Showing papers in "Revista Brasileira de Recursos Hídricos in 2022"
TL;DR: In this paper , a two-dimensional mathematical model was developed combining hydrodynamics and populational dynamics to simulate the distribution of mussels in a reservoir, and the results showed that dam's region was progressively infested, and after 18 months of simulation it has reached around 80% of its carrying capacity.
Abstract: ABSTRACT Golden mussel is an invasive species in Brazil which impacts local environments, dislocating native species and altering microecological conditions as well as affecting hydroelectric power plants and water treatment systems. The objective of this research is to establish a method that is both effective and efficient to quantify the population of the Golden mussel in hydroelectric power plant reservoirs, with a focus on population control measures. A two-dimensional mathematical model was developed combining hydrodynamics and populational dynamics to simulate the distribution of mussels in a reservoir. The results showed that dam’s region was progressively infested, and after 18 months of simulation it has reached around 80% of its carrying capacity. The method proved to be satisfactory and the generated map of cluster locations for the golden mussel corresponds to field observations. Furthermore, the result of the algae density simulation matched chlorophyll-a density map obtained from satellite images. The methodology can be further applied to new areas and could be expanded to predict population variations in order to guide environmental measures for preservation and recovery of impacted reservoirs, presenting another tool for hydroelectric operators who can use information together with field inspections to plan maintenance intervals before infestation damages equipment.
4 citations
TL;DR: Siqueira et al. as mentioned in this paper evaluated the ability of large-scale models to obtain flood hazard maps for the municipalities of Uruguaiana, Montenegro and São Sebastião do Caí in the Rio Grande do Sul state.
Abstract: ABSTRACT Mapping flood risk areas is important for disaster management at the local, regional, and national scales. The aim of this study was to evaluate the ability of large-scale models to obtain flood hazard maps. The models were compared to the estimates developed by the Brazilian Geological Survey (CPRM) for different return periods (RP). The floods were evaluated for the municipalities of Uruguaiana, Montenegro and São Sebastião do Caí in the Rio Grande do Sul state. It was shown that the flood mapping generated by MGB covers larger areas (greater than 1000 km2; Siqueira et al. 2018), with a lower cost of obtaining for large scales. The - Hit Rate of the regional and continental MGB model versions with the CPRM maps ranged from about 40% to 90% in different cities, and the Hit Rate between the regional model and the CPRM map increased with the increased return period floods. The continental model compatibility was similar for all analyzed RPs. Our results suggest the agreement in terms of Hit Rate of current large-scale hydrological-hydrodynamic models to assess flood hazard.
2 citations
TL;DR: In this paper , a similarity measure that considers the randomness present in SAR data is proposed, and the similarity measure is carefully elaborated as a function of the stochastic distance such that its variation space is the interval [0, 1], facilitating its interpretation.
Abstract: ABSTRACT Change detection based on remote sensing images, has attracted increasing attention from researchers throughout the world. The synthetic aperture radar (SAR) images have become key resources for detecting changes on the land surface. However, due to the presence of speckle noise and its stochastic nature, SAR data require methodologies that consider these peculiarities. This article presents a similarity measure that considers the randomness present in SAR data. To retrieve the random component in the SAR data, we used the stochastic distance. The similarity measure is carefully elaborated as a function of the stochastic distance such that its variation space is the interval [0, 1], facilitating its interpretation. Our proposal shows promising results in two applications: contrast evaluation, ocean surface change detection and binary change map. It is noteworthy that the possible limitations of our proposal are investigated through simulations guided by a Monte Carlo experiment.
1 citations
TL;DR: In this article , seven stations were sampled along three rivers that serve as public water suppliers in three sampling campaigns, in the Upper Iguassu Basin, Brazil, in order to determine the presence of emergent contaminants in aquatic environments and to evaluate responses of the dominant taxa of benthic macrofauna.
Abstract: ABSTRACT To determine the presence of emergent contaminants in aquatic environments and to evaluate responses of the dominant taxa of benthic macrofauna, seven stations were sampled along three rivers that serve as public water suppliers in three sampling campaigns, in the Upper Iguassu Basin, Brazil. Concentrations of ethinylestradiol, fenofibrate, ibuprofen and triclosan were detected in the water and sediment. To correlate patterns of distribution and abundance benthic fauna with the various contaminants found a redundancy analysis (RDA) was applied and showed positive relationships between faunal groups, that indicate stress (such as Tubificinae), and emerging pollutants (such as ibuprofen and ethinylestradiol). The analysis also showed that the most influential variables in the distribution of the fauna were exclusively anthropogenic, which shows that these compounds can be harmful and that the rivers destined for the supply are receiving pollutant loads.
1 citations
TL;DR: In this article , the spatial and temporal variability patterns of water quality were evaluated through monthly collection of water samples (surface, sub-surface and bottom) from 2005 to 2012, and principal component analysis was used to define the relative importance of each variable and Anova (two way) to analyze the significance of differences in water quality.
Abstract: ABSTRACT Spatial and temporal variability patterns of water quality were evaluated through monthly collection of water samples (surface, sub-surface and bottom) from 2005 to 2012. Principal Component Analysis was used to define the relative importance of each variable and Anova (two way) to analyze the significance of differences in water quality in the longitudinal axis of the reservoir. The variables: turbidity, Secchi transparency, residence time and temperature have greater importance on water quality. It was observed spatial and temporal gradients, related to the circulation, sedimentation and resuspension processes, and the influence of low flow, high residence time and winter mixing of water column on the cycling of solids and nutrients may explain the variation in these processes. The use of multivariate statistical analysis methods provided important information to understand these processes, it helps the interpretation of complex data to improve monitoring, and use of information to decision makers.
1 citations
TL;DR: In this article , the results of Bayesian rating curve modeling, which considers the physical knowledge of the gauging station as prior information, were combined with Bayesian flood frequency analysis under asymptotic extreme value theory.
Abstract: ABSTRACT Maximum flows are often estimated from flood frequency analysis, by means of the statistical fitting of a theoretical probability distribution to maximum annual flow data. However, because of the limitations imposed by the practice of at-site flow measurement, empirical models are applied as the rating curve for estimating streamflow. These curves are approximations of the actual flows and incorporate different sources of uncertainty, especially in the extrapolation portions. These uncertainties are propagated in the frequency analysis and influence the estimated quantiles. For better understanding and describing the influence of the stage-discharge uncertainty in this process, the results of Bayesian rating curve modeling, which considers the physical knowledge of the gauging station as prior information, were combined with Bayesian flood frequency analysis under asymptotic extreme value theory. The method was applied to the Acorizal stream gauging station, located in the interior of the state of Mato Grosso - BR. The main results suggested that, although the uncertainties of the rating curve can be relevant in the estimation of maximum flow quantiles, the uncertainties arising from finite-sample inference might exert greater impacts on the flow credibility intervals even for moderate sample sizes.
1 citations
TL;DR: A Python implementation for this methodology with a user-friendly Graphical User Interface is proposed and the results are similar to those produced by the original implementation and can be generated considerably in less time and with less user interaction.
Abstract: ABSTRACT Since 2010, the Brazilian government has required that dams that fall within the national dam policy must present a safety plan, which, among other topics, must address the definition of the hypotheses and possible disaster scenarios. To achieve it, the flood zone due to an eventual failure must be modeled for the Hazard Potential (Dano Potencial Associado – DPA) classification. The flood zone is the result of complex hydraulic phenomena that are difficult to characterize. Given the demand for DPA analysis and the data unavailability, the National Water Agency (Agência Nacional de Águas - ANA) proposed a simplified methodology for generating the flood zone., This paper proposes a Python implementation for this methodology with a user-friendly Graphical User Interface. Our implementation relies on free and open-source software. The results are similar to those produced by the original implementation and can be generated considerably in less time and with less user interaction.
TL;DR: Improvements to the Pfafstetter basin coding system are proposed, maintaining it simple, while keeping the topological relationship between the stretches and including the possibility to represent the hydrography with multiple confluences, cycles, delta mouths, sinks, water masses and disruptions to drainage.
Abstract: ABSTRACT The coding basin system proposed by Pfafstetter (1989) is an important reference point and adopted by the principal water resources management system in the world. This adoption is due to the method’s simplicity and the topological relationship between the river stretches built-into the codes. Otherwise, the Pfafstetter basin coding system can only be applied in a hydrographic vector represented by an anti-arborescence binary graph. This type of representation causes loss of hydrographic information due to the simplification of regions where there are anabranching, braided or delta areas that implies multiple confluences, cycles or disruptions of the network. This paper proposes improvements to the Pfafstetter basin coding system, maintaining it simple, while keeping the topological relationship between the stretches and including the possibility to represent the hydrography with multiple confluences, cycles, delta mouths, sinks, water masses and disruptions to drainage.
TL;DR: In this paper , the authors defined technical criteria to operate water reservoirs in the context of water transfer between river basins by using Brazil's Armando Ribeiro Gonçalves (ARG) reservoir in the state of Rio Grande do Norte, one of the reservoirs receiving water from the São Francisco River Integration Project (PISF), as a case study.
Abstract: ABSTRACT Inter-basin water-transfer projects are used as a possible solution to increasing water scarcity in many regions, but these projects are often expensive and require large infrastructures, so their benefits need to be maximised and their costs reduced. In this context, this study’s objective was to define technical criteria to operate water reservoirs in the context of water transfer between river basins by using Brazil’s Armando Ribeiro Gonçalves (ARG) reservoir in the state of Rio Grande do Norte, one of the reservoirs receiving water from the São Francisco River Integration Project (PISF), as a case study. The results demonstrate that using hydrological conditions to define when and how much water to transfer is extremely important for water resource management, as it increases reservoir efficiency and reduces transferred volumes, thereby cutting costs.
TL;DR: In this paper , the authors used self-organizing maps (SOMs) to identify clusters of spatial synoptic precipitation patterns and compared these clusters with the precipitation regime of the ten main hydrographic subbasins in Brazil.
Abstract: ABSTRACT In this study, we used neural networks known as self-organizing maps (SOMs) to identify clusters of spatial synoptic precipitation patterns. These clusters were compared with the precipitation regime of the ten main hydrographic sub-basins in Brazil. Sixty years of daily precipitation data obtained from over 389 weather station in Brazil were used as input data for the SOMs, with a number of six clusters being prescribed as the optimal number according to the elbow and silhouette methods. The six precipitation patterns identified by the SOMs reflect the typical synoptic conditions associated mainly with the cold frontal systems (CF), South American Monsoon System (SAMS) and Inter-tropical Convergence Zone (ITCZ). In conclusion, SOMs perform well using interpolated precipitation data as the input data to identify synoptic precipitation patterns, which could be used to monitor the spatial distribution of precipitation, which affects the hydrographic basins in Brazil and hence hydropower plant performance.
TL;DR: In this paper , a study of the groundwater-surface water interaction in the Onça Creek Watershed (Guarani Aquifer System outcrop) using stream discharge data and temperature as a natural tracer is presented.
Abstract: ABSTRACT The use of temperature as a natural tracer in hydrology is noticed since the 1960s. In recent years, there has been a revival of the use of this physical property in the investigation of water cycle. The main reasons are the cost reduction of temperature measurements and the development of distributed temperature sensing. Here, we present a study of the groundwater-surface water interaction in the Onça Creek Watershed (Guarani Aquifer System outcrop) using stream discharge data and temperature as a natural tracer. Two Parshall flumes were installed 1.2 km apart to quantify stream discharge and determine groundwater contribution. We used an optic fiber cable to identify interaction locations and a probe with thermistors to measure the vertical temperature gradient and estimate flux rates. The results show a discharge difference of ~250 m3.h-1 between both flumes, which we interpret as baseflow contribution. The distributed temperature sensing allowed the identification of regions with gaining behavior. Discharge rates between 200 and 300 mm.day-1 were determined from vertical temperature measurements, which agrees with the streamflow data. The study demonstrated that temperature is attractive as natural tracer in tropical conditions, where the groundwater temperature is higher than the surface water temperature, especially during the winter.