In Portugal, particularly in the greater Lisbon area, there are widespread alluvial sandy deposits, which need to be carefully assessed in terms of liquefaction susceptibility and risk zonation. For this purpose, a pilot site has been set up, as part of the European H2020 LIQUEFACT project. An extensive database of geological and geotechnical reports was collected and a comprehensive site investigation campaign was carried out, including boreholes with standard penetration (SPT), piezocone penetrometer and seismic dilatometer tests as well as geophysical methods, complemented by undisturbed soil sampling for laboratory characterisation. The assessment of liquefaction susceptibility based on field tests was made using the simplified procedure, considering the factor of safety against liquefaction (FSliq), which relates the cyclic resistance ratio (CRR) with the cyclic stress ratio (CSR). While the computation of the CSR is relatively straightforward, the reliability of the CRR strongly depends on the adopted in situ testing technique. Alternative approaches to liquefaction assessment have been proposed, based on quantitative liquefaction damage indexes, namely the Liquefaction Potential Index (LPI) and Liquefaction Severity Number. In this paper, the geotechnical field data is integrated in these distinct approaches to liquefaction assessment. A comparative and in-depth analysis of the conventional approach is presented and the inclusion of specific information on soil type, as a means to overcome the observed differences, is discussed particularly for SPT and VS results. The combination of these criteria enabled to clearly identify the most critical layers, in terms of liquefaction potential and severity.

Comparative analysis of liquefaction susceptibility assessment methods based on the investigation on a pilot site in the greater Lisbon area

Wildland fires can be responsible for negative impacts on the environment, causing damage to the fauna and flora and increasing the release of greenhouse gases. In the state of Amazonas, wildland fires represent a risk for biodiversity conservation, since more than 95% of the state is covered by Amazon rainforest, one of the largest and most biodiverse tropical forests of the world. This study aimed to analyze the spatiotemporal variation of fire occurrence from 2003 to 2016 in the state of Amazonas, based on data from the AQUA satellite processed by the Brazilian National Institute for Space Research, using the “Collection 5” detection algorithm. The correlation between fire incidence versus anthropogenic and climatic variables was also tested. A significant uptrend was observed in the number of hot spots recorded over the years. About 83% of the wildland fires occurred during the months of August, September and October. The variables that correlated significantly with the number of hot spots for each municipality were deforested area, pasture area, agricultural area, municipality area and mean annual rainfall. The municipality with the highest number of hot spots detected was Labrea, while Careiro da Varzea presented the highest incidence per km2. The southern and eastern regions of the state were the areas most affected by fire during the analyzed period. The results from this study emphasize the need for implementation of public policies aimed to reduce deforestation and wildland fires in the state, thus ensuring the conservation of the Amazon rainforest and its biodiversity.

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Spatiotemporal variation in fire occurrence in the state of Amazonas, Brazil, between 2003 and 2016

Dynamic properties of two historically liquefiable sands in the Lisbon area

Obtaining undisturbed high-quality samples is a challenge in geotechnical engineering since soils may present significant volume changes and collapse in its structure during sampling or handling at...

Performance of Gel-Push sampling in liquefiable soils

The yield and quality of grapes and by-products are dependent on the soil fertility and nutritional status. Thus, in acid soils and with low natural fertility, applications of acidity correctives and fertilizers are required. But, for example, fertilizer doses should be applied considering results of prediction criteria, as soil and tissue analysis, yield expectation, plant growth, and also the results of univariate methods (critical level and sufficiency range) or bivariate methods (diagnosis and recommendation integrated system and compositional nutrient diagnosis). In addition, fertilizers should be applied at the most appropriate times and modes, to avoid symptoms of deficiency or excess nutrients and soil contamination. Thus, in this chapter, we will focus on the main grapevine cultivars. We will also address the origin of excess and deficiency symptoms of nutrients, the criteria for fertilization, lime and gypsum application, and possible alternative methods to better estimate plant nutritional status. Lastly, we will report on the main management practices used to increase nutrient use in grapevines, thus reducing soil contamination of vineyards and surrounding areas.

Diagnosis and management of nutrient constraints in grape

This work is part of the European research project LIQUEFACT, of which the Faculty of Civil Engineering of the University of Porto (FEUP) is an associate partner. During this research, a vast amount of existing geological and geotechnical reports were collected for the creation of a solid database for selection of a pilot site, for supplementary in situ tests, towards a liquefaction susceptibility microzonation. The analysis of this geotechnical information (mainly SPT, CPT and CH) included the assessment of liquefaction risk indexes, namely the Liquefaction Safety Factor (FSliq), the Liquefaction Potential Index (LPI) and Liquefaction Severity Number (LSN), from which a pilot site was selected in the area of Leziria Grande de Vila Franca de Xira. The experimental campaign at the pilot site involved SPT, CPTu, SDMT, various geophysical methods and the collection of high quality samples for subsequent laboratory characterization. Data treatment of these test results was subdivided into three types of analyses, namely Risk Indexes, classification according to VS30, and expected settlements and lateral displacements. From this work, it was possible to establish and propose a preliminary earthquake-induced liquefaction susceptibility microzonation.

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Microzonamento de suscetibilidade à liquefação: caso de estudo no vale inferior do Tejo

A conversao de florestas tropicais e um grande problema ambiental, com impactos no clima e nos regimes hidrologicos. Diversas pesquisas apontam que o desmatamento em larga-escala da Amazonia poderia levar a alteracoes no clima, se refletindo em reducao de chuvas. Assim, o objetivo aqui e analisar o impacto da mudanca de cobertura vegetal na precipitacao e na vazao de uma bacia de grande-escala na Amazonia, a qual ja sofreu desflorestamento extenso. A Bacia do Rio Uraim, localizada no Para, foi entao selecionada porque originalmente era uma area de floresta, mas atualmente ja experimentou desflorestamento da ordem de 65% de sua extensao. Usando serie historica de dados, testes estatisticos z-teste e t-teste foram realizados para verificar as diferencas hidrologicas entre dois periodos (representando condicoes distintas de cobertura vegetal). Os resultados indicam que a precipitacao media anual do periodo desmatado e aproximadamente 25% menor que para os anos com floresta (p=0,04). Como consequencia da diminuicao de chuvas ha uma reducao de 22% na vazao do canal (p=0,006). No que diz respeito aos regimes da bacia os resultados tambem indicam reducao de 65% na precipitacao durante a estacao seca (p=0,0001) e de 36% na vazao durante os meses de estiagem (p=8,9E-8). Esses resultados sao particularmente relevantes uma vez que confirmam com dados de campo a ocorrencia de decrescimo na chuva como resultado de desmatamento em larga-escala, fenomeno apontado ate entao apenas como previsao, obtida por meio de simulacoes, para cenarios futuros. A B S T R A C T Conversion of tropical forests is a major environmental problem, with impacts on climate and on hydrological regimes. Several researches point that Amazon deforestation on a large scale could lead to climate changes, reflecting in reduced rainfall. So, objective here is to analyze the impact of vegetation cover changes in precipitation and streamflow of a large-scale catchment in Amazon which has already undergone extensive deforestation. The Uraim River Basin, located in Para, was then selected because this was originally a rainforest area, but currently has already experienced deforestation in the order of 65% of its extension.  Using long-time series data, classical statistical z-tests and t-tests were performed to verify the hydrological differences between two periods (representing different conditions of land cover vegetation). The results indicate that mean annual precipitation of deforested period is approximately 25% lower than the values for forested years (p=0.04). As consequence of decreasing rainfall there is a 22% reduction in the channel´s discharge (p=0.006). Regarding basin´s regime the results also indicate a 65% reduction in precipitation during dry season (p = 0.0001) and a 36% reduction in streamflow during low-flow months (p = 8,9E-8). These results are particularly relevant once confirm with field data the occurrence of decrease in rainfall as a result of large-scale deforestation,  phenomenon pointed until now only as forecasts obtained by various simulations of future scenarios . Keywords: land cover change, hydroclimatology, precipitation, streamflow.

https://periodicos.ufpe.br/revistas/rbgfe/article/download/233810/27343

Efeitos do Desmatamento em Larga-Escala na Hidrologia da Bacia do Uraim, Amazônia (Effects of large-scale deforestation on hydrology of Uraim basin, Amazonia)

O avanco do agronegocio na Amazonia tem sido objeto de debate e controversia. Se por um lado e uma atividade economica de grande importância para o pais, por outro lado pode levar a diversos impactos ambientais e, assim, comprometer o desenvolvimento sustentavel da regiao. O presente trabalho procurou, entao, contrastar os aspectos positivos e negativos relacionados a atividade, por meio de uma pesquisa bibliografico-analitica. A analise concluiu que o preservacionismo nao parece realista e viavel, porque os ecossistemas serao sempre e inevitavelmente alterados para atender as demandas de recursos para a humanidade. Ao mesmo tempo, a exploracao nao pode acontecer de forma desordenada e aleatoria, sem cuidados minimos que visem a disponibilidade futura de tais recursos. Concluiu-se ainda que o elevado rendimento proporcionado pela pecuaria de corte e pela industria agricola torna muito dificil o cumprimento de solucoes que facilitem a conservacao apenas por meio de "comando e controle", indicando que sua associacao com mecanismos adicionais como a restricao dos mercados apenas para os produtores que efetivamente adotem a gestao ambiental em suas propriedades forma um conjunto mais eficaz no combate ao desmatamento.

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Agronegócios na Amazônia: ameaças e oportunidades para o desenvolvimento sustentável da região

In geotechnics, several models, empirical or not, have been proposed for the calculation of load capacity in deep foundations. These models run mainly through physical assumptions and construction of approximations by mathematical models. Artificial Neural Networks (ANN), in addition to other applications, are excellent computational mechanisms that, based on biological neural learning, can perform predictions and approximations of functions. In this work, an application of artificial neural networks is presented. The objective here is to propose a mathematical model based on artificial intelligence focused on Artificial Neural Network (ANN) learning capable of predicting the load capacity for driven piles. The results obtained through the neural network were compared with actual values of load capacities obtained in the field through load tests. For this quantitative comparison, the following metrics have been chosen: Pearson correlation coefficient and mean squared error. The database used to carry out the project consisted of 233 load tests, carried out in diverse cities and different countries, for which load capacity, hammer weight, hammer drop height, pile length, pile diameter and pile penetration per blow values ​​were available. These values have been used as input values in a multilayer perceptron neural network to estimate the load capacities of the respective piles. It has been found that the proposed neural model presented, in general, correlation with field values above 90%, reaching 96% in the best result.

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Artificial neural network model for predicting load capacity of driven piles

RESUMO A populacao de Sao Luis do Maranhao apresentou crescimento de 17% entre o periodo de 2000 e 2010. O objetivo nesse trabalho e estudar a distribuicao populacional nos bairros da cidade, identificar quais tiveram maiores variacoes percentuais e analisar os reflexos dessas mudancas no adensamento da cidade em um periodo recente. Para determinar tais variacoes foram utilizados dados referentes ao numero de habitantes em cada bairro nos anos de 2000, 2007 e 2010. A partir destes valores foram determinados os percentuais de acrescimo e decrescimo dos seis bairros com maior crescimento e maior decrescimo, respectivamente, bem como as densidades demograficas dos mesmos. Os resultados encontrados demonstram que o crescimento da cidade vem ocorrendo de uma forma muito heterogenea, com expansao acelerada em alguns bairros contrastando com retracao em outros e tambem com densidades demograficas muito altas em algumas areas e baixas em outras. Tais situacoes sao preocupantes, uma vez que trazem consigo problemas para a adequada oferta de servicos basicos como abastecimento de agua, esgoto, dentre outros.

Rodrigo da Cruz de Araujo

Papers

Microzonamento de suscetibilidade à liquefação: caso de estudo no vale inferior do Tejo

Efeitos do Desmatamento em Larga-Escala na Hidrologia da Bacia do Uraim, Amazônia (Effects of large-scale deforestation on hydrology of Uraim basin, Amazonia)

Agronegócios na Amazônia: ameaças e oportunidades para o desenvolvimento sustentável da região

Artificial neural network model for predicting load capacity of driven piles

Estudo da expansão urbana da cidade de são luis –ma