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The occurrence of hydrological extremes in the Amazon region and the associated sediment loss during rainfall events are key features in the global climate system. Climate extremes alter the sediment and carbon balance but the ecological consequences of such changes are poorly understood in this region. With the aim of examining the interactions between precipitation and landscape-scale controls of sediment export from the Amazon basin, we developed a parsimonious hydro-climatological model on a multi-year series (1997&ndash, 2014) of sediment discharge data taken at the outlet of &Oacute, bidos (Brazil) watershed (the narrowest and swiftest part of the Amazon River). The calibrated model (correlation coefficient equal to 0.84) captured the sediment load variability of an independent dataset from a different watershed (the Magdalena River basin), and performed better than three alternative approaches. Our model captured the interdecadal variability and the long-term patterns of sediment export. In our reconstruction of yearly sediment discharge over 1859&ndash, 2014, we observed that landscape erosion changes are mostly induced by single storm events, and result from coupled effects of droughts and storms over long time scales. By quantifying temporal variations in the sediment produced by weathering, this analysis enables a new understanding of the linkage between climate forcing and river response, which drives sediment dynamics in the Amazon basin.

INTRODUCTION: Malaria is an infectious disease of high transmission in the Amazon region, but its dynamics and spatial distribution may vary depending on the interaction of environmental, socio-cultural, economic, political and health services factors. OBJECTIVE: To verify the existence of malaria case patterns in consonance with the fluviometric regimes in Amazon basin. METHOD: Methods of descriptive and inferential statistics were used in malaria and water level data for 35 municipalities in the Amazonas State, in the period from 2003 to 2014. RESULTS: The existence of a tendency to modulate the seasonality of malaria cases due to distinct periods of rivers flooding has been demonstrated. Differences were observed in the annual hydrological variability accompanied by different patterns of malaria cases, showing a trend of remodeling of the epidemiological profile as a function of the flood pulse. CONCLUSION: The study suggests the implementation of regional and local strategies considering the hydrological regimes of the Amazon basin, enabling municipal actions to attenuate the malaria in the Amazonas State.INTRODUçÃO: A malária é uma doença infecciosa de alta transmissão na região amazônica, porém sua dinâmica e distribuição espacial podem variar, dependendo da interação de fatores ambientais, socioculturais, econômicos e políticos e serviços de saúde. OBJETIVO: Verificar a existência de padrões de casos de malária em consonância com os regimes fluviométricos da bacia amazônica. MÉTODOS: Foram utilizados métodos de estatística descritiva e inferencial nos dados de casos de malária e nível d’água para 35 municípios do estado do Amazonas, no período de 2003 a 2014. RESULTADOS: A existência de uma tendência que module a sazonalidade dos casos de malária, devido a períodos distintos de inundação dos rios, foi demonstrada. Diferenças foram observadas na variabilidade hidrológica anual, acompanhada por diferentes padrões de casos de malária, mostrando uma tendência de remodelação do perfil epidemiológico em função do pulso de inundação. CONCLUSÃO: O estudo sugere a implementação de estratégias regionais e locais, considerando os regimes hidrológicos da Bacia Amazônica, possibilitando ações municipais de atenuação da malária no estado do Amazonas.

Understanding the relations between rainfall and river water levels and malaria cases can provide important clues on modulation of the disease in the context of local climatic variability. In order to demonstrate how these relations can vary in the same endemic space, a coherence and wavelet phase analysis was performed between environmental and epidemiological variables from 2003 to 2010 for 8 municipalities (counties) in the state of Amazonas, Brazil (Barcelos, Borba, Canutama, Carauari, Coari, Eirunepé, Humaitá, and São Gabriel da Cachoeira). The results suggest significant coherences, mainly on the scale of annual variability, but scales of less than 1 year and of 2 years were also found. The analyses show that malaria cases display a peak at approximately 1 and a half months before or after peak rainfall and on average 1-4 months after peak river water levels in most of the municipalities studied. Each environmental variable displayed distinct local behavior in time and in space, suggesting that other local variables (e.g. topography) may control environmental conditions, favoring different patterns in each municipality. However, when the analyses were performed jointly it was possible to show a non-random order in these relations. Although environmental and climatic factors indicate a certain influence on malaria dynamics, surveillance, prevention, and control issues should not be overlooked, meaning that government public health interventions can mask possible relations with local hydrological and climatic conditions. © 2019, Fundacao Oswaldo Cruz. All rights reserved.

Large hydrological systems aggregate compositionally different waters derived from a variety of pathways. In the case of continental‐scale rivers, such aggregation occurs noticeably at confluences between tributaries. Here we explore how such aggregation can affect solute concentration‐discharge (C‐Q) relationships and thus obscure the message carried by these relationships in terms of weathering properties of the Critical Zone. We build up a simple model for tributary mixing to predict the behavior of C‐Q relationships during aggregation. We test a set of predictions made in the context of the largest world's river, the Amazon. In particular, we predict that the C‐Q relationships of the rivers draining heterogeneous catchments should be the most “dilutional” and should display the widest hysteresis loops. To check these predictions, we compute 10 day‐periodicity time series of Q and major solute (Si, Ca²⁺, Mg²⁺, K⁺, Na⁺, Cl‐, urn:x-wiley:00431397:media:wrcr22891:wrcr22891-math-0001) C and fluxes (F) for 13 gauging stations located throughout the Amazon basin. In agreement with the model predictions, C‐Q relationships of most solutes shift from a fairly “chemostatic” behavior (nearly constant C) at the Andean mountain front and in pure lowland areas, to more “dilutional” patterns (negative C‐Q relationship) toward the system mouth. More prominent C‐Q hysteresis loops are also observed at the most downstream stations. Altogether, this study suggests that mixing of water and solutes between different flowpaths exerts a strong control on C‐Q relationships of large‐scale hydrological systems. Por pares

The Epidemiological Surveillance System for Malaria (SIVEP-Malaria) is the Brazilian governmental program that registers all information about compulsory reporting of detected cases of malaria by all medical units and medical practitioners. The objective of this study is to point out the main sources of errors in the SIVEP-Malaria database by applying a data cleaning method to assist researchers about the best way to use it and to report the problems to authorities. The aim of this study was to assess the quality of the data collected by the surveillance system and its accuracy. The SIVEP-Malaria data base used was for the state of Amazonas, Brazil, with data collected from 2003 to 2014. A data cleaning method was applied to the database to detect and remove erroneous records. It was observed that the collecting procedure of the database is not homogeneous among the municipalities and over the years. Some of the variables had different data collection periods, missing data, outliers and inconsistencies. Variables depending on the health agents showed a good quality but those that rely on patients were often inaccurate. We showed that a punctilious preprocessing is needed to produce statistically correct data from the SIVEP-Malaria data base. Fine spatial scale and multi-temporal analysis are of particular concern due to the local concentration of uncertainties and the data collecting seasonality observed. This assessment should help to enhance the quality of studies and the monitoring of the use of the SIVEP database. RESUMO O Sistema de Vigilância Epidemiológica de Malária (SIVEP-Malária) é um programa governamental brasileiro que arquiva automaticamente todas as informações sobre casos de malária registrados em todas as unidades de saúde e consultórios medicos. O objetivo deste estudo foi avaliar a qualidade dos dados coletados pelo sistema de vigilância e sua precisão. Foram utilizados os dados do SIVEP-Malária para o estado do Amazonas, Brasil, de 2003 a 2014. Um método de limpeza de dados foi aplicado para detectar e remover registros errôneos. Observamos que a coleta de dados não é homogênea entre os municipios e ao longo dos anos. Algumas variaveis tinham diferentes padrões de coleta, falta de dados, dados discrepantes e inconsistências. Dados que dependem do agente de saúde possuem boa qualidade mas aqueles que dependem dos pacientes são frequentemente imprecisos. Mostramos que um pre-processamento meticuloso é necessário para produzir dados estatisticamente corretos a partir do SIVEP-Malária. Analises em escala espacial detalhada ou multi-temporais são particularmente afetadas devido à concentração local de incertezas e a sazonalidade observada na coleta de dados. Esta avaliação deve auxiliar a melhorar os estudos e monitoramentos que fazem uso dos dados do SIVEP.