Social networks, like Twitter and Facebook, are valuable sources to monitor real-time events, such as earthquakes and epidemics. For this type of surveillance the user's location is an essential piece of information, but a substantial number of users choose not to disclose their geographical information. However, characteristics of the users' behavior, such as the friends they associate with and the types of messages published may hint on their spatial location. In this paper, we present a method to infer the spatial location of Twitter users. Unlike the approaches proposed so far, we incorporate two sources of information to learn the geographical position: the text posted by users and their friendship network. We propose a probabilistic approach that jointly models the geographical labels and the Twitter texts of the users organized in the form of a graph representing the friendship network. We use the Markov random field probability model to represent the network and learning is carried out through a Markov chain Monte Carlo simulation technique to approximate the posterior probability distribution of the missing geographical labels. We demonstrate the utility of this model in a large dataset of Twitter users, where the ground truth is the location given by the GPS position, GeoIP location or declared location. The method is evaluated and compared to two baseline algorithms that employ either of these two types of information. The accuracy rates achieved are significantly better than those of the baseline methods.

A precipitação é um parâmetro muito importante em estudos hidrológicos para a modelagem matemática e computacional para o dimensionamento das precipitações de projeto em obras de engenharia. Apesar desta importância, não são todas as regiões que dispõem de rede de monitoramento para registros pluviográficos e quando existente, em muitos casos, apresentam séries de dados inconsistentes. Para a caracterização de um evento pluviométrico é necessário conhecer a sua duração, intensidade e frequência (curva Intensidade-Duração-Frequência – IDF). Neste artigo foi proposto o estabelecimento da relação IDF, a partir da desagregação de dados diários de chuva, e ajustadas por meio do método paramétrico de ajustamento de observações, que é geralmente empregado em ajustes geodésicos, e se baseia no método dos mínimos quadrados. Os erros médios quadráticos entre os valores de intensidade ajustadas e observadas para o local de estudo foram relativamente baixos demonstrando a qualidade dos ajustamentos realizados. O método paramétrico de ajustamento se mostrou adequado para as simulações realizadas, além de facilitar a obtenção de parâmetros ajustados para as curvas IDF. Com base nos resultados obtidos, acredita-se também que esta metodologia pode ser empregada em outros locais.

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Purpose Finer sediment particles (silt and clay) transported by rivers carry the major part of nutrient loads by absorption; thus, sediment settling can remove nutrients from the water column. The purpose of this paper is to analyze the relation between reservoir sedimentation and water quality by assessing the reservoir sedimentation process and the sediments’ characteristics. Design/methodology/approach Bathymetric surveys from 2004 to 2014 were analyzed to assess the sedimentation process. Core samples provided information on a layer-by-layer basis of the sediment deposits, and water samples near the surface and near the bottom provided information on sediment concentration, and adsorbed and dissolved nutrients. Findings The upstream region of a reservoir is already silted. From 2004 to 2014, the delta evoluted approximately 500 m downstream and the deposits were mainly composed of clay. An area of approximately 1,000 m between the delta and the dam should still be able to continue allowing sediment deposition in the coming years. Most of the nutrients were absorbed into the sediment particles, except for the nitrogen measured in the dry season. Research limitations/implications Although analyses of the full cycle of the nutrients were not carried out, the constant sediment trapping of finer sediments and the high rate of absorbed nutrients in the suspended sediment support the hypothesis that the reservoir has removed nutrients from aqueous media by adsorption into sediments. Practical implications In the studied case, reservoir sedimentation has led to better water quality downstream. Originality/value It is shown in this study that reservoir sedimentation may have positive effects on river water quality.

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Purpose Brazilian sediment quality criteria were established based on pseudo-total metal contents, which is not suitable to determine their bioavailability and the ecological risk for aquatic biota. Therefore, the geochemical speciation of five metals (Cu, Fe, Ni, Pb and Zn) was determined to assess the distribution and ecological risk of sediments in a tropical shallow reservoir from Brazil. The paper aims to discuss these issues. Design/methodology/approach A survey of metals in ten representative stations of surface sediments (0-20 cm) from Carlos Botelho (Lobo-Broa) Reservoir was conducted during the dry season in April 2014. Sediment parameters were measured in situ. The geochemical speciation of metals was carried out using the modified three-stage BCR-701 procedure (Davutluoglu et al., 2011) and compared with pseudo-total metal contents. Findings Contamination at S-1 and S-8 was more severe than other sampling sites, especially for Cu, Ni, Pb and Zn. Metals such as Cu, Ni and Zn occasionally may be associated with adverse biological effects based on the comparison with sediment quality guidelines. The risk assessment code suggests no risk for Fe and low risk for Cu and Ni. Originality/value Geochemical speciation of metals could be useful in developing effective management strategies to control metal pollution in the Lobo-Broa Reservoir. Substantial amounts of Pb (classified as medium risk) were bound to humic substances and/or insoluble metal sulfides, and could pose serious risk to the benthic community through the food chain. Zinc at S-1, S-3 and S-8 showed high risk, indicating that an appreciable portion of Zn could be available to aquatic biota.

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