Evaluation of hydro-meteorological drought indices for characterizing historical droughts in the Mediterranean climate of Algeria

Achite, Mohammed; Bazrafshan, Ommolbanin; Katipoğlu, Okan Mert; Azhdari, Zahra

doi:10.1007/s11069-023-06012-y

Cited by 7 publications

(4 citation statements)

References 41 publications

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“…In Figure 1, the scheme summarizing the proposed methodology aimed at probabilistically characterizing the drought areal extent and the related derivation of SPEI-based SAF curves, is illustrated. Indeed, SPEI outperforms in identifying drought conditions by considering the monthly variance between precipitation and reference evapotranspiration, representing a fundamental climatic water balance across different time scales [32,33]. Additionally, as SPEI is a standardized index, it maintains the advantage of enabling comparisons of drought characteristics across diverse climatic regions.…”

Section: Methodsmentioning

confidence: 99%

“…Water 2023, 15, 3141 3 of 12 Indeed, SPEI outperforms in identifying drought conditions by considering the monthly variance between precipitation and reference evapotranspiration, representing a fundamental climatic water balance across different time scales [32,33]. Additionally, as SPEI is a standardized index, it maintains the advantage of enabling comparisons of drought characteristics across diverse climatic regions.…”

Section: Introductionmentioning

confidence: 99%

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A Probabilistic Analysis of Drought Areal Extent Using SPEI-Based Severity-Area-Frequency Curves and Reanalysis Data

Palazzolo,

Peres,

Bonaccorso

et al. 2023

Water

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Assessing and monitoring the spatial extent of drought is of key importance to forecasting the future evolution of drought conditions and taking timely preventive and mitigation measures. A commonly used approach in regional drought analysis involves spatially interpolating meteorological variables (e.g., rainfall depth during specific time intervals, deviation from long-term average rainfall) or drought indices (e.g., Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index) computed at specific locations. While plotting a drought descriptor against the corresponding percentage of affected areas helps visualize the historical extent of a drought, this approach falls short of providing a probabilistic characterization of the severity of spatial drought conditions. That can be overcome by identifying drought Severity-Area-Frequency (SAF) curves over a region, which establishes a link between drought features with a chosen probability of recurrence (or return period) and the corresponding proportion of the area experiencing those drought conditions. While inferential analyses can be used to estimate these curves, analytical approaches offer a better understanding of the main statistical features that drive the spatial evolution of droughts. In this research, a technique is introduced to mathematically describe the Severity-Area-Frequency (SAF) curves, aiming to probabilistically understand the correlation between drought severity, measured through the SPEI index, and the proportion of the affected region. This approach enables the determination of the area’s extent where SPEI values fall below a specific threshold, thus calculating the likelihood of observing SAF curves that exceed the observed one. The methodology is tested using data from the ERA5-Land reanalysis project, specifically studying the drought occurrences on Sicily Island, Italy, from 1950 to the present. Overall, findings highlight the improvements of incorporating the spatial interdependence of the assessed drought severity variable, offering a significant enhancement compared to the traditional approach for SAF curve derivation. Moreover, they validate the suitability of reanalysis data for regional drought analysis.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Probabilistic Analysis of Drought Areal Extent Using SPEI-Based Severity-Area-Frequency Curves and Reanalysis Data

Palazzolo,

Peres,

Bonaccorso

et al. 2023

Water

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“…According to [6,40], the SAI is classifed as extremely wet with an SAI value more than or equal to 2 and extremely dry with an SAI value less than or equal to −2, and other severity classes are described in Table 2.…”

Section: Standard Anomaly Index (Sai)mentioning

confidence: 99%

Temporal Dynamics and Trend Analysis of Areal Rainfall in Muger Subwatershed, Upper Blue Nile, Ethiopia

Moshe,

Beza

2024

Advances in Meteorology

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This study was employed to investigate the temporal variability and trend analysis of areal rainfall in the Muger subwatershed, Upper Blue Nile, Ethiopia. The study was run over the following procedures to handle the main objective: (1) determining the areal rainfall from gauged point rainfall using the Thiessen polygon method, (2) grouping the months in the season according to the study area, (3) evaluating the temporal dynamics of annual and seasonal areal rainfall using the coefficient of variation (CV), standard anomaly index (SAI), and precipitation concentration index (PCI), and (4) analyzing the trend of annual and seasonal areal rainfall using modified Mann–Kendall’s (modifiedmk) test in RStudio. Based on the temporal variability analysis, CV results depict that annual and summer areal rainfall had low variability with values of 13.43% and 13.7%, respectively. Winter and spring areal rainfall shows high variation with a CV value of 50.5% and 36%, respectively. According to the SAI output, around 70% of the considered year was in the normal condition of wetness. On the other hand, the seasonal (winter, spring, and summer) rainfall distribution of the study area shows strong irregularity distribution throughout the considered years as a result of PCI with a value of 57.5%. The trend of the areal rainfall was shown to be both increasing and decreasing. However, the trend was insignificant with a 10% confidence level.

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“…The National Drought Mitigation Center (NDMC) utilizes the SPI to monitor drought conditions and assess water storage conditions 22 . Numerous studies have explored the spatiotemporal variations in meteorological droughts across different regions, including Mexico 23 , Greece 24 , India 25 , 26 , China 27 – 29 , Turkey 30 , 31 , Iran 32 , 33 , the US 34 , Portugal 35 , Denmark 36 , Algeria 37 , Pakistan 38 , 39 , and the Kingdom of Saudi Arabia 40 . These studies assessed spatial and temporal variations in different drought severity categories using historical data, identifying the most vulnerable areas.…”

Section: Introductionmentioning

confidence: 99%

Exploring short- and long-term meteorological drought parameters in the Vaippar Basin of Southern India

Muthiah,

Sivarajan,

Madasamy

et al. 2024

Sci Rep

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Evaluating drought parameters at the basin level is one of the fundamental processes for planning sustainable crop production. This study aimed to evaluate both short-term and long-term meteorological drought parameters within the Vaippar Basin, located in southern India, by employing the standardized precipitation index (SPI). Gridded rainfall values developed from 13 rain gauge stations were employed to calculate the SPI values. Drought parameters, encompassing occurrence, intensity, duration, frequency, and trends, were assessed for both short-term and long-term droughts. The study findings indicated that the occurrence of short-term drought was 51.7%, while that of long-term drought was 49.82%. Notably, the basin experienced extreme short-term droughts in 1980, 1998 and 2016 and long-term droughts in 1981, 2013, and 2017. Utilizing an innovative trend identification method for SPI values, a significant monotonic upwards trend was identified in October and December for short-term drought and in December for long-term drought. This study defined the minimum threshold rainfall, which represents the critical amount required to prevent short-term drought (set at 390 mm) and long-term drought (set at 635 mm). The drought severity recurrence curves developed in this study indicate that when the SPI values fall below − 1.0, short-term drought affects 25% of the basin area, while long-term drought impacts 50% of the basin area at a 20-year recurrence interval. Additionally, the drought hazard index (DHI), which combines drought intensity and severity, demonstrated higher values in the northwestern regions for short-term drought and in the southern areas for long-term drought. The study's findings, highlighting areas of drought vulnerability, severity, and recurrence patterns in the basin, direct the attention for timely intervention when drought initiates.

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Evaluation of hydro-meteorological drought indices for characterizing historical droughts in the Mediterranean climate of Algeria

Cited by 7 publications

References 41 publications

A Probabilistic Analysis of Drought Areal Extent Using SPEI-Based Severity-Area-Frequency Curves and Reanalysis Data

A Probabilistic Analysis of Drought Areal Extent Using SPEI-Based Severity-Area-Frequency Curves and Reanalysis Data

Temporal Dynamics and Trend Analysis of Areal Rainfall in Muger Subwatershed, Upper Blue Nile, Ethiopia

Exploring short- and long-term meteorological drought parameters in the Vaippar Basin of Southern India

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