spatial domains. This paper presents a [...] Read more.

Hydrologic models are the primary tools that are used to simulate streamflow drought and assess impacts. However, there is little consensus about how to evaluate the performance of these models, especially as hydrologic modeling moves toward larger spatial domains. This paper presents a comprehensive multi-objective approach to systematically evaluating the critical features in streamflow drought simulations performed by two widely used hydrological models. The evaluation approach captures how well a model classifies observed periods of drought and non-drought, quantifies error components during periods of drought, and assesses the models’ simulations of drought severity, duration, and intensity. We apply this approach at 4662 U.S. Geological Survey streamflow gages covering a wide range of hydrologic conditions across the conterminous U.S. from 1985 to 2016 to evaluate streamflow drought using two national-scale hydrologic models: the National Water Model (NWM) and the National Hydrologic Model (NHM); therefore, a benchmark against which to evaluate additional models is provided. Using this approach, we find that generally the NWM better simulates the timing of flows during drought, while the NHM better simulates the magnitude of flows during drought. Both models performed better in wetter eastern regions than in drier western regions. Finally, each model showed increased error when simulating the most severe drought events. Full article

(This article belongs to the Special Issue Water Resource Management: Hydrological Modelling, Hydrological Cycles, and Hydrological Prediction)

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23 pages, 2206 KB

Open AccessEditor’s ChoiceArticle

Bottled or Tap Water? Factors Explaining Consumption and Measures to Promote Tap Water

by Iva Zvěřinová, Milan Ščasný and Jan Otáhal

Water 2024, 16(20), 3011; https://doi.org/10.3390/w16203011 - 21 Oct 2024

Cited by 7 | Viewed by 7128

Abstract

The production and consumption of plastic bottled water have several negative environmental impacts worldwide. To identify the barriers and motivations for drinking tap and bottled water, we conducted a nationally representative questionnaire survey among 3411 respondents in the Czech Republic in 2022. People [...] Read more.

The production and consumption of plastic bottled water have several negative environmental impacts worldwide. To identify the barriers and motivations for drinking tap and bottled water, we conducted a nationally representative questionnaire survey among 3411 respondents in the Czech Republic in 2022. People aged 18–34 are moderate consumers of bottled water and very frequent consumers of tap water. Bottled water consumption tends to be less frequent among people with a higher education, while tap water consumption is less frequent among people with lower incomes. The most important factors that explain the frequency of drinking bottled and tap water are taste perception, health concerns and habit. Health concerns about tap water and the unpleasant taste of tap water increase the consumption of bottled water. People with a strong habit of drinking tap water are less likely to consume bottled water. The constructs from the theory of planned behaviour were statistically significant. The results can guide decision-makers in promoting tap water to consumers. To encourage tap water drinking, we suggest measures to increase the availability of tap water in public places in conjunction with campaigns targeting the taste and health perception, as well as the habit, of drinking tap water. Full article

(This article belongs to the Section Water Use and Scarcity)

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17 pages, 2874 KB

Open AccessEditor’s ChoiceArticle

The Israeli Water Policy and Its Challenges During Times of Emergency

by Erez Cohen

Water 2024, 16(20), 2995; https://doi.org/10.3390/w16202995 - 20 Oct 2024

Cited by 5 | Viewed by 7928

Abstract

In a time of growing climate crisis, and despite the global warming trend, Israeli citizens routinely enjoy a regular constant supply of clean fresh water thanks to local desalination plants. Establishment of the desalination plants has become a model of water management for [...] Read more.

In a time of growing climate crisis, and despite the global warming trend, Israeli citizens routinely enjoy a regular constant supply of clean fresh water thanks to local desalination plants. Establishment of the desalination plants has become a model of water management for many countries in an era of growing climate crisis. At the same time, Israel’s water sector is faced with challenges and threats related to earthquakes, various states of warfare, and security confrontations. In such times of emergency, Israel’s water sector is particularly vulnerable to disruptions of the water infrastructure and its adequate operation by both contamination of the water sources and damage to the desalination plants. This study examines the challenges of the Israeli water sector that require it to contend with these emergency situations in an era of reliance on desalination plants. The research findings lead to the conclusion that public policy on managing the water sector, manifested in the development and establishment of water desalination plants, has resolved Israel’s water crisis, put an end to its dependency on the amount of precipitation and on natural water sources, and allowed for an increase in water production to match the rise in consumption. Nonetheless, as successful as this public policy may be, it does not consider the possibility of extreme scenarios and does not develop the entire range of steps necessary to confront them, and thus it undermines the ability of the Israeli water sector to provide its citizens with water in times of emergency. Full article

(This article belongs to the Section Urban Water Management)

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15 pages, 16024 KB

Open AccessFeature PaperEditor’s ChoiceArticle

Numerical Simulations of a Permeability Test on Non-Cohesive Soil Under an Increasing Water Level

by Weijie Zhang, Hongxin Chen, Lei Xiong and Liang Chen

Water 2024, 16(20), 2992; https://doi.org/10.3390/w16202992 - 20 Oct 2024

Viewed by 2111

Abstract

With the intensification of global climate change, extreme rainfall events are occurring more frequently. Continuous rainfall causes the debris flow gully to collect a large amount of rainwater. Under the continuous increase in the water level, the water flow has enough power to [...] Read more.

With the intensification of global climate change, extreme rainfall events are occurring more frequently. Continuous rainfall causes the debris flow gully to collect a large amount of rainwater. Under the continuous increase in the water level, the water flow has enough power to carry plenty of loose solids, thus causing debris flow disasters. The intensity of the soil is reduced with the infiltration of rainwater, which is one of the key causes of the disaster. The rise in the water level affects the infiltration behavior. There have been few previous studies on infiltration under variable head. In order to understand the infiltration behavior of soils under the action of water level rises, this paper conducted an indoor permeability test on non-cohesive soil under the condition of an increasing water level. A numerical model was established using the finite element analysis software, Abaqus 6.14, and the pore pressure was increased intermittently to simulate the intermittent increase in the water level. Thereafter, the permeability coefficient and seepage length were changed to interpret the changes in the flow velocity and rate in the permeability test of the non-cohesive soil. The results showed that the finite element numerical simulation method could not reflect the particle movement process in the soil. The test could better reflect the through passage and void plugging phenomenon in soil; when the permeability coefficient alone changed, the velocity of the measuring point with higher velocity changed more violently with the permeability coefficient; when the length of soil seepage diameter was uniformly shortened, the velocity of water flow increased faster and faster. Full article

(This article belongs to the Special Issue Flowing Mechanism of Debris Flow and Engineering Mitigation)

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16 pages, 1805 KB

Open AccessEditor’s ChoiceReview

The Water–Energy Nexus in 26 European Countries: A Review from a Hydrogeological Perspective

by Somayeh Rezaei Kalvani, Riccardo Pinardi and Fulvio Celico

Water 2024, 16(20), 2981; https://doi.org/10.3390/w16202981 - 19 Oct 2024

Cited by 3 | Viewed by 2139

Abstract

The significance of the interconnection between water and energy, known as the water–energy (WE) nexus, is highly regarded in scientific publications. This study used a narrative review method to analyze the existing WE nexus studies performed before 2024 in 26 European countries. The [...] Read more.

The significance of the interconnection between water and energy, known as the water–energy (WE) nexus, is highly regarded in scientific publications. This study used a narrative review method to analyze the existing WE nexus studies performed before 2024 in 26 European countries. The aim of this study is to provide a comprehensive analysis of the existing WE nexus to identify research gaps and to report a conceptual overview of energy consumption related to groundwater use phases, ranging from the tapping to distribution. This information is valuable as a guideline for any future estimates in this field. The results indicate that the WE nexus in 26 European countries comprises a variety of topics, including the water supply system, wastewater treatment, hydropower, desalination, and biofuel production. Most of the focus has been on fossil fuel production, while water supply and desalination were considered rarely. Italy and Portugal had the largest WE nexus. It is highlighted that there have been no studies on the WE nexus focusing on the groundwater supply system that consider the conceptual hydrological model or hydrodynamic processes. In this work, a view of these aspects was provided by taking into account different hydrogeological and hydraulic scenarios that may affect the amount of energy required for groundwater exploitation. Most scientific publications have focused on quantitative analysis. In the future, it will be necessary for WE nexus models to place a greater emphasis on governance and the implications of the WE nexus approach. Full article

(This article belongs to the Special Issue Water and Energy Synergies)

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22 pages, 2487 KB

Open AccessEditor’s ChoiceArticle

Applying a Comprehensive Model for Single-Ring Infiltration: Assessment of Temporal Changes in Saturated Hydraulic Conductivity and Physical Soil Properties

by Mirko Castellini, Simone Di Prima, Luisa Giglio, Rita Leogrande, Vincenzo Alagna, Dario Autovino, Michele Rinaldi and Massimo Iovino

Water 2024, 16(20), 2950; https://doi.org/10.3390/w16202950 - 16 Oct 2024

Cited by 2 | Viewed by 1925

Abstract

Modeling agricultural systems, from the point of view of saving and optimizing water, is a challenging task, because it may require multiple soil physical and hydraulic measurements to investigate the entire crop cycle. The Beerkan method was proposed as a quick and easy [...] Read more.

Modeling agricultural systems, from the point of view of saving and optimizing water, is a challenging task, because it may require multiple soil physical and hydraulic measurements to investigate the entire crop cycle. The Beerkan method was proposed as a quick and easy approach to estimate the saturated soil hydraulic conductivity, K_s. In this study, a new complete three-dimensional model for Beerkan experiments recently proposed was used. It consists of thirteen different calculation approaches that differ in estimating the macroscopic capillary length, initial (θ_i) and saturated (θ_s) soil water contents, use transient or steady-state infiltration data, and different fitting methods to transient data. A steady-state version of the simplified method based on a Beerkan infiltration run (SSBI) was used as the benchmark. Measurements were carried out on five sampling dates during a single growing season (from November to June) in a long-term experiment in which two soil management systems were compared, i.e., minimum tillage (MT) and no tillage (NT). The objectives of this work were (i) to test the proposed new model and calculation approaches under real field conditions, (ii) investigate the impact of MT and NT on soil properties, and (iii) obtain information on the seasonal variability of K_s and other main soil physical properties (θ_i, soil bulk density, ρ_b, and water retention curve) under MT and NT. The results showed that the model always overestimated K_s compared to SSBI. Indeed, the estimated K_s differed by a factor of 11 when the most data demanding (A1) approach was considered by a factor of 4–8, depending on the transient or steady-state phase use, when A3 was considered and by a practically negligible factor of 1.0–1.9 with A4. A relatively higher seasonal variability was detected for θ_i at the MT than NT system. Under both MT and NT, ρ_b did not change between November and April but increased significantly until the end of the season. The selected calculation approaches provided substantially coherent information on K_s seasonal evolution. Regardless of the approach, the results showed a temporal stability of K_s at least from early April to June under NT; conversely, the MT system was, overall, more affected by temporal changes with a relative stability at the beginning and middle of the season. These findings suggest that a common sampling time for determining K_s could be set at early spring. Soil management affected the soil properties, because the NT system was significantly wetter and more compact than MT on four out of five dates. However, only NT showed a significantly increasing correlation between K_s and the modal pore diameter, suggesting the presence of a relatively smaller and better interconnected pore network in the no-tilled soil. This study confirms the need to test infiltration models under real field conditions to evaluate their pros and cons. The Beerkan method was effective for intensive soil sampling and accurate field investigations on the temporal variability of K_s. Full article

(This article belongs to the Special Issue Soil Dynamics and Water Resource Management)

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25 pages, 2419 KB

Open AccessEditor’s ChoiceArticle

Decision Support Framework for Water Quality Management in Reservoirs Integrating Artificial Intelligence and Statistical Approaches

by Syeda Zehan Farzana, Dev Raj Paudyal, Sreeni Chadalavada and Md Jahangir Alam

Water 2024, 16(20), 2944; https://doi.org/10.3390/w16202944 - 16 Oct 2024

Cited by 9 | Viewed by 3957

Abstract

Planning, managing and optimising surface water quality is a complex and multifaceted process, influenced by the effects of both climate uncertainties and anthropogenic activities. Developing an innovative and robust decision support framework (DSF) is essential for effective and efficient water quality management, so [...] Read more.

Planning, managing and optimising surface water quality is a complex and multifaceted process, influenced by the effects of both climate uncertainties and anthropogenic activities. Developing an innovative and robust decision support framework (DSF) is essential for effective and efficient water quality management, so it can provide essential information on water quality and assist policy makers and water resource managers to identify potential causes of water quality deterioration. This framework is crucial for implementing actions such as infrastructure development, legislative compliance and environmental initiatives. Recent advancements in computational domains have created opportunities for employing artificial intelligence (AI), advanced statistics and mathematical methods for use in improved water quality management. This study proposed a comprehensive conceptual DSF to minimise the adverse effects of extreme weather events and climate change on water quality. The framework utilises machine learning (ML), deep learning (DL), geographical information system (GIS) and advanced statistical and mathematical techniques for water quality management. The foundation of this framework is the outcomes from our three studies, where we examined the application of ML and DL models for predicting water quality index (WQI) in reservoirs, utilising statistical and mathematical methods to find the seasonal trend of rainfall and water quality, exploring the potential connection between streamflow, rainfall and water quality, and employing GIS to show the spatial and temporal variability of hydrological parameters and WQI. Three potable water supply reservoirs in the Toowoomba region of Australia were taken as the study area for practical implementation of the proposed DSF. This framework can serve as a comprehensive mechanism to identify distinct seasonal characteristics and understand correlations between rainfall, streamflow and water quality. This will enable policy makers and water resource managers to enhance their decision making processes by selecting the management priorities to safeguard water quality in the face of future climate variability, including prolonged droughts and flooding. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources—an Issue of Environmental Global Safety)

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19 pages, 11753 KB

Open AccessEditor’s ChoiceArticle

Landslide Deformation Analysis and Prediction with a VMD-SA-LSTM Combined Model

by Chengzhi Wen, Hongling Tian, Xiaoyan Zeng, Xin Xia, Xiaobo Hu and Bo Pang

Water 2024, 16(20), 2945; https://doi.org/10.3390/w16202945 - 16 Oct 2024

Cited by 8 | Viewed by 1818

Abstract

The evolution of landslides is influenced by the complex interplay of internal geological factors and external triggering factors, resulting in nonlinear dynamic changes. Although deep learning methods have demonstrated advantages in predicting multivariate landslide displacement, their performance is often constrained by the challenges [...] Read more.

The evolution of landslides is influenced by the complex interplay of internal geological factors and external triggering factors, resulting in nonlinear dynamic changes. Although deep learning methods have demonstrated advantages in predicting multivariate landslide displacement, their performance is often constrained by the challenges of extracting intricate features from extended time-series data. To address this challenge, we propose a novel displacement prediction model that integrates Variational Mode Decomposition (VMD), Self-Attention (SA), and Long Short-Term Memory (LSTM) networks. The model first employs VMD to decompose cumulative landslide displacement into trend, periodic, and stochastic components, followed by an assessment of the correlation between these components and the triggering factors using grey relational analysis. Subsequently, the self-attention mechanism is incorporated into the LSTM model to enhance its ability to capture complex dependencies. Finally, each displacement component is fed into the SA-LSTM model for separate predictions, which are then reconstructed to obtain the cumulative displacement prediction. Using the Zhonghai Village tunnel entrance (ZVTE) landslide as a case study, we validated the model with displacement data from GPS point 105 and made predictions for GPS point 104 to evaluate the model’s generalization capability. The results indicated that the RMSE and MAPE for SA-LSTM, LSTM, and TCN-LSTM at GPS point 105 were 0.3251 and 1.6785, 0.6248 and 2.9130, and 1.1777 and 5.5131, respectively. These findings demonstrate that SA-LSTM outperformed the other models in terms of complex feature extraction and accuracy. Furthermore, the RMSE and MAPE at GPS point 104 were 0.4232 and 1.0387, further corroborating the model’s strong extrapolation capability and its effectiveness in landslide monitoring. Full article

(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence, 2nd Edition)

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13 pages, 3859 KB

Open AccessEditor’s ChoiceArticle

Effect of Pipe Materials and Interspecific Interactions on Biofilm Formation and Chlorine Resistance: Turn Enemies into Friends

by Lili Shan, Yunyan Pei, Siyang Xu, Yuhong Cui, Zhengqian Liu, Zebing Zhu and Yixing Yuan

Water 2024, 16(20), 2930; https://doi.org/10.3390/w16202930 - 15 Oct 2024

Cited by 5 | Viewed by 2225

Abstract

Drinking water distribution systems (DWDSs) may be contaminated to various degrees when different microorganisms attach to the pipe walls. Understanding the characteristics of biofilms on pipe walls can help prevent and control microbial contamination in DWDSs. The biofilm formation, interspecific interactions, and chlorine [...] Read more.

Drinking water distribution systems (DWDSs) may be contaminated to various degrees when different microorganisms attach to the pipe walls. Understanding the characteristics of biofilms on pipe walls can help prevent and control microbial contamination in DWDSs. The biofilm formation, interspecific interactions, and chlorine resistance of 10 dual-species biofilms in polyethylene (PE) and cast iron (CI) pipes were investigated in this paper. The biofilm biomass (heterotrophic bacterial plate count and crystal violet) of dual species in CI pipes is significantly higher than that in PE pipes, but the biofilm activity in CI pipes is significantly lower than that in PE pipes. The interspecific interaction of Sphingomonas-containing group presented synergistic or neutral relationship in PE pipes, whereas the interspecific interaction of the Acidovorax-containing group showed a competitive relationship in CI pipes. Although interspecific relationships may help bacteria resist chlorine, the chlorine resistance was more reliant on dual-species groups and pipe materials. In CI pipes, the Microbacterium containing biofilm groups showed better chlorine resistance, whereas in PE pipes, most biofilm groups with Bacillus exhibited better chlorine resistance. The biofilm groups with more extracellular polymeric substance (EPS) secretion showed stronger chlorine resistance. The biofilm in the PE pipe is mainly protected by EPS, while both EPS and corrosion products shield the biofilms within CI pipe. These results supported that dual-species biofilms are affected by pipe materials and interspecific interactions and provided some ideas for microbial control in two typical pipe materials. Full article

(This article belongs to the Topic Towards Energy-Positive and Carbon-Neutral Technology for Wastewater Treatment and Reclamation)

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16 pages, 7268 KB

Open AccessEditor’s ChoiceArticle

Traffic Intensity as a Factor Influencing Microplastic and Tire Wear Particle Pollution in Snow Accumulated on Urban Roads

by Karolina Mierzyńska, Wojciech Pol, Monika Martyniuk and Piotr Zieliński

Water 2024, 16(20), 2907; https://doi.org/10.3390/w16202907 - 13 Oct 2024

Cited by 6 | Viewed by 3916

Abstract

Traffic-related roads are an underestimated source of synthetic particles in the environment. This study investigated the impact of traffic volume on microplastic (MP) and tire wear particle (TWP) pollution in road snow. An examination was conducted in a medium-sized city situated in northeastern [...] Read more.

Traffic-related roads are an underestimated source of synthetic particles in the environment. This study investigated the impact of traffic volume on microplastic (MP) and tire wear particle (TWP) pollution in road snow. An examination was conducted in a medium-sized city situated in northeastern Poland, known for being one of the cleanest regions in the country. MPs and TWPs were found at all 54 sites, regardless of the intensity of traffic. The average concentration for all samples was 354.72 pcs/L. Statistically significant differences were found between the average values of the particle concentration on low, medium, and heavy traffic roads, amounting to 62.32 pcs/L, 335.97 pcs/L, and 792.76 pcs/L, respectively. Within all three studied groups of roads, MPs and TWPs with the smallest size, ranging from 50 to 200 μm, were prevalent. In all of the studied groups of roads, four analyzed shapes of particles were found, with irregular fragments being the most abundant form (89.23%). The most frequently recorded color among the collected samples was black (99.85%), and the least frequently recorded color was blue, constituting only 0.01%. This study suggests that snow cover on the roads may act like a temporary storage of pollutants during winter particularly in the temperate climate zone and, after thawing can significantly increase the concentration of MPs and TWPs in surface waters. Possible measures to decrease the release of MPs and TWPs into the environment in the city may include reducing the traffic volume and speed, implementing street sweeping, utilizing filtration chambers, and installing stormwater bioretention systems or settling ponds. Full article

(This article belongs to the Section Urban Water Management)

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16 pages, 1420 KB

Open AccessEditor’s ChoiceArticle

Short-Term Effects of Abrupt Salinity Changes on Aquaculture Biofilter Performance and Microbial Communities

by Eliza M. Costigan, Deborah A. Bouchard, Suzanne L. Ishaq and Jean D. MacRae

Water 2024, 16(20), 2911; https://doi.org/10.3390/w16202911 - 13 Oct 2024

Cited by 2 | Viewed by 2088

Abstract

In recirculating aquaculture systems (RASs), ammonia excreted by fish must be converted to the less toxic nitrate before recirculation. Nitrifying microorganisms in biofilters used for this transformation can be sensitive to changes in salinity, which can present issues for systems that raise anadromous [...] Read more.

In recirculating aquaculture systems (RASs), ammonia excreted by fish must be converted to the less toxic nitrate before recirculation. Nitrifying microorganisms in biofilters used for this transformation can be sensitive to changes in salinity, which can present issues for systems that raise anadromous fish such as Atlantic salmon. Freshwater biofilters maintained at a low level of salinity (such as biofilters operated in coastal areas) may be better equipped to handle more drastic salinity shifts; therefore, experiments were performed on freshwater and low-salinity (3 ppt) biofilters to assess their ability to recover nitrification activity after an abrupt change in salinity (3, 20, and 33 ppt). Two-week tests showed full nitrification recovery in freshwater biofilters after a shift to 3 ppt but no ammonia oxidation in 20 or 33 ppt. Low-salinity-adapted filters (transitioned from 0 to 3 ppt) showed a small recovery (about 11%) after a shift to 20 ppt, and no activity when shifted to 33 ppt. Illumina sequencing revealed that, while nitrification was slowed or stopped with shifting salinities, the nitrifiers survived the salinity increases; conversely, the heterotrophic communities were more greatly affected and were reduced in proportion with increasing salinity. This work indicates that biofilters operated at low salinity may recover more quickly after large salinity changes, though this slight benefit may not outweigh the cost of low-level salinity maintenance. Further research into halotolerant heterotrophs in biofilms may increase the effectiveness of nitrifying biofilters under variable salinities. Full article

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

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20 pages, 11684 KB

Open AccessEditor’s ChoiceArticle

Development of a Storm-Tracking Algorithm for the Analysis of Radar Rainfall Patterns in Athens, Greece

by Apollon Bournas and Evangelos Baltas

Water 2024, 16(20), 2905; https://doi.org/10.3390/w16202905 - 12 Oct 2024

Cited by 3 | Viewed by 2439

Abstract

This research work focuses on the development and application of a storm-tracking algorithm for identifying and tracking storm cells. The algorithm first identifies storm cells on the basis of reflectivity thresholds and then matches the cells in the tracking procedure on the basis [...] Read more.

This research work focuses on the development and application of a storm-tracking algorithm for identifying and tracking storm cells. The algorithm first identifies storm cells on the basis of reflectivity thresholds and then matches the cells in the tracking procedure on the basis of their geometrical characteristics and the distance within the weather radar image. A sensitivity analysis was performed to evaluate the preferable thresholds for each case and test the algorithm’s ability to perform in different time step resolutions. Following this, we applied the algorithm to 54 rainfall events recorded by the National Technical University X-Band weather radar, the rainscanner system, from 2018 to 2023 in the Attica region of Greece. Testing of the algorithm demonstrated its efficiency in tracking storm cells over various time intervals and reflecting changes such as merging or dissipation. The results reveal the predominant southwest-to-east storm directions in 40% of cases examined, followed by northwest-to-east and south-to-north patterns. Additionally, stratiform storms showed slower north-to-west trajectories, while convective storms exhibited faster west-to-east movement. These findings provide valuable insights into storm behavior in Athens and highlight the algorithm’s potential for integration into nowcasting systems, particularly for flood early warning systems. Full article

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

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14 pages, 3023 KB

Open AccessEditor’s ChoiceArticle

Activity Concentration of Natural Radionuclides in Surface Sediments of Major River Watersheds in Korea and Assessment of Radiological Hazards

by Tae-Woo Kang, Mijeong An, Young-Un Han, Hae Jong Yang, Taegu Kang, Soojung Jung, Won-Seok Lee and Won-Pyo Park

Water 2024, 16(20), 2897; https://doi.org/10.3390/w16202897 - 12 Oct 2024

Cited by 3 | Viewed by 1599

Abstract

The assessment of potential radiation hazards in accumulated sediments in aquatic ecosystems is vital for the management and disposal of sediments. Furthermore, preemptive management of radionuclides in terrestrial ecosystems is critical for marine ecosystem conservation. We analyzed the activity concentrations of natural radionuclides [...] Read more.

The assessment of potential radiation hazards in accumulated sediments in aquatic ecosystems is vital for the management and disposal of sediments. Furthermore, preemptive management of radionuclides in terrestrial ecosystems is critical for marine ecosystem conservation. We analyzed the activity concentrations of natural radionuclides (²²⁶Ra,²³²Th, ²³⁸U, and ⁴⁰K) in the surface sediments of major river watersheds in Korea and evaluated the radiation hazards stemming from these activity concentrations. The mean activity concentrations of ²²⁶Ra and ²³⁸U were lower than the global average, whereas those of ²³²Th and ⁴⁰K were higher. The mean values of radium equivalent activity, external hazard index, and internal hazard index calculated from these activity concentrations did not exceed the recommended maximum values. The mean values of absorbed gamma dose rate in air and annual outdoor effective dose rate (AEDR_out) were higher than the global average by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) but remarkably lower than the recommended and background values by the International Commission on Radiological Protection (ICRP) and the Korea Institute of Nuclear Safety (KINS). The contribution of ⁴⁰K and ²³²Th to the AEDR_out mean value was predominant. In conclusion, the surface sediments of major river watersheds in Korea are associated with negligible radiation hazards. These findings provide fundamental data for the management and treatment of sediments in terrestrial and marine ecosystems. Full article

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25 pages, 3175 KB

Open AccessEditor’s ChoiceArticle

Exploring Deep Learning Methods for Short-Term Tide Gauge Water Level Predictions

by Marina Vicens-Miquel, Philippe E. Tissot and F. Antonio Medrano

Water 2024, 16(20), 2886; https://doi.org/10.3390/w16202886 - 11 Oct 2024

Cited by 10 | Viewed by 3090

Abstract

Accurate and timely water level predictions are essential for effective shoreline and coastal ecosystem management. As sea levels rise, the frequency and severity of coastal inundation events are increasing, causing significant societal and economic impacts. Predicting these events with sufficient lead time is [...] Read more.

Accurate and timely water level predictions are essential for effective shoreline and coastal ecosystem management. As sea levels rise, the frequency and severity of coastal inundation events are increasing, causing significant societal and economic impacts. Predicting these events with sufficient lead time is essential for decision-makers to mitigate economic losses and protect coastal communities. While machine learning methods have been developed to predict water levels at specific sites, there remains a need for more generalized models that perform well across diverse locations. This study presents a robust deep learning model for predicting water levels at multiple tide gauge locations along the Gulf of Mexico, including the open coast, embayments, and ship channels, all near major ports. The selected architecture, Seq2Seq, achieves significant improvements over the existing literature. It meets the National Oceanic and Atmospheric Administration’s (NOAA) operational criterion, with the percentage of predictions within 15 cm for lead times up to 108 h at the tide gauges of Port Isabel (92.2%) and Rockport (90.4%). These results represent a significant advancement over current models typically failing to meet NOAA’s standard beyond 48 h. This highlights the potential of deep learning models to improve water level predictions, offering crucial support for coastal management and flood mitigation. Full article

(This article belongs to the Section Oceans and Coastal Zones)

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30 pages, 10054 KB

Open AccessEditor’s ChoiceArticle

Identifying the Layout of Retrofitted Rainwater Harvesting Systems with Passive Release for the Dual Purposes of Water Supply and Stormwater Management in Northern Taiwan

by Hsin-Yuan Tsai, Chia-Ming Fan and Chao-Hsien Liaw

Water 2024, 16(20), 2894; https://doi.org/10.3390/w16202894 - 11 Oct 2024

Cited by 2 | Viewed by 2067

Abstract

Due to its unique climate and geography, Taiwan experiences abundant rainfall but still faces significant water scarcity. As a result, rainwater harvesting systems (RWHSs) have been recognized as potential water resources within both water legal and green building policies. However, the effects of [...] Read more.

Due to its unique climate and geography, Taiwan experiences abundant rainfall but still faces significant water scarcity. As a result, rainwater harvesting systems (RWHSs) have been recognized as potential water resources within both water legal and green building policies. However, the effects of climate change—manifested in more frequent extreme rainfall events and uneven rainfall distribution—have heightened the risks of both droughts and floods. This underscores the need to retrofit existing RWHSs to function as stormwater management tools and water supply sources. In Taiwan, the use of simple and cost-effective passive release systems is particularly suitable for such retrofits. Four key considerations are central to designing passive release RWHSs: the type of discharge outlet, the size of the outlet, the location of the outlet, and the system’s operational strategy. This study analyzes three commonly used outlet types—namely, the orifice, short stub fitting, and drainage pipe. Their respective discharge flow formulas and design charts have been developed and compared. To determine the appropriate outlet size, design storms with 2-, 5-, and 10-year return periods in the Taipei area were utilized to examine three different representative buildings. Selected combinations of outlet diameters and five different outlet locations were assessed. Additionally, probably hazardous rainfall events between 2014 and 2023 were used to verify the results obtained from the design storm analysis. Based on these analyses, the short stub fitting outlet type with a 15 mm outlet diameter was selected and verified. For determining the suitable discharge outlet location, a three-step process is recommended. First, the average annual water supply reliability for different scenarios and outlet locations in each representative building is calculated. Using this information, the maximum allowable decline in water supply reliability and the corresponding outlet location can be identified for each scenario. Second, break-even points between average annual water supply and regulated stormwater release curves, as well as the corresponding outlet locations, are identified. Finally, incremental analyses of average annual water supply and regulated stormwater release curves are conducted to determine the suitable outlet location for each scenario and representative building. For the representative detached house (DH), scenario 2, which designates 50% of the tank’s volume as detention space (i.e., the discharge outlet located halfway up the tank), and scenario 3, which designates 75% (i.e., the discharge outlet at one-quarter of the tank height), are the most suitable options. For the four-story building (FSB), the outlet located at one-quarter of the tank’s height is suitable for both scenarios 2 and 3. For the eight-story building (ESB), scenario 2, with the outlet at one-quarter of the tank’s height, and scenario 3, with the outlet at the lowest point on the tank’s side, are preferred. The framework developed in this study provides drainage designers with a systematic method for determining the key parameters in passive-release RWHS design at the household scale. Full article

(This article belongs to the Special Issue Watershed Hydrology and Management under Changing Climate)

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16 pages, 8312 KB

Open AccessEditor’s ChoiceArticle

Impact of Thinning and Contour-Felled Logs on Overland Flow, Soil Erosion, and Litter Erosion in a Monoculture Japanese Cypress Forest Plantation

by Moein Farahnak, Takanori Sato, Nobuaki Tanaka, Anand Nainar, Ibtisam Mohd Ghaus and Koichiro Kuraji

Water 2024, 16(20), 2874; https://doi.org/10.3390/w16202874 - 10 Oct 2024

Cited by 3 | Viewed by 2297

Abstract

This study investigated the impact of thinning and felled logs (random- and contour-felled logs) on overland flow, soil erosion, and litter erosion in a Japanese cypress forest plantation (2400 tree ha⁻¹) with low ground cover, from 2018 to 2023 in central [...] Read more.

This study investigated the impact of thinning and felled logs (random- and contour-felled logs) on overland flow, soil erosion, and litter erosion in a Japanese cypress forest plantation (2400 tree ha⁻¹) with low ground cover, from 2018 to 2023 in central Japan. Monthly measurements of overland flow and soil and litter erosion were carried out using small-sized traps across three plots (two treatments and one control). In early 2020, a 40% thinning (tree ha⁻¹) was conducted in the two treatment plots. Overland flow increased in the plot with random-felled logs during the first year post-thinning (from 139.1 to 422.0 L m⁻¹), while it remained stable in the plot with contour-felled logs (from 341.8 to 337.1 L m⁻¹). A paired-plot analysis showed no change in overland flow in the contour-felled logs plot compared to the control plot from the pre- to post-thinning periods (pre-thinning Y = 0.41X − 0.69, post-thinning Y = 0.5X + 5.46, ANCOVA: p > 0.05). However, exposure to direct rainfall on uncovered ground areas post-thinning led to increased soil and litter erosion in both treatment plots. These findings suggest that thinning combined with contour-felled logs effectively stabilizes overland flow. Therefore, thinning with contour-felled logs can be considered a viable method for mitigating overland flow in monoculture plantations with low ground cover. Full article

(This article belongs to the Special Issue Forest Hydrology and Watershed Management)

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18 pages, 24214 KB

Open AccessEditor’s ChoiceArticle

A Modified Method for Evaluating the Stability of the Finite Slope during Intense Rainfall

by Xiaoyang Wei, Weizhong Ren, Wenhui Xu, Simin Cai and Longwei Li

Water 2024, 16(20), 2877; https://doi.org/10.3390/w16202877 - 10 Oct 2024

Cited by 4 | Viewed by 1180

Abstract

The Green–Ampt (GA) model is a widely used analytical method to calculate the depth of the wetting front during intense rainfall. However, it neglects the existence of the transition layer and the seepage parallel to the slope surface. Therefore, a modified stratified Green–Ampt [...] Read more.

The Green–Ampt (GA) model is a widely used analytical method to calculate the depth of the wetting front during intense rainfall. However, it neglects the existence of the transition layer and the seepage parallel to the slope surface. Therefore, a modified stratified Green–Ampt (MSGA) model is proposed. A process to assess the stability of the finite slope during a rainfall event is demonstrated by combining the MSGA model and the limit equilibrium method. In the case of the Liangshuijing landslide, the factor of safety presents a negative correlation with the depth of the wetting front. The factor of safety obtained by the stratified Green–Ampt (SGA) model is smaller than that calculated by the MSGA model, and the gap between the factor of safety based on the two methods widens with time. The moving speed of the wetting front accelerates with the increase in the length of the slope surface, and the size effect becomes apparent when the length is short. In the initial stage of infiltration, the effect of the seepage parallel to the slope surface is small. The effect of the seepage cannot be neglected at the latter stage. The result calculated by the MSGA model agrees well with the measured result in the test. Full article

(This article belongs to the Section Hydrology)

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14 pages, 3603 KB

Open AccessEditor’s ChoiceArticle

Investigating a Century of Rainfall: The Impact of Elevation on Precipitation Changes (Northern Tuscany, Italy)

by Matteo Nigro, Michele Barsanti, Brunella Raco and Roberto Giannecchini

Water 2024, 16(19), 2866; https://doi.org/10.3390/w16192866 - 9 Oct 2024

Cited by 3 | Viewed by 2499

Abstract

Precipitation is crucial for water resource renewal, but climate change alters their frequency and amounts, challenging societies for correct and effective water management. However, modifications of precipitation dynamics appear to be not uniformly distributed, both in space and time. Even in relatively small [...] Read more.

Precipitation is crucial for water resource renewal, but climate change alters their frequency and amounts, challenging societies for correct and effective water management. However, modifications of precipitation dynamics appear to be not uniformly distributed, both in space and time. Even in relatively small areas, precipitation shows the coexistence of positive and negative trends. Local topography seems to be a strong driver of precipitation changes. Understanding precipitation changes and their relationship with local topography is crucial for society’s resilience. Taking advantage of a dense and long-lasting (1920–2019) meteorological monitoring network, we analyzed the precipitation changes over the last century in a sensitive and strategic area in the Mediterranean hotspot. The study area corresponds to northern Tuscany (Italy), where its topography comprises mountain ridges and coastal and river plains. Forty-eight rain gauges were selected with continuous annual precipitation time series. These were analyzed for trends and differences in mean annual precipitation between the stable period of 1921–1970 and the last 30-year 1990–2019. The relationship between precipitation changes and local topography was also examined. The results show the following highlights: (i) A general decrease in precipitation was found through the century, even if variability is marked. (ii) The mountain ridges show the largest decrease in mean annual precipitation. (iii) The precipitation change entity over the last century was not homogenous and was dependent on topography and geographical setting. (iv) A decrease in annual precipitation of up to 400 mm was found for the mountainous sites. Full article

(This article belongs to the Section Hydrology)

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17 pages, 4531 KB

Open AccessEditor’s ChoiceArticle

Using Artificial Neural Networks to Predict Operational Parameters of a Drinking Water Treatment Plant (DWTP)

by Stylianos Gyparakis, Ioannis Trichakis and Evan Diamadopoulos

Water 2024, 16(19), 2863; https://doi.org/10.3390/w16192863 - 9 Oct 2024

Cited by 4 | Viewed by 2355

Abstract

The scope of the present study is the estimation of key operational parameters of a drinking water treatment plant (DWTP), particularly the dosages of treatment chemicals, using artificial neural networks (ANNs) based on measurable in situ data. The case study consists of the [...] Read more.

The scope of the present study is the estimation of key operational parameters of a drinking water treatment plant (DWTP), particularly the dosages of treatment chemicals, using artificial neural networks (ANNs) based on measurable in situ data. The case study consists of the Aposelemis DWTP, where the plant operator had an estimation of the ANN output parameters for the required dosages of water treatment chemicals based on observed water quality and other operational parameters at the time. The estimated DWTP main operational parameters included residual ozone (O₃) and dosages of the chemicals used: anionic polyelectrolyte (ANPE), poly-aluminum chloride hydroxide sulfate (PACl), and chlorine gas (Cl_2(g)). Daily measurable results of water sample analysis and recordings from the DWTP Supervisory Control and Data Acquisition System (SCADA), covering a period of 38 months, were used as input parameters for the artificial neural network (1188 values for each of the 14 measurable parameters). These input parameters included: raw water supply (Q), raw water turbidity (T₁), treated water turbidity (T₂), treated water residual free chlorine (Cl₂), treated water concentration of residual aluminum (Al), filtration bed inlet water turbidity (T₃), daily difference in water height in reservoir (∆H), raw water pH (pH₁), treated water pH (pH₂), and daily consumption of DWTP electricity (El). Output/target parameters were: residual O₃ after ozonation (O₃), anionic polyelectrolyte (ANPE), poly-aluminum chloride hydroxide sulfate (PACl), and chlorine gas supply (Cl_2(g)). A total of 304 different ANN models were tested, based on the best test performance (tperf) indicator. The one with the optimum performance indicator was selected. The scenario finally chosen was the one with 100 neural networks, 100 nodes, 42 hidden nodes, 10 inputs, and 4 outputs. This ANN model achieved excellent simulation results based on the best testing performance indicator, which suggests that ANNs are potentially useful tools for the prediction of a DWTP’s main operational parameters. Further research could explore the prediction of water chemicals used in a DWTP by using ANNs with a smaller number of operational parameters to ensure greater flexibility, without prohibitively reducing the reliability of the prediction model. This could prove useful in cases with a much higher sample size, given the data-demanding nature of ANNs. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence (AI) in Water Quality Monitoring)

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21 pages, 5459 KB

Open AccessEditor’s ChoiceArticle

A Practical, Adaptive, and Scalable Real-Time Control Approach for Stormwater Storage Systems

by Ruijie Liang, Holger Robert Maier, Mark Andrew Thyer and Graeme Clyde Dandy

Water 2024, 16(19), 2844; https://doi.org/10.3390/w16192844 - 7 Oct 2024

Cited by 3 | Viewed by 3941

Abstract

Traditionally, urban stormwater infrastructure systems consist of passive infrastructure that is not actively controlled in response to rainfall events. Recently, real-time control (RTC) has been considered as a means to significantly increase the capacity and lifespan of these systems. This paper introduces the [...] Read more.

Traditionally, urban stormwater infrastructure systems consist of passive infrastructure that is not actively controlled in response to rainfall events. Recently, real-time control (RTC) has been considered as a means to significantly increase the capacity and lifespan of these systems. This paper introduces the target flow control systems (TFCS) approach, which can use real-time control of systems of storages to achieve the desired flow conditions at the locations of interest. The first distinctive feature of this approach is that it does not require calibration to catchment-specific data, unlike existing approaches. This means that the TFCS approach is generally applicable to different catchments and is able to respond to future changes in runoff due to land use and/or climate change. The second distinctive feature is that the approach only requires storage-level information measured in real time with the aid of low-cost pressure sensors. This means that the approach is practical and relatively easy to implement. In addition to the introduction of the novel TFCS approach, a key innovation of this study is that the approach is tested on three case studies, each with different physical configurations and stormwater management objectives. Another key innovation is that the TFCS approach is compared to five RTC approaches, including three of the best-performing advanced approaches from the literature. Comparisons of multiple RTC approaches that consider both performance and practicality across multiple case studies are rare. Results show that the TFCS approach is the only one of the five control approaches analysed that has both the best overall performance and the highest level of practicality. The outcomes highlight the potential of the TFCS approach as a practical RTC approach that is applicable to a wide range of catchments with different stormwater management objectives. By maximizing the performance of existing stormwater storages, the TFCS approach can potentially extend the lifespan of existing infrastructure and avoid costly upgrades due to increased runoff caused by land use and climate change. Full article

(This article belongs to the Special Issue Urban Stormwater Control, Utilization, and Treatment)

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15 pages, 1835 KB

Open AccessEditor’s ChoiceArticle

Comparative Evaluation of Evapotranspiration and Optimization Schemes for Green Roof Runoff Simulations Using HYDRUS-1D

by Hwansuk Kim, Haein Sim, Seungwan Hong, Zong Woo Geem, Hafzullah Aksoy, Yongseok Hong and Jaeyoung Yoon

Water 2024, 16(19), 2835; https://doi.org/10.3390/w16192835 - 6 Oct 2024

Cited by 1 | Viewed by 1349

Abstract

The use of green roofs, a low-impact development practice, can be an effective means of reducing direct runoff in urban centers. Green roof modeling can enable efficient design by preliminarily grasping the behavior of the green roof system according to specific configurations. In [...] Read more.

The use of green roofs, a low-impact development practice, can be an effective means of reducing direct runoff in urban centers. Green roof modeling can enable efficient design by preliminarily grasping the behavior of the green roof system according to specific configurations. In this study, we aimed to find appropriate evapotranspiration and parameter optimization schemes for HYDRUS-1D, a commonly used modeling tool for green roofs. Comparative studies of this sort in the context of green roof runoff modeling have not been conducted previously and are important in guiding users to overcome the difficulties of choosing the right numerical schemes for an accurate prediction of runoff from a green roof. As a study site, the Portland Building Ecoroof in Portland, Oregon, USA, was chosen, as green roof configurations and observed data for climate and runoff were available. From the simulation results of the runoff volume, the Blaney–Criddle method, which was considered an alternative, was found to be appropriate for calculating evapotranspiration from a green roof (R² = 0.82) relative to the Hargreaves method built in HYDRUS-1D (R² = 0.46). In addition, this study showed that the optimization method using the harmony search algorithm, which was proposed as an alternative optimizer, was better (R² = 0.95) than that of the HYDRUS-1D’s own optimization module (R² = 0.82) in calibrating HYDRUS-1D for green roof runoff. The findings are thought to be useful in guiding modelers who are considering using HYDRUS-1D for green roof runoff simulations. Full article

(This article belongs to the Section Urban Water Management)

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23 pages, 11503 KB

Open AccessEditor’s ChoiceArticle

Novel Framework for Exploring Human–Water Symbiosis Relationship: Analysis, Quantification, Discrimination, and Attribution

by Xi Qin, Qiting Zuo, Qingsong Wu and Junxia Ma

Water 2024, 16(19), 2829; https://doi.org/10.3390/w16192829 - 6 Oct 2024

Viewed by 1709

Abstract

There is an interdependent symbiotic relationship between humans and water; scientific and effective assessment of the human–water symbiosis relationship is of great significance for the promotion of sustainable development. This study developed a novel framework of the human–water symbiosis relationship under an integrated [...] Read more.

There is an interdependent symbiotic relationship between humans and water; scientific and effective assessment of the human–water symbiosis relationship is of great significance for the promotion of sustainable development. This study developed a novel framework of the human–water symbiosis relationship under an integrated perspective, which included theoretical interpretation, quantitative assessment, pattern discrimination, and an attribution analysis. Based on the symbiosis theory, the theoretical analysis of the human–water relationship was carried out to analyze the three basic elements of the human–water system, and then the evaluation index system of the human–water symbiosis system was constructed to quantitatively assess the development level of the human system and the water system. The Lotka–Volterra model was used to identify the symbiotic pattern, and the human–water symbiosis index was calculated to characterize the health state of the human–water symbiosis system. The main influencing factors of the human–water symbiosis system were further identified through an attribution analysis. Finally, a case study was carried out with 18 cities in Henan Province. Results reveal that (a) the proposed method can effectively realize the quantitative characterization of the human–water symbiosis relationship, with good applicability and obvious advantages; (b) the human–water symbiosis pattern of cities in Henan Province is dominated by the “human system parasitizes water system (H⁺W⁻)” pattern, and more attention should be paid to the water system in the subsequent development of it; and (c) the main factors influencing the human system, the water system, and the human–water symbiosis system are the research and development (R&D) personnel equivalent full-time (H7), per capita water resources (W1), and proportion of water conservancy and ecological water conservancy construction investment (W6), respectively. The findings can provide theoretical and methodological support for the study of the human–water symbiosis relationship and sustainable development in other regions. Full article

(This article belongs to the Section Water Resources Management, Policy and Governance)

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13 pages, 545 KB

Open AccessEditor’s ChoiceArticle

How Top-Down Water Regulation Affects the Financial Performance of Enterprises: The River Chief System in China as an Example

by Peipei Zhao, Jiawen Li and Xin Luo

Water 2024, 16(19), 2827; https://doi.org/10.3390/w16192827 - 5 Oct 2024

Cited by 2 | Viewed by 1620

Abstract

As a top-down type of water regulation, the River Chief System (RCS) in China has effectively enhanced urban water quality. Simultaneously, environmental control significantly impacts the financial performance of enterprises. In recent years, the tension between environmental protection and economic development has escalated, [...] Read more.

As a top-down type of water regulation, the River Chief System (RCS) in China has effectively enhanced urban water quality. Simultaneously, environmental control significantly impacts the financial performance of enterprises. In recent years, the tension between environmental protection and economic development has escalated, underscoring the undeniable economic ramifications of stringent water regulations. Enterprises are the fundamental agents of economic activities and environmental impact, thus becoming the primary targets of water environment regulatory policies. This study adopts the differences-in-differences (DID) method and uses a sample of listed enterprises in the Yangtze River Economic Belt region from 2010 to 2021 to study the impact of the RCS on the financial performance of enterprises. The results show that the RCS harms the financial performance of enterprises. This impact primarily manifests through increased environmental protection investments. Conversely, the RCS does not have a positive influence on enterprises’ technological innovation. This indicates the challenge of stringent top-down environmental regulations in stimulating short-term technological advancements and enhancing enterprise performance. Moreover, the adverse effects of the RCS on financial performance are notably pronounced for non-state-owned enterprises and those located in the upper Yangtze River Economic Belt. This suggests that private enterprises and those in less-developed regions exhibit lower resilience to top-down environmental regulations. Full article

(This article belongs to the Special Issue Studies on Water Resource and Environmental Policies)

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15 pages, 2171 KB

Open AccessEditor’s ChoiceArticle

Experimental Study on the Impact of Sorption-Desorption on Nitrate Isotopes

by Yajing Zhao, Zhenbin Li, Chaoyao Zan, Yiman Li, Yan Zhang and Tianming Huang

Water 2024, 16(19), 2807; https://doi.org/10.3390/w16192807 - 2 Oct 2024

Viewed by 1406

Abstract

Nitrate pollution is a global environmental problem, and mean nitrate levels have risen by an estimated 36% in global waterways since 1990. Tracing nitrate sources is important for water quality management, and nitrate isotopes (δ¹⁵N-NO₃⁻ and δ¹⁸O-NO [...] Read more.

Nitrate pollution is a global environmental problem, and mean nitrate levels have risen by an estimated 36% in global waterways since 1990. Tracing nitrate sources is important for water quality management, and nitrate isotopes (δ¹⁵N-NO₃⁻ and δ¹⁸O-NO₃⁻) are commonly used for this purpose because of the different isotopic compositions of different sources. However, the impact of nitrate sorption on matrix and desorption from matrix on N and O isotopic composition of nitrate in liquid phase has not been well clarified. To explore the mechanism for the changes in nitrate concentration and isotopes in liquid phase during sorption and desorption, this study took a shale sample (enriched in clay minerals and commonly exposed in the Earth), conducted a series of laboratory experiments for nitrate sorption and desorption, and studied the impact of sorption and desorption on nitrate N and O isotopic composition in liquid phase. The results showed that the shale sample exhibited a rapid sorption and desorption rate for nitrate in the surface water samples, with the nitrate concentration in the solution decreasing from 14.3 mg/L to 4.1 mg/L within 5 min. The sorption data fit the Langmuir model better than that of the Freundlich model. The maximum possible sorption (Q_max) for the shale sample was estimated to be 46 μg/g. Preliminary laboratory experiments showed that changes in δ¹⁵N-NO₃⁻ values were not obvious, and changes in δ¹⁸O-NO₃⁻ values in liquid phase were minor during sorption and desorption of the shale sample, suggesting that nitrogen isotopic fractionation can be neglected, and the sorption of nitrate by the shale sample has a very limited impact on the distribution of nitrate isotopes in liquid phase. However, the impact of nitrate desorption on the nitrate isotopes in liquid phase depends on the isotopic composition of exchangeable nitrate in the solid phase, which may be related to antecedent water–rock interactions. This study provides important information for elucidating the evolution mechanism of nitrate and its isotopic compositions following sorption-desorption, and is conducive to revealing the nitrogen cycle law in the environment. Full article

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

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21 pages, 2910 KB

Open AccessEditor’s ChoiceArticle

Streamflow Prediction with Time-Lag-Informed Random Forest and Its Performance Compared to SWAT in Diverse Catchments

by Desalew Meseret Moges, Holger Virro, Alexander Kmoch, Raj Cibin, Rohith A. N. Rohith, Alberto Martínez-Salvador, Carmelo Conesa-García and Evelyn Uuemaa

Water 2024, 16(19), 2805; https://doi.org/10.3390/w16192805 - 2 Oct 2024

Cited by 6 | Viewed by 5214

Abstract

This study introduces a time-lag-informed Random Forest (RF) framework for streamflow time-series prediction across diverse catchments and compares its results against SWAT predictions. We found strong evidence of RF’s better performance by adding historical flows and time-lags for meteorological values over using only [...] Read more.

This study introduces a time-lag-informed Random Forest (RF) framework for streamflow time-series prediction across diverse catchments and compares its results against SWAT predictions. We found strong evidence of RF’s better performance by adding historical flows and time-lags for meteorological values over using only actual meteorological values. On a daily scale, RF demonstrated robust performance (Nash–Sutcliffe efficiency [NSE] > 0.5), whereas SWAT generally yielded unsatisfactory results (NSE < 0.5) and tended to overestimate daily streamflow by up to 27% (PBIAS). However, SWAT provided better monthly predictions, particularly in catchments with irregular flow patterns. Although both models faced challenges in predicting peak flows in snow-influenced catchments, RF outperformed SWAT in an arid catchment. RF also exhibited a notable advantage over SWAT in terms of computational efficiency. Overall, RF is a good choice for daily predictions with limited data, whereas SWAT is preferable for monthly predictions and understanding hydrological processes in depth. Full article

(This article belongs to the Special Issue Climate Change and Hydrological Processes)

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35 pages, 10116 KB

Open AccessEditor’s ChoiceArticle

Validation of an Enhanced Drinking Water Temperature Model during Distribution

by Mirjam Blokker, Quan Pan and Karel van Laarhoven

Water 2024, 16(19), 2796; https://doi.org/10.3390/w16192796 - 1 Oct 2024

Cited by 1 | Viewed by 1633

Abstract

Drinking water temperatures are expected to increase in the Netherlands due to climate change and the installation of district heating networks as part of the energy transition. To determine effective measures to prevent undesirable temperature increases in drinking water, a model was developed. [...] Read more.

Drinking water temperatures are expected to increase in the Netherlands due to climate change and the installation of district heating networks as part of the energy transition. To determine effective measures to prevent undesirable temperature increases in drinking water, a model was developed. This model describes the temperature in the drinking water distribution network as a result of the transfer of heat from the climate and above and underground heat sources through the soil. The model consists of two coupled applications. The extended soil temperature model (STM+) describes the soil temperatures using a two-dimensional finite element method that includes a drinking water pipe and two hot water pipes coupled with a micrometeorology model. The extended water temperature model (WTM+) describes the drinking water temperature as a function of the surrounding soil temperature (the boundary temperature resulting from the STM+), the thermal sphere of influence where the drinking water temperature influences the soil temperature, and the hydraulics in the drinking water network. Both models are validated with field measurements. This study describes the WTM+. Previous models did not consider the cooling effect of the drinking water on the surrounding soil, which led to an overestimation of the boundary temperature and how quickly the drinking water temperature reaches this boundary temperature. The field measurements show the improved accuracy of the WTM+ when considering one to two times the radius of the drinking water pipe as the thermal sphere of influence around the pipe. Full article

(This article belongs to the Special Issue Urban Water Systems: Challenges in Current Environment)

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30 pages, 2600 KB

Open AccessEditor’s ChoiceReview

Selection, Planning, and Modelling of Nature-Based Solutions for Flood Mitigation

by James Griffiths, Karine E. Borne, Annette Semadeni-Davies and Chris C. Tanner

Water 2024, 16(19), 2802; https://doi.org/10.3390/w16192802 - 1 Oct 2024

Cited by 9 | Viewed by 12944

Abstract

The use of nature-based solutions (NBSs) for hazard mitigation is increasing. In this study, we review the use of NBSs for flood mitigation using a strengths, weaknesses, opportunities, and threats (SWOT) analysis framework for commonly used NBSs. Approaches reviewed include retention and detention [...] Read more.

The use of nature-based solutions (NBSs) for hazard mitigation is increasing. In this study, we review the use of NBSs for flood mitigation using a strengths, weaknesses, opportunities, and threats (SWOT) analysis framework for commonly used NBSs. Approaches reviewed include retention and detention systems, bioretention systems, landcover and soil management, river naturalisation and floodplain management, and constructed and natural wetlands. Existing tools for identification and quantification of direct benefits and co-benefits of NBSs are then reviewed. Finally, approaches to the modelling of NBSs are discussed, including the type of model and model parameterisation. After outlining knowledge gaps within the current literature and research, a roadmap for development, modelling, and implementation of NBSs is presented. Full article

(This article belongs to the Special Issue Bridging the Gaps: Hydrological Research for Sustainable River Management)

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15 pages, 1905 KB

Open AccessEditor’s ChoiceArticle

Effect of Light Intensity on the Growth and Nutrient Uptake of the Microalga Chlorella sorokiniana Cultivated in Biogas Plant Digestate

by Thomas L. Palikrousis, Christos Manolis, Sotirios D. Kalamaras and Petros Samaras

Water 2024, 16(19), 2782; https://doi.org/10.3390/w16192782 - 30 Sep 2024

Cited by 17 | Viewed by 6096

Abstract

This study investigated the effect of light intensity on the growth and nutrient uptake of Chlorella sorokiniana cultivated in nitrogen-rich anaerobic digestion wastewater. Three light intensities (20, 68, and 162 µmol m⁻² s⁻¹) were applied over a 30-day period with [...] Read more.

This study investigated the effect of light intensity on the growth and nutrient uptake of Chlorella sorokiniana cultivated in nitrogen-rich anaerobic digestion wastewater. Three light intensities (20, 68, and 162 µmol m⁻² s⁻¹) were applied over a 30-day period with a 16:8 h light–dark photoperiod. The goal was to understand how light affects biomass productivity, nutrient assimilation, and biochemical composition under varying nitrogen concentrations originating from biogas plant digestate, up to 5 g L⁻¹. The results showed that higher light intensities significantly boosted biomass production, achieving a five-fold increase at 162 µmol m⁻² s⁻¹ compared to 20 µmol m⁻² s⁻¹. Nutrient uptake followed a similar pattern, with 94% of ammonium nitrogen removed in 7 days under high light, compared to 55% after 30 days under low light. Phosphorus content was also completely removed after 7 days under light intensities of 68 and 162 µmol m⁻² s⁻¹. Additionally, elevated light intensity led to increased lipid accumulation (from 29.7% to 34%) and reduced protein content (from 30.9% to 26.1%), with carbohydrate content not being affected by light intensity. These findings highlight light intensity as a critical factor for optimizing microalgae cultivation in nitrogen-rich biogas digestate, promoting both effective nutrient removal and biomass production for potential bioenergy applications. Full article

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29 pages, 7501 KB

Open AccessEditor’s ChoiceArticle

Water Resources’ AI–ML Data Uncertainty Risk and Mitigation Using Data Assimilation

by Nick Martin and Jeremy White

Water 2024, 16(19), 2758; https://doi.org/10.3390/w16192758 - 27 Sep 2024

Cited by 8 | Viewed by 1974

Abstract

Artificial intelligence (AI), including machine learning (ML) and deep learning (DL), learns by training and is restricted by the amount and quality of training data. Training involves a tradeoff between prediction bias and variance controlled by model complexity. Increased model complexity decreases prediction [...] Read more.

Artificial intelligence (AI), including machine learning (ML) and deep learning (DL), learns by training and is restricted by the amount and quality of training data. Training involves a tradeoff between prediction bias and variance controlled by model complexity. Increased model complexity decreases prediction bias, increases variance, and increases overfitting possibilities. Overfitting is a significantly smaller training prediction error relative to the trained model prediction error for an independent validation set. Uncertain data generate risks for AI–ML because they increase overfitting and limit generalization ability. Specious confidence in predictions from overfit models with limited generalization ability, leading to misguided water resource management, is the uncertainty-related negative consequence. Improved data is the way to improve AI–ML models. With uncertain water resource data sets, like stream discharge, there is no quick way to generate improved data. Data assimilation (DA) provides mitigation for uncertainty risks, describes data- and model-related uncertainty, and propagates uncertainty to results using observation error models. A DA-derived mitigation example is provided using a common-sense baseline, derived from an observation error model, for the confirmation of generalization ability and a threshold identifying overfitting. AI–ML models can also be incorporated into DA to provide additional observations for assimilation or as a forward model for prediction and inverse-style calibration or training. The mitigation of uncertain data risks using DA involves a modified bias–variance tradeoff that focuses on increasing solution variability at the expense of increased model bias. Increased variability portrays data and model uncertainty. Uncertainty propagation produces an ensemble of models and a range of predictions. Full article

(This article belongs to the Section Water Resources Management, Policy and Governance)

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16 pages, 2262 KB

Open AccessEditor’s ChoiceArticle

Decontamination Potential of Ultraviolet Type C Radiation in Water Treatment Systems: Targeting Microbial Inactivation

by Abayomi Olusegun Adeniyi and Modupe Olufunmilayo Jimoh

Water 2024, 16(19), 2725; https://doi.org/10.3390/w16192725 - 25 Sep 2024

Cited by 5 | Viewed by 6649

Abstract

Access to safe water and sanitation is a critical global challenge, posing significant health risks worldwide due to waterborne diseases. This study investigates the efficacy of ultraviolet type C radiation as a disinfection method for improving water quality. The research elucidates UV-C’s mechanism [...] Read more.

Access to safe water and sanitation is a critical global challenge, posing significant health risks worldwide due to waterborne diseases. This study investigates the efficacy of ultraviolet type C radiation as a disinfection method for improving water quality. The research elucidates UV-C’s mechanism of action, highlighting its ability to disrupt DNA and RNA replication, thereby inactivating pathogens. Furthermore, the study analyses the influence of key factors on UV-C disinfection effectiveness, including water turbidity and the presence of dissolved organic matter, which can attenuate UV-C penetration and reduce treatment efficiency. The experimental results demonstrate a substantial reduction in microbial content following UV-C treatment. River water samples exhibited a 57.143% reduction in microbial load, while well water samples showed a 50% reduction. Notably, Escherichia coli (E. coli) concentrations decreased significantly, with an 83.33% reduction in well water and a 62.5% reduction in borehole water. This study makes a novel contribution to the understanding of UV-C disinfection by identifying the presence of resistant organisms, including Adenoviruses, Bacterial spores, and the Protozoan Acanthamoeba, in water samples. This finding expands the scope of UV-C research beyond easily culturable bacteria. To address this challenge, future investigations should explore synergistic disinfection strategies, such as combining UV-C treatment with advanced oxidation processes. Optimising UV-C system designs and developing robust, real-time monitoring systems capable of detecting and quantifying known and emerging UV-resistant pathogens are crucial for ensuring comprehensive water decontamination. Full article

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

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25 pages, 398 KB

Open AccessEditor’s ChoiceReview

Beyond Bioremediation: The Untapped Potential of Microalgae in Wastewater Treatment

by Davide Liberti, Filipa Pinheiro, Beatriz Simões, João Varela and Luísa Barreira

Water 2024, 16(19), 2710; https://doi.org/10.3390/w16192710 - 24 Sep 2024

Cited by 22 | Viewed by 11518

Abstract

Microalgae-based wastewater bioremediation has emerged as a promising and sustainable solution for water purification by harnessing the natural ability of microalgae to absorb and transform pollutants. In the literature, it is possible to find diverse microalgae applications in wastewater treatment, highlighting their efficiency [...] Read more.

Microalgae-based wastewater bioremediation has emerged as a promising and sustainable solution for water purification by harnessing the natural ability of microalgae to absorb and transform pollutants. In the literature, it is possible to find diverse microalgae applications in wastewater treatment, highlighting their efficiency in nutrient removal, heavy metal sequestration, and overall water quality enhancement. Although microalgae demonstrate remarkable potential for wastewater treatment, there is a critical gap in research concerning the utilization of biomass produced during the treatment process, including large-scale biomass harvesting methods, economic viability assessments, and the exploration of innovative downstream applications. By shedding light on these deficiencies, the aim of this review is to encourage further research and development to maximize the potential of microalgae in removing wastewater pollution and the application of biomass derived from the treatment. In conclusion, this review not only underscores the overall efficiency of microalgae in wastewater bioremediation but also emphasizes the necessity of a more comprehensive approach that considers the full lifecycle of microalgae, from wastewater treatment to innovative applications of biomass, addressing both environmental and economic concerns. Full article

(This article belongs to the Special Issue Persistent and Emerging Organic Contaminants in Natural Environments)

28 pages, 910 KB

Open AccessEditor’s ChoiceReview

Microplastics’ Impact on the Environment and the Challenging Selection of Reliable Key Biomonitors

by Luigi Rosati, Federica Carraturo, Fiore Capozzi, Teresa Chianese, Alessandra La Pietra, Michela Salamone, Valeria Spagnuolo, Ida Ferrandino and Simonetta Giordano

Water 2024, 16(18), 2637; https://doi.org/10.3390/w16182637 - 17 Sep 2024

Cited by 7 | Viewed by 6066

Abstract

Microplastics (MPs) persist for long periods in the environment, causing adverse effects on aquatic and terrestrial ecosystems. The accumulation of MPs in various trophic levels mostly depends on weathering phenomena, their reduced dimensions and the improved bioavailability; this ultimately causes their ingestion by [...] Read more.

Microplastics (MPs) persist for long periods in the environment, causing adverse effects on aquatic and terrestrial ecosystems. The accumulation of MPs in various trophic levels mostly depends on weathering phenomena, their reduced dimensions and the improved bioavailability; this ultimately causes their ingestion by organisms living in different niches. The modern concern about MPs toxicity collides with the current unavailability of standardized and reliable methodologies to assess the risks associated with the exposure of organisms from different habitats. Hence, the identification and selection of appropriate biomonitors for MPs pollution risk assessment should focus on the identification of easy-to-implement assays, rapidly interpretable results (e.g., based on the MPs bioaccumulation capabilities in their tissues) and standardizable methodologies. The present review analyzed some emerging biomonitors exploited for MPs evaluation, selected and examined according to their potential use as specific biological indicators for diverse environments. The research was focused on plants, as biological models for airborne microfibers toxicity evaluation; mussels, as key organisms for the establishment of MPs accumulation in marine environments; land snails, representing emerging organisms selected for studies of MPs’ impact on soil. Furthermore, recent findings evidenced the influence of microplastics on the composition of environmental microbiota, enhancing pathogenic biofilms formation, leading to increased water, soil, food, crops and waste contamination. Disposing of harmonized and validated methods to study MPs’ impact on the environment, integrated with promising machine learning tools, might sensibly support the risk management strategies protecting human and animal health. Full article

(This article belongs to the Section Water and One Health)

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20 pages, 2569 KB

Open AccessEditor’s ChoiceArticle

Seasonal Variability and Hydrological Patterns Influence the Long-Term Trends of Nutrient Loads in the River Po

by Edoardo Cavallini, Pierluigi Viaroli, Mariachiara Naldi, Mattia Saccò, Alessandro Scibona, Elena Barbieri, Silvia Franceschini and Daniele Nizzoli

Water 2024, 16(18), 2628; https://doi.org/10.3390/w16182628 - 16 Sep 2024

Cited by 8 | Viewed by 2523

Abstract

This study investigates the long-term trends (1992–2022) of nitrogen and phosphorus loadings exported by the River Po to the Adriatic Sea, to better analyse how changes in hydrology are affecting the timing and magnitude of river nutrient loads. We used 30 years of [...] Read more.

This study investigates the long-term trends (1992–2022) of nitrogen and phosphorus loadings exported by the River Po to the Adriatic Sea, to better analyse how changes in hydrology are affecting the timing and magnitude of river nutrient loads. We used 30 years of monitoring data in order to (a) identify the main temporal patterns and their interactions at a decadal, annual and seasonal scale, (b) estimate precipitation effects on load formation and evaluate whether and to which extent the hydrological regime affects nutrient export across the years and (c) analyse the nutrient export regime at a monthly scale and the main transport dynamic of N and P chemical species (hydrological vs. biogeochemical control). The long-term analysis shows a general decrease of both P and N loadings, but the trends are different between the elements and their chemical species, as well as undergoing different seasonal variations. We found a statistically significant relationships between precipitation and loads, which demonstrates that precipitation patterns drive the exported load at the intra- and interannual time scales considered in this study. Precipitation-induced load trends trigger seasonal changes in nutrient deliveries to the sea, peaking in spring and autumn. The nitrogen decrease is mainly concentrated in the summer dry period, while total phosphorus diminishes mainly in spring and autumn. This mismatch of N and P results in variable molar N:P ratios within the year. The effects of extreme drought and flood events, along with the progressive decrease in the snowmelt contribution to water fluxes, are expected to exacerbate the variability in the N and P loadings, which in turn is expected to perturbate the biodiversity, food webs and trophic state of the Northern Adriatic Sea. Full article

(This article belongs to the Special Issue Anthropogenic and Climatic Disturbances in Aquatic Ecosystems: Multiscale Spatio-Temporal Evolution and Effects)

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22 pages, 3249 KB

Open AccessEditor’s ChoiceArticle

LSTM-Autoencoder Based Detection of Time-Series Noise Signals for Water Supply and Sewer Pipe Leakages

by Yungyeong Shin, Kwang Yoon Na, Si Eun Kim, Eun Ji Kyung, Hyun Gyu Choi and Jongpil Jeong

Water 2024, 16(18), 2631; https://doi.org/10.3390/w16182631 - 16 Sep 2024

Cited by 8 | Viewed by 4542

Abstract

The efficient management of urban water distribution networks is crucial for public health and urban development. One of the major challenges is the quick and accurate detection of leaks, which can lead to water loss, infrastructure damage, and environmental hazards. Many existing leak [...] Read more.

The efficient management of urban water distribution networks is crucial for public health and urban development. One of the major challenges is the quick and accurate detection of leaks, which can lead to water loss, infrastructure damage, and environmental hazards. Many existing leak detection methods are ineffective, especially in complex and aging pipeline networks. If these limitations are not overcome, it can result in a chain of infrastructure failures, exacerbating damage, increasing repair costs, and causing water shortages and public health risks. The leak issue is further complicated by increasing urban water demand, climate change, and population growth. Therefore, there is an urgent need for intelligent systems that can overcome the limitations of traditional methodologies and leverage sophisticated data analysis and machine learning technologies. In this study, we propose a reliable and advanced method for detecting leaks in water pipes using a framework based on Long Short-Term Memory (LSTM) networks combined with autoencoders. The framework is designed to manage the temporal dimension of time-series data and is enhanced with ensemble learning techniques, making it sensitive to subtle signals indicating leaks while robustly dealing with noise signals. Through the integration of signal processing and pattern recognition, the machine learning-based model addresses the leak detection problem, providing an intelligent system that enhances environmental protection and resource management. The proposed approach greatly enhances the accuracy and precision of leak detection, making essential contributions in the field and offering promising prospects for the future of sustainable water management strategies. Full article

(This article belongs to the Special Issue Prediction and Assessment of Hydrological Processes)

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24 pages, 853 KB

Open AccessEditor’s ChoiceReview

The Convergence of Antibiotic Contamination, Resistance, and Climate Dynamics in Freshwater Ecosystems

by Marcelo Pedrosa Gomes

Water 2024, 16(18), 2606; https://doi.org/10.3390/w16182606 - 14 Sep 2024

Cited by 35 | Viewed by 12236

Abstract

The convergence of antibiotic contamination, antimicrobial resistance (AMR), and climate dynamics poses a critical environmental and public health challenge. Freshwater ecosystems are increasingly threatened by the persistent presence of antibiotics, which, coupled with rising global temperatures, accelerate the development and spread of AMR. [...] Read more.

The convergence of antibiotic contamination, antimicrobial resistance (AMR), and climate dynamics poses a critical environmental and public health challenge. Freshwater ecosystems are increasingly threatened by the persistent presence of antibiotics, which, coupled with rising global temperatures, accelerate the development and spread of AMR. This review examines the sources, pathways, and mechanisms through which antibiotics enter freshwater systems and how climate change exacerbates these processes. This review discusses this convergence’s ecological and human health impacts, highlighting the implications for biodiversity and public health. It also explored the current monitoring and mitigation strategies, including advanced oxidation processes, natural-based solutions, and policy interventions. Finally, this review identifies critical research gaps and proposes future directions for managing the intertwined threats of antibiotic contamination, resistance, and climate change. It emphasizes the need for integrated, multidisciplinary approaches to protect freshwater resources in an increasingly volatile global environment. Full article

(This article belongs to the Special Issue Toxicology in Freshwater Ecosystems)

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41 pages, 2467 KB

Open AccessEditor’s ChoiceArticle

Comprehensive Resilience Assessment Framework for Water Distribution Networks

by Joana Carneiro, Dália Loureiro, Marta Cabral and Dídia Covas

Water 2024, 16(18), 2611; https://doi.org/10.3390/w16182611 - 14 Sep 2024

Cited by 6 | Viewed by 2645

Abstract

A novel comprehensive resilience assessment framework for drinking water systems is proposed integrating different resilience perspectives (i.e., robustness, autonomy, flexibility, reliability, preparedness and recovery), oriented by objectives, criteria and metrics, applicable at the tactical level. The resilience assessment framework is applied to a [...] Read more.

A novel comprehensive resilience assessment framework for drinking water systems is proposed integrating different resilience perspectives (i.e., robustness, autonomy, flexibility, reliability, preparedness and recovery), oriented by objectives, criteria and metrics, applicable at the tactical level. The resilience assessment framework is applied to a Portuguese real water distribution network, enabling the evaluation of the system’s resilience. The infrastructure dimension is the main contributor to the low resilience results, particularly in terms of infrastructural robustness, as the infrastructure has exceeded the average service life and has low rehabilitation rates. In terms of autonomy, the system highly depends on external water and energy sources. Regarding the service dimension, most of the drinking water available is used for non-potable uses (e.g., irrigation), without alternative sources. The detailed diagnosis identified network area R6 as the priority area. Assets rehabilitation, increasing storage capacity, finding alternative water and energy sources, and minimizing non-potable uses are relevant improvement measures that promote the reinforcement of the system’s resilience. The resilience assessment framework is a very useful tool for the daily and tactical management of drinking water systems. Full article

(This article belongs to the Section Urban Water Management)

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15 pages, 6817 KB

Open AccessEditor’s ChoiceArticle

A Fully Connected Neural Network (FCNN) Model to Simulate Karst Spring Flowrates in the Umbria Region (Central Italy)

by Francesco Maria De Filippi, Matteo Ginesi and Giuseppe Sappa

Water 2024, 16(18), 2580; https://doi.org/10.3390/w16182580 - 12 Sep 2024

Cited by 9 | Viewed by 1948

Abstract

In the last decades, climate change has led to increasingly frequent drought events within the Mediterranean area, creating an urgent need of a more sustainable management of groundwater resources exploited for drinking and agricultural purposes. One of the most challenging issues is to [...] Read more.

In the last decades, climate change has led to increasingly frequent drought events within the Mediterranean area, creating an urgent need of a more sustainable management of groundwater resources exploited for drinking and agricultural purposes. One of the most challenging issues is to provide reliable simulations and forecasts of karst spring discharges, whose reduced information, as well as the hydrological processes involving their feeding aquifers, is often a big issue for water service managers and researchers. In order to plan a sustainable water resource exploitation that could face future shortages, the groundwater availability should be assessed by continuously monitoring spring discharge during the hydrological year, using collected data to better understand the past behaviour and, possibly, forecast the future one in case of severe droughts. The aim of this paper is to understand the factors that govern different spring discharge patterns according to rainfall inputs and to present a model, based on artificial neural network (ANN) data training and cross-correlation analyses, to evaluate the discharge of some karst spring in the Umbria region (Central Italy). The model used is a fully connected neural network (FCNN) and has been used both for filling gaps in the spring discharge time series and for simulating the response of six springs to rainfall seasonal patterns from a 20-year continuous daily record, collected and provided by the Regional Environmental Protection Agency (ARPA) of the Umbria region. Full article

(This article belongs to the Special Issue Recent Advances in Karstic Hydrogeology, 2nd Edition)

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28 pages, 26581 KB

Open AccessEditor’s ChoiceArticle

Empirical Bayesian Kriging, a Robust Method for Spatial Data Interpolation of a Large Groundwater Quality Dataset from the Western Netherlands

by Mojtaba Zaresefat, Reza Derakhshani and Jasper Griffioen

Water 2024, 16(18), 2581; https://doi.org/10.3390/w16182581 - 12 Sep 2024

Cited by 25 | Viewed by 5919

Abstract

No single spatial interpolation method reigns supreme for modelling the precise spatial distribution of groundwater quality data. This study addresses this challenge by evaluating and comparing several commonly used geostatistical methods: Local Polynomial Interpolation (LPI), Ordinary Kriging (OK), Simple Kriging (SK), Universal Kriging [...] Read more.

No single spatial interpolation method reigns supreme for modelling the precise spatial distribution of groundwater quality data. This study addresses this challenge by evaluating and comparing several commonly used geostatistical methods: Local Polynomial Interpolation (LPI), Ordinary Kriging (OK), Simple Kriging (SK), Universal Kriging (UK), and Empirical Bayesian Kriging (EBK). We applied these methods to a vast dataset of 3033 groundwater records encompassing a substantial area (11,100 km²) in the coastal lowlands of the western Netherlands. To our knowledge, no prior research has investigated these interpolation methods in this specific hydrogeological setting, exhibiting a range of groundwater qualities, from fresh to saline, often anoxic, with high natural concentrations of PO₄ and NH₄. The prediction performance of the interpolation methods was assessed through statistical indicators such as root means square error. The findings indicated that EBK outperforms the other geostatistical methods in forecasting groundwater quality for the five variables considered: Cl, SO₄, Fe, PO₄, and NH₄. In contrast, SK performed worst for the species except for SO₄. We recommend not using SK to interpolate groundwater quality species unless the data exhibit low spatial variation, high sample density, or evenly distributed sampling. Full article

(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence, 2nd Edition)

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31 pages, 15174 KB

Open AccessEditor’s ChoiceArticle

Flood Susceptibility Assessment for Improving the Resilience Capacity of Railway Infrastructure Networks

by Giada Varra, Renata Della Morte, Mario Tartaglia, Andrea Fiduccia, Alessandra Zammuto, Ivan Agostino, Colin A. Booth, Nevil Quinn, Jessica E. Lamond and Luca Cozzolino

Water 2024, 16(18), 2592; https://doi.org/10.3390/w16182592 - 12 Sep 2024

Cited by 19 | Viewed by 6172

Abstract

Floods often cause significant damage to transportation infrastructure such as roads, railways, and bridges. This study identifies several topographic, environmental, and hydrological factors (slope, elevation, rainfall, land use and cover, distance from rivers, geology, topographic wetness index, and drainage density) influencing the safety [...] Read more.

Floods often cause significant damage to transportation infrastructure such as roads, railways, and bridges. This study identifies several topographic, environmental, and hydrological factors (slope, elevation, rainfall, land use and cover, distance from rivers, geology, topographic wetness index, and drainage density) influencing the safety of the railway infrastructure and uses multi-criteria analysis (MCA) alongside an analytical hierarchy process (AHP) to produce flood susceptibility maps within a geographic information system (GIS). The proposed methodology was applied to the catchment area of a railway track in southern Italy that was heavily affected by a destructive flood that occurred in the autumn of 2015. Two susceptibility maps were obtained, one based on static geophysical factors and another including triggering rainfall (dynamic). The results showed that large portions of the railway line are in a very highly susceptible zone. The flood susceptibility maps were found to be in good agreement with the post-disaster flood-induced infrastructural damage recorded along the railway, whilst the official inundation maps from competent authorities fail to supply information about flooding occurring along secondary tributaries and from direct rainfall. The reliable identification of sites susceptible to floods and damage may provide railway and environmental authorities with useful information for preparing disaster management action plans, risk analysis, and targeted infrastructure maintenance/monitoring programs, improving the resilience capacity of the railway network. The proposed approach may offer railway authorities a cost-effective strategy for rapidly screening flood susceptibility at regional/national levels and could also be applied to other types of linear transport infrastructures. Full article

(This article belongs to the Special Issue Advances in Flood Hazard and Risk Analysis: Theory, Methods, Numerical Models, Strategies, and Applications)

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29 pages, 5060 KB

Open AccessEditor’s ChoiceArticle

Effectiveness of Collars and Hooked-Collars in Mitigating Scour around Different Abutment Shapes

by Zaka Ullah Khan, Afzal Ahmed, Manousos Valyrakis, Ghufran Ahmed Pasha, Rashid Farooq, Nadir Murtaza and Diyar Khan

Water 2024, 16(17), 2550; https://doi.org/10.3390/w16172550 - 9 Sep 2024

Cited by 9 | Viewed by 1567

Abstract

Abutment scour is a major cause of bridge failures worldwide, leading to disruptions, economic losses, and loss of life. The present experimental study examines countermeasures against abutment scour using hooked-collar protections on vertical-wall and wing-wall abutments (at 45° and 60°) under different flow [...] Read more.

Abutment scour is a major cause of bridge failures worldwide, leading to disruptions, economic losses, and loss of life. The present experimental study examines countermeasures against abutment scour using hooked-collar protections on vertical-wall and wing-wall abutments (at 45° and 60°) under different flow conditions. All 60 experiments were performed under sub-critical flow conditions by investigating scour around an abutment 20 cm long, 20 cm wide, and 25 cm tall. Two distinct values of the Froude number, 0.154 and 0.179, and a sediment particle diameter (d₅₀) of 0.88 mm were used throughout the experimental phase. The resulting equilibrium scour around the abutments was compared to those with collar and hooked-collar protections. It was determined that the maximum abutment scour depth reduction was 83.89% when hooked collars were placed on vertical wall abutments beneath the bed surface level, and for wing-wall abutments at 45° and 60°, it was 74.2% and 73.5%, respectively, at the bed surface level. Regression analysis was conducted to assess the non-dimensional scour depth (D_s/Y_f) and scour reduction (R_Ds/Y_f), with a high enough coefficient of determination (R² values of 0.96 and 0.93, respectively), indicating high confidence in the analysis. The sensitivity analysis findings demonstrate that the width of the collar (W_c) and L_a are the most influencing factors affecting D_s/Y_f and RD_s/Y_f. Full article

(This article belongs to the Special Issue Advances in Hydraulic and Water Resources Research (2nd Edition))

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64 pages, 5373 KB

Open AccessEditor’s ChoiceReview

Harmful Algal Blooms in Eutrophic Marine Environments: Causes, Monitoring, and Treatment

by Jiaxin Lan, Pengfei Liu, Xi Hu and Shanshan Zhu

Water 2024, 16(17), 2525; https://doi.org/10.3390/w16172525 - 5 Sep 2024

Cited by 88 | Viewed by 28504

Abstract

Marine eutrophication, primarily driven by nutrient over input from agricultural runoff, wastewater discharge, and atmospheric deposition, leads to harmful algal blooms (HABs) that pose a severe threat to marine ecosystems. This review explores the causes, monitoring methods, and control strategies for eutrophication in [...] Read more.

Marine eutrophication, primarily driven by nutrient over input from agricultural runoff, wastewater discharge, and atmospheric deposition, leads to harmful algal blooms (HABs) that pose a severe threat to marine ecosystems. This review explores the causes, monitoring methods, and control strategies for eutrophication in marine environments. Monitoring techniques include remote sensing, automated in situ sensors, modeling, forecasting, and metagenomics. Remote sensing provides large-scale temporal and spatial data, while automated sensors offer real-time, high-resolution monitoring. Modeling and forecasting use historical data and environmental variables to predict blooms, and metagenomics provides insights into microbial community dynamics. Control treatments encompass physical, chemical, and biological treatments, as well as advanced technologies like nanotechnology, electrocoagulation, and ultrasonic treatment. Physical treatments, such as aeration and mixing, are effective but costly and energy-intensive. Chemical treatments, including phosphorus precipitation, quickly reduce nutrient levels but may have ecological side effects. Biological treatments, like biomanipulation and bioaugmentation, are sustainable but require careful management of ecological interactions. Advanced technologies offer innovative solutions with varying costs and sustainability profiles. Comparing these methods highlights the trade-offs between efficacy, cost, and environmental impact, emphasizing the need for integrated approaches tailored to specific conditions. This review underscores the importance of combining monitoring and control strategies to mitigate the adverse effects of eutrophication on marine ecosystems. Full article

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

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36 pages, 2483 KB

Open AccessEditor’s ChoiceReview

A Review of the Efficiency of Phosphorus Removal and Recovery from Wastewater by Physicochemical and Biological Processes: Challenges and Opportunities

by Sima Abdoli, Behnam Asgari Lajayer, Zahra Dehghanian, Nazila Bagheri, Amir Hossein Vafaei, Masoud Chamani, Swati Rani, Zheya Lin, Weixi Shu and G. W. Price

Water 2024, 16(17), 2507; https://doi.org/10.3390/w16172507 - 4 Sep 2024

Cited by 34 | Viewed by 16943

Abstract

Phosphorus (P) discharge from anthropogenic sources, notably sewage effluent and agricultural runoff, significantly contributes to eutrophication in aquatic environments. Stringent regulations have heightened the need for effective P removal technologies in wastewater treatment processes. This paper provides a comprehensive review of current P [...] Read more.

Phosphorus (P) discharge from anthropogenic sources, notably sewage effluent and agricultural runoff, significantly contributes to eutrophication in aquatic environments. Stringent regulations have heightened the need for effective P removal technologies in wastewater treatment processes. This paper provides a comprehensive review of current P removal methods, focusing on both biological and chemical approaches. Biological treatments discussed include enhanced biological P removal in activated sludge systems, biological trickling filters, biofilm reactors, and constructed wetlands. The efficiency of microbial absorption and novel biotechnological integrations, such as the use of microalgae and fungi, are also examined. Chemical treatments reviewed encompass the application of metal salts, advanced oxidation processes such as chlorination, ozonation, and the Fenton reaction, as well as emerging techniques including the Electro-Fenton process and photocatalysis. Analytical methods for P, including spectrophotometric techniques and fractionation analyses, are evaluated to understand the dynamics of P in wastewater. This review critically assesses the strengths and limitations of each method, aiming to identify the most effective and sustainable solutions for P management in wastewater treatment. The integration of innovative strategies and advanced technologies is emphasized as crucial for optimizing P removal and ensuring compliance with environmental regulations. Full article

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

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20 pages, 9509 KB

Open AccessEditor’s ChoiceArticle

High-Performance Crown Ether-Modified Membranes for Selective Lithium Recovery from High Na⁺ and Mg²⁺ Brines Using Electrodialysis

by Xiaochun Yin, Pei Xu and Huiyao Wang

Water 2024, 16(17), 2489; https://doi.org/10.3390/w16172489 - 2 Sep 2024

Cited by 8 | Viewed by 4503

Abstract

The challenge of efficiently extracting Li⁺ from brines with high Na⁺ or Mg²⁺ concentrations has led to extensive research on developing highly selective separation membranes for electrodialysis. Various studies have demonstrated that nanofiltration membranes or adsorbents modified with crown ethers [...] Read more.

The challenge of efficiently extracting Li⁺ from brines with high Na⁺ or Mg²⁺ concentrations has led to extensive research on developing highly selective separation membranes for electrodialysis. Various studies have demonstrated that nanofiltration membranes or adsorbents modified with crown ethers (CEs) such as 2-OH-12-crown-4-ether (12CE), 2-OH-18-crown-6-ether (18CE), and 2-OH-15-crown-5-ether (15CE) show selectivity for Li⁺ in brines. This study aims to develop high-performance cation exchange membranes (CEMs) using CEs to enhance Li⁺ selectivity and to compare the performance of various CE-modified membranes for selective electrodialysis. The novel CEM (CR671) was modified with 12CE, 18CE, and 15CE to identify the optimal CE for efficient Li⁺ recovery during brine electrodialysis. The modification process included polydopamine (PDA) treatment and the deposition of polyethyleneimine (PEI) complexes with the different CEs via hydrogen bonding. Interfacial polymerization with 1,3,5-benzenetricarbonyl trichloride-crosslinked PEI was used to create specific channels for Li⁺ transport within the modified membranes (12CE/CR671, 15CE/CR671, and 18CE/CR671). The successful application of CE coatings and Li⁺ selectivity of the modified membranes were verified through Fourier-transform infrared spectroscopy, zeta-potential measurements, and electrochemical impedance spectroscopy. Bench-scale electrodialysis tests showed significant improvements in permselectivity and Li⁺ flux for all three modified membranes. In brines with high Na⁺ and Mg²⁺ concentrations, the 15CE/CR671 membrane demonstrated more significant improvements in permselectivity compared to the 12CE/CR671 (3.3-fold and 1.7-fold) and the 18CE/CR671 (2.4-fold and 2.6-fold) membranes at current densities of 2.3 mA/cm² and 2.2 mA/cm², respectively. At higher current densities of 14.7 mA/cm² in Mg²⁺-rich brine and 15.9 mA/cm² in Na⁺-rich brine, the 15CE/CR671 membrane showed greater improvements in Li⁺ flux, approximately 2.1-fold and 2.3-fold, and 3.2-fold and 3.4-fold compared to the 12CE/CR671 and 18CE/CR671 membranes. This study underscores the superior performance of 15CE-modified membranes for efficient Li⁺ recovery with low energy demand and offers valuable insights for advancing electrodialysis processes in challenging brine environments. Full article

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

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22 pages, 2666 KB

Open AccessEditor’s ChoiceReview

Future Agricultural Water Availability in Mediterranean Countries under Climate Change: A Systematic Review

by André M. Claro, André Fonseca, Helder Fraga and João A. Santos

Water 2024, 16(17), 2484; https://doi.org/10.3390/w16172484 - 1 Sep 2024

Cited by 14 | Viewed by 6048

Abstract

Warming and drying trends in the Mediterranean Basin exacerbate regional water scarcity and threaten agricultural production, putting global food security at risk. This study aimed to review the most significant research on future water availability for the Mediterranean agricultural sector under climate change [...] Read more.

Warming and drying trends in the Mediterranean Basin exacerbate regional water scarcity and threaten agricultural production, putting global food security at risk. This study aimed to review the most significant research on future water availability for the Mediterranean agricultural sector under climate change (CC) scenarios published during 2009–2024. Two searches were performed in the Scopus and Web of Science databases, to which previously identified significant studies from different periods were also added. By applying a methodology duly protocoled in the PRISMA2020-based guideline, a final number of 44 particularly relevant studies was selected for review. A bibliometric analysis has shown that most of the published research was focused on Southwestern European countries (i.e., Spain, Italy, Portugal) and grapevine and olive tree crops. Overall, the reviewed studies state that future Mediterranean water reserves may not meet agricultural water demands, due to reduced reservoir inflows and higher irrigation demands under future CC and socioeconomic scenarios. Regarding adaptation measures to improve water-use management in agriculture, the majority of the reviewed studies indicate that the use of integrated modelling platforms and decision–support systems can significantly contribute to the development and implementation of improved water/land-management practices. Full article

(This article belongs to the Section Water, Agriculture and Aquaculture)

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16 pages, 3426 KB

Open AccessEditor’s ChoiceArticle

Mapping Flood Impacts on Mortality at European Territories of the Mediterranean Region within the Sustainable Development Goals (SDGs) Framework

by Iraklis Stamos and Michalis Diakakis

Water 2024, 16(17), 2470; https://doi.org/10.3390/w16172470 - 30 Aug 2024

Cited by 7 | Viewed by 2155

Abstract

Despite significant advances in technology and flood risk management, as well as the countless risk prevention initiatives undertaken by governments and institutions in recent decades, flood hazards persist in threatening human life and health, especially under the effects of climate change. To assess [...] Read more.

Despite significant advances in technology and flood risk management, as well as the countless risk prevention initiatives undertaken by governments and institutions in recent decades, flood hazards persist in threatening human life and health, especially under the effects of climate change. To assess the effectiveness of the various programs or measures devised to protect human life and health from floods, it is crucial to measure and understand its impacts on society, establishing the capability to track indicators or metrics that reflect the spatial distribution and temporal progress of floods and their impacts. In this context, this study uses disaster loss data derived from international disaster databases adapted in regional context following the Nomenclature of Territorial Units for Statistics level 2 (or NUTS2), to examine the spatial distribution and temporal evolution of deaths, directly attributable to flood disasters. In addition, we explore the potential of currently available datasets in understanding and monitoring flood-related mortality, an important standardized progress indicator of flood disaster impacts. This study is framed within the United Nations’ Sustainable Development Goals (SDGs), recently adopted by the European Union, and is focused on the Union’s territories in the Mediterranean region, an area particularly sensitive to climate change. Results show interesting spatial patterns, and generally inconclusive temporal trends, although locally we see evidence of both an increase and a decline in flood mortality. In addition, this work discusses the currently available datasets potential, weaknesses and limitations, as well as the importance of tracking flood impacts on human life in a future increasingly influenced by extreme weather events and climate change. Full article

(This article belongs to the Special Issue Risks of Hydrometeorological Extremes)

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19 pages, 8448 KB

Open AccessEditor’s ChoiceReview

State-of-the-Art Techniques for Real-Time Monitoring of Urban Flooding: A Review

by Jiayi Song, Zhiyu Shao, Ziyi Zhan and Lei Chen

Water 2024, 16(17), 2476; https://doi.org/10.3390/w16172476 - 30 Aug 2024

Cited by 13 | Viewed by 5328

Abstract

In the context of the increasing frequency of urban flooding disasters caused by extreme weather, the accurate and timely identification and monitoring of urban flood risks have become increasingly important. This article begins with a bibliometric analysis of the literature on urban flood [...] Read more.

In the context of the increasing frequency of urban flooding disasters caused by extreme weather, the accurate and timely identification and monitoring of urban flood risks have become increasingly important. This article begins with a bibliometric analysis of the literature on urban flood monitoring and identification, revealing that since 2017, this area has become a global research hotspot. Subsequently, it presents a systematic review of current mainstream urban flood monitoring technologies, drawing from both traditional and emerging data sources, which are categorized into sensor-based monitoring (including contact and non-contact sensors) and big data-based monitoring (including social media data and surveillance camera data). By analyzing the advantages and disadvantages of each technology and their different research focuses, this paper points out that current research largely emphasizes more “intelligent” monitoring technologies. However, these technologies still have certain limitations, and traditional sensor monitoring techniques retain significant advantages in practical applications. Therefore, future flood risk monitoring should focus on integrating multiple data sources, fully leveraging the strengths of different data sources to achieve real-time and accurate monitoring of urban flooding. Full article

(This article belongs to the Special Issue Urban Flooding Control and Sponge City Construction)

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29 pages, 5562 KB

Open AccessEditor’s ChoiceArticle

On the Necessity for Improving Water Efficiency in Commercial Buildings: A Green Design Approach in Hot Humid Climates

by A. Chandana Hemantha J. Thebuwena, S. M. Samindi M. K. Samarakoon and R. M. Chandima Ratnayake

Water 2024, 16(17), 2396; https://doi.org/10.3390/w16172396 - 26 Aug 2024

Cited by 6 | Viewed by 7737

Abstract

Water, a fundamental and indispensable resource necessary for the survival of living beings, has become a pressing issue in numerous regions worldwide due to scarcity. Urban areas, where the majority of the global population resides, witness a substantial consumption of blue water, particularly [...] Read more.

Water, a fundamental and indispensable resource necessary for the survival of living beings, has become a pressing issue in numerous regions worldwide due to scarcity. Urban areas, where the majority of the global population resides, witness a substantial consumption of blue water, particularly in commercial buildings. This study investigates the potential for enhancing water efficiency within an ongoing high-rise office building construction situated in a tropical climate. The investigation utilizes the green building guidelines of leadership in energy and environmental design (LEED) through a case-study-based research approach. Strategies included using efficient plumbing fixtures (such as high air–water ratio fixtures and dual-flush toilets), the selection of native plants, implementing a suitable irrigation system, introducing a rainwater harvesting system (RWHS) and improving the mechanical ventilation and air conditioning (MVAC) system. The results showed a 55% reduction in water use from efficient fixtures, a 93% reduction in landscaping water needs and a 73% overall water efficiency with a RWHS from the baseline design. Additionally, efficient cooling towers and the redirection of condensed water into the cooling tower make-up water tank improved the overall water efficiency to 38%, accounting for the water requirements of the MVAC system. The findings of this study can contribute to more sustainable and water-efficient urban development, particularly in regions facing water scarcity challenges. The significance of these findings lies in their potential to establish industry standards and inform policymakers in the building sector. They offer valuable insights for implementing effective strategies aimed at reducing blue water consumption across different building types. Full article

(This article belongs to the Special Issue Water-Sensitive and Sustainable Urban Development)

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21 pages, 4526 KB

Open AccessEditor’s ChoiceReview

Sustainable Solutions for Mitigating Water Scarcity in Developing Countries: A Comprehensive Review of Innovative Rainwater Storage Systems

by Geoffrey Ssekyanzi, Mirza Junaid Ahmad and Kyung-Sook Choi

Water 2024, 16(17), 2394; https://doi.org/10.3390/w16172394 - 26 Aug 2024

Cited by 20 | Viewed by 17372

Abstract

As global water resources decline and demand increases due to population growth and climate change, innovative rainwater storage systems (IRSSs) have become crucial. This review examines the potential of IRSSs to sustainably address rainwater challenges by analyzing key factors that influence their success. [...] Read more.

As global water resources decline and demand increases due to population growth and climate change, innovative rainwater storage systems (IRSSs) have become crucial. This review examines the potential of IRSSs to sustainably address rainwater challenges by analyzing key factors that influence their success. Drawing on research from Scopus and Google Scholar, it evaluates IRSSs in both urban and rural settings across different countries and regions, focusing on their contribution to Sustainable Development Goal (SDG) 6. This review highlights how social, environmental, economic, and policy factors affect the success of IRSS compared to traditional systems common in developing nations. IRSSs can outperform traditional methods in sustainability, encouraging their adoption. However, there is a significant gap in policy integration that needs to be addressed for successful implementation. Further research is needed to better understand the contributing factors and their role in achieving sustainability. Integrating rainwater harvesting into national water policies could offer valuable guidance for policymakers and water resource managers in addressing issues like urban floods, water scarcity, and related social and environmental challenges in developing countries. Full article

(This article belongs to the Section Water Resources Management, Policy and Governance)

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15 pages, 6230 KB

Open AccessEditor’s ChoiceArticle

Modern Treatment Using Powdered Chlorella vulgaris for Adsorption of Heavy Metals from Freshwater

by Eleonora Sočo, Dorota Papciak, Andżelika Domoń and Dariusz Pająk

Water 2024, 16(17), 2388; https://doi.org/10.3390/w16172388 - 25 Aug 2024

Cited by 4 | Viewed by 3848

Abstract

In the face of current challenges related to climate change, maintaining the appropriate quality of freshwater becomes crucial. This study examined the effectiveness of removing heavy metals (Cu(II) and Co(II)) using Chlorella vulgaris biosorbents (dietary supplements in the form of powder). This study [...] Read more.

In the face of current challenges related to climate change, maintaining the appropriate quality of freshwater becomes crucial. This study examined the effectiveness of removing heavy metals (Cu(II) and Co(II)) using Chlorella vulgaris biosorbents (dietary supplements in the form of powder). This study determined the parameters of the biosorbent (point of zero charge (PZC) analysis using scanning electron microscopy with back-scattered electron (SEM-BSE) and Fourier transform infrared spectroscopy (FT-IR) analysis). Batch tests were also performed to determine the kinetic constants and adsorption equilibrium of Cu(II) and Co(II) ions. Based on the conducted research, it was found that a pseudo-second-order equation describes the kinetics of the biosorption process. Among the studied adsorption isotherms, the Langmuir and Freundlich models fit best. The results indicate that single-layer adsorption took place and Chlorella vulgaris is a microporous adsorbent. The maximum sorption capacity in the single-component system for Cu(II) and Co(II) was 30.3 mg·g⁻¹ and 9.0 mg·g⁻¹, respectively. In contrast, in the binary system, it was 20.8 mg·g⁻¹ and 19.6 mg·g⁻¹ (extended Langmuir model) and 23.5 mg·g⁻¹ and 19.6 mg·g⁻¹ (Jain-Snoeyinka model). Chlorella vulgaris is an effective biosorbent for removing heavy metals from freshwater. This technology offers an ecological and economical solution for improving water quality, making it a promising alternative to traditional purification methods. Full article

(This article belongs to the Special Issue Freshwater Quality Challenges in Southern Europe under an Increasingly Warmer and Drier Climate Scenario)

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42 pages, 16420 KB

Open AccessEditor’s ChoiceArticle

Multi-Objective and Multi-Variable Optimization Models of Hybrid Renewable Energy Solutions for Water–Energy Nexus

by João S. T. Coelho, Maaike van de Loo, Juan Antonio Rodríguez Díaz, Oscar E. Coronado-Hernández, Modesto Perez-Sanchez and Helena M. Ramos

Water 2024, 16(17), 2360; https://doi.org/10.3390/w16172360 - 23 Aug 2024

Cited by 12 | Viewed by 3301

Abstract

A new methodology, called HY4RES models, includes hybrid energy solutions (HESs) based on the availability of renewable sources, for 24 h of water allocation, using WaterGEMS 10.0 and PVGIS 5.2 as auxiliary calculations. The optimization design was achieved using Solver, with GRG nonlinear/evolutionary [...] Read more.

A new methodology, called HY4RES models, includes hybrid energy solutions (HESs) based on the availability of renewable sources, for 24 h of water allocation, using WaterGEMS 10.0 and PVGIS 5.2 as auxiliary calculations. The optimization design was achieved using Solver, with GRG nonlinear/evolutionary programming, and Python, with the non-dominated sorting genetic algorithm (NSGA-II). The study involves the implementation of complex multi-objective and multi-variable algorithms with different renewable sources, such as PV solar energy, pumped hydropower storage (PHS) energy, wind energy, grid connection energy, or battery energy, and also sensitivity analyses and comparisons of optimization models. Higher water allocations relied heavily on grid energy, especially at night when solar power was unavailable. For a case study of irrigation water needs of 800 and 1000 m³/ha, the grid is not needed, but for 3000 and 6000 m³/ha, grid energy rises significantly, reaching 5 and 14 GWh annually, respectively. When wind energy is also integrated, at night, it allows for reducing grid energy use by 60% for 3000 m³/ha of water allocation, yielding a positive lifetime cashflow (EUR 284,781). If the grid is replaced by batteries, it results in a lack of a robust backup and struggles to meet high water and energy needs. Economically, PV + wind + PHS + grid energy is the most attractive solution, reducing the dependence on auxiliary sources and benefiting from sales to the grid. Full article

(This article belongs to the Special Issue Water and Energy Synergies)

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