Performance of the multi-U-style structure based flow field for polymer electrolyte membrane fuel cell.

The design of the reactant gas flow field structure in bipolar plates significantly influences the performance of proton exchange membrane fuel cells (PEMFCs). In this study, we introduced four innovative U-shaped flow field designs, namely: In-Out Multi-U, Out-In Multi-U, Distro In-Out Multi-U, and Distro Out-In Multi-U. To investigate the impact of these various flow fields on PEMFC performance, we conducted computational fluid dynamics (CFD) numerical simulations, validated through model experiments. Our results indicate that the Distro Out-In Multi-U flow field offers notable advantages compared to the conventional parallel flow field (CPFF) and conventional serpentine flow field (CSFF). These benefits include reduced inlet and outlet pressures, lower liquid water content, more uniform liquid water distribution, and a more even current density distribution. Furthermore, the Distro Out-In Multi-U design demonstrates improved efficiency, consuming less H2 (91.9%) than the CSFF while achieving a higher net power density output (10.1%). As a result, for the same power output, the Distro Out-In Multi-U utilizes only 83.5% of the H2 consumed by the CSFF. In summary, the U-shaped structured flow field exhibits superior output performance, enhanced energy efficiency, and improved resistance to flooding. These findings suggest that the U-shaped flow field design holds significant potential as a reactive flow field for PEMFCs.

Simulating runoff changes and evaluating under climate change using CMIP6 data and the optimal SWAT model: a case study.

This study examines the influence of climate change on hydrological processes, particularly runoff, and how it affects managing water resources and ecosystem sustainability. It uses CMIP6 data to analyze changes in runoff patterns under different Shared Socioeconomic Pathways (SSP). This study also uses a Deep belief network (DBN) and a Modified Sparrow Search Optimizer (MSSO) to enhance the runoff forecasting capabilities of the SWAT model. DBN can learn complex patterns in the data and improve the accuracy of runoff forecasting. The meta-heuristic algorithm optimizes the models through iterative search processes and finds the optimal parameter configuration in the SWAT model. The Optimal SWAT Model accurately predicts runoff patterns, with high precision in capturing variability, a strong connection between projected and actual data, and minimal inaccuracy in its predictions, as indicated by an ENS score of 0.7152 and an R2 coefficient of determination of 0.8012. The outcomes of the forecasts illustrated that the runoff will decrease in the coming years, which could threaten the water source. Therefore, managers should manage water resources with awareness of these conditions.

Applying a novel mechanistic framework for drinking water management to mitigate emerging contaminants.

A novel framework has been developed which summarizes the efficacy of treatment technologies for emerging contaminants (ECs) based on the general mitigation mechanisms of Removal, Inactivation/Degradation, and Destruction (i.e., RIDD). The RIDD framework allows for a concise critical evaluation of the efficacy of treatment processes for their mitigation potential, and provides an efficient methodology for drinking water system managers to identify knowledge gaps related to the management of ECs in water treatment with respect to current technologies available in practice. Additionally, the RIDD framework provides an understanding of the treatment processes which provide: (1) broad spectrum treatment, (2) effective mitigation for certain categories of contaminants or under certain circumstances, or (3) little or no mitigation of ECs. In the proposed format, this information is intended to assist water managers to make more informed treatment decisions. Four categories of ECs noted in recent literature as presently concerning to drinking water utilities, including both anthropogenic and microbial contaminants, were used in this study to provide examples of RIDD framework application. In many cases, broad-spectrum treatment barriers (e.g., high-pressure membranes) are expected to provide cost-effective management of a suite of ECs, which then can be compared to the costs and practicality of additional treatment barriers for individual ECs (e.g., selective ion exchange resins or tailored biological processes). Additionally, understanding the typical performance of existing treatment processes can help assist with capital planning for alternative treatment processes or upgrades, or for developing novel treatment approaches at the watershed scale such as integrated urban water management and One Water frameworks.

Integrated water resource management in the Segura Hydrographic Basin: An artificial intelligence approach.

Managing resources effectively in uncertain demand, variable availability, and complex governance policies is a significant challenge. This paper presents a paradigmatic framework for addressing these issues in water management scenarios by integrating advanced physical modelling, remote sensing techniques, and Artificial Intelligence algorithms. The proposed approach accurately predicts water availability, estimates demand, and optimizes resource allocation on both short- and long-term basis, combining a comprehensive hydrological model, agronomic crop models for precise demand estimation, and Mixed-Integer Linear Programming for efficient resource distribution. In the study case of the Segura Hydrographic Basin, the approach successfully allocated approximately 642 million cubic meters (hm3) of water over six months, minimizing the deficit to 9.7% of the total estimated demand. The methodology demonstrated significant environmental benefits, reducing CO2 emissions while optimizing resource distribution. This robust solution supports informed decision-making processes, ensuring sustainable water management across diverse contexts. The generalizability of this approach allows its adaptation to other basins, contributing to improved governance and policy implementation on a broader scale. Ultimately, the methodology has been validated and integrated into the operational water management practices in the Segura Hydrographic Basin in Spain.

A framework for developing a real-time lake phytoplankton forecasting system to support water quality management in the face of global change.

Phytoplankton blooms create harmful toxins, scums, and taste and odor compounds and thus pose a major risk to drinking water safety. Climate and land use change are increasing the frequency and severity of blooms, motivating the development of new approaches for preemptive, rather than reactive, water management. While several real-time phytoplankton forecasts have been developed to date, none are both automated and quantify uncertainty in their predictions, which is critical for manager use. In response to this need, we outline a framework for developing the first automated, real-time lake phytoplankton forecasting system that quantifies uncertainty, thereby enabling managers to adapt operations and mitigate blooms. Implementation of this system calls for new, integrated ecosystem and statistical models; automated cyberinfrastructure; effective decision support tools; and training for forecasters and decision makers. We provide a research agenda for the creation of this system, as well as recommendations for developing real-time phytoplankton forecasts to support management.

Enhancing Corn (Zea mays L.) Productivity under Varying Water Regimes with At-Plant Application of Xyway Fungicide.

A fungicide's ingredients can play a physiological role in crop water-management decisions. Our greenhouse study in 2021 demonstrated that Xyway LFR@FMC at-plant fungicide can significantly improve water-saving potential in corn. In 2022 and 2023, a field study was conducted to validate this finding. The 1.11 L ha-1 of Xyway LFR@FMC and no-fungicide/check were the main plot effects. Three water regimes, high (HI) and low (LO) numbers of irrigation events and rainfed (RF), were the subplot effect. Plants treated with Xyway LFR@FMC had significantly higher plant height, stem diameter, and leaf water potential (LWP), and had 11.9, 13.4, and 18.3% higher yield under RF, LO, and HI, respectively, in 2022. In 2023, there were no significant differences for the yield components and growth parameters when the combined effect of fungicide treatments and water regimes was considered. However, plants treated with the fungicide had a higher number of rows per ear, kernel number per row, and cob diameter compared to the check. There was no significant separation for yield among the water regimes in 2023, but the crop yield was overall higher for the fungicide-treated plots. Our results indicate that Xyway LFR@FMC fungicide has the potential to improve plant growth and protect the yield when limited water is applied.

Ecohydraulics-based environmental flow assessment in two arid North African rivers.

North Africa is among the most water-stressed regions in the world; still, the habitat requirements of its freshwater biota are largely unknown. In this study, (i) we developed habitat suitability curves (HSCs) for freshwater macroinvertebrates in two poorly studied, regulated North African rivers (Ziz and Oum Er-Rbia), and (ii) assessed environmental flows downstream of each river dam by incorporating the HSCs in two-dimensional ecohydraulic models. We demonstrate a low-cost sampling methodology combined with freely distributed ecohydraulic modeling software. The results showed that macroinvertebrates in the arid-desert Ziz River could tolerate a wide range of habitats in terms of flow velocity and water depth compared to the arid-steppe Oum Er-Rbia River, probably due to their adaptation to extreme (arid-desert) environmental conditions. Optimal environmental flows downstream of the Al Hassan Addakhil (Ziz River) and the Al Massira (Oum Er-Rbia River) dams were 1 m3/s and 2 m3/s, respectively. However, environmental flows at 0.5 m3/s and 1 m3/s, respectively, could still maintain sustainable freshwater biota downstream of the dams. The results further highlight the critical status of the Ziz River, which was completely dry, and the alarming status of the Oum Er-Rbia River due to the significant reduction in the water levels of the Al Massira Dam. In a continuously changing climate, we suggest that the proposed environmental flows should be immediately delivered to prevent droughts and ensure healthy freshwater communities downstream of the dams, within a basin-wide freshwater management framework. In this water scarce region, more research is necessary to increase ecological awareness about these understudied freshwater systems and achieve a balance between human needs and ecosystem requirements.

How much rainwater contributes to a spring discharge in the Guarani Aquifer System: insights from stable isotopes and a mass balance model.

Outcrops play an important role in groundwater recharge. Understanding groundwater origins, dynamics and its correlation with different water sources is essential for effective water resources management and planning in terms of quantity and quality. In the case of the Guarani Aquifer System (GAS) outcrop areas are particularly vulnerable to groundwater pollution due to direct recharge processes. This study focuses on the Alto Jacaré-Pepira sub-basin, a watershed near Brotas, a city in the central region of the state of São Paulo, Brazil, where groundwater is vital for supporting tourism, agriculture, urban water supply, creeks, river and wetlands. The area has a humid tropical climate with periods of both intense rainfall and drought, and the rivers remain perennial throughout the year. Therefore, the aim of this study is to investigate the interconnections between a spring and its potential sources of contribution, namely rain and groundwater, in order to elucidate the relationships between the different water sources. To achieve this, on-site monitoring of groundwater depth, rainfall amount, and stable isotope ratios (deuterium (2H) and oxygen-18 (18O)) from rain, spring discharge, and a monitoring well was carried out from 2013 to 2021. The results indicate that the mean and standard deviations for δ18O in rainwater exhibit higher variability, resulting in -4.49 ± 3.18 ‰ VSMOW, while δ18O values from the well show minor variations, similar to those of the spring, recording -7.25 ± 0.32 ‰ and -6.94 ± 0.28 ‰ VSMOW, respectively. The mixing model's outcomes reveal seasonal variations in water sources contribution and indicate that groundwater accounts for approximately 80 % of spring discharge throughout the year. Incorporating stable isotopes into hydrological monitoring provides valuable data for complementing watershed analysis. The values obtained support the significance of the aquifer as a primary source, thereby offering critical insights into stream dynamics of the region.

Revisiting the concept, urban practices, current advances, and future prospects of green infrastructure.

The inevitable increase in the human population's reliance on natural resources necessitates practical, and result-oriented solutions and strategies to enhance human's standard of living while minimizing its impact on essential resources. The global water resource depletion has spurred discourse among key international stakeholder in uniting efforts to achieve sustainability. For decades, the application of a combination of key strategies which relies on designing cities to promote the sustainable use of water and water resources have received global endorsement. The roadmap towards designing water-wise infrastructure in urban areas has derived from preexisting water conservation schemes. Green infrastructure (GI) is based on the key principle of the harmonious integration of natural elements and ecological processes to sustainably conserve natural resources. This paper aims to analyze and assess the development of sustainable and effective solutions for urban water quality management, by providing a comprehensive review of the concept of GI. We further digest the components and strategies of GI, its historical evolution, the rate of adoption and application on a regional scale and future prospects. GI with continued innovation and refinement, holds immense potential to mitigate the detrimental effects of urbanization on water resources and promote sustainable urban water management.

Assessment of Low-Cost and Higher-End Soil Moisture Sensors across Various Moisture Ranges and Soil Textures.

The accuracy and unit cost of sensors are important factors for a continuous soil moisture monitoring system. This study compares the accuracy of four soil moisture sensors differing in unit costs in coarse-, fine-, and medium-textured soils. The sensor outputs were recorded for the VWC, ranging from 0% to 50%. Low-cost capacitive and resistive sensors were evaluated with and without the external 16-bit analog-to-digital converter ADS1115 to improve their performances without adding much cost. Without ADS1115, using only Arduino's built-in analog-to-digital converter, the low-cost sensors had a maximum RMSE of 4.79% (v/v) for resistive sensors and 3.78% for capacitive sensors in medium-textured soil. The addition of ADS1115 showed improved performance of the low-cost sensors, with a maximum RMSE of 2.64% for resistive sensors and 1.87% for capacitive sensors. The higher-end sensors had an RMSE of up to 1.8% for VH400 and up to 0.95% for the 5TM sensor. The RMSE differences between higher-end and low-cost sensors with the use of ADS1115 were not statistically significant.

Machine learning and structural equation modeling for revealing the influence factors and pathways of different water management regimes acting on brown rice cadmium.

Excessive cadmium (Cd) in brown rice has detrimental effects on rice growth and human health. Water management is a cost-effective, eco-friendly measure to suppress Cd accumulation in rice. However, there is no acknowledged water management regime that reduces Cd accumulation in brown rice without compromising the yield. Meanwhile, the major factors affecting brown rice Cd and the pathways of water management affecting rice Cd are not clear. This study explored major factors affecting brown rice Cd using machine learning (ML) and examined the pathways of water management affecting rice Cd using a structural equation model (SEM). Three water management systems were set up, namely flooding, water-saving, and wetting irrigation. Results showed that water-saving irrigation increased dry matter and reduced Cd content and translocation. Root uptake during the grain filling stage and Cd remobilization before the grain filling stage contributed 36 % and 64 % of the Cd accumulation in brown rice, respectively. ML explained 97 % of the variance, suggesting that crop covariates were the most important (e.g., the brown rice bioconcentration factor (12 %), stem Cd (9 %), root-to-stem translocation factor (7 %)), followed by soil covariates (e.g., reducing substances 12 %) and water management (3 %). All SEM explanatory variables collectively explained 94 % of the variation, with a predictive power of 76 %. Water treatments indirectly affected soil available Fe and Mn (indirect effect coefficient = 0.909), iron plaques (indirect effect coefficient = 0.866), soil available Cd (indirect effect coefficient = -0.671), and Cd intensity of xylem sap (BICd, indirect effect coefficient = -0.664) via pH and reducing substances. BICd significantly positively affected stem Cd (path coefficient = 0.445). These findings provide insight into the agronomic and environmental effects of water management on brown rice Cd and influence pathways in soil-rice systems, suggesting that water-saving irrigation may alleviate Cd contamination in the paddy soil.

Assessment of water quality and identification of priority areas for intervention in Guanabara Bay basin, Rio de Janeiro, Brazil, using nonparametric and multivariate statistical methods.

The Guanabara Bay hydrographic region (GBHR) has served as a central hub for human settlement and resource utilization throughout Brazil's history. However, the region's high population density and intense industrial activity have come at a cost, leading to a significant decline in water quality. This work aimed to identify homogeneous regions in GBHR according to water quality parameters in dry and rainy periods. The following water quality monitoring variables were monitored at 49 gauge stations: total phosphorus (TP), nitrate (NO3-), dissolved oxygen (DO), hydrogenionic potential (pH), turbidity (Turb), thermotolerant coliforms (TCol), total dissolved solids (TDS), biochemical oxygen demand (BOD), water temperature (Tw), and air temperature (Ta). The statistical analysis consisted of determining principal components, cluster analysis, seasonal differences, and Spearman's correlation. The water quality parameter correlations were not expressively influenced by seasonality, but there are differences in the concentrations of these parameters in the dry and rainy periods. In the dry period, urban pressure on water quality is mainly due to fecal coliforms. The resulting clusters delimited areas under urban, agricultural, and forestry influence. Clusters located in areas with high demographic density showed high concentrations of TCol and TP, while clusters influenced by forestry and agriculture had better water quality. In the rainy season, clusters with urban influence showed problems with TCol and TP, in addition to some characteristics in each group, such as high TDS, NO3-, and BOD. Forested areas showed high DO, and clusters under agricultural influence had higher concentrations of TCol, BOD, and NO3- concerning forested regions. The troubling state of sanitation in GBHR occurs in metropolitan regions due to lack of a formal sanitation system.

Unravelling surface water dynamics in semi-arid central Indian region for sustainable agricultural practices.

The distribution and availability of water resources have been greatly impacted by global climate change and unsustainable human activities. This has resulted in increased pressure on surface water supplies, human consumption and socioeconomic growth. Although water management requires monitoring, a substantial amount of water consumption globally, including both groundwater and surface water, remains unmeasured. Madhya Pradesh (MP) has a very varied semi-arid geographical region in Central India. Recent studies have found that 36 out of 51 districts in the state of MP have been facing severe hydrological drought conditions. Despite the challenges in the MP region, there is little understanding of the permanent and seasonal changes in surface water and the overall availability of surface water resources in each district. Field-based monitoring of surface water bodies in large regions such as MP poses considerable difficulties. However, gaining knowledge about changes in the distribution of water on the Earth's surface across time and space can be enhanced by analysing data obtained via remote sensing. To understand the long-term changes in surface water in different districts of Madhya Pradesh, India, over the past 38 years, we analysed a publicly accessible global surface water dataset provided by the Joint Research Centre (JRC) European Commission. This dataset is based on Landsat imagery and covers the period from 1984 to 2021. This research study examines the associations between variations in the permanent surface water level and the extent of land being irrigated, the intensity of agricultural activities and the seasonal oscillations in surface water for several districts in Madhya Pradesh. The findings from this research will be beneficial for assessing several significant MP districts in terms of their water footprint and sustainable management.

Ways to mitigate greenhouse gas production from rice cultivation.

Rice cultivation boasts a rich historical legacy, serving as the primary sustenance for over 50% of the global population. However, the cultivation process gives rise to the emission of methane (CH4) and nitrous oxide (N2O), two potent greenhouse gases. Notably, the global warming potential (GWP) of CH4 and N2O surpasses CO2 by 27-30 times and 273 times over 100 years, respectively. Addressing this environmental challenge necessitates exploring technical approaches and management strategies to curb gas emissions while sustaining rice yields. Several critical factors have been identified and analyzed for their potential to mitigate greenhouse gas production during rice cultivation. These include water management, fertilizer management, biochar application, cultivar selection, straw management, modified planting methods, and integration of new energy machinery. A comprehensive understanding and implementation of these methods can contribute significantly to achieving a dual objective: reducing emissions and maintaining optimal rice yields. Looking ahead, a synergistic integration of these diverse methods and management approaches holds promise for more effective results. Furthermore, the intricate water networks associated with rice cultivation should be carefully considered in the overall strategy. By adopting a holistic approach that addresses both emission reduction and sustainable water usage, the future of rice cultivation can be shaped to align with environmental stewardship and food security.

Different impacts of natural and anthropogenic factors on dissolved organic matter chemistry in coastal rivers: Implications for water management.

The chemical composition of dissolved organic matter (DOM) exerts significant influence on aquatic energy dynamics, pollutant transportation, and carbon storage, thereby playing pivotal roles in the local water quality and regional-global biogeochemical cycling. However, the effects of natural climate change and local human activities on watershed characteristics and in-river processes have led to uncertainties regarding their contributions to DOM chemistry in coastal rivers, creating challenges for effective water management and the study of organic matter cycling. In this investigation, we employed a combination of stable isotopic analysis, optical techniques, and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) to elucidate the sources, optical properties, and molecular composition of DOM in three South China coastal rivers. Our results suggest that terrestrial DOM entering the three rivers through natural or anthropogenic pathways is gradually diluted by in situ primary production as it moves downstream, ultimately being influenced by seawater intrusion near the estuary. Additionally, terrestrial processes influenced by temperature likely govern DOC concentration, while seawater intrusion promotes the natural production of S-containing organic compounds. In contrast, human-altered landcover significantly impacts DOM molecular composition. Increased water areas lead to the enrichment of lignins with high disinfection byproduct formation potential, and agricultural residue burning appears to be the dominant source of pyrogenic DOM in these coastal rivers. Our distinct results suggest that the development of specific water management plans that consider the combined effects of temperature, seawater intrusion, landcover changes, and agricultural practices will be essential to ensure sustainable water resource.

Water Quality Trade-offs for Risk Management Interventions in a Green Building.

Premise plumbing water quality degradation has led to negative health impacts from pathogen outbreaks (e.g., Legionella pneumophila and non-tuberculous mycobacteria), as well as chronic effects from exposure to heavy metals or disinfection by-products (DBP). Common water quality management interventions include flushing, heat shock (thermal disinfection), supplemental disinfection (shock or super chlorination), and water heater temperature setpoint change. In this study, a Legionella pneumophila- colonized Leadership in Energy and Environmental Design (LEED) certified building was monitored to study health-relevant water quality changes before and after three controlled management interventions: (1) flushing at several points throughout the building; (2) changing the water heater set point; and (3) a combination of interventions (1) and (2) by flushing during a period of elevated water heater set point (incompletely performed due to operational issues). Microbial (culturable L. pneumophila, the L. pneumophila mip gene, and cATP) and physico-chemical (pH, temperature, conductivity, disinfectant residual, disinfection by-products (DBPs; total trihalomethanes, TTHM), and heavy metals) water quality were monitored alongside building occupancy as approximated using Wi-Fi logins. Flushing alone resulted in a significant decrease in cATP and L. pneumophila concentrations (p = 0.018 and 0.019, respectively) and a significant increase in chlorine concentrations (p = 0.002) as well as iron and DBP levels (p = 0.002). Copper concentrations increased during the water heater temperature setpoint increase alone to 140°F during December 2022 (p = 0.01). During the flushing and elevated temperature in parts of the building in February 2023, there was a significant increase in chlorine concentrations (p = 0.002) and iron (p = 0.002) but no significant decrease in L. pneumophila concentrations in the drinking water samples (p = 0.27). This study demonstrated the potential impacts of short term or incompletely implemented interventions which in this case were not sufficient to holistically improve water quality. As implementing interventions is logistically- and time-intensive, more effective and holistic approaches are needed for informing preventative and corrective actions that are beneficial for multiple water quality and sustainability goals.

Green gold or carbon beast? Assessing the environmental implications of cryptocurrency trading on clean water management and carbon emission SDGs.

This study addresses the ongoing debate concerning the environmental implications of cryptocurrencies. Specifically, it investigates the impact of Bitcoin trading volume on water and sanitation (Sustainable Development Goal (SDG) 6) and climate action (SDG 13). The research employs Ordinary Least Squares (OLS) panel data analysis to examine these relationships using a sample of 32 countries with available Bitcoin trading volume data from 2013 to 2020. The findings indicate that Bitcoin trading significantly and positively impacts progress towards SDG 6, suggesting potential benefits for water and sanitation initiatives. However, the study reveals a significant negative impact of higher Bitcoin trading volume on increased carbon emissions, underscoring the environmental costs associated with cryptocurrency activities. Similar impacts are observed for gold reserves, as their mining necessitates substantial energy consumption. These results highlight the need to regulate cryptocurrency trading and promote voluntary sustainable practices, particularly given the disparities between developed and emerging markets based on their governance frameworks. Additionally, the study considers the disparities between countries based on technology exports and economic policy uncertainty as influential determinants. The study's results emphasize the importance of proactive measures to ensure the responsible and sustainable use of cryptocurrencies. While cryptocurrencies offer significant economic returns, their early adoption stage necessitates further investigation into environmentally friendly approaches. Potential strategies include directing financial returns from cryptocurrencies towards alternative energy projects and supporting other environmental SDGs, thereby fostering a positive impact on the overall ecosystem. The study's implications extend to policymakers, regulators, and stakeholders, advocating for comprehensive and collaborative efforts to integrate sustainability into the rapidly evolving cryptocurrency market. This integration is crucial to ensure that the economic benefits of cryptocurrencies do not come at the cost of our environment.

Long-term sustainability of the water-agriculture-energy nexus in Brazil's MATOPIBA region: A case study using system dynamics.

The global demand for agricultural commodities has driven extensive land conversion to agriculture in Brazil, especially in the MATOPIBA region. This area encompasses the Rio Grande Basin, a major tributary of the São Francisco Basin that is known for expanding intensive irrigated agriculture and hydropower generation. However, recent data reveal declining precipitation and aquifer recharge, potentially exacerbating ongoing water and land conflicts. This study investigates the long-term sustainability of agricultural expansion amid the worsening water scarcity using a system dynamics model. Findings suggest that rising costs and decreasing profits due to irrigation water shortages may hinder the expansion of irrigated land. By 2040, the irrigation demand may remain partly unmet, while downstream flow and baseflow could decrease. Additionally, agricultural expansion will significantly raise energy demand, posing a developmental challenge. We suggest that ensuring the sustainability of the Rio Grande Basin depends on improved water management and exploring alternative energy sources to address existing constraints.

Excluding livestock access to farm dams reduces methane emissions and boosts water quality.

Farm dams, also known as 'agricultural ponds', are ubiquitous features of agricultural landscapes globally. Those accessed by livestock have high methane (CH4) emissions per unit area relative to other freshwater systems. Fencing dams and installing water troughs to prevent livestock from entering the dams are promising strategies to improve water quality and substantially reduce their carbon footprints. However, previous studies only measured the effects of fencing on methane diffusive emissions without considering ebullitive fluxes (i.e., methane bubbles), which is often the dominant emission pathway in smaller water bodies. Also, data is lacking on how the benefits of fencing farm dams vary across seasons. Using Australia as a test case, this study investigates the benefit of fencing off farm dams by monitoring total CH4 (diffusion + ebullition) and carbon dioxide (CO2) in summer and winter. Fenced dams had 72 % lower CH4 emissions in summer and 92 % lower in winter than unfenced dams. Similarly, CO2-equivalent (CO2 + CH4) fluxes were lower in fenced dams by 59 % in summer and 73 % in winter. Fenced dams had higher water quality, with 51 % less total dissolved nitrogen, 57 % less phosphorous, and 23-49 % more dissolved oxygen. Average daily air temperature was a key predictor of CH4 emissions from farm dams, underscoring the importance of considering temporal dynamics for estimating yearly farm dam emissions. We confirmed that excluding livestock from entering farm dams using fences significantly mitigates CH4 emissions and enhances water quality, and these benefits are maintained seasonally.

The Role of Superabsorbent Polymers and Polymer Composites in Water Resource Treatment and Management.

In the last century, the issue of "water reserves" has become a remarkably strategic topic in modern science and technology. In this context, water resource treatment and management systems are being developed in both agricultural and urban area scenarios. This can be achieved using superabsorbent polymers (SAPs), highly cross-linked hydrogels with three-dimensional, hydrophilic polymer structures capable of absorbing, swelling and retaining huge amounts of aqueous solutions. SAPs are able to respond to several external stimuli, such as temperature, pH, electric field, and solution composition and concentration. They can be used in many areas, from sensor technology to drug delivery, agriculture, firefighting applications, food, and the biomedical industry. In addition, new categories of functional SAP-based materials, mainly superabsorbent polymer composites, can also encapsulate fertilizers to efficiently provide the controlled release of both water and active compounds. Moreover, SAPs have great potential in wastewater treatment for the removal of harmful elements. In this respect, in the following review, the most promising and recent advances in the use of SAPs and composite SAPs as tools for the sustainable management and remediation of water resource are reviewed and discussed by identifying opportunities and drawbacks and highlighting new challenges and aims to inspire the research community.