Journal of Vascular Nursing

ABSTRACT This study presents an initial assessment of the hydrographic characteristics in the region of the Japaratuba Canyon on the continental shelf of Sergipe, Brazil. An oceanographic campaign was conducted, during which two high spatial resolution transects were made on the north and south sides of the canyon, along with a transverse transect. The results indicate that the hydrographic features are similar to those found on the continental shelf of Pernambuco, with the dominant water mass being Tropical Water. However, it differs in having a much greater influence from Coastal Water, as a result of the dispersion of the São Francisco River plume to the south and from small rivers that discharge into the northern portion of the continental shelf of the state of Sergipe. The near bottom turbidity and chlorophyll were relatively higher in the southern section, what can be an indication that the presence of the canyon can produce a localized upwelling effect, with the canyon playing a role in allowing the approach of water from the top of the nearest permanent thermocline to the coast.

ABSTRACT The flood map outputs from hydrodynamic models may contain uncertainties due to inaccuracies in the input parameters. On the other hand, the results of dam break models are crucial for performing risk analyses of potential material and social damage. Thus, this study applied a global sensitivity analysis (GSA) to evaluate the effects of the floodplain Manning coefficient on the inundation generated by the hypothetical dam break of a real water dam in HEC-RAS 2D. Three aspects of flood output, the peak discharge, the arrival time and the time of flood damping, were analyzed via variance tests. The Manning coefficient varied from 0.026 to 0.150, resulting in a change of up to 54% in the peak discharge at a distance of 25 km and a delayed arrival time corresponding to 16 minutes in the cross section located 1 km downstream of the dam. However, Manning coefficients between 0.026 and 0.050 show statistically similar results in terms of two aspects (the peak discharge and the arrival time). This study indicated that the GSA and variance tests may contribute to critical analyses of Manning coefficient adoption and help decision-makers develop criteria for planning emergency actions.

ABSTRACT Swift detection and repair of leaks in water distribution networks are essential to ensure the operational efficiency of the system. It’s not viable, both financially and technically, to scour the entire extension of the system to look for leaks, therefore it’s important to narrow down areas prone to leakage. Hydraulic techniques are useful to that end, since hydraulic data can be used to identify anomalies and guide efforts on field campaigns. Among these techniques, those based on the transient state are used to infer about the actual condition of the system by causing controlled disturbances, such as closing a valve, as to reveal anomalies like leaks, deposits or illegal connections. In this paper, the software OpenFlows Hammer, was used to model the transient state and generate the transient state data. This data was then analyzed based on signal theory. The results show that it’s possible to identify the presence of leaks, even minor ones, and their location in relation to the monitoring point. However, further studies are needed to better establish metrics relevant to characterize the behavior of the data in the frequency domain.

ABSTRACT Cavitation is a phenomenon that reduces the useful life of hydraulic machines, taking place in function of the variation of the pressure gradient at a constant temperature. In hydraulic turbines, cavitation occurs when the turbine operates beyond nominal conditions, generating abnormal vibrations, erosion to blades and other key components, thus resulting in stoppage for maintenance. This article proposes a cavitation monitoring system based on the analysis of vibration spectra via two Machine Learning (ML) models: a Multilayer Perceptron (MLP) neural network and a Radial Basis Function (RBF) neural network. Drawing upon vibration analysis and pressure coefficient parameter standards, such models are capable of identifying the vibratory state of a given machine, distinguishing its cavitating and non-cavitating states. Moreover, it is proposed that these models may estimate real conditions for turbine functioning, thus enabling planning for the most opportune moment to carry out turbine maintenance. Both ML models were evaluated through a series of experiments with data from a Francis turbine installed in Brazil, where vibration spectra and flow pressure coefficients were monitored; they identified cavitating and non-cavitating states with precision levels between 95% and 100%, thus demonstrating satisfactory performance and serving as an important step in the development of a system for monitoring hydropowers.

ABSTRACT Water main bursts not only lead to financial losses, but also water losses. Climate change and water resources scarcity puts in perspective the need to understand the conditions of the water transportation infrastructure to prevent accidents. The objective of this work is to present resilience indices related to the operation of the water system and infrastructure operational limits to aid decision maker to evaluate risk. The resilience indexes were established based on four indexes arising from transient flows simulation: burst pressure, minimum transient pressure, maximum air volume and resultant forces. Decision making on a complex problem with many parameters based on a simple index is not straightforward, therefore we used a multicriteria decision technique to assist, the simplified three-scale Analytic Hierarchy Process (AHP). To test the proposed method, a case study of a trunk main from the municipality of Franca, Brazil is presented. To calculate the indexes a hydraulic model with transient flows of the referred system was simulated. For the case study, a few scenarios were evaluated. The scenario where no protection devices are present is the most critical.

ABSTRACT Reservoirs present different and intrinsic characteristics from the point of view of physical, chemical, and biological nature from other environmental systems. They therefore should be characterized differently for a better representation aiming for proper planning and management strategies. This paper analyzes eleven reservoirs and develops a classification and zonation strategy for those systems. First, temporal variation and statistical analysis are performed, followed by a residence time calculation, to assess the reservoir's dynamics. Next, stratification and spatial variation analysis are proposed to verify their necessity. Three of the reservoirs analyzed behave as lentic systems, with a high residence time. In addition, all three have significant tributaries, indicating the potential necessity of considering spatial variation for their classification, later verified in 3D modeling. Even if every reservoir is unique in its dynamics and characteristics, the classification scheme is suitable for different types of reservoirs, since it works like a decision tree, where input loads and hydrodynamics are considered.

ABSTRACT Araruama is a perennial hypersaline lagoon where seawater flows in through a narrow connection and spreads, where it is intensively evaporated. Although the inflow of seawater increases the salts load, a high inflow may reduce flushing time, decreasing salinity. Although reducing flushing time would improve water quality, the accompanying reduction in the salinity may change the ecological equilibrium. In the present research, a numeric hydrodynamic model was applied to Araruama Lagoon, to determine the maximum connection depth that promotes reduction of flushing time, however maintaining salinity. Five scenarios were executed in the hydrodynamic model SisBaHiA© with changing hydraulic area, including channel average depths of 2.5 m, 3.0 m, and 4.0 m. The salinity simulations outlined three segmented sectors, the first associated with the connection channel, but also affecting the proximal portion of the lagoon; the second is an intense evaporation area, with high salinity values, and the third, in the western portion of the lagoon where freshwater inputs can affect salinity. The tested channel bathymetry scenarios promoted a salinity increase with a channel depth of 3.0 meters. With a connection channel depth of 4.0 meters (highest hydraulic area), the threshold limit is attained, and salinities are reduced in the lagoon.

ABSTRACT For effective management practices and decision-making, the uncertainties associated with regional climate models (RCMs) and their scenarios need to be assessed in the context of climate change. This study analyzes long-term trends in precipitation and temperature data sets (maximum and minimum values) from the NASA, Earth Exchange Global Daily Downscaled Prediction (NEX-GDDP), under the São Francisco River Basin Representative Concentration Path (RCP) 4.5 and 8.5, using the REA (Reliable Ensemble Average) method. In each grid, the built multi-model was bias-corrected using the CMhyd software for annual, dry, wet, and pre-season periods – for historical (1961-2005) and future (2006-2100) periods. The multi-model and four different methods, namely: The Mann-Kendall, Mann-Kendall pre-brightening test, bias-corrected pre-brightening, and Spearman correlation, were used to detect trends in precipitation, and minimum and maximum temperature. In the analysis of precipitation and temperature metrics, the results for the NRMSD showed that, in general, the CSIRO model presented more satisfactory results in all physiographic regions. Person's correlation coefficient showed a better adjustment of precipitation for the MIROC5, EC.EARTH and NORESMI1 models, in areas of sub-medium and upper São Francisco. For the minimum temperature, the CSIRO and NORESMI1 models showed the best fit, in general. At maximum temperature, the EC.EARTH and CSIRO models showed more satisfactory results. With regard to trend analysis, the results indicated an increasing trend in mean annual temperature and precipitation across the basin. When analyzed by subregion, the results show an increasing trend in monthly average minimum and maximum temperatures in the middle and lower SFRB, while average monthly rainfall increases during the rainy season and preseason in Upper São Francisco. The results of this research can be used by government entities, such as Civil Defense, to subsidize decision-making that requires actions/measures to relocate people/communities to less risky locations to minimize risk or vulnerability situations for the population living nearby to the river.

ABSTRACT The occurrence of floods causes hundreds of drowning deaths annually. Therefore, it is necessary to develop measures and risk management policies related to flood disasters. One approach is the definition of stability thresholds for individuals in water flows, as safety is compromised when people are exposed to flows that surpass their ability to stand or cross. Based on these considerations, the objective of the study was to conduct a literature review of experimental, empirical, and theoretical studies on this topic, evaluating stability thresholds for individuals exposed to water flow. In total, 34 studies conducted until the year 2023 were identified. Key factors influencing stability include water flow characteristics and the physical attributes of individuals. In addition to these factors, adverse conditions such as uneven terrain, poor lighting, and psychological factors were also considered important. However, it was noted that few studies have assessed such adverse conditions, and there is a gap in the experimental analysis of these variables. Therefore, this study emphasizes the importance of conducting more physical experiments to address these gaps, obtain a more comprehensive database, and improve precision in numerical and experimental models, ultimately supporting tools for flood risk management.

ABSTRACT The pursuit of efficient water distribution network (WDN) projects that reflect the complexities of real systems has spurred the development and application of various optimization techniques. Among these, multi and many-objective optimization hold particular significance due to the intrinsic interplay between variables within water distribution networks. Within this domain, evolutionary algorithms have emerged as a promising optimization option, offering a range of methodologies documented in the literature. To systematically evaluate these approaches, a methodology was devised to compare six evolutionary algorithms in the context of water distribution networks optimization: NSGA-II, NSGA-III, U-NSGA-III, R-NSGA-III, MOEA/D, and RVEA, using two distinct objective functions. The comparative analysis utilized as key metrics the efficiency criteria (E), cumulative distribution function (CDF), error statistics and algorithm complexity. The findings revealed that while most algorithms successfully converged to the known global optimum of the employed case study, NSGA-II and NSGA-III exhibited superior performance, notably in minimizing costs. These results demonstrate the efficacy of these algorithms in tackling the complexities inherent in water distribution networks optimization, positioning them as leading contenders in this field.

ABSTRACT This work presents a two-dimensional simulation of infiltration dynamics in a real permeable pavement (PP) structure in the city of Recife, representing more realistically the geometry of the infiltration bulb and the dynamics of water redistribution processes in the PP. Sixteen infiltration tests were carried out on the PP using the Beerkan method. The hydrodynamic parameters of the PP surface were determined by applying the inverse method to the infiltration data. Simulations of water transfer processes were carried out with Hydrus-2D using the hydrodynamic properties corresponding to the highest and lowest saturated hydraulic conductivity observed on the surface. Satisfactory infiltration characteristics were observed in the PP. The inverse method showed good adjustment capacity to the accumulated infiltration curves and estimation of hydrodynamic properties. Simulations using Hydrus-2D demonstrated that the infiltration process and water redistribution in the subgrade depend on the hydrodynamic properties of the coating.

ABSTRACT This Technical Note aims to present data from in-situ measurements conducted with Acoustic Doppler Current Profiler (ADCP) under the highest level recorded in the Guaíba River. Flow measurements carried out on May 5th and 6th, with water levels of 5.27 and 5.25 m, resulted in average values of 30,180 and 29,852 m3/s, respectively. The profiles with the river flow are presented, as well as the water level readings at the Usina do Gasômetro gauges. These data can be accessed on a open platform, can contributes to the understanding of the Guaíba's hydrodynamics and the flooding at Patos Lagoon and can provide valuable information for modeling maximum flow scenarios in these systems.

ABSTRACT The quality of water distribution and the coefficients that express water use efficiency are evaluated from the distribution of the irrigation depth (I). However, a hypothesis has been proposed that it may be more effective to base these analyses on the water depth stored in the soil profile (H), after irrigation. To evaluate this hypothesis, in a very clayey soil, bean was cultivated under irrigation by conventional sprinkling, with four scenarios of water application uniformity. During the crop cycle, irrigations were carried out, scheduled according to a lower limit of soil-water potential. The four scenarios were associated with 64, 144, 192 and 256 experimental points, which were characterized as having excellent (S1), adequate (S2), inadequate (S3) and unacceptable (S4) uniformity, according to obtained values of Christiansen’s uniformity coefficient (CUC) and distribution uniformity coefficient (DUC). At the end of the cycle, harvest was carried out in each grid, obtaining the crop yield. The uniformity of water distribution in the soil negatively impact crop yield only in S4, with an unacceptable water application pattern. The irrigation quality analysis based on values of H is more consistent with the results observed for the crop than the analysis based on the applied water depth.

ABSTRACT Environmental monitoring of water is essential for efficient management of water source conservation in river basins. However, there is a lack of studies with this synergy applying unconventional techniques. We evaluated chemical characteristics of surface and underground waters (2021-2022), including for the first time the analysis of the isotopic composition of waters collected from water sources throughout Educandos`s Basin, in the city of Manaus-AM/Brazil, to evaluate chemical-isotopic changes in the view of anthropogenic impacts. Statistical analyzes were used to compare means, graphical analyzes and Principal Component Analysis to identify the main patterns of the data sets. Our results demonstrated a significant increase in pH, electrical conductivity and an increased in nitrates in polluted groundwater and reduced DO in contaminated surface waters. Furthermore, the isotopic signature did not indicate pollution through changes in the isotopic composition of natural and polluted waters, however, it showed more depleted signatures in one of the underground monitoring wells, indicating an impact site vulnerable to the interaction of aquifer waters with Rio Negro and Igarapé. When analyzing chemical parameters with isotopic composition, it can be allowed a better understanding of the mechanisms of circulation and mineralization of underground and surface waters in the Urban Hydrographic Basin.

ABSTRACT The presence of emerging contaminants in surface water is a growing concern, as these substances are not typically monitored by environmental quality systems, potentially leading to the consumption of contaminated water. In this study, the presence of caffeine, an emerging contaminant that is ingested solely by humans and is present in surface water due to its chemical characteristics, was investigated as a potential indicator of anthropogenic contamination in the Itajaí-Açu River in the southern Brazilian Atlantic Forest biome. Additionally, twelve other emerging pollutants were examined in the Itajaí-Açu River, including estrone (E1), estradiol (E2), ethinylestradiol (EE2), estriol (E3), prednisone (PD), hexestrol (HEX), acetaminophen (ACM), Oxytetracicline (OC). Surface water samples were collected over five months and analyzed using high-performance liquid chromatography. The results revealed that caffeine was present in 84% of the analyzed samples, and emerging pollutants were present in all monitored municipalities. The study also investigated the relationship between an integrated water quality index, the magnitudes and occurrences of caffeine, and land use. The emerging pollutants Estrone, Ethinylestradiol, Hexestrol, Naproxen and Oxytetracycline were not detected in the analyzed samples. However, Ibuprofen, Tetracycline, Prednisone, and Acetaminophen were present in 44% and 36% of the samples, respectively, with Estriol, Ketoprofen, and Estradiol having a lower occurrence. The mean concentrations of Estradiol, Estriol, Ketoprofen, Acetaminophen, and Ibuprofen were 0.08 µg L-1, 0.23 µg L-1, 0.15 µg L-1, 0.42 µg L-1, and 0.44 µg L-1, respectively, and were higher than previously reported. The concentration range of caffeine during the study was <0.10 to 1.48 µg L-1, with the mean concentration being 0.30 µg L-1. These findings highlight the presence of emerging pollutants in the Itajaí-Açu River and the need for continued monitoring and regulatory legislation to protect surface water quality in Brazil.