Development of an annual drought classification system based on drought severity indexes

Lima, Rafael Petruceli Coelho; Silva, Demétrius D. da; Moreira, Michel Castro; Passos, J. B. M. C.; Coelho, Clívia Dias; Elesbon, Abrahão Alexandre Alden

doi:10.1590/0001-3765201920180188

Cited by 20 publications

(7 citation statements)

References 11 publications

(8 reference statements)

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“…Although it is difficult to prevent a meteorological drought occurrence, when its relationship with the hydrological drought is known, actions can be taken to mitigate the impact on the rivers (Barker et al, 2016). However, most of the drought studies carried out in Brazil are focused on meteorological drought, as Lima et al (2019) and Gois et al (2015). Melo et al (2016) evaluated the linkages between meteorological and hydrological droughts in the Paraná Basin, Southeastern Brazil, and identified a reduction from 20 to 50% of precipitation compared to the long-term average in the early 2000s and 2014.…”

Section: Introductionmentioning

confidence: 99%

“…Besides, the Brazilian Ministry of Integration estimates that from 2012 to 2014 the most severe droughts of the last decades occurred in Southeastern Brazil with losses of approximately 6 billion dollars in the agricultural sector (Marengo et al, 2016). Lima et al (2019) developed an annual drought classification system for Doce River Basin, divided it into nine sub-basins, based on four indices, including the Standardized Precipitation Index (SPI). The most critical drought events were observed in the second half of the time series (from 2000 to 2015), where the events were more intense and longer-lasting.…”

Section: Introductionmentioning

confidence: 99%

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Meteorological and hydrological drought from 1987 to 2017 in Doce River Basin, Southeastern Brazil

Jesus

Amorim

Junqueira

et al. 2020

RBRH

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ABSTRACT Meteorological drought is a natural hazard characterized as below-average precipitation from expected or normal that can affect various economic sectors, and lead to period with inadequate streamflow for established uses of the water (hydrological drought). We aimed to apply the Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) to identify the occurrence and the intensity of droughts in Doce River Basin (DRB), Southeastern Brazil. For this purpose, 71 rain gauge stations and one streamflow station were selected with 30-year monthly historical series (1987 to 2017). The SPI and SSI were calculated for the hydrological year (October-September) and the seasons (Spring, Summer, Fall, and Winter). SPI mapping was performed by geostatistical procedures. Pearson's coefficient was calculated to analyze the influence of meteorological on hydrological drought. The main meteorological drought events, observed in the hydrological years of 1994/95, 2000/01, and a recent and consecutive period of four hydrological years (2013-2017), were mainly influenced by events in spring and summer and, to a lesser extent, in fall. It was observed the influence of the meteorological drought on the hydrological drought on an annual and seasonal scale, except winter, where low precipitation does not influence in the streamflow.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Meteorological and hydrological drought from 1987 to 2017 in Doce River Basin, Southeastern Brazil

Jesus

Amorim

Junqueira

et al. 2020

RBRH

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“…Wetlands and open water areas could be much larger if the classification process were more effective and regional and local rainfall were within the regular range during the study. The severe drought in southeastern Brazil during 2014 and 2015 (Nobre et al 2016) was considered the most extreme drought at the Rio Doce Basin for the last 30 years (Lima et al 2019). Since 2015, rainfall in the river basin, and particularly at LDRV, has been low, which can be regarded for the shrinkage and disappearance wetland areas.…”

Section: Resultsmentioning

confidence: 99%

Wetland Mapping With Multitemporal Sentinel Radar Remote Sensing in the Southeast Region of Brazil

Salinas

Eggerth

Miller

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. A classification method with multi-temporal images of synthetic aperture radar (SAR) combined with Geographic information system, geoinformation data, and field validation, was applied for wetland mapping accuracy and typology. Wetland mapping is vital for management and conservation, particularly under environmental pressures such as wetland drainage and land reclamation. The aim of this study is to develop an accurate mapping of wetlands and open water systems of the Lower Doce River Valley - LDRV (Southeastern Brazil) with Synthetic Aperture Radar (SAR) imagery, using multitemporal classification techniques and ground truth validation. Sentinel-1B SAR imagery from 2016 and 2019 was processed with Google Earth Engine (GEE). Monthly median imagery condition for the rainy season was obtained and K-means unsupervised classification was applied. The study yields 4,157 wetlands, 262.27 km2 with predominant small patches. Fieldwork revealed three main wetlands categories: coastal wetlands, inland wetlands and artificial wetlands. The results have shown an overall accuracy of 81.9% and a Kappa coefficient of 0.71. Wetlands, non-wetlands, and open waters classes present accuracy of 50, 80 and 95%, respectively.

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“…Para o cálculo desse índice, agrupou-se os valores de precipitação média ponderada anual da série histórica de 31 anos (1988 -2018) em Decis (décimos da distribuição dos dados), dividindo-se a série em dez partes iguais, em ordem crescente, da menor precipitação até a precipitação mais elevada, de forma a gerar uma distribuição de frequências acumuladas. Detalhes dessa metodologia pode ser encontrada em Lima et al (2019). A classificação da severidade de seca foi realizada pelo método do Decis proposto por Gibbs e Maher (1967).…”

Section: Methodsunclassified

Impacto de Secas e Antropização na Dinâmica da Cobertura Florestal em Fragmento do Domínio Fitogeográfico da Caatinga

Aquino

Andrade

Filho

et al. 2021

Rev. Bras. Geog. Fis.

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Este trabalho objetivou avaliar a influência da antropização e de secas severas na dinâmica da cobertura florestal de um fragmento de caatinga na região semiárida do Brasil, ao longo de 32 anos. Para o cálculo do índice de seca, agrupou-se os valores de precipitação média pondera da anual da série histórica (1988 - 2019) em Decis. A partir do quantitativo de área encontrada nas classes de uso e ocupação (cobertura florestal conservada, cobertura natural campestre, área antropizada e corpos d’água) dos anos extremos secos e chuvosos, procedeu-se à análise estatística multivariada pelo método da análise de agrupamento hierárquico. Os valores médios dos agrupamentos foram submetidos à análise estatística e confrontados pelo teste T de Student (p ≤ 0,05). Foram encontrados três grupos distintos: G1 constituído por anos secos e muito secos da década de 90, o agrupamento 2 formado por anos extremos úmidos e muito úmidos, independentemente do período, e G3 (agrupamento intermediário) constituído tanto por anos típicos secos quanto chuvosos, especificamente de períodos mais recentes (2000 a 2019). Os grupos G2 e G3 contribuíram com as maiores quantitativo de cobertura florestal conservada, 143.176,50 e 144.928,13 ha, respectivamente. Os resultados demonstram que a precipitação pluviométrica está mais estritamente correlacionada com as áreas antropizadas do que propriamente com a regeneração natural da cobertura florestal. A vegetação arbórea-arbustiva do fragmento investigado tem passado por um processo de regeneração natural na década recente (2002 - 2019) em virtude do abandono de áreas anteriormente antropizadas na década de 90. Drought and Anthropogenic Effect on the Dynamics of Forest Cover in a Fragment of Caatinga Phytogeographic Domain A B S T R A C TThe aim of this study was to evaluate the influence of anthropogenic action and severe drought on the dynamics of forest cover in a fragment of caatinga in the semi-arid region of Brazil, over 32 years. To calculate the drought index, the values for weighted mean annual precipitation from an historical series (1988 - 2019) were grouped into deciles. Based on the quantification of the area found in the classes of use and occupation (conserved forest cover, natural rural cover, anthropogenic area and water bodies) for the extreme dry and rainy years, multivariate statistical analysis was carried out using hierarchical cluster analysis. The mean values of the clusters were submitted to statistical analysis and compared by Student's t-test (p ≤ 0.05). Three distinct groups were found: G1, consisting of dry and very dry years from the 1990s; G2, formed by extreme wet and very wet years regardless of the period; and G3 (intermediate group), comprising both dry and rainy years, specifically from more recent periods (2000 to 2019). Groups G2 and G3 contributed the greatest amount of conserved forest cover, 143,176.50 and 144,928.13 ha respectively. The results show that rainfall is more closely correlated with the anthropogenic areas than with the natural regeneration of forest cover. The woody vegetation of the fragment under investigation has undergone a process of natural regeneration during the last decade (2008 - 2016), due to previously anthropogenic areas being abandoned in the 1990s.Keywords: Caatinga, remote sensing, desertification.

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Development of an annual drought classification system based on drought severity indexes

Cited by 20 publications

References 11 publications

Meteorological and hydrological drought from 1987 to 2017 in Doce River Basin, Southeastern Brazil

Meteorological and hydrological drought from 1987 to 2017 in Doce River Basin, Southeastern Brazil

Wetland Mapping With Multitemporal Sentinel Radar Remote Sensing in the Southeast Region of Brazil

Impacto de Secas e Antropização na Dinâmica da Cobertura Florestal em Fragmento do Domínio Fitogeográfico da Caatinga

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