Assessment, regionalization, and modeling rainfall erosivity over Brazil: Findings from a large national database.

In this study, we used a large national database to assess the rainfall erosivity (RE) patterns in time and space over the Brazilian territory. Thereby, RE and erosivity density (ED) values were obtained for 5166 rainfall gauges. Also, the concentration of the RE throughout the year and the RE's gravity center locations were analyzed. Finally, homogeneous regions regarding RE values were delimited and estimative regression models were established. The results show that Brazil's mean annual RE value is 5620 MJ mm ha-1 h-1 year-1, with considerable spatial variation over the country. The highest RE magnitudes were found for the north region, while the northeast region shows the lowest values. Regarding the RE's distribution throughout the year, in the southern region of Brazil, it is more equitable, while in some spots of the northeastern region, it is irregularly concentrated in specific months. Further analyses revealed that for most of the months, the RE's gravity centers for Brazil are in the Goiás State and that they present a north-south migration pattern throughout the year. Complementarily, the ED magnitudes allowed the identification of high-intensity rainfall spots. Additionally, the Brazilian territory was divided into eleven homogeneous regions regarding the RE patterns and for each defined region, a regression model was established and validated. These models' statistical metrics were considered satisfactory and, thus, can be used to estimate RE values for the whole country using monthly rainfall depths. Finally, all database produced are available for download. Therefore, the values and maps shown in this study are relevant for improving the accuracy of soil loss estimates in Brazil and for the establishment of soil and water conservation planning on a national scale.

Statistical process control in assessing water quality in the Doce river basin after the collapse of the Fundão dam (Mariana, Brazil).

The process of extracting information from data generated in environmental monitoring programs is often carried out using statistical tools, with Statistical Process Control (SPC) showing great potential for application in environmental monitoring. In November 2015, millions of cubic metres of tailings were dumped into the basin of the River Doce with the collapse of the Fundão dam. A study of the impact of this incident requires new approaches in data monitoring and processing, so it was sought to evaluate, using SPC tools, changes in water quality in the basin of the River Doce following the collapse of the dam. Using process charts and the process capability index (PCI), water quality parameters in the Doce and Carmo rivers were evaluated between 2009 and 2020. There, turbidity has improved since 2018, and Mn since 2016. Control charts showed that by December 2020 dissolved Fe was still not within normal pre-event fluctuation patterns. The PCI value showed that the situation worsened after the event for each of the parameters, with the lowest values for Mn and E. coli. By using a reference period, SPC makes it possible to infer the permanence of the impact of extreme pollution on the waterbody, which can be used in the routine monitoring of water quality in such events.

Water Footprint of soybean, cotton, and corn crops in the western region of Bahia State / Pegada Hídrica das culturas de soja, algodão e milho na região oeste do Estado da Bahia

ABSTRACT Water catchment to subsidize agricultural activities is estimated at 70% of world consumption. In the western region of Bahia, the main agricultural center of the state, there is intensive use of water for the production of agricultural commodities. In regions with high water demand, quantification of the use of this resource can be performed using anthropic pressure indicators, such as the Water Footprint. Thus, this work determined the Water Footprint of the soybean, cotton, and corn crops produced in the western region of Bahia State. In order to determine the Water Footprint, data of the environmental characteristics and crop production in the region were used, were obtained from different Brazilian public and private institutions. The calculation of Water Footprint of the crops was performed by the sum of the green, blue, and gray components. The average Water Footprint between 2012 and 2017 for soybean corresponded to 1,972.3 m3 t-1, with cotton at 1,825.2 m3 t-1, and corn 512.4 m3 t-1. The analyses of the results and the comparison with the values of the Water Footprint of other regions demonstrate that the edaphoclimatic conditions of the western region of Bahia are propitious to the development of these crops.

RESUMO A captação de água doce para subsidiar as atividades agrícolas é estimada em 70% do consumo mundial. Na região oeste da Bahia, maior polo agrícola do estado, verifica-se o uso intensivo de água para a produção de commodities agrícolas. Em regiões com elevada demanda de água, a quantificação do uso desse recurso pode ser realizada utilizando indicadores da pressão antrópica, como a Pegada Hídrica. Deste modo, este trabalho determinou as Pegadas Hídricas das culturas de soja, algodão e milho produzidas na região oeste do Estado da Bahia. A fim de se determinar a Pegada Hídrica foram utilizados dados das características ambientais e de produção das culturas na região, os quais foram obtidos de diferentes instituições públicas e privadas do país. O cálculo das Pegadas Hídricas das culturas foi realizado pela soma das componentes verde, azul e cinza. A Pegada Hídrica média entre 2012 e 2017 para a soja correspondeu a 1.972,3 m3 t-1, sendo a do algodão de 1.825,2 m3 t-1 e a do milho de 512,4 m3 t-1. Na análise dos resultados obtidos e na comparação com os valores de Pegada Hídrica de outras regiões, demonstrou-se que as condições edafoclimáticas da região oeste da Bahia são propícias ao desenvolvimento dessas culturas.

Effect of environmental covariable selection in the hydrological modeling using machine learning models to predict daily streamflow.

There are different methods for predicting streamflow, and, recently machine learning has been widely used for this purpose. This technique uses a wide set of covariables in the prediction process that must undergo a selection to increase the precision and stability of the models. Thus, this work aimed to analyze the effect of covariable selection with Recursive Feature Elimination (RFE) and Forward Feature Selection (FFS) in the performance of machine learning models to predict daily streamflow. The study was carried out in the Piranga river basin, located in the State of Minas Gerais, Brazil. The database consisted of an 18-year-old historical series (2000-2017) of streamflow data at the outlet of the basin and the covariables derived from the streamflow of affluent rivers, precipitation, land use and land cover, products from the MODIS sensors, and time. The highly correlated covariables were eliminated and the selection of covariables by the level of importance was carried out by the RFE and FFS methods for the Multivariate Adaptive Regression (EARTH), Multiple Linear Regression (MLR), and Random Forest (RF) models. The data were partitioned into two groups: 75% for training and 25% for validation. The models were run 50 times and had their performance evaluated by the Nash Sutcliffe efficiency coefficient (NSE), Determination coefficient (R2), and Root of Mean Square Error (RMSE). The three models tested showed satisfactory performance with both covariable selection methods, however, all of them proved to be inaccurate for predicting values associated with maximum streamflow events. The use of FFS, in most cases, improved the performance of the models and reduced the number of selected covariables. The use of machine learning to predict daily streamflow proved to be efficient and the use of FFS in the selection of covariables enhanced this efficiency.

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.

Environmental flow in the River Ondas basin in Bahia, Brazilian Cerrado.

This paper aimed to estimate the environmental flow of a water basin located in the Brazilian Cerrado using the bidimensional model River2D. The study was carried out in a stretch of the lower portion of the River Ondas in the western part of the state of Bahia, Brazil. To carry out the ecohydrological modeling, the following were used: topobathymetry, hydraulic characterization, the streamflows with the probability of non-exceedances (Q50, Q60, Q70, Q80, Q90, and Q95), and the Habitat Suitability Index for species of the genus Hypostomus. In the River2D, the weighted usable areas (WUAs) pertaining to the streamflows associated with different non-exceedances were simulated for the later construction of optimization and identification matrices of the streamflows that maximize the habitat area throughout the year. For juvenile Hypostomus, WUA increased as streamflow increased, with higher values associated with Q50. For adult specimens, lower WUA values were observed associated with Q50, while higher values were associated with Q95, which shows a preference for lower streamflows. The environmental flows found for the stretch of the River Ondas varied over the course of the year. The lowest environmental flows were observed in September (30.31 m(3) s(-1)) and October (29.98 m(3) s(-1)), while the highest were observed in February (44.22 m(3) s(-1)) and March (43.16 m(3) s(-1)). The environmental flow regime obtained restricts the water availability in the basin, for the purpose of water capture, which shows the importance of ecohydrological studies in forming a basis for water resource management actions.