Comparison between Parametric and Nonparametric Approaches for the Calculation of Two Drought Indices: SPI and SSI

Soľáková, Tatiana; Michele, Carlo De; Vezzoli, Renata

doi:10.1061/(asce)he.1943-5584.0000942

Cited by 56 publications

(26 citation statements)

References 28 publications

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“…This methodological issue is addressed in this paper by assigning SPI values for zero precipitation based on the ‘centre of mass’ of the zero distribution rather than the maximum probability, thereby producing SPI values that maintain statistical interpretability (mean, μ = 0). The concept of ‘probability mass’ when normalizing zeros in the SPI was discussed in Solakova et al (), although the implementation in this paper eventually used the former method discussed above. In the ‘proposed’ method for normalizing zero precipitation, the likelihood of zero precipitation is calculated based on the empirical cumulative distribution.…”

Section: Methodsmentioning

confidence: 99%

Candidate Distributions for Climatological Drought Indices (SPI and SPEI)

Stagge

Tallaksen

Gudmundsson

et al. 2015

Intl Journal of Climatology

549

544

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ABSTRACT:The Standardized Precipitation Index (SPI), a well-reviewed meteorological drought index recommended by the World Meteorological Organization (WMO), and its more recent climatic water balance variant, the Standardized Precipitation-Evapotranspiration Index (SPEI), both rely on selection of a univariate probability distribution to normalize the index, allowing for comparisons across climates. Choice of an improper probability distribution may impart bias to the index values, exaggerating or minimizing drought severity. This study compares a suite of candidate probability distributions for use in SPI and SPEI normalization using the 0.5 ∘ × 0.5 ∘ gridded Watch Forcing Dataset (WFD) at the continental scale, focusing on Europe. Several modifications to the SPI and SPEI methodology are proposed, as well as an updated procedure for evaluating SPI/SPEI goodness of fit based on the Shapiro-Wilk test. Candidate distributions for SPI organize into two groups based on their ability to model short-term accumulation (1-2 months) or long-term accumulation (>3 months). The two-parameter gamma distribution is recommended for general use when calculating SPI across all accumulation periods and regions within Europe, in agreement with previous studies. The generalized extreme value distribution is recommended when computing the SPEI, in disagreement with previous recommendations.

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Section: Methodsmentioning

confidence: 99%

Candidate Distributions for Climatological Drought Indices (SPI and SPEI)

Stagge

Tallaksen

Gudmundsson

et al. 2015

Intl Journal of Climatology

549

544

View full text Add to dashboard Cite

show abstract

“…This issue can be addressed by using the Weibull plotting position function (Equation (1)) to estimate the probability of zero precipitation. Further information about this latter method, which is based on the concept of 'centre of mass' and was applied in this study, can be found in Solakova et al (2014).…”

Section: Cumulative Distribution Functions and Zero Precipitation Valuesmentioning

confidence: 99%

Using the normality assumption to calculate probability‐based standardized drought indices: selection criteria with emphases on typical events

Blain

Ávila

Pereira

2017

Intl Journal of Climatology

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Enhancing the capability of both standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) for quantifying wet and dry events under distinct climate conditions is of paramount importance. The different recommendations of recent studies regarding the best distribution to calculate the SPEI and the lack of studies addressing the effect of different parameters estimation methods on the SPI motivated us to apply and adapt distinct testing methodologies to select candidate models for calculating these standardized drought indices (SDI). The study is based on two data sets. The first represents a tropical–subtropical region of Brazil. The second comprises the same weather stations that were used for developing the original version of the SPEI. The study also emphasized the performance of the models within the range of typical SDI values [−2.0 : 2.0]. Along with goodness‐of‐fit tests, we calculated the mean absolute errors between the indices values estimated from the candidate distributions, and their corresponding theoretical values derived from the standard normal distribution. The two‐parameter gamma and the generalized extreme value distributions are, respectively, recommended for general use in SPI and SPEI algorithms (1–12‐month timescales). The unbiased probability weighted moments are recommended to estimate the distributions parameters. The study also described a trade‐off between choosing the best model for the central part and for the tails of the distributions. This trade‐off suggests that the methodologies used to select models for the SDI algorithms may have to decide which part of the distribution (central or tails) should be emphasized. The behaviour of the errors among different wet/dry categories showed that both indices were only capable of representing drought and floods in a similar probabilistic way within the range [−2.0 : 2.0]. This feature supports our decision to emphasize model performances within such range.

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“…Sometimes it is hard to discriminate among canonical forms of FXw(x), or they may not provide a good fit to the data (Soláková et al 2014;Lall et al, 2016). On the other hand, using different distribution functions could lead to different tail behavior and thus inconsistencies in characteristics of extremes across space .…”

Section: Spi and Ssi Indicesmentioning

confidence: 99%

Composite Agrometeorological Drought Index Accounting for Seasonality and Autocorrelation

et al. 2018

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

show abstract

Comparison between Parametric and Nonparametric Approaches for the Calculation of Two Drought Indices: SPI and SSI

Cited by 56 publications

References 28 publications

Candidate Distributions for Climatological Drought Indices (SPI and SPEI)

Candidate Distributions for Climatological Drought Indices (SPI and SPEI)

Using the normality assumption to calculate probability‐based standardized drought indices: selection criteria with emphases on typical events

Composite Agrometeorological Drought Index Accounting for Seasonality and Autocorrelation

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