Nowcast flood predictions in the Amazon watershed based on the remotely sensed rainfall product PDIRnow and artificial neural networks.

The aim of this study was to develop artificial neural network (ANN) models to predict floods in the Branco River, Amazon basin. The input data for the models included the river levels and the average rainfall within the drainage area of the basin, which was estimated from the remotely sensed rainfall product PDIRnow. The hourly water level data used in the study were recorded by fluviometric telemetric stations belonging to the National Agency of Water. The multilayer perceptron was used as the neural framework of the ANNs, and the number of neurons in each layer of the model was determined via optimization with the SCE-UA algorithm. Most of the fitted ANN models showed Nash-Sutcliffe efficiency index values greater than 0.9. It is possible to conclude that the ANNs are effective for predicting the flood levels of the Branco River, with horizons of 6, 12 and 24 h; thus, constituting a viable option for use in river-flood warning systems in the Amazon basin. For the forecast with a 24-h horizon, it is essential to include the average rainfall of the basin that accumulated over the last 48 h as input data into the ANNs, along with the levels measured by the streamflow stations. The indirect rainfall estimates provided by PDIRnow are an excellent alternative as input data for ANN models used to predict floods and constitute a viable solution for regions where the density of rain gauge stations is low, as is the case in the Amazon basin.

Environmental vulnerability assessment of the Doce River basin, southeastern Brazil.

Environmental vulnerability is an important tool to understand the natural and anthropogenic impacts associated with the susceptibility to environmental damage. This study aims to assess the environmental vulnerability of the Doce River basin in Brazil through Multicriteria Decision Analysis based on Geographic Information Systems (GIS-MCDA). Natural factors (slope, elevation, relief dissection, rainfall, pedology, and geology) and anthropogenic factors (distance from urban centers, roads, mining dams, and land use) were used to determine the environmental vulnerability index (EVI). The EVI was classified into five classes, identifying associated land uses. Vulnerability was verified in water resource management units (UGRHs) and municipalities using hot spot analysis. The study employed the water quality index (WQI) to assess the EVI and global sensitivity analysis (GSA) to evaluate the model input parameters that most influence the basin's environmental vulnerability. The results showed that the regions near the middle Doce River were considered environmentally more vulnerable, especially the UGRHs Guandu, Manhuaçu, and Caratinga; and 35.9% of the basin has high and very high vulnerabilities. Hot spot analysis identified regions with low EVI values (cold spot) in the north and northwest, while areas with high values (hot spot) were concentrated mainly in the middle Doce region. Water monitoring stations with the worst WQI values were found in the most environmentally vulnerable areas. The GSA determined that land use and slope were the primary factors influencing the model's response. The results of this study provide valuable information for supporting environmental planning in the Doce River basin.

Modeling of surface sediment concentration in the Doce River basin using satellite remote sensing.

Surface sediment concentration (SSC) is linked to several problems related to water quality and its monitoring is costly because of the required fieldwork and laboratory analyses. Thus, sediment measurements are often sporadic, punctual, and performed during a short period. Orbital remote sensing allows the monitoring of SSC along the river channel permitting continuous and spatial information. This work had two objectives: (1) to model the surface concentration of sediments in the main channel of the Doce river using data from Multispectral Instrument (MSI)/Sentinel 2 and Operational Land Imager (OLI)/Landsat 8 satellite sensors; and (2) to compare different linear modeling approaches to select the best variables for SSC monitoring. For comparison with actual field data, we used mean SSC measurements in 14 sediment gauge stations from 2013 to 2020. Reflectance data of the MSI/Sentinel 2 and OLI/Landsat 8 satellites bands and spectral indices related to the monitoring of water resources were used as explanatory variables. Simple and multiple linear regression models (SLR and MLR), least absolute shrinkage and selection operator (LASSO), and Elastic Net regression were used to predict the SSC. The near-infrared band images from both MSI/Sentinel 2 and OLI/Landsat 8 satellites showed a strong linear relationship with the SSC. Multiple linear regression, LASSO and Elastic Net regressions showed good performance for SSC prediction. Sediment flow maps show an SSC reduction in the Doce river channel in recent years, indicating that part of the material from the Fundão tailings dam rupture may have been transported through sediment resuspension and transport processes.

Sistema para análise das outorgas de captação de água e diluição de efluentes na bacia do rio Piracicaba (MG) / System for analysis of water abstraction and effluent dilution in Piracicaba river basin, Minas Gerais State, Brazil

RESUMO A outorga de direito de uso da água é um dos principais instrumentos de gestão para controle quantitativo e qualitativo dos recursos hídricos. Para sua implantação, é necessário, entre outras ações, definir critérios e desenvolver ferramentas para análise integrada dos aspectos quantitativos e qualitativos da água. Dessa forma, o objetivo do estudo foi desenvolver um sistema para análise das outorgas de captação de água e diluição de efluentes aplicado à bacia hidrográfica do rio Piracicaba (MG). Inicialmente, foram realizados o levantamento e a preparação da base de dados geográfica, hidrológica e administrativa. O sistema foi desenvolvido utilizando tecnologias open source, sendo estruturado em três camadas: de dados, de negócios e de apresentação. De acordo com os resultados, constatou-se que os trechos mais críticos quanto à vazão passível de outorga localizam-se na foz e na cabeceira do rio Piracicaba. A análise dos dados permitiu concluir que o sistema determina, de forma consistente, a disponibilidade hídrica outorgável ao longo da hidrografia e as vazões de diluição e indisponível pelos lançamentos, além de identificar trechos dos cursos d'água com disponibilidade hídrica crítica, fornecendo subsídios para análises das outorgas quali-quantitativas dos recursos hídricos na bacia.

ABSTRACT The granting of water use rights is one of the main management instruments for the quantitative and qualitative control of water resources. For its implementation, it is necessary, among other actions, to develop tools for integrated analysis of the quantitative and qualitative aspects of water. Thus, the objective of the study was to create a system for the analysis of water abstraction and effluent dilution in the Piracicaba river basin in Minas Gerais. Initially, the survey and preparation of the geographic, hydrological and administrative database were carried out. The system was developed using open-source technologies, with a three-layer structure: data, business, and presentation. According to the results, it was verified that the most critical sections regarding the grantable flow available are located at the mouth and spring of the Piracicaba river. The analysis of the data allowed us to conclude that the system consistently determines the availability of water throughout the hydrography, the dilution flow and discharge unavailability, and identifies stretches of the watercourses with critical water availability, providing support for analyses of the quali-quantitative granting of water resources in the basin.