Intensive rainfall is an important meteorological variable that is of technical interest in hydraulic projects. This study therefore generated Intensity-Duration-Frequency equations (IDF) for 14 weather stations in Mato Grosso State, based on pluviograph analysis. Annual maximum rainfall data regarding 10-to-1440-minute long rainfall events were collected from digitized daily pluviographs. Data adherence to the generalized extreme value distribution (GEV) was checked through the Kolmogorov-Smirnov test at a 20% significance level. Next, the maximum probable rainfall for return periods such as 2, 5, 10, 20, 30, 50 and 100 years was calculated and the IDF equations were adjusted. The performance of the IDF equations was evaluated based on mean absolute error (MAE), root mean square error (RMSE), bias, Willmott's concordance index and Nash-Sutcliffe efficiency index (ENS). Adjusting the IDF equations was only possible for rainfall durations ranging from 10 to 360 min at each station due to the low frequency of longer rainfalls. High variation was present in parameters of the IDF equation and in maximum rainfall intensity between stations. The satisfactory performance of the models, as attested to by statistical indices, allows using IDF equations adjusted for rainfall durations from 10 to 360 min, and return periods from 2 to 100 years, in the regions of the Mato Grosso weather stations.
Analisou-se as mudanças de parâmetros biofísicos e tendências de índices de extremos anuais da temperatura do ar na região de Sinop, Mato Grosso, considerando estações meteorológicas automáticas (EMA) instaladas em área urbana e rural. As estimativas das mudanças no uso do solo, albedo da superfície, saldo de radiação (Rn) e fluxos de calor sensível (H) e calor latente (LE) foram obtidas por imagens dos satélites Landsat 8 e Landsat 5, no mês de agosto dos anos de 2007, 2011 e 2017. Com o software Rclimdex, foram calculadas as tendências de seis índices de extremos dos valores máximos, mínimos e médios das temperaturas máximas e mínimas anuais, com calibração pelo método dos mínimos quadrados e significâncias estatísticas consideradas pelo teste de Fisher com nível de significancia igual a α: 0,05. Foram observadas mudanças no uso e ocupação solo e dos parâmetros biofísicos com aumento do albedo e redução do Rn para EMA na área rural, enquanto na estação urbana (UFMT Sinop) observou-se a inversão das parcelas de LE e H. Os índices de extremos indicaram tendência no aumento das temperaturas extremas na área urbana, sendo significativas as mudanças nos índices TNx, DTR, Tn90p e Tx90p. Na última década, com a expansão do município de Sinop-MT, ocorreram alterações nas tendências dos índices de extremos de temperatura, sendo estas, serem atribuídas as mudanças no uso do solo e parâmetros biofísico.
Avaliou-se a variação espaço-temporal dos parâmetros biofísicos em plantios de Eucalipto, na transição Cerrado-Amazônia Mato-Grossense, por meio de sensoriamento remoto. A área localiza-se no município de Lucas do Rio Verde-MT, sendo composta por talhões de E. urophylla, E. urograndis, mata nativa e solo exposto. As imagens foram adquiridas no site do U. S. Geological Survey referentes aos meses de fevereiro 2015/16 e janeiro 2017 (estação chuvosa) e junho 2015-2017 (estação seca). O Índice de Vegetação da Diferença Normalizada (NDVI), albedo da superfície ( ); temperatura da superfície (Ts); Saldo de Radiação (Rn) e evapotranspiração (ET) foram calculados em etapas do modelo R-SSEB. Os plantios de Eucalipto, comparado a floresta nativa, apresentaram aumento de 3% a 4% nos valores de NDVI, Ts, Rn e ET. A exposição de solo provocou aumento do albedo (69% a 109%) e da Ts (14% a 34%) e redução do NDVI (63% a 58%), do Rn (13% a 20%) e da ET (57% a 26%), nos períodos de chuva e seca, respectivamente. Conclui-se que as mudanças no uso e ocupação do solo alteraram os parâmetros biofísicos e a evapotranspiração, sendo estas mais acentuadas em áreas desmatadas do que em áreas com cultivo de Eucalipto.
This paper aimed to analyze the dynamics of the energy budget components: latent heat flux (LE), sensible heat flux (H) and soil heat flux (G), in the Mato Grosso Pantanal. The estimates of LE, H, and G were obtained by the Bowen ratio methods, using data from the micrometeorological tower located in the Baía das Pedras Park of SESC-Pantanal Ecological Resort, for the years 2011 to 2013. The normality of the variables Rn, LE, H and G, were tested by Kolmogorov-Smirnov test at 5% significance, and the seasonal differences of the fluxes were verified by the KruskalWallis test, α = 0.05. LE and H data from the remote sensing products MATMNXFLX and FLDAS_NOAH of the MERRA model was also acquired, and their comparison with the tower data was performed by the statistics of Spearman correlation (r), Mean Absolute Error (MAE), Root Mean Squared Erro (RMSE), bias, and Willmott's Concordance Index (d). It was observed that most of the available energy is used for evapotranspiration (latent heat), followed by sensible heat and soil heat flux. In the rainy season there is an increase in the partition of LE and G and reduction of H. Only the estimates of LE of MATMNXFLX and FLDAS_NOAH products correlate with the data observed in the meteorological tower. It is concluded that the energy partitions have a seasonal behavior and that the MATMNXFLX and FLDAS_NOAH products, after being calibrated, can be used to estimate LE in the Mato Grosso Pantanal.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.