Mecanismo financeiro projetado com índices de seca como instrumento de gestão de risco em recursos hídricos

Silva, Samíria Maria Oliveira da; Souza-Filho, Francisco de Assis de; Araujo-Junior, Luiz Martins de

doi:10.21168/rbrh.v20n2.p320-330

Cited by 4 publications

(3 citation statements)

References 1 publication

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“…The drought analysis was based on the calculation of the Standard Precipitation Index (SPI) [64] with 12 months aggregated timescale (SPI12). The time scale used for the calculation of the index is directly related to the time required for the effects of drought to be felt on the different activity sectors and the region's water resources [65]. A new time-series was created with only December SPI12 values (SPI12 DEC ) to represent the accumulated annual information.…”

Section: Drought Analysismentioning

confidence: 99%

Copula-Based Multivariate Frequency Analysis of the 2012–2018 Drought in Northeast Brazil

Filho

Martins

et al. 2020

Water

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The 2012–2018 drought was such an extreme event in the drought-prone area of Northeast Brazil that it triggered a discussion about proactive drought management. This paper aims at understanding the causes and consequences of this event and analyzes its frequency. A consecutive sequence of sea surface temperature anomalies in the Pacific and Atlantic Oceans, at both the decadal and interannual scales, led to this severe and persistent drought. Drought duration and severity were analyzed using run theory at the hydrographic region scale as decision-makers understand impact analysis better at this scale. Copula functions were used to properly model drought joint characteristics as they presented different marginal distributions and an asymmetric behavior. The 2012–2018 drought in Ceará State had the highest mean bivariate return period ever recorded, estimated at 240 years. Considering drought duration and severity simultaneously at the level of the hydrographic regions improves risk assessment. This result advances our understanding of exceptional events. In this sense, the present work proposes the use of this analysis as a tool for proactive drought planning.

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Section: Drought Analysismentioning

confidence: 99%

Copula-Based Multivariate Frequency Analysis of the 2012–2018 Drought in Northeast Brazil

Filho

Martins

et al. 2020

Water

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“…This SPI was used to compare the precipitation over the 12 consecutive months specific to our study to the 12 consecutive months of all years preceding this period in the historical data series. In accordance with Silva et al [41], the time scale used for calculating the SPI is directly related to the time needed for the effects of the drought to be experienced in the different economic sectors and the various water resources of the region. As such, this index facilitates the determination of the intensity, magnitude, duration, and onset probability of a specific drought, given a historical data series.…”

Section: Drought Characterizationmentioning

confidence: 90%

Use of Machine Learning in Evaluation of Drought Perception in Irrigated Agriculture: The Case of an Irrigated Perimeter in Brazil

Xavier

Silva

Carvalho

et al. 2020

Water

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This study aimed to understand the perception of drought among farmers, in order to support decision-making in the water allocation process. This study was carried out in the Tabuleiro de Russas irrigated perimeter, in northeast Brazil, over the drought period of 2012–2018. Two analyses were conducted: (i) drought characterization, using the Standardized Precipitation Index (SPI) based on drought duration and frequency criteria; and (ii) analysis of farmers’ perceptions of drought via selection of explanatory variables using the Random Forest (RF) and the Decision Tree (DT) methods. The 2012–2018 drought period was defined as a meteorological phenomenon by local farmers; however, an SPI evaluation indicated that the drought was of a hydrological nature. According to the RF analysis, four of the nine study variables were more statistically important than the others in influencing farmers’ perception of drought: number of cultivated land plots, farmer’s age, years of experience in the agriculture sector, and education level. These results were confirmed using DT analysis. Understanding the relationship between these variables and farmers’ perception of drought could aid in the development of an adaptation strategy to water deficit scenarios. Farmers’ perception can be beneficial in reducing conflicts, adopting proactive management practices, and developing a holistic and efficient early warning drought system.

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“…Although there are different methods to study hydrological droughts, each with its own advantages and limitations, in Brazil, many studies have used the SPI on a 12-month scale [13][14][15][16]. The SPI is an index developed by McKee et al [17] that is based on the accumulated precipitation deficit for a given period.…”

Section: Introductionmentioning

confidence: 99%

Drought Assessment in São Francisco River Basin, Brazil: Characterization through SPI and Associated Anomalous Climate Patterns

et al. 2021

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The São Francisco River Basin (SFRB) is one of the main watersheds in Brazil, standing out for generating energy and consumption, among other ecosystem services. Hence, it is important to identify hydrological drought events and the anomalous climate patterns associated with dry conditions. The Standard Precipitation Index (SPI) for 12 months was used to identify hydrological drought episodes over SFRB 1979 and 2020. For these episodes, the severity, duration, intensity, and peak were obtained, and SPI-1 was applied for the longest and most severe episode to identify months with wet and dry conditions within the rainy season (Nov–Mar). Anomalous atmospheric and oceanic patterns associated with this episode were also analyzed. The results revealed the longest and most severe hydrological drought episode over the basin occurred between 2012 and 2020. The episode over the Upper portion of the basin lasted 103 months. The results showed a deficit of monthly precipitation up to 250 mm in the southeast and northeast regions of the country during the anomalous dry months identified through SPI-1. The dry conditions observed during the rainy season of this episode were associated with an anomalous high-pressure system acting close to the coast of Southeast Brazil, hindering the formation of precipitating systems.

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Mecanismo financeiro projetado com índices de seca como instrumento de gestão de risco em recursos hídricos

Cited by 4 publications

References 1 publication

Copula-Based Multivariate Frequency Analysis of the 2012–2018 Drought in Northeast Brazil

Copula-Based Multivariate Frequency Analysis of the 2012–2018 Drought in Northeast Brazil

Use of Machine Learning in Evaluation of Drought Perception in Irrigated Agriculture: The Case of an Irrigated Perimeter in Brazil

Drought Assessment in São Francisco River Basin, Brazil: Characterization through SPI and Associated Anomalous Climate Patterns

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