Description and Attribution Analysis of the 2017 Spring Anomalous High Temperature Causing Floods in Kazakhstan

Zou, Shan; Abuduwaili, Jilili; Ding, Jianli; Duan, Weili; Maeyer, Philippe De; Voorde, Tim Van de

doi:10.2151/jmsj.2020-070

Cited by 8 publications

(3 citation statements)

References 46 publications

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“…Several studies have explored the potential linkage between the precipitation extremes and the large-scale atmospheric circulation in CA, suggesting that the large-scale atmospheric circulation changes play a vital role in the changes of the precipitation amounts and extreme precipitation events 32,[42][43][44][45] . The large-scale atmospheric circulation is controlled by a series of large-scale climate indices, including the Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO) and El Nino-Southern Oscillation (ENSO).…”

Section: Discussionmentioning

confidence: 99%

Attribution of changes in the trend and temporal non-uniformity of extreme precipitation events in Central Asia

Zou

Abuduwaili

Duan

et al. 2021

Sci Rep

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Extreme precipitation events exhibit an increasing trend for both the frequency and magnitude on global and regional scales and it has already proven the impact of man-made global warming on the extreme precipitation amplification. Based on the observed datasets and global climate model (GCM) output, this study has evaluated the impact from anthropogenic forcing on the trend and temporal non-uniformity (i.e. increase in unevenness or disparity) of the precipitation amounts (PRCPTOT), extremes (R95p and RX5day) and intensity (SDII) in Central Asia (CA) from 1961 to 2005. Results indicate that radiative forcing changes, mainly driven by human activities, have significantly augmented the extreme precipitation indices in CA. The median trend with the influence of anthropogenic activities for the PRCPTOT, SDII, R95p and RX5day amounted to 2.19 mm/decade, 0.019 mm/decade, 1.39 mm/decade and 0.21 mm/decade during the study period, respectively. A statistically insignificant decrease in non-uniformity was noticed for the PRCPTOT, SDII and RX5day in Central CA (CCA) and Western CA (WCA), while Eastern CA (ECA) was the only region with a statistically significant increase in non-uniformity of the PRCPTOT, SDII, R95p and RX5day by 4.22%, 3.98%, 3.73% and 3.97%, respectively from 1961 to 2005 due to anthropogenic forcing. These results reflect the difference in various regions regarding the impact of anthropogenic forcing on the non-uniformity of extreme precipitation events in CA, which might help to fully understand the role of anthropogenic forcing in the changes of the precipitation extremes in CA and contribute to the development of water resource management strategies.

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Section: Discussionmentioning

confidence: 99%

Attribution of changes in the trend and temporal non-uniformity of extreme precipitation events in Central Asia

Zou

Abuduwaili

Duan

et al. 2021

Sci Rep

Self Cite

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“…Asia is also experiencing climate change due to global warming [4], and it has been predicted that precipitation patterns in China will include more frequent and severe precipitation patterns than those predicted in RCP8.5, a widely used climate change scenario model. Abnormal patterns have also been reported from Kazakhstan [5], where it was found that the increase in temperature due to global warming was a factor in the occurrence of flood damage. In addition, Weili et al (2015) [6] analyzed changes in precipitation in Japan, from 1901 to 2012, and found that precipitation has decreased considerably in recent decades, while Mohammad et al (2020) [7] reviewed annual climate change and evaluated associated trends in Iran from 1961 to 2010.…”

Section: Introductionmentioning

confidence: 68%

Development of a Multiple Linear Regression Model for Meteorological Drought Index Estimation Based on Landsat Satellite Imagery

Kim

Jung

Choung³

2020

Water

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Climate polarization due to global warming has increased the intensity of drought in some regions, and the need for drought estimation studies to help minimize damage is increasing. In this study, we constructed remote sensing and climate data for Boryeong, Chungcheongnam-do, Korea, and developed a model for drought index estimation by classifying data characteristics and applying multiple linear regression analysis. The drought indices estimated in this study include four types of standardized precipitation indices (SPI1, SPI3, SPI6, and SPI9) used as meteorological drought indices and calculated through cumulative precipitation. We then applied statistical analysis to the developed model and assessed its ability as a drought index estimation tool using remote sensing data. Our results showed that its adj.R2 value, achieved using cumulative precipitation for one month, was very low (approximately 0.003), while for the SPI3, SPI6, and SPI9 models, the adj.R2 values were significantly higher than the other models at 0.67, 0.64, and 0.56, respectively, when the same data were used.

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“…Flooding, among the most pervasive natural hazards, continues to pose substantial risks to human life and property worldwide (Rentschler et al 2022, Wang et al 2023. Although characterized by its archetypal arid nature, Central Asia, comprising Kazakhstan (KAZ), Kyrgyzstan (KGZ), Tajikistan (TJK), Turkmenistan (TKM), Uzbekistan (UZB) and China's Xinjiang (XJI), has been confronted with a recurring pattern of seasonal floods (Zou et al 2020, Wang et al 2022, resulting in substantial socioeconomic losses. Within the confines of TJK, the inundation incident of 1992 precipitated a lamentable toll of more than 1300 fatalities and inflicted economic damage amounting to nearly $500 million, which is approximately 23% of the country's gross domestic product (GDP) for the same year, as indicated by the World Bank Group (2016).…”

Section: Introductionmentioning

confidence: 99%

The heterogeneity of human flood adaptation characteristics in Central Asia based on human-flood distance

Wang,

Sun,

Yang

et al. 2024

Environ. Res. Lett.

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The Central Asian region is subject to frequent seasonal floods, resulting in substantial losses. These recurrent floods have induced certain changes in human flood adaptation characteristics in Central Asia, an area that is currently under-researched. This study, grounded in meticulously simulated flood inundation outcomes, multisource population distribution data, and flood protection infrastructure data, introduces an improved approach to calculating the distance between human and flood (HFD) and investigates human flood adaptation characteristics in Central Asia. Our findings indicate that residents in Central Asia get close to flood-prone areas from 1970 to 2007, with the exceptions of Turkmenistan (TKM) and Kyrgyzstan (KGZ). Notably, this trend is particularly pronounced in regions such as Xinjiang, China, and Tajikistan (TJK). An intricate exponential increase is observed in the population exposed to floods as the HFD decreases. Under future scenarios, KGZ exhibits the most significant trend of staying away from flood-prone areas, while TJK presents the opposite trend, and TKM experiences minimal changes. Additionally, compared with urban areas, rural areas of Central Asia exhibit a trend towards approaching floods. This study underscores the optimum nature of human flood adaptation when the HFD reaches 4.23 km, showing the potential for substantial benefits by implementing population evacuation within this threshold buffer zone. These insights highlight the complex interplay between human behaviours and floods and can inform the formulation of effective flood risk mitigation strategies.

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Description and Attribution Analysis of the 2017 Spring Anomalous High Temperature Causing Floods in Kazakhstan

Abstract: This pre-publication manuscript may be downloaded, distributed and used under the provisions of the Creative Commons Attribution 4.0 International (CC BY 4.0) license. It may be cited using the DOI below.

Cited by 8 publications

References 46 publications

Attribution of changes in the trend and temporal non-uniformity of extreme precipitation events in Central Asia

Attribution of changes in the trend and temporal non-uniformity of extreme precipitation events in Central Asia

Development of a Multiple Linear Regression Model for Meteorological Drought Index Estimation Based on Landsat Satellite Imagery

The heterogeneity of human flood adaptation characteristics in Central Asia based on human-flood distance

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