The Santa Barbara post-wildfire debris flows and the Brumadinho tailing-dam failure were two of the most catastrophic flood events of the late 2010s. Both these events carried so much solid-phase material, that classic, clear-water, flood risk approaches cannot replicate them, or forecast other events like them. This case study applied the new non-Newtonian features in HEC-RAS 6.1 to these two events, testing the most widely used flood risk model on the two most common mud and debris flow hazards (post-wildfire floods and mine tailing dam failures). HEC-RAS reproduced the inundation boundaries and the event timing (where available) for both events. The ratio between the largest debris flow clasts and the channel size, parametric trade-offs, the “convex” alluvial plain topography, and the stochasticity introduced by urban infrastructure made the Santa Barbara modeling more difficult and less precise than Brumadinho. Despite these challenges, the results provide prototype scale validation and verification of these new tools in this widely applied flood risk model.

The understanding of the atmospheric phase of the hydrological cycle is an important step forward in improving our abilities to predict droughts and floods, as well as the impacts of climate change on water resources. Here we focus on the study of the atmospheric moisture transport to the Upper Paraná River basin, Brazil, through the hybrid single‐particle Lagrangian integrated trajectory (HYSPLIT) dispersion model, which is used to generate air masses trajectories based on the 1970–2010 National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data. In terms of moisture source regions, we found that the tropical South Atlantic is the main contributor to the Upper Paraná River basin, exporting about 175 mm/month of water vapour during the rainy season. The North Atlantic contribution is relevant in February (about 38 mm/month). Other regions over the Atlantic Ocean (North and subtropical South) are also identified as sources, and moisture evaporated from these places has a significant impact on the streamflow variability at the Itaipu streamflow gauge, located at the basin outlet. The continental sources play a more relevant role during the dry season (May–October). The Amazon region is more relevant as a moisture source during the dry season, exporting an average of 45 mm/month. A similar pattern is observed in other continental sources, such as Chaco/Pantanal/Cerrado, which together export about 99 mm/month to the Paraná River basin during the dry season. An extreme event analysis reveals that changes in moisture advection from the tropical South Atlantic are related to floods and droughts in the region. Particularly, we observe that flood events are preceded by positive anomalies of moisture advection up to 2 months in advance, while persistent, negative anomalies of moisture transport lead seasonal droughts by up to 8 months beforehand.

Este trabalho teve como objetivo fazer uma análise comparativa entre Modelos Digitais de Elevação (MDE) de abrangência global ou nacional, disponíveis gratuitamente na web: ASTER-GDEM, SRTM 4, TOPODATA, HydroSHEDS e um Modelo oriundo de interpolação de mapeamento na escala de 1:10000. Esta análise foi realizada para duas bacias hidrográficas com características de relevo diferentes: a bacia do Rio Paranoá, que possui relevo suave e densidade de drenagem baixa e a do Rio São Bartolomeu, que apresenta relevo movimentado, com alta densidade de drenagem. O método consiste no uso do Padrão de Exatidão Cartográfica dos Produtos Cartográficos Digitais - PEC-PCD, descrito na versão 2.1.3 da Especificação Técnica para a Aquisição de Dados Geoespaciais Vetoriais (ET-ADGV) e teste estatístico do parâmetro t de Student. Na bacia do Paranoá os MDEs TOPODATA, SRTM e HydroSHEDS dem enquadraram-se na escala 1:50000 classe B, enquanto o ASTER e o HydroSHEDS con enquadraram-se na escala 1:100000 classe B. Apenas os MDEs SRTM e HydroSHEDS dem não apresentaram tendências sistemáticas. Na bacia do São Bartolomeu os MDEs TOPODATA, SRTM e ASTER atenderam à escala 1:100000 classe B, enquanto o HydroSHEDS dem atendeu a 1:100000 classe D e o HydroSHEDS con a 1:250000 classe B. Apenas o MDE ASTER não apresentou tendências sistemáticas.

This paper has the goal of evaluating monotonic trends in the Xingu and\ud Tapajós river basins in the Austral Amazon region, Brazil.\ud Non-parametric statistical tests such as Mann–Kendall, Bootstrap\ud Mann–Kendall, Sen and Bootstrap Sen are applied on streamflow gauging\ud stations data, to determine the significance and magnitude of possible\ud trends. Data in these river basins is relatively scarce, with time series\ud ranging from twenty to forty years, having many gaps. Former studies\ud indicate a decreasing trend for both annual average and minimum streamflow\ud values in the Tapajós river basin, with 99% confidence level, and a\ud decrease in maximum values in the Xingu river basin, with 90% confidence\ud level. However, past analyses have only used one station near the basin\ud outlet. This study uses data from 7 gauging stations in the Xingu basin and\ud 14 stations in the Tapajós basin. Results indicate opposite trends at\ud the 95% confidence level for different regions in the basins, and for\ud different flow regimes. For the Xingu river basin, trends in the minimum\ud flow for different sub-basins even out at the Altamira station, near its\ud outlet. For the Tapajós river, the southeastern part of the basin has\ud increasing trends, while the southwestern part decreases. At the Itaituba\ud station, they also balance out