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Mr. Andre Almagro
Federal University of Mato Grosso do Sul

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Research Keywords & Expertise

0 Machine Learning
0 soil erosion
0 Streamflow Modelling
0 Hydrology, Water Resources Management, Horological Modelling, Hydraulics, Surface Hydrology, Optimization, Water Distribution Network, Irrigation Engineering, Remote Sensing, Gis, Groundwater Quality, Groundwater Engineering, River Engineering, Runoff Mod
0 Climate Change and Environmental Management

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Preprint content
Published: 16 June 2021
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Similar to most countries, the Brazilian water resources management considers topographically delineated catchment as a territorial unit for policy implementation. Yet, previous studies have shown that catchments are not hydrologically isolated, and topographic limits often neglect the groundwater boundaries. Thus, studies on effective catchment area are promising for shedding light on inter-catchment groundwater flow. Here, we investigated the deviation between the topographic and effective areas across Brazil. We applied the Effective Catchment Area index (ECI) to 733 Brazilian catchments and identified the most influencing attributes on the ECI by using Principal Component and Random Forest Analyses (PCA and RFA, respectively). Further analysis of consistency was carried out by contrasting the ECI values against the expected range of the Budyko curve considering both topographic and effective catchment areas (classic and adjusted framework). Considering the studied catchments, 15% and 16% of their effective areas were respectively smaller than half (strong losing water condition) and larger than double (strong gaining water condition) of their corresponding topographic areas. The aridity index was the main driving factor and negatively correlated with ECI followed by mean slope, precipitation seasonality, and mean elevation. In general, the more arid biomes in Brazil — the Cerrado and Caatinga — are prone to have smaller effective areas while larger effective areas were mostly found in the Atlantic Forest biome, a humid tropical region with a higher mean elevation. We highlight the potential of adopting a pooling of catchments based on their interconnectivity to minimize management costs while maximizing synergies and lessening trade-offs of water transfer processes. Our results contribute to a better country-scale understanding of hydrological connectivity among catchments and highlight the need to consider the effective catchment area to overcome water-food-energy security challenges on multiple scales.

ACS Style

Dimaghi Schwamback; Gabriela Chiquito Gesualdo; Jullian Souza Sone; Alex Naoki Asato Kobayashi; Luis Eduardo Bertotto; Maria Vitória Da Silva Garcia; André Almagro; Paulo Tarso Sanches de Oliveira. Are Brazilian Catchments Gaining or Losing Water? The Effective Area of Tropical Catchments. 2021, 1 .

AMA Style

Dimaghi Schwamback, Gabriela Chiquito Gesualdo, Jullian Souza Sone, Alex Naoki Asato Kobayashi, Luis Eduardo Bertotto, Maria Vitória Da Silva Garcia, André Almagro, Paulo Tarso Sanches de Oliveira. Are Brazilian Catchments Gaining or Losing Water? The Effective Area of Tropical Catchments. . 2021; ():1.

Chicago/Turabian Style

Dimaghi Schwamback; Gabriela Chiquito Gesualdo; Jullian Souza Sone; Alex Naoki Asato Kobayashi; Luis Eduardo Bertotto; Maria Vitória Da Silva Garcia; André Almagro; Paulo Tarso Sanches de Oliveira. 2021. "Are Brazilian Catchments Gaining or Losing Water? The Effective Area of Tropical Catchments." , no. : 1.

Journal article
Published: 09 June 2021 in Hydrology and Earth System Sciences
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In this paper, we present the Catchments Attributes for Brazil (CABra), which is a large-sample dataset for Brazilian catchments that includes long-term data (30 years) for 735 catchments in eight main catchment attribute classes (climate, streamflow, groundwater, geology, soil, topography, land cover, and hydrologic disturbance). We have collected and synthesized data from multiple sources (ground stations, remote sensing, and gridded datasets). To prepare the dataset, we delineated all the catchments using the Multi-Error-Removed Improved-Terrain Digital Elevation Model (MERIT DEM) and the coordinates of the streamflow stations provided by the Brazilian Water Agency, where only the stations with 30 years (1980–2010) of data and less than 10 % of missing records were included. Catchment areas range from 9 to 4 800 000 km2, and the mean daily streamflow varies from 0.02 to 9 mm d−1. Several signatures and indices were calculated based on the climate and streamflow data. Additionally, our dataset includes boundary shapefiles, geographic coordinates, and drainage area for each catchment, aside from more than 100 attributes within the attribute classes. The collection and processing methods are discussed, along with the limitations for each of our multiple data sources. CABra intends to improve the hydrology-related data collection in Brazil and pave the way for a better understanding of different hydrologic drivers related to climate, landscape, and hydrology, which is particularly important in Brazil, having continental-scale river basins and widely heterogeneous landscape characteristics. In addition to benefitting catchment hydrology investigations, CABra will expand the exploration of novel hydrologic hypotheses and thereby advance our understanding of Brazilian catchments' behavior. The dataset is freely available at https://doi.org/10.5281/zenodo.4070146 and https://thecabradataset.shinyapps.io/CABra/ (last access: 7 June 2021).

ACS Style

André Almagro; Paulo Tarso S. Oliveira; Antônio Alves Meira Neto; Tirthankar Roy; Peter Troch. CABra: a novel large-sample dataset for Brazilian catchments. Hydrology and Earth System Sciences 2021, 25, 3105 -3135.

AMA Style

André Almagro, Paulo Tarso S. Oliveira, Antônio Alves Meira Neto, Tirthankar Roy, Peter Troch. CABra: a novel large-sample dataset for Brazilian catchments. Hydrology and Earth System Sciences. 2021; 25 (6):3105-3135.

Chicago/Turabian Style

André Almagro; Paulo Tarso S. Oliveira; Antônio Alves Meira Neto; Tirthankar Roy; Peter Troch. 2021. "CABra: a novel large-sample dataset for Brazilian catchments." Hydrology and Earth System Sciences 25, no. 6: 3105-3135.

Journal article
Published: 22 December 2020 in Water
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Water scarcity is a key challenge to global development. In Brazil, the Sao Francisco River Basin (SFB) has experienced water scarcity problems because of decreasing streamflow and increasing demands from multiple sectors. However, the drivers of decreased streamflow, particularly the potential role of the surface-groundwater interaction, have not yet been investigated. Here, we assess long-term trends in the streamflow and baseflow of the SFB during 1980–2015 and constrain the most likely drivers of observed decreases through a trend analysis of precipitation (P), evapotranspiration (ET), and terrestrial water storage change (TWS). We found that, on average, over 86% of the observed decrease in streamflow can be attributed to a significant decreasing baseflow trend along the SFR, with a spatial agreement between the decreased baseflow, increased ET, and irrigated agricultural land in the Middle SFB. We also noted a decreasing trend in TWS across the SFB exceeding –20 mm year−1. Overall, our findings indicate that decreasing groundwater contributions (i.e., baseflow) are providing the observed reduction in the total SFR flow. A lack of significant P trends and the strong TWS depletion indicate that a P variability only has likely not caused the observed baseflow reduction, in mainly the Middle and Sub-middle SFB. Therefore, groundwater and surface withdrawals may likely be a driver of baseflow reduction in some regions of the SFB.

ACS Style

Murilo Cesar Lucas; Natalya Kublik; Dulce B. B. Rodrigues; Antonio A. Meira Neto; André Almagro; Davi De C. D. Melo; Samuel C. Zipper; Paulo Tarso Sanches Oliveira. Significant Baseflow Reduction in the Sao Francisco River Basin. Water 2020, 13, 2 .

AMA Style

Murilo Cesar Lucas, Natalya Kublik, Dulce B. B. Rodrigues, Antonio A. Meira Neto, André Almagro, Davi De C. D. Melo, Samuel C. Zipper, Paulo Tarso Sanches Oliveira. Significant Baseflow Reduction in the Sao Francisco River Basin. Water. 2020; 13 (1):2.

Chicago/Turabian Style

Murilo Cesar Lucas; Natalya Kublik; Dulce B. B. Rodrigues; Antonio A. Meira Neto; André Almagro; Davi De C. D. Melo; Samuel C. Zipper; Paulo Tarso Sanches Oliveira. 2020. "Significant Baseflow Reduction in the Sao Francisco River Basin." Water 13, no. 1: 2.

Preprint content
Published: 14 October 2020
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In this paper, we present the Catchments Attributes for Brazil (CABra), which is a large-sample dataset for Brazilian catchments that includes long-term data (30 years) for 735 catchments in eight main catchment attribute classes (climate, streamflow, groundwater, geology, soil, topography, land-cover, and hydrologic disturbance). We have collected and synthesized data from multiple sources (ground stations, remote sensing, and gridded datasets). To prepare the dataset, we delineated all the catchments using the Multi-Error-Removed Improved-Terrain Digital Elevation Model and the coordinates of the streamflow stations provided by the Brazilian Water Agency, where only the stations with 30 years (1980–2010) of data and less than 10 % of missing records were included. Catchment areas range from 9 to 4 800 000 km2 and the mean daily streamflow varies from 0.02 to 9 mm d-1. Several signatures and indices were calculated based on the climate and streamflow data. Additionally, our dataset includes boundary shapefiles, geographic coordinates, and drainage area for each catchment, aside from more than 100 attributes within the attribute classes. The collection and processing methods are discussed along with the limitations for each of our multiple data sources. The CABra intends to improve the hydrology-related data collection in Brazil and pave the way for a better understanding of different hydrologic drivers related to climate, landscape, and hydrology, which is particularly important in Brazil, having continental-scale river basins and widely heterogeneous landscape characteristics. In addition to benefitting catchment hydrology investigations, CABra will expand the exploration of novel hydrologic hypotheses and thereby advance our understanding of Brazilian catchments' behavior. The dataset is freely available at https://doi.org/10.5281/zenodo.4070147.

ACS Style

André Almagro; Paulo Tarso S. Oliveira; Antônio Alves Meira Neto; Tirthankar Roy; Peter Troch. CABra: a novel large-sample dataset for Brazilian catchments. 2020, 2020, 1 -40.

AMA Style

André Almagro, Paulo Tarso S. Oliveira, Antônio Alves Meira Neto, Tirthankar Roy, Peter Troch. CABra: a novel large-sample dataset for Brazilian catchments. . 2020; 2020 ():1-40.

Chicago/Turabian Style

André Almagro; Paulo Tarso S. Oliveira; Antônio Alves Meira Neto; Tirthankar Roy; Peter Troch. 2020. "CABra: a novel large-sample dataset for Brazilian catchments." 2020, no. : 1-40.

Preprint
Published: 17 September 2020
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Water scarcity is a key challenge to global development. In Brazil, the Sao Francisco River Basin (SFB) has experienced water scarcity problems because of decreasing streamflow and increasing demands from multiple sectors. However, the drivers of decreased streamflow, particularly the potential role of surface-groundwater interaction, have not been yet investigated. Here, we assess long-term trends in baseflow, quickflow, and streamflow of the SFB during 1980–2015 and constrain the most likely drivers of observed decreases through trend analysis of precipitation (P), evapotranspiration (ET), and terrestrial water storage change (TWS). We found that over 82% of the observed decrease in streamflow can be attributed to a significant decreasing baseflow trend (< -20 m3 s-1 y-1) along the SFR with spatial agreement between decreased baseflow, increased ET, and irrigated agricultural land. We also noted a decrease in TWS across the SFB with trends exceeding -20 mm y-1. Overall, our findings indicate that decreasing groundwater contributions (i.e., baseflow) is providing the observed reduction in total SFR flow. A lack of significant P trends indicates that only P variability likely has not caused the observed baseflow reduction, mainly in the Middle and Sub-middle SFB. Therefore, groundwater and surface withdrawals may be likely a driver of water scarcity over the SFB.

ACS Style

Murilo Cesar Lucas; Natalya Kublik; Dulce B. B. Rodrigues; Antonio A. Meira Neto; André Almagro; Davi De C. D. Melo; Samuel C. Zipper; Paulo Tarso Sanches Oliveira. Significant baseflow reduction in the Sao Francisco River Basin. 2020, 1 .

AMA Style

Murilo Cesar Lucas, Natalya Kublik, Dulce B. B. Rodrigues, Antonio A. Meira Neto, André Almagro, Davi De C. D. Melo, Samuel C. Zipper, Paulo Tarso Sanches Oliveira. Significant baseflow reduction in the Sao Francisco River Basin. . 2020; ():1.

Chicago/Turabian Style

Murilo Cesar Lucas; Natalya Kublik; Dulce B. B. Rodrigues; Antonio A. Meira Neto; André Almagro; Davi De C. D. Melo; Samuel C. Zipper; Paulo Tarso Sanches Oliveira. 2020. "Significant baseflow reduction in the Sao Francisco River Basin." , no. : 1.

Journal article
Published: 20 May 2020 in Atmospheric Research
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Climate change effects can have significant impacts worldwide. Extreme events can modify water availability and agricultural production, making climate change planning an essential task. The National Institute for Space Research (INPE in Portuguese) in Brazil has made a large dataset of regional climate model outputs (simulations and projections) available, which opens up many possibilities of carrying out high-resolution climate change studies. However, there is still no performance evaluation of the model-derived rainfall output against high-resolution ground-based observation data considering the Brazilian biomes. This paper attempts to fill this gap and evaluates the simulated precipitation throughout Brazil. We used gridded observed precipitation data and historical climate simulations from the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) and from the Hadley Center Global Environment Model, version 2 (HadGEM2-ES), which were downscaled by the Eta RCM (Regional Climate Model). For the overlapping period (1980–2005), there is good agreement (PBIAS up to 10%) of downscaled annual simulations for the Amazon and Cerrado biomes and large biases (reaching 40%) in the Pampa biome, compared to the observations. Our results showed that HadGEM2-ES is capable of representing long-term mean monthly precipitation for large areas well, such as the Amazon and Cerrado. Furthermore, the Eta RCM has considerably improved the driving GCM MIROC5 simulations. In conclusion, we recommend using the HadGEM2-ES simulations for the Amazon, Eta/HadGEM2-ES for the Atlantic Forest, Cerrado, and Pampa, and Eta/MIROC5 for the Caatinga and Pantanal. Our study provides an overview of two downscaled simulation datasets in Brazil that may help verify the models' suitability for further climate change assessments.

ACS Style

André Almagro; Paulo Tarso S. Oliveira; Rafael Rosolem; Stefan Hagemann; Carlos A. Nobre. Performance evaluation of Eta/HadGEM2-ES and Eta/MIROC5 precipitation simulations over Brazil. Atmospheric Research 2020, 244, 105053 .

AMA Style

André Almagro, Paulo Tarso S. Oliveira, Rafael Rosolem, Stefan Hagemann, Carlos A. Nobre. Performance evaluation of Eta/HadGEM2-ES and Eta/MIROC5 precipitation simulations over Brazil. Atmospheric Research. 2020; 244 ():105053.

Chicago/Turabian Style

André Almagro; Paulo Tarso S. Oliveira; Rafael Rosolem; Stefan Hagemann; Carlos A. Nobre. 2020. "Performance evaluation of Eta/HadGEM2-ES and Eta/MIROC5 precipitation simulations over Brazil." Atmospheric Research 244, no. : 105053.

Journal article
Published: 10 December 2019 in Sustainability
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The Pantanal biome integrates the lowlands of the Upper Paraguay Basin (UPB), which is hydrologically connected to the biomes of the Cerrado and Amazon (the highlands of the UPB). The effects of recent land-cover and land-use (LCLU) changes in the highlands, combined with climate change, are still poorly understood in this region. Here, we investigate the effects of soil erosion in the Brazilian Pantanal under climate and LCLU changes by combining different scenarios of projected rainfall erosivity and land-cover management. We compute the average annual soil erosion for the baseline (2012) and projected scenarios for 2020, 2035, and 2050. For the worst scenario, we noted an increase in soil loss of up to 100% from 2012 to 2050, associated with cropland expansion in some parts of the highlands. Furthermore, for the same period, our results indicated an increase of 20 to 40% in soil loss in parts of the Pantanal biome, which was associated with farmland increase (mainly for livestock) in the lowlands. Therefore, to ensure water, food, energy, and ecosystem service security over the next decades in the whole UPB, robust and comprehensive planning measures need to be developed, especially for the most impacted areas found in our study.

ACS Style

Carina Colman; Paulo Oliveira; André Almagro; Britaldo Soares-Filho; Dulce Rodrigues. Effects of Climate and Land-Cover Changes on Soil Erosion in Brazilian Pantanal. Sustainability 2019, 11, 7053 .

AMA Style

Carina Colman, Paulo Oliveira, André Almagro, Britaldo Soares-Filho, Dulce Rodrigues. Effects of Climate and Land-Cover Changes on Soil Erosion in Brazilian Pantanal. Sustainability. 2019; 11 (24):7053.

Chicago/Turabian Style

Carina Colman; Paulo Oliveira; André Almagro; Britaldo Soares-Filho; Dulce Rodrigues. 2019. "Effects of Climate and Land-Cover Changes on Soil Erosion in Brazilian Pantanal." Sustainability 11, no. 24: 7053.

Journal article
Published: 20 August 2019 in International Soil and Water Conservation Research
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The Revised Universal Soil Loss Equation (RUSLE)'s cover and management factor (C-factor) is one of the most difficult factors to obtain, mainly because long-term monitoring soil erosion plots under natural rainfall are needed. Therefore, remote sensing approaches have been used as an alternative for obtaining this factor. However, there is a lack of studies comparing values of this factor computed from remote sensing approaches with measured data. In this study, we compare two widely used remote sensing approaches (CrA and CVK) to estimate the C-factor based on the Normalized Difference Vegetation Index (NDVI) with the literature (CLIT) and field experimental data. We also investigated the influence of C-factor methods on the prediction of soil loss and sediment yield (SY) using measured data in the Guariroba basin, Central-West Brazil. We obtained mean C-factor values of 0.032, 0.023 and 0.137 for CLIT, CrA and CVK, respectively. We found an average annual soil loss of 2.20 t ha−1 yr−1, 2.02 t ha−1 yr−1 and 10.07 t ha−1 yr−1 and SY values of 6875 t yr−1, 6468 t yr−1 and 33,435 t yr1, for CLIT, CrA and CVK, respectively. Our results indicated a significant improvement in soil loss and SY estimations by using the CrA approach developed for tropical regions, with a bias of 13% to the measured SY (5709 t yr−1). We conclude that the CrA method present the most suitable alternative to compute soil loss and SY in tropical regions. Furthermore, this approach allows large-scale evaluation and temporal monitoring, therefore enhancing multi spatial and temporal assessment of soil erosion processes.

ACS Style

André Almagro; Thais Caregnatto Thomé; Carina Barbosa Colman; Rodrigo Bahia Pereira; José Marcato Junior; Dulce Buchala Bicca Rodrigues; Paulo Tarso Sanches Oliveira. Improving cover and management factor (C-factor) estimation using remote sensing approaches for tropical regions. International Soil and Water Conservation Research 2019, 7, 325 -334.

AMA Style

André Almagro, Thais Caregnatto Thomé, Carina Barbosa Colman, Rodrigo Bahia Pereira, José Marcato Junior, Dulce Buchala Bicca Rodrigues, Paulo Tarso Sanches Oliveira. Improving cover and management factor (C-factor) estimation using remote sensing approaches for tropical regions. International Soil and Water Conservation Research. 2019; 7 (4):325-334.

Chicago/Turabian Style

André Almagro; Thais Caregnatto Thomé; Carina Barbosa Colman; Rodrigo Bahia Pereira; José Marcato Junior; Dulce Buchala Bicca Rodrigues; Paulo Tarso Sanches Oliveira. 2019. "Improving cover and management factor (C-factor) estimation using remote sensing approaches for tropical regions." International Soil and Water Conservation Research 7, no. 4: 325-334.

Journal article
Published: 15 August 2017 in Scientific Reports
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The impacts of climate change on soil erosion may bring serious economic, social and environmental problems. However, few studies have investigated these impacts on continental scales. Here we assessed the influence of climate change on rainfall erosivity across Brazil. We used observed rainfall data and downscaled climate model output based on Hadley Center Global Environment Model version 2 (HadGEM2-ES) and Model for Interdisciplinary Research On Climate version 5 (MIROC5), forced by Representative Concentration Pathway 4.5 and 8.5, to estimate and map rainfall erosivity and its projected changes across Brazil. We estimated mean values of 10,437 mm ha−1 h−1 year−1 for observed data (1980–2013) and 10,089 MJ mm ha−1 h−1 year−1 and 10,585 MJ mm ha−1 h−1 year−1 for HadGEM2-ES and MIROC5, respectively (1961–2005). Our analysis suggests that the most affected regions, with projected rainfall erosivity increases ranging up to 109% in the period 2007–2040, are northeastern and southern Brazil. Future decreases of as much as −71% in the 2071–2099 period were estimated for the southeastern, central and northwestern parts of the country. Our results provide an overview of rainfall erosivity in Brazil that may be useful for planning soil and water conservation, and for promoting water and food security.

ACS Style

André Almagro; Paulo Tarso Oliveira; Mark A. Nearing; Stefan Hagemann. Projected climate change impacts in rainfall erosivity over Brazil. Scientific Reports 2017, 7, 1 -12.

AMA Style

André Almagro, Paulo Tarso Oliveira, Mark A. Nearing, Stefan Hagemann. Projected climate change impacts in rainfall erosivity over Brazil. Scientific Reports. 2017; 7 (1):1-12.

Chicago/Turabian Style

André Almagro; Paulo Tarso Oliveira; Mark A. Nearing; Stefan Hagemann. 2017. "Projected climate change impacts in rainfall erosivity over Brazil." Scientific Reports 7, no. 1: 1-12.