Modelagem computacional da rede de drenagem urbana usando alternativas LID em uma sub-bacia na cidade de Maringá, Paraná, Brasil

With urbanization development, inundations and urban floods become more frequent. In the city of Maringa, Parana, this type of event is often observed in some specific dense urban locations, resulted by intense rainfall. In this context, the objective of this paper is to perform a computational modelling in the urban drainage network, most specifically in the sub-basin defined by the intersection of avenues Guaiapo and Palmares, in the city of Maringa, Parana, considering the current situation and with the application of Low Impact Development (LID) compensatory techniques. In this regard, the computational program SewerGEMS® was used to develop the scenarios simulations. The results shown that the actual network is undersized (Scenario 01), and it is proposed the adoption of LID compensatory measures (Scenarios 02, 03 and 04). The computational modelling in the elaboration of the scenarios was effective and it may support the municipal urban management with the implementation of an adequate and efficient system of stormwater management.Com o avanço da urbanização, tornam-se frequentes os problemas de alagamentos, inundações e enchentes urbanas. Na cidade de Maringá, Paraná, constatam-se alagamentos frequentes, decorrentes de chuvas intensas, em pontos específicos densamente urbanizadas. Neste contexto, o objetivo desse trabalho é elaborar cenários de um trecho da rede de drenagem urbana, mais especificamente no ponto de cruzamento entre as avenidas Guaiapó e dos Palmares, localizado na cidade de Maringá, Paraná: com a situação atual e utilizando técnicas compensatórias de Low Impact Development (LID). Para isso, foi utilizado o programa computacional SewerGEMS® a fim de realizar as simulações dos cenários propostos. Os resultados mostraram que a rede atual no trecho considerado está subdimensionada (Cenário 1) e uma das soluções propostas é a adoção de técnicas compensatórias LID para construção dos Cenários 2, 3 e 4. Conclui-se que a modelagem computacional para a elaboração de cenários mostrou-se efetiva e pode ser uma grande aliada para fornecer subsídios para a gestão municipal urbana, auxiliando na implementação de um manejo de águas urbanas adequado e eficiente.

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Comparison of methods for the evaluation of adaptability and stability for yield in cotton genotypes

O objetivo deste trabalho foi comparar diferentes métodos de estimação da adaptabilidade e estabilidade produtiva em 17 genótipos de algodoeiro avaliados em 23 ambientes do Cerrado brasileiro. Os efeitos de genótipos e ambientes e a interação genótipos x ambientes foram significativos. Os modelos da ecovalência e AMMI indicaram a cultivar BRS Cedro como a mais estável, enquanto as cultivares Delta Penta e BRS Ipê foram identificadas como as mais instáveis; nenhuma delas esteve entre as mais produtivas. De acordo com o método de Eberhart & Russell, Lin & Binns e Annicchiarico, as cultivares BRS 269 – Buriti e FMT 701 e o genótipo CNPA GO 2001-999 foram os mais indicados para plantio no Cerrado, e se destacaram entre as cinco mais produtivas na média dos ambientes. A identificação de adaptabilidades específicas, proporcionada pela análise AMMI, é de grande relevância no estudo do comportamento dos genótipos. Pelo conjunto de informações obtidas e pela facilidade de uso e interpretação, recomenda-se o emprego do método de Lin & Binns , que pode ser complementado pela análise AMMI.The objective of this work was to compare different methods used to estimate adaptability and stability of 17 cotton genotypes evaluated in 23 locations of the Brazilian savannah. Genotype and environment effects and genotype x environment interaction were significant. According to ecovalence and AMMI models, cultivar BRS Cedro showed the best stability. Varieties Delta Penta and BRS Ipê were among the most unstable genotypes, but not among the most productive. Using the methods of Eberhart & Russel, Lin & Binns and Annicchiarico, genotypes BRS 269 – Buriti, FMT 701 and CNPA GO 2001-999 were the most stable and among the five most productive on average. The evaluation of the specific adaptabilities provided by the AMMI analysis is of great importance in the study of the behavior of genotypes. The amount of information generated and the facilities of interpretation favors Lin & Binns method, which can be complemented by an AMMI analysis

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio