Spatial Patterns and Temporal Variability of Drought in Western Iran

Raziei, Tayeb; Saghafian, Bahram; Paulo, Ana A.; Pereira, Luís S.; Bordi, Isabella

doi:10.1007/s11269-008-9282-4

Cited by 252 publications

(131 citation statements)

References 37 publications

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“…Thus, the variation of drought conditions across the Loess Plateau region could be represented by the first four principal components. The time series of scores for each rotated principal component (RPC) could represent the common temporal behavior of the SPI and SPEI time series in the areas with maximum loadings (Raziei et al, 2009).…”

Section: Principal Component Analysismentioning

confidence: 99%

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Spatiotemporal analysis of multiscalar drought characteristics across the Loess Plateau of China

Liu

Wang

Shao

et al. 2016

Journal of Hydrology

162

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s u m m a r yDrought is the most widespread and destructive hazard in arid and semiarid regions, with behaviors that become more complicated under climate change. To provide an overall view of drought conditions across the Loess Plateau of China, two multiscalar drought indices, the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), were used to identify the regional spatiotemporal characteristics of drought conditions from 1957 to 2012. Climatic data from 54 meteorological stations across the region were used to calculate the SPI and SPEI time series at 1-, 3-, 6-, 12-and 24-month time scales. Subregions with independent drought characteristics and the corresponding representative meteorological stations were identified by principal component analysis to facilitate regional drought monitoring. A temporal trend of drought severity over a 12-month time scale, as detected by the Mann-Kendall test, was mapped for the entire region. The intensity of the increasing trend of drought severity based on the SPEI was weaker than that based on the SPI. The area with a significant increasing trend of drought severity based on the SPEI was only found in the southwest of the region and was much smaller than that based on the SPI. The temporal behavior of drought frequency from January to December differed over different time scales and levels of drought severity. The regional distributions of the drought frequency were mapped for different months. Generally, the drought frequency spatially decreased from southeast to northwest and was higher in the middle of the winter, late spring and early summer. While the drought-hit area also changed with time, it was generally within the central and northwest areas of the region. Drought behaviors identified by the SPI and SPEI also changed with different time scales. Clear differences were also found among the drought characteristics identified by SPI, SPEI and the self-calibrated Palmer Drought Severity Index. The SPEI is considered as a robust index for regional drought monitoring and analysis under global climate change scenarios because of its multiscalar nature, simple form, low data requirement, and ability to identify the effects of temperature on drought conditions.

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Section: Principal Component Analysismentioning

confidence: 99%

“…In this paper, the PCA results over the 12-month time scale (SPI-12 and SPEI-12) are discussed. This is because the annual time scale could avoid seasonal cycles while keeping the inter-annual variability by the memory effect (Raziei et al, 2009). …”

Section: Principal Component Analysismentioning

confidence: 99%

Spatiotemporal analysis of multiscalar drought characteristics across the Loess Plateau of China

Liu

Wang

Shao

et al. 2016

Journal of Hydrology

162

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“…Drought can be regarded as regional and time-series water deficit processes, resulting in diminished water resource availability and ecosystem carrying capacity [3][4][5]. However, there is no universal definition of drought because of its large-scale spatiotemporal variability in timing and duration [6].…”

Section: Introductionmentioning

confidence: 99%

Temporal and Spatial Variability of Droughts in Southwest China from 1961 to 2012

Huang

Yang

et al. 2015

Sustainability

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Southwest China (SC) has suffered a series of super extreme droughts in the last decade. This study analyzed the temporal and spatial variations of drought in SC from 1961 to 2012. Based on precipitation anomaly index (PAI) that was derived from 1 km gridded precipitation data, three time scales (month, year and decade) for the drought frequency (DF) and drought area were applied to estimate the spatio-temporal structure of droughts. A time-series analysis showed that winter droughts and spring droughts occurred frequently for almost half of the year from November to March. Summer droughts occasionally occurred in severe drought decades: the 1960s, 1980s and 2000s. During the period of observation, the percent of drought area in SC increased from the 1960s (<5%) to the 2000s (>25%). A total of 57% of the area was affected by drought in 2011, when the area experienced its most severe drought both in terms of area and severity. The spatial analysis, which benefitted from the gridded data, detailed that all of SC is at drought risk except for the central Sichuan Basin. The area at high risk for severe and extreme droughts was localized in the mountains of the junction of Sichuan and Yunnan. The temporal and OPEN ACCESSSustainability 2015, 7 13598 spatial variability can be prerequisites for drought resistance planning and drought risk management of SC.

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“…By applying a principal component analysis (PCA) to the SPI data, regions with similar variability can be identified and according spatial maps provided [cf., e.g., Raziei et al, 2009].…”

Section: Introductionmentioning

confidence: 99%

Spatial assessment of precipitation deficits in the Duero basin (central Spain) with multivariate extreme value statistics

2013

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[1] Nonirrigated agriculture on the Iberian Peninsula is regularly affected by dry periods that can cause important losses. This paper focuses on the comparison of the classical Standard Precipitation Index (SPI) with a fragility index developed by the multivariate extreme value theory community, which is used to describe monthly precipitation deficits below 30.5 mm (about 1 mm/d) in the Spanish Duero basin. The multivariate extreme value model allows to capture relevant information concerning the dependence structure among extreme precipitation deficits. Maps of those extremal dependence summaries and of loadings of principal components of the SPI provide quantitative information for water management. In addition, jointly analyzing data from several stations improves the inference of uncertainty. Spatial patterns of extremal dependence emerged with respect to orographic features. Most severe dry spells occur in the southeast of the Duero basin. In central plain of the Duero basin, a predominantly agricultural area, a strong fragility index for severity of dry spells is particularly found in eastern regions. Results of the MEVT and SPI analysis point in the same direction. Beyond this, the MEVT assessment gives a quantitative measure of the dependence between stations and regions. Estimates of return periods for extreme dry spell severity are discussed. Deficits below 42.7 mm are also analyzed.Citation: Kallache, M., P. Naveau, and M. Vrac (2013), Spatial assessment of precipitation deficits in the Duero basin (central Spain) with multivariate extreme value statistics, Water Resour. Res., 49,[6716][6717][6718][6719][6720][6721][6722][6723][6724][6725][6726][6727][6728][6729][6730]

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Spatial Patterns and Temporal Variability of Drought in Western Iran

Cited by 252 publications

References 37 publications

Spatiotemporal analysis of multiscalar drought characteristics across the Loess Plateau of China

Spatiotemporal analysis of multiscalar drought characteristics across the Loess Plateau of China

Temporal and Spatial Variability of Droughts in Southwest China from 1961 to 2012

Spatial assessment of precipitation deficits in the Duero basin (central Spain) with multivariate extreme value statistics

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