Classificação climática para o estado de Minas Gerais segundo as zonas de vida de Holdridge

Ferreira, Heitor Renan; Tres, Andressa; Tetto, Alexandre França; Soares, Ronaldo Viana; Wendling, William Thomaz; Batista, Antônio Carlos

doi:10.20873/jbb.uft.cemaf.v7n2.ferreira

Cited by 5 publications

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“…The austral summer (December-January-February) represents the season with higher accumulated precipitation (600-800 mm), with an average of 350 mm occurring specifically during January (da Silva, 2014). The average elevation throughout the state is 700 m, ranging from 500 to 2000 m, and the terrain is often hilly (Ferreira et al, 2019). The natural land cover of the region is split between Cerrado savannas and tropical Atlantic forests (IBGE, 2004), with predominant land being used for smallholding agriculture and cattle ranching (IBGE, 2018a).…”

Section: Study Areamentioning

confidence: 99%

Extreme rainfall and its impacts in the Brazilian Minas Gerais state in January 2020: Can we blame climate change?

et al. 2021

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In January 2020, an extreme precipitation event occurred over southeast Brazil, with the epicentre in Minas Gerais state. Although extreme rainfall frequently occurs in this region during the wet season, this event led to the death of 56 people, drove thousands of residents into homelessness, and incurred millions of Brazilian Reais (BRL) in financial loss through the cascading effects of flooding and landslides. The main question that arises is: To what extent can we blame climate change? With this question in mind, our aim was to assess the socioeconomic impacts of this event and whether and how much of it can be attributed to human-induced climate change. Our findings suggest that human-induced climate change made this event >70% more likely to occur. We estimate that >90,000 people became temporarily homeless, and at least BRL 1.3 billion (USD 240 million) was lost in public and private sectors, of which 41% can be attributed to human-induced climate change. This assessment brings new insights about the necessity and urgency of taking action on climate change, because it is already effectively impacting our society in the southeast Brazil region. Despite its dreadful impacts on society, an event with this magnitude was assessed to be quite common (return period of ∼4 years). This calls for immediate improvements on strategic planning focused on mitigation and adaptation.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Study Areamentioning

confidence: 99%

Extreme rainfall and its impacts in the Brazilian Minas Gerais state in January 2020: Can we blame climate change?

et al. 2021

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“…The study was conducted in the Mata Seca State Park (Figure 1) in the Manga and Itacarambi municipalities, Northern of the state of Minas Gerais, Brazil (14°52'00" S 43°59'57" W), amounting to an area of 15,360.07 ha of Seasonal Deciduous Forest, in the Atlantic Forest Domain (oliVeira-Filho 2006). The forest presents deciduous tree strata because of its two well-defined climatic seasons: a rainy and a dry one, which extends from April to October so the tropical climate predominates in the Mata Seca State Park region (Ferreira et al 2019), where the average annual rainfall is 818 mm, with an average temperature of 24º C for year (madeira et al 2009; rodrigues et al 2013). More than 50% of tree species in the forest lose their leaves (i.e., decidual) in adverse periods (Belém et al 2021), significantly changing the vegetal structure of the area (Figure 2).…”

Section: Methodsmentioning

confidence: 99%

Response of Odonata communities to dry season in a Deciduous Forest in the Northern Minas Gerais, Brazil

et al. 2022

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Odonata sampling effort in the state of Minas Gerais has intensified throughout the 21st century. However, research on these insects in some regions and ecosystems such as the Deciduous Forest are incipient, and the effect of prolonged dry periods over these insects is still unknown. This study thus aimed to assess changes in adult Odonata species composition over one year in a Brazilian Deciduous Forest and the Odonata species richness in the Mata Seca State Park in the Manga and Itacarambi municipalities in the Northern region of the state of Minas Gerais State, Brazil. Twenty-four days of sampling were distributed in February, May, July and November, adopting an active search through entomological nets close to lentic environments (Lagoa Angical, Lagoa Comprida, Lagoa Encantada, Lagoa da Prata and two wetlands of Lajedo da Lua); lotic environments (São Francisco river) and in associated terrestrial ecosystems. In total, 55 species were collected. Rainy and dry periods altered Odonata communities’ composition but did not affect species richness and abundance due to the presence of permanent lagoons associated with the São Francisco river. This study shows the importance of the Mata Seca State Park for preserving Odonatofauna in the state of Minas Gerais and for protecting those permanent lagoons.

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“…e Caracterização da Área Experimental Apresentando um clima altamente influenciado pela sua continentalidade e características geomorfológicas, o estado de Minas Gerais manifesta duas estações do ano bem definidas, sendo uma chuvosa, entre o período de outubro e março, e outra seca, entre os meses de abril e setembro, vide sua predominância pelos climas tropical e subtropical úmido com inverno seco (Ferreira et al, 2019;Santos et al, 2021).…”

Section: Localizaçãounclassified

Comparação de modelos geoestatísticos para estimativa de precipitação em Minas Gerais, Brasil, entre os anos hidrológicos de 2000 e 2021

Guimarães

Alves²

2023

Rev. Bras. Geog. Fis.

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A gestão integrada dos recursos hídricos no Brasil e no mundo tem passado por desafios provenientes de processos naturais e antrópicos. Assim, o conhecimento preciso das condições quantitativas e qualitativas dos recursos hídricos é de fundamental importância, sendo o monitoramento pluviométrico por estações pluviométricas distribuídas no estado um componente central deste, no que diz respeito ao entendimento da dinâmica espacial e temporal da precipitação. Em Minas Gerais, tais estações estão concentradas em determinadas áreas, dificultando o processo de tomada de decisão pelos agentes gestores. As técnicas de geoestatística têm se mostrado acuradas para estimativa de precipitação em espaços sem estações pluviométricas, sendo que tal trabalho visou aplicá-las no estado, nos anos hidrológicos de outubro de 2000 a setembro de 2021. Verificou-se o potencial dos modelos Circular, Gaussiano, Esférico, Tetraesférico, Pentaesférico e Exponencial, e o Grau de Dependência Espacial entre as variáveis, utilizando-se do tratamento de dados por linguagem de programação Python e R e por técnicas de geoprocessamento. Os resultados apontaram para maior aplicabilidade do modelo Gaussiano em toda série histórica, sendo sucedido pelo modelo Exponencial em períodos chuvosos, e pelo modelo Circular na estação seca. Os modelos Pentaesférico, Esférico e Tetraesférico foram os menos aplicados. Viu-se também uma relação irregular entre o desempenho dos modelos e o Grau de Dependência Espacial das variáveis.Palavras-chave: krigagem, dependência espacial, estações pluviométricas, gestão integrada dos recursos hídricos. Comparison of geostatistical models for rainfall forecast in Minas Gerais, Brazil, between 2000 and 2021 hydrological years A B S T R A C TThe integrated water resources management in Brazil and worldwide had been through challenges from anthropic activities and natural processes. In that regard, the precise knowledge of water resources quality and quantity conditions has major importance, with the rainfall monitoring network by rainfall stations as a core component for understanding the precipitation spatial and temporal dynamics. These stations are concentrated in a few sites within Minas Gerais, which makes the decision-making process difficult for the manager agents. Geostatistical analysis has been shown as an accurate method for rainfall forecast in spaces with lack of rainfall stations, and this work aimed to apply it in Minas Gerais, between October 2000 and September 2021 hydrological years. It was checked Circular, Gaussian, Spherical, Tetraspherical, Pentaspherical, and Exponential models potential, and the degree of spatial dependence, using data treatment by Python and R programming language and geoprocessing tools. The results showed that Gaussian model has greater applicability in the time series, being succeed by Exponential model in wet season, and Circular model in dry season. Pentaspherical, Spherical, and Tetraspherical models were the least applied. It was found an irregular relationship between models’ performance and the degree of spatial dependence.Keywords: kriging, degree of spatial dependence, rainfall stations, integrated water resources management.

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Classificação climática para o estado de Minas Gerais segundo as zonas de vida de Holdridge

Cited by 5 publications

References 5 publications

Extreme rainfall and its impacts in the Brazilian Minas Gerais state in January 2020: Can we blame climate change?

Extreme rainfall and its impacts in the Brazilian Minas Gerais state in January 2020: Can we blame climate change?

Response of Odonata communities to dry season in a Deciduous Forest in the Northern Minas Gerais, Brazil

Comparação de modelos geoestatísticos para estimativa de precipitação em Minas Gerais, Brasil, entre os anos hidrológicos de 2000 e 2021

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