Search Results (230)

Water planning and governance strategies must adapt to challenges associated with population growth, climate change, and projected water shortages. In the Western United States, agriculture is the dominant water use, and agricultural water users are being asked to conserve or share their water with other uses. Managing scarce water supplies at the local level often involves creative solutions, many of which are not well documented, especially in the agricultural sector. It is therefore critical to understand ideas to manage scarce water resources from the perspective of agricultural water users and those who work with them. In our research, we used interviews to explore how agricultural water users are managing increasing water scarcity in the Middle Rio Grande basin of central New Mexico and what enables or prevents them from taking innovative action to manage water scarcity. We hypothesized that we would find undocumented water use innovations born out of water users’ responses to lower and more variable water availability in recent years. We primarily recruited interviewees through snowball sampling, with a total of 42 (47%) agricultural water users, decision makers, and non-profit leaders influencing agricultural water governance in the basin accepting our invitation to participate. Our approximately one-hour, semi-structured and open-ended interviews explored agricultural water users’ lived experiences with water governance and opportunities to manage water scarcity. The interviews were recorded, transcribed, coded, and analyzed using HyperRESEARCH software (version 4.5.4). Our results did not support our hypothesis. Instead, we found that agricultural water users struggled to implement well-known innovations amid the pressures of water scarcity, supply uncertainty, administrative complexity, and constraints on their time, labor, and money. Water users and decision makers were mutually interested in implementing innovations in crop choice, flexibility in water storage, use, and management, stricter enforcement of water use efficiency, and access to more efficient irrigation equipment. However, high costs, a lack of knowledge, education, and training, and challenges related to water distribution and scheduling prevented agricultural water users from accessing these and other innovations. Recommendations include incentive-based policies to promote agricultural water use innovations that require high initial costs, improved water accounting at the basin and regional levels to promote flexible and reliable access to agricultural water, targeted education and outreach programming on alternative irrigation methods and cropping patterns, and improved access to irrigation scheduling information to support agricultural water users in planning for water scarcity. Full article

Urban green spaces provide recreation opportunities that contribute to physical wellbeing, health, and social wellbeing. However, managing green spaces to promote access and use for recreation and at the same time meet the preferences of visitors is often challenging, especially in developing countries. Using Port Moresby Nature Park (PMNP) in Papua New Guinea as a case study, the objective of this study was to examine visitors’ perceptions of how to manage the park to improve its use for recreation, perceptions of acceptable user fees and preferences for nature types and recreation amenity alternatives. Data were obtained using interviews with 295 visitors to PMNP, of which 291 responses was valid for this study. The data were analysed using descriptive statistics and a multinomial logit regression marginal effect model. The results showed that PMNP can be improved by constructing more toilets, providing more benches at strategic positions, providing water fountains, expanding the children’s playgrounds and training more PMNP staff in customer care. A picnic area was the most preferred and an area containing the Papuan hornbill was the least preferred. On average, the visitors would pay 35% more than the park user fee. A recreation amenity associated with reptiles and birds of paradise was the most preferred and an amenity with only reptiles was the least preferred. Multinomial logit regression model results revealed that preferences for recreation amenity alternatives were influenced by demographic characteristics, the nature type visited, recreation activities, the level of the park user fee, and the time spent at and distance of the interviewees’ dwelling to PMNP. The most important explanatory variables associated with the choice of each of the recreation amenities as reflected by marginal effects include the use of a children’s playground for recreation, grilling and partying during recreation, engagement in walking in natural areas during recreation, the use of animal-dominated areas during recreation and the use of picnic areas during recreation. These findings will assist park managers in making informed decisions by considering visitors’ preferences, the affordability of the park user fee and how to improve an urban green space in a sustainable manner. Full article

Tropical cyclones (TCs) significantly impact the Caribbean Lesser Antilles, often causing severe wind and water damage. Traditional flood hazard assessments simplify TC rainfall as single-peak, short-duration events tied to specific return periods, overlooking the spatial–temporal variability in rainfall that TCs introduce. To address this limitation, a new user-friendly tool incorporates spatial–temporal rainfall variability into TC-related flood hazard assessments. The tool utilizes satellite precipitation data to break down TC-associated rainfall into distinct pathways/scenarios, mapping them to ground locations and linking them to specific sections of the storm’s rainfall footprint. This approach demonstrates how different areas can be affected differently by the same TC. In this study, we apply the tool to evaluate rainfall patterns and flood hazards in St. George’s, Grenada, during Hurricane Beryl in 2024. The scenario representing the 75th quantile in Spatial Region 2 (S2-Q_0.75) closely matched the actual rainfall observed in the study area. By generating multiple hazard maps based on various rainfall scenarios, the tool provides decision-makers with valuable insights into the multifaced flood hazard risks posed by a single TC. Ultimately, island communities can enhance their early warning and mitigation strategies for TC impacts. Full article

Background: Diseases in humans caused by amphizoic amoebae that can result in visual impairment and even blindness, have recently been identified more frequently worldwide. Etiologically complex incidents of keratitis, including those connected with Acanthamoeba strains detected in Poland, were evaluated in this study. Methods: Corneal samples from cases resistant to antimicrobial therapy assessed for epidemiological, microbiological and parasitological aspects were investigated by phase-contrast microscope, slit lamp and by confocal microscopy. In vitro techniques were applied for detection of bacteria and fungi, and corneal isolates cultured under axenic condition using BSC medium—for detection of Acanthamoeba spp.; molecular techniques were applied for amoeba species identification. Results: Most etiologically complicated keratitis cases, detected in ~84% of incidents, was due to exposure of contact lenses to tap water or pool water; trophozoites and cysts of Acanthamoeba, concomitant bacteriae, e.g., Pseudomonas aeruginosa, fungi and microfilariae were identified in contact lens users. Conclusions: In samples from contact lens wearers where microbial keratitis is identified along with some connection with the patient’s exposure to contaminated water environments, a risk of Acanthamoeba spp. infections should be considered. Understanding the complicated relationship between Acanthamoeba spp., co-occurring pathogens including associated endosymbionts is needed. In vivo confocal microscopy and in vitro cultivation were necessary to identify potentially contagious concomitant factors affecting the complex course of the keratitis. Full article

The research introduces a revolutionary Internet of Things (IoT)-based system for fish farming, designed to significantly enhance efficiency and cost-effectiveness. By integrating the NodeMcu12E ESP8266 microcontroller, this system automates the management of critical water quality parameters such as pH, temperature, and oxygen levels, essential for fostering optimal fish growth conditions and minimizing mortality rates. The core of this innovation lies in its intelligent monitoring and control mechanism, which not only supports accelerated fish development but also ensures the robustness of the farming process through automated adjustments whenever the monitored parameters deviate from desired thresholds. This smart fish farming solution features an Arduino IoT cloud-based framework, offering a user-friendly web interface that enables fish farmers to remotely monitor and manage their operations from any global location. This aspect of the system emphasizes the importance of efficient information management and the transformation of sensor data into actionable insights, thereby reducing the need for constant human oversight and significantly increasing operational reliability. The autonomous functionality of the system is a key highlight, designed to persist in adjusting the environmental conditions within the fish farm until the optimal parameters are restored. This capability greatly diminishes the risks associated with manual monitoring and adjustments, allowing even those with limited expertise in aquaculture to achieve high levels of production efficiency and sustainability. By leveraging data-driven technologies and IoT innovations, this study not only addresses the immediate needs of the fish farming industry but also contributes to solving the broader global challenge of protein production. It presents a scalable and accessible approach to modern aquaculture, empowering stakeholders to maximize output and minimize risks associated with fish farming, thereby paving the way for a more sustainable and efficient future in the global food supply. Full article

Urban green infrastructure (UGI) is a network composed of natural and semi-natural areas, such as greenspaces, open areas, and water bodies, designed to enhance the provision of ecosystem services and to meet the needs and expectations of local communities. UGIs should be accessible and should improve the well-being and health of their users, protect and enhance biodiversity, and allow for the enjoyment of natural resources. The study proposes a methodological approach to defining a UGI, conceived as a network of areas connected by urban ecological corridors and suitable for providing climate regulation, flood risk mitigation, outdoor recreation, and biodiversity and habitat quality enhancement. The methodology is applied to the functional urban area (FUA) of the City of Cagliari, Italy. The analysis results show that areas with high values of climate regulation, carbon storage and sequestration, and habitat quality enhancement are particularly suitable to be part of a UGI. Although values for outdoor recreation appear to be less significant, the provision of this service is particularly relevant within the Cagliari FUA. However, areas characterized by high values of flood risk mitigation show a different behavior, which highlights how the presence of impermeable surface within urban areas is associated with a loss of patch connectivity. Full article

So far, many researchers have attempted to tackle issues associated with intermittent water supply (IWS) systems, such as the inequitable distribution of water, by employing deterministic models that rely on multiple assumptions about input parameters. However, owing to the diverse practices and operations associated with IWS systems, significant uncertainty prevails in various aspects, including user water consumption, supply characteristics, and household tank sizes. In this work, a novel uncertainty quantification framework for assessing uncertain model input parameters is proposed. Full article

Utility management demands two basic functions for an optimal automation scenario, which are monitoring and control. Here, we report a novel approach utilizing free spectrum communication technology and the Internet of Things (IoT) framework for Water Distribution Network (WDN) management. We make use of an architecture combining the free spectrum protocols included in the ISM (Industrial, Scientific, and Medical) radio band, along with cloud-based data management. The main aspects of the developed system are user-friendly operation and control, along with reliable and fault-free operation. In this paper, we discuss, in detail, the architecture, hardware design, and software applications associated with the IoT-based wireless monitoring and control of WDNs. Full article

Wastewater reuse is a proven strategy to mitigate water stress in drought-prone regions. However, this practice is still limited due to high implementation costs, regulatory hurdles, and limited public acceptance. In regions with low reclaim rates, a thorough evaluation of the potential for reuse is needed to support decision-making, focusing on opportunities that address both low-hanging fruit and high-leverage projects. This paper introduces a streamlined, data-centric methodology for assessing wastewater reuse potential, adaptable to various regional contexts. The methodology involves comprehensive data collection and processing to evaluate wastewater treatment plant (WWTP) capabilities and identify potential users, allowing the prioritisation of case studies based on demand alignment. Different treatment and distribution systems are analysed to match WWTP capabilities with user needs, considering volume, quality, and infrastructure requirements. Cost analysis incorporates capital expenditure (CAPEX), operational expenditure (OPEX) and unit costs using novel cost functions for treatment and distribution. Risk analysis adheres to WHO methodology to ensure safety and sustainability. A case study in the Lisbon and Oeste areas in Portugal validates this approach, revealing key insights into the potential and economic viability of water reuse. By comparing tariffs and costs associated with different reuse scenarios, this paper offers benchmarks for the economic feasibility of reuse projects. Full article

In today’s digital age, innovative artificial intelligence (AI) methodologies, notably machine learning (ML) approaches, are increasingly favored for their superior accuracy in anticipating the characteristics of cementitious composites compared to typical regression models. The main focus of current research work is to improve knowledge regarding application of one of the new ML techniques, i.e., gene expression programming (GEP), to anticipate the ultra-high-performance concrete (UHPC) properties, such as flowability, flexural strength (FS), compressive strength (CS), and porosity. In addition, the process of training a model that predicts the intended outcome values when the associated inputs are provided generates the graphical user interface (GUI). Moreover, the reported ML models that have been created for the aforementioned UHPC characteristics are simple and have limited input parameters. Therefore, the purpose of this study is to predict the UHPC characteristics while taking into account a wide range of input factors (i.e., 21) and use a GUI to assess how these parameters affect the UHPC properties. This input parameters includes the diameter of steel and polystyrene fibers (µm and mm), the length of the fibers (mm), the maximum size of the aggregate particles (mm), the type of cement, its strength class, and its compressive strength (MPa) type, the contents of steel and polystyrene fibers (%), and the amount of water (kg/m³). In addition, it includes fly ash, silica fume, slag, nano-silica, quartz powder, limestone powder, sand, coarse aggregates, and super-plasticizers, with all measurements in kg/m³. The outcomes of the current research reveal that the GEP technique is successful in accurately predicting UHPC characteristics. The obtained R², i.e., determination coefficients, from the GEP model are 0.94, 0.95, 0.93, and 0.94 for UHPC flowability, CS, FS, and porosity, respectively. Thus, this research utilizes GEP and GUI to accurately forecast the characteristics of UHPC and to comprehend the influence of its input factors, simplifying the procedure and offering valuable instruments for the practical application of the model’s capabilities within the domain of civil engineering. Full article

Effective and sustainable water resource management requires flexibility and adaptation to local contexts. Our study analyzes the emergence and evolution of local water self-governing associations, reviewing how their struggles and conflicts, both with the public sector and among locals themselves, have been pivotal to achieving agreements and actions towards sustainable water management. Using an adapted version of the Combined Institutional Analysis and Development (IAD) and social–ecological system (SES) framework, also known as CIS, we conducted a comparative analysis of two distinct Chilean cases. This research highlights the critical role of historical factors alongside institutional support, political landscapes, and financial realities in shaping current water management practices. The findings suggest that when the actors are aligned and actions are taken to support local water user management, more efficient, sustainable, and less conflict-ridden water resource management occurs. Furthermore, this study reveals how the experiences, struggles, and successes of these local user associations have shaped national policies, particularly regarding the development of monitoring mechanisms and the promotion of public–private cooperation in water governance. These efforts have not only fostered more resilient water management systems but have also demonstrated the power of grassroots organizations in shaping broader sustainable policies. Full article

Jerusalem artichoke (JA) (Helianthus tuberosus L., family Asteraceae) is an important feedstock for biofuel production due to its high biomass yield per unit area and the low costs associated with plantation establishment and cultivation technology. The chemical composition of the aerial biomass of JA grown in a perennial cycle and harvested once or twice during the growing season was determined, to assess the potential of JA for energy production. The experiment was conducted in 2018–2020 in north-eastern Poland. The study demonstrated that the crude ash (CA) content of the biomass was significantly (by 24.1%) higher when JA was harvested twice rather than once during the growing season, making it less suitable for energy purposes. However, double cutting induced an increase in the content of crude fiber (CFR), cellulose, and hemicellulose (by 87%, 41%, and 52%, respectively) in JA biomass compared with single cutting. In addition, twice-harvested JA biomass was also characterized by higher concentrations of neutral detergent fiber (NDF), acid detergent fiber (ADF), and acid detergent lignin (ADL) (by 40.7%, 38.9%, and 30.3%, respectively), and a lower (by 29.3%) concentration of water-soluble carbohydrates (WSC). These results indicate that the chemical composition of a JA biomass can be modified by selecting the appropriate harvest strategy, which is an important consideration for end users. Full article

The current study begins with an experimental investigation focused on measuring the pressure drop of a water–air mixture under different flow conditions in a setup consisting of horizontal smooth tubes. Machine learning (ML)-based pipelines are then implemented to provide estimations of the pressure drop values employing obtained dimensionless features. Subsequently, a feature selection methodology is employed to identify the key features, facilitating the interpretation of the underlying physical phenomena and enhancing model accuracy. In the next step, utilizing a genetic algorithm-based optimization approach, the preeminent machine learning algorithm, along with its associated optimal tuning parameters, is determined. Ultimately, the results of the optimal pipeline provide a Mean Absolute Percentage Error (MAPE) of 5.99% on the validation set and 7.03% on the test. As the employed dataset and the obtained optimal models will be opened to public access, the present approach provides superior reproducibility and user-friendliness in contrast to existing physical models reported in the literature, while achieving significantly higher accuracy. Full article

Dementia can be associated with social withdrawal, mood changes, and decreased interaction. Animal-assisted therapies and robotic companions have shown potential in enhancing well-being but come with limitations like high maintenance costs and complexity. This research presents an interactive digital aquarium called Mindful Waters, which was developed to promote social interaction and engagement among People with Dementia. The pilot study involved interactive sessions at a community center and a care facility, with situated observations, video and audio recordings, and interviews to assess user engagement motivation, behavior, and user experience with Mindful Waters. The study revealed that Mindful Waters functioned well with People with Dementia and stimulated conversational topics about aquariums through engagement. User feedback was generally positive, with participants appreciating the visual appeal and simplicity. However, some participants with advanced dementia found it challenging to interact due to their mobility limitations, cognitive impairments, and the limited duration of interaction sessions. The overall results suggest that Mindful Waters can benefit dementia care; further research is needed to optimize its design and functionality for long-term placement in care facilities. Full article

Pseudomonas aeruginosa is a common pathogen associated with recreational water facilities and poses risks to public health. However, data on the prevalence of P. aeruginosa in tourist destinations like the Canary Islands, Spain, remain limited. We assessed P. aeruginosa prevalence in 23 tourist facilities from 2016 to 2019. Compliance with water quality standards was evaluated, and 3962 samples were collected and analyzed. We examined different types of recreational water installations, including outer swimming pools, whirlpools, and cold wells. Of the sampled facilities, 31.2% did not comply with the current legislation’s parametric values, mainly due to inadequate disinfectant levels, water temperature, and P. aeruginosa presence. The prevalence of P. aeruginosa was 4.8%, comparable to some European countries but lower than others. Cold wells displayed the highest non-compliance rate (89.2%) and yet exhibited a lower P. aeruginosa prevalence (1.9%) than outer swimming pools and whirlpools. Children’s presence did not significantly impact P. aeruginosa contamination. Chlorine-based disinfectants are more effective than bromine-based ones in controlling P. aeruginosa. Regional variability in contamination was observed, with Fuerteventura showing lower colonization rates. Disinfectant levels play a critical role in P. aeruginosa control, and maintaining adequate levels is essential, particularly in bromine-treated installations. Our findings provide valuable insights into the prevalence and distribution of P. aeruginosa in recreational waters within tourist facilities. Tailored strategies are needed to ensure water safety in different Spanish regions. Continued monitoring and assessment, combined with artificial intelligence and machine learning, will enable the implementation of targeted interventions to protect the health of recreational water users. Full article