Desempenho de índices quantitativos de seca na estimativa da produtividade de arroz de terras altas

Fernandes, Diego Simões; Heinemann, A. B.; Paz, Rosidalva Lopes Feitosa; Amorim, André de Oliveira

doi:10.1590/s0100-204x2010000800001

Cited by 16 publications

(17 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…available soil moisture or natural reservoirs; Dutra et al, 2013). Further information on the advantages and drawbacks of the SPI and its association with the different types of drought can be found in several studies including Fernandes et al (2010) and Blain (2012).…”

Section: Introductionmentioning

confidence: 99%

Inadequacy of the gamma distribution to calculate the Standardized Precipitation Index

Blain

Meschiatti

2015

Rev. bras. eng. agríc. ambient.

View full text Add to dashboard Cite

A B S T R A C TThe Standardized Precipitation Index was developed as a probability-based index able to monitor rainfall deficit in a standardized or normalized way. Thus, the performance of this drought index is affected by the use of a distribution that does not provide an appropriate fit for the rainfall data. The goal of this study was to evaluate the adjustment of the gamma distribution for the rainfall amounts summed over several time scales (Pelotas, Rio Grande do Sul, Brazil), to assess the goodness-of-fit of alternative distributions to these rainfall series and to evaluate the normality assumption of the Standardized Precipitation Index series calculated from several distributions. Based on the Lilliefors test and on a normality test, it is verified that the gamma distribution is not suitable for calculating this Index in several timescales. The generalized normal distribution presented the best performance among all analysed distributions. It was also concluded that the drought early warning systems and the academic studies should re-evaluate the use of the gamma distribution in the Standardized Precipitation Index calculation algorithm. A computational code that allows calculating this drought index based on the generalized normal distribution has also been provided. Inadequação da distribuição gama para o cálculo do Índice Padronizado de Precipitação R E S U M OO Índice Padronizado de Precipitação foi desenvolvido para ser um método probabilístico que monitora os déficits de precipitação pluvial, de forma normalizada. Assim, a confiabilidade deste índice é afetada pelo uso de distribuições inadequadas aos dados de precipitação. Com isto, o objetivo do trabalho foi: avaliar o ajuste da distribuição gama aos totais de precipitação acumulados em distintas escalas temporais (Pelotas, Rio Grande do Sul), analisar o desempenho de demais distribuições no cálculo desse índice e avaliar o pressuposto de normalidade das séries desse quantificador de seca, calculadas com base nessas distintas distribuições. Os testes Lilliefors e de normalidade indicaram que a distribuição gama não é apropriada para o cálculo do índice em diversas escalas temporais. A distribuição generalizada normal mostrou-se apropriada. O uso desta função também resultou no maior número de séries com distribuição normal. Recomenda-se, então, que os sistemas de monitoramento de seca e os estudos acadêmicos reavaliem o uso da distribuição gama no cálculo do Índice Padronizado de Precipitação. Um código computacional capaz de calcular este índice de seca a partir da distribuição generalizada normal é também apresentado.

show abstract

Section: Introductionmentioning

confidence: 99%

Inadequacy of the gamma distribution to calculate the Standardized Precipitation Index

Blain

Meschiatti

2015

Rev. bras. eng. agríc. ambient.

View full text Add to dashboard Cite

show abstract

“…Results also show the SPI values between -1.50 to -1.99 and those smaller than -2.00, ranked by Fernandes et al (2010) as extreme and severe drought, respectively, with a larger number of events of severe and extreme drought in the series observed compared to the simulated series. In observed series, from 1991 to 2012, there were 9 events and 11 severe drought of extreme drought, while for the simulated series, 6 of 6 severe drought and extreme drought.…”

Section: Resultsmentioning

confidence: 90%

“…After determination of the SPI values to monthly ranking, classification of scale values was used as the severity of the drought, according to Fernandes et al (2010) (Table 1).…”

Section: Methodsmentioning

confidence: 99%

“…Table1 -Classification of the strength of the drought according to the Standardized Precipitation Index (Fernandes et al, 2010 To check the adjustment of the rainfall probability distribution Gamma series, prior to application of the SPI, the graph plotting position was used as well as the adherence tests Chi-square and KolmogorovSmirnov tests, at a significance level of 5% (Wilks, 2006).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Stochastic modeling using Markov chain on the forecast standardized precipitation index

Teixeira-Gandra¹,

Damé²,

Silva³

2017

Científica

View full text Add to dashboard Cite

Grain production and livestock are the basis of the state of Rio Grande do Sul/Brazil economy and favorable rainfall conditions accounts for about 20% of Brazilian production. However, the state has faced periods of drought, especially in the campaign area, decisively affecting agricultural production and hence the economy. The objective of this paper is to predict the Standardized Precipitation Index (SPI) on a monthly scale, from a series of rainfall from 1991 to 2012, for the city of Bagé/RS/Brazil, in order to extend it by over 22 years, using a Markov chain to simulate the occurrence of rainfall and the Gamma distribution for predicting the precipitated amount. The results showed that the model simulated two-state Markov sequences of dry and wet days, keeping the statistical characteristics of the series. There were underestimations of the number on events classified as extreme and severe drought, obtained by serial SPI simulated compared to observed ones.Additional keywords: climate anomaly; drought index; SPI. ResumoA produção de grãos e a pecuária constituem a base da economia do Estado do Rio Grande do Sul/Brasil, e em condições pluviais favoráveis produz cerca de 20% da produção. No entanto, o estado tem enfrentado períodos de estiagem, especialmente na região da campanha, afetando de forma decisiva a produção agrícola e, consequentemente, a economia. Assim, objetivou-se prever o comportamento do Índice Padronizado de Precipitação (SPI) em escala mensal, a partir de uma série de precipitações pluviais de 1991 a 2012, para o município de Bagé/RS/Brasil, de forma a estendê-la por mais 22 anos, utilizando a cadeia de Markov para a simulação da ocorrência da precipitação e a distribuição Gama para a predição da quantidade precipitada. Os resultados obtidos permitiram concluir que o modelo de Markov de dois estados simulou as sequências de dias secos e chuvosos, mantendo as características estatísticas das séries. Houve subestimativa no número de eventos classificados como seca extrema e severa, obtidos mediante a série de SPI simulada, comparativamente à observada.Palavras-chave adicionais: anomalia climática; índice de seca; SPI.

show abstract

“…This reference yield represents the actual portion of the theoretical potential yield that can be achieved, depending on the available technology for inputs and crop management techniques. Similarly, adjusted yield series were used by Fernandes et al (2010) in order to minimize the effects of technological advances in rice yields while comparing them to drought indices.…”

Section: Regionmentioning

confidence: 99%

Rice yield estimation based on weather conditions and on technological level of production systems in Brazil

Monteiro

Azevedo

Assad

et al. 2013

Pesq. agropec. bras.

View full text Add to dashboard Cite

-The objective of this work was to evaluate an estimation system for rice yield in Brazil, based on simple agrometeorological models and on the technological level of production systems. This estimation system incorporates the conceptual basis proposed by Doorenbos & Kassam for potential and attainable yields with empirical adjusts for maximum yield and crop sensitivity to water deficit, considering five categories of rice yield. Rice yield was estimated from 2000/2001 to 2007/2008, and compared to IBGE yield data. Regression analyses between model estimates and data from IBGE surveys resulted in significant coefficients of determination, with less dispersion in the South than in the North and Northeast regions of the country. Index of model efficiency (E 1 ') ranged from 0.01 in the lower yield classes to 0.45 in higher ones, and mean absolute error ranged from 58 to 250 kg ha -1 , respectively.

show abstract

Desempenho de índices quantitativos de seca na estimativa da produtividade de arroz de terras altas

Cited by 16 publications

References 20 publications

Inadequacy of the gamma distribution to calculate the Standardized Precipitation Index

Inadequacy of the gamma distribution to calculate the Standardized Precipitation Index

Stochastic modeling using Markov chain on the forecast standardized precipitation index

Rice yield estimation based on weather conditions and on technological level of production systems in Brazil

Contact Info

Product

Resources

About